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Background: Covid-19 pandemic highlighted the need for implementing Personal Electronic Health Records (PEHR) for patients' data management. Furthermore, this pandemic underscored the relevance for integrated and interoperable Electronic Health Records (EHR) to support disease surveillance, hospital capacity planning and resource management (Peek N, Sujan M, Scott P (2020) Digital health and care in pandemic times: impact of COVID-19. BMJ Health Care Inf 27(1):e100166. https://doi.org/10.1136/bmjhci-2020-100166). Due to the lack of comprehensive patients' record in plastic, reconstructive and aesthetic surgery, Axon's myHealth app offers a break-through patient-centric design allowing patients to be in control of their records and updating them in real-time for their plastic and aesthetic care providers to have a clearer understanding of patients' history and progress from pre-op to post-op. Methods: The Axon Dublin survey took place during Covid-19 pandemic in two phases: Phase 1 aimed to assess the feasibility of patients integrating the Axon myHealth application into their clinical visits. Testing occurred in a clinical environment, where patients were encouraged to download and use the Axon system with a health practitioner (HP) present. Phase 2 focused on home testing, evaluating patients' willingness to manage their health remotely with HP assistance. This phase included self-testing activities such as performing rapid Covid-19 antigen tests, recording medical history, and measuring blood pressure at home. Results: The Axon Dublin Study aimed to assess patient engagement, clinical impact, and cost-effectiveness of the Axon myHealth application. Over 85% of patients showed interest in owning a Personal Electronic Health Record. Notably, 36% continuously monitored chronic conditions. Clinical decisions, informed by patient data, saw 61.9% compliance. Noteworthy, 23% of hypertensive participants required immediate medication changes. Patient self-capture of data reduced consultation time. Public health implications were significant, with 39% vaccinated and 31% reporting complications. High user satisfaction (97%) demonstrated the app's effectiveness in infection control and chronic care. Conclusions: Offering patients the ability to update and control their data is a growing interest, with a clear need in plastic and aesthetic surgery to have a better understanding of a patient's medical past and progress throughout the surgical process and period. This platform, which is time and cost efficient, can only facilitate personalised care and improve outcomes while maintaining patient's confidentiality. Level of evidence: Not gradable. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things with the Cloud improves our lives by facilitating smooth connections between people and items. Predictive analytics, fueled by cutting-edge machine learning and artificial intelligence, turns reactive healthcare initiatives into proactive ones. A subset of machine learning called deep learning is essential for quickly analyzing large datasets, producing insightful conclusions, and efficiently addressing challenging problems. For early interventions and preventive care, especially for those who are at risk, accurate and timely illness prediction is crucial. Making accurate prediction models becomes crucial when utilizing electronic medical records. Accuracy is improved by using deep learning variations of recurrent neural networks that can handle sequential time-series data. Predictive analytics is applied to cloud-stored electronic medical records and data from Internet of Things devices in this suggested system. With a remarkable accuracy of 98.86%, the smart healthcare system is intended to monitor and anticipate the risk of heart disease utilizing Bi-LSTM (bidirectional long short-term memory). Furthermore, it reaches 98.9% accuracy, 98.8% sensitivity, 98.89% specificity, and 98.86% F-measure. These outcomes greatly surpass the performance of current smart heart disease prediction systems. [ABSTRACT FROM AUTHOR]

In certain cloud Electronic Medical Records (EMRs) applications, the data ownership may need to be transferred. In practice, not only the data but also the auditing ability should be transferred securely and efficiently. However, we investigate and find that most of the existing data ownership transfer protocols only work well between two individuals, and they become inefficient when dealing between two communities. The proposals for transferring tags between communities are problematic as well since, they require all members get involved or a fully trusted aggregator facilitates ownership transfer, which are unrealistic in certain scenarios. To alleviate these problems, in this paper we develop a secure auditing protocol with decentralized (t, n)-threshold ownership transfer for cloud EMRs. This protocol is designed to operate efficiently without requiring the mandatory participation of every user or the involvement of any trusted third-party. It is achieved by employing the threshold signature. Rigorous security analyses and comprehensive performance evaluations illustrate the security and practicality of our protocol. Specifically, according to the evaluations and comparisons, the communication and computational consumption is independent of the file size, i.e., it is constant in our protocol for both communities. [ABSTRACT FROM AUTHOR]

