EHR Systems Research Articles

Effects of HBsAg carriers on pregnancy complications in pregnant women: a retrospective cohort study.

Hepatitis B virus (HBV) infection is a major health threat worldwide, especially in developing countries. We aimed to investigate the impact of hepatitis B carrier on pregnancy complications in pregnant women, in China. This retrospective cohort study was conducted by using data from the EHR system of Longhua District People's Hospital in Shenzhen, China, from January 2018 to June 2022. Binary logistic regression was used to evaluate the relationship between HBsAg carrier status and pregnancy complications and pregnancy outcomes. The study included 2095 HBsAg carriers (exposed group) and 23,019 normal pregnant women (unexposed group). Pregnant women in the exposed group were older than the pregnant women in the unexposed group (29 (27,32) vs. 29 (26,32), p < 0.001). In addition, the incidence of some adverse pregnancy complications in the exposure group was lower than that in the unexposed group, including hypothyroidism of pregnancy (adjusted odds ratio [aOR], 0.779; 95% confidence interval [CI], 0.617-0.984; p = 0.036), hyperthyroidism of pregnancy (aOR, 0.388; 95% CI, 0.159-0.984; p = 0.038), pregnancy induced hypertension (aOR, 0.699; 95% CI, 0.551-0.887; p = 0.003), antepartum hemorrhage (aOR, 0.294; 95% CI, 0.093-0.929; p = 0.037). However, compared with the unexposed group, the exposed group had a higher risk of lower birth weight (aOR, 1.12; 95% CI, 1.02-1.23; p = 0.018) and intrahepatic cholestasis of pregnancy (aOR, 2.888, 95% CI, 2.207-3.780; p < 0.001). The prevalence rate of HBsAg carriers in pregnant women in Longhua District of Shenzhen was 8.34%. Compared with normal pregnant women, HBsAg carriers have a higher risk of ICP, a lower risk of gestational hypothyroidism and PIH, and a lower birth weight of their infants.

ELGA Terminology Server for Clinical Decision Support: A Case-Study Using an Existing Knowledge Base, CDS Hooks and FHIR.

There are many medical knowledge bases with potential for supporting medical professionals in their decision-making during routine care, yet usage of these sources remains low. Standardized linking of Clinical Decision Support (CDS) applications and existing medical knowledge bases is not a common practice. Using existing eHealth standards to increase the utilization of knowledge bases and implement a prototype. Linking an existing online knowledge base via a FHIR CodeSystem supplement to the Austrian national EHR (ELGA) terminology server and accessing these data using CDS Hooks and FHIR. We tested the approach by incorporating photosensitivity data of medications into a local copy of the Austrian terminology server. These data are directly used by a CDS Hooks compliant CDS service. The Austrian Terminology Server could be an important interface to access existing knowledge bases from within EHR systems. FHIR and CDS Hooks could lead the way for a simple and open integration of CDS services into EHR systems.

Evaluating a CDS Hook for FHIR Questionnaires in a SMART on FHIR App and an Existing Dermatological CDS System.

To deploy clinical decision support (CDS) systems in routine patient care they have to be certified as a medical device. The European Medical Device Regulation explicitly asks for the use of standards and interoperability in the approval process. We extended an existing dermatological CDS system with emerging standards for CDS interoperability, to facilitate a future integration into existing healthcare infrastructure, and approval as a medical device. The data collection part of a CDS system was extended with the endpoints required by the CDS Hooks specification. FHIR QuestionnaireResponse resources trigger a newly defined hook. One hundred and seventeen clinical observations and patient variables needed for the ranking of a disease were mapped to SNOMED CT or LOINC and modeled as FHIR Questionnaire which is rendered using LHC LForms in a SMART on FHIR app with the SMART Dev Sandbox. SMART on FHIR in combination with CDS Hooks facilitates the integration of existing CDS systems into EHR systems, potentially improving education and patient care.

