Building a regional pediatric asthma learning health system in support of optimal, equitable outcomes.

Introduction: Asthma is characterized by preventable morbidity, cost, and inequity. We sought to build an Asthma Learning Health System (ALHS) to coordinate regional pediatric asthma improvement activities. Methods: We generated quantitative and qualitative insights pertinent to a better, more equitable care delivery system. We used electronic health record data to calculate asthma hospitalization rates for youth in our region. We completed an "environmental scan" to catalog the breadth of asthma-related efforts occurring in our children's hospital and across the region. We supplemented the scan with group-level assessments and focus groups with parents, clinicians, and community partners. We used insights from this descriptive epidemiology to inform the definition of shared aims, drivers, measures, and prototype interventions. Results: Greater Cincinnati's youth are hospitalized for asthma at a rate three times greater than the U.S. average. Black youth are hospitalized at a rate five times greater than non-Black youth. Certain neighborhoods bear the disproportionate burden of asthma morbidity. Across Cincinnati, there are many asthma-relevant activities that seek to confront this morbidity; however, efforts are largely disconnected. Qualitative insights highlighted the importance of cross-sector coordination, evidence-based acute and preventive care, healthy homes and neighborhoods, and accountability. These insights also led to a shared, regional aim: to equitably reduce asthma-related hospitalizations. Early interventions have included population-level pattern recognition, multidisciplinary asthma action huddles, and enhanced social needs screening and response. Conclusion: Learning health system methods are uniquely suited to asthma's complexity. Our nascent ALHS provides a scaffold atop which we can pursue better, more equitable regional asthma outcomes.

Pre-exercise protein intake is associated with reduced time in hypoglycaemia among adolescents with type 1 diabetes.

AIM: Secondary analyses were conducted from a randomized trial of an adaptive behavioural intervention to assess the relationship between protein intake (g and g/kg) consumed within 4 h before moderate-to-vigorous physical activity (MVPA) bouts and glycaemia during and following MVPA bouts among adolescents with type 1 diabetes (T1D). MATERIALS AND METHODS: Adolescents (n = 112) with T1D, 14.5 (13.8, 15.7) years of age and 36.6% overweight/obese, provided measures of glycaemia using continuous glucose monitoring [percentage of time above range (>180 mg/dl), time in range (70-180 mg/dl), time below range (TBR; <70 mg/dl)], self-reported physical activity (previous day physical activity recalls), and 24 h dietary recall data at baseline and 6 months post-intervention. Mixed effects regression models adjusted for design (randomization assignment, study site), demographic, clinical, anthropometric, dietary, physical activity and timing covariates estimated the association between pre-exercise protein intake on percentage of time above range, time in range and TBR during and following MVPA. RESULTS: Pre-exercise protein intakes of 10-19.9 g and >20 g were associated with an absolute reduction of -4.41% (p = .04) and -4.83% (p = .02) TBR during physical activity compared with those who did not consume protein before MVPA. Similarly, relative protein intakes of 0.125-0.249 g/kg and ≥0.25 g/kg were associated with -5.38% (p = .01) and -4.32% (p = .03) absolute reductions in TBR during physical activity. We did not observe a significant association between protein intake and measures of glycaemia following bouts of MVPA. CONCLUSIONS: Among adolescents with T1D, a dose of ≥10 g or ≥0.125 g/kg of protein within 4 h before MVPA may promote reduced time in hypoglycaemia during, but not following, physical activity.

Conceptualizing and redefining successful patient engagement in patient advisory councils in learning health networks.

