Two-Dimensional Gel Electrophoresis for Protein Separation of Plant Samples.

This chapter provides a description of the procedure for two-dimensional electrophoresis that can be performed for any given gel size and isoelectric focusing range. This will enable the operator to recognize critical steps and gain sufficient information to generate 2D images suitable for computer-assisted analysis of 2D-gel, as well as mass spectrometry analysis for protein identification and characterization.

One-Dimensional Acrylamide Gel Electrophoresis for Analysis of Plant Samples.

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique for separating proteins from complex plant samples. Prior to the analysis, proteins must be extracted from plant tissues, which are rather complex than other types of biological material. Different protocols have been applied depending on the protein source, such as seeds, pollen, leaves, roots, and flowers. Total protein amounts must also be determined before conducting gel electrophoresis. The most common methodologies include PAGE under native or denaturing conditions. Both procedures are used consequently for protein identification and characterization via mass spectrometry. Additionally, various staining procedures are available to visualize protein bands in the gel, facilitating the software-based digital evaluation of the gel through image acquisition.

Promoting diversity, equity and inclusion awareness in clinical documentation through postgraduate year one training.

BACKGROUND AND PURPOSE: As healthcare providers increasingly focus on emerging issues of diversity, equity and inclusion (DEI) in patient care, less is known about the training in postgraduate year one (PGY1) pharmacy residency on DEI clinical documentation considerations. This pilot project explored whether training, discussion and self-reflection within a peer review activity promoted DEI self-awareness in clinical documentation through a centralized curriculum of a multisite PGY1. EDUCATIONAL ACTIVITY AND SETTING: Building upon an established peer review of clinical documentation activity, PGY1 pharmacy residents practicing in ambulatory care settings received training on DEI considerations and completed small and large group discussions, a post-activity mixed methods survey with self-reflection prompts, and a three-month follow-up survey. FINDINGS: Twenty-two residents participated in the peer review of clinical documentation activity, DEI training and discussions. Twelve residents completed the post-activity survey with reflection prompts; 6 (50%) reported similar previous DEI training prior to residency. After the DEI training and discussions, 12 (100%) agreed or strongly agreed that their awareness of DEI documentation considerations increased; 10 (83%) would document their submitted notes differently, while one resident was unsure and one would not make changes. Twelve residents completed the follow-up survey three months following the activity. Themes from the free-text responses on key learnings collected post-activity and three-month post (respectively) included: 1) new knowledge, increased self-awareness, and intended action and 2) increased self-awareness and changes in note-making convention. SUMMARY: Integrating DEI training, discussion, and self-reflection prompts into a peer review clinical documentation activity increased self-awareness and knowledge of DEI considerations and promoted intended changes in patient care documentation for pharmacy residents. Regardless of previous training, residents reported continued self-awareness and changes in documentation conventions continued three months later.

Exploring the Use and Implications of AI in Sexual and Reproductive Health and Rights: Protocol for a Scoping Review.