Transforming Documents of the Austrian Nationwide EHR System into the OMOP CDM.

The Austrian nationwide EHR system ELGA can contribute valuable data for research due to its high volume of data and broad population coverage. In order to be applicable in international research projects, transformation to a standardized, research-oriented data model such as the OMOP common data model is essential. In this paper we describe our experience with the corresponding transformation task. Using Python scripts, we implemented a prototypical process that extracts, transforms, maps, and loads fully structured sections of ELGA documents to an OMOP database.

Abstract 3565: Establishing a multimodal data warehousing platform to accelerate discoveries in pediatric brain tumors for the Children’s Brain Tumor Network

Abstract Brain tumors are the leading cause of disease-related death in children and young adults ages 0-19 in largely populated countries such as the United States. In one year alone, 4,000 children and young adults will be diagnosed with a brain or central nervous system tumor in the United States. Brain tumors are complex and difficult to treat in growing children, with current treatments oftentimes causing significant and lifelong side effects. Furthermore, there have only been five drugs in the last 20 years approved by the FDA to treat pediatric brain tumors. Founded in 2011, the Children’s Brain Tumor Network (CBTN) is focused on accelerating the pace of translational research, the discovery of new treatments, and informing precision medicine for children diagnosed with brain tumors. CBTN comprises 32 member institutions/hospitals having over 4700 patient subjects enrolled, spanning 30+ brain tumor diagnoses, over 66,000 biobanked samples and 150 preclinical models. Longitudinal clinical data is also collected for every subject that is enrolled in the observational protocol. Through large scale data generation efforts funded by the NCI and foundational support, CBTN has whole genome, RNA-seq and other molecular characterization for over half of the enrolled patient population. Additionally, efforts have been underway to collect all pathology and radiology imaging and reporting for the subjects. With sequencing being done by multiple vendors, imaging protocols being different across multiple hospitals, and complex clinical treatment and longitudinal follow up data being translated from EHR systems, CBTN has created a rich, but complex, data landscape that is the largest of its kind in the world. In order to accelerate the process of going from data to cures, the data needs to be centralized, organized, and easily distributable. To do this, CBTN has built a first of its kind data workflow that acts as the inventory system for its various data assets. Using a modern data stack including dbt, PostgresSQL, Meltano and AWS, combined with utilization of FHIR as an interchange standard, data from multiple disparate sources such as REDcap, EHR systems, and PAC systems flow in near “real-time” to be utilized as integrated data resources The result of this modern, multimodal, and multi-institutional warehouse allows CBTN to distribute data quickly and accurately to translational researchers around the world and contribute data to key research efforts such as AACR Project Genie, Kids First Data Resource Center, NCI Childhood Cancer Data Initiative, and the NCI’s Open Targets Platform. Citation Format: Bailey K. Farrow, Nicholas Van Kuren, Nathan Young, Christopher Friedman, Meen Chul Kim, Alex Lubneuski, Jennifer Mason, Thinh (Bin) Nguyen, Zeinab Helili, Elizabeth Frenkel, Catherine Sullivan, Ariana Familiar, Yuankun Zhu, Mateusz Koptyra, Tatiana Patton, Jena Lilly, Phillip B. Storm, Adam Resnick, Allison P. Heath. Establishing a multimodal data warehousing platform to accelerate discoveries in pediatric brain tumors for the Children’s Brain Tumor Network. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3565.

Designing and implementing an electronic health record (Ehr) for telemedicine purposes

This research deals with the problem of maintaining data, deemed to be one of the biggest problems of health entities. Most hospitals and clinic suffer loss of data saved in databases and unavailability of strong cohesive information systems. The objective of this study is to design and implement a web-based EHR system that can help create a national repository of health data, and will therefore, make the deployment of telemedicine applications easier in the future. The EHR system ables to store the patient information, which normally includes personal information, address, demographics, progress notes, immunization, lab data, Radiology information, past medical history, family history, vital sign, tobacco history, alcohol history, examinations, and so on. The proposed system consists of two another components, Queries system which is built to combine data from different tables by using a combination of mathematical or logical operators, Queries system used to answer on a an academic researchers questions. And the front-end of the EHR system which it is a set of GUI(Graphic User Interfaces) that act as a bridge in between the end users and the EHR system.

