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).

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.

Leveraging artificial intelligence in neurosurgery-unveiling ChatGPT for neurosurgical discharge summaries and operative reports.

PURPOSE: Chat generative pre-trained transformer (GPT) is a novel large pre-trained natural language processing software that can enable scientific writing amongst a litany of other features. Given this, there is a growing interest in exploring the use of ChatGPT models as a modality to facilitate/assist in the provision of clinical care. METHODS: We investigated the time taken for the composition of neurosurgical discharge summaries and operative reports at a major University hospital. In so doing, we compared currently employed speech recognition software (i.e., SpeaKING) vs novel ChatGPT for three distinct neurosurgical diseases: chronic subdural hematoma, spinal decompression, and craniotomy. Furthermore, factual correctness was analyzed for the abovementioned diseases. RESULTS: The composition of neurosurgical discharge summaries and operative reports with the assistance of ChatGPT leads to a statistically significant time reduction across all three diseases/report types: p < 0.001 for chronic subdural hematoma, p < 0.001 for decompression of spinal stenosis, and p < 0.001 for craniotomy and tumor resection. However, despite a high degree of factual correctness, the preparation of a surgical report for craniotomy proved to be significantly lower (p = 0.002). CONCLUSION: ChatGPT assisted in the writing of discharge summaries and operative reports as evidenced by an impressive reduction in time spent as compared to standard speech recognition software. While promising, the optimal use cases and ethics of AI-generated medical writing remain to be fully elucidated and must be further explored in future studies.

The 21st Century Cures Act: Inpatient Clinician Perceptions of Changes to Information Sharing at an Academic Medical Center.

Introduction To comply with the Information Blocking Rule in the 21st Century Cures Act, many hospitals began to release inpatient electronic health information such as clinical notes and results to patients immediately, starting in April 2021. We sought to understand the perceptions of hospital-based clinicians regarding the impact of these changes in information sharing on clinicians and patients. Materials and methods We developed and distributed an electronic survey to 122 inpatient attending physicians, resident physicians, and physician assistants within the internal medicine and family medicine departments at an academic medical center. The survey asked clinicians to rate their comfort with information-sharing protocols and describe their perceptions of the impact of immediate information sharing on their documentation habits and patient interactions following the implementation of the Cures Act. Results The survey response rate was 37.7% (46/122). Of the respondents, 56.5% felt comfortable with the note-sharing process, 84.8% reported omitting specific information from their notes to prevent patients from reading it, and 39.1% of clinicians agreed that patients have found clinical notes "more confusing than helpful." Conclusions Immediate sharing of electronic health information has the potential to be a powerful tool for communicating with hospitalized patients. However, our results show many hospital-based clinicians report limited comfort with the note-sharing process and perceive it to be confusing to patients. Efforts are needed to educate clinicians regarding information sharing, understand patient and family perspectives, and develop best practices to enhance communication through electronic notes.

Comparison of Endocrinologists' Physical Examination Documentation for In-person vs Video Telehealth Diabetes Visits.

Objective: Outpatient diabetes mellitus (DM) care over video telehealth (TH) requires modifications to how endocrinologists complete physical examinations (PEs). But there is little guidance on what PE components to include, which may incur wide variation in practice. We compared endocrinologists' documentation of DM PE components for in-person (IP) vs TH visits. Methods: Retrospective chart review of 200 notes for new patients with DM from 10 endocrinologists (10 IP and 10 TH visits each) in the Veterans Health Administration between April 1, 2020, and April 1, 2022. Notes were scored from 0 to 10 based on documentation of 10 standard PE components. We compared mean PE scores for IP vs TH across all clinicians using mixed effects models. Independent samples t-tests were used to compare both mean PE scores within clinician and mean scores for each PE component across clinicians for IP vs TH. We described virtual care-specific and foot assessment techniques. Results: The overall mean (SE) PE score was higher for IP vs TH (8.3 [0.5] vs 2.2 [0.5]; P < .001). Every endocrinologist had higher PE scores for IP vs TH. Every PE component was more commonly documented for IP vs TH. Virtual care-specific techniques and foot assessment were rare. Conclusions: Our study quantifies the degree to which Pes for TH were attenuated among a sample of endocrinologists, raising a flag that process improvements and research are needed for virtual Pes. Organizational support and training could help increase PE completion via TH. Research should examine reliability and accuracy of virtual PE, its value to clinical decision-making, and its impact on clinical outcomes.

