Search

Purpose: Population level tracking of post-stroke functional outcomes is critical to guide interventions that reduce the burden of stroke-related disability. However, functional outcomes are often missing or documented in unstructured notes. We developed a natural language processing (NLP) model that reads electronic health records (EHR) notes to automatically determine the modified Rankin Scale (mRS)., Method: We included consecutive patients (⩾18 years) with acute stroke admitted to our center (2015-2024). mRS scores were obtained from the Get With the Guidelines registry and clinical notes (if documented), and used as the gold standard to compare against NLP-generated scores. We used text-based features from notes, along with age, sex, discharge status, and outpatient follow-up to train a logistic regression for prediction of good (0-2) versus poor (3-6) mRS, and a linear regression for the full range of mRS scores. The models were trained for prediction of mRS at hospital discharge and post-discharge. The models were externally validated in a dataset of patients with brain injuries from a different healthcare center., Findings: We included 5307 patients, 5006 in train and test and 301 in validation; average age was 69 (SD 15) and 65 (SD 17) years, respectively; 47% female. The logistic regression achieved an area under the receiver operating curve (AUROC) of 0.94 [CI 0.93-0.95] (test) and 0.94 [0.91-0.96] (validation), and the linear model a root mean squared error (RMSE) of 0.91 [0.87-0.94] (test) and 1.17 [1.06-1.28] (validation)., Discussion and Conclusion: The NLP-based model is suitable for use in large-scale phenotyping of stroke functional outcomes and population health research., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Zafar is a clinical neurophysiologist for Corticare, received speaking honoraria from Marinus, and received royalties from Springer publishing, unrelated to this work. Dr. Westover is a co-founder, scientific advisor, and consultant to Beacon Biosignals and has a personal equity interest in the company. He receives royalties for authoring Pocket Neurology from Wolters Kluwer and Atlas of Intensive Care Quantitative EEG by Demos Medical. None of these interests played any role in the present work.

Objectives: Unstructured and structured data in electronic health records (EHR) are a rich source of information for research and quality improvement studies. However, extracting accurate information from EHR is labor-intensive. Here we introduce an automated EHR phenotyping model to identify patients with Alzheimer's Disease, related dementias (ADRD), or mild cognitive impairment (MCI)., Methods: We assembled medical notes and associated International Classification of Diseases (ICD) codes and medication prescriptions from 3,626 outpatient adults from two hospitals seen between February 2015 and June 2022. Ground truth annotations regarding the presence vs. absence of a diagnosis of MCI or ADRD were determined through manual chart review. Indicators extracted from notes included the presence of keywords and phrases in unstructured clinical notes, prescriptions of medications associated with MCI/ADRD, and ICD codes associated with MCI/ADRD. We trained a regularized logistic regression model to predict the ground truth annotations. Model performance was evaluated using area under the receiver operating curve (AUROC), area under the precision-recall curve (AUPRC), accuracy, specificity, precision/positive predictive value, recall/sensitivity, and F1 score (harmonic mean of precision and recall)., Results: Thirty percent of patients in the cohort carried diagnoses of MCI/ADRD based on manual review. When evaluated on a held-out test set, the best model using clinical notes, ICDs, and medications, achieved an AUROC of 0.98, an AUPRC of 0.98, an accuracy of 0.93, a sensitivity (recall) of 0.91, a specificity of 0.96, a precision of 0.96, and an F1 score of 0.93 The estimated overall accuracy for patients randomly selected from EHRs was 99.88%., Conclusion: Automated EHR phenotyping accurately identifies patients with MCI/ADRD based on clinical notes, ICD codes, and medication records. This approach holds potential for large-scale MCI/ADRD research utilizing EHR databases., Competing Interests: Competing Interests The authors declare that there are no competing interests regarding the publication of this paper. Additional Declarations: The authors declare no competing interests.

