Electronic Health Record Adoption Research Articles

Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review.

The cognitive load theory suggests that completing a task relies on the interplay between sensory input, working memory, and long-term memory. Cognitive overload occurs when the working memory's limited capacity is exceeded due to excessive information processing. In health care, clinicians face increasing cognitive load as the complexity of patient care has risen, leading to potential burnout. Electronic health records (EHRs) have become a common feature in modern health care, offering improved access to data and the ability to provide better patient care. They have been added to the electronic ecosystem alongside emails and other resources, such as guidelines and literature searches. Concerns have arisen in recent years that despite many benefits, the use of EHRs may lead to cognitive overload, which can impact the performance and well-being of clinicians. We aimed to review the impact of EHR use on cognitive load and how it correlates with physician burnout. Additionally, we wanted to identify potential strategies recommended in the literature that could be implemented to decrease the cognitive burden associated with the use of EHRs, with the goal of reducing clinician burnout. Using a comprehensive literature review on the topic, we have explored the link between EHR use, cognitive load, and burnout among health care professionals. We have also noted key factors that can help reduce EHR-related cognitive load, which may help reduce clinician burnout. The research findings suggest that inadequate efforts to present large amounts of clinical data to users in a manner that allows the user to control the cognitive burden in the EHR and the complexity of the user interfaces, thus adding more "work" to tasks, can lead to cognitive overload and burnout; this calls for strategies to mitigate these effects. Several factors, such as the presentation of information in the EHR, the specialty, the health care setting, and the time spent completing documentation and navigating systems, can contribute to this excess cognitive load and result in burnout. Potential strategies to mitigate this might include improving user interfaces, streamlining information, and reducing documentation burden requirements for clinicians. New technologies may facilitate these strategies. The review highlights the importance of addressing cognitive overload as one of the unintended consequences of EHR adoption and potential strategies for mitigation, identifying gaps in the current literature that require further exploration.

How do opt-in versus opt-out settings nudge patients toward electronic health record adoption? An exploratory study of facilitators and barriers in Austria and France.

Electronic health records (EHR)are becoming an integral part of the health system in many developed countries, though implementations and settings vary across countries. Some countries have adopted an opt-out policy, in which patients are enrolled in the EHR system following a default nudge, while others have applied an opt-in policy, where patients have to take action to opt into the system. While opt-in systems may exhibit lower levels of active user requests for access, this contrasts with opt-out systems where a notable percentage of users may passively retain access. Thus, our research endeavor aims to explore facilitators and barriers that contribute to explaining EHR usage (i.e., actively accessing the EHR system) in two countries with either an opt-in or opt-out setting, exemplified by France and Austria. A qualitative exploratory approach using a semi-structured interview guideline was undertaken in both countries: 1) In Austria, with four homogenously composed group discussions, and 2) in France, with 19 single patient interviews. The data were collected from October 2020 to January 2021. Influencing factors were categorized into twelve subcategories. Patients have similar experiences in both countries with regard to all facilitating categories, for instance, the role of health providers, awareness of EHR and social norms. However, we highlighted important differences between the two systems regarding hurdles impeding EHR usage, namely, a lack of communication as well as transparency or information security about EHR. Implementing additional safeguards to enhance privacy protection and supporting patients to improve their digital ability may help to diminish the perception of EHR-induced barriers and improve patients' health and commitment in the long term. Understanding the differences and similarities will help to develop practical implications to tackle the problem of low EHR usage rates in the long run. This problem is prevalent in countries with both types of EHR default settings.

Electronic Health Record Adoption in Oral and Dental Health Centres in Turkey

The digitalisation studies in public hospitals in Turkey started with the Health Transformation Program in 2003. The Ministry of Health has been measuring the dissemination of meaningful usage and adoption of electronic health record (EHR) using Electronic Medical Record Adoption Model (EMRAM) and Outpatient Electronic Medical Record Adoption Model (O-EMRAM). Using a comprehensive survey, our study intends to measure the stage of EHR adoption in oral and dental health centres (ODHCs) providing primary healthcare services in Turkey. The results obtained were classified by basic and comprehensive EHR functions and benchmarked against the studies addressing EHR adoption in primary healthcare institutions of other countries. In 2021, 167 ODHCs/oral and dental health hospitals (ODHHs) actively operating in Turkey completed the O-EMRAM survey. The data obtained from the survey results were analysed with QlikView Personal Edition. The availability and prevalence of medical information systems and EHR functions and their use were measured. It is observed that 59 (40.7%) of ODHCs/ODHHs have comprehensive EHR functions, while the remaining 86 (59.3%) have basic EHR functions. Under these circumstances, it can be stated that all ODHCs/ODHHs in Turkey use at least basic EHR functions. All ODHCs/ODHHs in Turkey have at least basic EHR functions. The integration of e-prescription, electronic authorisation system and e-Pulse used throughout Turkey and Health Information Management System Society (HIMSS) used in ODHCs/ODHHs can be listed as one of the decisive factors in this result. ODHCs/ODHHs still have a long way to go in adopting EHR, but the current circumstances are also promising. It is considered that this study will serve as a baseline for future measurements and produce a notable result for decision-makers.

