Automated Identification of Postoperative Infections to Allow Prediction and Surveillance Based on Electronic Health Record Data: Scoping Review.

BACKGROUND: Postoperative infections remain a crucial challenge in health care, resulting in high morbidity, mortality, and costs. Accurate identification and labeling of patients with postoperative bacterial infections is crucial for developing prediction models, validating biomarkers, and implementing surveillance systems in clinical practice. OBJECTIVE: This scoping review aimed to explore methods for identifying patients with postoperative infections using electronic health record (EHR) data to go beyond the reference standard of manual chart review. METHODS: We performed a systematic search strategy across PubMed, Embase, Web of Science (Core Collection), the Cochrane Library, and Emcare (Ovid), targeting studies addressing the prediction and fully automated surveillance (ie, without manual check) of diverse bacterial infections in the postoperative setting. For prediction modeling studies, we assessed the labeling methods used, categorizing them as either manual or automated. We evaluated the different types of EHR data needed for the surveillance and labeling of postoperative infections, as well as the performance of fully automated surveillance systems compared with manual chart review. RESULTS: We identified 75 different methods and definitions used to identify patients with postoperative infections in studies published between 2003 and 2023. Manual labeling was the predominant method in prediction modeling research, 65% (49/75) of the identified methods use structured data, and 45% (34/75) use free text and clinical notes as one of their data sources. Fully automated surveillance systems should be used with caution because the reported positive predictive values are between 0.31 and 0.76. CONCLUSIONS: There is currently no evidence to support fully automated labeling and identification of patients with infections based solely on structured EHR data. Future research should focus on defining uniform definitions, as well as prioritizing the development of more scalable, automated methods for infection detection using structured EHR data.

Effect of Intra-articular Atelocollagen Injections for Patients With Knee Osteoarthritis: A Retrospective Chart Review.

Background Osteoarthritis (OA) is a prevalent and exhausting condition often requiring long-term management. While there is a steady growth in the use of collagen-based treatment for OA, there is a lack of studies assessing the safety and efficacy of repeated administration of injectable atelocollagen for OA. Objective This study aims to evaluate the clinical efficacy and safety of repeated administration of injectable atelocollagen in reducing knee pain for patients with knee OA. Methods Clinical records of 91 patients from five hospitals were reviewed for this retrospective study. All 91 patients had received repeated administration of injectable atelocollagen (CartiPRO®, Dalim Tissen Co., Ltd., South Korea) as a treatment for knee OA for seven months. The efficacy of injectable atelocollagen was evaluated by physicians at least 30 days after the last administration, with outcomes categorized as "effective", "moderately effective", or "not effective". For analysis purposes, both "effective" and "moderately effective" were grouped as "effective" while "not effective" was classified as "ineffective". Safety was assessed by monitoring the incidence of adverse events (AEs) reported within six months following the re-administration of atelocollagen. Results Among the 91 patients, 96.7% (88 patients) experienced effective pain relief following the re-administration of CartiPRO®, with 3.3% (three patients) reporting ineffectiveness. In terms of safety assessment, 35 patients reported AEs, totaling up to 44 events, with no serious or unexpected device-related AEs. Conclusion The repeated use of atelocollagen was found to be both safe and effective in managing knee pain for patients with knee OA. These findings support the repeated use of injectable atelocollagen as a reliable treatment option for managing knee OA pain in clinical practice.

Factors Associated with Take Home Naloxone Refusal among Emergency Department Patients Participating in an Opioid Overdose Prevention Program.