Pompe disease (OMIM #232300), a rare genetic disorder, leads to glycogen buildup in the body due to an enzyme deficiency, particularly harming the heart and muscles. Infantile-onset Pompe disease (IOPD) requires urgent treatment to prevent mortality, but the unavailability of these methods often delays diagnosis. Our study aims to streamline IOPD diagnosis in the UAE using electronic health records (EHRs) for faster, more accurate detection and timely treatment initiation. This study utilized electronic health records from the Abu Dhabi Healthcare Company (SEHA) healthcare network in the UAE to develop an expert rule-based screening approach operationalized through a dashboard. The study encompassed six diagnosed IOPD patients and screened 93,365 subjects. Expert rules were formulated to identify potential high-risk IOPD patients based on their age, particular symptoms, and creatine kinase levels. The proposed approach was evaluated using accuracy, sensitivity, and specificity. The proposed approach accurately identified five true positives, one false negative, and four false positive IOPD cases. The false negative case involved a patient with both Pompe disease and congenital heart disease. The focus on CHD led to the overlooking of Pompe disease, exacerbated by no measurement of creatine kinase. The false positive cases were diagnosed with Mitochondrial DNA depletion syndrome 12-A (SLC25A4 gene), Immunodeficiency-71 (ARPC1B mutation), Niemann–Pick disease type C (NPC1 gene mutation leading to frameshift), and Group B Streptococcus meningitis. The proposed approach of integrating expert rules with a dashboard facilitated efficient data visualization and automated patient screening, which aids in the early detection of Pompe disease. Future studies are encouraged to investigate the application of machine learning methodologies to enhance further the precision and efficiency of identifying patients with IOPD. [ABSTRACT FROM AUTHOR]

Background: Cancer is a complex disease, caused and impacted by a combination of genetic, demographic, clinical, environmental and lifestyle factors. Analysis of cancer characteristics, risk factors, treatment options and the heterogeneity across cancer types has been the focus of medical research for years. The aim of this study is to describe and summarise genetic, clinicopathological, behavioural and demographic characteristics and their differences across ten common cancer types and evaluate their impact on overall survival outcomes. Methods: This study included data from 9977 patients with bladder, breast, colorectal, endometrial, glioma, leukaemia, lung, ovarian, prostate, and renal cancers. Genetic data collected through the 100,000 Genomes Project was linked with clinical and demographic data provided by the National Cancer Registration and Analysis Service (NCRAS), Hospital Episode Statistics (HES) and Office for National Statistics (ONS). Descriptive and Kaplan Meier survival analyses were performed to visualise similarities and differences across cancer types. Cox proportional hazards regression models were applied to identify statistically significant prognostic factor associations with overall survival. Results: 161 clinical and 124 genetic factors were evaluated for prognostic association with overall survival. Of these, 116 unique factors were found to have significant prognostic effect for overall survival across ten cancer types when adjusted for age, sex and stage. The findings confirmed prognostic associations with overall survival identified in previous studies in factors such as multimorbidity, tumour mutational burden, and mutations in genes BRAF, CDH1, NF1, NRAS, PIK3CA, PTEN, TP53. The results also identified new prognostic associations with overall survival in factors such as mental health conditions, female health-related conditions, previous hospital encounters and mutations in genes FANCE, FBXW7, GATA3, MSH6, PTPN11, RB1, RNF43. Conclusion: This study provides a comprehensive view of clinicopathological and genetic prognostic factors across different cancer types and draws attention to less commonly known factors which might help produce more precise prognosis and survival estimates. The results from this study contribute to the understanding of cancer disease and could be used by researchers to develop complex prognostic models, which in turn could help predict cancer prognosis more accurately and improve patient outcomes. [ABSTRACT FROM AUTHOR]

