Original researchShared decision making in primary care: Process evaluation of the intervention in the OPTIMAL study, a cluster randomised trial
Introduction
The management of type 2 diabetes mellitus (T2DM) requires a multitude of decisions, each one entailing different combinations of possible therapeutic or adverse effects [1,2]. Therefore, T2DM patients need to be involved in determining the management strategy most consistent with their preferences and values [3]. Shared Decision Making (SDM) is a healthcare decision making model that promotes patient involvement, and has been identified as the crux of patient-centred care [4]. In SDM, both parties share information and expertise: the physician shares medical information about options and their benefits and risks, and T2DM patients share their preferences and values [5]. But how to implement SDM in daily practice? It has been demonstrated that general practitioners (GPs) can learn to deliver patient-centred care [6,7], and that options can be made clearer to patients using decision aids [8]. With regard to SDM, there is broad consensus about two core physician competencies that should be acquired during training. The first is relational competence, involving the creation of a favourable environment for communication, and an appropriate interaction during the clinical encounter. The second is risk communication competence, including discussion of uncertainty in treatment outcomes, and effective communication about benefits and risks of different treatment options [6,8,9]. Charles et al. [10] highlighted the need for bidirectional information exchange, participation of both parties in deliberation and agreement about the resulting treatment plan. They developed their framework in the acute setting in which typically one-time decisions are made. Their framework is one of the most-often cited basis for later frameworks [5]. In 2006, Montori et al. modified it to make it applicable to the care of people with chronic conditions [11]. This modification stressed the need for an ongoing partnership between GP and patients with T2DM and the recognition that decisions in chronic care can be revised.
The American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) published a decision cycle to manage hyperglycaemia in T2DM patients, to be used during consultations. It integrates current lifestyle, comorbidities, clinical characteristics, and issues such as patient preferences, motivation, diabetes-related distress, depression, and financial resources. SDM is explicitly integrated in the cycle and the cycle requests smart goals to be set [12].
We conducted a Cluster-Randomised Controlled Trial (cRCT, the OPTIMAL study) with a follow-up of 24 months to assess to what extent the implementation of SDM, based on the framework by Montori et al., would affect the proportion of T2DM patients who achieve all their treatment targets (glucose, systolic blood pressure, and LDL-cholesterol) [13]. Furthermore, we were interested in the experienced SDM 24 months after training, to evaluate the sustainability of the effect of SDM training. SDM was introduced using two elements: a decision aid for T2DM patients, combined with a training of GPs. Here we evaluate the SDM-process during the trial, aiming to answer the following research questions:
- 1.
Did GPs and patients differ in their opinions regarding the extent to which SDM occurred during consultations at baseline and at 24 months follow-up?
- 2.
Which decisional role did GPs and patients experience in making the final decision at baseline and at 24 months follow-up?
- 3.
To what extent did the GPs adhere to the study protocol regarding the SDM elements?
Section snippets
Study design
The full details on the rationale and design of the study are described elsewhere [13,14]. In short, the OPTIMAL study was a Cluster-Randomised Controlled Trial (cRCT) with three annual reviews by the GP (at baseline and at 12- and 24-months follow-up). The intervention aimed at fostering SDM about diabetes treatment targets by means of a decision aid and SDM training for the GPs. The decision aid was designed according to the International Patient Decision Aids Standards [15], and based on the
Results
At 24 months follow-up, 23 out of 72 patients had dropped out of the study and three patients had incomplete data (Fig. 1). At baseline, the average age of the intervention participants with T2DM was 71 (SD 5.6) years. At baseline, the 23 drop-outs did not significantly differ in age (72 (SD 5.5) vs 70 (SD 5.5) years, p = 0.10) or self-reported SDM score (31.7 (SD 12.5) versus 36.6 (SD 9.8), (p = 0.08)) compared to completers. Significantly more women (65%) than men dropped out of the study
Discussion
This study shows that GPs and patients did not significantly differ in how much SDM they perceived during the first visit, when they first used the decision aid. However, patients experienced their role in making the final decision to be significantly more shared, while GPs experienced their own role to be more important. Regardless, we can conclude that both GPs and patients perceived to have shared the decision about treatment intensity, at the time they first used the decision aid. In
Conflict of interest
None.
Acknowledgments
The study was funded by a charitable foundation (Nuts OHRA) and no funding assistance was received from a commercial organization. The funding body has not any role in design, in the collection, analysis, and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.
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2022, Molecular Genetics and Metabolism ReportsCitation Excerpt :Data on patient phenotype was not collected in this survey, but data regarding mean age and sex ratio from nationwide and post-marketing surveys [24,25] were comparable to the data from this survey. The total number of patients and physicians in our study compares favorably with a recent study of SDM conducted in in patients with type 2 diabetes mellitus [26]. This study has some limitations, including those inherent to web-based surveys, such as physician and patient selection bias.