BACKGROUND: Artificial intelligence (AI) has emerged as a transformative force across the health sector and has garnered significant attention within sexual and reproductive health and rights (SRHR) due to polarizing views on its opportunities to advance care and the heightened risks and implications it brings to people's well-being and bodily autonomy. As the fields of AI and SRHR evolve, clarity is needed to bridge our understanding of how AI is being used within this historically politicized health area and raise visibility on the critical issues that can facilitate its responsible and meaningful use. OBJECTIVE: This paper presents the protocol for a scoping review to synthesize empirical studies that focus on the intersection of AI and SRHR. The review aims to identify the characteristics of AI systems and tools applied within SRHR, regarding health domains, intended purpose, target users, AI data life cycle, and evidence on benefits and harms. METHODS: The scoping review follows the standard methodology developed by Arksey and O'Malley. We will search the following electronic databases: MEDLINE (PubMed), Scopus, Web of Science, and CINAHL. Inclusion criteria comprise the use of AI systems and tools in sexual and reproductive health and clear methodology describing either quantitative or qualitative approaches, including program descriptions. Studies will be excluded if they focus entirely on digital interventions that do not explicitly use AI systems and tools, are about robotics or nonhuman subjects, or are commentaries. We will not exclude articles based on geographic location, language, or publication date. The study will present the uses of AI across sexual and reproductive health domains, the intended purpose of the AI system and tools, and maturity within the AI life cycle. Outcome measures will be reported on the effect, accuracy, acceptability, resource use, and feasibility of studies that have deployed and evaluated AI systems and tools. Ethical and legal considerations, as well as findings from qualitative studies, will be synthesized through a narrative thematic analysis. We will use the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) format for the publication of the findings. RESULTS: The database searches resulted in 12,793 records when the searches were conducted in October 2023. Screening is underway, and the analysis is expected to be completed by July 2024. CONCLUSIONS: The findings will provide key insights on usage patterns and evidence on the use of AI in SRHR, as well as convey key ethical, safety, and legal considerations. The outcomes of this scoping review are contributing to a technical brief developed by the World Health Organization and will guide future research and practice in this highly charged area of work. TRIAL REGISTRATION: OSF Registries osf.io/ma4d9; https://osf.io/ma4d9. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53888.

Assessing the Usability and Feasibility of Digital Assistant Tools for Direct Support Professionals: Participatory Design and Pilot-Testing.

BACKGROUND: The United States is experiencing a direct support professional (DSP) crisis, with demand far exceeding supply. Although generating documentation is a critical responsibility, it is one of the most wearisome aspects of DSPs' jobs. Technology that enables DSPs to log informal time-stamped notes throughout their shift could help reduce the burden of end-of-shift documentation and increase job satisfaction, which in turn could improve the quality of life of the individuals with intellectual and developmental disabilities (IDDs) whom DSPs support. However, DSPs, with varied ages, levels of education, and comfort using technology, are not likely to adopt tools that detract from caregiving responsibilities or increase workload; therefore, technological tools for them must be relatively simple, extremely intuitive, and provide highly valued capabilities. OBJECTIVE: This paper describes the development and pilot-testing of a digital assistant tool (DAT) that enables DSPs to create informal notes throughout their shifts and use these notes to facilitate end-of-shift documentation. The purpose of the pilot study was to assess the usability and feasibility of the DAT. METHODS: The research team applied an established user-centered participatory design process to design, develop, and test the DAT prototypes between May 2020 and April 2023. Pilot-testing entailed having 14 DSPs who support adults with IDDs use the first full implementation of the DAT prototypes during 2 or 3 successive work shifts and fill out demographic and usability questionnaires. RESULTS: Participants used the DAT prototypes to create notes and help generate end-of-shift reports. The System Usability Scale score of 81.79 indicates that they found the prototypes easy to use. Survey responses imply that using the DAT made it easier for participants to produce required documentation and suggest that they would adopt the DAT if this tool were available for daily use. CONCLUSIONS: Simple technologies such as the DAT prototypes, which enable DSPs to use mobile devices to log time-stamped notes throughout their shift with minimal effort and use the notes to help write reports, have the potential to both reduce the burden associated with producing documentation and enhance the quality (level of detail and accuracy) of this documentation. This could help to increase job satisfaction and reduce turnover in DSPs, both of which would help improve the quality of life of the individuals with IDDs whom they support. The pilot test results indicate that DSPs found the DAT easy to use. Next steps include (1) producing more robust versions of the DAT with additional capabilities, such as storing data locally on mobile devices when Wi-Fi is not available; and (2) eliciting input from agency directors, families, and others who use data about adults with IDDs to help care for them to ensure that data produced by DSPs are relevant and useful.

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study.

