Redesigning Diabetes Care for Treatment Inertia: A Population Health Model

Abstract

In the past 2 decades, health care has witnessed technological and pharmacological advancements leading to innovations in diabetes management. Despite these advances, published guidelines, and treatment algorithms, most people with diabetes remain above glycemic targets. Thus, the authors designed a novel care model aimed at improving several causative factors, including therapeutic inertia, limited access to endocrinology and cardiovascular specialists, time constraints, and complexity in incorporating clinical practice guidelines. The model involves collaboration between the diabetes specialty team and primary care providers (PCPs). The intervention reviewed uncontrolled diabetes data and the patient's electronic medical record (EMR) and sent personalized, evidence-based recommendations to the provider using the task function in the EMR. Other services (eg, diabetes education) were utilized to optimize patient care to achieve optimal glycemic targets and address cardiometabolic risk. The overall mean hemoglobin A1c (HbA1c) decreased pre-post intervention by almost 1%, and 52.1% (347 of 666) of the cohort had ≥−0.5% change in HbA1c post-intervention. All pathways exhibited a decrease in HbA1c. Team-based approaches to managing diabetes patient care were the most effective. The interventions effectively utilized the resources across the health system without placing additional load or burden on primary care or diabetes specialty care teams. In the future, the authors hope to address the limitations of the current gap caused by increasing diabetes numbers, decreasing availability of PCPs and endocrinologists, and fee-for-service models using the innovative specialty consultant–primary care connection and knowledge exchange offered by this novel model, which can only be sustained with payer's support.

Introduction

Over the past decade, less than 1-quarter of people with type 1 diabetes¹ and less than half of people with type 2 diabetes² (collectively called people with diabetes or PWD) met the American Diabetes Association's standard of care goal for hemoglobin A1c (HbA1c) of <7.0%.³ Pharmacotherapy to meet optimal glycemic targets earlier during the disease trajectory is associated with a lower HbA1c for a longer duration and reduced microvascular and macrovascular complications.⁴ Despite an improved understanding of the disease state, vast screening initiatives for complications, and pharmacological and technological advances, significant gaps remain in delivering effective diabetes care to optimize self-management outcomes.

A critical factor contributing to suboptimal outcomes is therapeutic inertia—the underuse of effective diabetes therapies.⁵ In 2020, the American Diabetes Association released its 3-year plan to address inertia. They highlighted the critical need to optimize clinic processes and workflows to more efficiently achieve optimal glycemic targets.⁶ Barriers such as time constraints, competing demands, lack of knowledge, confusion with current guidelines, and lack of experience all contribute to therapeutic inertia.⁷ Therapeutic inertia exists in both primary care and diabetes specialty services.

Up to 82% −90% of PWDs are treated for diabetes in primary care practices due to socioeconomic deprivation or inaccessibility to diabetes specialty care.^8,9 One challenge is having <6500 adult-care practicing endocrinologists in the United States.¹⁰ This number pales given the estimated 37.1 million PWD, 18 years or older, in 2019.¹¹ In more alarming terms, the approximate ratio of PWD to endocrinologists is 46,000 to 1, which is an impossible need to meet. Moreover, researchers expect a further decline in full-time adult endocrinologists through 2025 in the United States.⁸

When diabetes specialty care can be accessed, the main reasons for referral by primary care providers (PCP) are difficulty with insulin therapy or diabetes technology rather than the inability to optimize glycemic outcomes.¹² Yet, patients referred for diabetes specialty care are more likely to achieve an HbA1c <7.0% and start new medication classes earlier than those managed in primary care.¹³ In addition, diabetes care by an endocrinologist is associated with lower morbidity rates and health care costs, and fewer readmissions.¹⁴ Thus, the dilemma of benefits yet shortage of endocrinologists creates an imperative to find ways of partnering diabetes care specialists with PCPs.