Secure Cloud-Based Electronic Health Records: Cross-Patient Block-Level Deduplication with Blockchain Auditing.

In today's data-driven world, the exponential growth of digital information poses significant challenges in data management. In recent years, the adoption of cloud-based Electronic Health Records (EHR) sharing schemes has yielded numerous advantages like improved accessibility, availability, and enhanced interoperability. However, the centralized nature of cloud storage presents challenges in terms of information storage, privacy protection, and security. Despite several approaches that have been presented to ensure secure deduplication of similar EHRs, the validation of data integrity without a third-party auditor (TPA) remains a persistent task. Because involving a TPA raises concerns about the confidentiality and privacy of crucial healthcare information. To tackle this challenge, a novel cloud storage auditing technique is proposed that incorporates cross-patient block-level deduplication while upholding strong privacy protection, ensuring that EHR is not compromised. Here, we introduced blockchain technology to achieve integrity verification, thus eliminating the need for a TPA by providing a decentralized and transparent mechanism. Additionally, an index for all EHRs has been generated to facilitate block-level duplicate checks and employ a novel strategy to prevent adversaries from acquiring original information saved in the cloud storage. The security of the proposed approach is established against factorization attacks and decrypt exponent attacks. The performance evaluation demonstrates the superior efficiency of the proposed scheme in terms of file authenticator generation, challenge creation, and proof verification to other existing client-side deduplication approaches.

Legal and Ethical Issues Associated With Challenges in the Implementation of the Electronic Medical Record System and Its Current Laws in India.

Electronic health records (EHR) have revolutionized healthcare by providing efficient access to patient information, but their implementation poses various challenges. This paper examines the ethical and legal issues surrounding EHR adoption, particularly focusing on the healthcare landscape in India. Ethical considerations, including patient autonomy, confidentiality, beneficence, and justice, must guide EHR implementation to protect patient rights and privacy. Legal issues such as medical errors, malpractice, data breaches, and billing inaccuracies underscore the importance of robust policies and security measures. Threats to EHRs, such as phishing attacks, malware, encryption vulnerabilities, and insider threats, emphasize the need for comprehensive cybersecurity strategies. Overcoming challenges in EHR implementation requires meticulous planning, financial investment, staff training, and stakeholder support. Despite the complexities involved, the benefits of EHR adoption in improving patient care and operational efficiency justify the efforts required to address legal, ethical, and technical concerns. Embracing EHRs while mitigating associated risks is essential for delivering high-quality healthcare in the digital age.

Multimodal risk prediction with physiological signals, medical images and clinical notes

The broad adoption of electronic health record (EHR) systems brings us a tremendous amount of clinical data and thus provides opportunities to conduct data-based healthcare research to solve various clinical problems in the medical domain. Machine learning and deep learning methods are widely used in the medical informatics and healthcare domain due to their power to mine insights from raw data. When adapting deep learning models for EHR data, it is essential to consider its heterogeneous nature: EHR contains patient records from various sources including medical tests (e.g. blood test, microbiology test), medical imaging, diagnosis, medications, procedures, clinical notes, etc. Those modalities together provide a holistic view of patient health status and complement each other. Therefore, combining data from multiple modalities that are intrinsically different is challenging but intuitively promising in deep learning for EHR. To assess the expectations of multimodal data, we introduce a comprehensive fusion framework designed to integrate temporal variables, medical images, and clinical notes in EHR for enhanced performance in clinical risk prediction. Early, joint, and late fusion strategies are employed to combine data from various modalities effectively. We test the model with three predictive tasks: in-hospital mortality, long length of stay, and 30-day readmission. Experimental results show that multimodal models outperform uni-modal models in the tasks involved. Additionally, by training models with different input modality combinations, we calculate the Shapley value for each modality to quantify their contribution to multimodal performance. It is shown that temporal variables tend to be more helpful than CXR images and clinical notes in the three explored predictive tasks.

