Mobile-accessible personal health records increase the frequency and timeliness of PHR use for patients with diabetes

Impact of encounters on patient app use: results of a tethered mobile personal health record usage pattern analysis

INTRODUCTION

The adoption of tethered mobile personal health records provides not only medical information to patients but also various convenience functions related to hospital use, thereby increasing accessibility to healthcare services and promoting patient engagement. We analyse the tethered mobile personal health records app's usage logs to determine how it can contribute to improving medical service accessibility and patient engagement.

METHODS

Log data, that comprised menu type, log time, and date, were collected from the mobile personal health records app of a tertiary referral hospital. Clinical information, including patients' demographics and visit type, was collected from the clinical research warehouse system. The usage log was analysed in terms of the type of visit, service function, and time period.

RESULTS

Outpatients accounted for 34% of the total app usage and was the most app-accessed visit type. The most utilized menu functions were lab test and visit schedule for visits or non-visits. For Inpatient and Health check-ups, menu usage patterns showed a focus on lab test results. While investigations and other menu usage showed double peaks in the morning and afternoon, peak usage of lab test results correlated with inpatient blood sampling times, which was around 9 am.

DISCUSSION

App menus to access health information, particularly blood tests, emerged as the most accessed menu. Hence, when compared with blood sampling times and hospital information system usage patterns, encounters occurring in the hospital majorly impacted patient app use. For improved patient engagement, improving lab test function should be the priority.

Quality of Care in Hospitals and the Use of Mobile-Based Personal Health Record Applications: An Exploratory Study Using National Hospital Evaluation Data

The use of mobile-based personal health record (m-PHR) applications at the hospital level has been minimally studied. This study aimed to investigate the relationship between m-PHR use and quality of care. A cross-sectional study design was employed, analyzing data from 99 hospitals. Two data sources were utilized: a previous m-PHR investigation conducted from 26 May to 30 June 2022 and a hospital evaluation dataset on quality of care. The use of m-PHR applications was measured by the number of m-PHR application downloads. Three independent variables were assessed: quality of care in the use of antibiotic drugs, injection drugs, and polypharmacy with ≥6 drugs. A generalized linear model was used for the analysis. The hospitals providing high-quality care, as evaluated based on the rate of antibiotic prescription (relative risk [RR], 3.328; 95% confidence interval [CI], 1.840 to 6.020; p < 0.001) and polypharmacy (RR, 2.092; 95% CI, 1.027 to 4.261; p = 0.042), showed an increased number of m-PHR downloads. Among the hospital covariates, public foundation status and being part of multi-hospital systems were associated with the number of m-PHR downloads (p < 0.05). This exploratory study found a positive relationship between quality of care and m-PHR use. Hospitals providing high-quality care may also excel in various activities, including m-PHR application use.

A qualitative study of factors influencing ePHR adoption by caregivers and care providers of Alzheimer's patients: An extension of the unified theory of acceptance and use of technology model

Background and Aims

As the nowadays provision of many healthcare services relies on technology, a better understanding of the factors contributing to the acceptance and use of technology in health care is essential. For Alzheimer's patients, an electronic personal health record (ePHR) is one such technology. Stakeholders should understand the factors affecting the adoption of this technology for its smooth implementation, adoption, and sustainable use. So far, these factors have not fully been understood for Alzheimer's disease (AD)-specific ePHR. Therefore, the present study aimed to understand these factors in ePHR adoption based on the perceptions and views of care providers and caregivers involved in AD care.

Methods

This qualitative study was conducted from February 2020 to August 2021 in Kerman, Iran. Seven neurologists and 13 caregivers involved in AD care were interviewed using semi-structured and in-depth interviews. All interviews were conducted through phone contacts amid Covid-19 imposed restrictions, recorded, and transcribed verbatim. The transcripts were coded using thematic analysis based on the unified theory of acceptance and use of technology (UTAUT) model. ATLAS.ti8 was used for data analysis.

