Medical Students' Perspectives Regarding the Use of a Slit-Lamp Smartphone Adapter for Clinical Slit-Lamp Photography.

Background This study aimed to investigate medical students' perspectives regarding the ease and utility of smartphone slit-lamp photography. Methodology In this prospective experimental study, fourth and fifth-year medical students who were in or had finished ophthalmology rotation were included to attempt slit-lamp smartphone anterior segment photography on adult patients after a brief hands-on instruction course. Each medical student attempted to record five supervised slit-lamp videos of the anterior segment of five patients using the described adapter and their own smartphone. The time taken until photography was calculated for each attempt. After the fifth attempt, each medical student rated the ease of the use of this method of slit-lamp photography as well as their perspective regarding its utility as a potential means of medical education and telemedical consultations on a five-point Likert scale. Results A total of 33 medical students participated, with each successfully recording five slit-lamp examinations using their smartphones. The time used for the application of the adapter until the image capture ranged from 6 to 278 seconds (average = 39.51 ± 34.7 seconds) and markedly improved by the fifth attempt (30.5 ± 25.7 seconds) compared to the first attempt (67.3 ± 49.3 seconds). Learning this skill was perceived to be relatively easy (2.2 ± 1), with high potential in clinical education (4.6 ± 0.75) and teleconsultations (4.7 ± 0.65). Conclusions Smartphone slit-lamp photography is a relatively easy process. It can be quickly acquired by medical students and has the potential to enhance their medical education and telemedical consultation capabilities.

The Red Cross Red Crescent Health Information System (RCHIS): an electronic medical records and health information management system for the red cross red crescent emergency response units.

BACKGROUND: The Red Cross and Red Crescent Movement (RCRC) utilizes specialized Emergency Response Units (ERUs) for international disaster response. However, data collection and reporting within ERUs have been time-consuming and paper-based. The Red Cross Red Crescent Health Information System (RCHIS) was developed to improve clinical documentation and reporting, ensuring accuracy and ease of use while increasing compliance with reporting standards. CASE PRESENTATION: RCHIS is an Electronic Medical Record (EMR) and Health Information System (HIS) designed for RCRC ERUs. It can be accessed on Android tablets or Windows laptops, both online and offline. The system securely stores data on Microsoft Azure cloud, with synchronization facilitated through a local ERU server. The functional architecture covers all clinical functions of ERU clinics and hospitals, incorporating user-friendly features. A pilot study was conducted with the Portuguese Red Cross (PRC) during a large-scale event. Thirteen super users were trained and subsequently trained the staff. During the four-day pilot, 77 user accounts were created, and 243 patient files were documented. Feedback indicated that RCHIS was easy to use, requiring minimal training time, and had sufficient training for full utilization. Real-time reporting facilitated coordination with the civil defense authority. CONCLUSIONS: The development and pilot use of RCHIS demonstrated its feasibility and efficacy within RCRC ERUs. The system addressed the need for an EMR and HIS solution, enabling comprehensive clinical documentation and supporting administrative reporting functions. The pilot study validated the training of trainers' approach and paved the way for further domestic use of RCHIS. RCHIS has the potential to improve patient safety, quality of care, and reporting efficiency within ERUs. Automated reporting reduces the burden on ERU leadership, while electronic compilation enhances record completeness and correctness. Ongoing feedback collection and feature development continue to enhance RCHIS's functionality. Further trainings took place in 2023 and preparations for international deployments are under way. RCHIS represents a significant step toward improved emergency medical care and coordination within the RCRC and has implications for similar systems in other Emergency Medical Teams.

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.

Trends and Patterns in Electronic Health Record Research (1991-2022): A Bibliometric Analysis of Australian Literature.

Electronic Heath Records (EHRs) play vital roles in facilitating streamlined service provision and governance across the Australian health system. Given the recent challenges due to the COVID-19 pandemic, an ageing population, health workforce silos, and growing inefficiencies in traditional systems, a detailed historical analysis of the use of EHR research in Australia is necessary. The aim of this study is to examine the trends and patterns in EHR research in Australia over the past three decades by employing bibliometric methods. A total of 951 articles published in 443 sources were included in the bibliometric analysis. The annual growth rate of EHR research in Australia was about 17.1%. Since 2022, the main trending topics in EHR research were COVID-19, opioid usage, and natural language processing. A thematic analysis indicated aged care, clinical decision support systems, cardiovascular disease, drug allergy, and adverse drug reaction as the "hot" themes in EHR research in Australia. This study reveals a significant uptrend in EHR research in Australia, highlighting the evolving intellectual and collaborative landscape of this interdisciplinary field. The data also provide guidance for policymakers and funding institutions in terms of the most significant contributions and key fields of research while also holding public interest.

