Impact of electronic health record interoperability on safety and quality of care in high-income countries: A systematic review (Preprint)

Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review

BACKGROUND

Patient engagement when providing patient access to health data results from an interaction between the available tools and individual capabilities. The recent digital advancements of the healthcare field have altered the manifestation and importance of patient engagement. However, a comprehensive assessment of what factors contribute to patient engagement remain absent. In this review article, we synthesised the most frequently discussed factors that can foster patient engagement with their health data.

METHODS

A scoping review was conducted in MEDLINE, Embase, and Google Scholar. Relevant data were synthesized within 7 layers using a thematic analysis: (1) social and demographic factors, (2) patient ability factors, (3) patient motivation factors, (4) factors related to healthcare professionals' attitudes and skills, (5) health system factors, (6) technological factors, and (7) policy factors.

RESULTS

We identified 5801 academic and 200 Gy literature records, and included 292 (4.83%) in this review. Overall, 44 factors that can affect patient engagement with their health data were extracted. We extracted 6 social and demographic factors, 6 patient ability factors, 12 patient motivation factors, 7 factors related to healthcare professionals' attitudes and skills, 4 health system factors, 6 technological factors, and 3 policy factors.

CONCLUSIONS

Improving patient engagement with their health data enables the development of patient-centered healthcare, though it can also exacerbate existing inequities. While expanding patient access to health data is an important step towards fostering shared decision-making in healthcare and subsequently empowering patients, it is important to ensure that these developments reach all sectors of the community.

Has cross-level clinical coordination changed in the context of the pandemic? The case of the Catalan health system

BACKGROUND

The COVID-19 pandemic triggered numerous changes in health services organisation, whose effects on clinical coordination are unknown. The aim is to analyse changes in the experience and perception of cross-level clinical coordination and related factors of primary (PC) and secondary care (SC) doctors in the Catalan health system between 2017 and 2022.

METHODS

Comparison of two cross-sectional studies based on online surveys by means of the self-administration of the COORDENA-CAT (2017) and COORDENA-TICs (2022) questionnaires to PC and SC doctors. Final sample n = 3308 in 2017 and n = 2277 in 2022.

OUTCOME VARIABLES

experience of cross-level information and clinical management coordination and perception of cross-level clinical coordination in the healthcare area and related factors. Stratification variables: level of care and year. Adjusting variables: sex, years of experience, type of specialty, type of hospital, type of management of PC/SC. Descriptive bivariate and multivariate analysis using Poisson regressions models to detect changes between years in total and by levels of care.

RESULTS

Compared with 2017, while cross-level clinical information coordination remained relatively high, with a slight improvement, doctors of both care levels reported a worse experience of cross-level clinical management coordination, particularly of care consistency (repetition of test) and accessibility to PC and, of general perception, which was worse in SC doctors. There was also a worsening in organisational (institutional support, set objectives, time available for coordination), attitudinal (job satisfaction) and interactional factors (knowledge between doctors). The use of ICT-based coordination mechanisms such as shared electronic medical records and electronic consultations between PC and SC increased, while the participation in virtual joint clinical conferences was limited.

CONCLUSIONS

Results show a slight improvement in clinical information but also less expected setbacks in some dimensions of clinical management coordination and in the perception of clinical coordination, suggesting that the increased use of some ICT-based coordination mechanisms did not counteract the effect of the worsened organisational, interactional, and attitudinal factors during the pandemic. Strategies are needed to facilitate direct communication, to improve conditions for the effective use of mechanisms and policies to protect healthcare professionals and services in order to better cope with new crises.

Designing medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility

Advances in artificial intelligence (AI) and machine learning systems promise faster, more efficient, and more personalized care. While many of these models are built on the premise of improving access to the timely screening, diagnosis, and treatment of cardiovascular disease, their validity and accessibility across diverse and international cohorts remain unknown. In this mini-review article, we summarize key obstacles in the effort to design AI systems that will be scalable, accessible, and accurate across distinct geographical and temporal settings. We discuss representativeness, interoperability, quality assurance, and the importance of vendor-agnostic data types that will be available to end-users across the globe. These topics illustrate how the timely integration of these principles into AI development is crucial to maximizing the global benefits of AI in cardiology.