BACKGROUND: Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records. OBJECTIVE: This study sought to validate and test an artificial intelligence (AI)-based natural language processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes in pediatric patients. We specifically study patients presenting to the emergency department (ED) who can be sentinel cases in an outbreak. METHODS: Subjects in this retrospective cohort study are patients who are 21 years of age and younger, who presented to a pediatric ED at a large academic children's hospital between March 1, 2020, and May 31, 2022. The ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on Centers for Disease Control and Prevention (CDC) criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F1-score=0.986; positive predictive value [PPV]=0.972; and sensitivity=1.0). F1-score, PPV, and sensitivity were used to compare the performance of both NLP and the International Classification of Diseases, 10th Revision (ICD-10) coding to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-CoV-2 variant eras. RESULTS: There were 85,678 ED encounters during the study period, including 4% (n=3420) with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F1-score=0.796) than ICD-10 codes (F1-score =0.451). NLP accuracy was higher for positive symptoms (sensitivity=0.930) than ICD-10 (sensitivity=0.300). However, ICD-10 accuracy was higher for negative symptoms (specificity=0.994) than NLP (specificity=0.917). Congestion or runny nose showed the highest accuracy difference (NLP: F1-score=0.828 and ICD-10: F1-score=0.042). For encounters with patients with COVID-19, prevalence estimates of each NLP symptom differed across variant eras. Patients with COVID-19 were more likely to have each NLP symptom detected than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras. CONCLUSIONS: This study establishes the value of AI-based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance.

Table 0; documenting the steps to go from clinical database to research dataset.

OBJECTIVES: Data-driven decision support tools have been increasingly recognized to transform health care. However, such tools are often developed on predefined research datasets without adequate knowledge of the origin of this data and how it was selected. How a dataset is extracted from a clinical database can profoundly impact the validity, interpretability and interoperability of the dataset, and downstream analyses, yet is rarely reported. Therefore, we present a case study illustrating how a definitive patient list was extracted from a clinical source database and how this can be reported. STUDY DESIGN AND SETTING: A single-center observational study was performed at an academic hospital in the Netherlands to illustrate the impact of selecting a definitive patient list for research from a clinical source database, and the importance of documenting this process. All admissions from the critical care database admitted between January 1, 2013, and January 1, 2023, were used. RESULTS: An interdisciplinary team collaborated to identify and address potential sources of data insufficiency and uncertainty. We demonstrate a stepwise data preparation process, reducing the clinical source database of 54,218 admissions to a definitive patient list of 21,553 admissions. Transparent documentation of the data preparation process improves the quality of the definitive patient list before analysis of the corresponding patient data. This study generated seven important recommendations for preparing observational health-care data for research purposes. CONCLUSION: Documenting data preparation is essential for understanding a research dataset originating from a clinical source database before analyzing health-care data. The findings contribute to establishing data standards and offer insights into the complexities of preparing health-care data for scientific investigation. Meticulous data preparation and documentation thereof will improve research validity and advance critical care.

[Ophthalmic agents during pregnancy]. / Ophthalmika in der Schwangerschaft.

The use of ophthalmic agents during pregnancy and breastfeeding always represents an off-label use. Therefore, the use of drugs must be particularly carefully assessed with respect to the risk-benefit assessment. In this overview the literature databank of the PubMed library, pharmaceutical lists (Red List, Swiss pharmaceutical compendium), guidelines of the specialist societies the German Society of Ophthalmology (DOG), the Swiss Society of Ophthalmology (SOG), the European Glaucoma Society (EGS), the American Academy of Ophthalmology (AAO) and internet portals (embryotox, reprotox) were inspected and recommendations for the use of ophthalmic agents during pregnancy and breastfeeding were derived. More attention should be dedicated to this topic in the specialist societies.

Validity of inpatient electronic health record-based measures of oxygen-related therapy in the United States: Lessons applicable for studying COVID-19 endpoints.