Electronic Medical Record Data Missingness and Interruption in Antiretroviral Therapy Among Adults and Children Living With HIV in Haiti: Retrospective Longitudinal Study.

Background: Children (aged 0-14 years) living with HIV often experience lower rates of HIV diagnosis, treatment, and viral load suppression. In Haiti, only 63% of children living with HIV know their HIV status (compared to 85% overall), 63% are on treatment (compared to 85% overall), and 48% are virally suppressed (compared to 73% overall). Electronic medical records (EMRs) can improve HIV care and patient outcomes, but these benefits are largely dependent on providers having access to quality and nonmissing data. Objective: We sought to understand the associations between EMR data missingness and interruption in antiretroviral therapy treatment by age group (pediatric vs adult). Methods: We assessed associations between patient intake record data missingness and interruption in treatment (IIT) status at 6 and 12 months post antiretroviral therapy initiation using patient-level data drawn from iSanté, the most widely used EMR in Haiti. Missingness was assessed for tuberculosis diagnosis, World Health Organization HIV stage, and weight using a composite score indicator (ie, the number of indicators of interest missing). Risk ratios were estimated using marginal parameters from multilevel modified Poisson models with robust error variances and random intercepts for the facility to account for clustering. Results: Data were drawn from 50 facilities and comprised 31,457 patient records from people living with HIV, of which 1306 (4.2%) were pediatric cases. Pediatric patients were more likely than adult patients to experience IIT (n=431, 33% vs n=7477, 23.4% at 6 months; P<.001). Additionally, pediatric patient records had higher data missingness, with 581 (44.5%) pediatric records missing at least 1 indicator of interest, compared to 7812 (25.9%) adult records (P<.001). Among pediatric patients, each additional indicator missing was associated with a 1.34 times greater likelihood of experiencing IIT at 6 months (95% CI 1.08-1.66; P=.008) and 1.24 times greater likelihood of experiencing IIT at 12 months (95% CI 1.05-1.46; P=.01). These relationships were not statistically significant for adult patients. Compared to pediatric patients with 0 missing indicators, pediatric patients with 1, 2, or 3 missing indicators were 1.59 (95% CI 1.26-2.01; P<.001), 1.74 (95% CI 1.02-2.97; P=.04), and 2.25 (95% CI 1.43-3.56; P=.001) times more likely to experience IIT at 6 months, respectively. Among adult patients, compared to patients with 0 indicators missing, having all 3 indicators missing was associated with being 1.32 times more likely to experience IIT at 6 months (95% CI 1.03-1.70; P=.03), while there was no association with IIT status for other levels of missingness. Conclusions: These findings suggest that both EMR data quality and quality of care are lower for children living with HIV in Haiti. This underscores the need for further research into the mechanisms by which EMR data quality impacts the quality of care and patient outcomes among this population. Efforts to improve both EMR data quality and quality of care should consider prioritizing pediatric patients.

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening]. / Développement d'une solution d'intelligence artificielle pour améliorer le screening en recherche clinique.

INTRODUCTION: The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of an artificial intelligence driven tool (text mining, machine learning, classification…) for the screening and detection of patients, potentially eligible for recruitment in one of the clinical trials open at the "Institut de Cancérologie de Lorraine". METHODS: Computerized clinical data during the first medical consultation among patients managed in an anticancer center over the 2019-2023 period were used to study the performances of an artificial intelligence tool (SAS® Viya). Recall, precision and F1-score were used to determine the artificial intelligence algorithm effectiveness. Time saved on screening was determined by the difference between the time taken using the artificial intelligence-assisted method and that taken using the standard method in clinical trial participant screening. RESULTS: Out of 9876 patients included in the study, the artificial intelligence algorithm obtained the following scores: precision of 96 %, recall of 94 % and a 0.95 F1-score to detect patients with breast cancer (n=2039) and potentially eligible for inclusion in a clinical trial. The screening of 258 potentially eligible patient's files took 20s per file vs. 5min and 6s with standard method. DISCUSSION: This study suggests that artificial intelligence could yield sizable improvements over standard practices in several aspects of the patient screening process, as well as in approaches to feasibility, site selection, and trial selection.

