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# The Learning Healthcare Project

Emerging developments and their implications

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## Posts

- [Publications](https://learninghealthcareproject.org/publications/)
- [Learning Health Systems - Cambridge Elements](https://learninghealthcareproject.org/learning-health-systems-cambridge-elements/) - Despite enormous efforts at healthcare improvement, major challenges remain in achieving optimal outcomes, safety, cost, and value. This Element introduces the concept of learning health systems, which have been proposed as a possible solution. Though many different variants of the concept exist, they share a learning cycle of capturing data from practice, turning it into
- [Data, insights and statistics](https://learninghealthcareproject.org/data-insights-and-statistics/) - Authors: Dr Tom Foley, Dr Neil Lawrence Date: 2018/9 Publisher: NHS Digital Description: We have a major role in handling data for health and social care. Our data, insights, and statistics teams work across dozens of topics, providing information that will help improve care for patients. Here you’ll find an overview of the work our
- [Supporting sustainable behavior change and empowerment in ubiquitous and learning health systems](https://learninghealthcareproject.org/supporting-sustainable-behavior-change-and-empowerment-in-ubiquitous-and-learning-health-systems/) - The increasing integration of digital health technologies into everyday life marks a transformative shift in healthcare and prevention. Ubiquitous digital health systems include continuous monitoring and intervention capabilities, offering unprecedented opportunities for preventive and rehabilitative healthcare, moving beyond a primary focus on addressing health problems after they symptomatically manifest. This shift is not merely characterized by technological evolution but also by a paradigmatic change towards more personalized, data-driven, and sustainable healthcare approaches. In this editorial, we underscore the potential of ubiquitous and learning health systems to revolutionize healthcare, including fostering sustainable behavior change and empowering individuals in their health journeys.
- [Frontiers in Digital Health. Research Topic: Supporting Sustainable Behavior Change and Empowerment in Ubiquitous and Learning Health Systems](https://learninghealthcareproject.org/frontiers-in-digital-health-research-topic-supporting-sustainable-behavior-change-and-empowerment-in-ubiquitous-and-learning-health-systems/) - Special issue of Frontiers in Digital Health. "This Research Topic brings together relevant articles around sensor-enabled, data-driven, and increasingly ubiquitous digital health. It contributes to the pathway towards individually empowering digital health technology, using e.g., predictive methods that deliver increasingly more precise and preventative approaches, with the larger aim of preserving quality-adjusted life years at the individual and societal level."
- [Big Data](https://learninghealthcareproject.org/big-data/) - The term ‘big data’ has been used increasingly in healthcare research in the first two decades of the twenty-first century. Most definitions focus on its characteristics, namely volume, variety and velocity, and other attributes have been identified including veracity, variability and value. There is no consensus on the volume that is classed as ‘big’. This is summarised in Figure 4.1. It is clear that big data reflects advances in information technology and the ability to store, securely access, manage and analyse large-volume datasets. One approach to defining size is that big data requires high-powered storage and analytic methods. ‘Big data’ is also used by technology companies to refer to information gathered about the public, often personal in nature or relating to their use of devices or platforms. In any setting, the large size can come from the breadth of a dataset (how many people’s data are included), its depth (the number of variables per person) or both.
- [What Influences Parents and Practitioners’ Decisions to Share Personal Information within an Early Help (Social Care) Context? Implications for Practice in Sharing Digital Data across Sectors](https://learninghealthcareproject.org/what-influences-parents-and-practitioners-decisions-to-share-personal-information-within-an-early-help-social-care-context-implications-for-practice-in-sharing-digital-data-across-sectors/) - Meeting the multiple and often complex needs of families (children, young people and adults) within ‘Early Help’ support is dependent upon practitioners from different sectors sharing relevant and timely information, after gaining a family’s voluntary consent to share information. This article reports on qualitative one-to-one interviews with adults in families (n = 32), one mother/father dyad interview (n = 2) and focus groups with practitioners (n = 47) in five local authority areas in North East England receiving or providing Early Help support. We explored experiences of providing consent to share personal information and consider the usefulness of a digital health data system when providing Early Help support to families. Communication Privacy Management theory was used as a framework to analyse the data. Key themes in participants’ accounts include the degree of need for help and support; the importance of trusting relationships; stronger and structured joint working practices; and understanding how information is shared. This work provides insights into current information sharing practices for some of the most vulnerable families and the wider social contexts. It has implications for the usefulness of a digital data system that shares GP health data with Early Help services and suggests the role this could have in the parent–practitioner relationship.
- [The challenges and opportunities of mental health data sharing in the UK](https://learninghealthcareproject.org/the-challenges-and-opportunities-of-mental-health-data-sharing-in-the-uk/) - The UK’s National Health Service (NHS) generates uniquely rich data that should be rapidly deployed for policy and service improvement, yet researchers report difficulties in accessing these data. Paradoxically, these restrictions are occurring at the same time as the open science movement, which encourages data sharing to improve the rigour, transparency, and replicability of research. We describe the urgency of improvements to data access and propose solutions from a mental health research perspective, although the issues discussed extend to all areas in which analysis and linkage of health data support policy and practice. Actions are needed at every level, from data users and data custodians to government (panel).
- [The digital future of mental healthcare and its workforce: A report on a mental health stakeholder engagement to inform the Topol Review.](https://learninghealthcareproject.org/the-digital-future-of-mental-healthcare-and-its-workforce-a-report-on-a-mental-health-stakeholder-engagement-to-inform-the-topol-review/) - This report has been prepared in support of the Topol Review. The findings are based on a series of expert one-to-one interviews, five expert focus groups and purposeful literature searches conducted in summer 2018. The overarching finding is that new technologies can transform mental healthcare over the next 20 years, but to be successful they must be accompanied by organisational transformation. Together these will have enormous workforce implications. Key technologies that are poised to impact mental healthcare over the next 20 years include: ...
- [Clinical review: The impact of data released through the Data Access Request Service](https://learninghealthcareproject.org/clinical-review-the-impact-of-data-released-through-the-data-access-request-service/) - This publication assesses real world outcomes from data released through the Data Access Request Service (DARS). It looks at the impact data has had in health and care, research, commissioning, policy and more.
- [How data science can advance mental health research](https://learninghealthcareproject.org/how-data-science-can-advance-mental-health-research/) - Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial.
- [The Role of Health Education England Knowledge and Library Services in Supporting Learning Health Systems](https://learninghealthcareproject.org/supporting-learning-health-systems/) - NHS England report: "The Role of Health Education England Knowledge and Library Services in Supporting Learning Health Systems"
- [A framework for understanding, designing, developing and evaluating Learning Health Systems](https://learninghealthcareproject.org/a-framework-for-understanding-designing-developing-and-evaluating-learning-health-systems/) - A Learning Health System is not a technical project. It is the evolution of an existing health system into one capable of learning from every patient. This paper outlines a recently published framework intended to aid the understanding, design, development and evaluation of Learning Health Systems.
- [What role for learning health systems in quality improvement within healthcare providers?](https://learninghealthcareproject.org/what-role-for-learning-health-systems-in-quality-improvement-within-healthcare-providers/) - By Foley, Vale. Abstract Introduction Recent decades have seen a focus on quality in healthcare. Quality has been viewed across 6 dimensions—safe, effective, patient-centred, timely, efficient and equitable. As IT has enabled the transformation of other industries, there has been an increasing interest in the potential for learning health systems (LHS) to improve quality in
- [Data to knowledge to improvement: creating the learning health system](https://learninghealthcareproject.org/data-to-knowledge-to-improvement-creating-the-learning-health-system/) - Authors: Paige L McDonald, Tom J Foley, Robert Verheij, Jeffrey Braithwaite, Joshua Rubin, Kenneth Harwood, Jessica Phillips, Sarah Gilman, Philip J Van Der Wees Journal: British Medical Journal (BMJ) Date: 2024/1/25 URL: https://www.bmj.com/content/bmj/384/bmj-2023-076175.full.pdf Description: Paige McDonald and colleagues detail key domains, tools, and actions required to enact learning health systems for continuous intelligent improvement in healthcare.
- [Professor Charles Friedman Interview](https://learninghealthcareproject.org/professor-charles-friedman-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Professor Charles Friedman is Chair of the Department of Learning Health Sciences at the University of Michigan Medical School. He is the former Deputy National Coordinator and Chief Scientific Officer, Office of the National Coordinator for Health IT in the U.S. Department of Health and Human Services.
- [Realising the Potential of Learning Health Systems](https://learninghealthcareproject.org/realising-the-potential-of-learning-health-systems/) - This report offers guidance for building a Learning Health System, focusing on tools, models and frameworks that might be helpful. However, it is not a “how to” guide. Learning Health Systems are complex by nature, and must be co-designed with local stakeholders. It does however, present a framework for considering the key challenges facing anyone
- [Nonadoption, Abandonment, Scale-up, Spread and Sustainability in LHS Workshop](https://learninghealthcareproject.org/nonadoption-abandonment-scale-up-spread-and-sustainability-in-lhs-workshop/) - NASSS Workshop Writeup 201020Download
- [Platforms in LHS Workshop](https://learninghealthcareproject.org/platforms-in-lhs-workshop/) - LHS Platforms Workshop WriteupDownload
- [Evaluation in LHS Workshop](https://learninghealthcareproject.org/evaluation-in-lhs-workshop/) - Evaluation Workshop 251020Download
- [Digitising UK General Practice (Section of Wachter Review)](https://learninghealthcareproject.org/digitising-uk-general-practice-section-of-wachter-review/) - By Dr Tom Foley. Dr Tom Foley contributed a section on the Digitisation of General Practice in England, to support Prof Robert Wachter's broader review on how to Digitise Healthcare in England: Making IT Work: Harnessing the Power of Health Information Technology to Improve Care in England This review paved the way for the establishment
- [The Potential of Learning Healthcare Systems](https://learninghealthcareproject.org/the-potential-of-learning-healthcare-systems/) - By Dr Tom Foley, Dr Fergus Fairmichael. This is our first major report, examining the potential of Learning Healthcare Systems. It examines the major challenges facing healthcare, defines a Learning Healthcare System, outlines the building blocks that must be in place to realise it, provided use cases that are already in operation and discusses the longer
- [Integrating clinical research with the Healthcare Enterprise: From the RE-USE project to the EHR4CR platform](https://learninghealthcareproject.org/integrating-clinical-research-with-the-healthcare-enterprise-from-the-re-use-project-to-the-ehr4cr-platform/) - By El Fadly, AbdenNaji et al. Abstract BackgroundThere are different approaches for repurposing clinical data collected in the Electronic Healthcare Record (EHR) for use in clinical research. Semantic integration of “siloed” applications across domain boundaries is the raison d’être of the standards-based profiles developed by the Integrating the Healthcare Enterprise (IHE) initiative – an initiative
- [Evidence based medicine](https://learninghealthcareproject.org/evidence-based-medicine/) - By Davidoff, Frank et al. Abstract A new journal to help doctors identify the information they need Busy doctors have never had time to read all the journals in their disciplines. There are, for example, about 20 clinical journals in adult internal medicine that report studies of direct importance to clinical practice, and in 1992
- [Understanding controlled trials: Why are randomised controlled trials important?](https://learninghealthcareproject.org/understanding-controlled-trials-why-are-randomised-controlled-trials-important/) - By Sibbald, B. and M. Roland. Abstract Randomised controlled trials are the most rigorous way of determining whether a cause-effect relation exists between treatment and outcome and for assessing the cost effectiveness of a treatment. They have several important features: Random allocation to intervention groups Patients and trialists should remain unaware of which treatment was
- [How evidence-based is medicine? A systematic literature review.](https://learninghealthcareproject.org/how-evidence-based-is-medicine-a-systematic-literature-review/) - By Matzen P. INTRODUCTION: In the early 1990es, it was supposed that only 10-15 per cent of medical interventions were based on results from randomised controlled studies. A systematic review of available empirical studies on the topic was performed in order to elucidate to what extent interventions in different medical specialities are evidence-based. METHODS: Literature