Introduction: Patient engagement has historically referenced engagement in one's healthcare, with more recent definitions expanding patient engagement to encompass patient advocacy work in Learning Health Networks (LHNs). Efforts to conceptualize and define what patient engagement means-and what successful patient engagement means-are, however, lacking and a barrier to meaningful and sustainable patient engagement via patient advisory councils (PACs) across LHNs. Methods: Several co-authors (Madeleine Huwe, Becky Woolf, Jennie David) are former ImproveCareNow (ICN) PAC members, and we integrate a narrative review of the extant literature and a case study of our lived experiences as former ICN PAC members. We present nuanced themes of successful patient engagement from our lived experiences on ICN's PAC, with illustrative quotes from other PAC members, and then propose themes and metrics to consider in patient engagement across LHNs. Results: Successful patient engagement in our experiences with ICN's PAC reaches beyond the "levels of engagement" previously described in the literature. We posit that our successful patient/PAC engagement experiences with ICN represent key mechanisms that could be applied across LHNs, including (1) personal growth for PAC members, (2) PAC internal engagement/community, (3) PAC engagement and presence within the LHN, (4) local institutional engagement for those who participate in the LHN, and (5) tangible resources/products from PAC members. Conclusion: Patient engagement in LHNs, like ICN, holds significant power to meaningfully shape and co-produce healthcare systems, and engagement is undervalued and conceptualized dichotomously (eg, engaged or not engaged). Reconceptualizing successful patient/PAC engagement is critical in ongoing efforts to study, support, and understand mechanisms of sustainable and successful patient engagement. Having a modern, multidimensional definition for successful patient engagement in LHNs can support efforts to increase underrepresented voices in PACs, measure and track successful multidimensional patient engagement, and study how successful patient engagement may impact outcomes for patients and LHNs.

Eating behaviors and estimated body fat percentage among adolescents with type 1 diabetes.

AIMS: Estimate associations between select eating behaviors and estimated body fat percentage (eBFP) and explore effect modification by sex among adolescents with type 1 diabetes (T1D). METHODS: This analysis included 257 adolescents (mean age 14.9 ± 1.14 years; 49.8 % female) with baseline hemoglobin A1c (HbA1c) between 8 and 13 % (64 mmol/mol-119 mmol/mol) from a randomized trial designed to improve glycemia. Eating behaviors and eBFP were determined from surveys and validated equations respectively. Linear mixed models were used to estimate associations. Effect modification was assessed via stratified plots, stratified associations, and interaction terms. RESULTS: Disordered eating, dietary restraint, and eBFP were significantly higher among females while external eating was higher among males. Disordered eating (ß: 0.49, 95 %CI: 0.24, 0.73, p = 0.0001) and restraint (ß: 1.11, 95 %CI: 0.29, 1.92, p = 0.0081) were positively associated with eBFP while external eating was not (ß: -0.19, 95 %CI: -0.470, 0.096, p = 0.20). Interactions with sex were not significant (p-value range: 0.28-0.64). CONCLUSION: Disordered eating and dietary restraint were positively associated with eBFP, highlighting the potential salience of these eating behaviors to cardiometabolic risk for both female and male adolescents. Prospective studies should investigate whether these eating behaviors predict eBFP longitudinally to inform obesity prevention strategies in T1D.

The Cystic Fibrosis Learning Network: A mixed methods evaluation of program goals, attributes, and impact.

Introduction: The Cystic Fibrosis (CF) Foundation sponsored the design, pilot testing, and implementation of the CF Learning Network (CFLN) to explore how the Foundation's Care Center Network (CCN) could become a learning health system. Six years after the design, the Foundation commissioned a formative mixed methods evaluation of the CFLN to assess: CFLN participants' understanding of program goals, attributes, and perceptions of current and future impact. Methods: We performed semi-structured interviews with CFLN participants to identify perceived goals, attributes, and impact of the network. Following thematic analyses, we developed and distributed a survey to CFLN members and a matched sample of CCN programs to understand whether the themes were unique to the CFLN. Results: Interviews with 24 CFLN participants were conducted. Interviewees identified the primary CFLN goal as improving outcomes for people living with CF, with secondary goals of providing training in quality improvement (QI), creating a learning community, engaging all stakeholders in improvement, and spreading best practices to the CCN. Project management, use of data, common QI methods, and the learning community were seen as critical to success. Survey responses were collected from 103 CFLN members and 25 CCN members. The data revealed that CFLN respondents were more likely than CCN respondents to connect with other CF programs, routinely use data for QI, and engage patient and family partners in QI. Conclusions: Our study suggests that the CFLN provides value beyond that achieved by the CCN. Key questions remain about whether spread of the CFLN could improve outcomes for more people living with CF.

