Personal Health Records: A Systematic Literature Review

Population Digital Health: Continuous Health Monitoring and Profiling at Scale

UNSTRUCTURED

Our article provides a viewpoint on population digital health - the use of digital health information sourced from Health IoT and wearable devices for population health modeling - as an emerging research initiative for offering an integrated approach for continuous monitoring and profiling of diseases and health conditions at multiple spatial resolutions. Global healthcare systems are increasingly challenged by rising costs as life expectancy and the average age of people increases. Population digital health looks at how wearables, IoT, and AI can offer an alternative approach for understanding health issues within the population, significantly reducing cost and improving the completeness of information collection by current practices, such as electronic health records - including integration with mhealth personal health records - or survey instruments. This significantly improves our collective understanding of public health priorities, including factors affecting disease prevalence, occurrence and risk factors, ultimately helping to design targeted programmatic interventions apt at reducing the cost of healthcare provision and leading to better life quality, also reducing disparities. Realizing this vision requires overcoming several unique challenges, including data quality, availability, sparsity, and social and technical barriers in the use of health technologies. Our article highlights these challenges and offers solutions and empirical evidence to demonstrate how these challenges can be addressed. As population digital health addresses the impact large-scale sensor data collection and AI can have on improving healthcare delivery and society, we sincerely believe the topic is well within the journal's scope and would be highly interesting to its readership. Our experiments using a combination of real-world health IoT data and electronic health records also highlight the potential cross-disciplinary benefits of population digital health and challenge the research community to address the vision and challenges. Therefore, our article serves the dual purpose of challenging the research community and offering insights into the use of AI and sensor data, and how population digital health can serve as a catalyst for further research by the broader research community.

Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model

Introduction

Chronic diseases are the leading causes of death in the world. In sub-Saharan Africa, it leads to more mortality than almost every other region in the world. Currently, digital health technology like personal health records plays a crucial role in managing patients with chronic diseases. In low-resource countries like Ethiopia, it is uncertain how many chronic patients intend to use PHRs and the accompanying circumstances. Hence, the aim of this study was to assess chronic patients' intention to use PHRs and its predictors enrolled in public health hospitals in Bahir Dar city, northwest Ethiopia.

Method

An institutional-based cross-sectional study was conducted among 924 respondents from April 5 to May 9, 2023, in Bahir-Dar city public hospitals. A stratified sampling technique followed by a systematic sampling technique was applied to select the study participants. An interviewer-administrated questionnaire was conducted using Kobo Collect. A UTAUT2 model was applied to develop theoretical frameworks. SPSS version 25 software was used to estimate the descriptive statistics, and the structural equation model analysis was used to evaluate model constructs using AMOS version 21 software.

Results

In this study, a total of 908 study subjects participated. The proportion of chronic patients' intention to use PHR was 46.7% [95.0% CI (43.4-50.1)]. According to the findings, performance expectancy (β = 0.259, p-value <0.001), effort expectancy (β = 0.214, p-value <0.001), social influence (β = 0.174, p-value <0.001), and facilitating condition (β = 0.114, p-value <0.01) had a significant effect on the intention to use PHRs.

Conclusion

Generally, the overall intention to use PHR was low. Our finding illustrates that the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions had a positive effect on patients' intentions to use PHRs. The effect of effort expectancy on the intention to use a PHR was positively moderated by age. Since the findings of this study would help policymakers and programmers to future academics interested in this area and insight to future research workers. Therefore, implementers should focus on improving patient capacity, motivating users, and raising awareness regarding PHR.

Toward Personalized Care and Patient Empowerment and Perspectives on a Personal Health Record in Hemophilia Care: Qualitative Interview Study

BACKGROUND

To enable personalized treatment and shared decision-making in chronic care, relevant health information is collected. However, health information is often fragmented across hospital information systems, digital health apps, and questionnaire portals. This also pertains to hemophilia care, in which scattered information hampers integrated care. We intend to co-design a nationwide digital personal health record (PHR) for patients to help manage their health information. For this, user perspectives are crucial.

OBJECTIVE

This study aims to assess patients' and health care providers' perspectives regarding the use of a PHR in hemophilia care in the Netherlands, required functionalities, and expectations and concerns.

METHODS

In this semistructured interview study, 19 pediatric and adult persons with hemophilia, parents, and women with other inherited bleeding disorders, as well as 18 health care providers working within and outside of hemophilia treatment centers, participated. Perspectives of patients and providers were explored separately. To explore requirements, participants were asked to prioritize functionalities.

RESULTS

Participants expected a PHR would increase the transparency of health information, improve patients' understanding of their illness, and help the coordination of care between health care providers and institutions. Prioritized functionalities included the integration of relevant health information and patient-entered data. Formulated expectations and concerns focused on 4 themes: usability, safety, inclusiveness, and implementation. While patients expressed worries over medicalization (ie, more confrontational reminders of their illness), providers were concerned about an increased workload.

CONCLUSIONS

People with hemophilia, their parents, and health care providers welcomed the development of a PHR, as they expected it would result in better coordinated care. Formulated expectations and concerns will contribute to the successful development of a PHR for persons with hemophilia, and ultimately, for all persons with a chronic condition.

The feasibility and usability of a personal health record for patients with multiple sclerosis: a 2-year evaluation study

Background

Multiple sclerosis (MS) is a persistent inflammatory condition impacting the brain and spinal cord, affecting globally approximately 2.8 million individuals. Effective self-management plays a crucial role in the treatment of chronic diseases, including MS, significantly influencing health outcomes. A personal health record (PHR) is a promising tool to support self-management, potentially empowering patients and enhancing their engagement in treatment and health. Despite these promising aspects, challenges in implementation persist and PHRs are still a relatively new concept undergoing rapid development.

Objective

This study aimed to assess the feasibility and usability of the PHR. Secondary objectives included evaluating implementation determinants, and exploring preliminary effects on quality of care for both patients and healthcare professionals (HCPs), self-management, self-efficacy for patients, job satisfaction, efficiency, and demand for HCPs, and preliminary effects on costs and health-related quality of life.

Methods

This study had a mixed-methods design. Quantitative data of patients (n = 80) and HCPs (n = 12) were collected via self-reported questionnaires at baseline (T0), after one year (T1), and after two years (T2). One focus group interview was conducted at T2 with patients (n = 7), and another one with HCPs (n = 4), to get a more in-depth understanding of the feasibility and usability of the PHR via the Unified Theory of Acceptance and Use of Technology framework, and to further explore the secondary objectives in-depth.

Results

Most patients never logged in during the first year and logged in a couple of times per year during the second year, averaging around 15 min per log-in session. The HCPs mainly logged in a couple of times per year over the two years with an average use of six minutes per session. Patient usability and satisfaction scores were below average and moderate, respectively: with SUS-scores of 59.9 (SD = 14.2, n = 33) at T1 and 59.0 (SD = 16.3, n = 37) at T2, and CSQ-8 scores of 21.4 (SD = 5.0, n = 34) at T1, and 22.1 (SD = 5.0, n = 39) at T2. HCPs had similar usability and satisfaction scores. Multiple facilitators and barriers were identified by both patients and HCPs, such as (in)sufficient knowledge of how to use the PHR, lack of staff capacity and ICT obstacles. No significant differences were found in the preliminary effects. Qualitative data showed, among others, that both patients and HCPs saw the benefit of the PHR in terms of performance expectancy, by gaining more insight into health and health data, but challenges remained regarding effort expectancy, such as log-in issues and experiencing difficulties with information retrieval.

Conclusion

The feasibility and usability were considered moderate by patients and HCPs; however, potential regarding the performance of the PHR was observed. Implementation challenges, such as the complexity of usage, lowered the adoption of the PHR. The evolving nature of PHRs requires ongoing evaluation and adaptation to optimize their potential benefits. Utilizing a participatory design approach and a dedicated implementation team could help in achieving this optimization, ultimately enhancing their adoption.

Using an mHealth approach to collect patient-generated health data for predicting adverse health outcomes among adult survivors of childhood cancer

Introduction

Cancer therapies predispose childhood cancer survivors to various treatment-related late effects, which contribute to a higher symptom burden, chronic health conditions (CHCs), and premature mortality. Regular monitoring of symptoms between clinic visits is useful for timely medical consultation and interventions that can improve quality of life (QOL). The Health Share Study aims to utilize mHealth to collect patient-generated health data (PGHD; daily symptoms, momentary physical health status) and develop survivor-specific risk prediction scores for mitigating adverse health outcomes including poor QOL and emergency room admissions. These personalized risk scores will be integrated into the hospital-based electronic health record (EHR) system to facilitate clinician communications with survivors for timely management of late effects.

