Making sense of diabetes medication decisions: a mixed methods cluster randomized trial using a conversation aid intervention

PURPOSE

To determine the effectiveness of a shared decision-making (SDM) tool versus guideline-informed usual care in translating evidence into primary care, and to explore how use of the tool changed patient perspectives about diabetes medication decision making.

METHODS

In this mixed methods multicenter cluster randomized trial, we included patients with type 2 diabetes mellitus and their primary care clinicians. We compared usual care with or without a within-encounter SDM conversation aid. We assessed participant-reported decisions made and quality of SDM (knowledge, satisfaction, and decisional conflict), clinical outcomes, adherence, and observer-based patient involvement in decision-making (OPTION12-scale). We used semi-structured interviews with patients to understand their perspectives.

RESULTS

We enrolled 350 patients and 99 clinicians from 20 practices and interviewed 26 patients. Use of the conversation aid increased post-encounter patient knowledge (correct answers, 52% vs. 45%, p = 0.02) and clinician involvement of patients (Mean between-arm difference in OPTION12, 7.3 (95% CI 3, 12); p = 0.003). There were no between-arm differences in treatment choice, patient or clinician satisfaction, encounter length, medication adherence, or glycemic control. Qualitative analyses highlighted differences in how clinicians involved patients in decision making, with intervention patients noting how clinicians guided them through conversations using factors important to them.

CONCLUSIONS

Using an SDM conversation aid improved patient knowledge and involvement in SDM without impacting treatment choice, encounter length, medication adherence or improved diabetes control in patients with type 2 diabetes. Future interventions may need to focus specifically on patients with signs of poor treatment fit.

CLINICAL TRIAL REGISTRATION

ClinicalTrial.gov: NCT01502891.

Deploying Clinical Decision Support for Familial Hypercholesterolemia

Objective

Familial hypercholesterolemia (FH), a prevalent genomic disorder that increases risk of coronary heart disease, remains significantly underdiagnosed. Clinical decision support (CDS) tools have the potential to increase FH detection. We describe our experience in the development and implementation of a genomic CDS for FH at a large academic medical center.

Methods

CDS development and implementation were conducted in four phases: (1) development and validation of an algorithm to identify "possible FH"; (2) obtaining approvals from institutional committees to develop the CDS; (3) development of the initial prototype; and (4) use of an implementation science framework to evaluate the CDS.

Results

The timeline for this work was approximately 4 years; algorithm development and validation occurred from August 2018 to February 2020. During this 4-year period, we engaged with 15 stakeholder groups to build and integrate the CDS, including health care providers who gave feedback at each stage of development. During CDS implementation six main challenges were identified: (1) need for multiple institutional committee approvals; (2) need to align the CDS with institutional knowledge resources; (3) need to adapt the CDS to differing workflows; (4) lack of institutional guidelines for CDS implementation; (5) transition to a new institutional electronic health record (EHR) system; and (6) limitations of the EHR related to genomic medicine.

Conclusion

We identified multiple challenges in different domains while developing CDS for FH and integrating it with the EHR. The lessons learned herein may be helpful in streamlining the development and deployment of CDS to facilitate genomic medicine implementation.

Encounter Decision Aid vs. Clinical Decision Support or Usual Care to Support Patient-Centered Treatment Decisions in Osteoporosis: The Osteoporosis Choice Randomized Trial II

PURPOSE

Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.

METHODS

Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.

RESULTS

We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01), improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively), had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001). Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer). There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07); medication adherence at 6 months was no different across arms.

CONCLUSION

Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.

TRIAL REGISTRATION

clinical trials.gov NCT00949611.

Shared decision making for patients with type 2 diabetes: a randomized trial in primary care

Background

Patient-centered diabetes care requires shared decision making (SDM). Decision aids promote SDM, but their efficacy in nonacademic and rural primary care clinics is unclear.

Methods

We cluster-randomized 10 practices in a concealed fashion to implement either a decision aid (DA) about starting statins or one about choosing antihyperglycemic agents. Each practice served as a control group for another practice implementing the other type of DA. From April 2011 to July 2012, 103 (DA=53) patients with type 2 diabetes participated in the trial. We used patient and clinician surveys administered after the clinical encounter to collect decisional outcomes (patient knowledge and comfort with decision making, patient and clinician satisfaction). Medical records provided data on metabolic control. Pharmacy fill profiles provided data for estimating adherence to therapy.

Results

Compared to usual care, patients receiving the DA were more likely to report discussing medications (77% vs. 45%, p<.001), were more likely to answer knowledge questions correctly (risk reduction with statins 61% vs. 33%, p=.07; knowledge about options 57% vs. 33%, p=.002) and were more engaged by their clinicians in decision making (50. vs. 28, difference 21.4 (95% CI 6.4, 36.3), p=.01). We found no significant impact on patient satisfaction, medication starts, adherence or clinical outcomes, in part due to limited statistical power.

Conclusion

DAs improved decisional outcomes without significant effect on clinical outcomes. DAs designed for point-of-care use with type 2 diabetes patients promoted shared decision making in nonacademic and rural primary care practices.

Trial Registration

NCT01029288

The diabetes mellitus medication choice decision aid: a randomized trial

BACKGROUND

Patient involvement in the choice of antihyperglycemic agents could improve adherence and optimize glycemic control in patients with type 2 diabetes mellitus.

METHODS

We conducted a pilot, cluster randomized trial of Diabetes Medication Choice, a decision aid that describes 5 antihyperglycemic drugs, their treatment burden (adverse effects, administration, and self-monitoring demands), and impact on hemoglobin A(1c) (HbA(1c)) levels. Twenty-one clinicians were randomized to use the decision aid during the clinical encounter and 19 to dispense usual care and an educational pamphlet. We used surveys and video analysis to assess postvisit decisional outcomes, and medical and pharmacy records to assess 6-month medication adherence and HbA(1c) levels.

RESULTS

Compared with usual care patients (n = 37), patients receiving the decision aid (n = 48) found the tool more helpful (clustered-adjusted mean difference [AMD] in a 7-point scale, 0.38; 95% confidence interval [CI], 0.04-0.72); had improved knowledge (AMD, 1.10 of 10 questions; 95% CI, 0.11-2.09); and had more involvement in making decisions about diabetes medications (AMD, 21.8 of 100; 95% CI, 13.0-30.5). At 6-month follow-up, both groups had nearly perfect medication use (median, 100% of days covered), with better adherence (AMD, 9% more days covered; 95% CI, 4%-14%) and persistence (AMD, 12 more days covered; 95% CI, 3-21 days) in the usual care group, and no significant impact on HbA(1c) levels (AMD, 0.01; 95% CI, -0.49 to 0.50).

CONCLUSION

An innovative decision aid effectively involved patients with type 2 diabetes mellitus in decisions about their medications but did not improve adherence or HbA(1c) levels. Trial Registration clinicaltrials.gov Identifier: NCT00388050.