High Body Mass Index and Response to Anti-Tumor Necrosis Factor Therapy in Pediatric Crohn's Disease.

INTRODUCTION: Obesity is common among patients with pediatric Crohn's disease (PCD). Some adult studies suggest obese patients respond less well to anti-tumor necrosis factor (TNF) treatment. This study sought compares anti-TNF response and anti-TNF levels between pediatric patients with normal and high body mass index (BMI). METHODS: The COMBINE trial compared anti-TNF monotherapy with combination therapy with methotrexate in patients with PCD. In this secondary analysis, a comparison of time-to-treatment failure among patients with normal BMI vs BMI Z -score >1, adjusting for prescribed anti-TNF (infliximab [IFX] or adalimumab [ADA]), trial treatment assignment (combination vs monotherapy), and relevant covariates. Median anti-TNF levels across BMI category was also examined. RESULTS: Of 224 participants (162 IFX initiators and 62 ADA initiators), 111 (81%) had a normal BMI and 43 (19%) had a high BMI. High BMI was associated with treatment failure among ADA initiators (7/10 [70%] vs 12/52 [23%], hazard ratio 0.29, P = 0.007) but not IFX initiators. In addition, ADA-treated patients with a high BMI had lower ADA levels compared with those with normal BMI (median 5.8 vs 12.8 µg/mL, P = 0.02). IFX trough levels did not differ between BMI groups. DISCUSSION: Overweight and obese patients with PCD are more likely to experience ADA treatment failure than those with normal BMI. Higher BMI was associated with lower drug trough levels. Standard ADA dosing may be insufficient for overweight children with PCD. Among IFX initiators, there was no observed difference in clinical outcomes or drug levels, perhaps due to weight-based dosing and/or greater use of proactive drug monitoring.

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.

Electronic health records identify timely trends in childhood mental health conditions.

BACKGROUND: Electronic health records (EHRs) data provide an opportunity to collect patient information rapidly, efficiently and at scale. National collaborative research networks, such as PEDSnet, aggregate EHRs data across institutions, enabling rapid identification of pediatric disease cohorts and generating new knowledge for medical conditions. To date, aggregation of EHR data has had limited applications in advancing our understanding of mental health (MH) conditions, in part due to the limited research in clinical informatics, necessary for the translation of EHR data to child mental health research. METHODS: In this cohort study, a comprehensive EHR-based typology was developed by an interdisciplinary team, with expertise in informatics and child and adolescent psychiatry, to query aggregated, standardized EHR data for the full spectrum of MH conditions (disorders/symptoms and exposure to adverse childhood experiences (ACEs), across 13 years (2010-2023), from 9 PEDSnet centers. Patients with and without MH disorders/symptoms (without ACEs), were compared by age, gender, race/ethnicity, insurance, and chronic physical conditions. Patients with ACEs alone were compared with those that also had MH disorders/symptoms. Prevalence estimates for patients with 1+ disorder/symptoms and for specific disorders/symptoms and exposure to ACEs were calculated, as well as risk for developing MH disorder/symptoms. RESULTS: The EHR study data set included 7,852,081 patients < 21 years of age, of which 52.1% were male. Of this group, 1,552,726 (19.8%), without exposure to ACEs, had a lifetime MH disorders/symptoms, 56.5% being male. Annual prevalence estimates of MH disorders/symptoms (without exposure to ACEs) rose from 10.6% to 2010 to 15.1% in 2023, a 44% relative increase, peaking to 15.4% in 2019, prior to the Covid-19 pandemic. MH categories with the largest increases between 2010 and 2023 were exposure to ACEs (1.7, 95% CI 1.6-1.8), anxiety disorders (2.8, 95% CI 2.8-2.9), eating/feeding disorders (2.1, 95% CI 2.1-2.2), gender dysphoria/sexual dysfunction (43.6, 95% CI 35.8-53.0), and intentional self-harm/suicidality (3.3, 95% CI 3.2-3.5). White youths had the highest rates in most categories, except for disruptive behavior disorders, elimination disorders, psychotic disorders, and standalone symptoms which Black youths had higher rates. Median age of detection was 8.1 years (IQR 3.5-13.5) with all standalone symptoms recorded earlier than the corresponding MH disorder categories. CONCLUSIONS: These results support EHRs' capability in capturing the full spectrum of MH disorders/symptoms and exposure to ACEs, identifying the proportion of patients and groups at risk, and detecting trends throughout a 13-year period that included the Covid-19 pandemic. Standardized EHR data, which capture MH conditions is critical for health systems to examine past and current trends for future surveillance. Our publicly available EHR-mental health typology codes can be used in other studies to further advance research in this area.

Racial Disparities in Pediatric Inflammatory Bowel Disease Care: Differences in Outcomes and Health Service Utilization Between Black and White Children.