Adapting hybrid approaches for electronic medical record management and sharing using blockchain sharding

In the past few years, it is noticed that management and sharing medical records is a key step towards increasing healthcare provider connectivity and making the healthcare system more efficient. The scalability and sustainability issues confer to mismanagement of patient is record and also raised several issues in privacy and security. The study aims to suggest more efficient alternatives for Electronic Healthcare System. Scalability and privacy are the major limitations that existing systems contain so the goal of this study is to define alternatives about how parameters like scalability, usability and data protection could be achieved in an efficient manner for healthcare system. In the healthcare industry, providing accurate, thorough, and up-to-date information on patients is critical. Another feature that allows researchers to consider efficient EHR systems is rapid access to patient records for boosting efficiency and coordination. Blockchain sharding technique is utilized along with hyper-ledger protocols and Proof-of-Authority to carry out our model implementation.

Privacy in electronic health records: a systematic mapping study

Abstract Main Electronic health record (EHR) applications are digital versions of paper-based patient health information. Traditionally, medical records are made on paper. However, nowadays, advances in information and communication technology have made it possible to change medical records from paper to EHR. Therefore, preserving user data privacy is extremely important in healthcare environments. The main challenges are providing ways to make EHR systems increasingly capable of ensuring data privacy and at the same time not compromising the performance and interoperability of these systems. Subject and methods This systematic mapping study intends to investigate the current research on security and privacy requirements in EHR systems and identify potential research gaps in the literature. The main challenges are providing ways to make EHR systems increasingly capable of ensuring data privacy, and at the same time, not compromising the performance and interoperability of these systems. Our research was carried out in the Scopus database, the largest database of abstracts and citations in the literature with peer review. Results We have collected 848 articles related to the area. After disambiguation and filtering, we selected 30 articles for analysis. The result of such an analysis provides a comprehensive view of current research. Conclusions We can highlight some relevant research possibilities. First, we noticed a growing interest in privacy in EHR research in the last 6 years. Second, blockchain has been used in many EHR systems as a solution to achieve data privacy. However, it is a challenge to maintain traceability by recording metadata that can be mapped to private data of the users applying a particular mapping function that can be hosted outside the blockchain. Finally, the lack of a systematic approach between EHR solutions and existing laws or policies leads to better strategies for developing a certification process for EHR systems.

Accuracy of COVID-19-Like Illness Diagnoses in Electronic Health Record Data: Retrospective Cohort Study.

