Toward a science of learning systems: a research agenda for the high-functioning Learning Health System

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 numerous scientific challenges.Materials and methods The National Science Foundation convened an invitational workshop to identify the fundamental scientific and engineering research challenges to achieving a national-scale LHS. The workshop was planned by a 12-member committee and ultimately engaged 45 prominent researchers spanning multiple disciplines over 2 days in Washington, DC on 11–12 April 2013.Results The workshop participants collectively identified 106 research questions organized around four system-level requirements that a high-functioning LHS must satisfy. The workshop participants also identified a new cross-disciplinary integrative science of cyber-social ecosystems that will be required to address these challenges.Conclusions The intellectual merit and potential broad impacts of the innovations that will be driven by investments in an LHS are of great potential significance. The specific research questions that emerged from the workshop, alongside the potential for diverse communities to assemble to address them through a ‘new science of learning systems’, create an important agenda for informatics and related disciplines.

Crisis analytics: big data-driven crisis response

“…This can lead to a coverage that involves a whole country to construct a Learning Health System (LHS) (Friedman et al 2014) in which stakeholders from government, healthcare, engineering and technology are brought together to analyze the prevailing health situation/emergency, in a country, more accurately and fight diseases/epidemics fast. The creation of such ecosystem will have the capability to establish an environment in which research and clinical practice are not performed in isolation; instead new research and analysis are directly applied to patients in a near real-time manner.…”

Toward an Information Infrastructure for Global Health Improvement

“…In 2015, the U.S. Office of the National Coordinator for Health IT, citing these LHS Core Values, established a nationwide LHS as the pinnacle goal of its 10-year Interoperability Roadmap [19], and other federal agencies have expressed strong endorsement of the concept [20,21]. The U.S. National Science Foundation (NSF) has supported workshops to identify the research challenges to achieving a high functioning LHS [22,23,24,25]. More recently, the Computing Community Consortium (CCC) [26], which advises and works with national research policy makers to understand and shape the future of computing and computing research, has funded a series of three workshops on the broader topic of Cyber-Social Learning Systems (CSLSs), of which LHSs are a special case [25].…”

“…LHSs represent a socio-technical, as opposed to almost purely technical, enterprise, far more complex than sending a human to the moon and safely back. There are deep open scientific, engineering, and design questions, invoking a broad range of sciences, that must be addressed to achieve highly functional LHSs [22]. By sharp contrast, when President Kennedy announced in May of 1961 the goal of putting a person on the moon by the end of the decade, he did so knowing that the Saturn booster rocket, representing the most fundamental engineering challenge, had been built and would be test-flown four months later [67].…”

Estimating Morbidity Rates Based on Routine Electronic Health Records in Primary Care: Observational Study (Preprint)

“…In this study, we developed a method to estimate countrywide morbidity rates based on EHRs of general practitioners (GPs). Morbidity estimates are a key element in the establishment of a learning healthcare system [1][2][3]. Valid estimations of morbidity rates in the general population are essential for patient management by health care providers and developing and evaluating health care policy and provide input for research.…”

“…Many European countries, including the Netherlands and the UK, already have a long history of using EHRs of GPs as a data source for morbidity estimates [1,2,[4][5][6] The extent to which EHRs of GPs are a valid data source to assess the health status of the general population, depends on how primary care is organized in a country. Important primary care characteristics for calculating valid morbidity rates include: 1) free access to primary care, 2) health problems are generally first presented in general practice, 3) GPs use a uniform coding system for recording diagnoses and symptoms 4) having valid information about the epidemiological denominator based on a fixed patient list, or using a method to estimate the patient list [7]. Dutch primary care meets all these requirements, since, like in many other European countries, the GP has a gatekeeper role for specialized care and the GP is the first professional to be consulted for health problems.…”