- [A Rapid-Learning Health System](https://learninghealthcareproject.org/a-rapid-learning-health-system/) - By Lynn M. Etheredge. Abstract Private- and public-sector initiatives, using electronic health record (EHR) databases from millions of people, could rapidly advance the U.S. evidence base for clinical care. Rapid learning could fill major knowledge gaps about health care costs, the benefits and risks of drugs and procedures, geographic variations, environmental health influences, the health
- [Use of primary care electronic medical record database in drug efficacy research on cardiovascular outcomes: comparison of database and RCT findings](https://learninghealthcareproject.org/use-of-primary-care-electronic-medical-record-database-in-drug-efficacy-research-on-cardiovascular-outcomes-comparison-of-database-and-rct-findings/) - By Tannen Richard L, Weiner Mark G, Xie Dawei. Abstract Objectives To determine whether observational studies that use an electronic medical record database can provide valid results of therapeutic effectiveness and to develop new methods to enhance validity. Design Data from the UK general practice research database (GPRD) were used to replicate previously performed randomised
- [Value in Health Care: Accounting for Cost, Quality, Safety, Outcomes, and Innovation: Workshop Summary](https://learninghealthcareproject.org/value-in-health-care-accounting-for-cost-quality-safety-outcomes-and-innovation-workshop-summary/) - By Institure of Medicine. Abstract The United States has the highest per capita spending on health care of any industrialized nation. Yet despite the unprecedented levels of spending, harmful medical errors abound, uncoordinated care continues to frustrate patients and providers, and U.S. healthcare costs continue to increase. The growing ranks of the uninsured, an aging
- [Achieving a Nationwide Learning Health System](https://learninghealthcareproject.org/achieving-a-nationwide-learning-health-system-2/) - By C. P. Friedman, A. K. Wong, D. Blumenthal. Abstract We outline the fundamental properties of a highly participatory rapid learning system that can be developed in part from meaningful use of electronic health records (EHRs). Future widespread adoption of EHRs will make increasing amounts of medical information available in computable form. Secured and
- [The behaviour change wheel: A new method for characterising and designing behaviour change interventions](https://learninghealthcareproject.org/the-behaviour-change-wheel-a-new-method-for-characterising-and-designing-behaviour-change-interventions/) - By Michie, S., et al. Abstract Background Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how
- [Evidence-Based Medicine in the EMR Era](https://learninghealthcareproject.org/evidence-based-medicine-in-the-emr-era/) - By Jennifer Frankovich, M.D., Christopher A. Longhurst, M.D., and Scott M. Sutherland, M.D. Abstract Pediatricians facing critical clinical decisions often lack data on which to draw. The authors recently put their institution's electronic medical record to unusual use to inform a decision about anticoagulation in a patient with systemic lupus erythematosus. Frankovich J, Longhurst CA, Sutherland
- [Prior event rate ratio adjustment: numerical studies of a statistical method to address unrecognized confounding in observational studies](https://learninghealthcareproject.org/prior-event-rate-ratio-adjustment-numerical-studies-of-a-statistical-method-to-address-unrecognized-confounding-in-observational-studies/) - By Yu, M., Xie, D., Wang, X., Weiner, M. G. and Tannen, R. L. ABSTRACTPurposeThe purpose of this study was to evaluate a statistical method, prior event rate ratio (PERR) adjustment, and an alternative, PERR‐ALT, both of which have the potential to overcome “unmeasured confounding,” both analytically and via simulation. MethodsFormulae were derived for the
- [Conceptualising and creating a global learning health system](https://learninghealthcareproject.org/conceptualising-and-creating-a-global-learning-health-system/) - By Charles Friedman, Michael Rigby. Abstract In any country the health sector is important in terms of human wellbeing and large in terms of economics. The health sector might therefore be expected to be a finely tuned enterprise, utilising corporate knowledge in a constant process of critically reviewing and improving its activities and processes. However,
- [The SMART Platform: early experience enabling substitutable applications for electronic health records.](https://learninghealthcareproject.org/the-smart-platform-early-experience-enabling-substitutable-applications-for-electronic-health-records/) - By Kenneth D Mandl , Joshua C Mandel , Shawn N Murphy, et al. AbstractObjective: The Substitutable Medical Applications, Reusable Technologies (SMART) Platforms project seeks to develop a health information technology platform with substitutable applications (apps) constructed around core services. The authors believe this is a promising approach to driving down healthcare costs, supporting standards
- [An Ethics Framework for a Learning Health Care System: A Departure from Traditional Research Ethics and Clinical Ethics](https://learninghealthcareproject.org/an-ethics-framework-for-a-learning-health-care-system-a-departure-from-traditional-research-ethics-and-clinical-ethics/) - By Ruth R. Faden, Nancy E. Kass, Steven N. Goodman, Peter Pronovost, Sean Tunis, and Tom L. Beauchamp. Abstract Calls are increasing for American health care to be organized as a learning health care system, defined by the Institute of Medicine as a health care system “in which knowledge generation is so embedded into the
- [Dr Know: A Knowledge Commons in Health](https://learninghealthcareproject.org/dr-know-a-knowledge-commons-in-health/) - By Loder, Bunt, Wyatt. Abstract The way we create, access and share information is changing rapidly. Every time we look something up on Wikipedia, rate an experience on Tripadvisor or enter search terms in Google, we are taking advantage of the increasingly sophisticated way in which technology and digital tools are allowing us to capture,
- [Ethics and Informed Consent for Comparative Effectiveness Research With Prospective Electronic Clinical Data](https://learninghealthcareproject.org/ethics-and-informed-consent-for-comparative-effectiveness-research-with-prospective-electronic-clinical-data/) - By Faden, Ruth, et al. Abstract Background:Electronic clinical data (ECD) will increasingly serve as an important source of information for comparative effectiveness research (CER). Although many retrospective studies have relied on ECD, new study designs propose using ECD for prospective CER. These designs have great potential but they also raise important ethics questions. Aims:Drawing on
- [Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory](https://learninghealthcareproject.org/electronic-health-records-based-phenotyping-in-next-generation-clinical-trials-a-perspective-from-the-nih-health-care-systems-collaboratory-2/) - By Richesson RL, Hammond WE, Nahm M, et al. Abstract Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can
- [Patient and public views on electronic health records and their uses in the United kingdom: cross-sectional survey.](https://learninghealthcareproject.org/patient-and-public-views-on-electronic-health-records-and-their-uses-in-the-united-kingdom-cross-sectional-survey/) - By Luchenski SA, Reed JE, Marston C, Papoutsi C, Majeed A, Bell D. AbstractBackground:The development and implementation of electronic health records (EHRs) remains an international challenge. Better understanding of patient and public attitudes and the factors that influence overall levels of support toward EHRs is needed to inform policy. Objective:To explore patient and public attitudes
- [Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records.](https://learninghealthcareproject.org/modeling-disease-severity-in-multiple-sclerosis-using-electronic-health-records/) - By Xia Z, Secor E, Chibnik LB, Bove RM, Cheng S, et al. Abstract ObjectiveTo optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of
- [Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory](https://learninghealthcareproject.org/electronic-health-records-based-phenotyping-in-next-generation-clinical-trials-a-perspective-from-the-nih-health-care-systems-collaboratory/) - By Rachel L Richesson et al. Abstract Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can draw on rich sources
- [Toward a science of learning systems: a research agenda for the high-functioning Learning Health System](https://learninghealthcareproject.org/toward-a-science-of-learning-systems-a-research-agenda-for-the-high-functioning-learning-health-system/) - By Charles Friedman , Joshua Rubin , Jeffrey Brown, et al. Abstract Objective The capability to share data, and harness its potential to generate knowledge rapidly and inform decisions, can have transformative effects that improve health. The infrastructure to achieve this goal at scale marrying technology, process, and policy is commonly referred to
- [Using electronic health records for clinical research: The case of the EHR4CR project](https://learninghealthcareproject.org/using-electronic-health-records-for-clinical-research-the-case-of-the-ehr4cr-project/) - By De Moor G et al. Abstract Objectives To describe the IMI EHR4CR project which is designing and developing, and aims to demonstrate, a scalable, widely acceptable and efficient approach to interoperability between EHR systems and clinical research systems. Methods The IMI EHR4CR project is combining and extending several previously isolated state-of-the-art technical
- [A "Green Button" For Using Aggregate Patient Data At The Point Of Care](https://learninghealthcareproject.org/a-green-button-for-using-aggregate-patient-data-at-the-point-of-care/) - By Christopher A. Longhurst, Robert A. Harrington and Nigam H. Shah. Abstract Randomized controlled trials have traditionally been the gold standard against which all other sources of clinical evidence are measured. However, the cost of conducting these trials can be prohibitive. In addition, evidence from the trials frequently rests on narrow patient-inclusion criteria and thus
- [Query Health: standards-based, cross-platform population health surveillance](https://learninghealthcareproject.org/query-health-standards-based-cross-platform-population-health-surveillance/) - By Jeffrey G Klann , Michael D Buck , Jeffrey Brown , et al. Abstract Objective Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level
- [Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): Architecture](https://learninghealthcareproject.org/scalable-collaborative-infrastructure-for-a-learning-healthcare-system-scilhs-architecture/) - By Mandl KD, Kohane IS, McFadden D, et al. Abstract We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the $48 billion dollar federal investment in health information technology (IT) to enable a queryable
- [Informed consent, comparative effectiveness, and learning health care](https://learninghealthcareproject.org/informed-consent-comparative-effectiveness-and-learning-health-care/) - By Faden, Ruth R., Tom L. Beauchamp, and Nancy E. Kass. Abstract Interest in learning health care systems and in comparative-effectiveness research (CER) is exploding. One major question is whether informed consent should always be required for randomized comparative-effectiveness studies, particularly studies conducted in a learning health care system. Our answer to this question
- [Why is healthcare inflation greater than general inflation?](https://learninghealthcareproject.org/why-is-healthcare-inflation-greater-than-general-inflation/) - By Anita Charlesworth. In the UK, spending on health care has increased by four per cent per year, since the NHS was founded 65 years ago. In this article, Anita Charlesworth, Chief Economist, Nuffield Trust, describes why inflation in health care costs has been greater in real terms than the general inflation. Website: http://hsr.sagepub.com/content/early/2014/04/15/1355819614531940.full.pdf
- [The future’s digital. Mental health and technology.](https://learninghealthcareproject.org/the-futures-digital-mental-health-and-technology/) - By Cotton, R., et al. Abstract Digital technology has the potential to transform mental health services. This report examines what the digital revolution means for the provision of NHS mental health services and recommends a way forward. The use of digital technology to improve health outcomes has the potential to transform the face of the
- [Toward a science of learning systems: a research agenda for the high-functioning Learning Health System](https://learninghealthcareproject.org/toward-a-science-of-learning-systems-a-research-agenda-for-the-high-functioning-learning-health-system-2/) - By Friedman, C., et al. Abstract OBJECTIVE: The capability to share data, and harness its potential to generate knowledge rapidly and inform decisions, can have transformative effects that improve health. The infrastructure to achieve this goal at scale--marrying technology, process, and policy--is commonly referred to as the Learning Health System (LHS). Achieving an LHS raises
- [Effectiveness of Computerized Decision Support Systems Linked to Electronic Health Records: A Systematic Review and Meta-Analysis](https://learninghealthcareproject.org/effectiveness-of-computerized-decision-support-systems-linked-to-electronic-health-records-a-systematic-review-and-meta-analysis/) - By Moja, L., et al. Abstract We systematically reviewed randomized controlled trials (RCTs) assessing the effectiveness of computerized decision support systems (CDSSs) featuring rule- or algorithm-based software integrated with electronic health records (EHRs) and evidence-based knowledge. We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Abstracts of Reviews of Effects.
- [Care Cost Inflation](https://learninghealthcareproject.org/care-cost-inflation/) - By RAND Corporation. Despite recent signs that efforts to slow the growth of U.S. health care costs are working, health care cost inflation remains a significant challenge. RAND researchers continue to examine solutions to slow cost inflation, such as cost-sharing and its effects; the role of new models of care delivery, such as retail health
- [Constructive comfort: accelerating change in the NHS](https://learninghealthcareproject.org/constructive-comfort-accelerating-change-in-the-nhs/) - By Allcock, C., et al. This report asks how best to design national policy on the NHS to accelerate improvements to health care? We argue that national bodies’ efforts to effect change follow three broad types of approach: •Type 1: ‘Prod organisations.’ This approach aims to direct, prod or nudge providers of care from the
- [Site visit to Geisinger Health System](https://learninghealthcareproject.org/site-visit-to-geisinger-health-system/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Geisinger Health System (GHS) is an integrated health services organization. GHS serves more than 2.6 million residents throughout 44 counties in central and northeast Pennsylvania. GHS is considered to be at the forefront of innovative care, with products and services aimed at improving quality, efficiency and value.