The Impact of Market Factors on Meaningful Use of Electronic Health Records Among Primary Care Providers: Evidence From Florida Using Resource Dependence Theory and Information Uncertainty Perspective.

Using federal funds from the 2009 Health Information Technology for Economic and Clinical Health Act, the Centers for Medicare and Medicaid Services funded the 2011-2021 Medicaid electronic health record (EHR) incentive programs throughout the country. Identify the market factors associated with Meaningful Use (MU) of EHRs after primary care providers (PCPs) enrolled in the Florida-EHR incentives program through Adopting, Improving, or Upgrading (AIU) an EHR technology. Retrospective cohort study using 2011-2018 program records for 8464 Medicaid providers. MU achievement after first-year incentives. The resource dependence theory and the information uncertainty perspective were used to generate key-independent variables, including the county's rurality, educational attainment, poverty, health maintenance organization penetration, and number of PCPs per capita. All the county rates were converted into 3 dichotomous measures corresponding to high, medium, and low terciles. Descriptive and bivariate statistics were calculated. A generalized hierarchical linear model was used because MU data were clustered at the county level (level 2) and measured at the practice level (level 1). Overall, 41.9% of Florida Medicaid providers achieved MU after receiving first-year incentives. Rurality was positively associated with MU ( P <0.001). Significant differences in MU achievements were obtained when we compared the "high" terciles with the "low" terciles for poverty rates ( P =0.002), health maintenance organization penetration rates ( P =0.02), and number of PCPs per capita ( P =0.01). These relationships were negative. Policy makers and health care managers should not ignore the contribution of market factors in EHR adoption.

Value of Electronic Health Records Measured Using Financial and Clinical Outcomes: Quantitative Study.

The Health Information Technology for Economic and Clinical Health Act of 2009 was legislated to reduce health care costs, improve quality, and increase patient safety. Providers and organizations were incentivized to exhibit meaningful use of certified electronic health record (EHR) systems in order to achieve this objective. EHR adoption is an expensive investment, given the resources and capital that are invested. Due to the cost of the investment, a return on the EHR adoption investment is expected. This study performed a value analysis of EHRs. The objective of this study was to investigate the relationship between EHR adoption levels and financial and clinical outcomes by combining both financial and clinical outcomes into one conceptual model. We examined the multivariate relationships between different levels of EHR adoption and financial and clinical outcomes, along with the time variant control variables, using moderation analysis with a longitudinal fixed effects model. Since it is unknown as to when hospitals begin experiencing improvements in financial outcomes, additional analysis was conducted using a 1- or 2-year lag for profit margin ratios. A total of 5768 hospital-year observations were analyzed over the course of 4 years. According to the results of the moderation analysis, as the readmission rate increases by 1 unit, the effect of a 1-unit increase in EHR adoption level on the operating margin decreases by 5.38%. Hospitals with higher readmission payment adjustment factors have lower penalties. This study fills the gap in the literature by evaluating individual relationships between EHR adoption levels and financial and clinical outcomes, in addition to evaluating the relationship between EHR adoption level and financial outcomes, with clinical outcomes as moderators. This study provided statistically significant evidence (P<.05), indicating that there is a relationship between EHR adoption level and operating margins when this relationship is moderated by readmission rates, meaning hospitals that have adopted EHRs could see a reduction in their readmission rates and an increase in operating margins. This finding could further be supported by evaluating more recent data to analyze whether hospitals increasing their level of EHR adoption would decrease readmission rates, resulting in an increase in operating margins. Hospitals would incur lower penalties as a result of improved readmission rates, which would contribute toward improved operating margins.

Understanding the role and impact of electronic health records in labor and delivery nursing practice: A scoping review protocol.