The authors theorized that using a comprehensive care model in primary care may deliver more thorough diabetes care and reduce therapeutic inertia. These models provide coordinated, consistent, team-based health care to PWDs with an increased risk of hospitalization, such as those with elevated HbA1c. Scripps Health System integrated a multidisciplinary diabetes care team in a primary care setting and improved glycemic control and diabetes self-management, and decreased medical costs.¹⁵

Integrating such a model in primary care in the author's health system required a redesign of the processes and workflows that deliver diabetes care. Therefore, the specific aims of this study were to:

Design and implement a novel diabetes care model to address clinician-level therapeutic inertia barriers, such as time constraints, limited access to specialists, and lag in use of updated clinical guidelines in clinical practice.

Improve HbA1c outcomes.

Improve the use of appropriate diabetes therapies recommended by the American Diabetes Association Standards of Care,³ and of resources in team-based care pathways.

The purpose of this article is to describe the innovative care model implemented in University Hospitals (UH) and report the pre- and post-intervention results.

Methods

The UH institutional review board reviewed the study protocol and deemed it non-human subjects research and exempt from further review.

Study design and setting

This prospective quality improvement evaluation was conducted at UH in Cleveland, a large Northeast Ohio health system. It has a Population Health Service Organization under the Accountable Care Organization (ACO) committed to the quality of care for the health system and ∼25,000 employees and dependents enrolled in a UH health plan. The UH Primary Care Institute is also under the ACO and supports an integrated network of <200 primary care practices located across 16 counties in northern Ohio.

The study team identified a cohort of people with diabetes from the UH employee health plan who were ≥18 years of age with an HbA1c >8.5%. The inclusion criteria were applied to a customized population health database for the ACO to find eligible employee health plan members. The database integrates data from patient electronic medical records (EMR) and scheduling and financial systems. The study team chose this population because of their commitment to improve UH employees' and dependents' health and wellness.

The Diabetes System of Excellence program (DSE) was developed in April 2021 and implemented in June 2021 and a pre-post evaluation done with no control group comparison.

Intervention: Diabetes System of Excellence Program

The goal of the DSE program was to optimize disease management by collaborating with PCPs and cardiovascular specialists and facilitating the use of evidence-based treatments. A diabetes specialty team (DST) led collaborations with PCPs. The DST comprised endocrine providers (B.H. and J.T.F.), certified diabetes care and education specialists (CDCES), and registered dietitians (RD).

The DST obtained written permission from the Primary Care Institute chair and PCPs to review patient charts and return recommendations via tasks or messages in the EMR. When employees enroll in a UH health plan, they sign an agreement allowing access to their EMR to recommend care. Cases were reviewed thrice weekly, individually by DST members to analyze each clinical profile and then as a team to formulate personalized, evidence-based recommendations and suggestions for team-based care services/pathways, as needed.

Initially, when the review process was new to the team and members were learning to work together, it took 10–15 minutes per patient. After 1 month, the review time decreased closer to 5 minutes.

The primary care-only group included the PWDs who only needed a simple medication prescription change or adjustment of a dose (Table 1), which was then performed by the individual's PCP. However, if a PWD clinically required more than just an adjustment of or addition of a medication, depending on their need, 1 or more team-based services/pathways were suggested to their PCP.

Table 1.

