Baseline Quality Improvement Capacity of 33 Endocrinology Centers Participating in the T1D Exchange Quality Improvement Collaborative

The T1DX-QI was established in 2016 and has grown over time. The T1DX-QI coordinating office invited 10 centers participating in the T1D Exchange clinic registry to join the first T1DX-QI cohort, which focused its efforts on improving glycemic control among youth and young adults with type 1 diabetes who had the highest A1C values (9,20). With increasing interest resulting from T1DX-QI presentations at national and international diabetes conferences, a second cohort of 20 centers enrolled in 2018–2019, followed by a third cohort of 11 centers in 2021. At present, the T1DX-QI encompasses more than 40 pediatric and adult diabetes centers caring for >55,000 people with type 1 diabetes.

As centers join the T1DX-QI, they provide information about the demographics and clinical characteristics of their patient population along with information regarding their QI experience (14,16). Participating centers are required to have their own QI projects that can be either self-generated or inspired by change packages shared by other centers participating in the T1DX-QI. QI projects must focus on one or more of the T1DX-QI quality measures (Table 2). To support these projects, centers joining the T1DX-QI participate in monthly calls with an experienced QI coach provided by the T1DX-QI to focus on individual centers’ projects. The collaborative also hosts monthly webinars and two in-person multiday learning sessions per year to provide a venue for networking and sharing of ideas among centers. Outside of these opportunities, member centers also have access to a T1DX-QI group e-mail list, Cloud-based file-sharing capabilities, and a QI Portal to allow for asynchronous collaboration.

The T1DX-QI Clinical Leadership Committee sought to assess key components of QI culture among centers joining the collaborative. A thorough literature review identified the central pillars of successful QI efforts with the goal of using those key components to develop a questionnaire assessing the baseline capabilities of centers joining the collaborative.

Two reviewers searched for articles in PubMed using the terms “quality culture assessment tool” and “elements of health care quality culture.” More than 80,000 hits were returned, including three meta-analyses. Results were then filtered to identify the 24 articles focusing on health care and organizational quality culture that were reviewed.

Based on this literature review, four central pillars of successful QI efforts were identified: 1) QI team structure, 2) QI foundation, 3) QI capacity, and 4) QI success. Establishing QI teams with clearly defined roles and training them as a team rather than as individuals promotes ongoing involvement in impactful QI activities (21–24). QI foundation recognizes that achieving systemwide change requires establishing systemwide processes for the use of proven QI tools and data collection to support improvement efforts (22–25). QI capacity captures the use of QI tools, including Plan-Do-Study- Act (PDSA) cycles, run charts, and process mapping (21–23,26). Finally, QI successes are defined by a team’s ability to scale up small tests of change through stakeholder engagement, prior QI successes, and ongoing institutional investments in QI efforts (23–25). In addition to the 24 articles that were reviewed, several validated QI knowledge assessment tools were studied to guide the development of the self-assessment tool. These included the QI Knowledge Application Tool Revised; the Beliefs, Attitudes, Skills, and Confidence in QI instrument; the Assessment of Quality Improvement Knowledge and Skills; and the Mayo Evaluation of Reflection on Improvement Tool (27–31).

The four identified central pillars of successful QI efforts subsequently guided the development of a preliminary questionnaire. A group of 13 individuals, including principal investigators (PIs) from the T1DX-QI cohort 1 sites and two QI experts, refined the preliminary questionnaire using the Delphi method. The final, 20-question QI self-assessment tool captures information about the four central pillars of successful QI efforts (Supplementary Table S1). Question responses included “yes,” “no,” or “do not know,” with “yes” reflecting more robust QI culture in each domain. Questions focused on QI team composition, team member roles, institutional support and prioritization, ongoing data collection and monitoring, team member familiarity with QI tools and processes (e.g., PDSA cycles, run charts, and process mapping), and the team’s ability to scale up small tests of change through stakeholder engagement, prior QI experiences, and ongoing investment in QI efforts.

The QI self-assessment tool was distributed to site PIs upon joining the T1DX-QI. Each site PI answered on behalf of the entire team. Self-reported online survey answers were validated by a T1DX-QI coach using semistructured interviews with the QI team at each site conducted during a virtual meeting. The survey and data collection were managed using Qualtrics data management software.