Pediatric endoscopy: how can we improve patient outcomes and ensure best practices?

INTRODUCTION: Strategies to promote high-quality endoscopy in children require consensus around pediatric-specific quality standards and indicators. Using a rigorous guideline development process, the international Pediatric Endoscopy Quality Improvement Network (PEnQuIN) was developed to support continuous quality improvement efforts within and across pediatric endoscopy services. AREAS COVERED: This review presents a framework, informed by the PEnQuIN guidelines, for assessing endoscopist competence, granting procedural privileges, audit and feedback, and for skill remediation, when required. As is critical for promoting quality, PEnQuIN indicators can be benchmarked at the individual endoscopist, endoscopy facility, and endoscopy community levels. Furthermore, efforts to incorporate technologies, including electronic medical records and artificial intelligence, into endoscopic quality improvement processes can aid in creation of large-scale networks to facilitate comparison and standardization of quality indicator reporting across sites. EXPERT OPINION: PEnQuIN quality standards and indicators provide a framework for continuous quality improvement in pediatric endoscopy, benefiting individual endoscopists, endoscopy facilities, and the broader endoscopy community. Routine and reliable measurement of data, facilitated by technology, is required to identify and drive improvements in care. Engaging all stakeholders in endoscopy quality improvement processes is crucial to enhancing patient outcomes and establishing best practices for safe, efficient, and effective pediatric endoscopic care.

The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis.

BACKGROUND: The digital transformation of health care is advancing rapidly. A well-accepted framework for health care improvement is the Quadruple Aim: improved clinician experience, improved patient experience, improved population health, and reduced health care costs. Hospitals are attempting to improve care by using digital technologies, but the effectiveness of these technologies is often only measured against cost and quality indicators, and less is known about the clinician and patient experience. OBJECTIVE: This study aims to conduct a systematic review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals. METHODS: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines were followed. The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched from January 2010 to June 2022. Studies that explored multidisciplinary clinician or adult inpatient experiences of digital hospitals (with a full electronic medical record) were included. Study quality was assessed using the Mixed Methods Appraisal Tool. Data synthesis was performed narratively for quantitative studies. Qualitative evidence synthesis was performed via (1) automated machine learning text analytics using Leximancer (Leximancer Pty Ltd) and (2) researcher-led inductive synthesis to generate themes. RESULTS: A total of 61 studies (n=39, 64% quantitative; n=15, 25% qualitative; and n=7, 11% mixed methods) were included. Most studies (55/61, 90%) investigated clinician experiences, whereas few (10/61, 16%) investigated patient experiences. The study populations ranged from 8 to 3610 clinicians, 11 to 34,425 patients, and 5 to 2836 hospitals. Quantitative outcomes indicated that clinicians had a positive overall satisfaction (17/24, 71% of the studies) with digital hospitals, and most studies (11/19, 58%) reported a positive sentiment toward usability. Data accessibility was reported positively, whereas adaptation, clinician-patient interaction, and workload burnout were reported negatively. The effects of digital hospitals on patient safety and clinicians' ability to deliver patient care were mixed. The qualitative evidence synthesis of clinician experience studies (18/61, 30%) generated 7 themes: inefficient digital documentation, inconsistent data quality, disruptions to conventional health care relationships, acceptance, safety versus risk, reliance on hybrid (digital and paper) workflows, and patient data privacy. There was weak evidence of a positive association between digital hospitals and patient satisfaction scores. CONCLUSIONS: Clinicians' experience of digital hospitals appears positive according to high-level indicators (eg, overall satisfaction and data accessibility), but the qualitative evidence synthesis revealed substantive tensions. There is insufficient evidence to draw a definitive conclusion on the patient experience within digital hospitals, but indications appear positive or agnostic. Future research must prioritize equitable investigation and definition of the digital clinician and patient experience to achieve the Quadruple Aim of health care.

Towards an evaluation framework for medical device-integrated electronic medical record.