INTRODUCTION: During the COVID-19 pandemic, inpatient electronic health records (EHRs) have been used to conduct public health surveillance and assess treatments and outcomes. Invasive mechanical ventilation (MV) and supplemental oxygen (O2) use are markers of severe illness in hospitalized COVID-19 patients. In a large US system (n = 142 hospitals), we assessed documentation of MV and O2 use during COVID-19 hospitalization in administrative data versus nursing documentation. METHODS: We identified 319 553 adult hospitalizations with a COVID-19 diagnosis, February 2020-October 2022, and extracted coded, administrative data for MV or O2. Separately, we developed classification rules for MV or O2 supplementation from semi-structured nursing documentation. We assessed MV and O2 supplementation in administrative data versus nursing documentation and calculated ordinal endpoints of decreasing COVID-19 disease severity. Nursing documentation was considered the gold standard in sensitivity and positive predictive value (PPV) analyses. RESULTS: In nursing documentation, the prevalence of MV and O2 supplementation among COVID-19 hospitalizations was 14% and 75%, respectively. The sensitivity of administrative data was 83% for MV and 41% for O2, with both PPVs above 91%. Concordance between sources was 97% for MV (κ = 0.85), and 54% for O2 (κ = 0.21). For ordinal endpoints, administrative data accurately identified intensive care and MV but underestimated hospitalizations with O2 requirements (42% vs. 18%). CONCLUSIONS: In comparison to nursing documentation, administrative data under-ascertained O2 supplementation but accurately estimated severe endpoints such as MV. Nursing documentation improved ascertainment of O2 among COVID-19 hospitalizations and can capture oxygen requirements in adults hospitalized with COVID-19 or other respiratory illnesses.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study.

BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics. The integration of ambient artificial intelligence (AI)-powered solutions offers a promising way to improve documentation while fitting seamlessly into existing workflows. OBJECTIVE: This study aims to assess the accuracy and quality of Subjective, Objective, Assessment, and Plan (SOAP) notes generated by ChatGPT-4, an AI model, using established transcripts of History and Physical Examination as the gold standard. We seek to identify potential errors and evaluate the model's performance across different categories. METHODS: We conducted simulated patient-provider encounters representing various ambulatory specialties and transcribed the audio files. Key reportable elements were identified, and ChatGPT-4 was used to generate SOAP notes based on these transcripts. Three versions of each note were created and compared to the gold standard via chart review; errors generated from the comparison were categorized as omissions, incorrect information, or additions. We compared the accuracy of data elements across versions, transcript length, and data categories. Additionally, we assessed note quality using the Physician Documentation Quality Instrument (PDQI) scoring system. RESULTS: Although ChatGPT-4 consistently generated SOAP-style notes, there were, on average, 23.6 errors per clinical case, with errors of omission (86%) being the most common, followed by addition errors (10.5%) and inclusion of incorrect facts (3.2%). There was significant variance between replicates of the same case, with only 52.9% of data elements reported correctly across all 3 replicates. The accuracy of data elements varied across cases, with the highest accuracy observed in the "Objective" section. Consequently, the measure of note quality, assessed by PDQI, demonstrated intra- and intercase variance. Finally, the accuracy of ChatGPT-4 was inversely correlated to both the transcript length (P=.05) and the number of scorable data elements (P=.05). CONCLUSIONS: Our study reveals substantial variability in errors, accuracy, and note quality generated by ChatGPT-4. Errors were not limited to specific sections, and the inconsistency in error types across replicates complicated predictability. Transcript length and data complexity were inversely correlated with note accuracy, raising concerns about the model's effectiveness in handling complex medical cases. The quality and reliability of clinical notes produced by ChatGPT-4 do not meet the standards required for clinical use. Although AI holds promise in health care, caution should be exercised before widespread adoption. Further research is needed to address accuracy, variability, and potential errors. ChatGPT-4, while valuable in various applications, should not be considered a safe alternative to human-generated clinical documentation at this time.

Medical photography and the reconstructive urologist: A 6-month prospective study.

Medical photography has multiple, important roles. The education of medical practitioners, documentation of disease, response to treatment, research, publication, intraoperative recording and trauma documentation all rely on medical photography. Additionally, there are important medicolegal implications pertaining to medical photography across many medical disciplines. Other than specific image use to document cases, there remains a paucity of urological literature regarding the use of medical photography in Urology. The aims of this 6-month study were to document the use of medical photography by a Reconstructive Urological Service in a tertiary referral centre and to assess the range of urological conditions photographed. A secondary aim was to specifically document intraoperative use of the medical photography.