A Standardized Ward Round Proforma Improves Documentation in a Specialist Stroke Unit.

Background and aim Ward-round documentation is important for clinical communication and patient safety. Standardized checklists have improved ward-round documentation in surgical and medical settings. This quality improvement project aimed to introduce a standardized ward round proforma to improve documentation in a UK specialist stroke unit. Methods Ward round entries were assessed against internally agreed standardized criteria. A stroke-specific ward round proforma was designed and introduced with input from the multidisciplinary team. A repeat audit was performed, including assessment of the use of different proforma sections. Multidisciplinary team members were invited to provide feedback via an anonymous online survey. Results A total of 111 ward round entries were reviewed before the proforma was introduced. Ninety-five ward round entries were reviewed following introduction of the proforma, and 84.2% of these used the proforma for documentation. Overall documentation of standardized criteria improved from 48.7% to 62.1% with substantial improvement seen in documentation of neurological examination, presence/absence of mechanical venous thromboembolism prophylaxis, and blood test results. Multidisciplinary team feedback was positive. Conclusions The stroke-specific ward round proforma improved the quality and consistency of documentation in the unit. An updated proforma was designed using these results and multidisciplinary team feedback.

Medical documentation practice and associated factors among health workers at private hospitals in the Amhara region, Ethiopia 2021.

INTRODUCTION: Medical documentation is an important part of the medical process as it is an essential way of communication within the health care system. However, medical documentation practice in the private sector is not well studied in Ethiopian context. The aim of this study was to assess the practice of medical documentation and its associated factors among health workers at private hospitals in the Amhara region, Ethiopia. METHOD: An institution-based cross-sectional quantitative study supplemented with a qualitative design was conducted among 419 health workers at the private hospitals in the Amhara Region, Ethiopia from March 29 to April 29 /2021. Data were collected using both a self-administered questionnaire and interview guide for quantitative and qualitative respectively. Data were entered using Epi data version 3.1 and analyzed using SPSS version 20. Descriptive statistics, Bi-variable, and multivariable logistic regression analysis were performed. In-depth interviews were conducted using semi-structured questionnaires with eight respondents to explore the challenges related to the practice of medical documentation. Respondent's response were analyzed using OpenCode version 4.03 thematically. RESULTS: Four hundred seven study participants returned the questionnaire. Nearly 50 % (47.2%) health workers had of good medical documentation practice. Health workers who received in-service training on medical documentation AOR = 2.77(95% CI: [1.49,5.14]), good knowledge AOR = 2.28 (95% CI: [1.34,3.89]), favorable attitude AOR = 1.78 (95%CI: [1.06,2.97]), strong motivation AOR = 3.49 (95% CI: [2.10,5.80]), available guide line formats AOR = 3.12 (95% CI: [1.41,6.84]), eHealth literacy AOR = 1.73(95% CI: [1.02,2.96]), younger age AOR = 2.64 (95% CI:[1.27,5.46]) were statistically associated with medical documentation. CONCLUSION: More than half of the medical services provided were not registered. Therefore, it is important to put extra efforts to improve documentation practice by providing planed trainings on standards of documentation to all health workers, creating positive attitudes and enhancing their knowledge by motivating them to develop a culture of information.

Best Practices in Medical Documentation: A Curricular Module.