- [Dr David W Bates Interview](https://learninghealthcareproject.org/dr-david-w-bates-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background David W. Bates, MD, MSc, is Senior Vice President and Chief Innovation Officer for Brigham and Women’s Hospital. He is a practicing general internist and maintains his positions as Chief of the Division of General Internal Medicine and Primary Care at Brigham and Women's Hospital, Professor of
- [Professor Richard Platt Interview](https://learninghealthcareproject.org/professor-richard-platt-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Professor Platt is Chair of the Harvard Medical School Department of Population Medicine at the Harvard Pilgrim Health Care Institute. He has extensive experience in developing systems and capabilities for using routinely collected electronic health information to support public health surveillance, medical product safety assessments, comparative effectiveness
- [Dr Jeff Brown Interview](https://learninghealthcareproject.org/dr-jeff-brown-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Dr Brown is an Associate Professor in the Department of Population Medicine (DPM) at Harvard Medical School and the Harvard Pilgrim Health Care Institute. He is Associate Director and Director of Scientific Operations for the FDA’s Mini-Sentinel project. Dr Brown is the lead architect of PopMedNet (www.popmednet.org),
- [Dr Christina Åkerman Interview](https://learninghealthcareproject.org/dr-christina-akerman-interview/) - By Dr Tom Foley. Background Dr Christina R. Åkerman is President of ICHOM. Between 2008 and 2014, she served as Director General for the Medical Products Agency (MPA) in Sweden, a national agency employing approximately 750 people and under the aegis of the Swedish Ministry of Health and Social Affairs. During this period, she was
- [IBM Watson Site Visit](https://learninghealthcareproject.org/ibm-watson-site-visit/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Dr Eric Brown Dr Eric Brown is Director of Watson Technologies at the IBM T.J. Watson Research Center, NY. Eric is currently working on the DeepQA project, advancing the state-of-the-art in automatic, open domain question answering technology. The DeepQA team is applying this technology to build Watson,
- [Dr Caleb Stowell Interview](https://learninghealthcareproject.org/dr-caleb-stowell-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Caleb Stowell is Vice President, Research and Development, at the International Consortium for Health Outcomes Measurement (ICHOM); and Senior Researcher at Harvard Business School. His role involves overseeing the development of ICHOM’s Standard Sets, developed in collaboration with international physician and registry leaders and patient advocates. In
- [Dr Lisa Simpson Interview](https://learninghealthcareproject.org/dr-lisa-simpson-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Dr. Simpson is the President and Chief Executive officer of AcademyHealth. Before joining AcademyHealth, Dr. Simpson was director of the Child Policy Research Center at Cincinnati Children's Hospital Medical Center and Professor of Paediatrics in the Department of Paediatrics, University of Cincinnati. She served as the Deputy
- [Clinical Documentation in the 21st Century: Executive Summary of a Policy Position Paper From the American College of Physicians](https://learninghealthcareproject.org/clinical-documentation-in-the-21st-century-executive-summary-of-a-policy-position-paper-from-the-american-college-of-physicians/) - By Kuhn T, Basch P, Barr M, Yackel T, et al. Abstract Clinical documentation was developed to track a patient's condition and communicate the author's actions and thoughts to other members of the care team. Over time, other stakeholders have placed additional requirements on the clinical documentation process for purposes other than direct care of
- [Taking the Long View: How Well Do Patient Activation Scores Predict Outcomes Four Years Later?](https://learninghealthcareproject.org/taking-the-long-view-how-well-do-patient-activation-scores-predict-outcomes-four-years-later/) - By Hibbard, J. H., et al. Abstract Patient activation is an important predictor of health outcomes and health care usage, yet we do not know how enduring the benefits of greater patient activation are. This study uses a large panel survey of people with chronic conditions (n = 4,865) to examine whether a baseline patient
- [OpenClinical](https://learninghealthcareproject.org/openclinical/) - By OpenClinical. OpenClinical was established in 2001 to promote adoption of technologies which support quality and safety of patient care, and to provide tools for creating and sharing applications that comply with the highest possible technical and professional standards. It has now been reconfigured to demonstrate a completely new way of disseminating medical knowledge. OpenClinical.org
- [The Need To Incorporate Health Information Technology Into Physicians' Education And Professional Development](https://learninghealthcareproject.org/the-need-to-incorporate-health-information-technology-into-physicians-education-and-professional-development/) - By Pierce Graham-Jones, Sachin H. Jain, Charles P. Friedman, Leah Marcotte and David Blumenthal. Abstract Nationwide, as physicians and health care systems adopt electronic health records, health information technology is becoming integral to the practice of medicine. But current medical education and professional development curricula do not systematically prepare physicians to use electronic health records
- [Dr Rupert Dunbar-Rees Interview](https://learninghealthcareproject.org/dr-rupert-dunbar-rees-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Dr Rupert Dunbar-Rees is a GP by background, and Founder of Outcomes Based Healthcare. He trained in Medicine at Imperial College, gaining a degree in Orthopaedics from University College London. He was a Partner in general practice for five years before joining the Department of Health, London
- [Workforce and Training Focus Group](https://learninghealthcareproject.org/workforce-and-training-focus-group/) - By Dr Tom Foley, Dr Fergus Fairmichael. Participants Dr Graham Willis, Head of Research and Development, Centre for Workforce Intelligence Dr Wai Keong Wong, Consultant Haematologist UCL Professor Alan Cribb, Professor of Bioethics and Education KCL Dr Fergus Fairmichael Synopsis Change in approach to healthcare The learning health system would be a significant change from
- [Ethics and Information Governance Focus Group](https://learninghealthcareproject.org/ethics-and-information-governance-focus-group/) - By Dr Tom Foley, Dr Fergus Fairmichael. Participants Dr Gregory Maniatopoulos, Senior Research Associate, Institute of Health and SocietyDr Graham Willis, Head of Research and Development, Centre for Workforce IntelligenceDr Jonathan Richardson, Chair of Informatics Committee, Royal College PsychiatryMs Anna Lee, Project Manager Patient Safety and Human Factors, Health Education EnglandProfessor Alan Cribb, Professor of
- [Mr Kingsley Manning interview](https://learninghealthcareproject.org/mr-kingsley-manning-interview/) - By Dr Tom Foley. Background Kingsley Manning is Chair of the Health and Social Care Information Centre. He was previously Founder and Managing Director of Newchurch Limited, Executive Chairman of Tribal Group’s health business and Senior Adviser at McKinsey & Company. HSCIC is the UK national provider of high-quality information, data and IT systems for
- [Dr James Munro Interview](https://learninghealthcareproject.org/dr-james-munro-interview/) - By Dr Fergus Fairmichael. Background Dr James Munro is chief executive and chief technology officer of Patient Opinion. He has a background in clinical medicine, public health and health services research. Patient Opinion was founded in 2005 and is now the UK's leading independent non-profit feedback platform for health services. Patient Opinion is about “honest
- [Dr Shaun O’Hanlon Interview](https://learninghealthcareproject.org/dr-shaun-ohanlon-interview/) - By Dr Fergus Fairmichael. Background Dr O’Hanlon is EMIS Group's Chief Medical Officer. He started with EMIS in 2006 as Clinical Design Director and was responsible for the clinical architecture of EMIS's flagship product EMIS Web. Dr O’Hanlon trained at Cambridge and St Thomas' Hospital, becoming a GP principal in 1994 and became Medical Director
- [Hospital finances and productivity: in a critical condition?](https://learninghealthcareproject.org/hospital-finances-and-productivity-in-a-critical-condition/) - By Lafond, S., et al. Abstract The NHS in England faces the huge challenge of meeting rising demand in a period of sustained financial pressure. The service is projected to overspend its budget by £626m in 2014/15, despite £250m additional Treasury funding and an extra £650m from transferred planned capital investment. In this report we
- [Mr John Loder Interview](https://learninghealthcareproject.org/mr-john-loder-interview/) - By Dr Tom Foley. Background John Loder is a senior programme manager at Nesta in the Health and Ageing team within the Innovation Lab. He works on the Centre for Social Action Innovation Fund that aims to use the skills and enthusiasm of citizens to solve the problems generated by long term conditions and an
- [Dr Gerry Morrow Interview](https://learninghealthcareproject.org/dr-gerry-morrow-interview/) - By Dr Tom Foley. Background Dr Gerry Morrow is Medical Director of Clarity Informatics, who aim to improve patient care and outcomes using data and analytics. Clarity offer a Quality Improvement Service (QIS) in 4 regions of England, that covers 11 clinical focus areas including Sepsis, acute myocardial infarction, coronary artery bypass grafting, dementia, first
- [Professor Faden and Professor Kass Interview](https://learninghealthcareproject.org/professor-faden-and-professor-kass-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Professor Faden is the Philip Franklin Wagley Professor of Biomedical Ethics and Andreas Dracopoulos Director of the Berman Institute of Bioethics. Professor Kass is the Phoebe R Berman Professor of Bioethics and Public Health at Johns Hopkins, Deputy Director for Public Health of the Berman Institute of
- [Dr Caroline Wood Interview](https://learninghealthcareproject.org/dr-caroline-wood-interview/) - By Dr Tom Foley. Background Dr Caroline Wood is Assistant Director at the UCL Centre for Behaviour Change. Dr Wood has kindly reviewed the behaviour change chapter of our report and offered many helpful additions. Website:
- [Learning Healthcare Systems: Emerging developments and their implications](https://learninghealthcareproject.org/learning-healthcare-systems-emerging-developments-and-their-implications/) - By Dr Tom Foley. A blog summarising the background to our project and some of the findings. Website: http://www.health.org.uk/blog/learning-healthcare-systems-emerging-developments-and-their-implications
- [Is IT the end for doctors?](https://learninghealthcareproject.org/is-it-the-end-for-doctors/) - By Tom Foley. A BMJ Careers article, that appeared in the print edition of the British Medical Journal in July 2016. This article explores the potential implications of Learning Health Systems, for doctors. Website: http://careers.bmj.com/careers/advice/Is_IT_the_end_for_doctors%3F
- [Professor Hiroshi Tanaka](https://learninghealthcareproject.org/professor-hiroshi-tanaka/) - By Dr Tom Foley. Professor Tanaka is Professor Emeritus in the School of Medicine at Tokyo Medical and Dental University. He is also Special Advisor to the Executive Director of the Tohoku Medical Megabank Organisation. The Megabank Project has built a database that integrates genomic as well as lifestyle data for a cohort that will
- [International Consortium for Health Outcomes Measurement (ICHOM)](https://learninghealthcareproject.org/international-consortium-for-health-outcomes-measurement-ichom/) - By Tom Foley. ICHOM has been set up to define global Standard Sets of outcome measures for all medical conditions and to drive adoption, reporting and benchmarking of these measures worldwide23. Essentially, these standard sets populatePorter’s hierarchy24 for each condition. They are created through international collaborations among patients, clinicians and outcomes researchers. The development of several of
- [Connected Health Cities (University of Liverpool) Learning system for unplanned care](https://learninghealthcareproject.org/connected-health-cities-university-of-bradford-empowering-independence-in-older-people-2/) - By Tom Foley. Linking routinely collected health and eventually social care data to compare the care pathways of those who attended Emergency Departments with exacerbations of COPD in different locations. This will be analysed and delivered to care teams so that they can improve their services and reduce unplanned admissions. Website: https://www.connectedhealthcities.org/research-projects/development-learning-system-unplanned-care/
- [EU Commission](https://learninghealthcareproject.org/eu-commission/) - By Tom Foley. The EU Commission has funded LHS research projects of varying scales. The TRANSFoRm project outlined above received over €7.5m from the EU Seventh Framework Programme, while other research collaborations have been funded under the European Cooperation in Science and Technology Programme (COST). The most relevant current funding programme is Horizon 2020, the
- [Disease Specific Charities](https://learninghealthcareproject.org/disease-specific-charities/) - By Tom Foley. Charities such as Cancer Research UK, MQ Mental Health and Asthma UK have significant disease specific research funding programmes and are collaborators on other broad based projects such as the Farr Institute. Website: www.cancerresearchuk.org/how-we-spend-your-money
- [Innovate UK](https://learninghealthcareproject.org/innovate-uk/) - By Tom Foley. Innovate UK is an executive non-departmental public body, sponsored by the Department for Business, Energy & Industrial Strategy. They work with people, companies and partner organisations to find and drive the science and technology innovations that will grow the UK economy. With a strong business focus, they attempt to drive growth by
- [The Health Foundation (THF)](https://learninghealthcareproject.org/the-health-foundation-thf/) - By Tom Foley. THF is an independent charity committed to bringing about better health for people in the UK. It aims to improve health service delivery and policy making by testing innovations, sharing evidence on what works, as well as building skills and knowledge. These aims and activities are closely aligned with those of a
- [Wellcome Trust](https://learninghealthcareproject.org/wellcome-trust/) - By Tom Foley. The Wellcome Trust is a global charitable foundation that supports scientists and researchers to take on big questions in population health, medical innovation, the humanities and social sciences and public engagement. They have supported research into LHS in low and middle income countries7 and have a track record of research into public
- [Engineering and Physical Sciences Research Council (EPSRC)](https://learninghealthcareproject.org/engineering-and-physical-sciences-research-council-epsrc/) - By Tom Foley. EPSRC is the main UK government agency for funding research and training in engineering and the physical sciences. Health is a significant strand of its work. Research funded projects include: CONSULT: Collaborative Mobile Decision Support for Managing Multiple Morbidities and Provenance templates as a method for facilitating provenance capture and simulating provenance
- [National Institute for Health Research (NIHR)](https://learninghealthcareproject.org/national-institute-for-health-research-nihr/) - By Tom Foley. NIHR is funded by DH, to drive research from bench to bedside for the benefit of patients. It supports a wide range of translational and applied research. So far, it has shown limited direct interest in LHS, however, several of its funded (or co-funded) projects have LHS strands, including, Collaborations for Leadership
- [Medical Research Council (MRC)](https://learninghealthcareproject.org/medical-research-council-mrc/) - By Tom Foley. MRC will invest £37.5m over 5 years to establish an independent UK Institute for Health and Biomedical Informatics Research (Farr 2). Additional funds will be contributed by the health research departments of England, Scotland and Wales, the British Heart Foundation, the Wellcome Trust, the Economic and Social Research Council (ESRC) and the
- [NHS England - Global Digital Exemplars](https://learninghealthcareproject.org/nhs-england-global-digital-exemplars/) - By Tom Foley. Ann Slee, ePrescribing Lead, Strategic Systems & Technology, Patients & Information, NHS England As well as her work with NHS England, Ann has recently been involved in Tech Fund and NIHR funded programmes, loosely based on a Learning Health System philosophy, that have been aimed at achieving improved digital maturity. NHS England
- [Farr Institute](https://learninghealthcareproject.org/farr-institute/) - By Tom Foley. The Farr Institute is a UK-wide research collaboration involving 21 academic institutions and health partners in England, Scotland and Wales. Publically funded by a consortium of ten organisations led by the Medical Research Council, the Institute is committed to delivering high-quality, cutting-edge research using ‘big data’ to advance the health and care
- [Faculty of Medical Informatics (FMI)](https://learninghealthcareproject.org/faculty-of-medical-informatics-fmi/) - By Tom Foley. Work is underway to establish the FMI, this aims to overcome problems currently faced by doctors with an interest in informatics: no career structure, inconsistent remuneration, isolation, lack of systemic approach and inadequate appraisal/revalidation. It would define the specialty, set entry requirements and a curriculum, much as royal colleges in other medical
- [NHS Digital Academy](https://learninghealthcareproject.org/nhs-digital-academy/) - By Tom Foley. Plans are underway to create a virtual organisation that will provide a unique training and development opportunity for Chief Clinical Information Officers (CCIOs), Chief Information Officers (CIOs) and aspirant leaders across the country. The Academy is being established in response to the Wachter Review5. Cohorts will receive up to 12 months part-time
- [AHSNs](https://learninghealthcareproject.org/ahsns/) - By Tom Foley. There are 15 Academic Health Science Networks (AHSNs) across England, established by NHS England in 2013 to spread innovation at pace and scale – improving health and generating economic growth. They connect NHS and academic organisations, local authorities, the third sector and industry, to facilitate innovation. These partnerships are particularly important to
- [Connected Health Cities Citizen Juries](https://learninghealthcareproject.org/connected-health-cities-citizen-juries/) - By Tom Foley. Data sharing within Connected Health Cities will require the building of public trust, so that the population understand and consent to the use of data. This will have to be built on openness, transparency and engagement. This has already begun with the hosting of two Citizen’s Juries. Over four days, the citizens
- [GDE Learning Network](https://learninghealthcareproject.org/gde-learning-network/) - By Tom Foley. NHS England is establishing a Learning Network to encourage GDEs to share learning but also to collaborate on developing common solutions, so that they do not each have to reinvent wheels unnecessarily. This will be reinforced by independent evaluation of the GDEs, measuring progress against qualitative and quantitative measures, including digital maturity.