Survey data were analyzed using RStudio software (www.rstudio.com). Survey responses of “do not know” were counted as “no.” Pairwise deletion was used for omitted questions. Scores on the self-assessment tool were collated according to the geographical location of the center within the United States, adult versus pediatric centers, T1DX-QI cohort, number of people with type 1 diabetes receiving care at each center, and prevalence of public insurance at each center. Spider/radar diagrams and Fisher exact tests were used to display and analyze the data according to geographical region.

This study was deemed exempt by the Western Institutional Review Board.

By the end of 2021, 33 of 41 participating T1DX-QI centers (81%) had completed the QI self-assessment survey. Overall, participating centers reflected an even distribution of center size, geographical region within the United States, and T1DX-QI cohorts (Table 3). Most centers (73%) were pediatric, and 45% of centers served populations in which 30–49% of patients with type 1 diabetes had public insurance. Overall, QI culture scores were high, as reflected by the following percentages of affirmative answers for each of the four domains of QI efforts: QI foundation 80%, QI team structure 79%, QI capacity 64%, and QI success 58% (Figure 1).

There were no significant differences in overall QI culture according to geographical region (P = 0.08) (Figure 2). QI team structure was highest in the Northeast (88%) and lowest in the West (55%) (P <0.01). QI capacity was highest in the Midwest (75%) and lowest in the South (49%) (P = 0.02). Despite challenges with QI team structure, QI successes were highest in the West (83%) and lowest in the South (45%) (P <0.01). There were no differences in QI foundation (P = 0.96) based on geographical region.

Figure 3 compares responses from pediatric versus adult centers. QI culture at pediatric centers was higher than at adults centers (P <0.001). Despite no significant differences between pediatric and adult centers in QI team structure and QI capacity, QI foundation (P <0.001) and QI success (P = 0.04) were greater at pediatric centers.

There were also differences in QI culture according to the T1DX-QI enrollment cohort (P <0.001) (Figure 4). The first cohort of the T1DX-QI, enrolled in 2016–2017, had the highest scores in QI foundation and capacity compared with the second (2019–2020) and third (2021) cohorts. There were no differences in QI success or team structure among the cohorts.

Despite vast differences in the number of people with type 1 diabetes seen at each given center (ranging from <125 to ≥250 per month), there were no significant differences in overall QI culture according to center size (P = 0.537) (Figure 5). Similarly, there were no overall differences in QI culture according to the percentage of publicly insured patients with type 1 diabetes (P = 0.17) (Figure 6). However, QI successes were higher in centers where ≥50% of patients with type 1 diabetes were publicly insured (P = 0.02).

The T1DX-QI LHS has grown tremendously over a short period of time, while simultaneously demonstrating many tangible improvements in care resulting from its QI efforts (10,13,15). Successful LHSs have demonstrated improvement in a number of health outcomes and health care efficiency, including reducing postoperative complications and improved remission rates among cancer patients (3). Understanding QI culture is crucial for an LHS to meet member centers where they are, build on existing capacity, and strive toward collective improvement. Despite the presence of LHSs in many areas of pediatrics and several international type 1 diabetes registries, this is the first report describing the characteristics of centers participating in a flourishing type 1 diabetes LHS in the United States. Similarly, there are limited publications describing the type 1 diabetes quality metrics that are outlined in Table 2; this publication provides insights into areas of focus and benchmarking for type 1 diabetes improvement programs.

Although centers participating in the T1DX-QI have strong QI cultures overall, those with less experience implementing QI methodology have joined the collaborative in subsequent cohorts. The initial recruitment of centers with greater QI capacity supported the development of a strong infrastructure, which has allowed for the subsequent addition of less experienced centers. Sites in cohorts 1 and 2 completed, on average, 2.1 and 1.6 QI projects, respectively, in their first 18 months of participation in the T1DX-QI. Although cohort 3 sites have been with the collaborative for <1 year, all of these sites are currently implementing one QI project at a time. The T1DX-QI has appropriately adjusted its QI coaching structure over the years to accommodate newer sites, including building out a formal QI introduction and orientation and offering T1DX-QI clinics access to the Institute for Healthcare Improvement Open School QI courses, an online platform to document and share PDSA cycles, and the T1DX-QI Portal. Cohort 1 sites participated in bimonthly intervention-specific QI check-in calls with clinics working on similar projects. Sites in cohorts 2 and 3 have since participated in one-on-one check-in calls with a T1DX-QI coach. Understanding the profiles of member centers and the characteristics of successful QI teams will allow for the recruitment of centers with characteristics not yet represented in the collaborative. The recruitment of representative type 1 diabetes care centers is essential for developing QI initiatives that are relevant and applicable to more people living with type 1 diabetes in the United States.