Methods

This prospective study will recruit 600 adult survivors of childhood cancer from the St. Jude Lifetime Cohort study. Data collection include 20 daily symptoms via a smartphone, objective physical health data (physical activity intensity, sleep performance, and biometric data including resting heart rate, heart rate variability, oxygen saturation, and physical stress) via a wearable activity monitor, patient-reported outcomes (poor QOL, unplanned healthcare utilization) via a smartphone, and clinically ascertained outcomes (physical performance deficits, onset of/worsening CHCs) assessed in the survivorship clinic. Participants will complete health surveys and physical/functional assessments in the clinic at baseline, 2) report daily symptoms, wear an activity monitor, measure blood pressure at home over 4 months, and 3) complete health surveys and physical/functional assessments in the clinic 1 and 2 years from the baseline. Socio-demographic and clinical data abstracted from the EHR will be included in the analysis. We will invite 20 cancer survivors to investigate suitable formats to display predicted risk information on a dashboard and 10 clinicians to suggest evidence-based risk management strategies for adverse health outcomes.

Analysis

Machine and statistical learning will be used in prediction modeling. Both approaches can handle a large number of predictors, including longitudinal patterns of daily symptoms/other PGHD, along with cancer treatments and socio-demographics.

Conclusion

The individualized risk prediction scores and added communications between providers and survivors have the potential to improve survivorship care and outcomes by identifying early clinical presentations of adverse events.

Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study

Rheumatoid arthritis causes joint inflammation due to immune abnormalities, resulting in joint pain and swelling. In recent years, there have been considerable advancements in the treatment of this disease. However, only approximately 60% of patients achieve remission. Patients with multifactorial diseases shift between states from day to day. Patients may remain in a good or poor state with few or no transitions, or they may switch between states frequently. The visualization of time-dependent state transitions, based on the evaluation axis of stable/unstable states, may provide useful information for achieving rheumatoid arthritis treatment goals. Energy landscape analysis can be used to quantitatively determine the stability/instability of each state in terms of energy. Time-series clustering is another method used to classify transitions into different groups to identify potential patterns within a time-series dataset. The objective of this study was to utilize energy landscape analysis and time-series clustering to evaluate multidimensional time-series data in terms of multistability. We profiled each patient's state transitions during treatment using energy landscape analysis and time-series clustering. Energy landscape analysis divided state transitions into two patterns: "good stability leading to remission" and "poor stability leading to treatment dead-end." The number of patients whose disease status improved increased markedly until approximately 6 months after treatment initiation and then plateaued after 1 year. Time-series clustering grouped patients into three clusters: "toward good stability," "toward poor stability," and "unstable." Patients in the "unstable" cluster are considered to have clinical courses that are difficult to predict; therefore, these patients should be treated with more care. Early disease detection and treatment initiation are important. The evaluation of state multistability enables us to understand a patient's current state in the context of overall state transitions related to rheumatoid arthritis drug treatment and to predict future state transitions.

Knowledge, Attitudes, and Practices about Electronic Personal Health Records: A Cross-Sectional Study in a Region of Northern Italy

The Electronic Personal Health Record (EPHR) provides an innovative service for citizens and professionals to manage health data, promoting patient-centred care. It enhances communication between patients and physicians and improves accessibility to documents for remote medical information management. The study aims to assess the prevalence of awareness and acceptance of the EPHR in northern Italy and define determinants and barriers to its implementation. In 2022, a region-wide cross-sectional study was carried out through a paper-based and online survey shared among adult citizens. Univariable and multivariable regression models analysed the association between the outcome variables (knowledge and attitudes toward the EPHR) and selected independent variables. Overall, 1634 people were surveyed, and two-thirds were aware of the EPHR. Among those unaware of the EPHR, a high prevalence of specific socio-demographic groups, such as foreign-born individuals and those with lower educational levels, was highlighted. Multivariable regression models showed a positive association between being aware of the EPHR and educational level, health literacy, and perceived poor health status, whereas age was negatively associated. A higher knowledge of the EPHR was associated with a higher attitude towards the EPHR. The current analysis confirms a lack of awareness regarding the existence of the EPHR, especially among certain disadvantaged demographic groups. This should serve as a driving force for a powerful campaign tailored to specific categories of citizens for enhancing knowledge and usage of the EPHR. Involving professionals in promoting this tool is crucial for helping patients and managing health data.

Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence

With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unprecedented speed and scale every day. For the first time, these multi-modal biomedical data are able to make precision medicine close to a reality. However, due to data volume and the complexity, making good use of these multi-modal biomedical data requires major effort. Researchers and clinicians are actively developing artificial intelligence (AI) approaches for data-driven knowledge discovery and causal inference using a variety of biomedical data modalities. These AI-based approaches have demonstrated promising results in various biomedical and healthcare applications. In this review paper, we summarize the state-of-the-art AI models for integrating multi-omics data and electronic health records (EHRs) for precision medicine. We discuss the challenges and opportunities in integrating multi-omics data with EHRs and future directions. We hope this review can inspire future research and developing in integrating multi-omics data with EHRs for precision medicine.

Adoption of Electronic Medical Records for Chronic Disease Care in Kenyan Refugee Camps: Quantitative and Qualitative Prospective Evaluation

Background

Noncommunicable disease (NCD) prevention and control in humanitarian emergencies is a well-recognized need, but there is little evidence to guide responses, leading to varying care delivery. The Sana.NCD mobile health (mHealth) app, initially developed in Lebanon, is the only known mHealth tool for NCD management designed to increase care quality and coverage for providers in humanitarian settings.

Objective

We evaluated a specialized mHealth app consisting of an abbreviated medical record for patients with hypertension or diabetes, adapted for a Kenyan refugee camp setting.

Methods

We tested an adapted version of the Sana.NCD app (diabetes and hypertension medical record) in an 11-month (May 2021 to March 2022) quantitative and qualitative prospective evaluation in Kenya's Hagadera refugee camp. Leveraging the rollout of a general electronic medical record (EMR) system in the Kakuma refugee camp, we compared a specialized NCD management app to a general EMR. We analyzed secondary data collected from the Sana.NCD app for 1539 patients, EMR data for 68 patients with NCD from Kakuma's surgical and outpatient departments, and key informant interviews that focused on Hagadera clinic staff perceptions of the Sana.NCD app.

Results

The Hagadera NCD clinic reported 18,801 consultations, 42.1% (n=7918) of which were reported in the NCD app. The Kakuma EMR reported 350,776 visits, of which 9385 (2.7%) were for NCDs (n=4264, 1.2% hypertension; n=2415, 0.7% diabetes). The completeness of reporting was used as a quality-of-care metric. Age, sex, prescribed medicines, random blood sugar, and smoking status were consistently reported in both the NCD app (>98%) and EMR (100%), whereas comorbidities, complications, hemoglobin A1c, and diet were rarely reported in either platform (≤7% NCD app; 0% EMR). The number of visits, BMI, physical activity, and next visit were frequently reported in the NCD app (≥99%) but not in the EMR (≤15%). In the NCD app, the completeness of reporting was high across the implementation period, with little meaningful change. Although not significantly changed during the study, elevated blood sugar (P=.82) and blood pressure (P=.12) were reported for sizable proportions of patients in the first (302/481, 62.8%, and 599/1094, 54.8%, respectively) and last (374/602, 62.1%, and 720/1395, 51.6%, respectively) study quarters. Providers were satisfied with the app, as it standardized patient information and made consultations easier. Providers also indicated that access to historic patient information was easier, benefiting NCD control and follow-up.

Conclusions

A specialized record for NCDs outperformed a more general record intended for use in all patients in terms of reporting completeness. This CommCare-based NCD app can easily be rolled out in similar humanitarian settings with minimal adaptation. However, the adaptation of technologies to the local context and use case is critical for uptake and ensuring that workflows and time burden do not outweigh the benefits of EMRs.

