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PURPOSE: We not only developed a clinical practice program for the assessment and feedback vis-à-vis medical students' medical records but also evaluated the effectiveness of this program via a self-assessment of medical students' competence in writing medical records pre- and post-program. METHODS: In 2022, 74 third-year medical students were divided into four groups and participated in a 2-week program. The students' medical records were graded on a scale ranging from 1 to 3 daily, and the mean scores for 2 weeks were compared. Pre- and post-program, the students' self-assessment survey was conducted. RESULTS: The mean scores increased from 1.30 in the first week to 2.14 in the second week. The mean score of self-assessment showed significant improvements, increasing from 2.43 to 4.00 for medical record, 2.64 to 4.08 for write present illness, 2.08 to 3.89 for initial orders, 2.35 to 4.34 for signature, and 2.38 to 3.97 for consent (all p<0.001). CONCLUSION: We found that providing students with real-time assessment and feedback on their medical records increased their skills and confidence in medical records writing.

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This nonrandomized clinical trial investigated the electronic health record (EHR) experiences of clinicians before and after implementation of an artificial intelligence (AI)­powered clinical documentation tool.

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BACKGROUND: The Surgical Tool for Auditing Records scoring system [STAR] focuses on surgical record auditing with promising outcomes. It offers a structured approach to evaluating the quality of surgical notes. AIMS AND OBJECTIVES: This study aimed to assess the effectiveness of the STAR in evaluating oral surgical records and identifying areas for improvement in documentation practices. MATERIALS AND METHODS: The data was obtained from the Dental Information Archival Software (DIAS) of our institution. The sample size was determined using G*Power 3.1.9.4 software. Fifty consecutive oral surgery clinical records of oral squamous cell carcinoma patients were evaluated using STAR. Each record was reviewed for adherence to documentation standards including Initial Assessment (10 points), Follow-up Entries (8 points), Consent Documentation (7 points), Anesthesia Report (7 points), Surgical Log (9 points), and Discharge Synopsis (9 points). compiling a total STAR score (50 points). The data was tabulated in Google Sheets. The descriptive statistics with inter-observer agreement and the mean score were recorded. RESULTS: We observed that each of the 50 records received a score of 49/50 points on the STAR. Deductions were necessary in the Operative record section due to the lack of information regarding the sutures used. CONCLUSION: To summarize, this study emphasizes the effectiveness of the STAR scoring system in evaluating the quality of oral surgical records. Identifying deficiencies, particularly in documenting operative details, can improve the completeness and accuracy of patient records. It can ultimately enhance patient care and facilitate better communication among healthcare professionals.

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Objective: To evaluate the impact of electronic nursing documentation on patient safety, quality of nursing care and documentation. METHODS: The systematic review was conducted in December 2022, and comprised a comprehensive search on Scopus, ScienceDirect, ProQuest, PubMed, Cumulative Index to Nursing and Allied Health Literature, Sage Journals and Google Scholar databases for English-language human studies published between 2018 and 2022. The key words used in the search included "Nursing", "care", "documentation", "record", "electronic", "process" and "health services". The risk of bias was assessed using Strengthening the Reporting of Observational Studies in Epidemiology tool. RESULTS: Of the 469 items initially identified, 15(3.2%) were analysed in detail, indicating a positive influence of electronic nursing documentation on patient safety, care quality, and documentation. However, shortcomings were observed in the development of electronic nursing documentation for optimal effectiveness. Conclusion: Electronic nursing documentation significantly enhanced patient safety, care quality and documentation. To facilitate its integration into clinical settings, a standardised and logically structured electronic nursing documentation system is essential.

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Only a few physicians are willing to comprehensively concern themselves with how a legally watertight treatment documentation should be structured, in addition to their practical activities; however, the importance of the documentation cannot be emphasized enough, not only for a potential case of liability but also for the medical (further) treatment. This article therefore illustrates the legal foundations of the mandatory documentation and the most important questions associated with it for the practice, in particular on the content of the documentation, the timing of the documentation, the preservation of treatment documents and on the conduct in cases of an impending incident.