BACKGROUND: Increasing the equitable distribution of take home naloxone (THN) may result in reduced deaths from opioid overdose (OD). OBJECTIVES: The primary study objective is to describe the demographic and clinical characteristics of emergency department (ED) patients who decline THN. The findings of this descriptive study may generate new hypotheses for successful THN distribution. METHODS: Retrospective chart review using prospectively collected program evaluation data from a single urban EDs Health Education THN database and electronic health record. Characteristics of participants who refused versus accepted THN were compared using Chi-square testing for categorical variables and t-tests for continuous variables. A multivariate model was built to assess associations of statistical and clinically relevant characteristics with THN refusal. RESULTS: A total of 711 ED patients were offered THN of which 334 (46%) declined. In unadjusted analysis, with the independent variable being refusal of the THN offer, being currently on medication for opioid use disorder (MOUD) was associated with a greater odds of refusal (OR 1.9, 95%CI 1.3-2.6) while any drug related overdose (OR 0.6, 95%CI 0.4-0.8) or being given a prescription for buprenorphine in the ED (OR 0.2, 95%CI 0.1-0.9) were both associated with a lower odds of refusal. CONCLUSIONS: Demographic characteristics did not differ between those who accept versus refuse THN. Patients already receiving MOUD were more likely to refuse THN while those starting MOUD in the ED were less likely to refuse THN. Further studies are needed to determine the root causes of patients' declination of THN and develop targeted interventions to address these causes.

Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study.

OBJECTIVE: Phenotypic misclassification in genetic association analyses can impact the accuracy of PRS-based prediction models. The bias reduction method proposed by Tong et al. (2019) has demonstrated its efficacy in reducing the effects of bias on the estimation of association parameters between genotype and phenotype while minimizing variance by employing chart reviews on a subset of the data for validating phenotypes, however its improvement of subsequent PRS prediction accuracy remains unclear. Our study aims to fill this gap by assessing the performance of simulated PRS models and estimating the optimal number of chart reviews needed for validation. METHODS: To comprehensively assess the efficacy of the bias reduction method proposed by Tong et al. in enhancing the accuracy of PRS-based prediction models, we simulated each phenotype under different correlation structures (an independent model, a weakly correlated model, a strongly correlated model) and introduced error-prone phenotypes using two distinct error mechanisms (differential and non-differential phenotyping errors). To facilitate this, we used genotype and phenotype data from 12 case-control datasets in the Alzheimer's Disease Genetics Consortium (ADGC) to produce simulated phenotypes. The evaluation included analyses across various misclassification rates of original phenotypes as well as quantities of validation set. Additionally, we determined the median threshold, identifying the minimal validation size required for a meaningful improvement in the accuracy of PRS-based predictions across a broad spectrum. RESULTS: This simulation study demonstrated that incorporating chart review does not universally guarantee enhanced performance of PRS-based prediction models. Specifically, in scenarios with minimal misclassification rates and limited validation sizes, PRS models utilizing debiased regression coefficients demonstrated inferior predictive capabilities compared to models using error-prone phenotypes. Put differently, the effectiveness of the bias reduction method is contingent upon the misclassification rates of phenotypes and the size of the validation set employed during chart reviews. Notably, when dealing with datasets featuring higher misclassification rates, the advantages of utilizing this bias reduction method become more evident, requiring a smaller validation set to achieve better performance. CONCLUSION: This study highlights the importance of choosing an appropriate validation set size to balance between the efforts of chart review and the gain in PRS prediction accuracy. Consequently, our study establishes a valuable guidance for validation planning, across a diverse array of sensitivity and specificity combinations.

Recorded Rates of Trauma-Exposure in a Retrospective Epidemiologically Complete First-Episode Psychosis Cohort.

BACKGROUND: Trauma plays an important role in the development and maintenance of psychosis. However, it is still under-examined in daily clinical practice. The current study investigated the rates of recording of trauma-exposure in the clinical histories of a first-episode psychosis (FEP) cohort attending an early intervention psychosis service. METHODS: This study used a retrospective chart review methodology in a 6-year epidemiologically complete FEP cohort attending an early intervention psychosis service. The Trauma and Life Events Checklist was used to define the rate and types of trauma-exposure reported in clinical histories. The relationships were examined between recorded trauma-exposure and positive and negative symptoms, depression and duration of untreated psychosis at first assessment. RESULTS: Trauma-exposure was frequently recorded within clinical histories. Childhood trauma-exposure was recorded in 47.4% of the sample, which is lower than may be expected. No significant relationships between the recorded trauma-exposure and symptom measures were found. A significant relationship was found between interpersonal stressors and positive symptoms, and work-related stress and negative symptoms, highlighting the importance of proximal stressful life events. DISCUSSION: This study found that clinicians were frequently recording trauma-exposure in daily practice. However, it was unclear whether the recording of trauma-exposure highlighted led to systematic diagnosis, assessment or treatment of trauma for people with psychosis. The importance of treatment and service planning to include information about trauma-exposure is discussed.