Electronic health records have a significant impact on nursing practice, particularly in specializations such as labor and delivery, or acute care maternity nursing practice. Although primary studies on the use of electronic health records in labor and delivery have been done, no reviews on this topic exist. Moreover, the topic of labor and delivery nurses' organizing work in the electronic health record-enabled context has not been addressed. To (a) synthesize research on electronic health record use in labor and delivery nursing and (b) map how labor and delivery nursing organizing work is transformed by the electronic health record (as described in the reviewed studies). The scoping review will be guided by a modified methodology based on selected recommendations from the Joanna Briggs Institute and the Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews. A comprehensive search will be conducted in the following databases: CINAHL Complete, MEDLINE, Academic Search Complete, Web of Science, Scopus and Dissertations and Theses Abstracts and Indexes. Included sources will be primary research, dissertations, or theses that address the use of electronic health records in labor and delivery nursing practice in countries with high levels of electronic health record adoption. Data extracted from included sources will be analyzed thematically. Further analysis will theorize labor and delivery nurses' organizing work in the context of electronic health record use by utilizing concepts from Davina Allen's Translational Mobilization Theory. Findings will be presented in tabular and descriptive formats. The findings of this review will help understand transformations of nursing practice in the electronic health record-enabled labor and delivery context and identify areas of future research. We will propose an extension of the Translational Mobilization Theory and theorize nurses' organizing work involving the use of the electronic health record.

FACTORS ASSOCIATED WITH ELECTRONIC HEALTH RECORD ADOPTION AMONG ADULT DAY SERVICES IN THE US

Abstract Successful adoption of Electronic Health Records (EHR) is becoming increasingly important for Adult Day Service Centers (ADSC) to function effectively and competently, particularly in care coordination with other healthcare providers. Therefore, in the present study, we assessed the EHR adoption among ADSC and its associated organizational characteristics using the 2018 National Study of Long-Term Care Providers (NPALS). The sample included 4,035 ADSC from a national representative sample. Directors or managers of ADSC completed the survey that included questions on organization characteristics, staffing, practice procedures, services, technology use, etc. Findings reveal that the adoption rate of EHR among ADSC was less than thirty percent and less than twenty percent of ADSC used EHR for health information exchange with either physicians or pharmacists. In addition, we found that an ADSC located near other healthcare providers, with Medicaid authorization and a higher percentage of Medicaid patients, and various computer capabilities such as recording participants’ demographic information, clinical notes, medications, service plans, and lab results were related to a higher likelihood of EHR use and EHR exchange. However, possibly due to privacy concerns, the capabilities to record participant problems and view lab results, negatively predict EHR exchange with physicians or pharmacists. The findings are discussed in terms of challenges and strategies to promote EHR adoption in ADSC.

Adoption of Electronic Health Record Among Substance Use Disorder Treatment Programs: Nationwide Cross-Sectional Survey Study.

Electronic health record (EHR) systems have been shown to be associated with improvements in care processes, quality of care, and patient outcomes. EHR also has a crucial role in the delivery of substance use disorder (SUD) treatment and is considered important for addressing SUD crises, including the opioid epidemic. However, little is known about the adoption of EHR in SUD treatment programs or the organizational-level factors associated with the adoption of EHR in SUD treatment. We examined the adoption of EHR in SUD programs, with a focus on changes in adoption from 2014 to 2017, and identified organizational-level factors associated with EHR adoption. We used data from the 2014 and 2017 National Drug Abuse Treatment System Surveys. Our analysis included 1027 SUD programs (531 in 2014 and 496 in 2017). We used chi-square and Mann-Whitney U tests for categorical and continuous variables, respectively, to assess changes in EHR adoption, technology use, program, and client characteristics. We also investigated differences in characteristics and barriers to adoption by EHR adoption status (adopted EHR vs had not adopted or were planning to adopt EHR). We then conducted multivariate logistic regressions to examine internal and external factors associated with EHR adoption. The adoption of EHR increased significantly from 57.6% (306/531) in 2014 to 69.2% (343/496) in 2017 (P<.001), showing that nearly one-third (153/496, 30.8%) of SUD programs had not yet adopted an EHR system by 2017. We identified a significant increase in technology use and ownership by a parent company (P=.01 and P<.001) and a decrease in the percentage of uninsured patients in 2017 (P<.001), compared to 2014. Our analysis further showed significant differences by adoption status for three major barriers to adoption: (1) start-up costs, (2) ongoing financial costs, and (3) privacy or security concerns (P<.001). Programs that used computerized scheduling (adjusted odds ratio [AOR] 3.02, 95% CI 2.23-4.09) and billing systems (AOR 2.29, 95% CI 1.62-3.25) were more likely to adopt EHR. Similarly, ownership type, such as private nonprofit (AOR 1.86, 95% CI 1.31-2.65) and public (AOR 2.14, 95% CI 1.27-3.67), or interest in participating in a patient-centered medical home (AOR 1.93, 95% CI 1.29-2.92), were associated with an increased likelihood to adopt EHR. Overall, SUD programs were more likely to adopt an EHR system in 2017 compared to 2014 (AOR 1.44, 95% CI 1.07-1.94). Our findings highlighted that SUD programs may be on track to achieve widespread EHR adoption. However, there is a need for focused strategies, resources, and policies explicitly designed to systematically address barriers and tackle obstacles to expanding the adoption of EHR systems. These efforts must be holistic and address factors at multiple organizational levels.

