The impact of patient characteristics and the Internet usage on potential PHR adoption in Primary Care

Background: A Personal Health Record (PHR) provides patient access to their health information and facilitates continuity of care. This provides an opportunity to explore how the PHR could be used to empower patients and enable them to be active participants in the healthcare delivery. But first there is a need to explore how the characteristics of patients and current Internet usage may affect PHR adoption. Objective: The objective of this study is to determine how patient characteristics and current Internet usage patterns are associated with potential PHR use. Methods: This was a prospective cohort study. The data were collected from participants using a self-reported questionnaire about their outcome of logging into a primary care PHR system at three different family medicine sites. Data were summarized in tables with descriptive statistics. Frequency and proportion were computed for the categorical variables. Bivariate comparisons were made using Fisher exact and Chi-square statistics where applicable. Logistic regression modeling was applied to evaluate the association between patient characteristics and Internet usage and subsequent PHR login. The significance level (α) for variable selection in multivariate model was set at 0.05. Using the statistical analysis software (SAS University Edition), at the first step of the analysis, univariate regression models were created for all explanatory variables to identify variables that have at least a moderate association with outcome (PHR login). Further, explanatory variables that were found to have a strong to modest association with the result (p≤0.25) were included in the final multivariate model. Using a "forward selection" technique, the final model for PHR login was refitted. The pre-defined criterion for retaining variables in the final model was set conservatively with P-value ≤ 0.05. Results: Of the 116 respondents, 89% intended to use the system, 95% thought it would be of benefit and 25.8% logged in to the PHR (n=30). There was no significant difference in the characteristics of the patients who searched for health versus non-health information online. The group that logged in were predominantly more than 35 years old as 35-64 (57%) and 65-75 (33%), female (63%), postgraduates (53%), employed (57%), English-speaking (77%), had previously heard about electronic PHR (60%), used the Internet from home (83%), at least once a day (97%), and 30 and more hours per week (33%). Also, 87% had a regular medical doctor and 57% had one or more chronic health conditions. In the final multivariate logistic model, patients 65-75 years old (15.85 OR, 2.72-92.19 95%CI) were significantly associated with PHR log-in. Similarly, postgraduate (18.17 OR, 2.14-154.35 95%CI) and those who requested an online prescription renewal (15.09 OR, 2.35-96.77 95%CI) were also more likely to log-in to the PHR system. Conclusion: Very few patients logged in to the PHR system despite its ability to enhance patient engagement, its positive perceived benefits, and their stated intention to use the PHR system. This discrepancy needs to be explored further. Although the literature suggests that an integrated PHR was successful in a few countries compared to a stand-alone PHR, future research is needed to explore the impact of the integrated PHR in the Canadian Primary Care context.

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