Establishing a Cystic Fibrosis Learning Network: Interventions to promote collaboration and data-driven improvement at scale.

Introduction: A learning health network is a type of learning health system in which stakeholders use network organization to improve health and health care. Building on existing resources in the cystic fibrosis (CF) community, the Cystic Fibrosis Learning Network (CFLN) was designed to improve medical outcomes and quality of life through an intentional focus on achieving reliable evidence-based chronic care delivery and creating a system for data-driven collaborative learning. Methods: We describe the development and growth of the CFLN considering six domains of a Network Maturity Grid: system leadership; governance and policy management; quality improvement (QI); engagement and community building; data and analytics; and research. We illustrate the impact of the CFLN experience on chronic care processes and indicators of collaborative infrastructure. Results: The CFLN represents 36 accredited care centers in the CF Foundation Care Center Network caring for over 6300 patients. Of 6779 patient clinical care visits/quarter, 77% are entered into the CF Foundation Patient Registry within 30 days, providing timely means to track outcomes. Collaborative visit planning is occurring in 93% of clinical care visits to share agenda setting with patients and families. Almost all CFLN teams (94%, n = 34) have a patient/family partner (PFP), and 74% of PFPs indicate they are actively participating, taking ownership of, or leading QI initiatives with the interdisciplinary care team. In 2022, 97% of centers reported completing 1-13 improvement cycles per month, and 82% contributed to monthly QI progress reports to share learning. Conclusion: The CFLN is a maturing, collaborative infrastructure. CFLN centers practice at an advanced level of coproduction. The CFLN fosters interdisciplinary and PFP leadership and the performance of consistent data-driven improvement cycles. CFLN centers are positioned to respond to rapid changes in evidence-based care and advance the practice of QI and implementation science on a broader scale.

Comparative Effectiveness of Anti-TNF in Combination With Low-Dose Methotrexate vs Anti-TNF Monotherapy in Pediatric Crohn's Disease: A Pragmatic Randomized Trial.

BACKGROUND & AIMS: Tumor necrosis factor inhibitors, including infliximab and adalimumab, are a mainstay of pediatric Crohn's disease therapy; however, nonresponse and loss of response are common. As combination therapy with methotrexate may improve response, we performed a multicenter, randomized, double-blind, placebo-controlled pragmatic trial to compare tumor necrosis factor inhibitors with oral methotrexate to tumor necrosis factor inhibitor monotherapy. METHODS: Patients with pediatric Crohn's disease initiating infliximab or adalimumab were randomized in 1:1 allocation to methotrexate or placebo and followed for 12-36 months. The primary outcome was a composite indicator of treatment failure. Secondary outcomes included anti-drug antibodies and patient-reported outcomes of pain interference and fatigue. Adverse events (AEs) and serious AEs (SAEs) were collected. RESULTS: Of 297 participants (mean age, 13.9 years, 35% were female), 156 were assigned to methotrexate (110 infliximab initiators and 46 adalimumab initiators) and 141 to placebo (102 infliximab initiators and 39 adalimumab initiators). In the overall population, time to treatment failure did not differ by study arm (hazard ratio, 0.69; 95% CI, 0.45-1.05). Among infliximab initiators, there were no differences between combination and monotherapy (hazard ratio, 0.93; 95% CI, 0.55-1.56). Among adalimumab initiators, combination therapy was associated with longer time to treatment failure (hazard ratio, 0.40; 95% CI, 0.19-0.81). A trend toward lower anti-drug antibody development in the combination therapy arm was not significant (infliximab: odds ratio, 0.72; 95% CI, 0.49-1.07; adalimumab: odds ratio, 0.71; 95% CI, 0.24-2.07). No differences in patient-reported outcomes were observed. Combination therapy resulted in more AEs but fewer SAEs. CONCLUSIONS: Among adalimumab but not infliximab initiators, patients with pediatric Crohn's disease treated with methotrexate combination therapy experienced a 2-fold reduction in treatment failure with a tolerable safety profile. CLINICALTRIALS: gov, Number: NCT02772965.