Results

The factors affecting ePHR adoption in our study comprised subthemes under the five main themes of performance expectancy, effort expectancy, social influence, facilitating conditions of the UTAUT model, and the participants' sociodemographic factors. From the 37 facilitating factors and 13 barriers identified for ePHR adoption, in general, the participants had positive attitudes toward the ease of use of this system. The stated obstacles were dependent on the participants' sociodemographic factors (such as age and level of education) and social influence (including concern about confidentiality and privacy). In general, the participants considered ePHRs efficient and useful in increasing neurologists' information about their patients and managing their symptoms in order to provide better and timely treatment.

Conclusion

The present study gives a comprehensive insight into the acceptance of ePHR for AD in a developing setting. The results of this study can be utilized for similar healthcare settings with regard to technical, legal, or cultural characteristics. To develop a useful and user-friendly system, ePHR developers should involve users in the design process to take into account the functions and features that match their skills, requirements, and preferences.

Hospitals' Adoption of Mobile-Based Personal Health Record Systems and Patients' Characteristics: A Cross-Sectional Study Analyzing National Healthcare Big Data

Insufficient information exists on the associations between hospitals' adoption of mobile-based personal health record (mPHR) systems and patients' characteristics. This study explored the associations between patients' characteristics and hospitals' adoption of mPHR systems in Korea. This cross-sectional study used 316 hospitals with 100 or more beds as the unit of analysis. Previously collected data on mPHR adoption from May 1 to June 30, 2020 were analyzed. National health insurance claims data for 2019 were also used to analyze patients' characteristics. The dependent variable was mPHR system adoption (0 vs 1) and the main independent variables were the number of patients, age distribution, and proportions of patients with cancer, diabetes, and hypertension among inpatients and outpatients. The number of inpatients was significantly associated with mPHR adoption (adjusted odds ratio [aOR]: 1.174; 1.117-1.233, P < .001), as was the number of outpatients (aOR: 1.041; 1.028-1.054, P < .001). The proportion of inpatients aged 31 to 60 years to those aged 31 years and older was also associated with hospital mPHR adoption (aOR: 1.053; 1.022-1.085, P = .001). mPHR system adoption was significantly associated with the proportion of inpatients (aOR: 1.089; 1.012-1.172, P = .024) and outpatients (aOR: 1.138; 1.026-1.263, P = .015) with cancer and outpatients (aOR: 1.271; 1.101-1.466, P = .001) with hypertension. Although mPHR systems are useful for the management of chronic diseases such as diabetes and hypertension, the number of patients, younger age distribution, and the proportion of cancer patients were closely associated with hospitals' introduction of mPHR systems.

The Role of Access Type and Age Group in the Breadth of Use of Patient Portals: Observational Study

BACKGROUND

Health care delivery and patient satisfaction are improved when patients engage with their medical information through patient portals. Despite their wide availability and multiple functionalities, patient portals and their functionalities are still underused.

OBJECTIVE

We seek to understand factors that lead to patient engagement through multiple portal functionalities. We provide recommendations that could lead to higher patients' usage of their portals.

METHODS

Using data from the Health Information National Trends Survey 5, Cycle 3 (N=2093), we performed descriptive statistics and used a chi-square test to analyze the association between the demographic variables and the use of mobile health apps for accessing medical records. We further fitted a generalized linear model to examine the association between access type and the use of portal functionalities. We further examined the moderation effects of age groups on the impact of access type on portal usage.

RESULTS

Our results show that accessing personal health records using a mobile health app is positively associated with greater patient usage of access capabilities (β=.52; P<.001), patient-provider interaction capabilities (β=.24, P=.006), and patient-personal health information interaction capabilities (β=.23, P=.009). Patients are more likely to interact with their records and their providers when accessing their electronic medical records using a mobile health app. The impacts of mobile health app usage fade with age for tasks consisting of viewing, downloading, and transmitting medical results to a third party (β=-.43, P=.005), but not for those involving patient-provider interaction (β=.05, P=.76) or patient-personal health information interaction (β=-.15, P=.19).

CONCLUSIONS

These findings provide insights on how to increase engagement with diverse portal functionalities for different age groups and thus improve health care delivery and patient satisfaction.

Tablet distribution to veterans: an opportunity to increase patient portal adoption and use

OBJECTIVE

Examine whether distribution of tablets to patients with access barriers influences their adoption and use of patient portals.