Background: Atrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and effective management are crucial. Given the prevalence of obstructive sleep apnea among AF patients, electrocardiogram (ECG) analysis from polysomnography (PSG) offers a unique opportunity for early AF prediction. Our aim is to identify individuals at high risk of AF development from single‑lead ECGs during standard PSG., Methods: We analyzed 18,782 single‑lead ECG recordings from 13,609 subjects undergoing PSG at the Massachusetts General Hospital sleep laboratory. AF presence was identified using ICD-9/10 codes. The dataset included 15,913 recordings without AF history and 2054 recordings from patients diagnosed with AF between one month to fifteen years post-PSG. Data were partitioned into training, validation, and test cohorts ensuring that individual patients remained exclusive to each cohort. The test set was held out during the training process. We employed two different methods for feature extraction to build a final model for AF prediction: Extraction of hand-crafted ECG features and a deep learning method. For extraction of ECG-hand-crafted features, recordings were split into 30-s windows, and those with a signal quality index (SQI) below 0.95 were discarded. From each remaining window, 150 features were extracted from the time, frequency, time-frequency domains, and phase-space reconstructions of the ECG. A compilation of 12 statistical features summarized these window-specific features per recording, resulting in 1800 features (12 × 150). A pre-trained deep neural network from the PhysioNet Challenge 2021 was updated using transfer learning to discriminate recordings with and without AF. The model processed PSG ECGs in 16-s windows to generate AF probabilities, from which 13 statistical features were extracted. Combining 1800 features from feature extraction with 13 from the deep learning model, we performed a feature selection and subsequently trained a shallow neural network to predict future AF and evaluated its performance on the test cohort., Results: On the test set, our model exhibited sensitivity, specificity, and precision of 0.67, 0.81, and 0.3, respectively, for AF prediction. Survival analysis revealed a hazard ratio of 8.36 (p-value: 1.93 × 10 -52 ) for AF outcomes using the log-rank test., Conclusions: Our proposed ECG analysis method, utilizing overnight PSG data, shows promise in AF prediction despite modest precision, suggesting false positives. This approach could enable low-cost screening and proactive treatment for high-risk patients. Refinements, including additional physiological parameters, may reduce false positives, enhancing clinical utility and accuracy., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier Inc.)

Dogs are often referred to as "human's best friend," with many households in the United Kingdom and worldwide including a dog. Yet, whilst research highlights the myriad of human health benefits associated with canine companionship, many dogs are relinquished, or euthanized, for purported behavioral problems. A key behavior often cited in these situations is Reactivity, despite a lack of consensus in the literature (or in the lay population) as to exactly what is encompassed within this term. Resultantly, this paper reports on an online survey to investigate how the term Reactivity is understood by humans. Following the completion of a thematic analysis, six sub-themes were developed, forming three overarching theme clusters, namely; Canine Characteristics, The Importance of Human Perception and Human Capability. In sum, this research highlights the complex, nuanced and, sometimes, contradictory nature of understanding around the label of Reactivity, encompassing both canine and human factors. As such, conclusions include the proposal of a preliminary Perceived Reactivity Framework to conceptualize this seemingly multi-faceted concept.