- [Farr Institute (Edinburgh University)](https://learninghealthcareproject.org/farr-institute-edinburgh-university/) - By Tom Foley. The Farr Institute at Edinburgh is collaborating with Asthma UK to build a LHS for Asthma. There is currently limited information available on this initiative. Website: www.aukcar.ac.uk/roadmap-for-creating-a-scottish-learning-health-system-for-asthma-the-next-steps/
- [Farr Institute & (University College London)](https://learninghealthcareproject.org/farr-institute-university-college-london/) - By Tom Foley. Dr Amitava Banerjee, Senior Lecturer in Clinical Data Science and Honorary Consultant inCardiology at the Farr Institute of Health Informatics Head of Education at Royal College of Physicians Informatics Unit Learning Health Systems have had fluid definitions, but within the Farr, the emphasis has been more on the importance of continuous data.
- [Farr Institute – Centre for Improvement in Population Health through E-records Research (CIPHER) (Swansea University)](https://learninghealthcareproject.org/farr-institute-centre-for-improvement-in-population-health-through-e-records-research-cipher-swansea-university/) - By Tom Foley. CIPHER undertakes research that covers both observational and interventional research across all disease areas with an emphasis on methodological innovation and development in e-records research, including public engagement. There are a number of specific research programmes on injury, the built environment, substance use, mental health, infection and child health, as well as
- [Biomedical Informatics Group (King’s College London)](https://learninghealthcareproject.org/biomedical-informatics-group-kings-college-london/) - By Tom Foley. The KCL Biomedical Informatics Group is a multidisciplinary group of informaticians, clinicians, psychologists and computer scientists, researching the role of data and knowledge in medical research and practice. Their core area of interest is the LHS concept. They are developing software infrastructures to support LHS, mainly in primary care, and focusing on
- [Centre for Patient Safety and Service Quality (CPSSQ) & NIHR Patient Safety Translational Research Centre (Imperial College London)](https://learninghealthcareproject.org/centre-for-patient-safety-and-service-quality-cpssq-nihr-patient-safety-translational-research-centre-imperial-college-london/) - By Tom Foley. Researchers within the centres have expertise including surgery, medicine, pharmacy, infection prevention, psychology, economic evaluation, technological innovation, organisational development and patient involvement. Close links between academic research and clinical services help with translation of research findings into patient care, and ensure that research is clinically relevant. Prof Brendan Delaney, Director of CPSSQ,
- [Centre for Health Informatics (CHI) (Manchester University)](https://learninghealthcareproject.org/centre-for-health-informatics-chi-manchester-university/) - By Tom Foley. The CHI hosts the MRC Health eResearch Centre and leads research across a number of methodological disciplines, particularly health informatics, bioinformatics, biostatistics, computer science and software engineering. It also builds regional capacity in health informatics, and capability for data-intensive health science and care, through research-led training and education, as well as developing
- [Institute for Health and Society (Newcastle University)](https://learninghealthcareproject.org/institute-for-health-and-society-newcastle-university/) - By Tom Foley. IHS is a health improvement institute that has traditionally been underpinned by, Health Economics, Health Psychology, Medical Sociology and Health Technology Evaluation and which is now developing a significant health informatics capability. These are among the key disciplines required to develop a LHS that embeds informatics within a genuine improvement cycle. It
- [Doncaster Integrated Digital Care Record](https://learninghealthcareproject.org/doncaster-integrated-digital-care-record/) - By Tom Foley. Doncaster CCG plans to launch this system in Summer 2017. It will allow sharing of records across community, acute, mental health, and social care systems, however, the project is described as proof of concept and will initially be limited to a new falls pathway. Website: www.digitalhealth.net/2017/03/doncaster-deploying-shared-care-record/
- [Hampshire Health Record](https://learninghealthcareproject.org/hampshire-health-record/) - By Tom Foley. Supported and run by South Central and West Commissioning Support Unit, this system has been operational for over 10 years. It allows patient data to be viewed between hospital, general practice, community care and social services and has been used to support a small number of observational research studies. Website: www.hantshealthrecord.nhs.uk
- [Lancashire Patient Record Exchange](https://learninghealthcareproject.org/lancashire-patient-record-exchange/) - By Tom Foley. A patient record exchange that appears to be focused on enabling records to be viewed across different providers within the region. Only very limited technical specifications available online. Website: www.northwestsis.nhs.uk/lpres/lpres-process
- [Great North Care Record (GNCR)](https://learninghealthcareproject.org/great-north-care-record-gncr/) - By Tom Foley. A regional shared record system for the North East of England and Cumbria. This currently consists of an implementation of the Medical Interoperability Gateway (MIG), a system that allows secondary care clinicians to view a summary of the GP record. There are plans to update this with a full shared care record
- [Manchester Data Well](https://learninghealthcareproject.org/manchester-data-well/) - By Tom Foley. Datawell is an informatics platform designed to enable health data to be shared and Linked across Greater Manchester. In time, it is expected to become a genuine shared care record and a health data exchange. Patient information will be viewable across providers, but it will also be possible to query records to
- [QRESEARCH](https://learninghealthcareproject.org/qresearch/) - By Tom Foley. QRESEARCH is a large consolidated database derived from the pseudonymised health records of over 24 million patients. The data currently come from approximately 1500 general practices using the EMIS clinical computer system. The practices are spread throughout the UK and include data from patients who are currently registered with the practices as
- [Clinical Practice Research Datalink (CPRD)](https://learninghealthcareproject.org/clinical-practice-research-datalink-cprd/) - By Tom Foley. The Clinical Practice Research Datalink (CPRD) is a governmental, not-for-profit research service, jointly funded by the NHS National Institute for Health Research (NIHR) and the Medicines and Healthcare products Regulatory Agency (MHRA). It has been providing anonymised primary care records for public health research since 1987. Research using CPRD data has resulted
- [NHS Digital](https://learninghealthcareproject.org/nhs-digital/) - By Tom Foley. In England, HES (Hospital Episode Statistics) data, collected by providers and collated by NHS Digital provides, demographic, diagnostic and intervention data for all inpatient episodes, along with very limited details of outpatient episodes and data on A&E attendances. Data is recorded through Patient Administrative Systems (PAS) at an individual provider level. This
- [East London Patient Record](https://learninghealthcareproject.org/east-london-patient-record/) - By Tom Foley. Luke Readman, Chief Information Officer, East London Learning Health System The use of data to drive improvement is central to the Learning Health System (LHS) approach in east London. CCGs, GPs, provider organisations and system suppliers[1] in east London contribute to this work. Data driven collaborative improvement work in primary care locally
- [Cambridge University Hospitals NHS Foundation Trust (CUH)](https://learninghealthcareproject.org/cambridge-university-hospitals-nhs-foundation-trust-cuh/) - By Tom Foley. Dr Afzal Chaudhry, Consultant Nephrologist, Chief Clinical Information Officer and Associate Lecturer, Cambridge University Hospitals In 2014, CUH became the first UK healthcare provider to implement Epic, the market leading EHR. The Trust now has 2.5 years of rich structured clinical data that has been recorded through the EHR. The Trust is
- [Children and Young People’s Health Partnership (CYPHP)](https://learninghealthcareproject.org/children-and-young-peoples-health-partnership-cyphp/) - By Tom Foley. Dr Ingrid Wolfe, Consultant in children's public health medicine and Programme Director of Children and Young People’s Health Partnership (CYPHP) Background to CYPHP CYPHP’s purpose is to improve children’s health through clinical practice, research, educationand training. We are a Partnership of local decision-makers promoting continued health service and system improvement through ongoing
- [School of Health and Related Research (ScHARR)(Unversity of Sheffield)](https://learninghealthcareproject.org/school-of-health-and-related-research-scharrunversity-of-sheffield/) - By Tom Foley. Dr Clare Relton, Senior Research Fellow, University of Sheffield How do you define a Learning Health System? One that learns from the healthcare it provides, helping the healthcare it offers to continuously improve. What work your group is doing on Learning Health Systems? Professor Jon Nicholl, myself and other colleagues have
- [Connected Health Cities – (Bradford University) Promoting Healthier Child Growth](https://learninghealthcareproject.org/connected-health-cities-bradford-university-promoting-healthier-child-growth/) - By Tom Foley. Combining health visitor and primary care records with schools based national child measurement service data and the “Born in Bradford dataset”, to gain insights into the aetiology of obesity and to compare the effectiveness of a range of interventions. Website: https://www.connectedhealthcities.org/research-projects/test/
- [Connected Health Cities – (University of Liverpool) Learning system for alcohol related conditions](https://learninghealthcareproject.org/connected-health-cities-university-of-liverpool-learning-system-for-alcohol-related-conditions/) - By Tom Foley. Using routinely collected health data, linked with social care and other data, to analyse alcohol care pathways in the North West. Making linked data available at the point of care and ultimately, aiming to identify and disseminate the most effective management options. Website: https://www.connectedhealthcities.org/research-projects/development-learning-system-alcohol/
- [Connected Health Cities (Public Health England) – Using data to tackle antibiotic resistance](https://learninghealthcareproject.org/connected-health-cities-public-health-england-using-data-to-tackle-antibiotic-resistance/) - By Tom Foley. Anonymised GP, A&E and out of hours clinic records across Greater Manchester will be extracted, analysed and visualised so that GPs can compare their prescribing behaviour with others across the city. Behaviour change interventions will then be applied. Website: https://www.connectedhealthcities.org/research-projects/using-data-tackle-antibiotic-resistance/
- [Model Hospital (Department of Health)](https://learninghealthcareproject.org/model-hospital-department-of-health/) - By Tom Foley. The Carter Review1 identified unwarranted variation in running costs, sickness absence, infection rates and prices paid for supplies and services between providers. As part of the review, a ‘model hospital’ was developed, which links provider data, to allow hospitals to measure their financial performance, across many metrics, against other trusts. It was
- [Connected Health Cities (Durham University) – Forecasting emergency unplanned care](https://learninghealthcareproject.org/connected-health-cities-durham-university-forecasting-emergency-unplanned-care/) - By Tom Foley. A collaboration to produce statistical models, powered by linked health, local authority and other data, that can be routinely used to produce daily forecasts, up to 6 months in advance, of variations in Urgent and Emergency Care usage, to enable planning in hospitals, walk in centres and GP practices. Eventually, it will
- [Connected Health Cities – (Newcastle University) Learning Health System for vulnerable families](https://learninghealthcareproject.org/connected-health-cities-newcastle-university-learning-health-system-for-vulnerable-families/) - By Tom Foley. Building a platform to link data between health, social care and other agencies, relating to families, across North East England, that have multiple risk factors, such as poverty, chronic illness or unemployment. Data will be viewable by those working with families but will also be available for predictive analytics and other LHS
- [Connected Health Cities (Greater Manchester) – Using data to improve diagnosis and treatment of stroke in Greater Manchester](https://learninghealthcareproject.org/connected-health-cities-greater-manchester-using-data-to-improve-diagnosis-and-treatment-of-stroke-in-greater-manchester/) - By Tom Foley. A collaboration between Manchester University, AHSN, local trusts, local authorities and the Greater Manchester Stroke Operational Delivery Network. Linking data from GP, providers, the ambulance service and patient reporting apps, to surveil and build models of stroke service use. This will help build predictive models and service interventions to reduce false-positive (stroke
- [Connected Health Cities – (University of Sheffield) Supporting community care and reducing demand on A&E](https://learninghealthcareproject.org/connected-health-cities-university-of-sheffield-supporting-community-care-and-reducing-demand-on-ae/) - By Tom Foley. Linked de-identified data from the ambulance service, 111, hospital trusts and out of hours services across the Yorkshire and Humber region, is to be used to monitor patterns of service use and outcomes by different patient groups. This will allow clinicians, commissioners, NHS England and researchers to monitor the impact of interventions.