Patient and caregiver perspectives on causes and prevention of ambulatory adverse events: multilingual qualitative study

CONTEXT

Ambulatory adverse events (AEs) affect up to 25% of the global population and cause over 7 million preventable hospital admissions around the world. Though patients and caregivers are key actors in promoting and monitoring their own ambulatory safety, healthcare teams do not traditionally partner with patients in safety efforts. We sought to identify what patients and caregivers contribute when engaged in ambulatory AE review, focusing on under-resourced care settings.

METHODS

We recruited adult patients, caregivers and patient advisors who spoke English, Spanish and/or Cantonese, from primary care clinics affiliated with a public health network in the USA. All had experience taking or managing a high-risk medication (blood thinners, insulin or opioid). We presented two exemplar ambulatory AEs: one involving a warfarin drug-drug interaction, and one involving delayed diagnosis of colon cancer. We conducted semistructured focus groups and interviews to elicit participants' perceptions of causal factors and potential preventative measures for similar AEs. The study team conducted a mixed inductive-deductive qualitative analysis to derive major themes.

FINDINGS

The sample included 6 English-speaking patients (2 in the focus group, 4 individual interviews), 6 Spanish-speaking patients (individual interviews), 4 Cantonese-speaking patients (2 in the focus group, 2 interviews), and 6 English-speaking patient advisors (focus group). Themes included: (1) Patients and teams have specific safety responsibilities; (2) Proactive communication drives safe ambulatory care; (3) Barriers related to limited resources contribute to ambulatory AEs. Patients and caregivers offered ideas for operational changes that could drive new safety projects.

CONCLUSIONS

An ethnically and linguistically diverse group of primary care patients and caregivers defined their agency in ensuring ambulatory safety and offered pragmatic ideas to prevent AEs they did not directly experience. Patients and caregivers in a safety net health system can feasibly participate in AE review to ensure that safety initiatives include their valuable perspectives.

Using 42 CFR part 2 revisions to integrate substance use disorder treatment information into electronic health records at a safety net health system

BACKGROUND

Regulations put in place to protect the privacy of individuals receiving substance use disorder (SUD) treatment have resulted in an unintended consequence of siloed SUD treatment and referral information outside of the integrated electronic health record (EHR). Recent revisions to these regulations have opened the door to data integration, which creates opportunities for enhanced patient care and more efficient workflows. We report on the experience of one safety-net hospital system integrating SUD treatment data into the EHR.

METHODS

SUD treatment and referral information was integrated from siloed systems into the EHR through the implementation of a referral order, treatment episode definition, and referral and episode-related tools for addiction therapists and other clinicians. Integration was evaluated by monitoring SUD treatment episode characteristics, patient characteristics, referral linkage, and treatment episode retention before and after integration. Satisfaction of end-users with the new tools was evaluated through a survey of addiction therapists.

RESULTS

After integration, three more SUD treatment programs were represented in the EHR. This increased the number of patients that could be tracked as initiating SUD treatment by 250%, from 562 before to 1,411 after integration. After integration, overall referral linkage declined (74% vs. 48%) and treatment episode retention at 90-days was higher (45% vs. 74%). Addiction therapists appreciated the efficiency of having all SUD treatment information in the EHR but did not find that the tools provided a large time savings shortly after integration.

CONCLUSIONS

Integration of SUD treatment program data into the EHR facilitated both care coordination in patient treatment and quality improvement initiatives for treatment programs. Referral linkage and retention rates were likely modified by a broader capture of patients and changed outcome definition criteria. Greater preparatory workflow analysis may decrease initial end-user burden. Integration of siloed data, made possible given revised regulations, is essential to an efficient hub-and-spoke model of care, which must standardize and coordinate patient care across multiple clinics and departments.

Towards understanding and improving medication safety for patients with mental illness in primary care: A multimethod study

INTRODUCTION

Medication safety incidents have been identified as an important target to improve patient safety in mental healthcare. Despite this, the causes of preventable medication safety incidents affecting patients with mental illness have historically been poorly understood, with research now addressing this knowledge gap through a healthcare professional lens. However, patients and carers can also provide complimentary insight into safety issues, and as key stakeholders in healthcare, it is vital to consider their needs when designing effective interventions.