Healthcare information management and operational cost performance: empirical evidence.

Healthcare knowledge management systems can mitigate hospitals' operational inefficiency. As a healthcare information technology, the electronic health record (EHR) receives much attention from medical institutions due to its considerable impact on operational cost performance. This paper focuses on EHR systems to address operational inefficiency by which patients pay more for health care services, and many U.S. hospitals are filing for bankruptcy. From the theoretical perspective of the practice-based view, this paper introduces a path to implement EHR systems for improving cost performance. The empirical investigation is archival data of 200 hospitals collected from the U.S. healthcare agencies. Findings contribute to prior work by hypothesizing moderating and mediating roles in EHR systems implementation. This paper introduces absorptive capacity and monitoring mechanisms as enablers of implementing EHR systems. The results showed that hospital monitoring strengthens the relationship between absorptive capacity and electronic health record systems implementation, which results in better operational cost performance. Theoretically, this study supports the long-term potential benefits of EHR adoption, and its findings are consistent with optimizing efficiency through data standardization and interoperability. From a practical perspective, this study supports hospitals' investments in evolving healthcare information technology systems through the development of a knowledge-based system employing EHR, particularly when hospitals are merging or need a financial strategic plan to control expenses.

Pre-pandemic assessment: a decade of progress in electronic health record adoption among U.S. hospitals.

As the COVID-19 pandemic loomed, the adoption of electronic health records (EHRs) in US hospitals became a pivotal concern. This study provides a pre-pandemic assessment, highlighting a decade of progress in EHR adoption from 2009 to 2019, with the last available survey conducted from January to June of 2020. It delves into the current EHR adoption rates, variations across different hospital categories, the influence of major vendors, and the challenges in implementing these systems. The study found that basic EHR adoption surged from 6.6% to 81.2%, while comprehensive systems increased from 3.6% to 63.2%. Despite this growth, the findings point to enduring disparities among hospitals, a concentrated market share by 6 vendors (90%), and significant concerns regarding maintenance costs. These insights provide an invaluable snapshot of the state of EHR adoption at the brink of the pandemic, serving as a benchmark to assess hospitals' readiness to utilize digital infrastructure in health care. The conclusions underscore the necessity for strategic policy interventions to encourage a competitive landscape and guarantee equitable access, ultimately strengthening the health care system's responsiveness to global health crises such as COVID-19.

Medical Specialty Classification Based on Semiadversarial Data Augmentation.

Rapidly increasing adoption of electronic health record (EHR) systems has caused automated medical specialty classification to become an important research field. Medical specialty classification not only improves EHR system retrieval efficiency and helps general practitioners identify urgent patient issues but also is useful in studying the practice and validity of clinical referral patterns. However, currently available medical note data are imbalanced and insufficient. In addition, medical specialty classification is a multicategory problem, and it is not easy to remove sensitive information from numerous medical notes and tag them. To solve those problems, we propose a data augmentation method based on adversarial attacks. The semiadversarial examples generated during the dynamic process of adversarial attacking are added to the training set as augmented examples, which can effectively expand the coverage of the training data on the decision space. Besides, as nouns in medical notes are critical information, we design a classification framework incorporating probabilistic information of nouns, with confidence recalculation after the softmax layer. We validate our proposed method on an 18-class dataset with extremely unbalanced data, and comparison experiments with four benchmarks show that our method improves accuracy and F1 score to the optimal level, by an average of 14.9%.