Electronic health record (EHR) data provide a unique opportunity to study the epidemiology of COVID-19, clinical outcomes of the infection, comparative effectiveness of therapies, and vaccine effectiveness but require a well-defined computable phenotype of COVID-19-like illness (CLI). The objective of this study was to evaluate the performance of pathogen-specific and other acute respiratory illness (ARI) International Statistical Classification of Diseases-9 and -10 codes in identifying COVID-19 cases in emergency department (ED) or urgent care (UC) and inpatient settings. We conducted a retrospective observational cohort study using EHR, claims, and laboratory information system data of ED or UC and inpatient encounters from 4 health systems in the United States. Patients who were aged ≥18 years, had an ED or UC or inpatient encounter for an ARI, and underwent a SARS-CoV-2 polymerase chain reaction test between March 1, 2020, and March 31, 2021, were included. We evaluated various CLI definitions using combinations of International Statistical Classification of Diseases-10 codes as follows: COVID-19-specific codes; CLI definition used in VISION network studies; ARI signs, symptoms, and diagnosis codes only; signs and symptoms of ARI only; and random forest model definitions. We evaluated the sensitivity, specificity, positive predictive value, and negative predictive value of each CLI definition using a positive SARS-CoV-2 polymerase chain reaction test as the reference standard. We evaluated the performance of each CLI definition for distinct hospitalization and ED or UC cohorts. Among 90,952 hospitalizations and 137,067 ED or UC visits, 5627 (6.19%) and 9866 (7.20%) were positive for SARS-CoV-2, respectively. COVID-19-specific codes had high sensitivity (91.6%) and specificity (99.6%) in identifying patients with SARS-CoV-2 positivity among hospitalized patients. The VISION CLI definition maintained high sensitivity (95.8%) but lowered specificity (45.5%). By contrast, signs and symptoms of ARI had low sensitivity and positive predictive value (28.9% and 11.8%, respectively) but higher specificity and negative predictive value (85.3% and 94.7%, respectively). ARI diagnoses, signs, and symptoms alone had low predictive performance. All CLI definitions had lower sensitivity for ED or UC encounters. Random forest approaches identified distinct CLI definitions with high performance for hospital encounters and moderate performance for ED or UC encounters. COVID-19-specific codes have high sensitivity and specificity in identifying adults with positive SARS-CoV-2 test results. Separate combinations of COVID-19-specific codes and ARI codes enhance the utility of CLI definitions in studies using EHR data in hospital and ED or UC settings.

Impact of Implementing Simulated Electronic Health Record into Nurse Aide CourseImpact of Implementing Simulated Electronic Health Record into Nurse Aide Course

Electronic health records are an integral part of the healthcare system and have been found to improve access to health services, increase efficiency within the health care system, &amp;amp; enhance the safety and quality of patient care (Kleib et al., 2021). Despite how vital EHRs are in healthcare, research found that only 20% of nurses surveyed had EHR training within the school (Repsha et al., 2020). When nursing students do receive simulated EHR training their documenting and critical thinking skills have shown to improve (Everett-Thomas et al., 2021). Students also report high satisfaction with use of the simulated EHR system. While there is research on the impact of simulated EHR education on nursing students, there is limited information on the impact of simulated EHR education on nurse aide students. It is anticipated that nurse aide students who experienced simulated EHR training within their nurse aide course reported higher confidence levels when using EHR systems in the clinical environment and when in the workforce than nurse aide students who did not receive simulated EHR training

Automated HL7v2 LRI informatics framework for streamlining genomics-EHR data integration

While VCF formatted files are the lingua franca of next-generation sequencing, most EHRs do not provide native VCF support. As a result, labs often must send non-structured PDF reports to the EHR. On the other hand, while FHIR adoption is growing, most EHRs support HL7 interoperability standards, particularly those based on the HL7 Version 2 (HL7v2) standard. The HL7 Version 2 genomics component of the HL7 Laboratory Results Interface (HL7v2 LRI) standard specifies a formalism for the structured communication of genomic data from lab to EHR. We previously described an open-source tool (vcf2fhir) that converts VCF files into HL7 FHIR format. In this report, we describe how the utility has been extended to output HL7v2 LRI data that contains both variants and variant annotations (e.g., predicted phenotypes and therapeutic implications). Using this HL7v2 converter, we implemented an automated pipeline for moving structured genomic data from the clinical laboratory to EHR. We developed an open source hl7v2GenomicsExtractor that converts genomic interpretation report files into a series of HL7v2 observations conformant to HL7v2 LRI. We further enhanced the converter to produce output conformant to Epic's genomic import specification and to support alternative input formats. An automated pipeline for pushing standards-based structured genomic data directly into the EHR was successfully implemented, where genetic variant data and the clinical annotations are now both available to be viewed in the EHR through Epic's genomics module. Issues encountered in the development and deployment of the HL7v2 converter primarily revolved around data variability issues, primarily lack of a standardized representation of data elements within various genomic interpretation report files. The technical implementation of a HL7v2 message transformation to feed genomic variant and clinical annotation data into an EHR has been successful. In addition to genetic variant data, the implementation described here releases the valuable asset of clinically relevant genomic annotations provided by labs from static PDFs to calculable, structured data in EHR systems.

