Abstract Body: Introduction
In 2019, the revised WHO CVD risk prediction charts for 21 global regions, including Southeast Asia, were developed. These charts provide a non-laboratory-based risk score and are practical for implementation in resource-limited areas. We used this chart to develop a web-based application for assessing CVD risk prediction scores. We aimed to evaluate the effectiveness of computer-based technology in enhancing CVD risk assessment by health workers in rural communities across four geographic regions in Thailand.
Methods
In a preliminary analysis of a randomized controlled trial conducted between July and September 2024, we enrolled 16 health workers working in primary care units in rural areas. These health workers included registered nurses and public health technical officers aged 27–52. They were randomly assigned to either the intervention group (web-based application) or the control group (traditional chart-based tool). Each health worker used the assigned tool to assess ten simulated patients' CVD risk. The primary outcome was a reduction in the duration of the CVD risk assessment. The secondary outcomes were the reduction of error in predicted CVD risk scores and predicted CVD risk group. We performed mixed-effects regression models to evaluate the primary and secondary outcomes. Furthermore, the two groups' usefulness, satisfaction, and ease of use (USE) scores (ranging from 1-7) were compared using a t-test.
Results
The mean duration of CVD risk assessment per one simulated patient in the intervention group was 26.2±0.5 seconds, while it was70.9±2.4 in the control group. The mean reduction was 44.8 seconds with the intervention effect size (95% CI: 34.4 to 55.2; p<0.0001), which reduced the duration of CVD assessment by 63.1%. The error in predicted CVD risk scores and predicted CVD risk group in the intervention group demonstrated a significant reduction of 27.5% (95% CI: 15.1% to 39.9%; p <0.0001) and 17.5% (95% CI: 8.4% to 26.6%); p<0.0001), respectively, compared to the control group. The mean overall USE score in the intervention group was 6.8±0.1, significantly higher than 5.0±0.3 in the control group (p<0.0001), indicating a more satisfying user experience.
Conclusion
For health workers in Thai rural communities, computer-based technology significantly reduced the duration of CVD risk assessment and errors in predicted CVD risk scores and groups. Additionally, users reported higher scores for usefulness, satisfaction, and ease of use.