We compared the risks and benefits of COVID-19 vaccines using a causal pathway analysis to weigh up possible risk factors of thromboembolic events post-vaccination. The self-controlled case series (SCCS) method examined the association between thromboembolic events and vaccination while a case-control study assessed the association between thromboembolic events and COVID-19, addressing under-reported infection data issues. The net vaccine effect was estimated using results from SCCS and case-control studies. We used electronic health record data from Corewell Health (16,640 subjects in SCCS and 106,143 in case-control). We found increased risks of thromboembolic events post-vaccination (incidence rate ratio: 1.19, 95% CI: [1.08, 1.31] after the first dose; 1.22, 95% CI: [1.11, 1.34] after the second dose). Vaccination attenuated infection-associated thromboembolic risks (odds ratio: 4.65, 95% CI: [4.18, 5.17] in unvaccinated vs 2.77, 95% CI: [2.40, 3.24] in vaccinated). After accounting for vaccine efficacy and protection against infection-associated thromboembolic events, vaccination decreases thromboembolic event risk, especially during high infection rate periods. [ABSTRACT FROM AUTHOR]

Background: Atherosclerotic Cardiovascular Disease (ASCVD) is a global public health concern. This study aimed to estimate the healthcare resource utilization (HRU) and costs stratified by cardiovascular disease (CVD) risk categories using real-world evidence, in a regional population in Portugal. Methods: This is a retrospective observational study, using data from Electronic Health Records between 2017 and 2021. Patients aged ≥ 40 years, and with at least one general practitioner (GP) appointment in the 3 years before 31st of December 2019, were included. CVD risk categories were determined based on 2021 ESC prevention guidelines. HRU encompassed hospital data (hospitalizations, outpatient and emergency room visits) and GP appointments. Total direct costs per patient were calculated based on the reference cost of the Portuguese legislation for payment methodology on Diagnosis-Related Groups (DRGs). Results: Analysis of 3 122 695 episodes, revealed consistent HRU and costs across the five years. Very high-risk patients, showed higher HRU, particularly in hospital admissions. Costs tended to rise with higher CVD risk level. Very high-risk patients with ASCVD had higher costs for hospital admissions, while low-to-moderate risk patients had higher costs for GP visits. Despite a smaller proportion, very high-risk patients with prior ASCVD represent the highest costs per patient across healthcare settings (from 115€ in emergency visits to 2 673€ in hospitalizations), followed by very high-risk patients without prior ASCVD (ASCVD-risk equivalents). Conclusion: This study revealed a substantial HRU and costs by patients with very high CVD risk, particularly those with prior ASCVD. Moreover, ASCVD-risk equivalents emerge as notable consumers, emphasizing the importance of risk assessment and preventive measures in cost-effective management of these patients. [ABSTRACT FROM AUTHOR]

Background: The utilization of genomic information to improve health outcomes is progressively becoming more common in clinical practice. Nonetheless, disparities persist in accessing genetic services among ethnic minorities, individuals with low socioeconomic status, and other vulnerable populations. The Rio Grande Valley (RGV) at the Texas-Mexico border is predominantly Hispanic/Latino with a high poverty rate and very limited access to genetic services. Funded by the National Center for Advancing Translational Sciences, Project GIVE (Genetic Inclusion by Virtual Evaluation) was launched in 2022 to reduce the time to diagnosis and increase provider knowledge of genomics in this region, with the goal of improving pediatric health outcomes. We describe our experience of establishing a virtual pediatric genomic service in this region to expeditiously identify, recruit, and evaluate pediatric patients with undiagnosed diseases. Methods: We have utilized an innovative electronic health record (EHR) agnostic virtual telehealth and educational platform called Consultagene to receive referrals from healthcare providers in the RGV. Using this portal, genetic services, including virtual evaluation and genome sequencing (GS), are being delivered to children with rare diseases. The study has also integrated effective methods to involve and educate community providers through in-person meetings and Continuing Professional Education (CPE) events. Results: The recruitment efforts have proven highly successful with the utilization of Consultagene in this medically underserved region. The project's ongoing engagement efforts with local healthcare providers have resulted in progressively more referrals to the study over time, thus improving inclusion and access to genomic care in the RGV. Additionally, the curated CPE content has been well received by healthcare providers in the region. Conclusions: Project GIVE study has allowed advanced genetic evaluation and delivery of GS through the virtual Consultagene portal, effectively circumventing the recognized socioeconomic and logistical barriers to accessing genetic services within this border community. [ABSTRACT FROM AUTHOR]