Electronic medical record and its impact on health care and management. A systematic review between the years 2013 – 2023

The adoption of Electronic Health Records (EHR) has revolutionized the landscape of healthcare and healthcare management in recent decades. These technological systems have been the subject of extensive interest and study to understand their impact on improving patient care and efficiency in health management. For this reason, this study proposes to evaluate the impact of the use of electronic medical records on health care and management. In addition, the study includes a systematic review of the literature of research carried out between 2013 and 2023 on the use of the Electronic Health Record (EHR) focused on patient care and health management. The PICO methodology was used to formulate the search equation in the Scopus database. To select the studies, the PRISMA methodology was used through 3 stages: identification, screening, and inclusion, obtaining a total of 17 articles for review, according to inclusion and exclusion eligibility criteria. At the beginning of the systematic search, 56400 studies were found, 5220 were related to health care, 244 researchers work carried out between 2013 and 2023 focused on health management. Also, 17 studies obtained at the end of the third search stage, 42,11 % indicated that the EHR facilitates medical care, 21,05 % indicated that it provides better safety and greater patient satisfaction. On the other hand, 36,36 % and 45,45 % mentioned that with the EHR there is a good quality of care and better clinical management, respectively, compared to the use of paper medical records. In conclusion, the EHR offers benefits in medical care and facilitates decision making at the health management level. Its interoperability means that clinical management is integrated with all other medical systems to provide quality care, despite certain limitations that persist in the health field.

Ethical Challenges of Using Synthetic Data

There is an outburst of digitized medical data with the growing adoption of Electronic Health Record (EHR) systems but have restricted access due to legal compliances. This lack of data accessibility has piqued the interest in generating and using synthetic data. Synthetic data is programmatically generated using the statistical properties of the real dataset. Although synthetic data tackles the issue of legal compliance, there are some ethical concerns associated with it. In this paper, we discuss three ethical concerns of synthetic medical data such as fairness, privacy and unwarranted use. Further, we identify a need to develop a practical framework for statistical evaluation metrics for synthetically generated data.

Assessing Electronic Health Record (EHR) Use during a Major EHR Transition: An Innovative Mixed Methods Approach

BackgroundElectronic health record (EHR) transitions are inherently disruptive to healthcare workers who must rapidly learn a new EHR and adapt to altered clinical workflows. Healthcare workers’ perceptions of EHR usability and their EHR use patterns following transitions are poorly understood. The Department of Veterans Affairs (VA) is currently replacing its homegrown EHR with a commercial Cerner EHR, presenting a unique opportunity to examine EHR use trends and usability perceptions.ObjectiveTo assess EHR usability and uptake up to 1-year post-transition at the first VA EHR transition site using a novel longitudinal, mixed methods approach.DesignA concurrent mixed methods strategy using EHR use metrics and qualitative interview data.Participants141 clinicians with data from select EHR use metrics in Cerner Lights On Network®. Interviews with 25 healthcare workers in various clinical and administrative roles.ApproachWe assessed changes in total EHR time, documentation time, and order time per patient post-transition. Interview transcripts (n = 90) were coded and analyzed for content specific to EHR usability.Key ResultsTotal EHR time, documentation time, and order time all decreased precipitously within the first four months after go-live and demonstrated gradual improvements over 12 months. Interview participants expressed ongoing concerns with the EHR’s usability and functionality up to a year after go-live such as tasks taking longer than the old system and inefficiencies related to inadequate training and inherent features of the new system. These sentiments did not seem to reflect the observed improvements in EHR use metrics.ConclusionsThe integration of quantitative and qualitative data yielded a complex picture of EHR usability. Participants described persistent challenges with EHR usability 1 year after go-live contrasting with observed improvements in EHR use metrics. Combining findings across methods can provide a clearer, contextualized understanding of EHR adoption and use patterns during EHR transitions.

Basic electronic health record (EHR) adoption in **Türkiye is nearly complete but challenges persist