METHODS

A two-stage approach was adopted by (i) conducting three focus groups (FG) comprising 13 patients with mental illness and their carers to develop a holistic picture of medication safety in primary care with extraction of themes guided by the P-MEDS framework; (ii) conducting two separate nominal group consensus workshops with seven patients with mental illness/carers and seven healthcare professionals to identify priority areas for targeted interventions.

RESULTS

Seven themes were identified in the FGs: communication; trust, involvement and respect; continuity and support; access; the healthcare professional; the patient and carer; and the organisation. Priority areas identified for intervention by key stakeholders included improving communication within and between clinical services, enhancing patient support with holistic continuity of care, maximising shared decision-making and empowerment, ensuring timely access to medicines and services, strengthening healthcare professional knowledge regarding mental illnesses and associated medications, and increasing patient dignity and respect.

CONCLUSION

This study has developed a holistic picture of contributors to medication safety incidents affecting patients with mental illness in primary care. This theory was then used by key stakeholders to inform and generate priority recommendations for targeted interventions. These findings can be used to inform future intervention research, as they consider the needs of those who access or work within primary care services.

PATIENT OR PUBLIC CONTRIBUTION

An advisory group consisting of three expert patients with lived experience of mental illness was consulted on the design of both stages of this study. Patients with mental illness and/or their carers were recruited and participated in both stages of this study. Patients/carers aided with data analysis and interpretation during the patient/carer nominal group consensus workshop.

Pharmacovigilance Practices by Healthcare Providers in Oncology: A Cross-Sectional Study

Investigating pharmacovigilance (PV) practices among oncology healthcare providers (HCPs) is crucial for patient safety in oncology settings. This study aimed to assess the awareness, attitudes, and practices towards PV and identify barriers to effective adverse drug reaction (ADR) reporting for HCPs working in oncology-related settings. Employing a cross-sectional survey design, we collected data from 65 HCPs, focusing on their experiences with ADR reporting, education on ADR management, and familiarity with PV protocols. The results showed that about half of the responders were pharmacists. Around 58.9% of the respondents reported ADRs internally, and 76.9% had received some form of ADR-related education. However, only 38.5% were aware of formal ADR review procedures. Methotrexate and paclitaxel emerged as the drugs most frequently associated with ADRs. The complexity of cancer treatments was among the common reasons for the low reporting of ADRs by the study participants. The findings highlight the need for enhanced PV education and standardized reporting mechanisms to improve oncology care. We conclude that reinforcing PV training and streamlining ADR-reporting processes are critical to optimizing patient outcomes and safety in oncology, advocating for targeted educational interventions and the development of unified PV guidelines.

The Integration and Impact of Artificial Intelligence in Otolaryngology-Head and Neck Surgery: Navigating the Last Mile

Incorporating artificial Intelligence and machine learning into otolaryngology requires careful data handling, security, and ethical considerations. Success depends on interdisciplinary cooperation, consistent innovation, and regulatory compliance to improve clinical outcomes, provider experience, and operational effectiveness.

Prescription and Dispensation of QT-Prolonging Medications in Individuals Receiving Hemodialysis

Importance

Individuals with dialysis-dependent kidney failure have numerous risk factors for medication-related adverse events, including receipt of care by multiple clinicians and initiation of some QT-prolonging medications with known risk of torsades de pointes (TdP), which is associated with higher risk of sudden cardiac death. Little is known about the prescription and dispensation patterns of QT-prolonging medications among people receiving dialysis, hindering efforts to reduce drug-related harm from these and other medications in this high-risk population.

Objective

To examine prescription and dispensation patterns of QT-prolonging medications with known TdP risk and selected interacting medications prescribed to individuals receiving hemodialysis.

Design, Setting, and Participants

This cross-sectional study included patients 60 years or older who were enrolled in Medicare Parts A, B, and D receiving in-center hemodialysis from January 1 to December 31, 2019. Analyses were conducted from October 20, 2022, to June 16, 2023.

Exposures

New-user prescriptions for the 7 most frequently filled QT-prolonging medications characterized by the timing of the new prescription relative to acute care encounters, the type of prescribing clinician and pharmacy that dispensed the medication, and concomitant use of selected medications known to interact with the 7 most frequently filled QT-prolonging medications with known TdP risk.

Main Outcomes and Measures

The main outcomes were the frequencies of the most commonly filled and new-use episodes of QT-prolonging medications; the timing of medication fills relative to acute care events; prescribers and dispensing pharmacy characteristics for new use of medications; and the frequency and types of new-use episodes with concurrent use of potentially interacting medications.

