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

Surka, Sam, Edirippulige, Sisira, Steyn, Krisela, Gaziano, Thomas, Puoane, Thandi and Levitt, Naomi (2014) Evaluating the use of mobile phone technology to enhance cardiovascular disease screening by community health workers. International Journal of Medical Informatics, 83 9: 648-654. doi:10.1016/j.ijmedinf.2014.06.008

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Author Surka, Sam
Edirippulige, Sisira
Steyn, Krisela
Gaziano, Thomas
Puoane, Thandi
Levitt, Naomi
Title Evaluating the use of mobile phone technology to enhance cardiovascular disease screening by community health workers
Journal name International Journal of Medical Informatics   Check publisher's open access policy
ISSN 1386-5056
1872-8243
Publication date 2014-01-01
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.ijmedinf.2014.06.008
Open Access Status File (Author Post-print)
Volume 83
Issue 9
Start page 648
End page 654
Total pages 7
Place of publication Shannon, Co. Clare, Ireland
Publisher Elsevier
Language eng
Abstract 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.

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.

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.

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.
Formatted 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 12.3 h for the paper-based chart tool and 3 h 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.
Keyword mHealth
Community health workers
Cardiovascular disease risk assessment
Task-shifting
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID HHSN268200900030C
Institutional Status UQ
Additional Notes Published online ahead of print 21 June 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Medicine Publications
Centre for Online Health Publications
 
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Created: Tue, 01 Jul 2014, 22:24:10 EST by Burke, Eliza on behalf of Centre for On-Line Health