Team-Based Care Services/Pathways

Services received (N = 666)	n (%)	Description	Example of case
PCP Only	124 (18.6%)	DST recommended simple, appropriate medication prescription changes or dose adjustment to the PCP.	PWD needed only adjustment of medications or change in treatment modality
Multiprogram	142 (21.3%)	Recommended 2 or more services/pathways offered in the DSE program to thoroughly address the patient's needs.	PWD needed CDCES and endocrinology consult due to complex insulin therapy adjustment
Navigator	106 (15.9%)	Care coordinator program with resource services (eg, getting lost-to-follow-up patients scheduled, offering scheduling or Milestones program enrollment).	PWD with socioeconomic burden that was a barrier to care
CINEMA	30 (4.5%)	Individuals with type 2 diabetes and a high risk for cardiovascular events are referred to a multidisciplinary preventative cardiometabolic program.	PWD with high cardiometabolic risk to optimize care and reduce risk for cardiovascular disease
ACCENT/Complex Care	3 (0.5%)	Complex patients who need psychiatry resources. ACCENT/Complex Care program is for individuals currently experiencing acute mental health crises who need intensive outpatient treatment and resources.	PWD needing psychosocial support in addition to insulin management
Milestones	81 (12.2%)	Diabetes care and education program for individuals on the employee health plan, which includes a visit with an endocrine APP, population health APP and RD, and CDCES.	Any PWD under the employee health plan with elevated HbA1c
Pharmacy	61 (9.2%)	Ambulatory care pharmacist phone call or telehealth visit for medication affordability, access, or compliance and medication optimization.	PWD with a compliance challenge
CDCES	15 (2.4%)	CDCES provides DSMES education following the ADCES7 Curriculum.¹⁶	PWD without diabetes self-management documentation within the past 3 years
Endocrine	103 (15.5%)	Endocrine specialist to initiate new diabetes therapy or technology or make significant adjustments to diabetes therapy.	PWD with maximized medication and requiring insulin initiation or adjustment or technology use

APP, advanced practice provider; CDCES, certified diabetes care and education specialist; CINEMA, Center for Integrated and Novel Approaches in Vascular-Metabolic Disease; DSE, Diabetes System of Excellence program; DSMES, diabetes self-management education and support; DST, diabetes specialty team; HbA1c, hemoglobin A1c; PCP, Primary Care Provider; PWD, people with diabetes; RD, registered dietician.

In collaboration with the PCP, these services/pathways were then facilitated by the DST. Table 1 describes the team-based care services/pathways used to optimize the care and needs of PWD and includes a case example. Pathways consisted of multidisciplinary health care team members that aided in diabetes self-management or addressed barriers to care.

For example, assistance addressing medication obstacles or additional support services such as behavioral or preventative cardiology. Pathways covered specialty services in addition to endocrinology, such as care coordination (Navigator), additional diabetes education (Milestones, CDCES), assistance in addressing medication barriers (Pharmacy), preventing cardiovascular events (Center for Integrated and Novel Approaches in Vascular-Metabolic Disease, CINEMA), and behavioral support in addition to diabetes management (Complex Care/ACCENT). In some cases, individuals were referred to multiple team-based care pathways, categorized as a multiprogram.

Data collection and variables

Patient data were collected every 6 months over an 18-month period post-program initiation (June 2021 to December 2022). All data were collected from the population health database and EMR. Baseline data were collected from the month before the PWD's case review and included diabetes diagnosis (type 1, type 2, not specified) and demographics. Demographics included age in years, gender assigned at birth, race and ethnicity, and diabetes diagnosis (type 1, type 2, not specified).

Demographics were self-reported, and race categories include American Indian, Asian, Black, other, patient declined, unknown, and White. Ethnicity categories included Hispanic, not Hispanic, missing, and no answer. The primary outcome was HbA1c with a 0.5% decrease from the pre- to post-intervention period considered clinically significant. Secondary outcomes included systolic and diastolic blood pressure, body mass index, lipid panel values (triglyceride, high-density lipoprotein, low-density lipoprotein), and number of new diabetes medications started per team-based pathway group.

Data analysis

A pre-post evaluation was conducted to determine the impact of the intervention on patient outcomes, PCPs referring PWDs to team-based care services/pathways (Table 1), and prescription of new, appropriate diabetes medications. Appropriate medication was defined as those that target “intended treatment goals”³ such as SGLT2 agents, GLT1 agents, medications to reduce cardiovascular and renal disease risk, or starting insulin to achieve glucose control.