Results

Of 20 761 individuals receiving hemodialysis in 2019 (mean [SD] age, 74 [7] years; 51.1% male), 10 992 (52.9%) filled a study drug prescription. Approximately 80% (from 78.6% for odansetron to 93.9% for escitalopram) of study drug new-use prescriptions occurred outside of an acute care event. Between 36.8% and 61.0% of individual prescriptions originated from general medicine clinicians. Between 16.4% and 26.2% of these prescriptions occurred with the use of another QT-prolonging medication. Most potentially interacting drugs were prescribed by different clinicians (46.3%-65.5%).

Conclusions and Relevance

In this cross-sectional study, QT-prolonging medications for individuals with dialysis-dependent kidney failure were commonly prescribed by nonnephrology clinicians and from nonacute settings. Prescriptions for potentially interacting medications often originated from different prescribers. Strategies aimed at minimizing high-risk medication-prescribing practices in the population undergoing dialysis are needed.

System-level recommendations for improved wellness for gynecologic oncologists: A Society of Gynecologic Oncology Review

Burnout and its negative sequelae are a persistent problem in gynecologic oncology, threatening the health of our physician workforce. Individual-level interventions such as stress management training, physical activity, and sleep hygiene only partially address this widespread, systemic crisis rooted in the extended work hours and stressful situations associated with gynecologic oncology practice. There is an urgent need for systematic, institution-level changes to allow gynecologic oncologists to continue the crucial work of caring for people with gynecologic cancer. We present recommendations for institution-level changes which are grounded in the framework presented by the National Plan for Health Workforce Well-Being by the National Academy of Medicine. These are aimed at facilitating gynecologic oncologists' well-being and reduction of burnout. Recommendations include efforts to create a more positive and inclusive work environment, decrease administrative barriers, promote mental health, optimize electronic medical record use, and support a diverse workforce. Implementation and regular evaluation of these interventions, with specific attention to at-risk groups, is an important next step.

Key interoperability Factors for patient portals and Electronic health Records: A scoping review

AIM

To identify the key requirements and challenges to interoperability between patient portals and electronic health records (EHRs).

INTRODUCTION

Patient portals provide patients with access to their health information directly from EHRs within hospitals, primary care centres and general practices (GPs). Patient portals offer many benefits to patients including improved communication with healthcare providers and care coordination. However, many challenges exist with the integration and automatic and secure sharing of information between EHRs and patient portals. It is critical that countries learn from international experiences to successfully develop interoperable national patient portals.

METHODS

A scoping review methodology was undertaken. A search strategy using index terms and keywords was applied across four key databases, an additional grey literature search was also run. The identified studies were screened by two reviewers to determine eligibility against defined inclusion criteria. Data were abstracted from the eligible studies and reviewed to identify the key requirements and challenges to interoperability of patient portals with EHRs.

RESULTS

After screening 3,462 studies, 34 were included across 11 countries. Of the 29 unique patient portals studied, few offered patients access to their entire healthcare record across multiple sites and a number of different functionalities were available. Key interoperability requirements and challenges identified were: Data Sharing Incentives & Supports; Heterogenous Organisations & Information Systems; Data Storage & Management; Available Information & Functionalities; Data Formats & Standards; Identification of Individuals; User Access, Control & Consent; and Security & Privacy.

CONCLUSION

Seamless exchange of health information across patient portals and EHRs required organisational and individual factors, as well as technical considerations. Interorganisational collaboration and engagement of key stakeholders to determine standards and guidelines for consent and sharing of information, as well as technical standards and security measures were recommended.

Using Electronic Health Records to Facilitate Precision Psychiatry

The use of clinical prediction models to produce individualized risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implement them in routine clinical care. The current review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number needed to test). We review 4 externally validated clinical prediction models designed to predict psychosis onset, psychotic relapse, cardiometabolic morbidity, and suicide risk. We then discuss the prospects for clinically implementing these models and the potential added value of integrating data from evidence syntheses, standardized psychometric assessments, and biological data into EHRs. Clinical prediction models can utilize routinely collected EHR data in an innovative way, representing a unique opportunity to inform real-world clinical decision making. Combining data from other sources (e.g., meta-analyses) or enhancing EHR data with information from research studies (clinical and biomarker data) may enhance our abilities to improve the performance of clinical prediction models.