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Electronic health record (EHR) documentation serves multiple functions, including recording patient health status, enabling interprofessional communication, supporting billing, and providing data to support the quality infrastructure of a Learning Healthcare System. There is no definition and standardized method to assess documentation quality in EHRs. Using a human-centered design (HCD) approach, we define and describe a method to measure documentation quality. Documentation quality was defined as timely, accurate, user-centered, and efficient. Measurement of quality used a virtual simulated standardized patient visit via an EHR vendor platform. By observing and recording documentation efforts, nurse practitioners (NPs) (N = 12) documented the delivery of an Age-Friendly Health System (AFHS) 4Ms (what Matters, Medication, Mentation, and Mobility) clinic visit using a standardized case. Results for timely documentation indicated considerable variability in completion times of documenting the 4Ms. Accuracy varied, as there were many types of episodes of erroneous documentation and extra time in seconds in documenting the 4Ms. The type and frequency of erroneous documentation efforts were related to navigation burden when navigating to different documentation tabs. The evaluated system demonstrated poor usability, with most participants scoring between 60 and 70 on the System Usability Scale (SUS). Efficiency, measured as click burden (the number of clicks used to navigate through a software system), revealed significant variability in the number of clicks required, with the NPs averaging approximately 13 clicks above the minimum requirement. The HCD methodology used in this study to assess the documentation quality proved feasible and provided valuable information on the quality of documentation. By assessing the quality of documentation, the gathered data can be leveraged to enhance documentation, optimize user experience, and elevate the quality of data within a Learning Healthcare System.

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Reuse of clinical data within the healthcare process and for secondary purposes is particularly valuable. This study emphasizes the crucial role of Standardized, Structured Reports (SSRs) in supporting continuity of care while also advancing reusability of data, decision support functionalities, and accommodating future developments. Integrating SSRs with existing information systems poses a serious challenge. The integration of SSRs with information standards enhances their utility in diverse applications. The significance of SSRs is further highlighted by their seamless integration into healthcare processes, and development and implementation is supported by various available applications. This research contributes to the evolution of medical informatics by emphasizing the importance of collaborative efforts in standardized, structured reporting, all aimed at enhancing patient care.

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Rare neuromuscular diseases (NMDs) encompass various disorders of the nervous system and skeletal muscles, and present intricate challenges in diagnosis, treatment, and research due to their low prevalence and often diverse multisystemic manifestations. Leveraging collected patient data for secondary use and analysis holds promise for advancing medical understanding in this field. However, a certain level of data quality is a prerequisite for the methods that can be used to analyze data. The heterogeneous nature of NMDs poses a significant obstacle to the creation of standardized documentation, as there are still many challenges to accurate diagnosis and many discrepancies in the diagnostic process between different countries. This paper proposes the development of an information model tailored to NMDs, aiming to augment visibility, address deficiencies in documentation, and facilitate comprehensive analysis and research endeavors. By providing a structured framework, this model seeks to propel advancements in understanding and managing NMD, ultimately benefiting patients and healthcare providers worldwide.

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Over the last decades, magnetic resonance imaging (MRI) has emerged as a valuable adjunct to prenatal ultrasound for evaluating fetal malformations. Several radiological societies advocate for standardised and structured reporting practices to enhance the uniformity of imaging language. Compared to narrative formats, standardised and structured reports offer enhanced content quality, minimise reader variability, have the potential to save reporting time, and streamline the communication between specialists by employing a shared lexicon. Structured reporting holds promise for mitigating medico-legal liability, while also facilitating rigorous scientific data analyses and the development of standardised databases. While structured reporting templates for fetal MRI are already in use in some centres, specific recommendations and/or guidelines from international societies are scarce in the literature. The purpose of this paper is to propose a standardised and structured reporting template for fetal MRI to assist radiologists, particularly those with less experience, in delivering systematic reports. Additionally, the paper aims to offer an overview of the anatomical structures that necessitate reporting and the prevalent normative values for fetal biometrics found in current literature.

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INTRODUCTION: In German and international research networks different approaches concerning patient consent are applied. So far it is time-consuming to find out to what extent data from these networks can be used for a specific research project. To make the contents of the consents queryable, we aimed for a permission-based approach (Opt-In) that can map both the permission and the withdrawal of consent contents as well as make it queryable beyond project boundaries. MATERIALS AND METHODS: The current state of research was analysed in terms of approach and reusability. Selected process models for defining consent policies were abstracted in a next step. On this basis, a standardised semantic terminology for the description of consent policies was developed and initially agreed with experts. In a final step, the resulting code was evaluated with regards to different aspects of applicability. RESULTS: A first and extendable version for a Semantic Consent Code (SCC) based on 3-axis (CLASS, ACTION, PURPOSE) was developed, consolidated und published. The added value achieved by the SCC was illustrated using the example of real consents from large national research associations (Medical Informatics Initiative and NUM NAPKON/NUKLEUS). The applicability of the SCC was successfully evaluated in terms of the manual semantic mapping of consents by briefly trained personnel and the automated interpretability of consent policies according to the SCC (and vice versa). In addition, a concept for the use of the SCC to simplify consent queries in heterogeneous research scenarios was presented. CONCLUSIONS: The Semantic Consent Code has already successfully undergone initial evaluations. As the published 3-axis code SCC is an essential preliminary work to standardising initially diverse consent texts and contents and can iteratively be extended in multiple ways in terms of content and technical additions. It should be extended in cooperation with the potential user community.