BackgroundThe digitalization studies in public hospitals in Türkiye started with the Health Transformation Program in 2003. As digitalization was accomplished, the policymakers needed to measure hospitals’ electronic health record (EHR) usage and adoptions. The ministry of health has been measuring the dissemination of meaningful usage and adoption of EHR since 2013 using Electronic Medical Record Adoption Model (EMRAM). The first published study about this analysis covered the surveys applied between 2013 and 2017. The results showed that 63.1% of all hospitals in Türkiye had at least basic EHR functions, and 36% had comprehensive EHR functions. Measuring the countrywide EHR adoption level is becoming popular in the world. This study aims to measure adoption levels of EHR in public hospitals in Türkiye, indicate the change to the previous study, and make a benchmark with other countries measuring national EHR adoption levels. The research question of this study is to reveal whether there has been a change in the adoption level of EHR in the three years since 2018 in Türkiye. Also, make a benchmark with other countries such as the US, Japan, and China in country-wide EHR adoption in 2021.MethodsIn 2021, 717 public hospitals actively operating in Türkiye completed the EMRAM survey. The survey results, deals with five topics (General Stage Status, Information Technology Security, Electronic Health Record/Clinical Data Repository, Clinical Documentation, Closed-Loop Management), was reviewed by the authors. Survey data were compared according to hospital type (Specialty Hospitals, General Hospitals, Teaching and Research Hospitals) in terms of general stage status. The data obtained from the survey results were analyzed with QlikView Personal Edition. The availability and prevalence of medical information systems and EHR functions and their use were measured.ResultsWe found that 33.7% of public hospitals in Türkiye have only basic EHR functions, and 66.3% have extensive EHR functions, which yields that all hospitals (100%) have at least basic EHR functions. That means remarkable progress from the previous study covering 2013 and 2017. This level also indicates that Türkiye has slightly better adoption from the US (96%) and much better than China (85.3%) and Korea (58.1%).ConclusionsAlthough there has been outstanding (50%) progress since 2017 in Turkish public hospitals, it seems there is still a long way to disseminate comprehensive EHR functions, such as closed-loop medication administration, clinical decision support systems, patient engagement, etc. Measuring the stage of EHR adoption at regular intervals and on analytical scales is an effective management tool for policymakers. The bottom-up adoption approach established for adopting and managing EHR functions in the US has also yielded successful results in Türkiye.

Inpatient EHR User Experience and Hospital EHR Safety Performance

Despite the broad adoption and optimization of electronic health record (EHR) systems across the continuum of care, serious usability and safety problems persist. To assess whether EHR safety performance is associated with EHR frontline user experience in a national sample of hospitals. This cross-sectional study included all US adult hospitals that used the National Quality Forum Leapfrog Health IT Safety Measure and also used the ARCH Collaborative EHR User experience survey from January 1, 2017, to January 1, 2019. Data analysis was performed from September 2020 to November 2022. The primary outcomes were hospital performance on the Leapfrog Health IT Safety measure (overall and 10 subcomponents) and the ARCH collaborative frontline user experience scores (overall and 8 subcomponents). Ordinary least squares models with survey responses clustered by hospital were used to assess associations between the overall measures and their subcomponents. There were 112 hospitals and 5689 frontline user surveys included in the study. Hospitals scored a mean of 0.673 (range, 0.297-0.973) on the Leapfrog Health IT safety measure; the mean ARCH EHR user experience score was 3.377 (range, 1 [best] to 5 [worst]). The adjusted β coefficient between the overall safety score and overall user experience score was 0.011 (95% CI, 0.006-0.016). The ARCH overall score was also significantly associated with 10 subcategory scores of the Leapfrog Health IT safety score, and the overall Leapfrog score was associated with the 8 subcategory scores of the ARCH user experience score. This cross-sectional study found a positive association between frontline user-rated EHR usability and EHR safety performance. This finding suggests that improving EHR usability, which is a current well-known pain point for EHR users, could have direct benefits in terms of improved EHR safety.

Digital Technologies in Healthcare Management: A Study of Influence of National Culture for Adoption of Electronic Health Records in India and Australia

In the emerging healthcare landscape, digital technologies like electronic health records (EHRs) could play a vital role in healthcare management. While developed nations like Australia have taken the lead in implementing EHRs, developing nations like India, have lagged. Prior research in developing and developed countries has mainly focused on government policy, interoperability, standardization, security, technological infrastructure, and finance as EHR adoption factors, but the influence of national culture has remained unexplored. This study addresses this gap in the literature by comparing the influence of national culture on EHR adoption in India (a developing nation) and Australia (a developed nation). In this study, Hofstede's cultural dimensions were utilized to determine the influence of national culture. The assessment of India revealed that the adoption of EHRs could be influenced by the use of EHRs by respectable healthcare providers, the commitment and support of top management, and the education and training of healthcare managers to minimize risks connected with the use of EHRs. On the other hand, the adoption of EHRs in Australia may be influenced by professional involvement and discussion of the benefits of EHRs, business profitability, timely financial outcomes, and education and training of healthcare managers to understand the benefits of EHRs adoption.