Experiences, barriers and expectations regarding current patient monitoring systems among ICU nurses in a University Hospital in Lebanon: a qualitative study

Purpose

The aim of the study is to assess the experiences, barriers, and expectations regarding current patient monitoring systems among intensive care unit nurses at one university hospital.

Methods

A qualitative exploratory study approach was adopted to test the research questions.

Results

Intensive care unit personnel placed a high value on practical criteria such as user friendliness and visualization while assessing the present monitoring system. Poor alarm handling was recognized as possible patient safety hazards. The necessity of high accessibility was highlighted once again for a prospective system; wireless, noninvasive, and interoperability of monitoring devices were requested; and smart phones for distant patient monitoring and alert management improvement were required.

Conclusion

Core comments from ICU personnel are included in this qualitative research on patient monitoring. All national healthcare involved parties must focus more on user-derived insights to ensure a speedy and effective introduction of digital health technologies in the ICU. The findings from the alarm control or mobile device studies might be utilized to train ICU personnel to use new technology, minimize alarm fatigue, increase medical device accessibility, and develop interoperability standards in critical care practice.

A Machine Learning Approach with Human-AI Collaboration for Automated Classification of Patient Safety Event Reports: Algorithm Development and Validation Study

BACKGROUND

Adverse events refer to incidents with potential or actual harm to patients in hospitals. These events are typically documented through patient safety event (PSE) reports, which consist of detailed narratives providing contextual information on the occurrences. Accurate classification of PSE reports is crucial for patient safety monitoring. However, this process faces challenges due to inconsistencies in classifications and the sheer volume of reports. Recent advancements in text representation, particularly contextual text representation derived from transformer-based language models, offer a promising solution for more precise PSE report classification. Integrating the machine learning (ML) classifier necessitates a balance between human expertise and artificial intelligence (AI). Central to this integration is the concept of explainability, which is crucial for building trust and ensuring effective human-AI collaboration.

OBJECTIVE

This study aims to investigate the efficacy of ML classifiers trained using contextual text representation in automatically classifying PSE reports. Furthermore, the study presents an interface that integrates the ML classifier with the explainability technique to facilitate human-AI collaboration for PSE report classification.

METHODS

This study used a data set of 861 PSE reports from a large academic hospital's maternity units in the Southeastern United States. Various ML classifiers were trained with both static and contextual text representations of PSE reports. The trained ML classifiers were evaluated with multiclass classification metrics and the confusion matrix. The local interpretable model-agnostic explanations (LIME) technique was used to provide the rationale for the ML classifier's predictions. An interface that integrates the ML classifier with the LIME technique was designed for incident reporting systems.

RESULTS

The top-performing classifier using contextual representation was able to obtain an accuracy of 75.4% (95/126) compared to an accuracy of 66.7% (84/126) by the top-performing classifier trained using static text representation. A PSE reporting interface has been designed to facilitate human-AI collaboration in PSE report classification. In this design, the ML classifier recommends the top 2 most probable event types, along with the explanations for the prediction, enabling PSE reporters and patient safety analysts to choose the most suitable one. The LIME technique showed that the classifier occasionally relies on arbitrary words for classification, emphasizing the necessity of human oversight.

CONCLUSIONS

This study demonstrates that training ML classifiers with contextual text representations can significantly enhance the accuracy of PSE report classification. The interface designed in this study lays the foundation for human-AI collaboration in the classification of PSE reports. The insights gained from this research enhance the decision-making process in PSE report classification, enabling hospitals to more efficiently identify potential risks and hazards and enabling patient safety analysts to take timely actions to prevent patient harm.

The unfulfilled promises of electronic health records

We provide a brief update on the current evidence on electronic health records' benefits, risks, and potential harms through a rapid narrative review. Many of the promised benefits of electronic health records have not yet been realised. Electronic health records are often not user-friendly. To enhance their potential, electronic health record platforms should be continuously evaluated and enhanced by carefully considering feedback from all stakeholders.

