An action design research to facilitate the adoption of personal health records

Adoption and user perceptions are dominant on personal health records literature and have led to a better understanding of what individuals' behaviors and perceptions are about the adoption of personal health records. However, these insights are descriptive and are not actionable to allow creating personal health records that will overcome the adoption problems identified by users. This study uses action design research to provide actionable knowledge regarding user perceptions and adoption and their application in the case of the digital allergy card. To achieve this, we conducted interviews with patients and physicians as part of the evaluation of the digital allergy card mock-up and the first prototype. As results, we provided some research proposals regarding the benefits of, levers for, and barriers to adoption of the digital allergy card that can be tested for several other personal health records.

Risk factors for clinically relevant deviations in patients’ medication lists reported by patients in personal health records: a prospective cohort study in a hospital setting

Background Personal health records have the potential to identify medication discrepancies. Although they facilitate patient empowerment and broad implementation of medication reconciliation, more medication discrepancies are identified through medication reconciliation performed by healthcare professionals. Aim We aimed to identify the factors associated with the occurrence of a clinically relevant deviation in a patient’s medication list based on a personal health record (used by patients) compared to medication reconciliation performed by a healthcare professional. Method Three- to 14 days prior to a planned admission to the Cardiology-, Internal Medicine- or Neurology Departments, at Amphia Hospital, Breda, the Netherlands, patients were invited to update their medication file in their personal health records. At admission, medication reconciliation was performed by a pharmacy technician. Deviations were determined as differences between these medication lists. Associations between patient-, setting-, and medication-related factors, and the occurrence of a clinically relevant deviation (National Coordinating Council for Medication Error Reporting and Prevention class $$\ge$$ ≥ E) were analysed. Results Of the 488 patients approached, 155 patients were included. Twenty-four clinically relevant deviations were observed. Younger patients (adjusted odds ratio (aOR) 0.94; 95%CI:0.91–0.98), patients who used individual multi-dose packaging (aOR 14.87; 95%CI:2.02–110), and patients who used $$\ge$$ ≥ 8 different medications, were at highest risk for the occurrence of a clinically relevant deviation (sensitivity 0.71; specificity 0.62; area under the curve 0.64 95%CI:0.52–0.76). Conclusion Medication reconciliation is the preferred method to identify medication discrepancies for patients with individual multi-dose packaging, and patients who used eight or more different medications.

Protecting Personal Health Data through Privacy Awareness

Digital health data is important to keep secure, and patients' perception around the privacy of it is essential to the development of digital health records. In this paper we present people's perceptions of the communication of data protection, in relation to their personal health data and the access to it; we focused particularly on people with chronic or long-term illness. Based on their use of personally accessible health records, we inquired into their explicit perception of security and sense of data privacy in relation to their health data. Our goal was to provide insights and guidelines to designers and developers on the communication of data protection in health records in an accessible way for the users. We analyzed their approach to and experience with their own health care records and describe the details of their challenges. A conceptual framework called "Privacy Awareness' was developed from the findings and reflects the perspectives of the users. The conceptual framework forms the basis of a proposal for design guidelines for Digital Health Record systems, which aim to address, facilitate and improve the users' awareness of the protection of their online health data.

The Uptake and Vaccination Willingness of COVID-19 Vaccine among Chinese Residents: Web-Based Online Cross-Sectional Study

Objective: To investigate the uptake and vaccination willingness of the COVID-19 vaccine among Chinese residents and analyze the difference and factors that impact vaccination. Methods: The snowball sampling method was used to distribute online questionnaires. Relevant sociodemographic data along with the circumstances of COVID-19 vaccination were collected from the respondents. The χ2 test, independent samples t test and binary logistic regression analysis were used to analyze the data. Results: Among 786 respondents, 84.22% had been vaccinated. Over 80% of the vaccinated population have completed all the injections because of supporting the national vaccination policies of China, while the unvaccinated population (23.91%) is mainly due to personal health status. Meanwhile, statistical analysis revealed that the main predictors of not being vaccinated were younger age (3 to 18 years old), personal health status, and lower vaccinated proportion of family members and close friends (p < 0.05). Conclusions: There was a high level of uptake of the COVID-19 vaccine in China, and people who have not been vaccinated generally had a low willingness to vaccinate in the future. Based on our results, it suggested the next work to expand the coverage of the COVID-19 vaccination should be concentrated on targeted publicity and education for people who have not been vaccinated.

Cost-Utility of an Online Education Platform and Diabetes Personal Health Record: Analysis Over Ten Years

Background and Aims: My Diabetes My Way (MDMW) is Scotland’s interactive website and mobile app for people with diabetes and their caregivers. It contains multimedia resources for diabetes education and offers access to electronic personal health records. This study aims to assess the cost-utility of MDMW compared with routine diabetes care in people with type 2 diabetes who do not use insulin. Materials and Methods: Analysis used the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model 2. Clinical parameters of MDMW users (n = 2576) were compared with a matched cohort of individuals receiving routine care alone (n = 11 628). Matching criteria: age, diabetes duration, sex, and socioeconomic status. Impact on life expectancy, quality-adjusted life years (QALYs), and costs of treatment and complications were simulated over ten years, including a 10% sensitivity analysis. Results: MDMW cohort: 1670 (64.8%) men; average age 64.3 years; duration of diabetes 5.5 years. 906 (35.2%) women: average age 61.6 years; duration 4.7 years. The cumulative mean QALY (95% CI) gain: 0.054 (0.044-0.062) years. Mean difference in cost: –£118.72 (–£150.16 to –£54.16) over ten years. Increasing MDMW costs (10%): –£50.49 (–£82.24-£14.14). Decreasing MDMW costs (10%): –£186.95 (–£218.53 to –£122.51). Conclusions: MDMW is “dominant” over usual care (cost-saving and life improving) in supporting self-management in people with type 2 diabetes not treated with insulin. Wider use may result in significant cost savings through delay or reduction of long-term complications and improved QALYs in Scotland and other countries. MDMW may be among the most cost-effective interventions currently available to support diabetes.

Integrative adoption model for personal health records: A structural equation modeling approach

The adoption of a personal health record (PHR) is a crucial element in quality healthcare, allowing patients to permit the storage of their health information to create a more inclusive, reliable health record. However, the embracing of PHRs has been slow compared to other healthcare-related systems due to the poor design and behavioral aspects. The objective of this research is to study user acceptance factors to identify a better design for PHR systems and to promote healthy behaviors that support individuals' performance. The study proposes an integrative adoption model for PHRs that integrates theoretical factors from the health belief model with the user acceptance determinants from the technology acceptance model and innovation diffusion theory. Using structural equation modeling with the R “Lavaan” package, the study tested the hypothesis relationships of the constructs. The data were captured from individuals through Amazon’s MTurk. Among the nine relationships studied, the research revealed six significant relationships that inform the final PHR integrative adoption model. The research provides great insights into the factors that influence individuals’ PHR adoption. The results introduce a novel integration model to the current body of knowledge. This model will contribute to a better theoretical understanding of the actual use of healthcare-related technologies and bring greater estimates of patient engagement in healthy activities.