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Int J Med Inform. 2014 Sep;83(9):648-54. doi: 10.1016/j.ijmedinf.2014.06.008. Epub 2014 Jun 21.

Evaluating the use of mobile phone technology to enhance cardiovascular disease screening by community health workers.

Author information

1
Chronic Disease Initiative for Africa, University of Cape Town, South Africa. Electronic address: samsurka@gmail.com.
2
Centre for Online Health, University of Queensland, Brisbane, Australia.
3
Chronic Disease Initiative for Africa, University of Cape Town, South Africa.
4
Division of Cardiovascular Medicine, Brigham & Women's Hospital, Boston, USA.
5
School of Public Health, University of Western Cape, Cape Town, South Africa.
6
Chronic Disease Initiative for Africa, Division of Diabetes and Endocrinology, Department of Medicine, University of Cape Town, South Africa.

Abstract

BACKGROUND:

Primary prevention of cardiovascular disease (CVD),by identifying individuals at risk is a well-established, but costly strategy when based on measurements that depend on laboratory analyses. A non-laboratory, paper-based CVD risk assessment chart tool has previously been developed to make screening more affordable in developing countries. Task shifting to community health workers (CHWs) is being investigated to further scale CVD risk screening. This study aimed to develop a mobile phone CVD risk assessment application and to evaluate its impact on CHW training and the duration of screening for CVD in the community by CHWs.

METHODS:

A feature phone application was developed using the open source online platform, CommCare(©). CHWs (n=24) were trained to use both paper-based and mobile phone CVD risk assessment tools. They were randomly allocated to using one of the risk tools to screen 10-20 community members and then crossed over to screen the same number, using the alternate risk tool. The impact on CHW training time, screening time and margin of error in calculating risk scores was recorded. A focus group discussion evaluated experiences of CHWs using the two tools.

RESULTS:

The training time was 12.3h for the paper-based chart tool and 3h for the mobile phone application. 537 people were screened. The mean screening time was 36 min (SD=12.6) using the paper-base chart tool and 21 min (SD=8.71) using the mobile phone application, p=<0.0001. Incorrect calculations (4.3% of average systolic BP measurements, 10.4% of BMI and 3.8% of CVD risk score) were found when using the paper-based chart tool while all the mobile phone calculations were correct. Qualitative findings from the focus group discussion corresponded with the findings of the pilot study.

CONCLUSION:

The reduction in CHW training time, CVD risk screening time, lack of errors in calculation of a CVD risk score and end user satisfaction when using a mobile phone application, has implications in terms of adoption and sustainability of this primary prevention strategy to identify people with high CVD risk who can be referred for appropriate diagnoses and treatment.

KEYWORDS:

Cardiovascular disease risk assessment; Community health workers; Mobile phones; Task-shifting; mHealth

PMID:
25002305
PMCID:
PMC4108525
DOI:
10.1016/j.ijmedinf.2014.06.008
[Indexed for MEDLINE]
Free PMC Article
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