A High Protein Diet Is Associated with Improved Glycemic Control Following Exercise among Adolescents with Type 1 Diabetes.

Nutritional strategies are needed to aid people with type 1 diabetes (T1D) in managing glycemia following exercise. Secondary analyses were conducted from a randomized trial of an adaptive behavioral intervention to assess the relationship between post-exercise and daily protein (g/kg) intake on glycemia following moderate-to-vigorous physical activity (MVPA) among adolescents with T1D. Adolescents (n = 112) with T1D, 14.5 (13.8, 15.7) years of age, and 36.6% overweight or obese, provided measures of glycemia using continuous glucose monitoring (percent time above range [TAR, >180 mg/dL], time-in-range [TIR, 70-180 mg/dL], time-below-range [TBR, <70 mg/dL]), self-reported physical activity (previous day physical activity recalls), and 24 h dietary recall data at baseline and 6 months post-intervention. Mixed effects regression models adjusted for design (randomization assignment, study site), demographic, clinical, anthropometric, dietary, physical activity, and timing covariates estimated the association between post-exercise and daily protein intake on TAR, TIR, and TBR from the cessation of MVPA bouts until the following morning. Daily protein intakes of ≥1.2 g/kg/day were associated with 6.9% (p = 0.03) greater TIR and -8.0% (p = 0.02) less TAR following exercise, however, no association was observed between post-exercise protein intake and post-exercise glycemia. Following current sports nutrition guidelines for daily protein intake may promote improved glycemia following exercise among adolescents with T1D.

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

BACKGROUND: Despite the widespread clinical perception that hypoglycemia may drive weight gain in youth with type 1 diabetes (T1D), there is an absence of published evidence supporting this hypothesis. METHODS: We estimated the body fat percentage (eBFP) of 211 youth (HbA1c 8.0-13.0%, age 13-16) at baseline, 6, and 18 months of the Flexible Lifestyles Empowering Change trial using validated equations. Group-based trajectory modeling assigned adolescents to sex-specific eBFP groups. Using baseline 7-day blinded continuous glucose monitoring data, "more" vs. "less" percent time spent in hypoglycemia was defined by cut-points using sample median split and clinical guidelines. Adjusted logistic regression estimated the odds of membership in an increasing eBFP group comparing youth with more vs. less baseline hypoglycemia. RESULTS: More time spent in clinical hypoglycemia (defined by median split) was associated with 0.29 the odds of increasing eBFP in females (95% CI: 0.12, 0.69; p = 0.005), and 0.33 the odds of stable/increasing eBFP in males (95% CI: 0.14, 0.78; p = 0.01). CONCLUSIONS: Hypoglycemia may not be a major driver of weight gain in US youth with T1D and HbA1c ≥8.0. Further studies in different sub-groups are needed to clarify for whom hypoglycemia may drive weight gain and focus future etiological studies and interventions. IMPACT: We contribute epidemiological evidence that hypoglycemia may not be a major driver of weight gain in US youth with type 1 diabetes and HbA1c ≥8.0% and highlight the need for studies to prospectively test this hypothesis rooted in clinical perception. Future research should examine the relationship between hypoglycemia and adiposity together with psychosocial, behavioral, and other clinical factors among sub-groups of youth with type 1 diabetes (i.e., who meet glycemic targets or experience a frequency/severity of hypoglycemia above a threshold) to further clarify for whom hypoglycemia may drive weight gain and progress etiological understanding of and interventions for healthy weight maintenance.