Communicating Adolescent and Young Adult Oncology Treatment Guidelines in Practice: The Importance of Documentation for Ensuring Positive Impacts on Oncology Care.

Purpose: Improvements in outcomes for adolescent and young adult (AYA) oncology patients have lagged behind those of other age-specific cancer populations. Research has indicated that low availability of clinical trials, biological differences of this age-group, and several psychosocial factors including higher emotional distress impact outcomes. To improve care and survival rates for these patients, hospitals have implemented AYA oncology programs. The current study evaluated documentation of care in an AYA program housed in an academic medical center based on three areas emphasized in the National Comprehensive Cancer Network's Clinical Practice Guidelines in Oncology for AYAs: clinical trial enrollment, fertility, and psychosocial care. Methods: Retrospective chart reviews were conducted for 45 patients treated before the start of the AYA oncology program and 45 patients treated after program initiation. Patients aged 15-39 years with a diagnosis of a malignant tumor were included. Variables evaluated included documentation of clinical trial enrollment, fertility preservation and sexual health considerations, and behavioral health referrals. Results: Documentation of most clinical trial and fertility variables did not significantly improve from pre- to post-program, although a higher number of patients had these variables documented post-program. Behavioral health referrals increased significantly from 52.8% pre-program to 95.4% post-program. Conclusion: Access to behavioral health care improved the most following implementation of our AYA program, which is likely because of the integration of a dedicated psychologist for AYAs when the program began. The practice of guideline-based care for this population can be better assessed and improved with designated behavioral health providers and more systematic documentation processes.

United States clinical practice experience with eculizumab in myasthenia gravis: symptoms, function, and immunosuppressant therapy use.

BACKGROUND/OBJECTIVES: The phase 3 REGAIN study and its open-label extension demonstrated the efficacy of the complement C5 inhibitor eculizumab in patients with treatment-refractory, acetylcholine receptor antibody-positive generalized myasthenia gravis (gMG). The aim of the ELEVATE study was to assess the effectiveness of eculizumab in clinical practice in adults with MG in the United States. METHODS: A retrospective chart review was conducted in adults with MG who initiated eculizumab treatment between October 23, 2017 and December 31, 2019. Outcomes assessed before and during eculizumab treatment using a pre- versus post-treatment study design included Myasthenia Gravis-Activities of Daily Living (MG-ADL) total scores; minimal symptom expression (MSE); physician impression of clinical change; minimal manifestation status (MMS); and concomitant medication use. RESULTS: In total, 119 patients were included in the study. A significant reduction was observed in mean MG-ADL total score, from 8.0 before eculizumab initiation to 5.4 at 3 months and to 4.7 at 24 months after eculizumab initiation (both p < 0.001). At 24 months after eculizumab initiation, MSE was achieved by 19% of patients. MMS or better was achieved by 30% of patients at 24 months. Additionally, 64% of patients receiving prednisone at eculizumab initiation had their prednisone dosage reduced during eculizumab treatment and 13% discontinued prednisone; 32% were able to discontinue nonsteroidal immunosuppressant therapy. DISCUSSION: Eculizumab treatment was associated with sustained improvements in MG-ADL total scores through 24 months in adults with MG. Prednisone dosage was reduced in approximately two-thirds of patients, suggesting a steroid-sparing effect for eculizumab.

Spatiotemporal epidemiology of substance-related accidental acute toxicity deaths in Canada from 2016 to 2017.