All cases with pre-HbA1c data and at least 3 months of post-HbA1c data were included in this analysis. Type 1 and type 2 data within pathways were merged due to small sample sizes to analyze the effect of the intervention on HbA1c levels. For example, Cinema had 29 T2D cases and 1 unspecified case. Descriptive statistics including frequency, percentage, mean, range, standard deviation (SD), and confidence interval (95% CI) are reported. Missing data were handled pairwise. Paired-samples t tests were used to analyze comparisons and answer the following research questions:

RQ1. What is the frequency of PCPs referring PWDs to team-based care services/pathways?

RQ2. Is there a difference in the mean HbA1c level pre- versus post-implementation of the DSE program?

RQ3. Does implementing a partnership between primary care and diabetes specialty care increase the quantity of new appropriate diabetes medication prescriptions?

Alpha was set at <0.05 and SPSS Version 28 (IBM Corporation) used for all analyses. Due to small sample sizes, the new medications started were reported using descriptive statistics (frequencies) only.

Results

A total of 683 charts were identified and 17 cases managed under pediatric endocrinology were excluded, yielding 666 charts included in the quality improvement evaluation. At baseline, overall mean (SD) age was 54.6 (11.6) years and mean HbA1c level was 9.5% (1.6) (Table 2). Of 666 PWDs, 347 (52.1%) had a clinically significant change of ≥−0.5% in HbA1c post-intervention. Most PWDs self-reported as White (n = 416, 62.5%) or Black (n = 179, 26.9%), non-Hispanic (n = 599, 89.9%), and female gender assigned at birth (n = 354, 53.2%) (Table 3).

Table 2.

Baseline Clinical Characteristics

Characteristics ^a	Mean (SD)
Age in years (N = 666)	54.6 (11.6)
HbA1c, % (N = 666)	9.5 (1.6)
Systolic blood pressure, mm Hg (N = 661)	131.9 (16.6)
Diastolic blood pressure, mm Hg (N = 660)	79.1 (9.9)
Body mass index, kg/m² (N = 660)	34.9 (7.7)
Triglycerides, mg/dL (N = 630)	185.7 (158.7)
High-density lipoprotein cholesterol, mg/dL (N = 634)	44.4 (12.7)
Low-density lipoprotein cholesterol, mg/dL (N = 619)	94.7 (38.4)

Total sample size was 666; sample size reported for each characteristic to show missing data.

HbA1c, hemoglobin A1c; SD, standard deviation.

Table 3.