INTRODUCTION: Medical device (MD)-integrated (I) electronic medical record (EMR) (MDI-EMR) poses cyber threats that undermine patient safety, and thus, they require effective control mechanisms. We reviewed the related literature, including existing EMR and MD risk assessment approaches, to identify MDI-EMR comprehensive evaluation dimensions and measures. AREAS COVERED: We searched multiple databases, including PubMed, Web of Knowledge, Scopus, ACM, Embase, IEEE and Ingenta. We explored various evaluation aspects of MD and EMR to gain a better understanding of their complex integration. We reviewed numerous risk management and assessment frameworks related to MD and EMR security aspects and mitigation controls and then identified their common evaluation aspects. Our review indicated that previous evaluation frameworks assessed MD and EMR independently. To address this gap, we proposed an evaluation framework based on the sociotechnical dimensions of health information systems and risk assessment approaches for MDs to evaluate MDI-EMR integratively. EXPERT OPINION: The emergence of MDI-EMR cyber threats requires appropriate evaluation tools to ensure the safe development and application of MDI-EMR. Consequently, our proposed framework will continue to evolve through subsequent validations and refinements. This process aims to establish its applicability in informing stakeholders of the safety level and assessing its effectiveness in mitigating risks for future improvements.

Determining Adherence to Inhaled Corticosteroids From the Epic Electronic Medical Record.

OBJECTIVE: Often we call the patient's pharmacy to obtain a refill history to assess inhaled corticosteroid (ICS) adherence. The purpose of this project was to determine the accuracy of refill histories for ICS (with or without long-acting beta agonist) listed in Epic's Medication Dispense History. METHODS: We evaluated 61 patients and used data from 38 who met the following criteria: 1) under the care of the UF Pediatric Severe Asthma Clinic; 2) taking the same dose of the same ICS product for 6 months before the patient's last clinic visit; and 3) having data available from the pharmacy where the last ICS prescription was electronically sent. We called the pharmacies to obtain a verbal report of their refill record. Then, we compared the number of refills reported to the number listed in Epic's records using a Wilcoxon matched-pairs signed-ranks test. RESULTS: Of the 293 refill dates listed in Epic, 157 were duplicates, giving a 54% error. After deleting duplicates, the mean (SD) number of refills listed in Epic was 3.6 (2.0) compared with 3.3 (2.0) in pharmacies over a period of 6 months (p < 0.0001). After removing duplicates Epic correctly reported the total number of refills for 30 of the 38 patients (78.9%). Seven of the remaining patients had more refills listed in Epic while 1 patient had more refills dispensed. CONCLUSION: This study indicates that our version of Epic over-reports refills thus limiting assessment of adherence. In contrast, absence of refills in Epic is a clear indication of poor adherence.

Estimation of optimal treatment regimes with electronic medical record data using the residual life value estimator.

Clinicians and patients must make treatment decisions at a series of key decision points throughout disease progression. A dynamic treatment regime is a set of sequential decision rules that return treatment decisions based on accumulating patient information, like that commonly found in electronic medical record (EMR) data. When applied to a patient population, an optimal treatment regime leads to the most favorable outcome on average. Identifying optimal treatment regimes that maximize residual life is especially desirable for patients with life-threatening diseases such as sepsis, a complex medical condition that involves severe infections with organ dysfunction. We introduce the residual life value estimator (ReLiVE), an estimator for the expected value of cumulative restricted residual life under a fixed treatment regime. Building on ReLiVE, we present a method for estimating an optimal treatment regime that maximizes expected cumulative restricted residual life. Our proposed method, ReLiVE-Q, conducts estimation via the backward induction algorithm Q-learning. We illustrate the utility of ReLiVE-Q in simulation studies, and we apply ReLiVE-Q to estimate an optimal treatment regime for septic patients in the intensive care unit using EMR data from the Multiparameter Intelligent Monitoring Intensive Care database. Ultimately, we demonstrate that ReLiVE-Q leverages accumulating patient information to estimate personalized treatment regimes that optimize a clinically meaningful function of residual life.

Measuring Emergency Department Workload Perception Using Electronic Medical Record Measures of Patient Volume and Acuity.

BACKGROUND: Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload. OBJECTIVE: The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR). METHODS: This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression. RESULTS: We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations. CONCLUSIONS: In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.

Making the EHR Work for You-Modifications of an Electronic Health Record System to Improve Tracking and Management of Patients Receiving Outpatient Parenteral Antibiotic Therapy.