Older Persons' and Health Care Professionals' Design Choices When Co-Designing a Medication Plan Aiming to Promote Patient Safety: Case Study

BACKGROUND

Harm from medications is a major patient safety challenge among older persons. Adverse drug events tend to arise when prescribing or evaluating medications; therefore, interventions targeting these may promote patient safety. Guidelines highlight the value of a joint plan for continued treatment. If such a plan includes medications, a medication plan promoting patient safety is advised. There is growing evidence for the benefits of including patients and health care professionals in initiatives for improving health care products and services through co-design.

OBJECTIVE

This study aimed to identify participants' needs and requirements for a medication plan and explore their reasoning for different design choices.

METHODS

Using a case study design, we collected and analyzed qualitative and quantitative data and compared them side by side. We explored the needs and requirements for a medication plan expressed by 14 participants (older persons, nurses, and physicians) during a co-design initiative in a regional health system in Sweden. We performed a directed content analysis of qualitative data gathered from co-design sessions and interviews. Descriptive statistics were used to analyze the quantitative data from survey answers.

RESULTS

A medication plan must provide an added everyday value related to safety, effort, and engagement. The physicians addressed challenges in setting aside time to apply a medication plan, whereas the older persons raised the potential for increased patient involvement. According to the participants, a medication plan needs to support communication, continuity, and interaction. The nurses specifically addressed the need for a plan that was easy to gain an overview of. Important function requirements included providing instant access, automation, and attention. Content requirements included providing detailed information about the medication treatment. Having the plan linked to the medication list and instantly obtainable information was also requested.

CONCLUSIONS

After discussing the needs and requirements for a medication plan, the participants agreed on an iteratively developed medication plan prototype linked to the medication list within the existing electronic health record. According to the participants, the medication plan prototype may promote patient safety and enable patient engagement, but concerns were raised about its use in daily clinical practice. The last step in the co-design framework is testing the intervention to explore how it works and connects with users. Therefore, testing the medication plan prototype in clinical practice would be a future step.

Impact of primary to secondary care data sharing on care quality in NHS England hospitals

Health information exchange (HIE) is seen as a key component of effective care but remains poorly evidenced at a health system level. In the UK National Health Service (NHS), the ability to share primary care data with secondary care clinicians is a focus of continued digital investment. In this study, we report the evolution of interoperable technology across a period of rapid digital transformation in NHS England from 2015 to 2019, and test association of primary to secondary care data-sharing capabilities with clinical care quality indicators across all acute secondary care providers (n = 135 NHS Trusts). In multivariable analyses, data-sharing capabilities are associated with reduction in patients breaching an Accident & Emergency (A&E) 4-h decision time threshold, and better patient-reported experience of acute hospital care quality. Using synthetic control analyses, we estimate mean 2.271% (STD+/-3.371) absolute reduction in A&E 4-h decision time breach, 12 months following introduction of data-sharing capabilities. Our findings support current digital transformation programmes for developing regional HIE networks but highlight the need to focus on implementation factors in addition to technological procurement.

Jumping Through Hoops: Community Care Clinician and Staff Experiences Providing Primary Care to Rural Veterans

BACKGROUND

The 2019 VA Maintaining Systems and Strengthening Integrated Outside Networks Act, or MISSION Act, aimed to improve rural veteran access to care by expanding coverage for services in the community. Increased access to clinicians outside the US Department of Veterans Affairs (VA) could benefit rural veterans, who often face obstacles obtaining VA care. This solution, however, relies on clinics willing to navigate VA administrative processes.

OBJECTIVE

To investigate the experiences rural, non-VA clinicians and staff have while providing care to rural veterans and inform challenges and opportunities for high-quality, equitable care access and delivery.

DESIGN

Phenomenological qualitative study.

PARTICIPANTS

Non-VA-affiliated primary care clinicians and staff in the Pacific Northwest.

APPROACH

Semi-structured interviews with a purposive sample of eligible clinicians and staff between May and August 2020; data analyzed using thematic analysis.

KEY RESULTS

We interviewed 13 clinicians and staff and identified four themes and multiple challenges related to providing care for rural veterans: (1) Confusion, variability and delays for VA administrative processes, (2) clarifying responsibility for dual-user veteran care, (3) accessing and sharing medical records outside the VA, and (4) negotiating communication pathways between systems and clinicians. Informants reported using workarounds to combat challenges, including using trial and error to gain expertise in VA system navigation, relying on veterans to act as intermediaries to coordinate their care, and depending on individual VA employees to support provider-to-provider communication and share system knowledge. Informants expressed concerns that dual-user veterans were more likely to have duplication or gaps in services.

