Syed Mustafa Ali1, Richard Giordano2, Saima Lakhani3, Dawn Marie Walker4. 1. mHealth Coordinator at Mercy Corps, Pakistan. Electronic address: Mustafa_30_84@yahoo.com. 2. Senior Lecturer, Faculty of Health Sciences, University of Southampton, UK. 3. Manager Quality Assurance, Marie Stopes Society Pakistan, An affiliate of Marie Stopes International, UK. 4. Associate Professor, Faculty of Health Sciences, University of Southampton, UK.
Abstract
BACKGROUND: A gap between current diabetes care practice and recommended diabetes care standards has consistently been reported in the literature. Many IT-based interventions have been developed to improve adherence to the quality of care standards for chronic illness like diabetes. OBJECTIVE: The widespread implementation of electronic medical/health records has catalyzed clinical decision support systems (CDSS) which may improve the quality of diabetes care. Therefore, the objective of the review is to evaluate the effectiveness of CDSS in improving quality of type II diabetes care. Moreover, the review aims to highlight the key indicators of quality improvement to assist policy makers in development of future diabetes care policies through the integration of information technology and system. SELECTION OF STUDY: Setting inclusion criteria, a systematic literature search was conducted using Medline, Web of Science and Science Direct. Critical Appraisal Skills Programme (CASP) tools were used to evaluate the quality of studies. Eight randomized controlled trials (RCTs) were selected for the review. In the selected studies, seventeen clinical markers of diabetes care were discussed. Three quality of care indicators were given more importance in monitoring the progress of diabetes care, which is consistent with National Institute for Health and Care Excellence (NICE) guidelines. The presence of these indicators in the studies helped to determine which studies were selected for review. Clinical- and process-related improvements are compared between intervention group using CDSS and control group with usual care. Glycated hemoglobin (HbA1c), low density lipid cholesterol (LDL-C) and blood pressure (BP) were the quality of care indicators studied at the levels of process of care and clinical outcome. FINDINGS: The review has found both inconsistent and variable results for quality of diabetes care measures. A significant improvement has been found in the process of care for all three measures of quality of diabetes care. However, weak to modest positive results are observed for the clinical measures of the diabetes care indicators. In addition to this, technology adoption of CDSS is found to be consistently low. CONCLUSION: The review suggests the need to conduct further empirical research using the critical diabetes care indicators (HbA1c, LDL-C and BP) to ascertain if CDSS improves the quality of diabetes care. Research designs should be improved, especially with regard to baseline characteristics, sample size and study period. With respect to implementation of CDSS, rather than a sudden change of clinical work practice, there should instead be an incremental, gradual adoption of technology that minimizes the disruption in clinical workflow.
BACKGROUND: A gap between current diabetes care practice and recommended diabetes care standards has consistently been reported in the literature. Many IT-based interventions have been developed to improve adherence to the quality of care standards for chronic illness like diabetes. OBJECTIVE: The widespread implementation of electronic medical/health records has catalyzed clinical decision support systems (CDSS) which may improve the quality of diabetes care. Therefore, the objective of the review is to evaluate the effectiveness of CDSS in improving quality of type II diabetes care. Moreover, the review aims to highlight the key indicators of quality improvement to assist policy makers in development of future diabetes care policies through the integration of information technology and system. SELECTION OF STUDY: Setting inclusion criteria, a systematic literature search was conducted using Medline, Web of Science and Science Direct. Critical Appraisal Skills Programme (CASP) tools were used to evaluate the quality of studies. Eight randomized controlled trials (RCTs) were selected for the review. In the selected studies, seventeen clinical markers of diabetes care were discussed. Three quality of care indicators were given more importance in monitoring the progress of diabetes care, which is consistent with National Institute for Health and Care Excellence (NICE) guidelines. The presence of these indicators in the studies helped to determine which studies were selected for review. Clinical- and process-related improvements are compared between intervention group using CDSS and control group with usual care. Glycated hemoglobin (HbA1c), low density lipid cholesterol (LDL-C) and blood pressure (BP) were the quality of care indicators studied at the levels of process of care and clinical outcome. FINDINGS: The review has found both inconsistent and variable results for quality of diabetes care measures. A significant improvement has been found in the process of care for all three measures of quality of diabetes care. However, weak to modest positive results are observed for the clinical measures of the diabetes care indicators. In addition to this, technology adoption of CDSS is found to be consistently low. CONCLUSION: The review suggests the need to conduct further empirical research using the critical diabetes care indicators (HbA1c, LDL-C and BP) to ascertain if CDSS improves the quality of diabetes care. Research designs should be improved, especially with regard to baseline characteristics, sample size and study period. With respect to implementation of CDSS, rather than a sudden change of clinical work practice, there should instead be an incremental, gradual adoption of technology that minimizes the disruption in clinical workflow.
Keywords:
Clinical decision support system; Clinical performance in diabetes care; Diabetes patient outcome; Electronic health record; Electronic medical record; Quality of diabetescare
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