Background: Managing the complex needs of outpatient parenteral antibiotic therapy (OPAT) patients is challenging and time-consuming. We describe development of multimodal interventions to facilitate patient management within an Epic® (Epic Systems Corporation)-based electronic health record (EHR) platform. Methods: During 2016-2018, a multidisciplinary team created several modifications in our local EHR to improve gaps in OPAT care, including shared note templates, shared patient lists, automatically triggered notifications, and comprehensive order sets. A SmartForm was created, allowing collection of discrete, self-contained extractable data about each OPAT episode. We reviewed OPAT episodes from January 2019 through December 2022. Results: The multimodal EHR interventions culminated in the creation of a patient report, the "OPAT Monitoring View" collating OPAT-relevant data from multiple sections of the chart onto 1 screen display. This view is accessible both within the patient chart and from multiple list-based, in-basket, and snapshot-anchored preview functions in the EHR. Implementation of the EHR bundle facilitated management of 3402 OPAT episodes from 2019 to 2022 (850 episodes/year), about 50% higher than anticipated based on 540 OPAT courses in 2016. The OPAT EHR bundle allowed efficient (<3 hours) multidisciplinary rounds for management of 130-145 patients each week, streamlining of care transitions, and increasing staff satisfaction. Conclusions: Bundled multimodal modifications to the local EHR increased patient care efficiency and staff satisfaction and facilitated data collection to support a large OPAT program. These modifications apply commonly available EHR functionalities to OPAT care and could be adapted to other settings with different EHR platforms.

[Evaluation of electronic medical records from general practices using the example of the diagnosis of community-acquired pneumonia: A qualitative feasibility study]. / Nutzung von Daten aus dem Praxisverwaltungssystem eines großen hausärztlichen Verbundes medizinischer Versorgungszentren am Beispiel der Diagnosestellung einer ambulant erworbenen Pneumonie ­ eine qualitative Machbarkeitsstudie.

BACKGROUND: Data collected by general practitioners (GPs) may provide potential for health services research. In this study, we investigated if clinical questions can be answered with GPs' electronic medical records (EMRs) by means of diagnosing community-acquired pneumonia (CAP). METHOD: Patients diagnosed with CAP, defined as ICD code J18.9, were identified in the fourth quarter of 2021. The data were derived from the EMR system (Medical Office®) of a central German association of 30 general practices, using three different approaches: 1. The integrated statistic tool was used to record whether patients were referred for radiological diagnostic confirmation. 2. Retrospectively, EMRs were evaluated manually by a doctor familiar with the EMR. 3. The raw data of the EMR system were extracted by automated export. The information obtained through the three types of access was compared. For each patient case, detailed comments on problems and specifics were documented and evaluated by qualitative content analysis (QCA) according to Mayring. RESULTS: In total, 164 patients diagnosed with CAP were identified. The numbers of documented radiological diagnostic confirmations varied between data approaches: While the manual evaluation of the EMRs revealed 60 referred patients, the statistics tool identified 38 of these cases. The export of the raw data identified 58 referrals to radiography after adjustment. According to QCA, there was a high variation in applied diagnostics and time of diagnosis. Referrals for radiography were made both before and after coding of the diagnosis. In case of hospitalization, X-rays were usually performed during the inpatient stay. Laboratory tests were performed as an alternative to radiography. There was also a high variation in the documentation of risk factors and diagnostic certainty. DISCUSSION: The statistics tool integrated into the EMR system is a quick way to perform simple queries but proved to be impracticable for complex questions. The EMRs provide detailed information but need to be evaluated manually. An automated data export from the raw data offers both detailed information and access to large volumes of data but requires complex preparation and appropriate IT expertise. CONCLUSION: Based on the example of diagnosed CAP in a GP setting, the use of data extracted from an EMR system seems to be feasible to answer simple clinical questions. However, it is necessary to adapt the data export, and a comparison with a small number of manually evaluated cases is useful to achieve valid results.

Application of Failure Mode and Effects Analysis to Improve the Quality of the Front Page of Electronic Medical Records in China: Cross-Sectional Data Mapping Analysis.

BACKGROUND: The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences. OBJECTIVE: The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes. METHODS: From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People's Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures. RESULTS: We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased. CONCLUSIONS: In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China.

