Development and Validation of a Clinical and Computerised Decision Support System for Management of Hypertension (DSS-HTN) at a Primary Health Care (PHC) Setting

Abstract

BackgroundHypertension remains the top global cause of disease burden. Decision support systems (DSS) could provide an adequate and cost-effective means to improve the management of hypertension at a primary health care (PHC) level in a developing country, nevertheless evidence on this regard is rather limited.Methods Development of DSS software was based on an algorithmic approach for (a) evaluation of a hypertensive patient, (b) risk stratification (c) drug management and (d) lifestyle interventions, based on Indian guidelines for hypertension II (2007). The beta testing of DSS software involved a feedback from the end users of the system on the contents of the user interface. Software validation and piloting was done in field, wherein the virtual recommendations and advice given by the DSS were compared with two independent experts (government doctors from the non-participating PHC centers).ResultsThe overall percent agreement between the DSS and independent experts among 60 hypertensives on drug management was 85% (95% CI: 83.61 - 85.25). The kappa statistic for overall agreement for drug management was 0.659 (95% CI: 0.457 - 0.862) indicating a substantial degree of agreement beyond chance at an alpha fixed at 0.05 with 80% power. Receiver operator curve (ROC) showed a good accuracy for the DSS, wherein, the area under curve (AUC) was 0.848 (95% CI: 0.741 - 0.948). Sensitivity and specificity of the DSS were 83.33 and 85.71% respectively when compared with independent experts.ConclusionA point of care, pilot tested and validated DSS for management of hypertension has been developed in a resource constrained low and middle income setting and could contribute to improved management of hypertension at a primary health care level.

Cardiovascular Diseases in India

“…A cluster randomized trial evaluating the use of a point-of-care electronic decision support tool for management of hypertension has been completed in Andhra Pradesh, India, in 16 primary healthcare centers. 128 This study concluded that electronic clinical decision support systems are both effective and cost-effective in the management of hypertension in resource-constrained primary care settings. 129 In addition, a multifaceted strategy using mobile technology to assist rural primary healthcare doctors and frontline health workers in CVD risk management has been developed and was implemented in 18 primary health centers and 54 villages in rural Andhra Pradesh involving ≈15 000 adults aged ≥40 years at high CVD event risk.…”

Rising Above the Rhetoric: Mobile Applications and the Delivery of cost-effective Cardiovascular Care in resource-limited Settings

“…Decision support applications ('mHealth 2.0') have been tested in a variety of settings, particularly in the field of maternal and child health, where the most robust applications of this nature have been created to date. A typical decision support software will prompt the user -usually a community health worker or nurse -to ask the patient a specific set of questions or to collect specific clinical and laboratory data and then recommend a clinical intervention based on a preprogrammed algorithm [8]. For instance, the app prompts the nurse to collect the patient's blood pressure and to increase the dose of an antihypertensive or refer the patient to a local clinic if the blood pressure exceeds certain predefined thresholds.…”

Sistemas de apoio à decisão clínica e o desfecho clínico na atenção primária: Uma revisão sistemática.

“…Aproximadamente 18% dos estudos 14,15,16 12,14,15,16,18,19,22 (7 de 16 estudos) tem sua origem na academia e hospitais de ensino; em menor número, vieram os autores apenas da academia 10,13,17,23,25 (5 de 16 estudos); seguidos dos autores de origem na academia e órgãos privados de pesquisa 20,24 (2 de 16 estudos); e, por fim, autores advindos da academia e órgãos públicos 11,21 (2 de 16 estudos).…”

“…Ensaios Clínicos 10,12,13,18,20,21,23,24 e 8 estudos observacionais 11,14,15,16,17,19,22,25 . Os estudos com os melhores níveis de evidência foram Ensaios Clínicos Randomizados 10,18,20,21,24 com população do estudo superior a 1000 participantes, entretanto todos apresentavam múltiplas variáveis não controladas e não foram estudos mascarados.…”

“…Web-based CDSS 15,23 . Estudos que fizeram uso de Computer-based CDSS tiveram resultados pouco expressivos ou não tiveram resultados favoráveis 11,13,17,18 . Também foi possível associar a qualidade dos desfechos à aplicação do CDSS, sendo que os estudos com os melhores desfechos foram aqueles que aplicaram os sistemas de apoio na prevenção e diagnóstico 10,12,15,22,24,25 12,14,22 e até mesmo contribuindo para políticas e programas governamentais de saúde 10,25 .…”