Personal Health Record (PHR) Experience and Recommendations for a Transformation in Saudi Arabia

A Personal Health Record (PHR) is a patient-managed platform for health data. Most hospitals provide a PHR as an extension of the Electronic Medical Record (EMR). However, there are unresolved issues around the adoption rate, functionalities, barriers and, more importantly, the impact of the PHR on patients' health. A cross-sectional, survey-based descriptive study was conducted in which patients from four main tertiary hospitals in Saudi Arabia were targeted from September 2022 to February 2023. The survey was tested and validated to address the objectives of the study. The survey covered components related to intention to use the PHR, required functions, obstacles and expected outcomes. This study involved 396 participants from the top four hospitals. It was discovered that the majority of them had intentions to use the PHR (93%) and believed it to be useful (94%) and easy to use (94%). It was widely agreed that accessing medical records (77%), scheduling appointments (88%), renewing medication (90%), tracking patient data (70%) and receiving personalized education (78%) were essential aspects of the PHR. Furthermore, the survey revealed that 54% of respondents saw a positive effect on their health status. A significant number of participants, around 54%, expressed concerns about the privacy of their PHR, and 46% reported concerns about the accuracy of their information. The study found that demographic factors and the type of hospital did not have a statistically significant association with the intention to use the PHR. Our findings showed that there were no significant barriers to adopting the PHR. Additionally, we found that less than half of the participants believed that their current PHR helped them to improve their health. This highlights the need for healthcare organizations to focus on improving the PHR's functionality and overall purpose. Instead of simply providing basic features, the PHR should allow patients to manage their health information comprehensively, including compiling information from hospitals and patient-generated data. Having a PHR is crucial in improving an individual's overall health. As technology advances, more data are being generated that should be included in the PHR to ensure an accurate and comprehensive view of the patient's health. Expanding the scope of the PHR to include capabilities beyond merely hospital data is important. Achieving this requires an open and honest discussion about the role of the PHR, potential obstacles and how to coordinate efforts among different stakeholders.

Wearable Technologies and AI at the Far Edge for Chronic Heart Failure Prevention and Management: A Systematic Review and Prospects

Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors.

Patient and provider perspectives of personal health record use: a multisite qualitative study in HIV care settings

Use of tethered personal health records (PHRs) can streamline care, reduce unnecessary care utilization, and improve health outcomes for people living with human immunodeficiency virus (HIV). Providers play a role in influencing patients' decision to adopt and use PHRs. To explore patient and provider acceptance and use of PHRs in an HIV care setting. We used a qualitative study design guided by the Unified Theory of Acceptance and Use of Technology. Participants included providers of HIV care, patients living with HIV, and PHR coordinating and support staff in the Veterans Health Administration (VA). Interviews were analyzed using directed content analysis. We interviewed providers (n = 41), patients living with HIV (n = 60), and PHR coordinating and support staff (n = 16) at six VA Medical Centers between June and December 2019. Providers perceived PHR use could enhance care continuity, appointment efficiency, and patient engagement. Yet, some expressed concerns that patient PHR use would increase provider workload and detract from clinical care. Concerns about poor PHR interoperability with existing clinical tools further eroded acceptance and use of PHRs. PHR use can enhance care for patients with HIV and other complex, chronic conditions. Negative provider attitudes toward PHRs may impact providers' encouragement of use among patients, consequently limiting patient uptake. Multipronged interventions at the individual, institutional, and system level are needed to enhance PHR engagement among both providers and patients.

Factors associated with the download and use of mobile personal health record applications in Korean hospitals

The use of mobile personal health records (m-PHR) has been little studied at the organizational level. This study was to investigate the relationships of various hospital-related factors with m-PHR use in Korean hospitals. Downloads of m-PHR applications for 101 hospitals were examined from May 26 to 30 June 2022. The dependent variable was the number of m-PHR downloads, and the major independent variables included six technological, organizational, and environmental factors. As technological factors, the number of computed tomography and magnetic resonance imagery devices were significantly associated with downloads (RR = 1.119, CI = 1.022-1.226, p = 0.016; and RR = 1.155; 95% CI = 1.024-1.302, p = 0.019, respectively). At the organizational level, the number of physicians, adjusting for the number of beds, and the number of medical information management staff showed significant associations (RR = 1.059, CI = 1.019-1.100, p = 0.004; and RR = 1.026, CI = 1.002-1.050, p = 0.033, respectively). From an environmental standpoint, downloads were positively associated with the proportion of the local population of working age (20-59 years) (RR = 1.102, CI 1.022-1.189, p = 0.012). Healthcare policymakers should pay close attention to these factors to advocate for the widespread use of m-PHR applications.

Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control

Background

"Artificial intelligence" and "big data" increasingly take the step from just being interesting concepts to being relevant or even part of our lives. This general statement holds also true for transfusion medicine. Besides all advancements in transfusion medicine, there is not yet an established red blood cell quality measure, which is generally applied.

Summary

We highlight the usefulness of big data in transfusion medicine. Furthermore, we emphasize in the example of quality control of red blood cell units the application of artificial intelligence.

Key Messages

A variety of concepts making use of big data and artificial intelligence are readily available but still await to be implemented into any clinical routine. For the quality control of red blood cell units, clinical validation is still required.

GradeAid: a framework for automatic short answers grading in educational contexts-design, implementation and evaluation

Automatic short answer grading (ASAG), a hot field of natural language understanding, is a research area within learning analytics. ASAG solutions are conceived to offload teachers and instructors, especially those in higher education, where classes with hundreds of students are the norm and the task of grading (short)answers to open-ended questionnaires becomes tougher. Their outcomes are precious both for the very grading and for providing students with "ad hoc" feedback. ASAG proposals have also enabled different intelligent tutoring systems. Over the years, a variety of ASAG solutions have been proposed, still there are a series of gaps in the literature that we fill in this paper. The present work proposes GradeAid, a framework for ASAG. It is based on the joint analysis of lexical and semantic features of the students' answers through state-of-the-art regressors; differently from any other previous work, (i) it copes with non-English datasets, (ii) it has undergone a robust validation and benchmarking phase, and (iii) it has been tested on every dataset publicly available and on a new dataset (now available for researchers). GradeAid obtains performance comparable to the systems presented in the literature (root-mean-squared errors down to 0.25 based on the specific tuple ⟨ dataset-question⟩ ). We argue it represents a strong baseline for further developments in the field.

The status of patient portal use among Emergency Department patients experiencing houselessness: A large-scale single-center observational study

OBJECTIVE

Patient portal (PP) use has rapidly increased in recent years. However, the PP use status among houseless patients is largely unknown. We aim to determine 1) the PP use status among Emergency Department (ED) patients experiencing houselessness, and 2) whether PP use is linked to the increase in patient clinic visits.

METHODS

This is a single-center retrospective observational study. From March 1, 2019, to February 28, 2021, houseless patients who presented at ED were included. Their PP use status, including passive PP use (log-on only PP) and effective PP use (use PP of functions) was compared between houseless and non-houseless patients. The number of clinic visits was also compared between these two groups. Lastly, a multivariate logistic regression was analyzed to determine the association between houseless status and PP use.

RESULTS

We included a total of 236,684 patients, 13% of whom (30,956) were houseless at time of their encounter. Fewer houseless patients had effective PP use in comparison to non-houseless patients (7.3% versus 11.6%, p < 0.001). In addition, a higher number of clinic visits were found among houseless patients who had effective PP use than those without (18 versus 3, p < 0.001). The adjusted odds ratio of houseless status associated with PP use was 0.48 (95% CI 0.46-0.49, p < 0.001).

CONCLUSIONS

Houselessness is a potential risk factor preventing patient portal use. In addition, using patient portals could potentially increase clinic visits among the houseless patient population.

Healthcare professionals' knowledge, attitude and its associated factors toward electronic personal health record system in a resource-limited setting: A cross-sectional study

Introduction

Electronic personal health record (e-PHR) system enables individuals to access their health information and manage it themselves. It helps patient engagement management of health information that is accessed and shared with their healthcare providers using the platform. This improves individual healthcare through the exchange of health information between patients and healthcare providers. However, less is known about e-PHRs among healthcare professionals.

Objective

Therefore, this study aimed to assess Health professionals' Knowledge and attitude and its associated factors toward e-PHR at the teaching hospital in northwest Ethiopia.

Methods

An institution-based cross-sectional study design was used to determine healthcare professionals' knowledge and attitude and their associated factors toward e-PHR systems in teaching hospitals of Amhara regional state, Ethiopia, from 20 July to 20 August 2022. Pretested structured self-administered questionnaires were used to collect the data. Descriptive statistic was computed based on sociodemographic and other variables presented in the form of table graphs and texts. Bivariable and multivariable logistic analyses were performed with an adjusted odds ratio (AOR) and 95% CI to identify predictor variables.