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OBJECTIVE: To describe the associations between patient-to-nurse staffing ratios and rates of mortality, process of care events and vital sign documentation. DESIGN: Secondary analysis of data from the evaluating processes of care and outcomes of children in hospital (EPOCH) cluster-randomised trial. SETTING: 22 hospitals caring for children in Canada, Europe and New Zealand. PARTICIPANTS: Eligible hospitalised patients were aged>37 weeks and <18 years. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was all-cause hospital mortality. Secondary outcomes included five events reflecting the process of care, collected for all EPOCH patients; the frequency of documentation for each of eight vital signs on a random sample of patients; four measures describing nursing perceptions of care. RESULTS: A total of 217 714 patient admissions accounting for 849 798 patient days over the course of the study were analysed. The overall mortality rate was 1.65/1000 patient discharges. The median (IQR) number of patients cared for by an individual nurse was 3.0 (2.8-3.6). Univariate Bayesian models estimating the rate ratio (RR) for the patient-to-nurse ratio and the probability that the RR was less than one found that a higher patient-to-nurse ratio was associated with fewer clinical deterioration events (RR=0.88, 95% credible interval (CrI) 0.77-1.03; P (RR<1)=95%) and late intensive care unit admissions (RR=0.76, 95% CrI 0.53-1.06; P (RR<1)=95%). In adjusted models, a higher patient-to-nurse ratio was associated with lower hospital mortality (OR=0.77, 95% CrI=0.57-1.00; P (OR<1)=98%). Nurses from hospitals with a higher patient-to-nurse ratio had lower ratings for their ability to influence care and reduced documentation of most individual vital signs and of the complete set of vital signs. CONCLUSIONS: The data from this study challenge the assumption that lower patient-to-nurse ratios will improve the safety of paediatric care in contexts where ratios are low. The mechanism of these effects warrants further evaluation including factors, such as nursing skill mix, experience, education, work environment and physician staffing ratios. TRIAL REGISTRATION NUMBER: EPOCH clinical trial registered on clinical trial.gov NCT01260831; post-results.

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The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and comprehensive documentation. However, there are a number of significant issues with traditional documentation procedures, including as slowness, human error, and difficulties with regulatory standards. This review research looks at innovative ways to employ machine learning (ML) and artificial intelligence (AI) to enhance Six Sigma documentation processes in the pharmaceutical sector. AI and ML provide cutting-edge technologies that have the potential to drastically alter documentation processes by automating data entry, collection, and analysis. Natural language processing (NLP) and computer vision technologies have the potential to significantly reduce human error rates and increase the efficacy of documentation processes. By applying machine learning algorithms to support real-time data analysis, predictive analytics, and proactive quality management, pharmaceutical organizations may be able to identify potential quality issues early on and take proactive efforts to address them. Combining AI and ML improves documentation accuracy and reliability while also strengthening compliance with stringent regulatory criteria. The primary barriers and limitations to the current state of Six Sigma documentation in the pharmaceutical industry are identified in this study. It examines the fundamentals of AI and ML with an emphasis on their specific applications in quality assurance and potential benefits for Six Sigma processes. The report includes extensive case studies that highlight notable developments and explain how AI/ML enhanced documentation is used in the real world.

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In response to findings indicating poor standardisation and quality in nursing documentation, NHS Wales embarked on a transformative journey with the National Electronic Nursing Documentation Programme in 2014. Evolving into the Welsh Nursing Care Record (WNCR) by 2019, this initiative sought to streamline practices and enhance accuracy, compliance, and efficiency through a standardised digital platform. The case study explores the comprehensive project design, emphasising evidence-based practices, governance processes and the introduction of National Nursing Informatics roles. Accomplished from April 2021 to September 2023, the WNCR implementation achieved a 79% roll out across eligible wards, marked by strategic investments, robust training, and phased deployment. Evaluations to date show positive impacts on key performance indicators, exemplified by a 9-minute time saving per patient. Lessons learned noted the significance of user engagement, cultural transformation, and ongoing staff development, paving the way for future strategies including nationwide implementation, benefits realisation, and data visualisation initiatives.

