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Paper Type
Complete
Description
Online Medical Records (OMR) platforms can provide benefits to chronic disease patients. Yet, OMR use among them is suboptimal. The study identifies clusters among nonusers of OMR among chronic patients. The Health Information National Trends Survey (HINTS) iteration 5, Cycle 3 data were used to analyze 1071 respondents. Latent Class Analysis was run on the six reasons for nonuse (no record, speaking directly, privacy or security of the website, no Internet, login issues, and no need to access) and resulted in 3 clusters. About 19% subjects expressed multiple reasons and 69% just one strong reason. Demographic and clinical attributes were partially associated. For electronic wearable/tracking device use or electronic communication, differences among clusters were noted; persistent resisters showed lower propensities to use. Interventions to improve patient use of Internet-based health technologies should be customized and help produce patient-generated data facilitating healthcare decision-making.
Paper Number
1043
Recommended Citation
Mukhopadhyay, Surma; Basak, Ramsankar; and Reithel, Brian, "Barriers Driving Nonuse of Online Medical Records: Latent Class Analysis of Chronic Patients" (2023). AMCIS 2023 Proceedings. 1.
https://aisel.aisnet.org/amcis2023/sig_health/sig_health/1
Barriers Driving Nonuse of Online Medical Records: Latent Class Analysis of Chronic Patients
Online Medical Records (OMR) platforms can provide benefits to chronic disease patients. Yet, OMR use among them is suboptimal. The study identifies clusters among nonusers of OMR among chronic patients. The Health Information National Trends Survey (HINTS) iteration 5, Cycle 3 data were used to analyze 1071 respondents. Latent Class Analysis was run on the six reasons for nonuse (no record, speaking directly, privacy or security of the website, no Internet, login issues, and no need to access) and resulted in 3 clusters. About 19% subjects expressed multiple reasons and 69% just one strong reason. Demographic and clinical attributes were partially associated. For electronic wearable/tracking device use or electronic communication, differences among clusters were noted; persistent resisters showed lower propensities to use. Interventions to improve patient use of Internet-based health technologies should be customized and help produce patient-generated data facilitating healthcare decision-making.
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