Exploring Patient Empowerment and Health System Outcomes Associated With MyHealthNB, a Provincial Personal Health Record System: Exploratory Mixed Methods Study (Preprint)
Bibliographic record
Abstract
<sec> <title>BACKGROUND</title> Personal health record systems (PHRs) have been introduced to support patient empowerment by giving individuals direct access to their personal health information and other key health system resources. MyHealthNB is a province-wide PHR in New Brunswick, Canada, that allows residents to view laboratory results, medication lists, immunization records, imaging reports, and a range of digital health resources. As PHRs continue to expand, it is essential to understand how PHRs like MyHealthNB impact outcomes related to patient empowerment. </sec> <sec> <title>OBJECTIVE</title> This study uses MyHealthNB as a case example to examine empowerment-related impacts of PHRs on citizens. Building on a conceptual framework linking patient enablement, empowerment, involvement, and engagement, the study is guided by two questions: (1) What perceived impacts of PHR use emerge across enablement, empowerment, involvement, engagement, and cost-related outcomes? (2) Which impacts of PHR use are most prevalent, how are they interrelated, and what characteristics predict variation in these impacts? </sec> <sec> <title>METHODS</title> An exploratory sequential mixed methods study design was used. Phase 1 involved qualitative interviews with citizens to explore perceived impacts of using MyHealthNB, which were analyzed using rapid qualitative analysis. Findings informed a Phase 2 cross-sectional survey that measured MyHealthNB users’ self-reported impacts across enablement, empowerment, involvement, engagement, and cost-related outcomes. Survey data were analyzed using descriptive statistics, <i>t</i> tests, mediation analysis, and multivariable linear regressions to examine impacts, impact pathways, and impact predictors. </sec> <sec> <title>RESULTS</title> Data from 32 interviewees and 885 survey respondents were analyzed. The qualitative analysis showed that MyHealthNB supported a progression from improved access to health information (enablement), to increased confidence (empowerment), to more active participation in health management and health care decisions (involvement and engagement). The survey analysis confirmed significant positive impacts across all 21 outcomes measured that spanned enablement, empowerment, involvement, engagement, and cost-related outcomes (<i>P</i>&lt;.05). Mediation analyses showed that higher perceived enablement through MyHealthNB was associated with greater patient involvement and engagement, with empowerment emerging as a central linking factor. Regression models identified key predictors of MyHealthNB impacts, which included satisfaction with MyHealthNB, having a family doctor, provider support of MyHealthNB, digital literacy, and MyHealthNB use frequency. </sec> <sec> <title>CONCLUSIONS</title> Exploratory, self-reported citizen data suggest that PHRs may improve outcomes related to patient empowerment, behavior change, and health system benefits. The advantages of PHR use were most prominent when individuals had access to primary care, received support from health care providers, and had confidence using digital technologies. To fully realize the promise of PHRs, implementers should invest in digital literacy support and strengthen primary care access and integration. </sec>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".