OBJECTIVE: To describe racial inequities in pediatric inflammatory bowel disease care and explore potential drivers. METHODS: We undertook a single-center, comparative cohort study of newly diagnosed Black and non-Hispanic White patients with inflammatory bowel disease, aged <21 years, from January 2013 through 2020. Primary outcome was corticosteroid-free remission (CSFR) at 1 year. Other longitudinal outcomes included sustained CSFR, time to anti-tumor necrosis factor therapy, and evaluation of health service utilization. RESULTS: Among 519 children (89% White, 11% Black), 73% presented with Crohn's disease and 27% with ulcerative colitis. Disease phenotype did not differ by race. More patients from Black families had public insurance (58% vs 30%, P < .001). Black patients were less likely to achieve CSFR 1-year post diagnosis (OR: 0.52, 95% CI:0.3-0.9) and less likely to achieve sustained CSFR (OR: 0.48, 95% CI: 0.25-0.92). When adjusted by insurance type, differences by race to 1-year CSFR were no longer significant (aOR: 0.58; 95% CI: 0.33, 1.04; P = .07). Black patients were more likely to transition from remission to a worsened state, and less likely to transition to remission. We found no differences in biologic therapy utilization or surgical outcomes by race. Black patients had fewer gastroenterology clinic visits and 2-fold increased odds for emergency department visits. CONCLUSIONS: We observed no differences by race in phenotypic presentation and medication usage. Black patients had half the odds of achieving clinical remission, but a degree of this was mediated by insurance status. Understanding the cause of such differences will require further exploration of social determinants of health.

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.

The learning health system for pediatric nephrology: building better systems to improve health.

Learning health systems (LHS) align science, informatics, incentives, and culture for continuous improvement and innovation. In this organizational system, best practices are seamlessly embedded in the delivery process, and new knowledge is captured as an integral byproduct of the care delivery experience aimed to transform clinical practice and improve patient outcomes. The objective of this review is to describe how building better health systems that integrate clinical care, improvement, and research as part of an LHS can improve care within pediatric nephrology. This review will provide real-world examples of how this system can be established in a single center and across multiple centers as learning health networks.

Behavioral Health Diagnoses in Youth with Gender Dysphoria Compared with Controls: A PEDSnet Study.

OBJECTIVE: To assess the odds of a psychiatric or neurodevelopmental diagnosis among youth with a diagnosis of gender dysphoria compared with matched controls in a large electronic health record dataset from 6 pediatric health systems, PEDSnet. We hypothesized that youth with gender dysphoria would have higher odds of having psychiatric and neurodevelopmental diagnoses than controls. STUDY DESIGN: All youth with a diagnosis of gender dysphoria (n = 4173 age at last visit 16.2 ± 3.4) and at least 1 outpatient encounter were extracted from the PEDSnet database and propensity-score matched on 8 variables to controls without gender dysphoria (n = 16 648, age at last visit 16.2 ± 4.8) using multivariable logistic regression. The odds of having psychiatric and neurodevelopmental diagnoses were examined using generalized estimating equations. RESULTS: Youth with gender dysphoria had higher odds of psychiatric (OR 4.0 [95% CI 3.8, 4.3] P < .0001) and neurodevelopmental diagnoses (1.9 [1.7, 2.0], P < .0001). Youth with gender dysphoria were more likely to have a diagnosis across all psychiatric disorder subcategories, with particularly high odds of mood disorder (7.3 [6.8, 7.9], P < .0001) and anxiety (5.5 [5.1, 5.9], P < .0001). Youth with gender dysphoria had a greater odds of autism spectrum disorder (2.6, [2.2, 3.0], P < .0001). CONCLUSIONS: Youth with gender dysphoria at large pediatric health systems have greater odds of psychiatric and several neurodevelopmental diagnoses compared with youth without gender dysphoria. Further studies are needed to evaluate changes in mental health over time with access to gender affirming care.

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.

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.

Integrating shared decision making into trial consent: A nested, cluster-randomized trial.

OBJECTIVE: Using a nested, cluster-randomized trial, we tested the hypothesis that a shared decision-making intervention, as part of consent, would improve study-related knowledge. METHODS: We developed a shared decision-makingintervention then randomized sites in a clinical trial to intervention or control (standard consent). We collected participants' knowledge (primary outcome) and decisional support data. Other data came from a clinical registry and research coordinator surveys. We compared outcomes between study arms using generalized estimating equation models, accounting for clustering. We used qualitative description to understand variation in intervention use. RESULTS: 265 individuals, from 34 sites, enrolled in the parent trial during our study period. Of those, 241 participants completed our survey. There was no knowledge difference between arms (mean difference = 0.56 (95 %CI: -3.8, 4.9)). Both groups had a considerable number of participants with misunderstandings. We also found no difference for decisional support (mean difference = 1.5 (95 %CI: -1.8, 4.8)) or enrollment rate between arms. Clinician use of the intervention varied between sites. CONCLUSIONS: We found no differences in outcomes but demonstrated the feasibility and acceptability of incorporating a shared decision-making intervention into consent. PRACTICE IMPLICATIONS: Future work should consider adapting our intervention to other trials and more robust measurement strategies.

Technology-Enabled Health Care Collaboration in Pediatric Chronic Illness: Pre-Post Interventional Study for Feasibility, Acceptability, and Clinical Impact of an Electronic Health Record-Linked Platform for Patient-Clinician Partnership.