Result

Of the total study participants, 57% were males and nearly half of the respondents had a bachelor's degree. Out of 402 participants, ~65.7% [61–70%] and 55.5% [50–60%] had good knowledge and favorable attitude toward e-PHR systems, respectively. Having a social media account 4.3 [AOR = 4.3, 95% CI (2.3–7.9)], having a smartphone 4.4 [AOR = 4.4, 95% CI (2.2–8.6)], digital literacy 8.8 [(AOR = 8.8, 95% CI (4.6–15.9)], being male 2.7 [AOR = 2.7, 95% CI (1.4–5.0)], and perceived usefulness 4.5 [(AOR = 4.5, 95% CI (2.5–8.5)] were positively associated with knowledge toward e-PHR systems. Similarly, having a personal computer 1.9 [AOR = 1.9, 95% CI (1.1–3.5)], computer training 3.9 [AOR = 3.9, 95% CI (1.8–8.3)], computer skill 19.8 [AOR = 19.8, 95% CI (10.7–36.9)], and Internet access 6.0 [AOR = 6.0, 95% CI (3.0–12.0)] were predictors for attitude toward e-PHR systems.

Conclusion

The findings from the study showed that healthcare professionals have good knowledge and a favorable attitude toward e-PHRs. Providing comprehensive basic computer training to improve healthcare professionals' expectation on the usefulness of e-PHR systems has a paramount contribution to the advancement of their knowledge and attitude toward successfully implementing e-PHRs.

Automatic documentation of professional health interactions: A systematic review

Electronic systems are increasingly present in the healthcare system and are often related to improved medical care. However, the widespread use of these technologies ended up building a relationship of dependence that can disrupt the doctor-patient relationship. In this context, digital scribes are automated clinical documentation systems that capture the physician-patient conversation and then generate the documentation for the appointment, enabling the physician to engage with the patient entirely. We have performed a systematic literature review on intelligent solutions for automatic speech recognition (ASR) with automatic documentation during a medical interview. The scope included only original research on systems that could detect speech and transcribe it in a natural and structured fashion simultaneously with the doctor-patient interaction, excluding speech-to-text-only technologies. The search resulted in a total of 1995 titles, with eight articles remaining after filtering for the inclusion and exclusion criteria. The intelligent models mainly consisted of an ASR system with natural language processing capability, a medical lexicon, and structured text output. None of the articles had a commercially available product at the time of the publication and reported limited real-life experience. So far, none of the applications has been prospectively validated and tested in large-scale clinical studies. Nonetheless, these first reports suggest that automatic speech recognition may be a valuable tool in the future to facilitate medical registration in a faster and more reliable manner. Improving transparency, accuracy, and empathy could drastically change how patients and doctors experience a medical visit. Unfortunately, clinical data on the usability and benefits of such applications is almost non-existent. We believe that future work in this area is necessary and needed.

The Use of a Technology Acceptance Model (TAM) to Predict Patients' Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability

Personal health records (PHR) systems are designed to ensure that individuals have access and control over their health information and to support them in being active participants rather than passive ones in their healthcare process. Yet, PHR systems have not yet been widely adopted or used by consumers despite their benefits. For these advantages to be realized, adoption of the system is necessary. In this study, we examined how self-determination of health management influences individuals' intention to implement a PHR system, i.e., their ability to actively manage their health. Using an extended technology acceptance model (TAM), the researchers developed and empirically tested a model explaining public adoption of PHRs. In total, 389 Saudi Arabian respondents were surveyed in a quantitative cross-sectional design. The hypotheses were analysed using structural equation modelling-partial least squares (SEM-PLS4). Results indicate that PHR system usage was influenced by three major factors: perceived ease of use (PEOU), perceived usefulness (PU), and security towards intention to use. PHR PEOU and PHR intention to use were also found to be moderated by privacy, whereas usability positively moderated PHR PEOU and PHR intention to use and negatively moderated PHR PU and PHR intention to use. For the first time, this study examined the use of personal health records in Saudi Arabia, including the extension of the TAM model as well as development of a context-driven model that examines the relationship between privacy, security, usability, and the use of PHRs. Furthermore, this study fills a gap in the literature regarding the moderating effects of privacy influence on PEOU and intention to use. Further, the moderating effects of usability on the relationship between PEOU, PU, and intention to use. Study findings are expected to assist government agencies, health policymakers, and health organizations around the world, including Saudi Arabia, in understanding the adoption of personal health records.

A Blockchain-Based End-to-End Data Protection Model for Personal Health Records Sharing: A Fully Homomorphic Encryption Approach

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for processing, storing, and sharing health records. Furthermore, fully homomorphic encryption (FHE) is a set of techniques that allows the calculation of encrypted data, which can help to protect personal privacy in data sharing. In this context, we propose an architectural model that applies a DHT technique called the interplanetary protocol file system and blockchain networks to store and distribute data and metadata separately; two new elements, called data steward and shared data vault, are introduced in this regard. These new modules are responsible for segregating responsibilities from health institutions and promoting end-to-end encryption; therefore, a person can manage data encryption and requests for data sharing in addition to restricting access to data for a predefined period. In addition to supporting calculations on encrypted data, our contribution can be summarized as follows: (i) mitigation of risk to personal privacy by reducing the use of unencrypted data, and (ii) improvement of semantic interoperability among health institutions by using distributed networks for standardized PHR. We evaluated performance and storage occupation using a database with 1.3 million COVID-19 registries, which showed that combining FHE with distributed networks could redefine e-health paradigms.

Effect of Notes' Access and Complexity on OpenNotes' Utility

BACKGROUND

Health care providers are now required to provide their patients access to their consultation and progress notes. Early research of this concept, known as "OpenNotes," showed promising results in terms of provider acceptability and patient adoption, yet objective evaluations relating to patients' interactions with the notes are limited.

OBJECTIVES

To assess the effect of the complexity level of notes and number of accesses (initial read vs. continuous access) on the user's performance, perceived usability, cognitive workload, and satisfaction with the notes.

METHODS

We used a 2*2 mixed subjects experimental design with two independent variables: (1) note's complexity at two levels (simple vs. complex) and (2) number of accesses to notes at two levels (initial vs. continuous). Fifty-three participants were randomly assigned to receive a simple versus complex radiation oncology clinical note and were tested on their performance for understanding the note content after an initial read, and then with continuous access to the note. Performance was quantified by comparing each participant's answers to the ones developed by the research team and assigning a score of 0 to 100 based on participants' understanding of the notes. Usability, cognitive workload, and satisfaction scores of the notes were quantified using validated tools.

RESULTS

Performance for understanding was significantly better in simple versus complex notes with continuous access (p = 0.001). Continuous access to the notes was also positively associated with satisfaction scores (p = 0.03). The overall perceived usability, cognitive workload, and satisfaction scores were considered low for both simple and complex notes.

CONCLUSION

Simplifying notes can improve understanding of notes for patients/families. However, perceived usability, cognitive workload, and satisfaction with even the simplified notes were still low. To make notes more useful for patients and their families, there is a need for dramatic improvements to the overall usability and content of the notes.

Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course

A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to improve medical decision-making. However, there are many challenges and barriers that must be overcome before a DT can be used in health care. In this viewpoint paper, we build on the current literature, address these challenges, and describe a dynamic DT in health care for optimizing individual patient health care journeys, specifically for women at risk for cardiovascular complications in the preconception and pregnancy periods and across the life course. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods that will guide the development of the dynamic DT and implementation strategies in health care.

Public Attitudes Regarding Trade-offs Between the Functional Aspects of a Contact-Confirming App for COVID-19 Infection Control and the Benefits to Individuals and Public Health: Cross-sectional Survey

BACKGROUND

It is expected that personal health information collected through mobile information terminals will be used to develop health strategies that benefit the public. Against this background, several countries have actively attempted to use mobile phones to control infectious diseases. These collected data, such as activity logs and contact history, are countermeasures against diseases such as COVID-19. In Japan, the Ministry of Health, Labor, and Welfare has developed and disseminated a contact-confirming app (COVID-19 Contact-Confirming Application [COCOA]) to the public, which detects and notifies individuals whether they have been near someone who had subsequently tested positive for COVID-19. However, there are concerns about leakage and misuse of the personal information collected by such information terminals.

OBJECTIVE

This study aimed to investigate the possible trade-off between effectiveness in preventing infectious diseases and infringement of personal privacy in COCOA. In addition, we analyzed whether resistance to COCOA would reduce if the app contributed to public health or if a discount was provided on mobile phone charges.

METHODS

A cross-sectional, quantitative survey of Japanese citizens was conducted using Survey Monkey, a general-purpose web-based survey platform. When developing the questions for the questionnaire, we included the installation status of COCOA and recorded the anxiety stemming from the potential leakage or misuse of personal information collected for COVID-19 infection control. The respondents were asked to rate various factors to determine their perceptions on a 5-point scale.