OBJECTIVES: In Canada, substance-related accidental acute toxicity deaths (AATDs) continue to rise at the national and sub-national levels. However, it is unknown if, where, when, and to what degree AATDs cluster in space, time, and space-time across the country. The objectives of this study were to 1) assess for clusters of AATDs that occurred in Canada during 2016 and 2017 at the national and provincial/territorial (P/T) levels, and 2) examine the substance types detected in AATD cases within each cluster. METHODS: Two years of person-level data on AATDs were abstracted from coroner and medical examiner files using a standardized data collection tool, including the decedent's postal code and municipality information on the places of residence, acute toxicity (AT) event, and death, and the substances detected in the death. Data were combined with Canadian census information to create choropleth maps depicting AATD rates by census division. Spatial scan statistics were used to build Poisson models to identify clusters of high rates (p < 0.05) of AATDs at the national and P/T levels in space, time, and space-time over the study period. AATD cases within clusters were further examined for substance types most present in each cluster. RESULTS: Eight clusters in five regions of Canada at the national level and 24 clusters in 15 regions at the P/T level were identified, highlighting where AATDs occurred at far higher rates than the rest of the country. The risk ratios of identified clusters ranged from 1.28 to 9.62. Substances detected in clusters varied by region and time, however, opioids, stimulants, and alcohol were typically the most commonly detected substances within clusters. CONCLUSION: Our findings are the first in Canada to reveal the geographic disparities in AATDs at national and P/T levels using spatial scan statistics. Rates associated with substance types within each cluster highlight which substance types were most detected in the identified regions. Findings may be used to guide intervention/program planning and provide a picture of the 2016 and 2017 context that can be used for comparisons of the geographic distribution of AATDs and substances with different time periods.

Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors.

BACKGROUND: Manual chart review using validated assessment tools is a standardised methodology for detecting diagnostic errors. However, this requires considerable human resources and time. ChatGPT, a recently developed artificial intelligence chatbot based on a large language model, can effectively classify text based on suitable prompts. Therefore, ChatGPT can assist manual chart reviews in detecting diagnostic errors. OBJECTIVE: This study aimed to clarify whether ChatGPT could correctly detect diagnostic errors and possible factors contributing to them based on case presentations. METHODS: We analysed 545 published case reports that included diagnostic errors. We imputed the texts of case presentations and the final diagnoses with some original prompts into ChatGPT (GPT-4) to generate responses, including the judgement of diagnostic errors and contributing factors of diagnostic errors. Factors contributing to diagnostic errors were coded according to the following three taxonomies: Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC) and Generic Diagnostic Pitfalls (GDP). The responses on the contributing factors from ChatGPT were compared with those from physicians. RESULTS: ChatGPT correctly detected diagnostic errors in 519/545 cases (95%) and coded statistically larger numbers of factors contributing to diagnostic errors per case than physicians: DEER (median 5 vs 1, p<0.001), RDC (median 4 vs 2, p<0.001) and GDP (median 4 vs 1, p<0.001). The most important contributing factors of diagnostic errors coded by ChatGPT were 'failure/delay in considering the diagnosis' (315, 57.8%) in DEER, 'atypical presentation' (365, 67.0%) in RDC, and 'atypical presentation' (264, 48.4%) in GDP. CONCLUSION: ChatGPT accurately detects diagnostic errors from case presentations. ChatGPT may be more sensitive than manual reviewing in detecting factors contributing to diagnostic errors, especially for 'atypical presentation'.

Disease landscape of advanced HER2-breast cancer patients by treatment line in three EU countries and USA.

Aim: To report treatment patterns and quality of life (QoL) in HER2-negative advanced breast cancer patients. Methods: Data were drawn from a cross-sectional survey in Europe and USA. Results: Hormone plus targeted therapy was the most frequent first-line (1L, 62%) and second-line (2L, 45%) treatment for HR+/HER2-patients. Chemotherapy was most frequent at third-line or greater (3L+, 39%) for HR+/HER2- patients, 2L (51%) and 3L+ (48%) for triple negative breast cancer (TNBC) patients. Time to progression was 13.8 (2L) and 11.0 (3L+) months for HR+/HER2- patients. No comparisons were observed for TNBC patients. EQ-5D-5L scores were highest in patients at 1L and lowest at 3L+. Conclusion: Reduced QoL and treatment response were reported in patients at later lines of therapy.