Web-Based Mindfulness-Based Interventions for Well-being: Randomized Comparative Effectiveness Trial.

BACKGROUND: Mindfulness can improve overall well-being by training individuals to focus on the present moment without judging their thoughts. However, it is unknown how much mindfulness practice and training are necessary to improve well-being. OBJECTIVE: The primary aim of this study was to determine whether a standard 8-session web-based mindfulness-based cognitive therapy (MBCT) program, compared with a brief 3-session mindfulness intervention, improved overall participant well-being. In addition, we sought to explore whether the treatment effects differed based on the baseline characteristics of the participants (ie, moderators). METHODS: Participants were recruited from 17 patient-powered research networks, web-based communities of stakeholders interested in a common research area. Participants were randomized to either a standard 8-session MBCT or a brief 3-session mindfulness training intervention accessed on the web. The participants were followed for 12 weeks. The primary outcome of the study was well-being, as measured by the World Health Organization-Five Well-Being Index. We hypothesized that MBCT would be superior to a brief mindfulness training. RESULTS: We randomized 4411 participants, 3873 (87.80%) of whom were White and 3547 (80.41%) of female sex assigned at birth. The mean baseline World Health Organization-Five Well-Being Index score was 50.3 (SD 20.7). The average self-reported well-being in each group increased over the intervention period (baseline to 8 weeks; model-based slope for the MBCT group: 0.78, 95% CI 0.63-0.93, and brief mindfulness group: 0.76, 95% CI 0.60-0.91) as well as the full study period (ie, intervention plus follow-up; baseline to 20 weeks; model-based slope for MBCT group: 0.41, 95% CI 0.34-0.48; and brief mindfulness group: 0.33, 95% CI 0.26-0.40). Changes in self-reported well-being were not significantly different between MBCT and brief mindfulness during the intervention period (model-based difference in slopes: -0.02, 95% CI -0.24 to 0.19; P=.80) or during the intervention period plus 12-week follow-up (-0.08, 95% CI -0.18 to 0.02; P=.10). During the intervention period, younger participants (P=.05) and participants who completed a higher percentage of intervention sessions (P=.005) experienced greater improvements in well-being across both interventions, with effects that were stronger for participants in the MBCT condition. Attrition was high (ie, 2142/4411, 48.56%), which is an important limitation of this study. CONCLUSIONS: Standard MBCT improved well-being but was not superior to a brief mindfulness intervention. This finding suggests that shorter mindfulness programs could yield important benefits across the general population of individuals with various medical conditions. Younger people and participants who completed more intervention sessions reported greater improvements in well-being, an effect that was more pronounced for participants in the MBCT condition. This finding suggests that standard MBCT may be a better choice for younger people as well as treatment-adherent individuals. TRIAL REGISTRATION: ClinicalTrials.gov NCT03844321; https://clinicaltrials.gov/ct2/show/NCT03844321.

Toward an ontology of collaborative learning healthcare systems.

Objective: To establish a basis for a domain ontology - a formal, explicit specification of a shared conceptualization - of collaborative learning healthcare systems (CLHSs) in order to facilitate measurement, explanation, and improvement. Methods: We adapted the "Methontology" approach to begin building an ontology of CLHSs. We specified the purpose of an ontology, acquired domain knowledge via literature review, conceptualized a common framework of CLHSs using a grounded approach, refined these concepts based on expert panel input, and illustrated concept application via four cases. Results: The set of concepts identified as important to include in an ontology includes goals, values, structure, actors, environment, and products. To establish this set of concepts, we gathered input from content experts in two ways. First, expert panel methods were used to elicit feedback on these concepts and to test the elicitation of terms for the vocabulary of the Values concept. Second, from these discussions we developed a mapping exercise to test the intuitiveness of the concepts, requesting that network leaders from four CLHSs complete a mapping exercise to associate characteristics of their networks with the high-level concepts, building the vocabulary for each concept in a grounded fashion. We also solicited feedback from these participants on the experience of completing the mapping exercise, finding that the exercise is acceptable and could aid in CLHS development and collaboration. Respondents identified opportunities to improve the operational definitions of each concept to ensure that corresponding vocabularies are distinct and non-overlapping. Discussion: Our results provide a foundation for developing a formal, explicit shared conceptualization of CLHSs. Once developed, such a tool can be useful for measurement, explanation, and improvement. Further work, including alignment to a top-level ontology, expanding the vocabulary, and defining relations between vocabulary is required to formally build out an ontology for these uses.