Transferring and replicating predictive algorithms across healthcare systems constitutes a unique yet crucial challenge that needs to be addressed to enable the widespread adoption of machine learning in healthcare. In this study, we explored the impact of important differences across healthcare systems and the associated Electronic Health Records (EHRs) on machine-learning algorithms to predict mental health crises, up to 28 days in advance. We evaluated both the transferability and replicability of such machine learning models, and for this purpose, we trained six models using features and methods developed on EHR data from the Birmingham and Solihull Mental Health NHS Foundation Trust in the UK. These machine learning models were then used to predict the mental health crises of 2907 patients seen at the Rush University System for Health in the US between 2018 and 2020. The best one was trained on a combination of US-specific structured features and frequency features from anonymized patient notes and achieved an AUROC of 0.837. A model with comparable performance, originally trained using UK structured data, was transferred and then tuned using US data, achieving an AUROC of 0.826. Our findings establish the feasibility of transferring and replicating machine learning models to predict mental health crises across diverse hospital systems. [ABSTRACT FROM AUTHOR]

Objective: To develop and validate tools for measuring inpatient gastroenterology (GI) consultation quality on oncologic patients. Methods: A total of 145 inpatient GI consults were analyzed using electronic health records in this cross-sectional study. Essential Consult Elements on oncologic-hospitalized patients (EE-COH) and Hospitalized Oncologic Patients Enhanced Quality of Consult Assessment Tool (HOPE-QCAT) were used for grading. Interrater reliability was assessed. Results: Both EE-COH and HOPE-QCAT showed near-perfect interrater reliability across most measures in the validation cohort. On application of these measures for quality assessment, basic evaluation by the requesting hospitalist was partially complete in 24.8%, the request for GI consultation was inappropriate in 18.6%, while the rationale for recommended studies from the GI consultant was provided in 55.7% of cases suggesting key areas for quality improvement. Conclusion: We developed highly reliable quality measures for inpatient GI consults on oncology patients. The EE-COH and HOPE-QCAT tools can be utilized in future studies of inpatient GI consult quality and to form the basis for interventions to improve communication between consultants and hospitalists. Such tools could be adapted for inpatient quality assessment across other specialties and settings. [ABSTRACT FROM AUTHOR]

Purpose: To report the rate of fusion in a sample of patients undergoing lumbar fusion surgery and assess interrater reliability of computed tomography (CT)-based parameters for the assessment of fusion. Methods: All adult patients who underwent lumbar fusion surgery from 2017 to 2021 were retrospectively identified. Patient demographics and surgical characteristics were collected through chart review of the electronic medical records. CT scans were reviewed independently by two attending spine surgeons and two spine fellows. Fusion was defined as evidence of bone bridging in any one of (1) posterolateral gutters, (2) facets, or (3) interbody (when applicable) on any CT views. Evidence of screw haloing was indicative of nonunion. Interrater reliability was determined using cohen's kappa. Afterwards, a consensus agreement for each component of fusion was reached between participants. Results: The overall fusion rate among all procedures was 63/69 (91.3%). Overall 22/25 (88.0%) TLIF, 16/19 (84.2%) PLDF, 3/3 (100%) LLIF, and 22/22 (100%) circumferential fusions experienced a successful fusion. Interrater reliability was good for interbody fusion (k = 0.734) and moderate for all other measures (k = 0.561 for posterolateral fusion; k = 0.471 for facet fusion; k = 0.458 for screw haloing). Overall, interrater reliability as to whether a patient had a fusion or nonunion was moderate (k = 0.510). Conclusion: There was only moderate interrater reliability across most radiographic measures used in assessing lumbar fusion status. Reliability was highest when evaluating the presence of interbody fusion. The majority of fusions occurred across the facet joints. [ABSTRACT FROM AUTHOR]

Aims: Glargine 300 U/mL (Gla-300) has been recently approved for use in children and adolescents with type 1 diabetes (T1D). However, real-world effectiveness data are scarce, and aim of this analysis was to assess clinical outcomes in young patients with T1D switching from 1st generation basal insulin (1BI) to Gla-300. Methods: ISPED CARD is a retrospective, multicenter study, based on data anonymously extracted from Electronic Medical Records. The study involved a network of 20 pediatric diabetes centers. Data on all patients aged < 18 years with T1D switching from 1BI to Gla-300 were analyzed to assess clinical characteristics at the switch and changes after 6 and 12 months in glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and standardized body mass index (BMI/SDS). Titration of basal and short-acting insulin doses was also evaluated. Results: Overall, 200 patients were identified. The mean age at the switch to Gla-300 was 13 years, and mean duration of diabetes was 3.9 years. Average HbA1c levels at switch were 8.8%. After 6 months, HbA1c levels decreased by − 0.88% (95% CI − 1.28; − 0.48; p < 0.0001). The benefit was maintained after 12 months from the switch (mean reduction of HbA1c levels − 0.80%, 95% CI − 1.25; − 0.35, p = 0.0006). Trends of reduction in FBG levels were also evidenced both at 6 months and 12 months. No significant changes in short-acting and basal insulin doses were documented. Conclusions: The study provides the first real-world evidence of the effectiveness of Gla-300 in children and adolescents with T1D previously treated with 1BI. The benefits in terms of HbA1c levels reduction were substantial, and sustained after 12 months. Additional benefits can be expected by improving the titration of insulin doses. [ABSTRACT FROM AUTHOR]