Utilizing the integrated dual recording system to enhance documentation and analysis of airway management in children with difficult airway: A case report.

This case report highlights the use of an integrated Dual Recording System (iDRS) to document and analyze airway management. The iDRS combines video laryngoscopy and a wide-angle camera to capture dual-view recordings of the larynx and operating room during airway procedures. We utilized this system in a 5-month-old boy with a difficult airway who underwent pulmonary artery banding under general anesthesia. Retrospective video analysis showed discrepancies between written information and iDRS video findings, including differences in the desaturation cause, description of airway procedures, and effectiveness of interventions. Video analysis facilitated a revised airway management strategy for subsequent anesthesia for cardiac catheterization. This emphasizes the value of the comprehensive information provided by iDRS recordings that facilitate effective post-procedure analysis and better planning of airway management strategies for subsequent care, which ultimately improves clinical decision-making and patient care.

'Moko' drums and gongs, ritual musical instruments and local currency from Alor Island, Southeast Indonesia: A comprehensive and verified lexical data set.

This paper provides comprehensive and systematized lists of names of 'moko' drums from Alor Island, in Southeast Indonesia. 'Moko' drums are unique cultural objects from the Alor-Pantar Archipelago and, besides their ancient function of ritual instruments used mainly for religious purposes and in public events by the indigenous peoples of the islands, they represented and still are considered a very valuable local 'currency' for trade and for specific social interactions rooted in aboriginal culture, like bride price negotiations. Despite the fact that they are extremely popular and widespread among Papuan peoples in Alor and Pantar, the origins of these drums are still relatively obscure. The native speakers, indeed, cannot explain the name 'moko' in itself, at the etymological and semantic level, and, despite the fact that they agree upon non-local origins of the instruments, they do not know where the instruments themselves were produced and from where they came to the islands. Our paper provides the readers with comprehensive lists that systematically collect the names of the drums, with the related glosses and basic additional information, from three representative Papuan languages of Alor Island, namely Abui, Sawila, and Kula. Configured as potentially indispensable tools to develop further research, these lists enhance our knowledge and understanding of the culture of the 'moko' drums in the Alor-Pantar Archipelago, at the linguistic (etymology of the names), anthropological (social value of the drums), and archeological (typology and provenance of the instruments) levels. This cataloguing operation is also part of the effort of documentation of the languages and cultures, still scarcely documented and definitely endangered, of the native peoples of the Alor-Pantar Archipelago.

Do goals of care documentation reflect the conversation?: Evaluating conversation-documentation accuracy.

BACKGROUND: Documenting goals of care in the electronic health record is meant to relay patient preferences to other clinicians. Evaluating the content and documentation of nurse and social worker led goals of care conversations can inform future goals of care initiative efforts. METHODS: As part of the ADvancing symptom Alleviation with Palliative Treatment trial, this study analyzed goals of care conversations led by nurses and social workers and documented in the electronic health record. Informed by a goals of care communication guide, we identified five goals of care components: illness understanding, goals and values, end of life planning, surrogate, and advance directives. Forty conversation transcripts underwent content analysis. Through an iterative team process, we defined documentation accuracy as four categories: (1) Complete-comprehensive accurate documentation of the conversation, (2) Incomplete-partial documentation of the conversation, (3) Missing-discussed and not documented, and (4) Incorrect-misrepresented in documentation. We also defined-Not Discussed-for communication guide questions that were not discussed nor documented. A constant comparative approach was used to determine the presence or absence of conversation content in the documentation. RESULTS: All five goals of care components were discussed in 67% (27/40) of conversation transcripts. Compared to the transcripts, surrogate (37/40, 93%) and advance directives (36/40, 90%) were often documented completely. Almost 40% of goals and values (15/40, 38%) and half of end of life planning (19/40, 48%) were incomplete. Illness understanding was missing (13/40, 33%), not discussed (13/40, 33%), or incorrect (2/40, 5%). CONCLUSION: Nurse and social worker led goals of care conversations discussed and documented most components of the goals of care communication guide. Further research may guide how best to determine the relative importance of accuracy, especially in the broad setting of incomplete, missing, and incorrect EHR documentation.