RESULTS

In total, 1058 participants were included in the final analysis. In response to the question of whether the spread of the disease was being controlled by the infection control measures taken by the government, 25.71% (272/1058) of the respondents answered that they strongly agreed or agreed. One-quarter of the respondents indicated that they had already installed COCOA. This study found that the sense of resistance to government intervention was not alleviated by the benefits provided to individuals when using the app. The only factors that were positively associated with the response absolutely opposed to use of the app, even with a discount on mobile phone use charges, were those regarding leaks and misuse of personal information, which was true for all functions (function A: odds ratio [OR] 1.8, 95% CI 1.3-2.4; function B: OR 1.9, 95% CI 1.5-2.6; function C: OR 1.8, 95% CI 1.4-2.4).

CONCLUSIONS

Public organizations need to emphasize the general benefits of allowing them to manage personal information and assure users that this information is being managed safely rather than offering incentives to individuals to provide such personal information. When collecting and using citizens' health information, it is essential that governments and other entities focus on contributing to the public good and ensuring safety rather than returning benefits to individual citizens.

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.

Integration of Artificial Intelligence and Blockchain Technology in Healthcare and Agriculture

Over the last decade, the healthcare sector has accelerated its digitization and electronic health records (EHRs). As information technology progresses, the notion of intelligent health also gathers popularity. By combining technologies such as the internet of things (IoT) and artificial intelligence (AI), innovative healthcare modifies and enhances traditional medical systems in terms of efficiency, service, and personalization. On the other side, intelligent healthcare systems are incredibly vulnerable to data breaches and other malicious assaults. Recently, blockchain technology has emerged as a potentially transformative option for enhancing data management, access control, and integrity inside healthcare systems. Integrating these advanced approaches in agriculture is critical for managing food supply chains, drug supply chains, quality maintenance, and intelligent prediction. This study reviews the literature, formulates a research topic, and analyzes the applicability of blockchain to the agriculture/food industry and healthcare, with a particular emphasis on AI and IoT. This article summarizes research on the newest blockchain solutions paired with AI technologies for strengthening and inventing new technological standards for the healthcare ecosystems and food industry.

Low socioeconomic status worsens access to care and outcomes for rotator cuff repair: a scoping review

Background

Poor socioeconomic status (SES) is consistently associated with poor quality of health care, particularly in the field of orthopedics. Expanding insurance coverage has created a larger patient population by specifically making health care more accessible, translating to greater demand for care in the low-SES population. The purpose of this article is to provide a scoping review of literature observing access and outcomes of rotator cuff repair surgery among low-SES populations.

Methods

We performed a systematic review of articles using PubMed, Embase, and EBSCO (May 2021) from 2010 onward. Peer-reviewed articles that recorded at least one SES measure specific to patients who underwent rotator cuff repair from the United States were included. SES measures were methodically defined as income, occupation, employment, education, and race. All data that aligned with these SES measures were extracted.

Results

Of the 1009 titles reviewed, 109 studies were screened by abstract, 23 were reviewed in full, and 7 studies met criteria for inclusion. Of the 5 studies investigating access, all 5 found disparities among postoperative physical therapy, orthopedic consult, and surgery, using Medicaid status as a proxy for income in addition to other income measures. Of the 3 studies analyzing outcomes, 2 found that low-SES patients had worse pain and function, again based on Medicaid status and other income measures. Education did not have a significant impact on outcomes, as per the 1 study that included it. No studies included measures of occupation or employment.

Conclusion

Patients of low SES face reduced access to cuff repair care and worse associated outcomes, despite federal and state government efforts to reduce health care disparity through health care reform. The small nature of this review reflects how measures of SES are often not examined in rotator cuff repair studies.

Electronic Medical Records for (Visceral) Medicine: An Overview of the Current Status and Prospects

Background

Electronic medical records (EMRs) offer key advantages over analog documentation in healthcare. In addition to providing details about current and past treatments, EMRs enable clear and traceable documentation regardless of the location. This supports evidence-based, multi-professional treatment and leads to more efficient healthcare. However, there are still several challenges regarding the use of EMRs. Understanding these challenges is essential to improve healthcare. The aim of this article is to provide an overview of the current state of EMRs in the field of visceral medicine, to describe the future prospects in this field, and to highlight some of the challenges that need to be faced.

Summary

The benefits of EMRs are manifold and particularly pronounced in the area of quality assurance and improvement of communication not only between different healthcare professionals but also between physicians and patients. Besides the danger of medical errors, the health consequences for the users (cognitive load) arise from poor usability or a system that does not fit into the real world. Involving users in the development of EMRs in the sense of participatory design can be helpful here. The use of EMRs in practice together with patients should be accompanied by training to ensure optimal outcomes in terms of shared decision-making.

Key Message

EMRs offer a variety of benefits. However, it is critical to consider user involvement, setting specificity, and user training during development, implementation, and use in order to minimize unintended consequences.

Semantic interoperability in health records standards: a systematic literature review

The integration and exchange of information among health organizations and system providers are currently regarded as a challenge. Each organization usually has an internal ecosystem and a proprietary way to store electronic health records of the patient’s history. Recent research explores the advantages of an integrated ecosystem by exchanging information between the different inpatient care actors. Many efforts seek quality in health care, economy, and sustainability in process management. Some examples are reducing medical errors, disease control and monitoring, individualized patient care, and avoiding duplicate and fragmented entries in the electronic medical record. Likewise, some studies showed technologies to achieve this goal effectively and efficiently, with the ability to interoperate data, allowing the interpretation and use of health information. To that end, semantic interoperability aims to share data among all the sectors in the organization, clinicians, nurses, lab, the entire hospital. Therefore, avoiding data silos and keep data regardless of vendors, to exchange the information across organizational boundaries. This study presents a comprehensive systematic literature review of semantic interoperability in electronic health records. We searched seven databases of articles published between 2010 to September 2020. We showed the most chosen scenarios, technologies, and tools employed to solve interoperability problems, and we propose a taxonomy around semantic interoperability in health records. Also, we presented the main approaches to solve the exchange problem of legacy and heterogeneous data across healthcare organizations.

Early Adopters of Apple Health Records at a Large Academic Medical Center: Cross-sectional Survey of Users

Background

Mobile applications offer a new approach to personal health records, which are internet-based tools for patients to consolidate and manage their health information. The University of Pennsylvania Health System (UPHS) was one of the first health systems to participate in Apple Health Records (AHR), a prominent example of this new generation of personal health records.

Objective

This study aimed to characterize early adoption of AHR among UPHS patients and understand user perspectives.

Methods

An email-based survey with fixed answer, Likert scale, and open-ended questions was administered to all UPHS patients using AHR in the first 10 months of enrollment. Survey data linked to the UPHS electronic health record system were used to analyze responses. Multivariable logistic regression modeled the association of patient characteristics with user ratings. Content analysis was used to analyze open-ended questions.

Results

At the time of the survey, a total of 1458 patients had used AHR at least once. Mean age of AHR users was 47.5 years, 66.3% (967/1458) were male, 70.9% (1033/1458) were white, and 80.8% (1178/1458) had private insurance. Response rate was 26.8% (391/1458); 46.3% (180/389) were very satisfied with AHR, and 67.7% (264/390) described it as very easy to use. The most commonly utilized features were lab results (324/391, 82.9%), clinical vitals (264/391, 67.5%), and medications (253/391, 64.7%). No patient characteristics were associated with reporting high satisfaction or ease of use. The most common reason for using AHR was convenience/ease of use, and 58.2% (160/275) of users reported allowing no other apps to access their health information, citing privacy as one consideration.

Conclusions

Early adopters of AHR were demographically white, male, and privately insured. Convenience was an important facilitator, and users were selective in which apps they allowed to access their health information.

Exploring the COVID-19 Pandemic as a Catalyst for PHR App User Behavior Change in Taiwan: A Development and Usability Study

Background

During the COVID-19 pandemic, personal health records (PHRs) have enabled patients to monitor and manage their medical data without visiting hospitals and, consequently, minimize their infection risk. Taiwan’s National Health Insurance Administration (NHIA) launched the My Health Bank (MHB) service, a national PHR system through which insured individuals to access their cross-hospital medical data. Furthermore, in 2019, the NHIA released the MHB software development kit (SDK), which enables development of mobile apps with which insured individuals can retrieve their MHB data. However, the NHIA MHB service has its limitations, and the participation rate among insured individuals is low.

