Building the learning health system: Describing an organizational infrastructure to support continuous learning

Abstract

Introduction: Academic health centers are reorganizing in response to dramatic changes in the health-care environment. To improve value, they and other health systems must become a learning health system, specifically one that has the capacity to understand performance across the continuum of care and use that information to achieve continuous improvements in efficiency and effectiveness. While learning health system concepts have been well described, the practical steps to create such a system are not well defined. Establishing the necessary infrastructure is particularly challenging at academic health centers due to their tripartite missions and complex organizational structures.

Methods: Using an evidence-based framework, this article describes a series of organizational-level interventions implemented at an academic health center to create the structures and processes to support the functions of a learning health system.

Results: Following implementation of changes from 2008 to 2013, system-level performance improved in multiple domains: patient satisfaction, population health screenings, improvement education, and patient engagement.

Conclusions: This experience can be applied to health systems that wrestle with making system-level change when existing cultures, structures, and processes vary. Using an evidence -based framework is useful when developing the structures and processes that support the functions of a learning health system.

Keywords: academic health center; learning health system; quality improvement.

Figure 1

Testing and implementation process

Figure 2

Top‐box performance of University of Wisconsin (UW) Health primary care patients who strongly agreed “recommend a provider's office without hesitation to others.” Satisfaction survey items from the avatar international satisfaction monthly scores were averaged across quarters. The scores were aggregated as a top‐box score by using the percentage of patients who strongly agreed (strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree) with the statement that “I would recommend this provider's office without hesitation to others”

Figure 3

University of Wisconsin (UW) Health population health screening improvements over time compared with the median score of participating organizations in the Wisconsin Collaborative for Healthcare Quality. Note: Details on all Wisconsin Collaborative for Healthcare Quality (WCHQ) measure specifications can be reviewed at www.wchq.org. ^aBreast cancer screening rates are the values reported to the WCHQ that measure the percentage of eligible women who received a mammogram in the previous 24 months. From 2006 to 2009, this included women aged 40 to 68; in 2010, the screening age was changed to 50 to 74 years. ^bPneumococcal vaccination rates are the values reported to WCHQ that measure the percentage of eligible adults greater than or equal to 65 years who had a pneumococcal vaccination. ^cColorectal cancer screening rates are the values reported to WCHQ that measure the percent of eligible adult patients who received a colorectal cancer screening in the appropriate screening period (this varies by screening test, eg, 10 year interval for colonoscopy)

Figure 4

University of Wisconsin (UW) Health staff and faculty educated in the UW Health Improvement Network. Improvement training refers to the UW Health Improvement Network internal courses

Figure 5

Growth in University of Wisconsin (UW) Health patient and family advisory councils over time. Data from 2007 to 2010 were not available