BACKGROUND: Mobile health (mHealth) technology has the potential to support the Chronic Care Model's vision of closed feedback loops and patient-clinician partnerships. OBJECTIVE: This study aims to evaluate the feasibility, acceptability, and short-term impact of an electronic health record-linked mHealth platform (Orchestra) supporting patient and clinician collaboration through real-time, bidirectional data sharing. METHODS: We conducted a 6-month prospective, pre-post, proof-of-concept study of Orchestra among patients and parents in the Cincinnati Children's Hospital inflammatory bowel disease (IBD) and cystic fibrosis (CF) clinics. Participants and clinicians used Orchestra during and between visits to complete and view patient-reported outcome (PRO) measures and previsit plans. Surveys completed at baseline and at 3- and 6-month follow-up visits plus data from the platform were used to assess outcomes including PRO completion rates, weekly platform use, disease self-efficacy, and impact on care. Analyses included descriptive statistics; pre-post comparisons; Pearson correlations; and, if applicable, effect sizes. RESULTS: We enrolled 92 participants (CF: n=52 and IBD: n=40), and 73% (67/92) completed the study. Average PRO completion was 61%, and average weekly platform use was 80%. Participants reported improvement in self-efficacy from baseline to 6 months (7.90 to 8.44; P=.006). At 6 months, most participants reported that the platform was useful (36/40, 90%) and had a positive impact on their care, including improved visit quality (33/40, 83%), visit collaboration (35/40, 88%), and visit preparation (31/40, 78%). PRO completion was positively associated with multiple indicators of care impact at 3 and 6 months. CONCLUSIONS: Use of an mHealth tool to support closed feedback loops through real-time data sharing and patient-clinician collaboration is feasible and shows indications of acceptability and promise as a strategy for improving pediatric chronic illness management.

Development and evaluation of an EHR-based computable phenotype for identification of pediatric Crohn's disease patients in a National Pediatric Learning Health System.

OBJECTIVES: To develop and evaluate the classification accuracy of a computable phenotype for pediatric Crohn's disease using electronic health record data from PEDSnet, a large, multi-institutional research network and Learning Health System. STUDY DESIGN: Using clinician and informatician input, algorithms were developed using combinations of diagnostic and medication data drawn from the PEDSnet clinical dataset which is comprised of 5.6 million children from eight U.S. academic children's health systems. Six test algorithms (four cases, two non-cases) that combined use of specific medications for Crohn's disease plus the presence of Crohn's diagnosis were initially tested against the entire PEDSnet dataset. From these, three were selected for performance assessment using manual chart review (primary case algorithm, n = 360, primary non-case algorithm, n = 360, and alternative case algorithm, n = 80). Non-cases were patients having gastrointestinal diagnoses other than inflammatory bowel disease. Sensitivity, specificity, and positive predictive value (PPV) were assessed for the primary case and primary non-case algorithms. RESULTS: Of the six algorithms tested, the least restrictive algorithm requiring just ≥1 Crohn's diagnosis code yielded 11 950 cases across PEDSnet (prevalence 21/10 000). The most restrictive algorithm requiring ≥3 Crohn's disease diagnoses plus at least one medication yielded 7868 patients (prevalence 14/10 000). The most restrictive algorithm had the highest PPV (95%) and high sensitivity (91%) and specificity (94%). False positives were due primarily to a diagnosis reversal (from Crohn's disease to ulcerative colitis) or having a diagnosis of "indeterminate colitis." False negatives were rare. CONCLUSIONS: Using diagnosis codes and medications available from PEDSnet, we developed a computable phenotype for pediatric Crohn's disease that had high specificity, sensitivity and predictive value. This process will be of use for developing computable phenotypes for other pediatric diseases, to facilitate cohort identification for retrospective and prospective studies, and to optimize clinical care through the PEDSnet Learning Health System.

Networked health care: Rethinking value creation in learning health care systems.

Creating better value in health care service today is very challenging. The social pressure to do so is real for every health care system and its leadership. Real benefit has been achieved in manufacturing sector work by the use of "value-chain" thinking, which assumes that the work is a series of linked processes necessary to make a product. For those activities in health care systems that are similar, this model may be very helpful. Attempts to "install" the value chain widely in health care systems have, however, been frustrating. As a result, well-meaning leaders seeking better value have resorted to programs of cost reduction, rather than service redesign. Professionals have not been very happy or willing participants. The work of health care service invites an expanded model of value creation, one that better matches the work. This paper proposes a networked architecture that can mobilize and integrate the resources of health care professionals, interested patients, family, and other community members in the delivery and improvement of health care systems. It also suggests how this value-creation architecture might contribute to research and the development of new knowledge. Two cases illustrate the proposed architecture and its implications for system design and practice, technology development, and roles and responsibilities of all actors involved in health care systems. We believe that this model better fits the need of making and improving health care services. This expanded understanding of how value is created invites attention by senior leaders, by those attempting to facilitate the improvement of current systems, by patients and clinicians involved in the daily work of health care service coproduction, by those charged with the preparation and formation of future professionals, by those who measure and conduct research in health care services, and by those leading policy, payment, and reimbursement systems.