Electronic Health Record Stress and Burnout Among Clinicians in Hospital Settings: A Systematic Review.

There is growing evidence to suggest that EHRs may be associated with clinician stress and burnout, which could hamper their effective use and introduce risks to patient safety. This systematic review aimed to examine the association between EHR use and clinicians' stress and burnout in hospital settings, and to identify the contributing factors influencing this relationship. The search included peer-reviewed published studies between 2000 and 2023 in English in CINAHL, Ovid Medline, Embase, and PsychINFO. Studies that provided specific data regarding clinicians' stress and/or burnout related to EHRs in hospitals were included. A quality assessment of included studies was conducted. Twenty-nine studies were included (25 cross-sectional surveys, one qualitative study, and three mixed methods), which focused on physicians (n = 18), nurses (n = 10) and mixed professions (n = 3). Usability issues and the amount of time spent on the EHR were the most significant predictors, but intensity of the working environment influenced high EHR-related workload and thereby also contributed to stress and burnout. The differences in clinicians' specialties influenced the levels of stress and burnout related to EHRs. This systematic review showed that EHR use was a perceived contributor to clinicians' stress and burnout in hospitals, primarily driven by poor usability and excessive time spent on EHRs. Addressing these issues requires tailored EHR systems, rigorous usability testing, support for the needs of different specialities, qualitative research on EHR stressors, and expanded research in Non-Western contexts.

A comparative study on HIPAA technical safeguards assessment of android mHealth applications.

Protecting personal health records is becoming increasingly important as more people use Mobile Health applications (mHealth apps) to improve their health outcomes. These mHealth apps enable consumers to monitor their health-related problems, store, manage, and share health records, medical conditions, treatment, and medication. With the increase of mHealth apps accessibility and usability, it is crucial to create, receive, maintain or transmit protected health information (PHI) on behalf of a covered entity or another business associate. The Health Insurance Portability and Accountability Act (HIPAA) provides guidelines to the app developers so that the apps must be compliant with required and addressable Technical Safeguards. However, most mobile app developers, including mHealth apps are not aware of HIPAA security and privacy regulations. Therefore, a research opportunity has emerged to develop an analytical framework to assist the developer to maintain a secure and HIPAA-compliant source code and raise awareness among consumers about the privacy and security of sensitive and personal health information. We proposed an Android source code analysis framework that evaluates twelve HIPAA Technical Safeguards to check whether a mHealth application is HIPAA compliant or not. The implemented meta-analysis and data-flow analysis algorithms efficiently identify the risk and safety features of mHealth apps that violate HIPAA regulations. Furthermore, we addressed API level checking for secure data communication mandated by recent CMS guidelines between third-party mobile health apps and EHR systems. Experimentally, a web-based tool has been developed for evaluating the efficacy of analysis techniques and algorithms. We have investigated 200 top popular Medical and Health & Fitness category Android apps collected from Google Play Store. We identified from the comparative analysis of the HIPAA rules assessment results that authorization to access sensitive resources, data encryption-decryption, and data transmission security is the most vulnerable features of the investigated apps. We provided recommendations to app developers about the most common mistake made at the time of app development and how to avoid these mistakes to implement secure and HIPAA-compliant apps. The proposed framework enables us to develop an IDE plugin for mHealth app developers and a web-based interface for mHealth app consumers.