Breast cancer is the most common cancer in women. Differences in survival are seen depending on how widespread or advanced the cancer is, how many different treatments the patient has been given, as well as whether certain receptors on the tumor are present or absent. Many new treatments are available which can target these receptors. These treatments have improved survival in patients with advanced breast cancer, but other benefits for the patient are not always clear. In addition, differences between countries are possible as official guidance can vary. This study aimed to understand these issues, by asking physicians and their patients across Europe and USA for their views on quality of life and satisfaction with their treatments. We found that, in general, physicians prescribed treatments as recommended in the treatment guidelines. As breast cancer progressed and treatment stopped working, patients were switched on to different treatments. Survival, quality of life and treatment satisfaction were all worse in patients who had switched treatments. It appears that the patients lose confidence that their new treatment will work to improve their quality of life. We also saw differences in some of these outcomes between Europe and USA, which were likely due to differences in the treatment guidelines between countries. Both quality of life and treatment satisfaction are important for the well-being of patients with advanced breast cancer as they now live longer with these new treatments. This should be considered by physicians and taken into account for future work.

Characterization of Post-COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study.

BACKGROUND: Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear. OBJECTIVE: This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions. METHODS: Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic. RESULTS: Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems. CONCLUSIONS: This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.

Retrospective chart review of GI bleeding in people with von Willebrand disease.

INTRODUCTION: Gastrointestinal (GI) bleeding events (BEs) in von Willebrand disease (VWD) are difficult to diagnose and often recurrent. Limited data from clinical trials has led to lack of consensus on treatment options. AIM: Describe current treatments and outcomes for GI BEs in people with VWD. METHODS: This retrospective, observational, multicentre chart review study was conducted from January 2018 through December 2019 and included patients with inherited VWD with ≥1 GI BE in the preceding 5 years. Baseline characteristics, number and aetiology of BEs, associated GI-specific morbidities/lesions, treatment and outcomes were analysed descriptively. RESULTS: Sixty bleeds were reported in 20 patients with type 1 (20%), type 2 (50%) and type 3 (30%) VWD. During the 5-year study period, 31 (52%) BEs had one identified or suspected cause; multiple causes were reported in 11 (18%). Most GI BEs (72%) were treated with a combination of von Willebrand factor (VWF), antifibrinolytics and/or other haemostatic or non-haemostatic treatments. Time to resolution did not differ by VWF treatment use; however, BEs treated with non-VWF treatments tended to resolve later. In patients with GI-specific morbidities/lesions, 84% resolved with first-line treatment; time to resolution tended to be longer than in patients without such morbidities/lesions. Thirteen BEs occurred in patients receiving prophylaxis and 47 in patients receiving on-demand treatment; 18 BEs resulted in a switch to prophylaxis after bleed resolution. CONCLUSIONS: This study confirms the unmet need for the management of recurrent GI BEs in people with VWD and the need for prospective data, especially on prophylaxis.

Evaluating algorithms for identifying incident Guillain-Barré Syndrome in Medicare fee-for-service claims.

Objective: Claims data can be leveraged to study rare diseases such as Guillain-Barré Syndrome (GBS), a neurological autoimmune condition. It is difficult to accurately measure and distinguish true cases of disease with claims without a validated algorithm. Our objective was to identify the best-performing algorithm for identifying incident GBS cases in Medicare fee-for-service claims data using chart reviews as the gold standard. Study design and setting: This was a multi-center, single institution cohort study from 2015 to 2019 that used Medicare-linked electronic health record (EHR) data. We identified 211 patients with a GBS diagnosis code in any position of an inpatient or outpatient claim in Medicare that also had a record of GBS in their electronic medical record. We reported the positive predictive value (PPV = number of true GBS cases/total number of GBS cases identified by the algorithm) for each algorithm tested. We also tested algorithms using several prevalence assumptions for false negative GBS cases and calculated a ranked sum for each algorithm's performance. Results: We found that 40 patients out of 211 had a true case of GBS. Algorithm 17, a GBS diagnosis in the primary position of an inpatient claim and a diagnostic procedure within 45 days of the inpatient admission date, had the highest PPV (PPV = 81.6%, 95% CI (69.3, 93.9). Across three prevalence assumptions, Algorithm 15, a GBS diagnosis in the primary position of an inpatient claim, was favored (PPV = 79.5%, 95% CI (67.6, 91.5). Conclusions: Our findings demonstrate that patients with incident GBS can be accurately identified in Medicare claims with a chart-validated algorithm. Using large-scale administrative data to study GBS offers significant advantages over case reports and patient repositories with self-reported data, and may be a potential strategy for the study of other rare diseases.

