Effectiveness of shared decision-making for glycaemic control among type 2 diabetes mellitus adult patients: A systematic review and meta-analysis. - Edosa Tesfaye Geta; Dufera Rikitu Terefa; Wase Benti Hailu; Wolkite Olani; Emiru Merdassa; Markos Dessalegn; Miesa Gelchu; Dereje Chala Diriba (PLoS ONE)
Background In diabetes care and management guidelines, shared decision-making (SDM) implementation is explicitly recommended to help patients and health care providers to make informed shared decisions that enable informed choices and the selection of treatments. Despite widespread calls for SDM to be embedded in health care, there is little evidence to support SDM in the management and care of diabetes. It is still not commonly utilized in routine care settings because its effects remain poorly understood. Hence, the current systematic review and meta-analysis aimed to evaluate the effectiveness of SDM for glycaemic control among type 2 diabetes adult patients. Methods Literature sources were searched in MEDLINE, PubMed, Cochrane library and HINARI bibliographic databases and Google Scholar. When these records were searched and reviewed, the PICO criteria (P: population, I: intervention, C: comparator, and O: outcome) were applied. The extracted data was exported to RevMan software version 5.4 and STATA 17 for further analysis. The mean differences (MD) of glycated hemoglobin (HbA1c) were pooled using a random effect model (REM), and sub-group analysis were performed to evaluate the effect size differences across the duration of the follow-up period, modes of intervention, and baseline glycated hemoglobin level of patient groups. The sensitivity analysis was performed using a leave-one-out meta-analysis to quantify the impact of each study on the overall effect size in mean difference HbA1c%. Finally, the statistically significant MD of HbA1c% between the intervention groups engaged in SDM and control groups received usual care was declared at P ˂0.05, using a 95% confidence interval (CI). Results In the database search, 425 records were retrieved, with only 17 RCT studies fulfilling the inclusion criteria and were included in the meta-analysis. A total of 5416 subjects were included, out of which 2782(51.4%) were included in trial arms receiving SDM and 2634(48.6%) were included in usual diabetes care. The Higgins (I2) test statistics were calculated to be 59.1%, P = 0.002, indicating statistically significant heterogeneity was observed among the included studies, and REM was used as a remedial to estimate the pooled MD of HbA1c% level between patients who participated in SDM and received usual care. As a result, the pooled MD showed that the SDM significantly lowered HbA1c by 0.14% compared to the usual care (95% CI = [-0.26, -0.02], P = 0.02). SDM significantly decreased the level of HbA1c by 0.14% (95% CI = -0.28, -0.01, P = 0.00) when shared decisions were made in person or face-to-face at the point of care, but there was no statistically significant reduction in HbA1c levels when patients were engaged in online SDM. In patients with poorly controlled glycaemic level (≥ 8%), SDM significantly reduced level of HbA1c by 0.13%, 95% CI = [-0.29, -0.03], P = 0.00. However, significant reduction in HbA1c was not observed in patients with ˂ 8%, HbA1c baseline level. Conclusions Overall, statistically significant reduction of glycated hemoglobin level was observed among T2DM adult patients who participated in shared decision-making compared to those patients who received diabetes usual care that could lead to improved long-term health outcomes, reducing the risk of diabetes-related complications. Therefore, we strongly suggest that health care providers and policy-makers should integrate SDM into diabetes health care and management, and further study should focus on the level of patients' empowerment, health literacy, and standardization of decision supporting tools to evaluate the effectiveness of SDM in diabetes patients.