Demographics and Diabetes Diagnosis Compared by Team-based Care Pathways

	PCP (n = 124)	Multi (n = 142)	Nav (n = 106)	CINEMA (n = 30)	Accent ^a (n = 3)	Miles (n = 81)	Pharm (n = 61)	CDCES ^a (n = 16)	Endo (n = 103)	Total (N = 666)
Race, n (%)
American Indian	0 (0.0)	2 (1.4)	1 (0.9)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	3 (0.5)
Asian	0 (0.0)	1 (0.7)	2 (1.9)	0 (0.0)	0 (0.0)	2 (2.5)	2 (3.3)	1 (6.2)	2 (1.9)	10 (1.5)
Black	29 (23.4)	41 (28.9)	31 (29.2)	7 (23.3)	2 (66.7)	22 (27.2)	12 (19.7)	5 (31.2)	30 (29.1)	179 (26.9)
Other	6 (4.8)	6 (4.2)	3 (2.8)	0 (0.0)	1 (33.3)	2 (2.5)	0 (0.0)	1 (6.2)	2 (1.9)	21 (3.2)
Pt Declined	3 (2.4)	7 (4.9)	2 (1.9)	0 (0.0)	0 (0.0)	2 (2.5)	2 (3.3)	0 (0.0)	4 (3.9)	20 (3.0)
Unknown	2 (1.6)	6 (4.2)	4 (3.8)	0 (0.0)	0 (0.0)	1 (1.2)	1 (1.6)	0 (0.0)	3 (2.9)	17 (2.6)
White	84 (67.7)	79 (55.6)	63 (59.4)	23 (76.7)	0 (0.0)	52 (64.2)	44 (72.1)	9 (56.2)	62 (62.0)	416 (62.5)
Ethnicity, n (%)
Hispanic	2 (1.6)	8 (5.6)	3 (2.8)	1 (3.3)	0 (0.0)	2 (2.5)	0 (0.0)	1 (6.2)	1 (1.0)	18 (2.7)
Missing	2 (1.6)	2 (1.4)	2 (1.9)	0 (0.0)	0 (0.0)	1 (1.2)	0 (0.0)	0 (0.0)	2 (1.9)	9 (1.4)
No Answer	9 (7.3)	11 (7.7)	8 (7.5)	0 (0.0)	0 (0.0)	5 (6.2)	1 (1.6)	0 (0.0)	6 (5.8)	40 (6.0)
Not Hispanic	111 (89.5)	121 (85.2)	93 (87.7)	29 (96.7)	3 (100.0)	73 (90.1)	60 (98.4)	15 (93.8)	94 (91.3)	599 (89.9)
Gender, n (%)
Female	62 (50.0)	78 (54.9)	67 (63.2)	10 (33.3)	2 (66.7)	40 (49.4)	33 (54.1)	9 (56.2)	53 (51.5)	354 (53.2)
Male	62 (50.0)	64 (45.1)	39 (36.8)	20 (66.7)	1 (33.3)	41 (50.6)	28 (45.9)	7 (43.8)	49 (47.6)	311 (46.7)
Other	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	1 (1.0)	1 (0.2)
Diabetes type, n (%)
Type 1	14 (11.3)	15 (10.6)	10 (9.4)	0 (0.0)	1 (33.3)	0 (0.0)	0 (0.0)	6 (37.5)	35 (34.0)	81 (12.2)
Type 2	109 (87.9)	125 (88.0)	94 (88.7)	29 (96.7)	2 (66.7)	79 (97.5)	60 (98.4)	10 (62.5)	68 (66.0)	576 (86.5)
Not specified	1 (0.8)	2 (1.4)	2 (1.9)	1 (3.3)	0 (0.0)	2 (2.5)	1 (1.6)	0 (0.0)	0 (0.0)	9 (1.4)

Provided for descriptive purposes only. Excluded in additional data analysis (Table 4) due to small sample sizes.

CDCES, Certified diabetes care and education specialist; Endo, Endocrine; Miles, Milestones; Multi, Multiprogram; Nav, Navigator; PCP, primary care provider; Pharm, Pharmacy.

Table 4.

Comparison of Pre- and Post-Intervention HbA1c Levels by Diabetes Type and Pathway

	N	Pre-HbA1c, mean (SD)	Post-HbA1c, mean (SD)	Mean difference (95% CI)	P
Diabetes type^a
Overall (t = 12.544, df = 665)	666	9.52 (1.63)	8.57 (1.84)	−0.94 (−1.09 to −0.80)	<0.001
T1D (t = −1.48, df = 80)	81	9.40 (1.8)	9.16 (1.62)	−0.24 (−0.55 to 0.08)	0.142
T2D (t = −12.78, df = 575)	576	9.53 (1.6)	8.48 (1.88)	−1.05 (−1.21 to −0.89)	<0.001
Pathway programs^b
Endocrine (t = −3.88, df = 102)	103	9.15 (1.5)	8.40 (1.66)	−0.75 (−1.14 to −0.37)	<0.001
Multiprogram (t = −5.70, df = 141)	142	9.94 (1.61)	9.07 (1.90)	−0.87 (−1.18 to −0.57)	<0.001
Navigator (t = −3.61, df = 105)	106	9.37 (1.25)	8.73 (1.56)	−0.65 (−1.00 to −0.29)	<0.001
Pharmacy (t = −5.35, df = 60)	61	9.18 (1.06)	8.23 (1.46)	−0.96 (−1.31 to −0.60)	<0.001
Milestones (t = −6.02, df = 80)	81	10.5 (1.85)	8.98 (2.2)	−1.53 (−2.03 to −1.02)	<0.001
CINEMA (t = −3.66, df = 29)	30	9.36 (1.12)	8.22 (2.1)	−1.14 (−1.78 to −0.50)	0.001
PCP (t = −5.21, df = 123)	124	9.05 (1.89)	8.04 (1.76)	−1.00 (−1.39 to −0.62)	<0.001

Nine patients were missing diabetes type; group mean pre-HbA1c was 9.81% (SD 1.6), and mean post-HbA1c was 9.13% (SD 2.44).