The results presented here invite future lines of inquiry regarding differences in centers’ QI capacity by the demographics explored here. Endocrinology care is concentrated in urban areas, and there are many parts of the West and Midwest regions in which there is no access to an endocrinologist within a 20- or even 50-mile radius (32–35). Furthermore, our data show that QI expertise is cloistered in certain geographical regions and that QI culture is better represented in pediatric versus adult type 1 diabetes care centers. This initial study does not explain the discrepancy between team structure and QI success in the West; it is possible that the small sample size (n = 4) played a role in that finding. Despite similar self-assessment reports of QI team structures between adult and pediatric populations, adult centers reported having lower levels of QI foundation, capacity, and success. The current T1DX-QI membership overrepresents pediatric centers (73%), particularly given that only about 12.5% of those individuals living with type 1 diabetes in the United States are <20 years of age (36). Centers with a high percentage of publicly insured patients reported higher rates of QI success, possibly related to higher baseline A1C values, allowing more opportunities for improvement; further study is needed to confirm this suspicion. Collectively, these data suggest the need for further resources to support QI efforts at adult type 1 diabetes care centers.

Type 1 diabetes centers in countries with national health systems often participate in benchmarking and collaborative data-sharing to support QI efforts (37). The German/Austrian Diabetes-Patienten-Verlaufsdokumentation registry, the National Health Service in England, and the Swedish National Diabetes Register capture data from the majority of people living with type 1 diabetes in their respective countries. These and many other European countries participate in national QI registries that have led to stable, if not improved, glycemia from 2011 to 2017, whereas A1C levels rose in the United States in the same time span (37–39).

Many of these transatlantic differences have been attributed to disparities in health care coverage, insurance coverage for diabetes technology, and high out-of-pocket costs in the United States (37). Because of these challenges, developing effective type 1 diabetes collaborative networks in countries with multipayer systems such as the United States has proven more difficult. The effects of systemic racism in the United States also require systematic approaches to improve type 1 diabetes care. T1DX-QI member centers with the greatest number of publicly insured patients reported the greatest QI successes, speaking to the need to continue to recruit centers providing care to underserved populations.

Strengths of this study include the receipt of survey responses from most sites participating in the T1DX-QI, the only LHS for type 1 diabetes in the United States. However, there are several limitations that must be acknowledged. Although the majority of T1DX-QI centers responded, it is possible there was a nonresponse bias. Additionally, participating centers are all academic institutions, so these results might not be generalizable to community centers or other diabetes/endocrinology centers outside of the T1DX-QI. Because survey responses were self-reported by site PIs, there is the potential for self-report bias. Interviews with a T1DX-QI coach and several members of each site’s QI team helped to mitigate this effect through the use of clarifying questions and sharing of additional details to validate the yes/no responses while also corroborating details. Although the QI self-assessment tool is not validated, its development was guided by a literature review with refinement by applying the Delphi method.

The T1DX-QI LHS has attracted participating centers from across the United States with varying levels of QI experience. The ongoing success of the collaborative as it grows and continues to expand membership to centers with less QI capacity speaks to the importance of supporting LHSs as drivers to improve clinical care and outcomes for people with type 1 diabetes. To improve care for all people with type 1 diabetes, it is imperative to increase the involvement of adult care centers, small- to medium-sized centers, and centers serving underserved, publicly insured people with type 1 diabetes. Data-sharing, benchmarking, and peer collaboration will drive the collection of data that can lead to policy change.

The authors thank the Leona M. and Harry B. Helmsley Charitable Trust for funding the T1DX-QI. The authors acknowledge the contributions of patients, families, diabetes care teams, and collaborators within the T1DX-QI who continually seek to improve care and outcomes for people with diabetes.

No potential conflicts of interest relevant to this article were reported.

B.E.M. wrote the manuscript. A.M. and O.E. analyzed data, contributed to the introduction and discussion, and reviewed and edited the manuscript. A.N., L.L., N.R., D.E., J.M.L., M.B., N.H.-J., E.M., G.O., M.W., D.S., G.A., and S.A. reviewed and edited the manuscript. O.E. conceptualized the manuscript. A.M. is the guarantor of this work and, as such, had access to all of the data and takes responsibility for the integrity of the data and the accuracy of the data analysis.