Cystic fibrosis learning network telehealth innovation lab during the COVID-19 pandemic: a success QI story for interdisciplinary care and agenda setting.

INTRODUCTION: The Cystic Fibrosis Foundation chronic care guidelines recommend monitoring clinical status of a patient with cystic fibrosis (CF) through quarterly interdisciplinary visits. At the beginning of the COVID-19 pandemic, the Cystic Fibrosis Learning Network (CFLN) designed and initiated a telehealth (TH) innovation lab (TH ILab) to support transition from the classic CF care model of quarterly in-person office visits to a care model that included TH. AIM: The specific aims of the TH ILab were to increase the percentage of virtual visits with interdisciplinary care (IDC) from 60% to 85% and increase the percentage of virtual visits in which patients and families participated in shared agenda setting (AS) from 52% to 85% by 31 December 2020. METHODS: The model for improvement methodology was used to determine the ILab aims, theory, interventions and measures. In the testing phase of the ILab, data related to process and outcome measures as well as learnings from plan-do-study-act cycles were collected, analysed and shared weekly with the TH ILab teams. Participating centres created processes for IDC and AS for TH visits and developed and shared quality improvement tools specific to their local context with other centres during the ILab weekly meetings and via a secure CFLN-maintained platform. RESULTS: Both specific aims were achieved ahead of the expected target date. By August 2020, 85% of the TH ILab visits provided IDC and 92% of patients were seen for CF care by teams from the TH ILab that participated in AS. CONCLUSION: Shared learning through a collaborative, data-driven process in the CFLN TH ILab rapidly led to standardised TH IDC and AS, which achieved reliable and sustainable processes which could be reproduced by other networks.

Impact of guideline-recommended dietitian assessments on weight gain in infants with cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF)-specialized nutrition care strives to meet normal infant growth, but the relationship of dietitian assessments to weight outcomes is unknown. We characterize nutrition management for inadequate weight gain and assess association of dietitian assessments and center-level weight-for-age Z-scores (WAZ). METHODS: We used encounter data from 226 infants across 28 US CF Centers from the Baby Observational Nutritional study between January 2012 through December 2017. We identified dietitian assessments and consensus guideline-recommended responses to inadequate weight gain: calorie increases, pancreatic enzyme replacement therapy (PERT) increases, or shortened time to next visit. We compared center assessments by funnel plot and summarize median WAZ by center. RESULTS: Of 2,527 visits, 808 (32%) visits had identified inadequate weight gain, distributed in 216 infants. Assessments occurred in 1953 visits (77%), but varied widely between centers (range 17% - 98%). For inadequate weight gain, most and least common responses were calorie increase (64%) and PERT increase (21%). Funnel plot analysis identified 4 high-performers for frequent dietitian assessments (range 92% - 98%) and 4 under-performers (range 17% - 56%). High-performers treated inadequate weight gain more often with adequate calories (24/30, 80% v. 12/23, 52%) and closer follow up (104/164, 63% v. 60/120, 49%) compared to under-performers. Three of 4 high-performing sites met center nutrition goals for positive median WAZ at 2 years old unlike 3 under-performers (WAZHigh 0.33 v. WAZLow -0.15), despite similar patient characteristics. CONCLUSION: We characterized multicenter variation in dietitian assessments, identifying opportunities to improve care delivery to target early nutrition outcomes.