- [QSurveillance](https://learninghealthcareproject.org/qsurveillance/) - By Tom Foley QSurveillance® is a clinical surveillance system based on data from 3,400 EMIS general practices spread throughout the UK. It is run as a collaboration between the University of Nottingham, EMIS (GP EHR vendor) and ClinRisk Ltd (medical software company). It reports a range of metrics to the Department of Health and Public
- [Connected Health Cities (University of Bradford) – Empowering independence in older people](https://learninghealthcareproject.org/connected-health-cities-university-of-bradford-empowering-independence-in-older-people/) - By Tom Foley. Linking routinely collected primary, secondary, social care data with that from a large cohort study, to evaluate the comparative effectiveness of different interventions. Website: https://www.connectedhealthcities.org/research-projects/dementia-project/
- [Enabling a learning health system](https://learninghealthcareproject.org/enabling-a-learning-health-system/) - By Denwood, Foley. 30 Years of Hospital Episode Statistics in England Website: https://www.hdruk.ac.uk/news/enabling-a-learning-health-system/
- [Data Saves Lives](https://learninghealthcareproject.org/data-saves-lives/) - By Tom Foley. Tom Foley, Senior Clinical Lead for Data at NHS Digital, writes about the power of data in health and social care. Website: https://digital.nhs.uk/blog/transformation-blog/2020/data-saves-lives
- [NHS Data Collections as a platform for a Learning Health System](https://learninghealthcareproject.org/nhs-data-collections-as-a-platform-for-a-learning-health-system/) - By Dr Tom Foley, Dr Neil Lawrence. We created a guide to the work that NHS Digital does with data and described this within the framework of a Learning Health System. These data collections provide perhaps the largest available platform for a national Learning Health System. Our report is available: download PDF Website: http://digital.nhs.uk/dis
- [Dr Paul Wallace Interview](https://learninghealthcareproject.org/dr-paul-wallace-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Paul Wallace, MD, is Chief Medical Officer and Senior Vice President for Clinical Translation at Optum Labs. Before joining Optum Labs, Dr. Wallace was senior vice president and Director of the Center for Comparative Effectiveness Research (CER) at the Washington DC based Lewin Group. Dr. Wallace is
- [Mr Joshua Rubin Interview](https://learninghealthcareproject.org/mr-joshua-rubin-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Mr Joshua Rubin is the Program Officer for Learning Health System Initiatives at the Department of Learning Health Sciences, University of Michigan Medical School. Mr. Rubin is a former Executive Director of the Joseph H. Kanter Family Foundation, a non-profit organization working towards the realization of the
- [Dr Michael McGinnis Interview](https://learninghealthcareproject.org/dr-michael-mcginnis-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Dr Michael McGinnis is a physician, epidemiologist, and long-time contributor to national and international health programs and policy. An elected Member of the Institute of Medicine (IOM), he has, since 2005 also served as IOM Senior Scholar and Executive Director of the IOM Roundtable on Value &
- [Mr Lynn Etheredge Interview](https://learninghealthcareproject.org/mr-lynn-etheredge-interview/) - By Dr Tom Foley, Dr Fergus Fairmichael. Background Lynn Etheredge heads the Rapid Learning Project, a Washington DC area policy research center.. His career started at the White House Office of Management and Budget (OMB), where he was OMB’s principal analyst for Medicare and Medicaid and led its staff work on national health insurance proposals.
- [Translation into Practice Focus Group](https://learninghealthcareproject.org/translation-into-practice-focus-group/) - By Dr Tom Foley, Dr Fergus Fairmichael. Participants Dr Gregory Maniatopoulos, Senior Research Associate, Institute of Health and Society, Newcastle University Mr John Fellows, Analyst Centre for Workforce Intelligence Professor John Fox, Professor of Engineering Science, Medical Informatics and Cognitive Systems, Oxford University Professor David Ingram, Emeritus Professor of Health Informatics UCL, President OpenEHR Foundation
- [Technical Feasibility Focus Group](https://learninghealthcareproject.org/technical-feasibility-focus-group/) - By Dr Tom Foley, Dr Fergus Fairmichael. Participants Dr Wai Keong Wong, Consultant Haematologist UCL Prof Brendan Delaney, Professor of Primary Care Research Kings College London, Project Coordinator and Scientific Director TRANSFoRm project Mr Seref Arikan, Software developer at Ocean Informatics Prof Tony Cornford, Associate Professor in Information Systems, London School of Economics Mr John
- [Improving the Underlying Data Focus Group](https://learninghealthcareproject.org/improving-the-underlying-data-focus-group/) - By Dr Tom Foley, Dr Fergus Fairmichael. Participants Professor Brendan Delaney, Professor of Primary Care Research Kings College London, Project Coordinator and Scientific Director TRANSFoRm project Mr Seref Arikan, Software developer at Ocean Informatics Dr Jonathan Richardson, Chair of Informatics Committee, Royal College Psychiatry Dr Derek Tracy, Consultant Psychiatrist and Associate Clinical Director Oxleas NHS
- [OpenClinical.net](https://learninghealthcareproject.org/openclinical-net/) - By The Learning Healthcare Project. Please watch the video of Professor John Fox discussing OpenClinical at out workshop in London on 5 March 2015 by clicking on the thumbnail. OpenClinical was established in 2001 to support clinical knowledge management for translational medicine and evidence based practice and adoption of technologies to improve quality and safety
- [The TRANSFoRm Project](https://learninghealthcareproject.org/the-transform-project/) - By The Learning Healthcare Project. Please watch Professor Brendan Delaney discussing the TRANSFoRm Project and the challenges it has encountered by clicking on the thumbnail. The TRANSFoRm project aims to develop the technology to enable a rapid learning healthcare system that can improve patient care by speeding up translational research and enabling more cost effective
- [Biobanks and Electronic Medical Records: Enabling Cost-Effective Research](https://learninghealthcareproject.org/biobanks-and-electronic-medical-records-enabling-cost-effective-research/) - By E. Bowton, J. R. Field, S. Wang, J. S. Schildcrout, S. L. Van Driest, J. T. Delaney, J. Cowan, et al Abstract The use of electronic medical record data linked to biological specimens in health care settings is expected to enable cost-effective and rapid genomic analyses. Here, we present a model that highlights potential
- [Undetermined impact of patient decision support interventions on healthcare costs and savings: systematic review](https://learninghealthcareproject.org/undetermined-impact-of-patient-decision-support-interventions-on-healthcare-costs-and-savings-systematic-review/) - By Walsh, T., et al. Abstract Objective To perform a systematic review of studies that assessed the potential of patient decision support interventions (decision aids) to generate savings. Design Systematic review. Data sources After registration with PROSPERO, we searched 12 databases, from inception to 15 March 2013, using relevant MeSH terms and text words. Included
- [Computing Health Quality Measures Using Informatics for Integrating Biology and the Bedside](https://learninghealthcareproject.org/computing-health-quality-measures-using-informatics-for-integrating-biology-and-the-bedside/) - By Klann, J. G., & Murphy, S. N. ABSTRACT Background: The Health Quality Measures Format (HQMF) is a Health Level 7 (HL7) standard for expressing computable Clinical Quality Measures (CQMs). Creating tools to process HQMF queries in clinical databases will become increasingly important as the United States moves forward with its Health Information Technology Strategic
- [How Health Systems Could Avert ‘Triple Fail’ Events That Are Harmful, Are Costly, And Result In Poor Patient Satisfaction](https://learninghealthcareproject.org/how-health-systems-could-avert-triple-fail-events-that-are-harmful-are-costly-and-result-in-poor-patient-satisfaction/) - By Lewis, G., et al. Abstract Health care systems in many countries are using the "Triple Aim"--to improve patients' experience of care, to advance population health, and to lower per capita costs--as a focus for improving quality. Population strategies for addressing the Triple Aim are becoming increasingly prevalent in developed countries, but ultimately success will
- [The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavi](https://learninghealthcareproject.org/the-behavior-change-technique-taxonomy-v1-of-93-hierarchically-clustered-techniques-building-an-international-consensus-for-the-reporting-of-behavi/) - By Michie, S., et al. Abstract CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of interventions with precision and specificity. The objective of this study is to develop an extensive, consensually agreed hierarchically structured taxonomy of techniques [behavior change techniques (BCTs)] used in behavior change
- [SHRINE: Enabling Nationally Scalable Multi-Site Disease Studies.](https://learninghealthcareproject.org/shrine-enabling-nationally-scalable-multi-site-disease-studies/) - By McMurry AJ, Murphy SN, MacFadden D, Weber G, Simons WW, et al. Abstract Results of medical research studies are often contradictory or cannot be reproduced. One reason is that there may not be enough patient subjects available for observation for a long enough time period. Another reason is that patient populations may vary considerably
- [Ethical Oversight of Research on Patient Care](https://learninghealthcareproject.org/ethical-oversight-of-research-on-patient-care/) - By Solomon, M. Z. and Bonham, A. C. Abstract The Institute of Medicine has called on health care leaders to transform their health systems into “learning health care systems,� capable of studying and continuously improving their practices. Learning health care systems commit to carrying out numerous kinds of investigations, ranging from clinical effectiveness studies to
- [The Research-Treatment Distinction: A Problematic Approach for Determining Which Activities Should Have Ethical Oversight.](https://learninghealthcareproject.org/the-research-treatment-distinction-a-problematic-approach-for-determining-which-activities-should-have-ethical-oversight/) - By Kass, N. E., Faden, R. R., Goodman, S. N., Pronovost, P., Tunis, S. and Beauchamp, T. L. Abstract The rise of quality improvement research and comparative effectiveness research in health care settings constitutes progress toward the goal of what the Institute of Medicine has called a “learning healthcare system,� in which we are “drawing
- [Implementing the Learning Health System: From Concept to Action](https://learninghealthcareproject.org/implementing-the-learning-health-system-from-concept-to-action/) - By Greene SM, Reid RJ, Larson EB. Clinicians and health systems are facing widespread challenges, including changes in care delivery, escalating health care costs, and the need to keep up with rapid scientific discovery. Reorganizing U.S. health care and changing its practices to render better, more affordable care requires transformation in how health systems generate
- [Prospective Observational Studies to Assess Comparative Effectiveness: The ISPOR Good Research Practices Task Force Report.](https://learninghealthcareproject.org/prospective-observational-studies-to-assess-comparative-effectiveness-the-ispor-good-research-practices-task-force-report/) - By Berger, M. L., et al. Abstract OBJECTIVE: In both the United States and Europe there has been an increased interest in using comparative effectiveness research of interventions to inform health policy decisions. Prospective observational studies will undoubtedly be conducted with increased frequency to assess the comparative effectiveness of different treatments, including as a tool
- [Can Observational Studies Approximate RCTs?](https://learninghealthcareproject.org/can-observational-studies-approximate-rcts/) - By Greenfield, S. and R. Platt Abstract “It is the position of this Task Force that rigorous well designed and well executed Observational Studies (OS) can provide evidence of causal relationships” [1]. All flows from this carefully crafted statement in the middle of the ISPOR Good Research Practices Task Force Report, which provides a well-reasoned
- [Envisioning a Learning Health Care System: The Electronic Primary Care Research Network, A Case Study](https://learninghealthcareproject.org/envisioning-a-learning-health-care-system-the-electronic-primary-care-research-network-a-case-study/) - By Delaney B, Peterson K A., Speedie S, Taweel A, Arvanitis T, Hobbs R. Abstract PURPOSE: The learning health care system refers to the cycle of turning healthcare data into knowledge, translating that knowledge into practice, and creating new data by means of advanced information technology. The electronic Primary Care Research Network (ePCRN) was a
- [Use of a large general practice syndromic surveillance system to monitor the progress of the influenza A(H1N1) pandemic 2009 in the UK](https://learninghealthcareproject.org/use-of-a-large-general-practice-syndromic-surveillance-system-to-monitor-the-progress-of-the-influenza-ah1n1-pandemic-2009-in-the-uk/) - By Harcourt, S. E., et al. Abstract The Health Protection Agency/QSurveillance national surveillance system utilizes QSurveillance®, a recently developed general practitioner database covering over 23 million people in the UK. We describe the spread of the first wave of the influenza A(H1N1) pandemic 2009 using data on consultations for influenza-like illness (ILI), respiratory illness and
- [Variations in Health Care: The good, the bad and the inexplicable](https://learninghealthcareproject.org/variations-in-health-care-the-good-the-bad-and-the-inexplicable/) - By Appleby, et al. Variations in health care in the NHS are a persistent and ubiquitous problem. But which variations are acceptable or warranted – for example, variations driven by clinical need and informed patient choice – and which are not? The important question is how to promote 'good' variation and minimise 'bad' variation. Variations
- [Achieving a Nationwide Learning Health System](https://learninghealthcareproject.org/achieving-a-nationwide-learning-health-system/) - By Charles P. Friedman, Adam K. Wong and David Blumenthal Abstract We outline the fundamental properties of a highly participatory rapid learning system that can be developed in part from meaningful use of electronic health records (EHRs). Future widespread adoption of EHRs will make increasing amounts of medical information available in computable form. Secured
