Implementation of a “real‐world” learning health system: Results from the evaluation of the Connected Health Cities programme

Abstract

Background: The "learning health system" has been proposed to deliver better outcomes for patients and communities by analyzing routinely captured health information and feeding back results to clinical staff. This approach has been piloted in the Connected Health Cities (CHC) programme in four regions in the North of England. This paper presents the results of the evaluation of this program conducted between February and December 2018.Methods: Fifty nine semistructured interviews were completed with a mix of CHC programme staff and external partners who had contributed to the delivery of the CHC programme. Interviews were audio recorded and transcribed verbatim. This also included the review of project documentation including project reports and minutes of project group meetings, in addition to a short online survey that was completed by 31 members of CHC programme staff. Data were analyzed thematically.Results: Two overarching themes emerged through the thematic analysis of participant interview: (a) challenges in the implementation of learning health system pathways, and (b) benefits to the CHC approach for both staff and patients. In particular, time constraints in delivering an ambitious program of work, data quality, and accessibility, as well as the long-term sustainability of the CHC programme were noted as key challenges in implementing a LHS at scale. Conclusions:The findings from this evaluation provide valuable insight into creating learning health system at scale, including the potential benefits and likely challenges. K E Y W O R D S evaluation, learning health system, LHS infrastructure, quality improvement 1 | INTRODUCTION The use of routinely collected health and social care data has the potential to drive forward improvements in health outcomes. 1-3 This is especially important in the United Kingdom where an aging population increases in life expectancy and rapidly changing patterns of

From “Invented here” to “Use it everywhere!”: A Learning health system from bottom and/or top?

“…For example, we identified challenges connected to differences in organizational culture both between departments and hierarchical levels, impairing internal cooperation. Similar differences have been reported between stakeholders 16 and we suggest that they may exist within a single provider organization, in line with Harrison and Shortell. 13 Moreover, we recognized a need to operationalize the LHS concept in terms of concrete organizational structures that matches existing hierarchies to lead a transformation to an LHS based on networks and bottom‐up learning.…”

“…14 , 15 However, already in the seminal work on LHSs from 2007, it is recognized that “although all stakeholders seem to be aligned on the need to define evidence requirements, there is not alignment on what evidence is needed under specific circumstances,” 5 (p130) indicating the difficulty of alignment of stakeholders' views. Practical evidence for such challenges has also been presented, 16 and in the context of this study, an example is the ambitions to define outcome measures for psychiatric patients, where, simplified, first‐line professionals preferred local person‐centered measures about the care process and social functioning, managers pursued aggregable ratings of symptoms and quality of life, and regional authorities monitored process measures, like the proportion of patients that were reported in a quality register (see Solberg et al 17 for similar distinctions). A recent scoping report highlights “learning communities and networks,” “slack resources,” “culture change for shared incentives,” and “ways of thinking” as important areas for the creation of an LHS.…”

“… 4 , 29 , 30 , 31 , 32 Practical examples of real‐world implementations have also been presented, but often for applications on systems or provider level rather than transformations starting from the level of departments or divisions within a larger system. 16 , 33 For similar comprehensive management concepts translation 34 , 35 , 36 , 37 , 38 has been proposed as a more fruitful approach than implementation to guide management‐level applications. Translation emphasizes the need to adapt management innovations to achieve organizational objectives 39 and to negotiate essentials of the desired practice against essentials of the recipient context.…”

The role of co-production in Learning Health Systems

“…propose that LC-Model LHSs have organic, or even fractal, properties, in that LHSs can start as small, parallel initiatives that grow independently and gradually connect, provided that they use the same standards. The LC-model has been used to explain how LHSs work [ 31 ] and how LHSs of the future could be developed, and it has served as a theory of change in developing LHS applications internationally, both in local/regional [ 32 , 33 ] and national applications [ 34–36 ].…”

Deep learning in systems medicine

“…Initiatives such as NHS Digital have been created to curate the digital offering of the UK’s National Health Service (NHS) ( https://digital.nhs.uk ), including the management of secure access to restricted data sets. Academic units have also emerged as organizations that can curate data to support analysis, such as the OpenPrescribing data set that contains historical prescription data [ 33 ] and the Connected Health Cities Initiative, which has sought to build an interoperable system with patient engagement on top of existing NHS infrastructure [ 34 ].…”