Sustainable generation of patient-led resources in a learning health system.

BACKGROUND: Patient and Family Advisory Councils (PFACs) are an emerging mechanism to integrate patient and family voices into healthcare. One such PFAC is the Patient Advisory Council (PAC) of the ImproveCareNow (ICN) network, a learning health system dedicated to advancing the care of individuals with pediatric inflammatory bowel disease (IBD). Using quality improvement techniques and co-production, the PAC has made great strides in developing novel patient-led resources. METHODS: This paper, written by patients and providers from ICN, reviews current ICN data on PAC-generated resources, including creation processes and download statistics. RESULTS: Looking at different iterations of PAC infrastructure, this paper highlights specific leadership approaches used to increase patient involvement and improve resource creation. Emerging data suggests that the larger ICN learning health system has had limited interactions with these resources. CONCLUSION: ICN provides a novel approach for meaningful integration of patient partners into learning health systems. This paper points to the incredible value of PFAC expertise in the resource creation process. Future work should seek to support PFAC development across other diseases and address the challenges of integrating patient-led resources into clinical care.

A collaborative learning health system agent-based model: Computational and face validity.

INTRODUCTION: Improving the healthcare system is a major public health challenge. Collaborative learning health systems (CLHS) - network organizations that allow all healthcare stakeholders to collaborate at scale - are a promising response. However, we know little about CLHS mechanisms of actions, nor how to optimize CLHS performance. Agent-based models (ABM) have been used to study a variety of complex systems. We translate the conceptual underpinnings of a CLHS to a computational model and demonstrate initial computational and face validity. METHODS: CLHSs are organized to allow stakeholders (patients and families, clinicians, researchers) to collaborate, at scale, in the production and distribution of information, knowledge, and know-how for improvement. We build up a CLHS ABM from a population of patient- and doctor-agents, assign them characteristics, and set them into interaction, resulting in engagement, information, and knowledge to facilitate optimal treatment selection. To assess computational and face validity, we vary a single parameter - the degree to which patients influence other patients - and trace its effects on patient engagement, shared knowledge, and outcomes. RESULTS: The CLHS ABM, developed in Python and using the open-source modeling framework Mesa, is delivered as a web application. The model is simulated on a cloud server and the user interface is a web browser using Python and Plotly Dash. Holding all other parameters steady, when patient influence increases, the overall patient population activation increases, leading to an increase in shared knowledge, and higher median patient outcomes. CONCLUSIONS: We present the first theoretically-derived computational model of CLHSs, demonstrating initial computational and face validity. These preliminary results suggest that modeling CLHSs using an ABM is feasible and potentially valid. A well-developed and validated computational model of the health system may have profound effects on understanding mechanisms of action, potential intervention targets, and ultimately translation to improved outcomes.

Getting what is needed, when it's needed: Sharing information, knowledge, and know-how in a Collaborative Learning Health System.

BACKGROUND: Collaborative Learning Health Systems (CLHS) improve outcomes in part by facilitating collaboration among all stakeholders. One way to facilitate collaboration is by creating conditions for the production and sharing of medical and non-medical resources (information, knowledge, and knowhow [IKK]) so anybody can get "what is needed, when it's needed" (WINWIN) to act in ways that improve health and healthcare. Matching resources to needs can facilitate accurate diagnosis, appropriate prescribing, answered questions, provision of emotional and social support, and uptake of innovations. OBJECTIVES: We describe efforts in ImproveCareNow, a CLHS improving outcomes in pediatric inflammatory bowel disease (IBD), to increase the number of patients and families creating and accessing IKK, and the challenges faced in that process. METHODS: We applied tactics such as outreach through trusted messengers, community organizing, and digital outreach such as sharing resources on our website, via social media, and email to increase the number of people producing, able to access, and accessing IKK. We applied an existing measurement system to track our progress and supplemented this with community feedback. RESULTS: In August of 2017 we identified and began measuring specific actions to track community growth. The number of patients and families producing IKK has increased by a factor of 2.7, using resources has increased by a factor of 4.1 and aware of resources as increased by a factor of 4.0. We identified challenges to measurement and scaling. CONCLUSIONS: It is possible to intentionally increase the number of patients and caregivers engaged with a CHLS to produce and share resources to improve their health.