Objective

We aimed to integrate the MHB SDK with our developed blockchain-enabled PHR mobile app, which enables patients to access, store, and manage their cross-hospital PHR data. We also collected and analyzed the app’s log data to examine patients’ MHB use during the COVID-19 pandemic.

Methods

We integrated our existing blockchain-enabled mobile app with the MHB SDK to enable NHIA MHB data retrieval. The app utilizes blockchain technology to encrypt the downloaded NHIA MHB data. Existing and new indexes can be synchronized between the app and blockchain nodes, and high security can be achieved for PHR management. Finally, we analyzed the app’s access logs to compare patients’ activities during high and low COVID-19 infection periods.

Results

We successfully integrated the MHB SDK into our mobile app, thereby enabling patients to retrieve their cross-hospital medical data, particularly those related to COVID-19 rapid and polymerase chain reaction testing and vaccination information and progress. We retrospectively collected the app’s log data for the period of July 2019 to June 2021. From January 2020, the preliminary results revealed a steady increase in the number of people who applied to create a blockchain account for access to their medical data and the number of app subscribers among patients who visited the outpatient department (OPD) and emergency department (ED). Notably, for patients who visited the OPD and ED, the peak proportions with respect to the use of the app for OPD and ED notes and laboratory test results also increased year by year. The highest proportions were 52.40% for ED notes in June 2021, 88.10% for ED laboratory test reports in May 2021, 34.61% for OPD notes in June 2021, and 41.87% for OPD laboratory test reports in June 2021. These peaks coincided with Taiwan’s local COVID-19 outbreak lasting from May to June 2021.

Conclusions

This study developed a blockchain-enabled mobile app, which can periodically retrieve and integrate PHRs from the NHIA MHB's cross-hospital data and the investigated hospital's self-pay medical data. Analysis of users’ access logs revealed that the COVID-19 pandemic substantially increased individuals’ use of PHRs and their health awareness with respect to COVID-19 prevention.

Blockchain-based architecture design for personal health record (Preprint)

Background

The importance of blockchain-based architectures for personal health record (PHR) lies in the fact that they are thought and developed to allow patients to control and at least partly collect their health data. Ideally, these systems should provide the full control of such data to the respective owner. In spite of this importance, most of the works focus more on describing how blockchain models can be used in a PHR scenario rather than whether these models are in fact feasible and robust enough to support a large number of users.

Objective

To achieve a consistent, reproducible, and comparable PHR system, we build a novel ledger-oriented architecture out of a permissioned distributed network, providing patients with a manner to securely collect, store, share, and manage their health data. We also emphasize the importance of suitable ledgers and smart contracts to operate the blockchain network as well as discuss the necessity of standardizing evaluation metrics to compare related (net)works.

Methods

We adopted the Hyperledger Fabric platform to implement our blockchain-based architecture design and the Hyperledger Caliper framework to provide a detailed assessment of our system: first, under workload, ranging from 100 to 2500 simultaneous record submissions, and second, increasing the network size from 3 to 13 peers. In both experiments, we used throughput and average latency as the primary metrics. We also created a health database, a cryptographic unit, and a server to complement the blockchain network.

Results

With a 3-peer network, smart contracts that write on the ledger have throughputs, measured in transactions per second (tps) in an order of magnitude close to 10² tps, while those contracts that only read have rates close to 10³ tps. Smart contracts that write also have latencies, measured in seconds, in an order of magnitude close to 10¹ seconds, while that only read have delays close to 10⁰ seconds. In particular, smart contracts that retrieve, list, and view history have throughputs varying, respectively, from 1100 tps to 1300 tps, 650 tps to 750 tps, and 850 tps to 950 tps, impacting the overall system response if they are equally requested under the same workload. Varying the network size and applying an equal fixed load, in turn, writing throughputs go from 10² tps to 10¹ tps and latencies go from 10¹ seconds to 10² seconds, while reading ones maintain similar values.

Conclusions

To the best of our knowledge, we are the first to evaluate, using Hyperledger Caliper, the performance of a PHR blockchain architecture and the first to evaluate each smart contract separately. Nevertheless, blockchain systems achieve performances far below what the traditional distributed databases achieve, indicating that the assessment of blockchain solutions for PHR is a major concern to be addressed before putting them into a real production.

Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research: Bibliometric Analysis

Background

The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots.

Objective

The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis.

Methods

We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence.

Results

The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention.

Conclusions

Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including “allocative value,” “technology value,” and “personalized value.”

Ready for Prime Time? Using Normalization Process Theory to Evaluate Implementation Success of Personal Health Records Designed for Decision Making

Personal health records designed for shared decision making (SDM) have the potential to engage patients and provide opportunities for positive health outcomes. Given the limited number of published interventions that become normal practice, this preimplementation evaluation of an integrated SDM personal health record system (e-PHR) was underpinned by Normalization Process Theory (NPT). The theory provides a framework to analyze cognitive and behavioral mechanisms known to influence implementation success. A mixed-methods investigation was utilized to explain the work required to implement e-PHR and its potential to integrate into practice. Patients, care providers, and electronic health record (EHR) and clinical leaders (n = 27) offered a rich explanation of the implementation work. Reliability tests of the NPT-based instrument negated the use of scores for two of the four mechanisms. Participants indicated that e-PHR made sense as explained by two qualitative themes: game-changing technology and sensibility of change. Participants appraised e-PHR as explained by two themes: reflecting on value and monitoring and adapting. The combined qualitative and quantitative results for the other two NPT mechanisms corroborated. Participants strongly agreed (score = 4.6/5) with processes requiring an investment in commitment, explained by two themes: sharing ownership of the work and enabling involvement. Weak agreement (score = 3.6/5) was observed with processes requiring an investment in effort, explained by one theme: uncovering the challenge of building collective action, and three subthemes: assessing fit, adapting to change together, and investing in the change. Finally, participants strongly agreed (score = 4.5/5) that e-PHR would positively affect engagement in self-management decision-making in two themes: care is efficient, and care is patient-centered. Overall, successful integration of e-PHR will only be attained when systemic effort is invested to enact it. Additional investigation is needed to explore the collective action gaps to inform priorities and approaches for future implementation success. This research has implications for patients, care providers, EHR vendors, and the healthcare system for improving the effectiveness and efficiency of patient-centric services. Findings confirm the usefulness of NPT for planning and understanding implementation success of PHRs.

An Audio Personal Health Library of Clinic Visit Recordings for Patients and Their Caregivers (HealthPAL): User-Centered Design Approach

Background

Providing digital recordings of clinic visits to patients has emerged as a strategy to promote patient and family engagement in care. With advances in natural language processing, an opportunity exists to maximize the value of visit recordings for patients by automatically tagging key visit information (eg, medications, tests, and imaging) and linkages to trustworthy web-based resources curated in an audio-based personal health library.

Objective

This study aims to report on the user-centered development of HealthPAL, an audio personal health library.

Methods

Our user-centered design and usability evaluation approach incorporated iterative rounds of video-recorded sessions from 2016 to 2019. We recruited participants from a range of community settings to represent older patient and caregiver perspectives. In the first round, we used paper prototypes and focused on feature envisionment. We moved to low-fidelity and high-fidelity versions of the HealthPAL in later rounds, which focused on functionality and use; all sessions included a debriefing interview. Participants listened to a deidentified, standardized primary care visit recording before completing a series of tasks (eg, finding where a medication was discussed in the recording). In the final round, we recorded the patients’ primary care clinic visits for use in the session. Findings from each round informed the agile software development process. Task completion and critical incidents were recorded in each round, and the System Usability Scale was completed by participants using the digital prototype in later rounds.

Results

We completed 5 rounds of usability sessions with 40 participants, of whom 25 (63%) were women with a median age of 68 years (range 23-89). Feedback from sessions resulted in color-coding and highlighting of information tags, a more prominent play button, clearer structure to move between one’s own recordings and others’ recordings, the ability to filter recording content by the topic discussed and descriptions, 10-second forward and rewind controls, and a help link and search bar. Perceived usability increased over the rounds, with a median System Usability Scale of 78.2 (range 20-100) in the final round. Participants were overwhelmingly positive about the concept of accessing a curated audio recording of a clinic visit. Some participants reported concerns about privacy and the computer-based skills necessary to access recordings.

Conclusions

To our knowledge, HealthPAL is the first patient-centered app designed to allow patients and their caregivers to access easy-to-navigate recordings of clinic visits, with key concepts tagged and hyperlinks to further information provided. The HealthPAL user interface has been rigorously co-designed with older adult patients and their caregivers and is now ready for further field testing. The successful development and use of HealthPAL may help improve the ability of patients to manage their own care, especially older adult patients who have to navigate complex treatment plans.