OBJECTIVE: To create and validate a checklist for high-quality documentation and pilot a multi-modal, immersive educational module across multiple institutions. We hypothesized that this module would improve knowledge, skills, and attitudes in medical documentation. METHODS: Module design was grounded in an established curriculum design framework. We conducted the study across 12 pediatric critical care fellowship programs between September 2017 and January 2018. Workshops were allotted 90 minutes for completion. We utilized a pre-/post- study design to determine the workshop's impact. Changes in knowledge were assessed through pre and post testing. Changes in skills were evaluated with a validated checklist for inclusion of key documentation elements. Changes in attitudes were determined through learner self-assessment RESULTS: 83 of 138 eligible fellows (60%) started the module and 62 of 83 (75%) completed data sets for analysis. Immediate post-testing demonstrated modest statistically significant improvement in knowledge, skills, and attitudes. The workshop was easily disseminated and deployed CONCLUSIONS: This study demonstrates that a multi-modal educational intervention can lead to improvement in medical documentation knowledge, skills, and attitudes in a cohort of PCCM fellows and be easily disseminated for use by other specialties and types of clinicians.

Assessing the Accuracy of International Classification of Diseases (ICD) Coding for Delirium.

OBJECTIVE: We assessed the accuracy of the ICD-10 code for delirium (F05) and its relationship with delirium discharge summary documentation. METHODS: We performed a retrospective chart review at three academic hospitals. The Chart-based Delirium Identification Instrument (CHART-DEL) was used to identify 108 hospitalized patients aged ≥65 years with delirium, and 758 patients without delirium as controls. We assessed the proportion of patients who received the F05 code and calculated the sensitivity and specificity. We compared the rates of F05 code received between patients with and without "delirium" documented in the discharge summary. RESULTS: Among delirious patients, 46.3% received a F05 code, which has a sensitivity of 46.3% and specificity of 99.6% for delirium. Of charts with "delirium" in the discharge summary (n = 67), 67.2% were appropriately coded. CONCLUSIONS: Current ICD-10 data inadequately capture delirium. Delirium documentation in the discharge summary is associated with improved delirium coding.

A retrospective analysis of discharge summaries from a tertiary care hospital medical oncology unit: To assess compliance with documentation of recommended discharge summary components.

BACKGROUND: Discharge summaries are essential for health transition between inpatient hospital teams and outpatient general practices. The patient's outcome is dependent on the quality and timeliness of discharge summaries. AIM: A retrospective analysis was carried out to assess the compliance with recommended documentation of 697 electronic discharge summaries (eDSs) of oncology inpatients discharged in 2018 from the Canberra Hospital according to the National Guidelines of On-Screen Presentation of Discharge Summaries. METHODS AND RESULTS: Individual medical records were identified and screened for the recommended eDS components according to the National Guidelines. Out of the 17 recommended components, nine components were included in all discharge summaries, two components in more than 99% and two components in 95-96% of discharge summaries. The most frequently omitted components include "information provided to the patient," "ceased medicine" and "procedures," and these were omitted in 8, 38 and 82% of discharge summaries, respectively. CONCLUSION: Overall, most discharge summaries adhered to the national guidelines quite well by including most of the recommended components. However, the discharge summary quality is still inadequate in some domains.

Consideraciones legales sobre las notas de evolución en odontología / Legal considerations on medical charts in dentistry

El expediente clínico es considerado un documento de importancia médica y legal en donde se integran los datos necesarios para registrar el diagnóstico y los tratamientos realizados en cada paciente. Uno de los elementos más importantes dentro del expediente clínico son las notas de evolución, documentos con los que el odontólogo informa sobre el estado general del paciente y los tratamientos realizados cita tras cita. Existen legislaciones específicas en México que orientan al estomatólogo sobre los componentes mínimos necesarios que una nota de evolución debe tener; sin embargo, una de las omisiones más comunes de los odontólogos es que, por desconocimiento, no se dé la debida importancia a la elaboración de una adecuada nota de evolución, aumentando el riesgo de problemas legales. El objetivo del presente artículo es analizar la importancia de las notas de evolución dentro del expediente clínico, destacando su importancia clínica y legal (AU)

The clinical file is considered a document of medical and legal importance where the data necessary to record the diagnosis and the treatments performed on each patient are integrated. One of the most important elements within the clinical records are the medical charts, documents through which de dentist reports on the general condition of the patient and the treatments performed appointment after appointment. There are specific laws in Mexico that guide the stomatologist on the minimum necessary components that a medical chart must have, however, one of the most common omissions of dentist is that, due to ignorance, due importance is not given to the preparation of an adequate medical chart, increasing the risk of legal problems. The aim of this article is to analyze the importance of the evolution charts within the clinical records, highlighting their clinical and legal importance (AU)

A patient-centered digital scribe for automatic medical documentation.