STORIES from the FRONT LINES

Inside Precision MedicineVol. 9, No. S1 Spotlight SupplementSTORIES from the FRONT LINESNephi WaltonMD MS FACMG FAMIANephi WaltonMD MS FACMG FAMIADr Nephi Walton completed his MD and masters in biomedical informatics at the University of Utah School of Medicine. He completed a combined residency in pediatrics and genetics at Washington University in St Louis. He is boarded in both clinical genetics and clinical informatics. At Geisinger, he successfully completed a pilot integration of genomics data into the EPIC EHR system for both pharmacogenomics and CDC tier one genetic conditions. He currently serves as the associate medical director of Intermountain Precision Genomics where he co-leads the HerediGene genomic sequencing return of results program and runs the Intermountain precision genomics WGS clinic. He also serves as the associate medical director of Intermountain's sequencing laboratory. He is the chair of genomics and translational bioinformatics for the American Medical Informatics Association and has presented at several meetings on translating the use of genomics into general medical practice, something he is actively pursuing at Intermountain Healthcare.Search for more papers by this authorPublished Online:9 Jan 2023https://doi.org/10.1089/ipm.09.S1.05AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 9Issue S1Dec 2022 InformationCopyright © GEN PublishingTo cite this article:Nephi WaltonMD MS FACMG FAMIA.STORIES from the FRONT LINES.Inside Precision Medicine.Dec 2022.20-21.http://doi.org/10.1089/ipm.09.S1.05Published in Volume: 9 Issue S1: January 9, 2023PDF download

Robust Watermarking Method for Secure Transmission of Medical Images in EHR Systems

Robust Watermarking Method for Secure Transmission of Medical Images in EHR Systems

Safety and effectiveness of intranasal esketamine for treatment-resistant depression: a real-world retrospective study.

Aim: There is limited real-world evidence for patients with treatment-resistant depression (TRD) receiving esketamine nasal spray. Methods: This retrospective cohort study used data collected from a psychiatric clinic's EHR system. Results: A total of 171 TRD patients received esketamine July 2019-June 2021. This predominantly female, white population had several mental health comorbidities and high exposure to psychiatric medications. We observed significant reductions (p<0.001) in average PHQ-9 and GAD-7 scores from baseline (PHQ-9: mean: 16.7; SD: 5.8; GAD-7: mean: 12.0; SD: 5.8) to last available treatment (PHQ-9: mean: 12.0; SD: 6.4; GAD-7: mean: 8.7; SD: 5.6). There were no reports of serious adverse events. Conclusion: This study found a significant disease burden for patients with TRD. Esketamine appears to be well tolerated and effective in improving depression and anxiety.

Development of a Natural Language Processing System for Extracting Rheumatoid Arthritis Outcomes From Clinical Notes Using the National Rheumatology Informatics System for Effectiveness Registry.

To accelerate the use of outcome measures in rheumatology, we developed and evaluated a natural language processing (NLP) pipeline for extracting these measures from free-text outpatient rheumatology notes within the American College of Rheumatology's Rheumatology Informatics System for Effectiveness (RISE) registry. We included all patients in RISE (2015-2018). The NLP pipeline extracted scores corresponding to 8 measures of rheumatoid arthritis (RA) disease activity (DA) and functional status (FS) documented in outpatient rheumatology notes. Score extraction performance was evaluated by chart review, and we assessed agreement with scores documented in structured data. We conducted an external validation of our NLP pipeline using data from rheumatology notes from an academic medical center that is not included in the RISE registry. We processed over 34 million notes from 854,628 patients, 158 practices, and 24 electronic health record (EHR) systems from RISE. Manual chart review revealed a sensitivity, positive predictive value (PPV), and F1 score of 95%, 87%, and 91%, respectively. Substantial agreement was observed between scores extracted from RISE notes and scores derived from structured data (κ=0.43-0.68 among DA and 0.86-0.98 among FS measures). In the external validation, we found a sensitivity, PPV, and F1 score of 92%, 69%, and 79%, respectively. We developed an NLP pipeline to extract RA outcome measures from a national registry of notes from multiple EHR systems and found it to have good internal and external validity. This pipeline can facilitate measurement of clinical- and patient-reported outcomes for use in research and quality measurement.