Effects of a Personal Health Record in Maternity Care: A Stepped-Wedge Trial

To improve both the active involvement of pregnant women in their maternal health and multidisciplinary collaboration between maternal care professionals, we introduced a personal health record (PHR) in routine maternity care. We studied the effects of this intervention on the percentage of uncomplicated births, women’s perspectives on quality of care, and the collaboration between health care professionals. We performed a stepped-wedge cluster randomized controlled trial with four clusters and 13 maternity health centers (community-based midwife practices and hospitals) in one collaborative area. In total, 7350 pregnant women and 220 health care professionals participated. Uncomplicated births accounted for 51.8% (95% CI 50.1–53.9%) of total births in the control group and 55.0% (CI 53.5–56.5%) of total births in the intervention group (p = 0.289). Estimated means revealed that the differences detected in the stepped-wedge study were due to time and not the intervention. Women’s perspectives on quality of care and collaboration between health care professionals revealed no relevant differences between the control and intervention groups. The introduction of the PHR resulted in no significant effect on the chosen measures of quality of maternal care. The suggested positive effect in the raw data was a local trend which was less visible in the national database, and thus might be related to subtle changes toward an improved collaborative culture in the study region.

Mechanism Design of Health Care Blockchain System Token Economy: Development Study Based on Simulated Real-World Scenarios

Background

Despite the fact that the adoption rate of electronic health records has increased dramatically among high-income nations, it is still difficult to properly disseminate personal health records. Token economy, through blockchain smart contracts, can better distribute personal health records by providing incentives to patients. However, there have been very few studies regarding the particular factors that should be considered when designing incentive mechanisms in blockchain.

Objective

The aim of this paper is to provide 2 new mathematical models of token economy in real-world scenarios on health care blockchain platforms.

Methods

First, roles were set for the health care blockchain platform and its token flow. Second, 2 scenarios were introduced: collecting life-log data for an incentive program at a life insurance company to motivate customers to exercise more and recruiting participants for clinical trials of anticancer drugs. In our 2 scenarios, we assumed that there were 3 stakeholders: participants, data recipients (companies), and data providers (health care organizations). We also assumed that the incentives are initially paid out to participants by data recipients, who are focused on minimizing economic and time costs by adapting mechanism design. This concept can be seen as a part of game theory, since the willingness-to-pay of data recipients is important in maintaining the blockchain token economy. In both scenarios, the recruiting company can change the expected recruitment time and number of participants. Suppose a company considers the recruitment time to be more important than the number of participants and rewards. In that case, the company can increase the time weight and adjust cost. When the reward parameter is fixed, the corresponding expected recruitment time can be obtained. Among the reward and time pairs, the pair that minimizes the company’s cost was chosen. Finally, the optimized results were compared with the simulations and analyzed accordingly.

Results

To minimize the company’s costs, reward–time pairs were first collected. It was observed that the expected recruitment time decreased as rewards grew, while the rewards decreased as time cost grew. Therefore, the cost was represented by a convex curve, which made it possible to obtain a minimum—an optimal point—for both scenarios. Through sensitivity analysis, we observed that, as the time weight increased, the optimized reward increased, while the optimized time decreased. Moreover, as the number of participants increased, the optimization reward and time also increased.

Conclusions

In this study, we were able to model the incentive mechanism of blockchain based on a mechanism design that recruits participants through a health care blockchain platform. This study presents a basic approach to incentive modeling in personal health records, demonstrating how health care organizations and funding companies can motivate one another to join the platform.

Role of Individual Motivations and Privacy Concerns in the Adoption of German Electronic Patient Record Apps-A Mixed-Methods Study

Germany's electronic patient record ("ePA") launched in 2021 with several attempts and years of delay. The development of such a large-scale project is a complex task, and so is its adoption. Individual attitudes towards an electronic health record are crucial, as individuals can reject opting-in to it and making any national efforts unachievable. Although the integration of an electronic health record serves potential benefits, it also constitutes risks for an individual's privacy. With a mixed-methods study design, this work provides evidence that different types of motivations and contextual privacy antecedents affect usage intentions towards the ePA. Most significantly, individual motivations stemming from feelings of volition or external mandates positively affect ePA adoption, although internal incentives are more powerful.

Obstacles and features of health information systems: A systematic literature review

BACKGROUND

Currently many healthcare systems are supported by an increasing set of Health Information Sys-tems (HISs), which assist the activities for multiple stakeholders. The literature on HISs is, however, fragmented and a solid overview of the current state of HISs is missing. This impedes the understanding and characterization of the required HISs for the healthcare domain.

METHODS

In this article, we present the results of a Systematic Literature Review (SLR) that identifies the HISs, their domains, stakeholders, features, and obstacles.

RESULTS

In the SLR, we identified 1340 papers from which we selected 136 studies, on which we performed a full-text analysis. After the synthesis of the data, we were able to report on 33 different domains, 41 stakeholders, 73 features, and 69 obstacles. We discussed how these domains, features, and obstacles interact with each other and presented suggestions to overcome the identified obstacles. We recognized five groups of obstacles: technical problems, operational functionality, maintenance & support, usage problems, and quality problems. Obstacles from all groups require to be solved to pave the way for further research and application of HISs.

CONCLUSION

This study shows that there is a plentitude of HISs with unique features and that there is no consensus on the requirements and types of HISs in the literature.

Integrating multiple blockchains to support distributed personal health records

Blockchain technologies have evolved in recent years, as have the use of personal health record (PHR) data. Initially, only the financial domain benefited from Blockchain technologies. Due to efficient distribution format and data integrity security, however, these technologies have demonstrated potential in other areas, such as PHR data in the healthcare domain. Applying Blockchain to PHR data faces different challenges than applying it to financial transactions via crypto-currency. To propose and discuss an architectural model of a Blockchain platform named "OmniPHR Multi-Blockchain" to address key challenges associated with geographical distribution of PHR data. We analyzed the current literature to identify critical barriers faced when applying Blockchain technologies to distribute PHR data. We propose an architecture model and describe a prototype developed to evaluate and address these challenges. The OmniPHR Multi-Blockchain architecture yielded promising results for scenarios involving distributed PHR data. The project demonstrated a viable and beneficial alternative for processing geographically distributed PHR data with performance comparable with conventional methods. Blockchain's implementation tools have evolved, but the domain of healthcare still faces many challenges concerning distribution and interoperability. This study empirically demonstrates an alternative architecture that enables the distributed processing of PHR data via Blockchain technologies.

A Worker-Centered Personal Health Record App for Workplace Health Promotion Using National Health Care Data Sets: Design and Development Study

Background

Personal health record (PHR) technology can be used to support workplace health promotion, and prevent social and economic losses related to workers’ health management. PHR services can not only ensure interoperability, security, privacy, and data quality, but also consider the user’s perspective in their design.

Objective

Using Fast Healthcare Interoperability Resources (FHIR) and national health care data sets, this study aimed to design and develop an app for providing worker-centered, interconnected PHR services.

Methods

This study considered the user’s perspective, using the human-centered design (HCD) methodology, to develop a PHR app suitable for occupational health. We developed a prototype after analyzing quantitative and qualitative data collected from workers and a health care professional group, after which we performed a usability evaluation. We structured workers’ PHR items based on the analyzed data, and ensured structural and semantic interoperability using FHIR, Systematized Nomenclature of Medicine–Clinical Terms (SNOMED-CT), and Logical Observation Identifiers Names and Codes (LOINC). This study integrated workers’ health information scattered across different Korean institutions through an interface method, and workers’ PHRs were managed through a cloud server, using Azure API for FHIR.

Results

In total, 562 workers from industrial parks participated in the quantitative study. The preferred data items for PHR were medication, number of steps walked, diet, blood pressure, weight, and blood glucose. The preferred features were ability to access medical checkup results, health information content provision, consultation record inquiry, and teleconsultation. The worker-centered PHR app collected data on, among others, life logs, vital signs, and medical checkup results; offered health care services such as reservation and teleconsultation; and provided occupational safety and health information through material safety data sheet search and health questionnaires. The app reflected improvements in user convenience and app usability proposed by 19 participants (7 health care professionals and 12 end users) in the usability evaluation. The After-Scenario Questionnaire (ASQ) was evaluated with a mean score of 5.90 (SD 0.34) out of 7, and the System Usability Scale (SUS) was evaluated a mean score of 88.7 (SD 4.83) out of 100.