Purpose: Hydroxychloroquine is currently recommended for the treatment of systemic lupus erythematosus (SLE), but it can cause irreversible retinal toxicity. This study aimed to identify factors associated with early hydroxychloroquine-induced retinal toxicity in patients with SLE from a single centre for 20 years. Methods: SLE patients diagnosed between 1998 and 2017 and followed up for at least 1 year were included. Demographic, clinical, laboratory and therapeutic data were collected from the electronic medical records and retrospectively analysed. Early hydroxychloroquine-induced retinal toxicity was defined as the development of macular toxicity within the first 5 years of hydroxychloroquine treatment. Results: A total of 345 patients followed for a median of 15 years were analysed; 337 (97.7%) patients received hydroxychloroquine, 38 (11.3%) of them presented with retinal toxicity, and 10 (3%) developed early retinal toxicity. These patients had a mean treatment duration of 3.3 years with a mean cumulative dose of 241 g. Patients were diagnosed by visual field (VF) and fundoscopy, and two were also assessed using spectral domain optical coherence tomography (SD-OCT). The median (IQR) age of patients with early toxicity was 56 (51–66) years, and 80% were female. Factors independently associated with early hydroxychloroquine-induced retinal toxicity were lupus anticoagulant positivity (OR 4.2; 95% CI 1.2–15.5) and hypercholesterolaemia (OR 5.6; 95% CI 1.5–21.5). Conclusion: Our results suggest that lupus anticoagulant positivity and hypercholesterolaemia among SLE patients may be risk factors for early hydroxychloroquine-induced retinal toxicity, regardless of the dose or duration of treatment. [ABSTRACT FROM AUTHOR]

Today, the confidentiality and security of patient medical records is of great importance. This study proposes a scheme that aims to store, access, and share medical data without risking security vulnerabilities and attacks. In the proposed scheme, medical data are divided into sensitive and non-sensitive patient data. Three consensus mechanisms (Proof of Work (PoW), Proof of Stake (PoS), and Proof of Authority (PoA)) are implemented and compared to each other in terms of performance. The performance analysis of the proposed scheme shows that PoW provides approximately 21% and 9% better results than PoA and PoS for non-sensitive data in terms of block size, respectively. It also provides approximately 23% and 32% better results than PoA and PoS for sensitive data in terms of memory usage, respectively. The security analysis demonstrates that it has many security features and is strong against man-in-the-middle, impersonation, and modification attacks. [ABSTRACT FROM AUTHOR]

The eHealth sector has witnessed significant growth due to technological advancements, facilitating care delivery in patients' homes and moving away from traditional hospital settings. Blockchain and the Internet of Things (IoT) play pivotal roles in enhancing healthcare services, offering features such as remote patient monitoring, streamlined electronic medical record (EMR) management, drug traceability, and effective disease control, particularly during events like the COVID-19 pandemic. The growing utilization of IoT devices brings about security challenges, including concerns related to data integrity and device authentication. This paper proposes the integration of blockchain technology as a robust solution. Leveraging its decentralized and tamper-resistant features, blockchain establishes trust among diverse IoT devices, ensuring the integrity of IoT data. Additionally, smart contracts enhance device authentication, fortifying overall security by addressing vulnerabilities associated with centralization. Regarding the management of eHealth, this survey begins with an overview of the industry, highlighting IoT-related challenges in healthcare. It explores various IoT applications in eHealth and discusses how blockchain can effectively address obstacles in healthcare management through IoT. Notably, the paper provides insights into examining consensus algorithm parameters within blockchain systems, clarifying the methodology used to assess and optimize these critical components. The survey extends to a thorough review of existing research on integrating blockchain-based IoT in eHealth. Finally, it presents an overview of challenges and potential solutions for implementing blockchain-based IoT in the eHealth sector. This comprehensive survey aims to empower stakeholders by providing insights to enhance patient care in this dynamic and evolving field. [ABSTRACT FROM AUTHOR]