MATERIALS AND METHODS

This retrospective cohort study included Veterans Affairs (VA) patients (n = 28 659) who received a VA-issued tablet between November 1, 2020 and April 30, 2021. Tablets included an app for VA's My HealtheVet (MHV) portal. Veterans were grouped into 3 MHV baseline user types (non-users, inactive users, and active users) based on MHV registration status and feature use pre-tablet receipt. Three multivariable models were estimated to examine the factors predicting (1) MHV registration among non-users, (2) any MHV feature use among inactive users, and (3) more MHV use among active users post-tablet receipt. Differences in feature use during the 6 months pre-/post-tablet were examined with McNemar chi-squared tests of proportions.

RESULTS

In the 6 months post-tablet, 1298 (8%) non-users registered for MHV, 525 (24%) inactive users used at least one MHV feature, and 4234 (46%) active users increased feature use. Across veteran characteristics, there were differences in registration and feature use post-tablet, particularly among older adults and those without prior use of video visits (P < .01). Among active users, use of all features increased during the 6 months post-tablet, with the greatest differences in viewing prescription refills and scheduling appointments (P < .01).

CONCLUSION

Providing patients who experience barriers to in-person care with a portal-enabled device supports engagement in health information and management tasks. Additional strategies are needed to promote registration and digital inclusion among inactive and non-users of portals.

What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review

Background: Despite the growing popularity of mobile app interventions, specific engagement components of mobile apps have not been well studied. Methods: The objectives of this scoping review are to determine which components of mobile health intervention apps encouraged or hindered engagement, and examine how studies measured engagement. Results: A PubMed search on March 5, 2020 yielded 239 articles that featured the terms engagement, mobile app/mobile health, and adult. After applying exclusion criteria, only 54 studies were included in the final analysis. Discussion: Common app components associated with increased engagement included: personalized content/feedback, data visualization, reminders/push notifications, educational information/material, logging/self-monitoring functions, and goal-setting features. On the other hand, social media integration, social forums, poor app navigation, and technical difficulties appeared to contribute to lower engagement rates or decreased usage. Notably, the review revealed a great variability in how engagement with mobile health apps is measured due to lack of established processes. Conclusion: There is a critical need for controlled studies to provide guidelines and standards to help facilitate engagement and its measurement in research and clinical trial work using mobile health intervention apps.

Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs

Patient-generated health data (PGHD) can be managed easily by a mobile personal health record (mPHR) and can increase patient engagement. This study investigated the effect of PGHD functions on mPHR usage. We collected usage log data from an mPHR app, My Chart in My Hand (MCMH), for seven years. We analyzed the number of accesses and trends for each menu by age and sex according to the version-up. Generalized estimating equation (GEE) analysis was used to determine the likelihood of continuous app usage according to the menus and version-up. The total number of users of each version were 15,357 and 51,553, respectively. Adult females under 50 years were the most prevalent user group (30.0%). The “My Chart” menu was the most accessed menu, and the total access count increased by ~10 times after the version-up. The “Health Management” menu designed for PGHD showed the largest degree of increase in its likelihood of continuous usage after the version-up (1.245; p < 0.0001) across menus (range: 0.925–1.050). Notably, improvement of PGHD management in adult females over 50 years is needed.

Clinician experience with telemedicine at a safety-net hospital network during COVID-19: a cross-sectional survey

Objective

The COVID-19 pandemic prompted unprecedented expansion of telemedicine services. We sought to describe clinician experiences providing telemedicine to publicly-insured, low-income patients during COVID-19.

Methods

Online survey of ambulatory clinicians in an urban safety-net hospital system, conducted May 28 2020-July 14 2020.

Results

Among 311 participants (response rate 48.3%), 34.7% (N=108/311) practiced in primary/urgent care, 37.0% (N=115/311) medical specialty and 7.7% (N=24/311) surgical clinics. 87.8% (273/311) had conducted telephone visits, 26% (81/311) video. Participants reported observing both technical and non-technical patient barriers. Clinicians reported concerns about the diagnostic safety of telephone (58.9%, 129/219) vs video (35.3%, 24/68). However, clinician comfort with telemedicine was high (89.3% (216/242) for telephone, 91.0% (61/67) for video), with many clinicians (220/239 or 92.1% telephone, 60/66 or 90.9% video) planning to continue telemedicine after COVID-19.