Barriers to Implementing Registered Nurse-Driven Clinical Decision Support for Antibiotic Stewardship: Retrospective Case Study.

BACKGROUND: Up to 50% of antibiotic prescriptions for upper respiratory infections (URIs) are inappropriate. Clinical decision support (CDS) systems to mitigate unnecessary antibiotic prescriptions have been implemented into electronic health records, but their use by providers has been limited. OBJECTIVE: As a delegation protocol, we adapted a validated electronic health record-integrated clinical prediction rule (iCPR) CDS-based intervention for registered nurses (RNs), consisting of triage to identify patients with low-acuity URI followed by CDS-guided RN visits. It was implemented in February 2022 as a randomized controlled stepped-wedge trial in 43 primary and urgent care practices within 4 academic health systems in New York, Wisconsin, and Utah. While issues were pragmatically addressed as they arose, a systematic assessment of the barriers to implementation is needed to better understand and address these barriers. METHODS: We performed a retrospective case study, collecting quantitative and qualitative data regarding clinical workflows and triage-template use from expert interviews, study surveys, routine check-ins with practice personnel, and chart reviews over the first year of implementation of the iCPR intervention. Guided by the updated CFIR (Consolidated Framework for Implementation Research), we characterized the initial barriers to implementing a URI iCPR intervention for RNs in ambulatory care. CFIR constructs were coded as missing, neutral, weak, or strong implementation factors. RESULTS: Barriers were identified within all implementation domains. The strongest barriers were found in the outer setting, with those factors trickling down to impact the inner setting. Local conditions driven by COVID-19 served as one of the strongest barriers, impacting attitudes among practice staff and ultimately contributing to a work infrastructure characterized by staff changes, RN shortages and turnover, and competing responsibilities. Policies and laws regarding scope of practice of RNs varied by state and institutional application of those laws, with some allowing more clinical autonomy for RNs. This necessitated different study procedures at each study site to meet practice requirements, increasing innovation complexity. Similarly, institutional policies led to varying levels of compatibility with existing triage, rooming, and documentation workflows. These workflow conflicts were compounded by limited available resources, as well as an implementation climate of optional participation, few participation incentives, and thus low relative priority compared to other clinical duties. CONCLUSIONS: Both between and within health care systems, significant variability existed in workflows for patient intake and triage. Even in a relatively straightforward clinical workflow, workflow and cultural differences appreciably impacted intervention adoption. Takeaways from this study can be applied to other RN delegation protocol implementations of new and innovative CDS tools within existing workflows to support integration and improve uptake. When implementing a system-wide clinical care intervention, considerations must be made for variability in culture and workflows at the state, health system, practice, and individual levels. TRIAL REGISTRATION: ClinicalTrials.gov NCT04255303; https://clinicaltrials.gov/ct2/show/NCT04255303.

Effectiveness of standard treatments in non-small-cell lung cancer with METexon14 skipping mutation: a real-world study.

Aim: To assess real-world clinical outcomes with standard therapies for advanced non-small-cell lung cancer (aNSCLC) with METexon14 skipping mutation (METex14).Methods: In an oncologists-led retrospective review of medical records, data were abstracted and analyzed for patients initiating first-line (1L) systemic therapy after 1 January 2017.Results: In total 287 aNSCLC patients with METex14, the real-world best overall response rate was 73.4% for capmatinib (n = 146), 68.8% for immunotherapy (IO) monotherapy (n = 48), 52.0% for chemotherapy (CT, n = 30), and 54.8% for IO + CT (n = 63). As compared with capmatinib, patients receiving IO (hazard ratio [HR]: 1.57; 95% CI: 0.77-3.20; p = 0.220), CT (HR: 2.41; 95% CI: 1.19-4.85; p = 0.014) and IO + CT (HR: 2.33; 95% CI: 1.35-4.04; p = 0.003) had higher rates of progression. Further, patients receiving CT (HR: 4.43; 95% CI: 1.54-12.75; p = 0.006) and IO + CT (HR: 3.53, 95% CI: 1.41-8.85; p = 0.007) had higher rates of mortality than patients receiving capmatinib.Conclusion: The study showed better clinical outcomes with capmatinib than other standard therapies in 1L setting for aNSCLC harboring METex14.