Objectives: The proposed study aims to assess users' perceptions of a surgical safety checklist (SSC) reimplementation toolkit and its impact on SSC attitudes and operating room (OR) culture, meaningful checklist use, measures of surgical safety, and OR efficiency at 3 different hospital sites., Background: The High-Performance Checklist toolkit (toolkit) assists surgical teams in modifying and implementing or reimplementing the World Health Organization's SSC. Through the explore, prepare, implement, and sustain implementation framework, the toolkit provides a process and set of tools to facilitate surgical teams' modification, implementation, training on, and evaluation of the SSC., Methods: A pre-post intervention design will be used to assess the impact of the modified SSC on surgical processes, team culture, patient experience, and safety. This mixed-methods study includes quantitative and qualitative data derived from surveys, semi-structured interviews, patient focus groups, and SSC performance observations. Additionally, patient outcome and OR efficiency data will be collected from the study sites' health surveillance systems., Data Analysis: Statistical data will be analyzed using Statistical Product and Service Solutions, while qualitative data will be analyzed thematically using NVivo. Furthermore, interview data will be analyzed using the Consolidated Framework for Implementation Research and reach, effectiveness, adoption, implementation, maintenance implementation frameworks., Setting: The toolkit will be introduced at 3 diverse surgical sites in Alberta, Canada: an urban hospital, university hospital, and small regional hospital., Anticipated Impact: We anticipate the results of this study will optimize SSC usage at the participating surgical sites, help shape and refine the toolkit, and improve its usability and application at future sites., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Introduction: The WHO Surgical Safety Checklist (SSC) is a communication tool that improves teamwork and patient outcomes. SSC effectiveness is dependent on implementation fidelity. Administrative audits fail to capture most aspects of SSC implementation fidelity (ie, team communication and engagement). Existing research tools assess behaviours during checklist performance, but were not designed for routine quality assurance and improvement. We aimed to create a simple tool to assess SSC implementation fidelity, and to test its reliability using video simulations, and usability in clinical practice., Methods: The Checklist Performance Observation for Improvement (CheckPOINT) tool underwent two rounds of face validity testing with surgical safety experts, clinicians and quality improvement specialists. Four categories were developed: checklist adherence, communication effectiveness, attitude and engagement. We created a 90 min training programme, and four trained raters independently scored 37 video simulations using the tool. We calculated intraclass correlation coefficients (ICC) to assess inter-rater reliability (ICC>0.75 indicating excellent reliability). We then trained two observers, who tested the tool in the operating room. We interviewed the observers to determine tool usability., Results: The CheckPOINT tool had excellent inter-rater reliability across SSC phases. The ICC was 0.83 (95% CI 0.67 to 0.98) for the sign-in, 0.77 (95% CI 0.63 to 0.92) for the time-out and 0.79 (95% CI 0.59 to 0.99) for the sign-out. During field testing, observers reported CheckPOINT was easy to use. In 98 operating room observations, the total median (IQR) score was 25 (23-28), checklist adherence was 7 (6-7), communication effectiveness was 6 (6-7), attitude was 6 (6-7) and engagement was 6 (5-7)., Conclusions: CheckPOINT is a simple and reliable tool to assess SSC implementation fidelity and identify areas of focus for improvement efforts. Although CheckPOINT would benefit from further testing, it offers a low-resource alternative to existing research tools and captures elements of adherence and team behaviours., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: Modification of the World Health Organization's Surgical Safety Checklist (SSC) is a critical component of its implementation. To facilitate the SSC's use, it is important to know how surgical teams modify their SSCs, their reasons for making modifications, and the opportunities and challenges teams face in SSC tailoring., Objective: To study SSC modifications in high-income hospital settings in 5 countries: Australia, Canada, New Zealand, the United States, and the United Kingdom., Design, Setting, and Participants: This qualitative study used semistructured interviews based on the survey used in the quantitative study. Each interviewee was asked a core set of questions and various follow-up questions based on their survey responses. Interviews were conducted from July 2019 to February 2020 in person and online using teleconferencing software. Surgeons, anesthesiologists, nurses, and hospital administrators from the 5 countries were recruited through a survey and snowball sampling., Main Outcomes and Measures: Interviewees' attitudes and perceptions on SSC modifications and their perceived impact on operating rooms., Results: A total of 51 surgical team members and hospital administrators from the 5 countries were interviewed (37 [75%] with >10 years of service; 28 [55%] women). There were 15 (29%) surgeons, 13 (26%) nurses, 15 (29%) anesthesiologists, and 8 (16%) health administrators. Five themes emerged concerning the awareness and involvement in SSC modifications; reasons for modifications; types of modifications; the outcomes of modifications; and perceived barriers to SSC modifications. Based on the interviews, some SSCs may go many years without being revisited or modified. SSCs are modified to ensure they address local issues and standards of practice and that they are fit for purpose. Modifications are also made following adverse events to reduce the risk of reoccurrence. Interviewees described adding, moving, and removing elements from their SSCs, which increased their sense of ownership in their SSC and participation in its performance. Some barriers to modification included leadership and the SSC's inclusion in hospitals' electronic medical record., Conclusions and Relevance: In this qualitative study of surgical team members and administrators, interviewees described addressing contemporary surgical issues through various SSC modifications. The process of SSC modification may improve team cohesion and buy-in in addition to providing opportunities for teams to improve patient safety.

Lead poisoning occurs worldwide in populations of predatory birds, but exposure rates and population impacts are known only from regional studies. We evaluated the lead exposure of 1210 bald and golden eagles from 38 US states across North America, including 620 live eagles. We detected unexpectedly high frequencies of lead poisoning of eagles, both chronic (46 to 47% of bald and golden eagles, as measured in bone) and acute (27 to 33% of bald eagles and 7 to 35% of golden eagles, as measured in liver, blood, and feathers). Frequency of lead poisoning was influenced by age and, for bald eagles, by region and season. Continent-wide demographic modeling suggests that poisoning at this level suppresses population growth rates for bald eagles by 3.8% (95% confidence interval: 2.5%, 5.4%) and for golden eagles by 0.8% (0.7%, 0.9%). Lead poisoning is an underappreciated but important constraint on continent-wide populations of these iconic protected species.

