face with patients and providers in the clinic setting. This multidisciplinary team also works to ensure that patients meet various quality measures; however, only select patients qualify for this service.
Pharmacists at WVUH MGP largely meet with patients remotely through telephone or video visits. This method allows more frequent contact with patients who live in rural parts of the state. With West Virginia being the center of the Appalachian region, it can be difficult for patients to be seen by their primary care doctor. Pharmacists help to bridge that gap and expand care in this region.
This retrospective cohort study is the first to analyze the impact of a CPA on multiple CMS quality measures specifically related to diabetes to highlight the potential financial and clinical benefit of a pharmacist. While data have been published describing the clinical impact of a pharmacist within various chronic disease states, there are limited data tying these impacts to quality measures. The goal of this study is to contribute to the existing body of literature showcasing the impact pharmacists have on clinical outcomes in an ambulatory setting.
METHODS
This single-center, retrospective cohort study analyzed patients at WVUH MGP, and it was approved by the West Virginia University Institutional Review Board. Data collection points were obtained through a custom EHR report that included patients with both type 1 and type 2 diabetes and those who were established with a primary care physician at WVUH MGP. Data for these patients were housed in a secure web application, and the data collection tool was password protected within the application. Patients aged 18 years of age and older who did not meet the quality measure HbA1c < 9 % in 2023 and / or those who had a HbA1c > 9 % from January to June 2024 were included in this study.
Patients who met inclusion criteria were separated into a pharmacist intervention group and physician-only( control) group. Patients were included in the pharmacist intervention group if they had at least two visits with a pharmacist in 2024. To be included in the control group, patients had to have at least two visits with their primary care physician in 2024. Patients were excluded if they were discharged from the practice prior to December 2024, deceased prior to December 2024, or re-established with a different primary care practice site during the study period.
The primary outcome was the percentage of patients meeting the quality measure C10: Diabetes Care— Blood Sugar Controlled defined as HbA1c < 9 % by December 2024. Secondary outcomes included other CMS quality measures for diabetes. Specific quality measures that were evaluated included C09: Diabetes Care— Eye Exam, and D12: Statin Use in Persons with Diabetes( SUPD). Exploratory outcomes included merit-based Incentive Payment System( MIPS) Measure # 488 Kidney Health Evaluation defined by an estimated glomerular filtration rate( eGFR) and a urine albumin-creatinine ratio( uACR). Additionally, the percentage of patients on an ACE / ARB if uACR was > 30 mg / g, and the differences in HbA1c and number of patient hospitalizations and emergency department( ED) visits during 2024 were also explored.
Baseline Characteristics
TABLE 1: Baseline Demographics
Pharmacist Intervention( n = 31)
Control( n = 94)
P value
Age – years 60.2 + 11.5 55.9 + 13.5 0.15
Male sex 18( 58.1) 50( 53.2) 0.68 Caucasian 25( 80.6) 83( 88.3) 0.36 Baseline HbA1c- % 10.8 + 1.8 10.4 + 1.5 0.37
Insurance type
• Medicare
• Medicaid
• Commercial
• None
15( 48.4) 8( 25.8) 8( 25.8) 0( 0)
35( 37.2) 17( 18.1) 40( 42.6) 2( 2.1)
0.29
Provider visits in 2024 15( 48.4) 3.7 + 2 0.30 Seen by endocrine 8( 25.8) 44( 46.8) 0.096 All data are reported as n(%) or mean + standard deviation unless otherwise specified
HbA1c: hemoglobin A1c
Descriptive statistics were used to summarize patient characteristics. Categorical variables were described using contingency tables with counts and percentages. Continuous variables were summarized using mean with standard deviation or median with range. Chi-square test or Fisher’ s exact test was used to assess the independence between two categorical variables, while two-sample t-test or Wilcoxon rank sum test was used to assess the difference on continuous variables. Statistical inferences were based on two-sided tests at a significance level of p < 0.05. A total of 125 patients provided at least 80 % power to detect the effect size of 0.55 difference on HbA1c between two groups with equal proportions using a two-sided, two-sample t-test at a significance level of 0.05. Statistical analyses were carried out using SAS 9.4( SAS Institute, Cary, North Carolina) and R( version 3.6.3, R Foundation, Vienna, Austria).
RESULTS
A total of 1,651 patients at WVUH MGP with diabetes were screened for inclusion. A total of 125 patients( 7.6 %) met inclusion criteria: 31 in the pharmacist intervention group and 94 in the control group. There were no statistically significant differences in baseline characteristics between the two groups( Table 1); however, 46.8 % of those in the control group were followed by endocrinology as opposed to 29 % in the pharmacist intervention group.
There was no statistically significant difference between the intervention and control groups in the primary outcome of patients achieving a HbA1c < 9 % by the end of the study period( 61.3 % vs 69.1 %, P = 0.51)
West Virginia Medical Journal • September 2026 • 13