- [Distributed health data networks: a practical and preferred approach to multi-institutional evaluations of comparative effectiveness, safety...](https://learninghealthcareproject.org/distributed-health-data-networks-a-practical-and-preferred-approach-to-multi-institutional-evaluations-of-comparative-effectiveness-safety/) - By Brown, J. et al. Abstract BACKGROUND: Comparative effectiveness research, medical product safety evaluation, and quality measurement will require the ability to use electronic health data held by multiple organizations. There is no consensus about whether to create regional or national combined (eg, "all payer") databases for these purposes, or distributed data networks that leave
- ["Impactibility Models”: Identifying the Subgroup of High-Risk Patients Most Amenable to Hospital-Avoidance Programs.](https://learninghealthcareproject.org/impactibility-models-identifying-the-subgroup-of-high-risk-patients-most-amenable-to-hospital-avoidance-programs/) - By Lewis, G. H. Abstract Context: Predictive models can be used to identify people at high risk of unplanned hospitalization, although some of the high-risk patients they identify may not be amenable to preventive care. This study describes the development of “impactibility models,” which aim to identify the subset of at-risk patients for whom preventive
- [Research in action: using positive deviance to improve quality of health care.](https://learninghealthcareproject.org/research-in-action-using-positive-deviance-to-improve-quality-of-health-care/) - By Bradley, E. H., et al. BackgroundDespite decades of efforts to improve quality of health care, poor performance persists in many aspects of care. Less than 1% of the enormous national investment in medical research is focused on improving health care delivery. Furthermore, when effective innovations in clinical care are discovered, uptake of these innovations
- [Research on Medical Records Without Informed Consent](https://learninghealthcareproject.org/research-on-medical-records-without-informed-consent/) - By Miller, F. G. Abstract Observational research involving access to personally identifiable data in medical records has often been conducted without informed consent, owing to practical barriers to soliciting consent and concerns about selection bias. Nevertheless, medical records research without informed consent appears to conflict with basic ethical norms relating to clinical research and personal
- [Limitations of the randomized controlled trial in evaluating population-based health interventions.](https://learninghealthcareproject.org/limitations-of-the-randomized-controlled-trial-in-evaluating-population-based-health-interventions/) - By Sanson-Fisher, R. W., et al. Abstract Population- and systems-based interventions need evaluation, but the randomized controlled trial (RCT) research design has significant limitations when applied to their complexity. After some years of being largely dismissed in the ranking of evidence in medicine, alternatives to the RCT have been debated recently in public health and
- [Effect of a US National Institutes of Health programme of clinical trials on public health and costs.](https://learninghealthcareproject.org/effect-of-a-us-national-institutes-of-health-programme-of-clinical-trials-on-public-health-and-costs/) - By Johnston, S. C., et al. Abstract BACKGROUND: Few attempts have been made to estimate the public return on investment in medical research. The total costs and benefits to society of a clinical trial, the final step in testing an intervention, can be estimated by evaluating the effect of trial results on medical care and
- [Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success.](https://learninghealthcareproject.org/improving-clinical-practice-using-clinical-decision-support-systems-a-systematic-review-of-trials-to-identify-features-critical-to-success/) - By Kawamoto, K., et al. Abstract Objective To identify features of clinical decision support systems critical for improving clinical practice. Design Systematic review of randomised controlled trials. Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. Study
- [External validity of randomised controlled trials: "to whom do the results of this trial apply?".](https://learninghealthcareproject.org/external-validity-of-randomised-controlled-trials-to-whom-do-the-results-of-this-trial-apply/) - By Rothwell, P. M. Abstract In making treatment decisions, doctors and patients must take into account relevant randomised controlled trials (RCTs) and systematic reviews. Relevance depends on external validity (or generalisability)--ie, whether the results can be reasonably applied to a definable group of patients in a particular clinical setting in routine practice. There is concern
- [Observational research methods. Research design II: cohort, cross sectional, and case-control studies.](https://learninghealthcareproject.org/observational-research-methods-research-design-ii-cohort-cross-sectional-and-case-control-studies/) - By Mann, C. J. Abstract Cohort, cross sectional, and case-control studies are collectively referred to as observational studies. Often these studies are the only practicable method of studying various problems, for example, studies of aetiology, instances where a randomised controlled trial might be unethical, or if the condition to be studied is rare. Cohort studies
- [Real World’ pragmatic clinical trials: What are they and what do they tell us?](https://learninghealthcareproject.org/real-world-pragmatic-clinical-trials-what-are-they-and-what-do-they-tell-us/) - By Helms, P. J. Abstract Although the explanatory clinical therapeutic trial remains the foundation for assessing drug efficacy and is required for licensing purposes, the overall effectiveness of a treatment can be best judged by carefully designed and well conducted pragmatic ‘real world’ randomized trials. Pragmatic trials seek to inform prescribers and health care planners
- [Why we need observational studies to evaluate the effectiveness of health care.](https://learninghealthcareproject.org/why-we-need-observational-studies-to-evaluate-the-effectiveness-of-health-care/) - By Black, N. Abstract The view is widely held that experimental methods (randomised controlled trials) are the "gold standard" for evaluation and that observational methods (cohort and case control studies) have little or no value. This ignores the limitations of randomised trials, which may prove unnecessary, inappropriate, impossible, or inadequate. Many of the problems of
- [Evidence based medicine: what it is and what it isn't](https://learninghealthcareproject.org/evidence-based-medicine-what-it-is-and-what-it-isnt/) - By Sackett, et al. Abstract It's about integrating individual clinical expertise and the best external evidence Evidence based medicine, whose philosophical origins extend back to mid-19th century Paris and earlier, remains a hot topic for clinicians, public health practitioners, purchasers, planners, and the public. There are now frequent workshops in how to practice and teach

## Pages

- [Learning Healthcare Systems](https://learninghealthcareproject.org/) - ...and alternative research methodologies offer the possibility of a healthcare system that learns from each patient who is treated...
- [About Us](https://learninghealthcareproject.org/about/) - DR TOM FOLEY PRINCIPAL INVESTIGATOR Newcastle University Tom is a doctor, academic and ex-software engineer. His interest in Learning Healthcare Systems stems from a frustration with the inadequate evidence base that he encounters in his clinical work and the apparent inability of traditional methodologies to bridge the gap. In recent years, Tom has written reports
- [Platforms](https://learninghealthcareproject.org/technical-building-blocks/platforms/) - A Learning Health System is a complex system that cannot be lifted and shifted from one organisation to another. Still, many aspects of its infrastructure are common across organisations. Early examples – such as TRANSfoRm [116] or FDA Mini-Sentinel – had to develop a distributed network infrastructure and rules for operation before deploying the Learning
- [Knowledge to practice](https://learninghealthcareproject.org/technical-building-blocks/knowledge-to-practice/) - Generating knowledge is not the ultimate aim of a Learning Health System. Rather, the goal is to continuously improve health and care. For this to happen, the knowledge generated in the previous steps must be translated into action or mobilised. This section outlines how knowledge within a Learning Health System can be represented in a
- [Data to knowledge](https://learninghealthcareproject.org/technical-building-blocks/data-to-knowledge/) - Once data are consistently obtained in a standardised, comprehensive, exchangeable, analysable form, they must be used to derive knowledge. Within Learning Health Systems and clinical informatics more generally, the emphasis has often been on the collection, storage, analysis and dissemination of data. Too often, health systems collect reams of data but lack the means of
- [Practice to data](https://learninghealthcareproject.org/technical-building-blocks/practice-to-data/) - In a Learning Health System of any scale, informatics provides an opportunity to learn from every patient who is treated. The first step is to collect and assemble data that accurately represents what is happening within the system. This can include data on patients that is generated within healthcare organisations or elsewhere, as well as
- [Learning Healthcare System](https://learninghealthcareproject.org/background/learning-healthcare-system/) - This website offers guidance for building a Learning Health System (LHS), focusing on tools, models and frameworks that might be helpful. However, it is not a “how to” guide. Indeed, there is no model for building an LHS that can be “lifted and shifted”. LHSs are complex by nature, and must be co-designed with local
- [Strategy in a Learning Health System](https://learninghealthcareproject.org/strategy/) - Strategic direction is required to build a Learning Health System. A culture of learning and innovation will ensure that individuals are motivated to participate, while a scientific approach to implementation will increase the likelihood of success. Individuals and organisations will have to change their behaviour in ways that may not come naturally. All stakeholders must
- [Sources of Complexity](https://learninghealthcareproject.org/sources-of-complexity/) - Learning Health Systems could revolutionise healthcare practice. They have the potential to enable personalised, proactive services, capturing and analysing clinical data that can continuously inform and improve health decision making and practice [118, 119] . But six years after the first Learning Healthcare Project report [1] and 13 years since the IoM popularised the concept
- [References Report 2021](https://learninghealthcareproject.org/references-report-2021/) - [1] T. Foley and F. Fairmichael, "The Potential of Learning Health Care Systems," The Learning Healthcare Project, 2015. [Online]. Available: https://learninghealthcareproject.org/the-potential-of-learning-healthcare-systems/ [2] C. P. Friedman et al., "The science of learning health systems: foundations for a new journal," Learning Health Systems, vol. 1, no. 1, 2017. [Online]. Available: https://onlinelibrary.wiley.com/doi/full/10.1002/lrh2.10020. [3] D. A. Garwin. (1993) Building
- [Rationale](https://learninghealthcareproject.org/introduction-and-rationale/rationale/) - The rationale for developing a Learning Health System often includes some or all of the following, which were explored in more detail in the earlier Learning Healthcare Project report [1]: To improve patient outcomes and experience: While most health systems seek to improve the quality and safety of care, many fail even to measure comprehensive
- [Technical Building blocks of a Learning Health System](https://learninghealthcareproject.org/technical-building-blocks/) - Our earlier Learning Healthcare Project report [1] described the building blocks of a Learning Health System in detail. Here we will summarise that work, expanding on new developments. Learning Health Systems have been described as learning cycles at scale [38]. Once a decision is made on what to study, organisational Learning relies on data being
- [Introduction and Rationale](https://learninghealthcareproject.org/introduction-and-rationale/) - This website offers guidance for building a Learning Health System (LHS), focusing on tools, models and frameworks that might be helpful. However, it is not a “how to” guide. Indeed, there is no model for building an LHS that can be “lifted and shifted”. LHSs are complex by nature, and must be co-designed with local
- [Reducing and Responding to Complexity](https://learninghealthcareproject.org/sources-of-complexity/responding-to-complexity/) - Greenhalgh and colleagues have adapted existing [133] principles for managing complexity, so that they are relevant to the development of a Learning Health [134] System. They suggest that teams: Acknowledge unpredictability: Designers of interventions should contemplate multiple plausible futures. Implementation teams should tailor designs to the local context and view surprises as opportunities. Recognise self-organisation:
- [Applying the NASSS Framework to Learning Health Systems](https://learninghealthcareproject.org/sources-of-complexity/nasss-framework/) - The expert workshop found that the NASSS Framework could be applied to a broad range of Learning Health Systems. Moreover, the understanding gained could help select projects to fund, as well as aiding in their design, implementation and evaluation. Some NASSS domains will be more important than others for a given Learning Health System, while
- [Adapting over Time](https://learninghealthcareproject.org/sources-of-complexity/adapting-over-time/) - By its nature, a Learning Health System will change during its implementation and beyond. To succeed, it must be able to adapt. Likewise, the organisation must have the resilience to respond to critical events and maintain a flexible approach. HealthTracker required knowledgeable staff and was hard to sustain when staff turnover was high. There were
- [Wider Context](https://learninghealthcareproject.org/sources-of-complexity/wider-context/) - The wider institutional, policy and sociotechnical context is often identified as a key factor in the failure to move from a demonstration project to a transferable and sustainable mainstreamed service. This context can include policy, political, IG, interoperability, legal, market, IP and regulatory considerations. HealthTracker implemented existing guidelines but had limited success in securing endorsement