Conclusions

Clinicians in a safety-net healthcare system report high comfort with and intention to continue telemedicine after the pandemic, despite patient challenges and safety concerns.

Homeless Vulnerability During an Opioid Epidemic: Assessing the Mortality Risk Among People Experiencing Homelessness in Southern Californai

People experiencing homelessness suffer from a risk of mortality three to four times that of the general population, with drug-induced overdose replacing HIV as the emerging epidemic. This study assessed markers of mortality among people experiencing homelessness (N=157) in Orange County, CA during the Fall of 2016. We utilized the Vulnerability Index, an eight-question survey, to identify factors that may affect mortality risk among individuals experiencing homelessness and included two additional questions to identify potential risk of drug-induced overdose. Eighty-three percent of participants reported more than one heightened mortality risk marker and 64% may be at higher risk of drug-induced overdose. Given the state of the opioid epidemic, there is pressing need to couple public health interventions targeting people experiencing homelessness with harm reduction efforts including naloxone distribution (opioid-induced overdose reversal medication) and syringe exchange programs.

Interventions to increase patient portal use in vulnerable populations: a systematic review

BACKGROUND

More than 100 studies document disparities in patient portal use among vulnerable populations. Developing and testing strategies to reduce disparities in use is essential to ensure portals benefit all populations.

OBJECTIVE

To systematically review the impact of interventions designed to: (1) increase portal use or predictors of use in vulnerable patient populations, or (2) reduce disparities in use.

MATERIALS AND METHODS

A librarian searched Ovid MEDLINE, EMBASE, CINAHL, and Cochrane Reviews for studies published before September 1, 2018. Two reviewers independently selected English-language research articles that evaluated any interventions designed to impact an eligible outcome. One reviewer extracted data and categorized interventions, then another assessed accuracy. Two reviewers independently assessed risk of bias.

RESULTS

Out of 18 included studies, 15 (83%) assessed an intervention's impact on portal use, 7 (39%) on predictors of use, and 1 (6%) on disparities in use. Most interventions studied focused on the individual (13 out of 26, 50%), as opposed to facilitating conditions, such as the tool, task, environment, or organization (SEIPS model). Twelve studies (67%) reported a statistically significant increase in portal use or predictors of use, or reduced disparities. Five studies (28%) had high or unclear risk of bias.

CONCLUSION

Individually focused interventions have the most evidence for increasing portal use in vulnerable populations. Interventions affecting other system elements (tool, task, environment, organization) have not been sufficiently studied to draw conclusions. Given the well-established evidence for disparities in use and the limited research on effective interventions, research should move beyond identifying disparities to systematically addressing them at multiple levels.

Analysis of Platforms and Functions of Mobile-Based Personal Health Record Systems

OBJECTIVES

Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems.

METHODS

The unit of analysis was general hospitals with more than 100 beds. This study was based on a PHR survey conducted from May 1 to June 30, 2020 and the National Health Insurance administrative data as of March 31, 2020. The study considered the platform, Android and iPhone operation system (iOS), and types of functionalities of PHR systems. Among the 316 target hospitals, 103 hospitals had adopted PHR systems. A logistic regression analysis was used.

RESULTS

This study found that 103 hospitals had adopted mobile-based PHR systems for their patients. Sixty-four hospitals (62.1%) were adopting both Android and iOS, but 36 (35.0%) and 3 (2.9%) hospitals were adopting Android only or iOS only, respectively. The PHR systems of hospitals adopting both platforms were more likely to have functions for viewing prescriptions, clinical diagnostic test results, and upcoming appointment status compared to those adopting a single platform (p < 0.001). The number of beds (odds ratio [OR] = 1.004; confidence interval [CI], 1.001-1.007; p = 0.0029) and the number of computed tomography systems (CTs) per 100 beds (OR = 6.350; CI, 1.006-40.084; p = 0.0493) were significantly associated with the adoption of both platforms.

CONCLUSIONS

More than 60% of hospitals had adopted both Android and iOS platforms for their patients in Korea. Hospitals adopting both platforms had additional functionalities and significant association with the number of beds and CTs.