Small samples sizes excluded accent (n = 3) and certified diabetes care and education specialist (n = 15) from the analysis.

Paired-samples t Test compared pre–post-intervention data for all pathway programs.

The pathways were not analyzed by diabetes type due to small sample sizes by diabetes type for multiprogram (n = 15), navigator (n = 10), and PCP (n = 14).

CI, confidence interval; HbA1c, hemoglobin A1c; PCP, primary care provider; SD, standard deviation.

RQ1. What is the frequency of PCP referring PWDs to team-based care pathways?

Of 666 participants, 124 (18.6%) were in the PCP-only service/pathway (Table 1). The most common referral was Multiprogram (n = 142, 21.3%) followed by Navigator (n = 105, 15.9%), and Endocrine (n = 103, 15.5%) to optimize medical therapy or diabetes technology that could not be implemented by the PCP (Table 1).

RQ2. Is there a difference in the mean HbA1c pre- versus post-implementation of the DSE program?

The overall mean HbA1c decreased pre–post-intervention by 0.94% (95% CI, −1.09 to −0.80), and the mean difference for the T2D group decreased by 1.05% (95% CI, −1.21 to −0.89) (Table 4). All pathways achieved a statistically significant decrease in HbA1c from pre- to post-program. The Milestones pathway had the largest decrease in HbA1c of 1.53% (95% CI, −2.04 to −1.02) followed by CINEMA with 1.14% (95% CI, −1.78 to −0.50), and PCP with 1.00% (95% CI, −1.39 to −0.62).

RQ3. Does implementing a partnership between primary care and diabetes specialty care increase the quantity of new appropriate diabetes medication prescriptions?

Almost half of the study sample (301 of 666, 45.2%) started ≥1 new medication (Table 5). Fifty percent (62 of 124) of PWDs in the PCP-only care pathway started ≥1 new, appropriate diabetes medication, such as a GLP-1 receptor agonist or SGLT2 inhibitor, whereas 39.8% (41 of 103 PWDs) in the endocrine pathway started ≥1 new medication. Primary care had the highest percentage of ≥1 new diabetes medication started, followed by the multiprogram pathway (43.7%, 62 of 142 PWDs). In the PCP pathway, 5 PWDs were started on 3 new medications and 12 patients were started on 2 new medications.

Table 5.

Number of New Diabetes Medications by Team-based Care Program

	Total PWD N = 666	No new diabetes medication started N = 365 (54.8)	No. of new diabetes medications (n = 301)
	Total PWD N = 666	No new diabetes medication started N = 365 (54.8)	1 N = 226 (33.9)	2 N = 59 (8.9)	≥3 ^a N = 16 (2.4)
Accent	3 (0.5)	1 (0.3)	2 (0.9)	0	0 (0.0)
CDCES	16 (2.4)	10 (2.7)	4 (1.8)	2 (3.4)	0 (0.0)
CINEMA	30 (4.5)	15 (4.1)	11 (4.9)	2 (3.4)	2 (12.5)
Endo	103 (15.5)	62 (17.0)	34 (15.0)	4 (6.8)	3 (18.8)
Milestones	81 (12.2)	40 (11.0)	31 (13.7)	7 (11.9)	3 (18.8)
Multi	142 (21.3)	80 (21.9)	44 (19.5)	16 (27.1)	2 (12.5)
Navigator	106 (15.9)	58 (15.9)	33 (14.6)	15 (25.4)	0 (0.0)
PCP	124 (18.6)	62 (17.0)	45 (19.9)	12 (20.3)	5 (31.1)
Pharmacy	61 (9.2)	37 (10.1)	22 (9.7)	1 (1.7)	1 (6.3)

Of the 16 PWDs, 2 were prescribed 4 new diabetes medications and 14 were prescribed 3 new diabetes medications.