- [The Condition](https://learninghealthcareproject.org/sources-of-complexity/condition/) - The success of a Learning Health System depends on the clinical scenario in question. Previous studies have found that only a fraction of potential patients was deemed suitable for new technology because of the complexity of their condition, comorbidities or sociocultural situation. In reality, most patients are an exception to the general model. The HealthTracker
- [The Technology](https://learninghealthcareproject.org/sources-of-complexity/technology/) - Usability and dependability have often been cited as reasons for the failure of technology interventions. There has often been a failure to adequately prototype and test systems. There is also a risk that technology-produced data could be misinterpreted by patients or clinicians, particularly if it does not directly measure the underlying illness. Skills and training
- [The Value Proposition](https://learninghealthcareproject.org/sources-of-complexity/the-value-proposition/) - Who benefits from a Learning Health System? Is it worth developing? If there is no clear business case, a private company will be unable to scale and spread. If there is no value to the organisation (eg hospital, GP practice), then it is equally likely to fail. This value can include benefit to patients or
- [The Adopter System](https://learninghealthcareproject.org/sources-of-complexity/the-adopter-system/) - The staff, patients and carers who adopt and use a Learning Health System are critical to its success. Previous studies [127] have shown that staff sometimes abandon technology because of usability issues, but more often do so because of threats to their scope of practice, fear of job loss or concerns over the safety/welfare of
- [The Organisation](https://learninghealthcareproject.org/sources-of-complexity/the-organisation/) - The organisation’s capacity and readiness for change will influence the uptake and scale-up of Learning Health System interventions internally. The decision on whether to fund and support a Learning Health System will be influenced by the business planning, yet it is often impossible to predict costs and benefits in advance. Many healthcare organisations are already
- [Case studies](https://learninghealthcareproject.org/introduction-and-rationale/case-studies/) - No two Learning Health Systems are the same, but there is much to be learned by studying examples and considering what succeeded, and in what circumstances. A recent review of the literature identified 68 Learning Health System case studies across 20 countries [19]. A previous Learning Healthcare Project report and associated website described many other
- [What is a Learning Health System?](https://learninghealthcareproject.org/introduction-and-rationale/what-is-a-learning-health-system/) - Many years before the concept was applied to healthcare, a learning organisation was defined as “an organization skilled at creating, acquiring, and transferring knowledge, and at modifying its behaviour to reflect new knowledge and insights” [3]. The idea was introduced to healthcare in 2007 by the United States Institute of Medicine (IoM, now the National
- [Navigating the Framework](https://learninghealthcareproject.org/navigating-the-framework/) - Rationale A Learning Health System is described as a health system in which outcomes and experience are continually improved by applying science, informatics, incentives and culture to generate and use knowledge in the delivery of care. A Learning Health System can also improve value, reduce unjustified variation, support research and enhance workforce education, training and
- [Maturity](https://learninghealthcareproject.org/strategy/maturity/) - In addition to evaluating an outcome, it can also be helpful to assess the maturity of the processes within a Learning Health System. Maturity refers to the degree to which a process is able to achieve a specific objective in a predictable way [181]. The maturity of the underlaying technical infrastructure within a healthcare provider
- [Evaluation](https://learninghealthcareproject.org/strategy/evaluation/) - Learning Health Systems are expensive and impact the health of large populations, so it is important to understand how effective and cost-effective they are. Although failure is an important source of learning and can help others to decide whether and how to join a Learning Health System, organisations are generally less enthusiastic about publicising failures
- [Appraisal](https://learninghealthcareproject.org/strategy/appraisal/) - An expert workshop was commissioned to inform this report on the issues around evaluating Learning Health Systems [177]. It became clear during the evaluation workshop that the scope should be expanded to include appraisal: ie deciding if a project should proceed. There is no single route for an organisation to decide to implement a Learning
- [Participatory co-design](https://learninghealthcareproject.org/strategy/participatory-co-design/) - This report has emphasised the importance of stakeholder involvement when designing the elements of a Learning Health System. It has described how the stakeholders are critical to understanding the true complexity of what may superficially look like a technical undertaking. This process has been called many things – co-design, co-production, co-creation, patient-centred design, patient engagement
- [Behaviour](https://learninghealthcareproject.org/strategy/behaviour/) - To realise an improvement in practice, a Learning Health System often requires patients, clinicians and others to change their behaviour. There are many theories and models that can be deployed to understand and aid this process. The Behaviour Change Wheel (BCW) (Figure I) [159] is a systematic approach to designing, implementing and evaluating behaviour change
- [Implementation Science](https://learninghealthcareproject.org/strategy/implementation-science/) - Implementation Science is the scientific study of methods to promote the systematic uptake of research findings and other evidence-based practices into routine practice, to improve the quality and effectiveness of health services [155]. The fact that it takes on average 17 years for Evidence-Based Practices (EBP) to become routine [156] is a widely cited driver
- [Workforce](https://learninghealthcareproject.org/strategy/workforce/) - At the heart of a Learning Health System is a multidisciplinary team bringing together the right people, skills, specialisms and subject matter expertise. The nature of the work will determine the make-up of this team, but a multidisciplinary Learning Health System could include patients, clinicians, researchers, designers, strategy and operational delivery staff, information analysts and
- [Culture](https://learninghealthcareproject.org/strategy/culture/) - The most widely cited definition of an Learning Health System – from the Institute of Medicine (IoM) [120] – discusses an alignment of science, informatics, incentives and culture for continuous improvement and innovation. The need for a culture change is often noted to include learning, innovation, information use, sharing and implementation and research [146]. More
- [Strategy and Organisation](https://learninghealthcareproject.org/strategy/strategy-and-organisation/) - Strategy generally involves setting goals and priorities, determining actions to achieve these goals, and mobilising resources to execute the actions [135]. It is often thought of as a deliberate, explicitly stated plan, but can also be viewed as a “pattern in a stream of decisions” [136]. While much strategy literature addresses competition in business or
- [Conclusion](https://learninghealthcareproject.org/conclusion/) - Many organisations are setting a strategic goal of becoming or supporting a Learning Health System. However, Learning Health Systems are complex and constantly changing entities. No two are the same; they can’t be lifted and shifted from one environment to another. That being said, a great deal can be learnt from successful and unsuccessful case
- [Learning Healthcare System (Report 2015)](https://learninghealthcareproject.org/background/learning-healthcare-system-r2015/) - A Learning Healthcare System is defined, by the Institute of Medicine (IoM) (Institute of Medicine 2015), as a system in which, “science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.” The term
- [Surveillance](https://learninghealthcareproject.org/use-cases/surveillance/) - An advantage of recording outcomes and other routine data electronically, is that it can be collated and analysed in near real time. This feature holds out the potential for surveillance use-cases such as, epidemiological studies and monitoring the safety of new treatments. The US FDA has set up a nationwide electronic post-marketing product safety system
- [Predictive Modelling](https://learninghealthcareproject.org/use-cases/predictive-modelling/) - Within medicine, there are a large number of transactional interactions that generate data. Pattern recognition can be used to infer what might happen in the future, for example, what treatment might be effective given a particular set of circumstances (Foley and Fairmichael 2015). If it is possible to identify those who are at high risk
- [Positive Deviance](https://learninghealthcareproject.org/use-cases/positive-deviance/) - Data for operational management, such as for simple rotas, logistics, production management, flow management, etc., in healthcare could be significantly improved (Manning 2015). Analytics based on routine data, including outcome measures, would also enable the use of more robust research methodologies for understanding comparative performance different contexts. “This could challenge the current view, held by
- [Decision Support](https://learninghealthcareproject.org/use-cases/decision-support/) - It is impossible for clinicians to stay up to date with the medical literature in all but the narrowest fields of medicine (Etheredge 2015). This contributes to wide variations in practice between clinicians and regions. Clinical decision support systems (CDSSs) have been proposed as one potential remedy to this problem. A clinical decision support system has
- [Comparative Effectiveness Research](https://learninghealthcareproject.org/use-cases/comparative-effectiveness-research/) - Large Randomised Controlled Trials (RCT) and meta-analyses of RCTs are currently considered to be the Gold Standard form of evidence that underpins Evidence Based Practice. The reasons for this are well rehearsed, primarily that they can determine causal relationships while reducing confounders and bias (Sibbald and Roland 1998). The limitations of RCTs are also well
- [Automation](https://learninghealthcareproject.org/use-cases/automation/) - Clinicians have traditionally spent significant time performing basic tasks that would not constitute working “at the top of their license” and where their involvement does not add value. There is also an acknowledgement that clinicians are already busy and that adding to their workload is unlikely to result in adherence to system improvements (Foley and
- [Use Cases](https://learninghealthcareproject.org/use-cases/) - There are many potential sociotechnical configurations that would meet the definition of a Learning Healthcare System. The six use cases outlined below represent the systems that were most often cited by participants. They each rely on routinely collected data and medical knowledge that is assembled, analysed and interpreted, before being fed back into the healthcare
- [Workforce](https://learninghealthcareproject.org/implications/workforce/) - Learning Healthcare Systems will have significant implications for many of the professionals currently associated with the health service (Foley and Fairmichael 2015). Researchers To realise the potential of the Learning Healthcare System, the health services research community will have to upgrade their skills and change the way that they work (Simpson 2015). The majority of
- [Regulation](https://learninghealthcareproject.org/implications/regulation/) - The quality of healthcare is regulated in a variety of ways internationally. Routinely collected data often provides a foundation to that regulation. In England, quality is regulated by the Care Quality Commission (CQC). Attention is focused on the inspections carried out by the CQC, however, routine data is used extensively before and during inspections (CQC 2015). Over
- [Organisational](https://learninghealthcareproject.org/implications/organisational/) - Like individual clinicians, many healthcare organisations are already working at capacity and are focused on relatively short-term financial, process and regulatory targets. Elements of a Learning Healthcare System that are not aligned with these targets or that require upfront investment for long-term payback, may achieve limited uptake. Elements of a Learning Healthcare System that are
- [Future](https://learninghealthcareproject.org/implications/future/) - In 2013, an expert workshop was convened, by the US National Science Foundation, to establish the research agenda for the Learning Healthcare System (Friedman, Rubin et al. 2015). It identified 106 research questions around four system level requirements that a Learning Healthcare System must satisfy: 1. A LHS trusted and valued by all stakeholders2. An economically sustainable
- [Economic](https://learninghealthcareproject.org/implications/economic/) - Costs are a major concern for patients, clinicians, providers, commissioners and governments (Akerman 2015). Claims have been made that the Learning Healthcare System can help to solve the cost crisis in healthcare (Institute of Medicine 2010). At the same time, the considerable costs of implementing, maintaining and administering the required infrastructure have often been overlooked
- [Implications](https://learninghealthcareproject.org/implications/) - Learning Healthcare Systems will have significant workforce implications. They will certainly not remove the need for clinicians, but over time they will alter the skill set needed and may impact the type and number required. Likewise, there will be implications for researchers and a greater role for informaticians. Learning Healthcare Systems will be based within
- [Outcomes Measurement](https://learninghealthcareproject.org/building-blocks/outcomes-measurement/) - Improving health outcomes, through the prevention, diagnosis and treatment of illness, is the stated reason why most healthcare systems exist. It is therefore unfortunate that robust outcome measures are not routinely collected as part of the provision of care. If patients are even followed up, clinicians often record only subjective, unstandardised measures of response to treatment.