OBJECTIVE: We developed a digital scribe for automatic medical documentation by utilizing elements of patient-centered communication. Excessive time spent on medical documentation may contribute to physician burnout. Patient-centered communication may improve patient satisfaction, reduce malpractice rates, and decrease diagnostic testing expenses. We demonstrate that patient-centered communication may allow providers to simultaneously talk to patients and efficiently document relevant information. MATERIALS AND METHODS: We utilized two elements of patient-centered communication to document patient history. One element was summarizing, which involved providers recapping information to confirm an accurate understanding of the patient. Another element was signposting, which involved providers using transition questions and statements to guide the conversation. We also utilized text classification to allow providers to simultaneously perform and document the physical exam. We conducted a proof-of-concept study by simulating patient encounters with two medical students. RESULTS: For history sections, the digital scribe was about 2.7 times faster than both typing and dictation. For physical exam sections, the digital scribe was about 2.17 times faster than typing and about 3.12 times faster than dictation. Results also suggested that providers required minimal training to use the digital scribe, and that they improved at using the system to document history sections. CONCLUSION: Compared to typing and dictation, a patient-centered digital scribe may facilitate effective patient communication. It may also be more reliable compared to previous approaches that solely use machine learning. We conclude that a patient-centered digital scribe may be an effective tool for automatic medical documentation.

Evaluation of comprehensiveness and reliability of electronic health records concerning resuscitation efforts within academic intensive care units: a retrospective chart analysis.

BACKGROUND: According to the literature, the validity and reliability of medical documentation concerning episodes of cardiopulmonary resuscitation (CPR) is suboptimal. However, little is known about documentation quality of CPR efforts during intensive care unit (ICU) stays in electronic patient data management systems (PDMS). This study analyses the reliability of CPR-related medical documentation within the ICU PDMS. METHODS: In a retrospective chart analysis, PDMS records of three ICUs of a single university hospital were searched over 5 y for CPR check marks. Respective datasets were analyzed concerning data completeness and data consistency by comparing the content of three documentation forms (physicians' log, nurses' log, and CPR incident form), as well as physiological and therapeutic information of individual cases, for missing data and plausibility of CPR starting time and duration. To compare data reliability and completeness, a quantitative measure, the Consentaneity Index (CI), is proposed. RESULTS: One hundred sixty-five datasets were included into the study. In 9% (n = 15) of cases, there was neither information on the time points of CPR initiation nor on CPR duration available in any data source. Data on CPR starting time and duration were available from at least two data sources in individual cases in 54% (n = 90) and 45% (n = 74), respectively. In these cases, the specifications of CPR starting time did differ by a median ± interquartile range of 10.0 ± 18.5 min, CPR duration by 5.0 ± 17.3 min. The CI as a marker of data reliability revealed a low consistency of CPR documentation in most cases, with more favorable results, if the time interval between the CPR episode and the time of documentation was short. CONCLUSIONS: This study reveals relevant proportions of missing and inconsistent data in electronic CPR documentation in the ICU setting. The CI is suggested as a tool for documentation quality analysis and monitoring of improvements.

Evaluation of multidisciplinary shoulder dystocia simulation training on knowledge, performance, and documentation.