The Implementation of an Electronic Medical Record in a German Hospital and the Change in Completeness of Documentation: Longitudinal Document Analysis.

BACKGROUND: Electronic medical records (EMR) are considered a key component of the health care system's digital transformation. The implementation of an EMR promises various improvements, for example, in the availability of information, coordination of care, or patient safety, and is required for big data analytics. To ensure those possibilities, the included documentation must be of high quality. In this matter, the most frequently described dimension of data quality is the completeness of documentation. In this regard, little is known about how and why the completeness of documentation might change after the implementation of an EMR. OBJECTIVE: This study aims to compare the completeness of documentation in paper-based medical records and EMRs and to discuss the possible impact of an EMR on the completeness of documentation. METHODS: A retrospective document analysis was conducted, comparing the completeness of paper-based medical records and EMRs. Data were collected before and after the implementation of an EMR on an orthopaedical ward in a German academic teaching hospital. The anonymized records represent all treated patients for a 3-week period each. Unpaired, 2-tailed t tests, chi-square tests, and relative risks were calculated to analyze and compare the mean completeness of the 2 record types in general and of 10 specific items in detail (blood pressure, body temperature, diagnosis, diet, excretions, height, pain, pulse, reanimation status, and weight). For this purpose, each of the 10 items received a dichotomous score of 1 if it was documented on the first day of patient care on the ward; otherwise, it was scored as 0. RESULTS: The analysis consisted of 180 medical records. The average completeness was 6.25 (SD 2.15) out of 10 in the paper-based medical record, significantly rising to an average of 7.13 (SD 2.01) in the EMR (t178=-2.469; P=.01; d=-0.428). When looking at the significant changes of the 10 items in detail, the documentation of diet (P<.001), height (P<.001), and weight (P<.001) was more complete in the EMR, while the documentation of diagnosis (P<.001), excretions (P=.02), and pain (P=.008) was less complete in the EMR. The completeness remained unchanged for the documentation of pulse (P=.28), blood pressure (P=.47), body temperature (P=.497), and reanimation status (P=.73). CONCLUSIONS: Implementing EMRs can influence the completeness of documentation, with a possible change in both increased and decreased completeness. However, the mechanisms that determine those changes are often neglected. There are mechanisms that might facilitate an improved completeness of documentation and could decrease or increase the staff's burden caused by documentation tasks. Research is needed to take advantage of these mechanisms and use them for mutual profit in the interests of all stakeholders. TRIAL REGISTRATION: German Clinical Trials Register DRKS00023343; https://drks.de/search/de/trial/DRKS00023343.

Implementing Tap-to-Witness Technology in the Electronic Medical Record.

The implementation of an organisation-wide EMR system in 2019 included single sign-on technology for nurses and midwives. This first-in-Australia study extended the use of this technology to enable nurses and midwives to tap-to-witness for high-risk medications, blood and blood products, and expressed breast milk. A saving of 7 seconds per interaction was observed with nurses and midwives reporting appreciation for ongoing EMR enhancement to reduce EMR-related documentation burden.

Case-Based Learning in a Simulated Electronic Medical Record: Digital Health Education for Nursing Students.

Nursing graduates require competence in the use of digital health technologies. The Department of Nursing at the University of Melbourne has integrated an Electronic Medical Record (EMR) training platform into the entry-to-practice curriculum to enhance students' digital literacy. The Case Based Learning (CBL) software, developed by CSIRO and the University of Queensland, presents students with custom-built simulated cases in an EMR. Over 300 entry-to-practice students have used the CBL in 2022. Student experience, acceptability and usability of this software is reported. Data was collected via Qualtrics XM© survey. Student feedback suggests the software was easy to use and has the potential to enhance their understanding of digital health. Students suggested adjustments to the software to maximise their opportunities for clinical decision-making and improve fidelity.

Evaluation of Smart Pump Interoperability with an Electronic Medical Record System to Improve Infusion Safety.

Medications administered via intravenous (IV) infusions have high potential for patient harm. Evaluation of the rate of variances between the medication order on the Electronic Medical Record (EMR) and IV infusion details in the smart pump was performed pre and post- implementation of smart pump and EMR interoperability. Introduction of smart pumps with EMR interoperability resulted in a statistically significant reduction in frequency of variances.