A science of collaborative learning health systems.

INTRODUCTION: Improving the U.S. healthcare system and health outcomes is one of the most pressing public health challenges of our time. Previously described Collaborative Learning Health Systems (CLHSs) are a promising approach to outcomes improvement. In order to fully realize this promise, a deeper understanding of this phenomenon is necessary. METHODS: We drew on our experience over the past decade with CLHSs as well as qualitative literature review to answer three questions: What kind of phenomena are CLHSs? and what is an appropriate scientific approach? How might we frame CLHSs conceptually? What are potential mechanisms of action? RESULTS: CLHSs are complex adaptive systems in which all stakeholders are able to collaborate, at scale, to create and share resources to satisfy a variety of needs. This is accomplished by providing infrastructure and services that enable stakeholders to act on their inherent motivations. This framing has implications for both research and practice. CONCLUSION: Articulating this framework and potential mechanisms of action should facilitate research to test and refine hypotheses as well as guide practice to develop and optimize this promising approach to improving healthcare systems.

Measuring engagement in a collaborative learning health system: The case of ImproveCareNow.

BACKGROUND: Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, and track over time, engagement in ImproveCareNow, a collaborative learning health system for children with inflammatory bowel disease. INTRODUCTION: We developed a categorical classification scheme for engagement in ImproveCareNow. Each tier is defined in terms of observable individual behaviors. When an individual completes one or more qualifying behavior, s/he is classified as engaged at that tier. Individuals are entered into a database, which is accessible to care centers throughout the ImproveCareNow network. Database records include fields for individual name, behavior type, time, place, and level of engagement. RESULTS: The resulting system is employed at 79 ImproveCareNow care centers in the United States. The system recognizes four levels of engagement. Behaviors are recorded in a managed vocabulary and recorded in an online database. The database is queried weekly for individual engagement behaviors, which are tracked longitudinally. Center- and network-level statistics are generated and disseminated to stakeholders. CONCLUSION: It is possible to monitor longitudinal engagement in a collaborative learning health system, thereby charting progress toward engagement goals and enabling quantitative evaluation of interventions aimed at increasing engagement.

A maturity grid assessment tool for learning networks.

BACKGROUND: The vision of learning healthcare systems (LHSs) is attractive as a more effective model for health care services, but achieving the vision is complex. There is limited literature describing the processes needed to construct such multicomponent systems or to assess development. METHODS: We used the concept of a capability maturity matrix to describe the maturation of necessary infrastructure and processes to create learning networks (LNs), multisite collaborative LHSs that use an actor-oriented network organizational architecture. We developed a network maturity grid (NMG) assessment tool by incorporating information from literature review, content theory from existing networks, and expert opinion to establish domains and components. We refined the maturity grid in response to feedback from network leadership teams. We followed NMG scores over time for nine LNs and plotted scores for each domain component with respect to SD for one participating network. We sought subjective feedback on the experience of applying the NMG to individual networks. RESULTS: LN leaders evaluated the scope, depth, and applicability of the NMG to their networks. Qualitative feedback from network leaders indicated that changes in NMG scores over time aligned with leaders' reports about growth in specific domains; changes in scores were consistent with network efforts to improve in various areas. Scores over time showed differences in maturation in the individual domains of each network. Scoring patterns, and SD for domain component scores, indicated consistency among LN leaders in some but not all aspects of network maturity. A case example from a participating network highlighted the value of the NMG in prompting strategic discussions about network development and demonstrated that the process of using the tool was itself valuable. CONCLUSIONS: The capability maturity grid proposed here provides a framework to help those interested in creating Learning Health Networks plan and develop them over time.