K Singh1,2,3,4, L Johnson5, R Devarajan4,6, R Shivashankar1,2,4, P Sharma7,8, D Kondal1,2,4, V S Ajay1,2,4, K M V Narayan4,5, D Prabhakaran1,2,4, M K Ali4,5, N Tandon3,4. 1. Centre for Chronic Conditions and Injuries, Public Health Foundation of India, Gurgaon, Haryana, India. 2. Centre for Chronic Disease Control, New Delhi, India. 3. Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India. 4. Centre for Control of Chronic Conditions, New Delhi, India. 5. Rollins School of Public Health, Emory University, Atlanta, GA, USA. 6. Centre of Excellence - Centre for Cardio-metabolic Risk Reduction in South Asia. 7. St. Georges Medical University of London, London, UK. 8. Plovdiv Medical University, Plovdiv, Bulgaria.
Abstract
AIMS: To describe physicians' acceptance of decision-support electronic health record system and its impact on diabetes care goals among people with Type 2 diabetes. METHODS: We analysed data from participants in the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) trial, who received the study intervention (care coordinators and use of a decision-support electronic health record system; n=575) using generalized estimating equations to estimate the association between acceptance/rejection of decision-support system prompts and outcomes (mean changes in HbA1c , blood pressure and LDL cholesterol) considering repeated measures across all time points available. We conducted in-depth interviews with physicians to understand the benefits, challenges and value of the decision-support electronic health record system and analysed physicians' interviews using Rogers' diffusion of innovation theory. RESULTS: At end-of-trial, participants with diabetes for whom glycaemic, systolic blood pressure, diastolic blood pressure and LDL cholesterol decision-support electronic health record prompts were accepted vs rejected, experienced no reduction in HbA1c [mean difference: -0.05 mmol/mol (95% CI -0.22, 0.13); P=0.599], but statistically significant improvements were observed for systolic blood pressure [mean difference: -11.6 mmHg (95% CI -13.9, -9.3); P ≤ 0.001], diastolic blood pressure [mean difference: -5.2 mmHg (95% CI -6.5, -3.8); P ≤ 0.001] and LDL cholesterol [mean difference: -0.7 mmol/l (95% CI -0.6, -0.8); P ≤0.001], respectively. The relative advantages and compatibility of the decision-support electronic health record system with existing clinic set-ups influenced physicians' acceptance of it. Software complexities and data entry challenges could be overcome by task-sharing. CONCLUSION: Wider adherence to decision-support electronic health record prompts could potentially improve diabetes goal achievement, particularly when accompanied by assistance from a non-physician health worker.
AIMS: To describe physicians' acceptance of decision-support electronic health record system and its impact on diabetes care goals among people with Type 2 diabetes. METHODS: We analysed data from participants in the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) trial, who received the study intervention (care coordinators and use of a decision-support electronic health record system; n=575) using generalized estimating equations to estimate the association between acceptance/rejection of decision-support system prompts and outcomes (mean changes in HbA1c , blood pressure and LDL cholesterol) considering repeated measures across all time points available. We conducted in-depth interviews with physicians to understand the benefits, challenges and value of the decision-support electronic health record system and analysed physicians' interviews using Rogers' diffusion of innovation theory. RESULTS: At end-of-trial, participants with diabetes for whom glycaemic, systolic blood pressure, diastolic blood pressure and LDL cholesterol decision-support electronic health record prompts were accepted vs rejected, experienced no reduction in HbA1c [mean difference: -0.05 mmol/mol (95% CI -0.22, 0.13); P=0.599], but statistically significant improvements were observed for systolic blood pressure [mean difference: -11.6 mmHg (95% CI -13.9, -9.3); P ≤ 0.001], diastolic blood pressure [mean difference: -5.2 mmHg (95% CI -6.5, -3.8); P ≤ 0.001] and LDL cholesterol [mean difference: -0.7 mmol/l (95% CI -0.6, -0.8); P ≤0.001], respectively. The relative advantages and compatibility of the decision-support electronic health record system with existing clinic set-ups influenced physicians' acceptance of it. Software complexities and data entry challenges could be overcome by task-sharing. CONCLUSION: Wider adherence to decision-support electronic health record prompts could potentially improve diabetes goal achievement, particularly when accompanied by assistance from a non-physician health worker.