- [Non-Healthcare Data](https://learninghealthcareproject.org/building-blocks/non-healthcare-data/) - As the processing power and connectivity of mobile devices have increased and the number of on-board sensors has multiplied, there has been increasing interest in the role that these advancements can play in a Learning Healthcare System. At the same time, an increasing proportion of the population are engaging with social media and other online
- [Healthcare Data](https://learninghealthcareproject.org/building-blocks/healthcare-data/) - Learning Healthcare Systems seek to capture and generate knowledge from the data flowing from routine care. They then feed this knowledge back into the healthcare system in a way that changes the behavior of actors to improve outcomes. They are fueled by routinely collected data. Much of that data currently comes from sources such as,
- [Ethical Framework](https://learninghealthcareproject.org/building-blocks/ethical-framework/) - Patient Acceptability More than any other group, the Learning Healthcare System will have implications for patients. It was strange therefore that it was patient representatives who were the most difficult group to recruit for interviews and seminars on this topic. Approaches to ten patient leaders or representative groups resulted in only one participant. While there
- [Behaviour Change](https://learninghealthcareproject.org/building-blocks/behaviour-change/) - There was consensus among our participants that a Learning Healthcare System is about more than IT and informatics. Technical solutions alone or even journal articles and guidelines will not improve health outcomes (Munro 2015). This is demonstrated by the estimate that knowledge transfer, “from bench to bedside”, currently takes around 17 years (Friedman 2015). “Translating
- [Building Blocks](https://learninghealthcareproject.org/building-blocks/) - For Learning Healthcare Systems to enable rapid change, several building blocks will need to be in place. These include, accessible and comprehensive routine data, outcomes measurement, behaviour change techniques and an ethics framework that enables their use. This study has found examples in which each of these building blocks has been implemented at some scale,
- [Methodology](https://learninghealthcareproject.org/background/methodology/) - This study aimed to explore the meaning, feasibility and implications of the Learning Healthcare System concept. It was rooted in an English context, but it was recognised that much significant work on Learning Healthcare Systems was taking place in other countries, particularly in the US, so many of our interviews and site visits took place
- [Need for LHS](https://learninghealthcareproject.org/background/need-for-lhs/) - Modern medicine has brought remarkable advances. The application of scientific rigour to the art of healing has resulted in a better understanding of diseases, a proliferation of new treatments and has given hope to many. In large areas of medicine however, the complexity of the health condition and the heterogeneity of patient characteristics mean that
- [Contact](https://learninghealthcareproject.org/contact/) - DR TOM FOLEY PRINCIPAL INVESTIGATOR INSTITUTE OF HEALTH & SOCIETY Newcastle UniversityThe Baddiley-Clark BuildingRichardson RoadNewcastle upon TyneNE2 4AXUnited Kingdom Telephone: +44 (0)191 208 7045Fax: + 44 (0) 191 208 6043
- [Background](https://learninghealthcareproject.org/background/) - Learning Healthcare Systems Modern medicine has brought remarkable advances. The application of scientific rigour to the art of healing has resulted in a better understanding of diseases, a proliferation of new treatments and has given hope to many. In large areas of medicine however, the complexity of the health condition and the heterogeneity of patient
- [Terms and Conditions](https://learninghealthcareproject.org/terms-and-conditions/) - 1. Introduction The Learning Healthcare Project supports communication, collaboration and the free-flowing exchange of ideas on The Learning Healthcare Systems with the aim of informing each other and our report on Learning Healthcare Systems. The Learning Healthcare Project reserves the right to remove any message or user that, in our opinion, violates any section of
- [Value](https://learninghealthcareproject.org/implications/value/) - Value in healthcare is the health outcome created per unit of money spent (Porter and Teisberg 2006), therefore maximising value involves achieving the best outcomes at the lowest cost. The measurement of outcomes, along with improving data on costs could, for the first time, allow the routine measurement and comparison of value within healthcare.
- [Examples](https://learninghealthcareproject.org/use-cases/examples/) - Below you will find examples of the implementation of the learning healthcare system. We will continue to update this list as our project continues, so please come back again soon. Evidence Biobanks and Electronic Medical Records: Enabling Cost-Effective Research By E. Bowton, J. R. Field, S. Wang, J. S. Schildcrout, S. L. Van Driest, J. T.
- [Links](https://learninghealthcareproject.org/links/) - Learning Health Community The Learning Health Community is a grassroots stakeholder organisation, based in the US, but with members around the world. It aims to facilitate the realisation of a person centred, continuous and rapid Learning Health System. Visit page Learning Health Systems Journal Learning Health Systems (LHS) is an international, open access, peer-reviewed journal
- [PLICS](https://learninghealthcareproject.org/building-blocks/plics/) - Coming Soon...
- [Do Not Use](https://learninghealthcareproject.org/do-not-use/) - Modern medicine has brought remarkable advances. The application of scientific rigour to the art of healing has resulted in a better understanding of diseases, a proliferation of new treatments and has given hope to many. In large areas of medicine however, the complexity of the health condition and the heterogeneity of patient characteristics means that
- [Examples and Links](https://learninghealthcareproject.org/do-not-use/examples-and-links/) - We will use this page to build a repository of examples of current learning health systems. Please leave comments to make us aware of any examples that we have not listed below.
- [International LHS](https://learninghealthcareproject.org/do-not-use/international-lhs/) - International Learning Healthcare Systems offer the potential to study rare diseases, compare different healthcare systems and even to improve access to healthcare resources in developing countries. However, the technical, ethical and Information Governance implications can be enormous. Projects such as TRANSFoRm (cited below) are leading the way in resolving some of these challenges.
- [National LHS](https://learninghealthcareproject.org/do-not-use/national-lhs/) - Some of the most well known examples of Learning Healthcare Systems are being implemented at the national level. At this scale, routine data has the potential to improve the availability of comparative effectiveness research and to allow benchmarking of services between providers. These systems have also been used to deliver epidemiological insights and to monitor
- [Organisational LHS](https://learninghealthcareproject.org/do-not-use/organisational-lhs/) - We have encountered many examples of Learning Health Systems that operate at the provider level. Geisinger in the US, use routine data in a number of innovative ways to improve outcomes and cost effectiveness: 1. Process automation: Certain aspects of the routine management and preventative interventions for well patients have been automated. This has
- [Cost Effectiveness](https://learninghealthcareproject.org/do-not-use/cost-effectiveness/) - Can improvements in organisational and comparative effectiveness translate into improvements in cost effectiveness?
- [Workforce and Training](https://learninghealthcareproject.org/do-not-use/workforce-and-training/) - What competencies will be required of clinicians working in a learning healthcare system? How will these compare to competencies currently required of clinicians? How should medical education and training take account of this? What will be the impact on the number and type of professionals required?
- [Quality](https://learninghealthcareproject.org/do-not-use/quality/) - How will the ability to produce evidence, tailored to the individual, and the ability to better understand the systems within which care is delivered, result in quality improvements?
- [Ethical](https://learninghealthcareproject.org/do-not-use/ethical/) - What are the ethical implications of learning healthcare systems. Faden et al. have suggested an entirely new ethical framework for the learning healthcare system, with radically different rules on informed consent. Do you feel that such a radical approach is necessary? Learning healthcare systems might give clinicians and patient access to a previously unimaginable
- [Clinical Research](https://learninghealthcareproject.org/do-not-use/clinical-research/) - Modern medicine has brought remarkable advances. The application of scientific rigour to the art of healing has resulted in a better understanding of diseases, a proliferation of new treatments and has given hope to many. In large areas of medicine however, the complexity of the health condition and the heterogeneity of patient characteristics means that
- [Outcomes](https://learninghealthcareproject.org/do-not-use/outcomes/) - The measurement and publication of clinical outcomes has been recognised as a driver of better patient care. As a result, governments, healthcare payers and providers, and even individual clinicians have embarked on outcome measurement programmes. Efforts have started modestly, but hierarchical outcome frameworks have been defined and condition specific outcome measure repositories are being developed
- [IT](https://learninghealthcareproject.org/do-not-use/it/) - The development of information technology is well documented. Processing power and cost have followed Moore's exponential law for several decades, leading some experts to claim that technological development has reached an inflection point, beyond which, computers will become capable of solving problems that had not previously been considered possible. Smart phones, tablets, and wearable devices
- [Healthcare Demand](https://learninghealthcareproject.org/do-not-use/healthcare-demand/) - Demand for healthcare is increasing in many countries. There are various drivers for this trend, including an ageing population and the increase in chronic illness. Demand on the healthcare systems in most countries has been rising for several decades. This has been the result of growing and ageing populations, rising levels of chronic illness, health
- [Healthcare Supply](https://learninghealthcareproject.org/do-not-use/healthcare-supply/) - The cost of healthcare has been increasing faster than inflation for most of the past 50 years. This has resulted in healthcare consuming an ever greater share of GDP. This trend is clearly unsustainable, but it is unclear whether it will be ended by improved productivity or by constraining services.

## Draw Attention

- [Ring with links](https://learninghealthcareproject.org/?da_image=ring-with-explanations-on-hover-2)
- [Figure A The Learning Health System Framework](https://learninghealthcareproject.org/?da_image=914-2)
- [Figure A The Learning Health System Framework](https://learninghealthcareproject.org/?da_image=914)

## Categories

- [Uncategorized](https://learninghealthcareproject.org/category/uncategorized/)
- [Missing](https://learninghealthcareproject.org/category/missing/)
- [Interviews](https://learninghealthcareproject.org/category/interviews/)
- [Site Visits](https://learninghealthcareproject.org/category/site-visits/)
- [Reports](https://learninghealthcareproject.org/category/reports/)
- [Journal Articles](https://learninghealthcareproject.org/category/journal-articles/)
- [Blogs](https://learninghealthcareproject.org/category/blogs/)
- [External Project Links](https://learninghealthcareproject.org/category/external-project-links/)

## Tags

- [Need for LHS](https://learninghealthcareproject.org/tag/need-for-lhs/)
- [Healthcare Data](https://learninghealthcareproject.org/tag/healthcare-data/)
- [Non-Healthcare Data](https://learninghealthcareproject.org/tag/non-healthcare-data/)
- [IT](https://learninghealthcareproject.org/tag/it/)
- [Clinical Research](https://learninghealthcareproject.org/tag/clinical-research/)
- [Workforce and Training](https://learninghealthcareproject.org/tag/workforce-and-training/)
- [Quality](https://learninghealthcareproject.org/tag/quality/)
- [Cost Effectiveness](https://learninghealthcareproject.org/tag/cost-effectiveness/)
- [National LHS](https://learninghealthcareproject.org/tag/national-lhs/)
- [International LHS](https://learninghealthcareproject.org/tag/international-lhs/)
- [Workforce](https://learninghealthcareproject.org/tag/workforce/)
- [External publication](https://learninghealthcareproject.org/tag/external-publication/)
- [Image](https://learninghealthcareproject.org/tag/image/)
- [Healthcare Supply](https://learninghealthcareproject.org/tag/healthcare-supply/)
- [Economic](https://learninghealthcareproject.org/tag/economic/)
- [Ethical](https://learninghealthcareproject.org/tag/ethical/)
- [Organisational LHS](https://learninghealthcareproject.org/tag/organisational-lhs/)
- [Comparative Effectiveness Research](https://learninghealthcareproject.org/tag/comparative-effectiveness-research/)
- [Learning Healthcare System](https://learninghealthcareproject.org/tag/learning-healthcare-system/)
- [Organisational](https://learninghealthcareproject.org/tag/organisational/)
- [Future](https://learninghealthcareproject.org/tag/future/)
- [Ethical Framework](https://learninghealthcareproject.org/tag/ethical-framework/)
- [Examples and Links](https://learninghealthcareproject.org/tag/examples-and-links/)
- [Examples](https://learninghealthcareproject.org/tag/examples/)
- [Behaviour Change](https://learninghealthcareproject.org/tag/behaviour-change/)
- [Decision Support](https://learninghealthcareproject.org/tag/decision-support/)
- [Project publication](https://learninghealthcareproject.org/tag/project-publication/)
- [Video](https://learninghealthcareproject.org/tag/video/)
- [Outcomes Measurement](https://learninghealthcareproject.org/tag/outcomes-measurement/)
- [Outcomes](https://learninghealthcareproject.org/tag/outcomes/)
- [Positive Deviance](https://learninghealthcareproject.org/tag/positive-deviance/)
- [Regulation](https://learninghealthcareproject.org/tag/regulation/)
- [Surveillance](https://learninghealthcareproject.org/tag/surveillance/)
- [Predictive Modelling](https://learninghealthcareproject.org/tag/predictive-modelling/)
- [Healthcare Demand](https://learninghealthcareproject.org/tag/healthcare-demand/)
- [Automation](https://learninghealthcareproject.org/tag/automation/)
- [Value](https://learninghealthcareproject.org/tag/value/)
- [Data to Knowledge](https://learninghealthcareproject.org/tag/data-to-knowledge/)
- [Knowledge to Practise](https://learninghealthcareproject.org/tag/knowledge-to-practise/)
- [Practice to Data](https://learninghealthcareproject.org/tag/practice-to-data/)