Among CVRM patients , the results tended towards a beneficial effect of CDSS , but only LDL-c target attainment in diabetes patients reached statistical significance .
Prompting , integration into the electronical health record , patient empowerment , and medication support were related to more effective CVRM .
Conclusion We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment .
Some features of CDSS seem more promising than others .
Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment
Background Cardiovascular risk management ( CVRM ) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease .
Computerized decision support systems ( CDSS ) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies .
The effect on cardiovascular risk factor management is yet to be confirmed .
‘Decision support system (DSS) for prevention of cardiovascular disease (CVD) among hypertensive (HTN) patients in Andhra Pradesh, India’ – a cluster randomised community intervention trial
Background Very few studies having decision support systems as an intervention report on patient outcomes for cardiovascular disease in the Western world . The potential role of decision support system for the management of blood pressure among Indian hypertensives remains unclear . We propose a cluster r and omised trial that aims to test the effectiveness and cost effectiveness of DSS among Indian hypertensive patients . Methods The trial design is a cluster r and omised community intervention trial , in which the participants would be adult male and female hypertensive patients , in the age group of 35 to 64 years , reporting to the Primary Health Care centres of Mahabubnagar district , And hra Pradesh , India . The objective of the study is to test the effectiveness and compare the cost effectiveness and cost utility among hypertensive subjects r and omized to receive either decision support system or a chart based algorithmic support system in urban and rural areas of a district in the state of And hra Pradesh , India ( baseline versus 12 months follow up ) . The primary outcome would be a comparison of the systolic blood pressure at 0 and 12 months among hypertensive patients r and omized to receive the decision support system or the chart based algorithmic support system . Computer generated r and omisation and an investigator and analyser blinded method would be followed . 1600 participants ; 800 to each arm ; each arm having eight clusters of hundred participants each have been recruited between 01 August 2011 - 01 March 2012 . A twelve month follow up will be completed by March 2013 and results are expected by April 2013 . Discussion This cluster r and omized community intervention trial on DSS will enable policy makers to find out the effectiveness , cost effectiveness and cost utility of decision support system for management of blood pressure among hypertensive patients in India . Most of the previous studies on decision support system have focused on physician performance , adherence and on preventive care reminders . The uniqueness of the proposed study lies in finding out the effectiveness of a decision support system on patient related outcomes .Trial registration CTRI/2012/03/002476 , Clinical Trial Registry - India
Among CVRM patients , the results tended towards a beneficial effect of CDSS , but only LDL-c target attainment in diabetes patients reached statistical significance .
Prompting , integration into the electronical health record , patient empowerment , and medication support were related to more effective CVRM .
Conclusion We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment .
Some features of CDSS seem more promising than others .
Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment
Background Cardiovascular risk management ( CVRM ) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease .
Computerized decision support systems ( CDSS ) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies .
The effect on cardiovascular risk factor management is yet to be confirmed .