EHR &amp; EMR - A Wholesome View on its Impact in EDI Transaction

This research examines how EHR/EMR technology affects hospital EDI transactions. An extensive Google Scholar and Dimensions peer-reviewed literature analysis indicates various EHR/EMR integration advantages. This enhances data quality and efficiency. The paper identified significant data sharing and legal compliance issues that may impede information exchange and privacy. EHR and EMR systems offer many advantages, but the research demonstrates that more effort is needed to standardize procedures and ensure systems operate together to improve EDI operations.

The Factors Contributing to Physicians' Current Use of and Satisfaction With Electronic Health Records in Kuwait's Public Health Care: Cross-sectional Questionnaire Study.

BackgroundElectronic health record (EHR) has emerged as a backbone health care organization that aims to integrate health care records and automate clinical workflow. With the adoption of the eHealth care system, health information communication technologies and EHRs are offering significant health care advantages in the form of error reduction, improved communication, and patient satisfaction.ObjectiveThis study aimed to (1) investigate factors associated with physicians’ EHR adoption status and prevalence of EHRs in Kuwait and (2) identify factors predicting physician satisfaction with EHRs in public hospitals in Kuwait.MethodsThis study was conducted at Kuwait’s public Al-Jahra hospital from May to September 2019, using quantitative research methods. Primary data were gathered via questionnaires distributed among 295 physicians recruited using convenience sampling. Data were analyzed in SPSS using descriptive, bivariate, and multivariate linear regression, adjusted for demographics.ResultsResults of the study revealed that the controlled variable of gender (β=–.197; P=.02) along with explanatory variables, such as training quality (β=.068; P=.005), perception of barriers (β=–.107; P=.04), and effect on physician (β=.521; P<.001) have a significant statistical relationship with physicians’ EHR adoption status. Furthermore, findings also suggested that controlled variables of gender (β=–.193; P=.02), education (β=–.164; P=.03), effect on physician (β=.417; P<.001), and level of ease of use (β=.254; P<.001) are significant predictors of the degree of physician satisfaction with the EHR system.ConclusionsThe findings of this study had significant managerial and practical implications for creating an inductive environment for the acceptance of EHR systems across a broad spectrum of health care system in Kuwait.

Satisfied or not satisfied? Electronic health records system implementation in Ghana: Health leaders’ perspective

BackgroundElectronic Health Records (EHR) has been espoused to be an innovation from the paper-based system, with benefits such as fast access to patient information thereby facilitating healthcare provider communication, healthcare continuity and improved quality of care. However, it is the extent of the quality of the electronic health records that determines the access to these stated benefits. The quality of health care records indirectly contributes to patient safety because inaccurate patient data can lead to improper diagnosis and consequently wrong treatment of patients. Most hospitals in Ghana, have recently transitioned into the EHR system, hence, there is a need to assess its accuracy, impact on workflow, staff training on usage, support from the EHR team, and the overall satisfaction of the EHR system. As health leaders are at the frontline of its implementation, their views on the challenges and successes of the EHR system are imperative.MethodThis qualitative study sought to explore the views of the health leaders on the implemented electronic health records system in nine (9) hospitals within three (3) regions in Ghana. Following ethical approval, GHS-ERC:007/04/21, focus group discussions were conducted with a minimum of 10 hospital leaders in each facility. These included quasi, government and private hospitals. Data was collected between September and November 2021.ResultsThe study found poor quality of records, lack of involvement of frontline clinicians in the development of the EHR system, inadequate training of staff and limited workstations as some of the challenges associated with the use of EHR in hospitals. Health leaders were generally not satisfied with the EHR system.ConclusionIt is recommended that addressing inputs from end-users as well as circulating more computers will motivate EHR usage and acceptance. Provision of additional workstations for the various units and involvement of staff in the system development would be most prudent to enable health workers to accept the EHR system in improving the quality of care.