The Need for Standardized Nomenclature in Electronic Documentation of Female Genital Cutting in Health Records.

To evaluate the quality of Electronic Health Record (EHR) documentation practices of Female Genital Cutting (FGC) by medical providers. A retrospective chart review study of 99 patient encounter notes within the University of Minnesota health system (inclusive of 40 hospitals and clinics) was conducted. Extracted data included but was not limited to patient demographics, reason for patient visit, ICD code used in note, and provider description of FGC anatomy. Data was entered into REDCAP and categorized according to descriptive statistics. Out of 99 encounters, 45% used the unspecified code for FGC. The most common reason for patient visits was sexual pain, though many notes contained several reasons for the visit regarding reproductive, urological, or sexual concerns. 56% of visits discussed deinfibulation. 11 different terms for FGC were used, with "female circumcision" being the most common. 14 different terms for deinfibulation were found within 64 notes. 42% of encounters included a description of introitus size in the anatomical description, and only 38% of these provided a metric measurement. This study found significant variation in the quality of FGC documentation practices. Medical providers often used the unspecified FGC code, subjective and/or seemingly inaccurate descriptions of FGC/anatomy, and several different terms for both FGC and deinfibulation. Clearly, more education is needed in clinical training programs to (1) identify FGC type, (2) use the corresponding ICD code, and (3) use specific, objective descriptions (including presence/absence of structures and infibulation status).

A Comparison of Veterans with Problematic Opioid Use Identified through Natural Language Processing of Clinical Notes versus Using Diagnostic Codes.

Opioid use disorder is known to be under-coded as a diagnosis, yet problematic opioid use can be documented in clinical notes, which are included in electronic health records. We sought to identify problematic opioid use from a full range of clinical notes and compare the demographic and clinical characteristics of patients identified as having problematic opioid use exclusively in clinical notes to patients documented through ICD opioid use disorder diagnostic codes. We developed and applied a natural language processing (NLP) tool that combines rule-based pattern analysis and a trained support vector machine to the clinical notes of a patient cohort (n = 222,371) from two Veteran Affairs service regions to identify patients with problematic opioid use. We also used a set of ICD diagnostic codes to identify patients with opioid use disorder from the same cohort. The NLP tool achieved 96.6% specificity, 90.4% precision/PPV, 88.4% sensitivity/recall, and 94.4% accuracy on unseen test data. NLP exclusively identified 57,331 patients; 6997 patients had positive ICD code identifications. Patients exclusively identified through NLP were more likely to be women. Those identified through ICD codes were more likely to be male, younger, have concurrent benzodiazepine prescriptions, more comorbidities, and more care encounters, and were less likely to be married. Patients in both these groups had substantially elevated comorbidity levels compared with patients not documented through either method as experiencing problematic opioid use. Clinicians may be reluctant to code for opioid use disorder. It is therefore incumbent on the healthcare team to search for documentation of opioid concerns within clinical notes.

Medicolegal aspects of documentation and the electronic health record / Aspectos medicolegales de la documentación y la historia clínica electrónica

Introduction: The busiest times in the hospital are often met by the greatest challenges in complete and comprehensive documentation of the patient care event. The near complete transition to the Electronic Health Record (EHR) was to be the solution to a host of provider documentation concerns. It is clear the EHR provides reliability, reproducibility, integration, evidence based decision-making, multidisciplinary contribution across the entire healthcare spectrum.Methods: The use of a consensus of expert opinion supplemented by focused literature review allows a balanced evidence based presentation of data. Results: Documentation is not a perfect tool however, as issues with efficiency, reliability, use of shortcut maneuvers and potential for increased medico-legal risk have been raised. The solution is attention to documentation detail, and creation of systems that facilitate excellence. The focus on electronic documentation systems should include continual evaluation, ongoing improvement, involvement of a multidisciplinary patient care team and vendor receptiveness to in EHR development and operations. Conclusion: The most effective use of the EHR as a risk management tool requires documentation knowledge, targeted analysis, product improvement and co-development of clinical-commercial resource.(AU)