Real-world study that investigated the outcomes of different therapies used to treat non-small-cell lung cancer patients with mesenchymal-epithelial transition exon 14 skipping mutationWhat is this article about? A real-world study that investigated clinical outcomes in patients with diagnosis of advanced non-small-cell lung cancer (aNSCLC) with mesenchymal-epithelial transition exon 14 (METex14) skipping­a rare form of genetic mutation­who received treatment with one of the commonly used therapies for this disease: immunotherapy, chemotherapy, immunotherapy + chemotherapy combination and capmatinib, which is a highly selective inhibitor of MET tyrosine kinase protein involved in the growth of cancer cells.What were the results? The study showed that, in general, patients treated with capmatinib as the frontline therapy more frequently achieved a clinical response in the form of complete tumor resolution or tumor shrinkage, had a lower risk of disease worsening and lived longer than patients who were treated with immunotherapy, chemotherapy or immunotherapy + chemotherapy combination.What do the results of the study mean? This study suggests that capmatinib is effective in treating patients with aNSCLC with METex14 skipping who have not been treated with another anticancer therapy previously. It provides evidence to support the use of capmatinib in the frontline setting and may inform clinical decision-making in routine practice.

Achieving high inter-rater reliability in establishing data labels: a retrospective chart review study.

BACKGROUND: In medical research, the effectiveness of machine learning algorithms depends heavily on the accuracy of labeled data. This study aimed to assess inter-rater reliability (IRR) in a retrospective electronic medical chart review to create high quality labeled data on comorbidities and adverse events (AEs). METHODS: Six registered nurses with diverse clinical backgrounds reviewed patient charts, extracted data on 20 predefined comorbidities and 18 AEs. All reviewers underwent four iterative rounds of training aimed to enhance accuracy and foster consensus. Periodic monitoring was conducted at the beginning, middle, and end of the testing phase to ensure data quality. Weighted Kappa coefficients were calculated with their associated 95% confidence intervals (CIs). RESULTS: Seventy patient charts were reviewed. The overall agreement, measured by Conger's Kappa, was 0.80 (95% CI: 0.78-0.82). IRR scores remained consistently high (ranging from 0.70 to 0.87) throughout each phase. CONCLUSION: Our study suggests the detailed manual for chart review and structured training regimen resulted in a consistently high level of agreement among our reviewers during the chart review process. This establishes a robust foundation for generating high-quality labeled data, thereby enhancing the potential for developing accurate machine learning algorithms.

Mental health practices in rehabilitation for youth with physical disabilities: a chart review study.

PURPOSE: Evidence on co-occurring mental health problems in youth with physical disabilities is growing, however how services are provided remains unclear. This study examined current interprofessional rehabilitation practices for physical and mental health services. METHODS: Youth (aged 15-24) followed for a physical disability that had mental health problems were identified. Chart reviews were used to identify practices. Mental health-related diagnoses/symptoms, assessments, goals, interventions, and referrals were extracted for inductive content analysis. RESULTS: Sixty charts were reviewed. Mental health problems included anxiety (n = 53), depression (n = 25), neurodevelopmental (n = 19) and personality disorders (n = 8), often (n = 36) citing more than one. No mental health assessments were found, and in 43%, no goals or interventions were evident. Relevant goals (n = 98) targeted emotional management, autonomy/communication of needs, acceptance of physical condition, socialization, routines/energy levels, school/work supports, and leisure/calming environments. Interventions (n = 104) included emotional management, formal individual/group therapy, links with external supports, routines/activities, reflection/acceptance, and school/work support. Mental health services were received in-house (n = 24) and/or externally (n = 30), plus 18 referrals pending and 14 not referred. CONCLUSION: Many had more than one mental health problem, suggesting the complexity of their condition. While some mental health goals/interventions are documented, problems may often not be reported or addressed in this context.