BACKGROUND: Research has shown the utility of simulations involving individuals, yet little data exist on whether communication and documentation are impacted by the integration of all team members into a scenario. In 2018, the obstetrics department at this tertiary hospital began a multidisciplinary team-training simulation for shoulder dystocia. An educational portion was included, teaching a new practice where the provider announces delivery events (head, shoulder, body) to be marked on the delivery record, a standardized approach was introduced, and a pre- and post-simulation test was administered. OBJECTIVE: In this study, we sought to evaluate the lasting impact of this team-based tool on the outcomes and documentation of shoulder dystocia cases, specifically the recording of the exact shoulder dystocia duration in seconds. Secondary outcomes included evaluation of the documentation of shoulder dystocia maneuvers and a pre- and post-simulation knowledge test. Included in this test were questions from the validated survey, the Safety Attitudes Questionnaire, a tool focused on evaluating team dynamics and communication. It was hypothesized that this simulation would improve communication as shown by sustained improvement in documentation, competence in shoulder dystocia care, and confidence among members of the team as shown by improved scores on the Safety Attitudes Questionnaire. STUDY DESIGN: This was a retrospective cohort study of shoulder dystocia cases from 2017 and 2019 at a safety-net tertiary care hospital, 1 full year before and after the implementation of a multidisciplinary shoulder dystocia simulation in 2018. Delivery outcomes were compared, documentation of delivery event times was recorded and analyzed, and the delivery note was evaluated using the American College of Obstetricians and Gynecologists guidelines for shoulder dystocia. The surveys from participants were assessed for postsimulation improvement. Categorical variables were analyzed using chi-square tests and continuous variables were compared using Student t tests. Because shoulder dystocia duration is a nonparametric variable, this was compared using a Kruskal-Wallis test. RESULTS: There were 28 cases in the 2017 cohort and 25 in the 2019 cohort. In the 2017 cohort, 25% of delivery documentation (7 of 25) included the exact shoulder dystocia duration, which increased to 96% (24 of 25) in the 2019 cohort (P<.001). There was no significant impact on the shoulder dystocia duration (P=.163). On average, 2.7 maneuvers were required in the 2017 cohort, which increased to 3.4 maneuvers used in the 2019 cohort, showing a significant increase in the use of shoulder dystocia maneuvers (P=.030). The posttests showed no impact on shoulder dystocia background knowledge (P=.142) or knowledge of risk factors (P=.171) but did show an increased understanding of the definition and performance of shoulder dystocia maneuvers (P=.008). The Safety Attitudes Questionnaire revealed that simulation participants would feel safe being treated by their colleagues with a score of 4.7/5. On the paired responses after the simulation, nurses reported feeling that their input was more highly valued (P=.045), and participants of all disciplines felt they received adequate feedback on their performances (P=.041). CONCLUSION: A multidisciplinary simulation on shoulder dystocia led to sustained improvement in documentation and shoulder dystocia maneuvers used, suggesting increased comfort with advanced maneuvers. Future studies should evaluate whether multidisciplinary simulations, mimicking the normal delivery team, may lead to other sustained improvements in maternal care.

Deep Neural Network Driven Speech Classification for Relevance Detection in Automatic Medical Documentation.

The automation of medical documentation is a highly desirable process, especially as it could avert significant temporal and monetary expenses in healthcare. With the help of complex modelling and high computational capability, Automatic Speech Recognition (ASR) and deep learning have made several promising attempts to this end. However, a factor that significantly determines the efficiency of these systems is the volume of speech that is processed in each medical examination. In the course of this study, we found that over half of the speech, recorded during follow-up examinations of patients treated with Intra-Vitreal Injections, was not relevant for medical documentation. In this paper, we evaluate the application of Convolutional and Long Short-Term Memory (LSTM) neural networks for the development of a speech classification module aimed at identifying speech relevant for medical report generation. In this regard, various topology parameters are tested and the effect of the model performance on different speaker attributes is analyzed. The results indicate that Convolutional Neural Networks (CNNs) are more successful than LSTM networks, and achieve a validation accuracy of 92.41%. Furthermore, on evaluation of the robustness of the model to gender, accent and unknown speakers, the neural network generalized satisfactorily.

Technical and Medical Aspects of Burn Size Assessment and Documentation.