Data reported are numbers with percentages in parentheses.

CDCES, Certified diabetes care and education specialist; Endo, Endocrine; Multi, Multiprogram; PCP, primary care provider; PWD, people with diabetes.

Discussion

This quality improvement initiative implemented a novel team-based diabetes program to address therapeutic inertia and expand the reach of diabetes specialists to a larger population of adults with suboptimal glycemic outcomes. The DSE program reached 666 PWDs from the health system's employee health plan, assessed changes in HbA1c, and found that 52.1% of the cohort had a clinically significant change of ≥−0.5% post-intervention.

Not only was this decrease achieved, but it was exceeded and statistically significant for the overall sample (mean −0.94%) and the T2D group (mean −1.05%). The most common services/pathways recommended were multiprogram (21.3%), followed by navigator (15.9%), and endocrine specialty care (15.5%). The authors observed statistically and clinically significantly lower HbA1c in each group, described in Table 1, post-intervention. Almost half of the total sample started new diabetes medications. As expected, PWDs in the primary care-only group had a higher percentage of new diabetes medications started post-intervention compared with the other care groups.

The study findings highlight the importance of integrating primary care and diabetes specialty care to proactively address therapeutic inertia and achieve optimal clinical outcomes. An important component of the DSE model was approaching PCPs and offering clinical recommendations for PWDs with elevated HbA1c. This process change removed the time spent waiting for a specialist consult or service request and appointment, which is important given the shortage of endocrinologists and long appointment wait times.⁸

In addition, the DSE program utilized health system-wide resources without increasing the burden on primary care or diabetes specialty care teams. The concise and simplified patient-centric recommendations were well received by busy PCPs. For example, 1 recommendation to the PCP was to initiate the glucagon-like peptide 1 agonist and reduce basal insulin by 10%.

This was sent as a task in the provider messaging system. When services/pathways were recommended and agreed upon by the PCP, the DST directly facilitated the connection between the PWD and the services/pathways, simplifying the process and minimizing wait time for the care delivery.

Another benefit of the DSE program was the population-based approach to endocrinology services. This approach is vital to help address the prevalence of people with elevated HbA1c in the United States.^1,2 One study found that patients with T2D who are seen by an endocrinologist are more likely to achieve HbA1c <7.0% and start new medication classes earlier than in primary care.¹³

In the DSE program, an endocrine provider led the DST, reviewing all the cases and recommending evidence-based treatments and other services/pathways to PCPs. All of the pathway groups that were adequately powered for statistical analysis (n ≥ 30) achieved statistically and clinically significant decreases in HbA1c.

Previous efforts have implemented team-based approaches to manage diabetes via telehealth¹⁶ and one-on-one appointments with various health care professionals (eg, CDCES, nurse, PharmD, psychologist).¹² In contrast, the DSE program omitted the single patient encounter, leveraging the expertise and leadership of the DST to review cases, avoiding multiple one-on-one clinic visits. The workflow was more efficient, and diabetes specialty expertise was applied to a larger patient population. Almost half of the study sample started at least 1 new, appropriate diabetes medication, with 1-quarter of those prescribed at least 2 new medications.

The team-based pathways in the DSE program corroborate the benefits reported in other studies.¹⁷ Multiple analyses have found that empowering nonphysician providers can effectively address inertia.^5,7 The current intervention used physician and nonphysician providers to deliver evidence-based care. Care coordinators (Navigators) helped PWDs with social barriers, and CDCESs/RD delivered diabetes-related patient-centered education.

