Evaluation of an Enhanced Primary Care Team Model to Improve Diabetes Care.

PURPOSE: Primary care practices manage most patients with diabetes and face considerable operational, regulatory, and reimbursement pressures to improve the quality of this care. The Enhanced Primary Care Diabetes (EPCD) model was developed to leverage the expertise of care team nurses and pharmacists to improve diabetes care. METHODS: Using a retrospective, interrupted-time series design, we evaluated the EPCD model's impact on D5, a publicly reported composite quality measure of diabetes care: glycemic control, blood pressure control, low-density lipoprotein control, tobacco abstinence, and aspirin use. We examined 32 primary care practices in an integrated health care system that cares for adults with diabetes; practices were categorized as staff clinician practices (having physicians and advanced practice providers) with access to EPCD (5,761 patients); resident physician practices with access to EPCD (1,887 patients); or staff clinician practices without access to EPCD (10,079 patients). The primary outcome was the percentage of patients meeting the D5 measure, compared between a 7-month preimplementation period and a 10-month postimplementation period. RESULTS: After EPCD implementation, staff clinician practices had a significant improvement in the percentage of patients meeting the D5 composite quality indicator (change in incident rate ratio from 0.995 to 1.005; P = .01). Trends in D5 attainment did not change significantly among the resident physician practices with access to EPCD (P = .14) and worsened among the staff clinician practices without access to EPCD (change in incident rate ratio from 1.001 to 0.994; P = .05). CONCLUSIONS: Implementation of the EPCD team model was associated with an improvement in diabetes care quality in the staff clinician group having access to this model. Further study of proactive, multidisciplinary chronic disease management led by care team nurses and integrating clinical pharmacists is warranted.

Sociotechnical Intervention for Improved Delivery of Preventive Cardiovascular Care to Rural Communities: Participatory Design Approach.

BACKGROUND: Clinical practice guidelines recommend antiplatelet and statin therapies as well as blood pressure control and tobacco cessation for secondary prevention in patients with established atherosclerotic cardiovascular diseases (ASCVDs). However, these strategies for risk modification are underused, especially in rural communities. Moreover, resources to support the delivery of preventive care to rural patients are fewer than those for their urban counterparts. Transformative interventions for the delivery of tailored preventive cardiovascular care to rural patients are needed. OBJECTIVE: A multidisciplinary team developed a rural-specific, team-based model of care intervention assisted by clinical decision support (CDS) technology using participatory design in a sociotechnical conceptual framework. The model of care intervention included redesigned workflows and a novel CDS technology for the coordination and delivery of guideline recommendations by primary care teams in a rural clinic. METHODS: The design of the model of care intervention comprised 3 phases: problem identification, experimentation, and testing. Input from team members (n=35) required 150 hours, including observations of clinical encounters, provider workshops, and interviews with patients and health care professionals. The intervention was prototyped, iteratively refined, and tested with user feedback. In a 3-month pilot trial, 369 patients with ASCVDs were randomized into the control or intervention arm. RESULTS: New workflows and a novel CDS tool were created to identify patients with ASCVDs who had gaps in preventive care and assign the right care team member for delivery of tailored recommendations. During the pilot, the intervention prototype was iteratively refined and tested. The pilot demonstrated feasibility for successful implementation of the sociotechnical intervention as the proportion of patients who had encounters with advanced practice providers (nurse practitioners and physician assistants), pharmacists, or tobacco cessation coaches for the delivery of guideline recommendations in the intervention arm was greater than that in the control arm. CONCLUSIONS: Participatory design and a sociotechnical conceptual framework enabled the development of a rural-specific, team-based model of care intervention assisted by CDS technology for the transformation of preventive health care delivery for ASCVDs.

Computerized Advisory Decision Support for Cardiovascular Diseases in Primary Care: A Cluster Randomized Trial.