Further attention can be directed to the needs of youth with physical disabilities and co-occurring mental health problems as they are not fully addressed by current interdisciplinary rehabilitation practices.Follow-up (services and referrals) should be adapted to the holistic needs of youth and their goals within the rehabilitation context.Rehabilitation professionals can be provided with training to build workforce capacity in mental health screening and have access to guidance when addressing situations related to mental health or referring to external services.

Patterns and Characteristics of Diabetic Ketoacidosis in Children With Type I Diabetes in Saudi Arabia.

BACKGROUND: Type 1 diabetes mellitus (T1DM) in children, a significant public health concern, often leads to diabetic ketoacidosis (DKA). The prevalence of T1DM is increasing globally, with Saudi Arabia recording high rates of DKA at T1DM onset. This study aimed to evaluate the characteristics and risk factors of pediatric T1DM patients presenting with DKA in the emergency room in Saudi Arabia and quantify intensive care unit (ICU) admission incidences reflecting DKA severity. METHODS: This retrospective chart review, conducted at Medina Maternity and Children's Hospital, Saudi Arabia, analyzed data from 2017 to 2022. The study included children and adolescents under 18 presenting with DKA, using non-probability consecutive sampling. Patient medical records provided demographic, medical, and laboratory data, and the analysis employed SPSS for statistical assessment. RESULTS: The study enrolled 70 participants, predominantly female (n = 42, 60%) and Saudi nationals (n = 63, 90%). The average age at diabetes mellitus (DM) onset was 6.9 years, with a mean hospital stay of 3.31 days. About 18.57% (n = 13) were newly diagnosed with DM, and 81.43% (n = 57) were known cases of DM. Most participants (n = 59, 86.8%) had no comorbidities, while 7.4% (n = 5) had celiac disease. The recovery rate was high (n = 67, 95.7%), with 80% (n = 56) experiencing no complications. Notably, 44.3% (n = 31) were admitted to a ward, and 12.9% (n = 9) required ICU admission. Weight was found to be a significant predictor of ICU admission (OR = 1.26, 95% CI: 1.05 to 1.5; p = 0.011). CONCLUSIONS: This study highlights the importance of personalized insulin therapy and weight management in pediatric T1DM patients presenting with DKA. It suggests that early and effective management in emergency settings can significantly improve patient outcomes. The study also calls for further research into long-term management strategies and the impact of targeted educational programs.

A scoping review of the methodological approaches used in retrospective chart reviews to validate adverse event rates in administrative data.

Patient safety is a key quality issue for health systems. Healthcare acquired adverse events (AEs) compromise safety and quality; therefore, their reporting and monitoring is a patient safety priority. Although administrative datasets are potentially efficient tools for monitoring rates of AEs, concerns remain over the accuracy of their data. Chart review validation studies are required to explore the potential of administrative data to inform research and health policy. This review aims to present an overview of the methodological approaches and strategies used to validate rates of AEs in administrative data through chart review. This review was conducted in line with the Joanna Briggs Institute methodological framework for scoping reviews. Through database searches, 1054 sources were identified, imported into Covidence, and screened against the inclusion criteria. Articles that validated rates of AEs in administrative data through chart review were included. Data were extracted, exported to Microsoft Excel, arranged into a charting table, and presented in a tabular and descriptive format. Fifty-six studies were included. Most sources reported on surgical AEs; however, other medical specialties were also explored. Chart reviews were used in all studies; however, few agreed on terminology for the study design. Various methodological approaches and sampling strategies were used. Some studies used the Global Trigger Tool, a two-stage chart review method, whilst others used alternative single-, two-stage, or unclear approaches. The sources used samples of flagged charts (n = 24), flagged and random charts (n = 11), and random charts (n = 21). Most studies reported poor or moderate accuracy of AE rates. Some studies reported good accuracy of AE recording which highlights the potential of using administrative data for research purposes. This review highlights the potential for administrative data to provide information on AE rates and improve patient safety and healthcare quality. Nonetheless, further work is warranted to ensure that administrative data are accurate. The variation of methodological approaches taken, and sampling techniques used demonstrate a lack of consensus on best practice; therefore, further clarity and consensus are necessary to develop a more systematic approach to chart reviewing.