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Development and validation of a clinical and computerised decision support system for management of hypertension (DSS-HTN) at a primary health care (PHC) setting.

Anchala R, Di Angelantonio E, Prabhakaran D, Franco OH - PLoS ONE (2013)

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Department of Public Health & Primary Care, University of Cambridge, Cambridge, United Kingdom ; Public Health Foundation of India, New Delhi, India.

ABSTRACT

Background: Hypertension 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).

Results: The 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.

Conclusion: A 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.

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Related in: MedlinePlus

Receiver Operator Curve for comparing the DSS and independent experts on drug management.
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pone-0079638-g006: Receiver Operator Curve for comparing the DSS and independent experts on drug management.

Mentions: Based on the risk category; staging of BP; presence or absence of associated clinical conditions and target organ damage; DSS suggested drug management for 39 out of 60 HTN patients, whereas the independent experts opined that 42 out of 60 would need drug management (table 3 and table S1 in File S1). The positive and negative percent agreements were 85.71% and 83.33 % respectively. The overall percent agreement (Po) between the DSS and expert was 85% (95% CI: 83.61% - 85.25%). 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 (Figure 6). The kappa statistic (observed agreement beyond chance divided by the maximum agreement beyond chance), 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. The prevalence index was 0.31 and the bias index (extent to which the raters disagree on the proportion of positive or negative cases) was 0.05.


Development and validation of a clinical and computerised decision support system for management of hypertension (DSS-HTN) at a primary health care (PHC) setting.

Anchala R, Di Angelantonio E, Prabhakaran D, Franco OH - PLoS ONE (2013)

Receiver Operator Curve for comparing the DSS and independent experts on drug management.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3818237&req=5

pone-0079638-g006: Receiver Operator Curve for comparing the DSS and independent experts on drug management.
Mentions: Based on the risk category; staging of BP; presence or absence of associated clinical conditions and target organ damage; DSS suggested drug management for 39 out of 60 HTN patients, whereas the independent experts opined that 42 out of 60 would need drug management (table 3 and table S1 in File S1). The positive and negative percent agreements were 85.71% and 83.33 % respectively. The overall percent agreement (Po) between the DSS and expert was 85% (95% CI: 83.61% - 85.25%). 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 (Figure 6). The kappa statistic (observed agreement beyond chance divided by the maximum agreement beyond chance), 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. The prevalence index was 0.31 and the bias index (extent to which the raters disagree on the proportion of positive or negative cases) was 0.05.

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Department of Public Health & Primary Care, University of Cambridge, Cambridge, United Kingdom ; Public Health Foundation of India, New Delhi, India.

ABSTRACT

Background: Hypertension 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).

Results: The 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.

Conclusion: A 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.

Show MeSH
Related in: MedlinePlus