In addition, the DST initiated new therapies and technologies and adjusted suboptimal therapies, whereas pharmacists managed medication taking barriers and access. Thus, the DSE program provided comprehensive care for the PWD, which meant addressing all determinants of health to deliver successful diabetes care.

This study has several limitations. First, some 3-month HbA1c data were missing owing to the increased use of virtual care services during the COVID-19 pandemic and fewer in-person visits. This led to a different time frame for pre-and post-HbA1c measurements, but we indicated the mean pre-to-post length for data interpretation. Second, some of the team-based care pathways had small sample sizes and only descriptive statistics were reported. Nevertheless, these programs still had clinical significance and provided benefits to PWD. Third, this was a preliminary analysis. However, the authors plan to analyze longitudinal effectiveness, including additional metabolic outcome measures in the future.

Future Directions

The hope is to expand the reach of the DSE model by addressing the limitations of the current fee-for-service model. Fee-for-service reimburses the physician or specialist for their time per patient encounter using the relative value unit (RVU) calculation. There is no RVU for team-based care that involves multiple health care professionals and services.

A proposed new model would review patient cases without needing a fee-for-service package payment or multiple provider billing, which could change the reimbursement model. Such a model is needed to sustain a team-based diabetes care model, including the DSE program. The long-term outcomes of this intervention could help support changing reimbursement methods that can better address the complex diabetes needs of many PWD at a feasible cost.

Conclusions

The DSE is a novel team-based approach to diabetes management that addressed therapeutic inertia and optimized glycemic outcomes. A DST identified adult cases with HbA1c >8.5%, approached the PCPs, and after approval, reviewed the cases and made clinical recommendations and recommended services/pathways to improve social and clinical determinants of health. Importantly, the intervention leveraged health system-wide resources without increasing the patient load or burden for the primary care or diabetes specialty care teams.

Effective collaborations between primary and specialty care providers may be complex yet are key to delivering high-quality, patient-centered diabetes care, which addresses therapeutic inertia.¹⁸ Rather than support the status quo, it is time to innovate new models, and evaluate and broadly implement what works.

Footnotes

Acknowledgments

The authors thank Christine G. Holzmueller, MS for reviewing and editing the manuscript submitted to the journal.

Authors' Contributions

Ms. Fetzner: Validation (lead) and Investigation (lead)- nurse practitioner who performed clinical chart reviews for all identified patients and made recommendations for pathways, and writing—reviewing and editing (equal). Dr. Blanchette: Formal analysis (lead), writing—original draft (lead), writing—reviewing and editing (equal), and visualization (lead). Ozturk: Investigation-data collection (supporting) and writing—reviewing and editing (equal). Dr. Neeland: Resources—provision of patients (equal), and writing—review and editing (equal). Dr. Pronovost: Conceptualization (equal), methodology (equal), resources (equal), writing—review and editing (supporting), and supervision (equal). Dr. Hatipoglu: Conceptualization (lead), methodology (lead), validation (equal), formal analysis (equal), investigation (equal), resources (lead), data curation (lead), writing—original draft (equal), writing—reviewing and editing (lead), supervision (lead), and funding acquisition (lead).

Author Disclosure Statement

Blanchette reports receiving speaking fees from Insulet Corporation speaker's bureau, and consulting fees to serve on the advisory boards for Lifescan Diabetes and Cardinal Health. Neeland reports receiving consulting/speaking fees from Boehringer Ingelheim, Eli Lilly, Novo Nordis, Bayer Pharmaceuticals, Nestle Health Science, and AMRA Medical for various heart and vascular topics. Hatipoglu is a Principal Investigator for an insulin pump study funded by Tandem Diabetes Care, though it is unrelated to the work described in this paper. Fetzner, Ozturk, and Pronovost report no conflicts of interest to disclose.

Funding Information

Blanchette receives research support from the Leona M. and Harry B. Helmsley Charitable Trust (G-2305-05992). Hatipoglu has a Mary B. Lee Chair in Endocrinology, an internal award from University Hospitals that provides partial support for her endocrinology-related research.

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