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BACKGROUND: Normothermic regional perfusion (NRP) has emerged as a vital technique in organ procurement, particularly in donation after circulatory death (DCD) cases, offering the potential to optimize organ utilization and improve posttransplant outcomes. Recognizing its significance, the American Society of Transplant Surgeons (ASTS) convened a work group to develop standardized recommendations for abdominal NRP in the United States. METHODS: The workgroup, comprising experts in NRP, DCD, and transplantation, formulated recommendations through a collaborative process involving revisions and approvals by relevant committees and the ASTS council. Four key areas were identified for standardization: Preprocedure communication, NRP procedure, Terminology and documentation, and Mentorship/credentialing. RESULTS: The recommendations encompass a range of considerations, including preprocedure communication protocols to facilitate informed decision-making by transplant centers and organ procurement organizations, procedural guidelines for NRP teams, uniform terminology to clarify the NRP process, and standards for mentorship and credentialing of NRP practitioners. Specific recommendations address logistical concerns, procedural nuances, documentation requirements, and the importance of ongoing quality assurance. CONCLUSIONS: The standardized recommendations for abdominal NRP presented in this article aim to ensure consistency, safety, and efficacy in the organ procurement process. By establishing clear protocols and guidelines, the ASTS seeks to enhance organ utilization, honor donor wishes, and uphold public trust in the donation process. Implementation of these recommendations can contribute to the advancement of NRP practices and improve outcomes for transplant recipients.

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BACKGROUND: Electronic health records (EHRs) can accelerate documentation and may enhance details of notes, or complicate documentation and introduce errors. Comprehensive assessment of documentation quality requires comparing documentation to what transpires during the clinical encounter itself. We assessed outpatient primary care notes and corresponding recorded encounters to determine accuracy, thoroughness, and several additional key measures of documentation quality. METHODS: Patients and primary care clinicians across five midwestern primary care clinics of the US Department of Veterans Affairs were recruited into a prospective observational study. Clinical encounters were video-recorded and transcribed verbatim. Using the Physician Documentation Quality Instrument (PDQI-9) added to other measures, reviewers scored quality of the documentation by comparing transcripts to corresponding encounter notes. PDQI-9 items were scored from 1 to 5, with higher scores indicating higher quality. RESULTS: Encounters (N = 49) among 11 clinicians were analyzed. Most issues that patients initiated in discussion were omitted from notes, and nearly half of notes referred to information or observations that could not be verified. Four notes lacked concluding assessments and plans; nine lacked information about when patients should return. Except for thoroughness, PDQI-9 items that were assessed achieved quality scores exceeding 4 of 5 points. CONCLUSIONS: Among outpatient primary care electronic records examined, most issues that patients initiated in discussion were absent from notes, and nearly half of notes referred to information or observations absent from transcripts. EHRs may contribute to certain kinds of errors. Approaches to improving documentation should consider the roles of the EHR, patient, and clinician together.

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Nursing documentation is essential to communicate patient care delivery. This review explores available evidence on the contribution of nursing documentation toward quality care delivery during the COVID-19 pandemic. Nine articles were evaluated for at least one of the 6 factors of quality (eg, safe, timely, equitable, patient-centered, effective, and efficient). Analysis suggests that right-sizing documentation for optimal care quality requires continued efforts to reinforce the value and need of nursing documentation as a primary data source. Continued practice and research efforts are needed to reframe nursing documentation's essential role in benefiting a patient's current and future health care needs.

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BACKGROUND: Intraoperative neurophysiological monitoring (IOM) plays a pivotal role in enhancing patient safety during neurosurgical procedures. This vital technique involves the continuous measurement of evoked potentials to provide early warnings and ensure the preservation of critical neural structures. One of the primary challenges has been the effective documentation of IOM events with semantically enriched characterizations. This study aimed to address this challenge by developing an ontology-based tool. METHODS: We structured the development of the IOM Documentation Ontology (IOMDO) and the associated tool into three distinct phases. The initial phase focused on the ontology's creation, drawing from the OBO (Open Biological and Biomedical Ontology) principles. The subsequent phase involved agile software development, a flexible approach to encapsulate the diverse requirements and swiftly produce a prototype. The last phase entailed practical evaluation within real-world documentation settings. This crucial stage enabled us to gather firsthand insights, assessing the tool's functionality and efficacy. The observations made during this phase formed the basis for essential adjustments to ensure the tool's productive utilization. RESULTS: The core entities of the ontology revolve around central aspects of IOM, including measurements characterized by timestamp, type, values, and location. Concepts and terms of several ontologies were integrated into IOMDO, e.g., the Foundation Model of Anatomy (FMA), the Human Phenotype Ontology (HPO) and the ontology for surgical process models (OntoSPM) related to general surgical terms. The software tool developed for extending the ontology and the associated knowledge base was built with JavaFX for the user-friendly frontend and Apache Jena for the robust backend. The tool's evaluation involved test users who unanimously found the interface accessible and usable, even for those without extensive technical expertise. CONCLUSIONS: Through the establishment of a structured and standardized framework for characterizing IOM events, our ontology-based tool holds the potential to enhance the quality of documentation, benefiting patient care by improving the foundation for informed decision-making. Furthermore, researchers can leverage the semantically enriched data to identify trends, patterns, and areas for surgical practice enhancement. To optimize documentation through ontology-based approaches, it's crucial to address potential modeling issues that are associated with the Ontology of Adverse Events.

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