In burn medicine, the percentage of the burned body surface area (TBSA-B) to the total body surface area (TBSA) is a crucial parameter to ensure adequate treatment and therapy. Inaccurate estimations of the burn extent can lead to wrong medical decisions resulting in considerable consequences for patients. These include, for instance, over-resuscitation, complications due to fluid aggregation from burn edema, or non-optimal distribution of patients. Due to the frequent inaccurate TBSA-B estimation in practice, objective methods allowing for precise assessments are required. Over time, various methods have been established whose development has been influenced by contemporary technical standards. This article provides an overview of the history of burn size estimation and describes existing methods with a critical view of their benefits and limitations. Traditional methods that are still of great practical relevance were developed from the middle of the 20th century. These include the "Lund Browder Chart", the "Rule of Nines", and the "Rule of Palms". These methods have in common that they assume specific values for different body parts' surface as a proportion of the TBSA. Due to the missing consideration of differences regarding sex, age, weight, height, and body shape, these methods have practical limitations. Due to intensive medical research, it has been possible to develop three-dimensional computer-based systems that consider patients' body characteristics and allow a very realistic burn size assessment. To ensure high-quality burn treatment, comprehensive documentation of the treatment process, and wound healing is essential. Although traditional paper-based documentation is still used in practice, it no longer meets modern requirements. Instead, adequate documentation is ensured by electronic documentation systems. An illustrative software already being used worldwide is "BurnCase 3D". It allows for an accurate burn size assessment and a complete medical documentation.

Beyond Notes: Why It Is Time to Abandon an Outdated Documentation Paradigm.

Clinicians spend a substantial part of their workday reviewing and writing electronic medical notes. Here we describe how the current, widely accepted paradigm for electronic medical notes represents a poor organizational framework for both the individual clinician and the broader medical team. As described in this viewpoint, the medical chart-including notes, labs, and imaging results-can be reconceptualized as a dynamic, fully collaborative workspace organized by topic rather than time, writer, or data type. This revised framework enables a more accurate and complete assessment of the current state of the patient and easy historical review, saving clinicians substantial time on both data input and retrieval. Collectively, this approach has the potential to improve health care delivery effectiveness and efficiency.

Artificial Intelligence in the Healthcare System: An Overview.

This chapter aims to present insights into the influence of artificial intelligence (AI) on medicine, public health, and the economy. PubMed and Google Scholar databases were used for the identification and collection of articles with search commands of "artificial intelligence" AND "public health" and "artificial intelligence" AND "medicine". A total of 273 articles specifically handling the issue of artificial intelligence, dating ten years back, in three major medical journals: Science, The Lancet, and The New England Journal of Medicine, were analyzed. Computational power gets stronger by the day, giving us new solutions and possibilities. Current medicine problems like personalized medicine, storage of data, and documentation overload will likely be replaced by AI shortly. The application of AI may also bring substantial benefits to other areas of medicine like the diagnostic and therapeutic processes. The development and spread of AI are inescapable as it lowers healthcare and administrative costs, improves medical efficiency, and predicts and prevents major disease complications. The use of AI in medicine seems destined to carry the day.

A probable case of holoprosencephaly with cyclopia in a full-term fetus from a modern skeletal collection.

OBJECTIVE: This study presents evidence of a probable case of holoprosencephaly with cyclopia, which has been rarely reported in the paleopathological literature. MATERIALS: The skeletal remains of a male fetus between 36 and 40 gestational weeks from the Collezione Antropologica LABANOF (CAL) Milano Cemetery Skeletal Collection were studied. METHODS: The bones were macroscopically examined, and pathological anomalies were recorded and evaluated alongside paleopathological and clinical literature. RESULTS: Developmental anomalies were observed. In particular, a single orbit and optical canal were present, and the frontal, sphenoid and palatine bones were prematurely fused. These changes altered the normal morphology of the midline structures of the cranium and face. CONCLUSIONS: The developmental anomalies observed are consistent with a case of holoprosencephaly associated with cyclopia. SIGNIFICANCE: Holoprosencephaly is a fatal congenital condition caused by the failure of the prosencephalon to separate in two halves. This condition is clinically well-known, with an estimated modern incidence of 1/16,000 births; however, the paleopathological literature lacks reports that would help anthropologists and paleopathologists interpret these anomalous signs on dry bone. This report documents a rare paleopathological case of the condition on a full-term fetus from a modern skeletal collection. LIMITATIONS: Taphonomic and anthropic factors may have impaired the observation of all pathological features. SUGGESTIONS FOR FURTHER RESEARCH: Comparative studies with cases from documented collections could improve knowledge of the appearance of this condition on dry bones.