Essential communication between healthcare staff is considered one of the key requirements for both safety and quality care when patients are handed over from one clinical area to other. This is particularly important in environments such as the operating theatre and intensive care where mistakes can be devastating. Health care has learned from other high-risk organisations (HRO) such as aviation where the use of checklists and human factors awareness has virtually eliminated human error and mistakes. To our knowledge, little has been published around ways to improve pathology specimen handover following surgery, with pathology request forms often conveying the bare minimum of information to assist the laboratory staff. Furthermore, the request form might not warn staff about potential hazards. In this article, we provide a brief summary of the factors involved in human error and introduce a novel checklist that can be readily completed at the same time as the routine pathology request form. This additional measure enhances safety, can help to reduce processing and mislabelling errors and provides essential information in a structured way assisting both laboratory staff and pathologists when handling head and neck surgical specimens., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: To explore Calgary family physicians' knowledge about hospices, their attitudes toward the referral process, and their understanding of barriers to referral for hospice care., Design: Surveys were mailed to 400 randomly selected participants. The survey contained 18 questions related to hospice care, physician experience, attitudes, and perceived barriers to making a hospice referral., Setting: Calgary, Alta., Participants: Family physicians., Main Outcome Measures: Survey responses were analyzed quantitatively using the (2) goodness-of-fit test, Kruskal-Wallis tests, and logistic regression analyses to examine univariate associations. Qualitative analysis of open-ended questions was done by content analysis and thematic coding., Results: In total, 104 surveys were mailed back. Family physicians agreed that palliative care in a hospice setting can greatly improve quality of life for patients, but only 2 of 6 knowledge questions about hospice care were answered correctly by most. Family physicians with special areas of interest or subspecialties were more likely to feel well-informed about hospice referrals (P = .017), indicated a higher comfort level discussing hospice and palliative care (P = .030), and were less likely to defer discussing it with patients (P = .023). Physicians with a special interest in palliative medicine were more likely to correctly answer the knowledge questions (P < .034) and to be familiar with the referral process (P < .001), patient eligibility (P < .001), and the palliative home care program (P = .003). Qualitative analysis revealed support for palliative home care and consultation services but concerns about caregiver coping and family issues. Concerns about disengagement of family physicians and uncertainty about the referral process are obstacles to referral., Conclusion: While Calgary family physicians are appreciative of hospice care, there are knowledge gaps. It is important to engage family physicians in the referral process., (Copyright© the College of Family Physicians of Canada.)

Background: Countries with expansive rural regions often experience an unequal distribution of physicians between rural and urban communities. A growing body of evidence suggests that the exposure to positive rural learning experiences has an influence on a physician's choice of practice location. Capitalizing on this observation, many medical schools have developed approaches that integrate rural exposure into their curricula during clerkship. It is postulated that a preclinical rural exposure may also be effective. However, to proceed further in development, accreditation requirements must be considered. In this investigation, academic equivalence between a preclinical rural community based teaching method and the established education model was assessed., Method: Two separate preclinical courses from the University of Calgary's three year Undergraduate Medical program were taught at two different rural sites in 2010 (11 students) and 2012 (12 students). The same academic content was delivered in the pilot sites as in the main teaching centre. To ensure consistency of teaching skills, faculty development was provided at each pilot site. Academic equivalence between the rural based learners and a matched cohort at the main University of Calgary site was determined using course examination scores, and the quality of the experience was evaluated through learner feedback., Results: In both pilot courses there was no significant difference between examination scores of the rural distributed learners and the learners at the main University of Calgary site (p > 0.05). Feedback from the participating students demonstrated that the preceptors were very positively rated and, relative to the main site, the small group learning environment appeared to provide strengthened social support., Conclusion: These results suggest that community distributed education in pre-clerkship may offer academically equivalent training to existing traditional medical school curricula while also providing learners with positive rural social learning environments. The approach described may offer the potential to increase exposure to rural practice without the cost of constructing additional physical learning sites.