CONCLUSIONS

Findings highlight the need to reduce the bureaucratic burden of interacting with the VA. Further work is needed to tailor structures to address challenges rural community providers experience and to identify strategies to reduce care fragmentation across VA and non-VA providers and encourage long-term commitment to care for veterans.

Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis

BACKGROUND

The Supreme Court ruling in Dobbs v Jackson Women's Health Organization (Dobbs) overrules precedents established by Roe v Wade and Planned Parenthood v Casey and allows states to individually regulate access to abortion care services. While many states have passed laws to protect access to abortion services since the ruling, the ruling has also triggered the enforcement of existing laws and the creation of new ones that ban or restrict abortion. In addition to denying patients the full spectrum of reproductive health care, one major concern in the medical community is how the ruling will undermine trust in the patient-clinician relationship by influencing perceptions of the privacy of patient health information.

OBJECTIVE

This study aimed to study the effect of recent abortion legislation on Twitter user engagement, sentiment, expressions of trust in clinicians, and privacy of health information.

METHODS

We scraped tweets containing keywords of interest between January 1, 2020, and October 17, 2022, to capture tweets posted before and after the leak of the Supreme Court decision. We then trained a Latent Dirichlet Allocation model to select tweets pertinent to the topic of interest and performed a sentiment analysis using Robustly Optimized Bidirectional Encoder Representations from Transformers Pre-training Approach model and a causal impact time series analysis to examine engagement and sentiment. In addition, we used a Word2Vec model to study the terms of interest against a latent trust dimension to capture how expressions of trust for our terms of interest changed over time and used term frequency, inverse-document frequency to measure the volume of tweets before and after the decision with respect to the negative and positive sentiments that map to our terms of interest.

RESULTS

Our study revealed (1) a transient increase in the number of daily users by 576.86% (95% CI 545.34%-607.92%; P<.001), tweeting about abortion, health care, and privacy of health information postdecision leak; (2) a sustained and statistically significant decrease in the average daily sentiment on these topics by 19.81% (95% CI -22.98% to -16.59%; P=.001) postdecision leak; (3) a decrease in the association of the latent dimension of trust across most clinician-related and health information-related terms of interest; (4) an increased frequency of tweets with these clinician-related and health information-related terms and concomitant negative sentiment in the postdecision leak period.

CONCLUSIONS

The study suggests that the Dobbs ruling has consequences for health systems and reproductive health care that extend beyond denying patients access to the full spectrum of reproductive health services. The finding of a decrease in the expression of trust in clinicians and health information-related terms provides evidence to support advocacy and initiatives that proactively address concerns of trust in health systems and services.

Vertical Integration of Electronic Health Records in Medical Consortiums: Dynamic Modeling Approach Based on the Evolutionary Game Theory

BACKGROUND

China has continuously issued policies to speed up the interconnection, mutual recognition, sharing of medical information systems, and data integration management across regions and institutions. However, the vertical integration of electronic health records (EHRs) within the medical consortium is hampered by "poor mechanism and insufficient motivation" and the phenomenon of "free riding" among participating medical institutions, which makes the integration less effective.

OBJECTIVE

We hope to clarify the game mechanism of stakeholders in the vertical integration of EHRs, and put forward targeted policy suggestions for improvement.

METHODS

We constructed the "government-hospital-patient" tripartite evolutionary game model based on the detailed analysis of the research problems and their assumptions. We then simulated the game strategies and outcomes of each participant using the system dynamics approach to reveal the long-term strategy evolution mechanism of the core participants in the vertical integration of EHRs in the medical consortium, as well as the influencing factors and action mechanisms of each party's strategy evolution to provide references for improving relevant policies.

RESULTS

The evolutionary game system could eventually reach an optimal equilibrium, but in areas where the government was required to be in a dominant position, patient supervision was necessary to have a positive role, while a reasonable reward and punishment mechanism can promote active participation of hospitals.

CONCLUSIONS

The effective way to achieve the goal of vertical integration of EHRs in the medical consortium is to build a multiagent coordination mechanism under the guidance of the government. Meanwhile, it is necessary to establish a scientific integration performance evaluation mechanism, a reward and punishment mechanism, and a benefit distribution mechanism to promote the healthy development of vertical integration of EHRs in medical consortiums.