Association of Mobile Patient Portal Access With Diabetes Medication Adherence and Glycemic Levels Among Adults With Diabetes

IMPORTANCE

Online patient portals support self-management, and mobile devices expand portal access, but whether this translates to improvements in diabetes outcomes is unclear.

OBJECTIVE

To examine the association of adding mobile patient portal access with diabetes medication adherence and glycemic levels among adults with diabetes.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included patients with diabetes treated at Kaiser Permanente Northern California, a large, integrated health care delivery system, from April 1, 2015, to December 31, 2017. Inclusion criteria were adults with diabetes with an oral diabetes prescription at baseline and no insulin use. Data were analyzed from March 2018 to March 2019.

EXPOSURES

Patient portal access status for each calendar month from April 2015 to December 2017, categorized as never used, used from a computer only, used from a mobile device only, or used from both computer and mobile device.

MAIN OUTCOMES AND MEASURES

Medication adherence, measured by monthly percentage of days covered (PDC), and glycemic levels, measured by changes in glycated hemoglobin A1c (HbA1c) levels. The association of portal access with study outcomes was assessed using linear regression with patient-level fixed effects and adjusting for time-changing variables, stratified by baseline HbA1c level.

RESULTS

Among 111 463 included patients (mean [SD] age, 63.79 [12.93] years; 59 918 [53.76%] men), the number of patients using the portal from both a computer and mobile device increased over time from 38 371 patients (34.42%) in April 2015 to 57 920 patients (61.71%) in December 2017. Among patients with no prior portal access, adding computer-only portal access was associated with an increase in PDC of 1.16 (95% CI, 0.63 to 1.70) percentage points and a change of -0.06 (95% CI, -0.08 to -0.03) percentage points in HbA1c level, and adding both mobile and computer portal access was associated with an increase in PDC of 1.67 (95% CI, 1.10 to 2.23) percentage points and a change of -0.13 (95% CI, -0.16 to -0.10) percentage points in HbA1c level. Among patients with higher baseline HbA1c level (>8.0%), changing from no portal access to both computer and mobile access was associated with an increase in PDC of 5.09 (95% CI, 3.78 to 6.40) percentage points and a change of -0.19 (95% CI, -0.27 to -0.15) percentage points in HbA1c level.

CONCLUSIONS AND RELEVANCE

These findings suggest that providing patients with computer patient portal access and combining it with mobile patient portal access are associated with significantly improved diabetes medication adherence and glycemic control, with greater benefits among patients with more clinical need. Convenient access to portal self-management tools through a mobile device could significantly improve diabetes management.

Parents' Use of Technologies for Health Management: A Health Literacy Perspective

OBJECTIVE

Parent use of technology to manage child health issues has the potential to improve access and health outcomes. Few studies have examined how parent health literacy affects usage of Internet and cell phone technologies for health management.

METHODS

Cross-sectional analysis of data collected as part of a randomized controlled experiment in 3 urban pediatric clinics. English- and Spanish-speaking parents (n = 858) of children ≤8 years answered questions regarding use of and preferences related to Internet and cell phone technologies. Parent health literacy was measured using the Newest Vital Sign.

RESULTS

The majority of parents were high Internet (70.2%) and cell phone (85.1%) users (multiple times a day). A total of 75.1% had limited health literacy (32.1% low, 43.0% marginal). Parents with higher health literacy levels had greater Internet and cell phone use (adequate vs low: adjusted odds ratio [AOR], 1.7 [confidence interval, 1.2-2.5]) and were more likely to use them for health management (AOR, 1.5 [confidence interval, 1.2-1.8]); those with higher health literacy levels were more likely to use the Internet for provider communication (adequate vs marginal vs low: 25.0% vs 18.0% vs 12.0%, P = .001) and health-related cell phone apps (40.6% vs 29.7% vs 16.4%, P < .001). Overall preference for using technology for provider communication was high (∼70%) and did not differ by health literacy, although Internet and cell phone apps were preferred by higher literacy parents; no differences were seen for texting.

CONCLUSIONS

Health literacy-associated disparities in parent use of Internet and cell phone technologies exist, but parents' desire for use of these technologies for provider communication was overall high and did not differ by health literacy.