PURPOSE: The purpose of this research was to evaluate the impact of an outpatient computerized advisory clinical decision support system (CDSS) on adherence to guideline-recommended treatment for heart failure, atrial fibrillation, and hyperlipidemia. METHODS: Twenty care teams (109 clinicians) in a primary care practice were cluster-randomized to either access or no access to an advisory CDSS integrated into the electronic medical record. For patients with an outpatient visit, the CDSS determined if they had heart failure with reduced ejection fraction, hyperlipidemia, or atrial fibrillation; and if so, was the patient receiving guideline-recommended treatment. In the intervention group, an alert was visible in the medical record if there was a discrepancy between current and guideline-recommended treatment. Clicking the alert displayed the treatment discrepancy and recommended treatment. Outcomes included prescribing patterns, self-reported use of decision aids, and self-reported efficiency. The trial was conducted between May 1 and November 15, 2016, and incorporated 16,310 patient visits. RESULTS: The advisory CDSS increased adherence to guideline-recommended treatment for heart failure (odds ratio [OR] 7.6, 95% confidence interval [CI], 1.2, 47.5) but had no impact in atrial fibrillation (OR 0.94, 95% CI 0.15, 5.94) or hyperlipidemia (OR 1.1, 95% CI 0.6, 1.8). Clinicians with access to the CDSS self-reported greater use of risk assessment tools for heart failure (3.6 [1.1] vs 2.7 [1.0], mean [standard deviation] on a 5-point scale) but not for atrial fibrillation or hyperlipidemia. The CDSS did not impact self-assessed efficiency. The overall usage of the CDSS was low (19%). CONCLUSIONS: A computerized advisory CDSS improved adherence to guideline-recommended treatment for heart failure but not for atrial fibrillation or hyperlipidemia.

Impact of Patient Reminders on Papanicolaou Test Completion for High-Risk Patients Identified by a Clinical Decision Support System.

BACKGROUND: A clinical decision support system (CDSS) for cervical cancer screening identifies patients due for routine cervical cancer screening. Yet, high-risk patients who require more frequent screening or earlier follow-up to address past abnormal results are not identified. We aimed to assess the effect of a complex CDSS, incorporating national guidelines for high-risk patient screening and abnormal result management, its implementation to identify patients overdue for testing, and the outcome of sending a targeted recommendation for follow-up. MATERIALS AND METHODS: At three primary care clinics affiliated with an academic medical center, a reminder recommending an appointment for Papanicolaou (Pap) testing or Pap and human papillomavirus cotesting was sent to high-risk women aged 18 through 65 years (intervention group) identified by CDSS as overdue for testing. Historical control patients, who did not receive a reminder, were identified by CDSS 1 year before the date when reminders were sent to the intervention group. Test completion rates were compared between the intervention and control groups through a generalized estimating equation extension. RESULTS: Across the three sites, the average completion rate of recommended follow-up testing was significantly higher in the intervention group at 23.7% (61/257) than the completion rate at 3.3% (17/516) in the control group (p < 0.001). CONCLUSIONS: A CDSS with enhanced capabilities to identify high-risk women due for cervical cancer testing beyond routine screening intervals, with subsequent patient notification, has the potential to decrease cervical precancer and cancer by improving adherence to guideline-compliant follow-up and needed treatment.

Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management.

BACKGROUND: The 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on risk is challenging. We developed an informatics-based clinical decision support tool, MayoExpertAdvisor, to deliver automated cardiovascular risk scores and guideline-based treatment recommendations based on patient-specific data in the electronic heath record. OBJECTIVE: To assess the impact of our clinical decision support tool on the efficiency and accuracy of clinician calculation of cardiovascular risk and its effect on the delivery of guideline-consistent treatment recommendations. METHODS: Clinicians were asked to review the EHR records of selected patients. We evaluated the amount of time and the number of clicks and keystrokes needed to calculate cardiovascular risk and provide a treatment recommendation with and without our clinical decision support tool. We also compared the treatment recommendation arrived at by clinicians with and without the use of our tool to those recommended by the guidelines. RESULTS: Clinicians saved 3 minutes and 38 seconds in completing both tasks with MayoExpertAdvisor, used 94 fewer clicks and 23 fewer key strokes, and improved accuracy from the baseline of 60.61% to 100% for both the risk score calculation and guideline-consistent treatment recommendation. CONCLUSION: Informatics solution can greatly improve the efficiency and accuracy of individualized treatment recommendations and have the potential to increase guideline compliance.