Conclusions

The worker-centered PHR app integrates workers’ health information from different institutions and provides a variety of health care services from linked institutions through workers’ shared PHR. This app is expected to increase workers’ autonomy over their health information and support medical personnel’s decision making regarding workers’ health in the workplace. Particularly, the app will provide solutions for current major PHR challenges, and its design, which considers the user’s perspective, satisfies the prerequisites for its utilization in occupational health.

Improvement and Evaluation of the TOPCOP Taxonomy of Patient Portals: Taxonomy-Evaluation-Delphi Approach (TED)

Background

Patient portals have been introduced in many countries over the last 10 years, but many health information managers still feel they have too little knowledge of patient portals. A taxonomy can help them to better compare and select portals. This has led us to develop the TOPCOP taxonomy for classifying and comparing patient portals. However, the taxonomy has not been evaluated by users.

Objective

This study aimed to evaluate the taxonomy’s usefulness to support health information managers in comparing, classifying, defining a requirement profile for, and selecting patient portals and to improve the taxonomy where needed.

Methods

We used a modified Delphi approach. We sampled a heterogeneous panel of 13 health information managers from 3 countries using the criterion sampling strategy. We conducted 4 anonymous survey rounds with qualitative and quantitative questions. In round 1, the panelists assessed the appropriateness of each dimension, and we collected new ideas to improve the dimensions. In rounds 2 and 3, the panelists iteratively evaluated the taxonomy that was revised based on round 1. In round 4, the panelists assessed the need for a taxonomy and the appropriateness of patient engagement as a distinguishing concept. Then, they compared 2 real portals with the final taxonomy and evaluated its usefulness for comparing portals, creating an initial requirement profile, and selecting patient portals. To determine group consensus, we applied the RAND/UCLA Appropriateness Method.

Results

The final taxonomy consists of 25 dimensions with 65 characteristics. Five new dimensions were added to the original taxonomy, with 8 characteristics added to already existing dimensions. Group consensus was achieved on the need for such a taxonomy to compare portals, on patient engagement as an appropriate distinguishing concept, and on the comprehensibility of the taxonomy’s form. Further, consensus was achieved on the taxonomy’s usefulness for classifying and comparing portals, assisting users in better understanding portals, creating a requirement profile, and selecting portals. This allowed us to test the usefulness of the final taxonomy with the intended users.

Conclusions

The TOPCOP taxonomy aims to support health information managers in comparing and selecting patient portals. By providing a standardized terminology to describe various aspects of patient portals independent of clinical setting or country, the taxonomy will also be useful for advancing research and evaluation of patient portals.

The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities

Background

Information technology has shifted paper-based documentation in the health care sector into a digital form, in which patient information is transferred electronically from one place to another. However, there remain challenges and issues to resolve in this domain owing to the lack of proper standards, the growth of new technologies (mobile devices, tablets, ubiquitous computing), and health care providers who are reluctant to share patient information. Therefore, a solid systematic literature review was performed to understand the use of this new technology in the health care sector. To the best of our knowledge, there is a lack of comprehensive systematic literature reviews that focus on Fast Health Interoperability Resources (FHIR)-based electronic health records (EHRs). In addition, FHIR is the latest standard, which is in an infancy stage of development. Therefore, this is a hot research topic with great potential for further research in this domain.

Objective

The main aim of this study was to explore and perform a systematic review of the literature related to FHIR, including the challenges, implementation, opportunities, and future FHIR applications.

Methods

In January 2020, we searched articles published from January 2012 to December 2019 via all major digital databases in the field of computer science and health care, including ACM, IEEE Explorer, Springer, Google Scholar, PubMed, and ScienceDirect. We identified 8181 scientific articles published in this field, 80 of which met our inclusion criteria for further consideration.

Results

The selected 80 scientific articles were reviewed systematically, and we identified open questions, challenges, implementation models, used resources, beneficiary applications, data migration approaches, and goals of FHIR.

Conclusions

The literature analysis performed in this systematic review highlights the important role of FHIR in the health care domain in the near future.

Information sharing via electronic health records in team-based care: the patient perspective

PURPOSE

Team-based care offers potential improvements in communication, care coordination, efficiency, value and satisfaction levels of both patients and providers. However, the question of how to balance the need for information in team-based care without disregarding patient preferences remains unanswered. This study aims to determine patients' perceptions of information sharing via electronic health records (EHRs) in team-based care.

METHODS

This qualitative study used a focus group approach. Participants were primary care patients and representative members from minority groups (ethnic, racial or social). Audio recordings of the sessions were transcribed and coded consistent with thematic analyses.

RESULTS

The analysis revealed that the participants in the focus groups had diverging levels of understanding and personal beliefs around five major themes including (i) patient's understanding of the care team, (ii) perceptions of electronic health records, (iii) defining basic health care information, (iv) sharing information with the health care team and (v) patient's trust in doctors and the health care system.

CONCLUSIONS

The participants of our focus groups value team-based care and view patients as a critical part of those teams. With respect to electronic health records, our participants recognized their importance but had concerns about inaccuracies and limited options to correct errors in their records. In general, participants were willing to share basic information but disagreed about what information should be considered to be basic. Moreover, based on their trust and comfort level, many participants want to control what information is recorded and shared in the electronic health record.

Needs Assessment for the Development of an Electronic Cross-Facility Health Record (ECHR) for Pediatric Palliative Care: A Design Thinking Approach

Background: Pediatric palliative care (PPC) is characterized by years of multisectoral and multi-professional care. Sharing information between PPC professionals is, therefore, essential for quality care. The evidence shows that electronic cross-facility health records (ECHRs) provide useful support in this context. To our knowledge, no ECHRs have been developed through a user-centered approach for this specific setting in Germany. Methods: Guided by design thinking, first, qualitative interviews were conducted to assess the needs of PPC professionals. Second, the elicited needs were specified in focus groups (FGs). Based on the needs stated in the interviews, prototypes of the ECHR were developed and discussed in the FGs. The indicated needs were supplemented and specified in an iterative process. The prototypes were further adapted according to these results. The unified theory of acceptance and use of technology was the basic model in the evaluation of needs. Results: Across seven main categories, past and current medication, emergency view, and messaging functions were identified as the participants’ desired core components of an ECHR. Utilizing design thinking facilitated the explicit articulation of user needs. Conclusions: Developing an ECHR with the content identified would allow for real-time data during emergencies, tracking what other PPC professionals have done, and making the applied treatments visible to others. This would offer a broader picture of the complex conditions common to PPC.

Development and Validation of a Useful Taxonomy of Patient Portals Based on Characteristics of Patient Engagement

Objective  Taxonomies are classification systems used to reduce complexity and better understand a domain. The present research aims to develop a useful taxonomy for health information managers to classify and compare patient portals based on characteristics appropriate to promote patient engagement. As a result, the taxonomy should contribute to understanding the differences and similarities of the portals. Further, the taxonomy shall support health information managers to more easily define which general type and functionalities of patient portals they need and to select the most suitable solution offered on the market.

Methods  We followed the formal taxonomy-building method proposed by Nickerson et al. Based on a literature review, we created a preliminary taxonomy following the conceptional approach of the model. We then evaluated each taxa's appropriateness by analyzing and classifying 17 patient portals offered by software vendors and 11 patient portals offered by health care providers. After each iteration, we examined the achievement of the determined objective and subjective ending conditions.

Results  After two conceptional approaches to create our taxonomy, and two empirical approaches to evaluate it, the final taxonomy consists of 20 dimensions and 49 characteristics. To make the taxonomy easy to comprehend, we assigned to the dimensions seven aspects related to patient engagement. These aspects are (1) portal design, (2) management, (3) communication, (4) instruction, (5) self-management, (6) self-determination, and (7) data management. The taxonomy is considered finished and useful after all ending conditions that defined beforehand have been fulfilled. We demonstrated that the taxonomy serves to understand the differences and similarities by comparing patient portals. We call our taxonomy “Taxonomy of Patient Portals based on Characteristics of Patient Engagement (TOPCOP).”

Conclusion  We developed the first useful taxonomy for health information managers to classify and compare patient portals. The taxonomy is based on characteristics promoting patient engagement. With 20 dimensions and 49 characteristics, our taxonomy is particularly suitable to discriminate among patient portals and can easily be applied to compare portals. The TOPCOP taxonomy enables health information managers to better understand the differences and similarities of patient portals. Further, the taxonomy may help them to define the type and general functionalities needed. But it also supports them in searching and comparing patient portals offered on the market to select the most suitable solution.