Introducción: Los momentos de mayor actividad en el hospital a menudo se enfrentan con los mayores desafíos en cuanto a la documentación completa y exhaustiva del evento de atención al paciente. La transición casi completa a la historia clínica electrónica (HCE) iba a ser la solución a una serie de preocupaciones sobre la documentación de los proveedores. Está claro que la HCE proporciona confiabilidad, reproducibilidad, integración, toma de decisiones basada en la evidencia y contribución multidisciplinaria en todo el espectro de la atención médica.Métodos: El uso de un consenso de opinión de expertos complementado con una revisión de la literatura enfocada permite una presentación equilibrada de los datos basada en la evidencia.Resultados: La documentación no es una herramienta perfecta, ya que se han planteado problemas de eficiencia, confiabilidad, uso de maniobras abreviadas y la posibilidad de un mayor riesgo medicolegal. La solución es la atención al detalle de la documentación y la creación de sistemas que faciliten la excelencia. El enfoque en los sistemas de documentación electrónica debe incluir evaluación continua, mejora continua, participación de un equipo multidisciplinario de atención al paciente y receptividad de los proveedores en el desarrollo y las operaciones de la HCE. Conclusión: El uso más eficaz de la HCE como herramienta de gestión de riesgos requiere conocimiento de la documentación, análisis específicos, mejora del producto y desarrollo conjunto de recursos clínico-comerciales.(AU)

General ward nurses detection and response to clinical deterioration in three hospitals at the Kenyan coast: a convergent parallel mixed methods study.

BACKGROUND: In low and middle-income countries like Kenya, critical care facilities are limited, meaning acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to deterioration. METHODS: This convergent parallel mixed methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the vital signs 24 h before a cardiac arrest (death) occurred was retrieved from patients' medical records. In-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards. RESULTS: This study reviewed 405 patient records and found most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 h prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points, i.e. four hourly. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs linked to limited availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers. CONCLUSION: The study showed that nurses did not consistently monitor and record vital signs in the general wards. They also worked in suboptimal ward environments that do not support their ability to promptly detect and respond to clinical deterioration. The findings illustrate the importance of implementation of standardised systems for patient assessment and alert mechanisms for deterioration response. Furthermore, creating a supportive work environment is imperative in empowering nurses to identify and respond to patient deterioration. Addressing these issues is not only beneficial for the nurses but, more importantly, for the well-being of the patients they serve.

New Documentation System for Ulnar Longitudinal Deficiency.

Background: This study examines the value of a new alphanumerical documentation system to classify the whole spectrum of deformities in ulnar longitudinal deficiency (ULD). Methods: The patients with ULD, whom were referred during a 35-year period, were identified from the hospital database. A total of 7 patients with photographs and/or conventional radiographs that could be adequately reproduced were enrolled in the study. Results: Six patients could be classified with the previously proposed classifications and the new documentation system. Three of them were diagnosed with ulnar-deficient hands. One had aplasia of the fifth finger ray (phalanges and metacarpal), a second aplasia of the fourth and fifth finger rays with narrowing of the first web, and a third aplasia of the fifth metacarpal. Furthermore, a fourth patient was diagnosed with hypoplasia of the ulna and congenital wrist amputation; a fifth with hypoplasia of the ulna, dislocation of the radial head, and a bowed radius; and a sixth with partial aplasia involving the middle and distal diaphysis of the ulna. Finally, one patient with an absent ulnar styloid process and oligodactyly with thumb could be classified only with the new system. Conclusions: The proposed new alphanumerical documentation system incorporates all the most widely accepted previous classification schemes, facilitates the morphological and radiographic description of the whole spectrum of the deformities detected in patients with ULD for better communication between scientists, and secures the unrestricted inclusion of new variants in the future.