Hunt, Vicki L.

AbstractThe Adult Medical Care Coordination program (“the program”) was implemented at Mayo Clinic to promote patient self‐management and improve 30‐day unplanned readmission for patients with high risk for readmission after hospital discharge. This study aimed to evaluate the impact of the program compared to usual care using a pragmatic, stepped wedge cluster randomized trial (“stepped wedge trial”). However, several challenges arose including large differences between the study arms. Our goal is to describe the challenges and present lessons learned on how to overcome such challenges and generate evidence to support practice decisions. We describe the challenges encountered during the trial, the approach to addressing these challenges, and lessons learned for other learning health system researchers facing similar challenges. The trial experienced several challenges in implementation including several clinics dropping from the study and care disruptions due to COVID‐19. Additionally, there were large differences in the patient population between the program and usual care arms. For example, the mean age was 76.8 for the program and 68.1 for usual care. Due to these differences, we adapted the methods using the propensity score matching approach that is traditionally applied to observational designs and adjusted for differences in observable characteristics. When conducting pragmatic research, researchers will encounter factors beyond their control that may introduce bias. The lessons learned include the need to weigh the tradeoffs of pragmatic design elements and the potential value of adaptive designs for pragmatic trials. Applying these lessons would promote the successful generation of evidence that informs practice decisions.

ABSTRACT Background and purpose: Diabetes mellitus is an epidemic. Many organizations and states have established reportable quality care measures. Our organization explored novel ways of chronic disease management. The purpose of this article is to decrease the percentage of patients with a hemoglobin A1c (HbA1c) more than 8%. Methods: Prospective, pre- and postintervention, quality improvement project was implemented in the Employee and Community Health Clinic using an endocrinology nurse practitioner (NP) to coordinate and provide care to adult patients with diabetes. A convenience sample of 103 patients with diabetes was selected for this project. Patients were excluded from the project if they did not complete preintervention satisfaction surveys or did not sign research release forms. Conclusions: One hundred three patients were referred, and two met exclusion criteria. Of those patients, 51% were female with an average HbA1c of 9.1%. Eighty-one of the referred patients attended their appointment. The patients who sought care had a reduction in HbA1c from 9.0% ± 1.8% to 8.3% ± 1.7% (p value < .001). Patients who did not appear had no significant change in their HbA1c from 9.8% ± 3.1% to 9.4% ± 2.7% (p value = .61). Implications for practice: Incorporating specialty trained NPs can lead to improvements in HbA1c, patient-reported control of diabetes, and a reduction in the frequency of hypoglycemia.

To be effective, nurse care coordination must be targeted at individuals who will use the service. The purpose of this study was to identify variables that predicted use of care coordination by primary care patients. Data on the potential predictor variables were obtained from patient interviews, the electronic health record, and an administrative database of 178 adults eligible for care coordination. Use of care coordination was obtained from an administrative database. A multivariable logistic regression model was developed using a bootstrap sampling approach. Variables predicting use of care coordination were dependence in both activities of daily living (ADL) and instrumental activities of daily living (IADL; odds ratio [OR] = 5.30, p = .002), independent for ADL but dependent for IADL (OR = 2.68, p = .01), and number of prescription medications (OR = 1.12, p = .002). Consideration of these variables may improve identification of patients to target for care coordination.