Introduction: Guidelines recommend that patients with acute venous thromboembolism (VTE) represented by low-risk deep vein thrombosis (DVT) and pulmonary embolism (PE) receive initial treatment at home versus at the hospital, but a large percentage of these patients are not managed at home. This study assessed the effectiveness of a quality intervention on provider knowledge and confidence in evaluating outpatient treatment for patients with VTE in the emergency department (ED). Methods: A pilot program to overcome obstacles to outpatient VTE treatment in appropriate patients was initiated at Baylor Scott & White Health Temple ED. Subsequently, a formalized quality intervention with a targeted educational program was developed and delivered to ED providers. Provider surveys were administered pre- and post-quality intervention in order to assess clinical knowledge, confidence levels, and perceived barriers. Patient discharge information was extracted from electronic health records. Results: Twenty-five ED providers completed the pre- and post-surveys; 690 and 356 patients with VTE were included in the pre- and post-pilot and pre- and post-quality intervention periods, respectively. Many ED providers reported that a major barrier to discharging patients to outpatient care was the lack of available and adequate patient follow-up appointments. Notably, after the quality intervention, an increase in provider clinical knowledge and confidence scores was observed. Discharge rates for patients with VTE increased from 25.6% to 27.5% after the pilot intervention and increased from 28.5% to 29.9% after the quality intervention, but these differences were not statistically significant. Despite instantaneous uptick in discharge rates after the interventions, there was not a long-lasting effect. Conclusion: Although the quality intervention led to improvements in provider clinical knowledge and confidence and identified barriers to discharging patients with VTE, discharge rates remained stable, underscoring the need for additional endeavors. Plain Language Summary: When patients develop blood clots in their veins or have blood clots travel to their lungs, they may seek treatment at the hospital emergency department. As a best practice, most people can treat blood clots with medicines at home; however, many patients are treated at the hospital. This study looked at how an education program for doctors in the hospital could help more patients be treated at home. The education program improved doctors' knowledge and confidence when evaluating patients with blood clots who could be treated at home. However, this study found that the number of patients treated at home was the same before and after the doctors participated in the education program. Two major problems that prevented patients from being treated at home were not having follow-up appointments readily available and patients taking their medicine as needed. More and different types of programs may help doctors understand the best ways to treat patients with blood clots in the emergency department. [ABSTRACT FROM AUTHOR]

Background: Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC. Objective: To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA). Design: Observational study using item response theory (IRT) and differential item functioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment. Patients: Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15–8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist. Main measure: The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only). Key Results: Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0–11) patients endorse. Conclusions: The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT. [ABSTRACT FROM AUTHOR]

Background: Primary care providers (PCPs) are often the first point of contact for discussing lung cancer screening (LCS) with patients. While guidelines recommend against screening people with limited life expectancy (LLE) who are less likely to benefit, these patients are regularly referred for LCS. Objective: We sought to understand barriers PCPs face to incorporating life expectancy into LCS decision-making for patients who otherwise meet eligibility criteria, and how a hypothetical point-of-care tool could support patient selection. Design: Qualitative study based on semi-structured telephone interviews. Participants: Thirty-one PCPs who refer patients for LCS, from six Veterans Health Administration facilities. Approach: We thematically analyzed interviews to understand how PCPs incorporated life expectancy into LCS decision-making and PCPs' receptivity to a point-of-care tool to support patient selection. Final themes were organized according to the Cabana et al. framework Why Don't Physicians Follow Clinical Practice Guidelines, capturing the influence of clinician knowledge, attitudes, and behavior on LCS appropriateness determinations. Key Results: PCP referrals to LCS for patients with LLE were influenced by limited knowledge of the life expectancy threshold at which patients are less likely to benefit from LCS, discomfort estimating life expectancy, fear of missing cancer at the point of early detection, and prioritization of factors such as quality of life, patient values, clinician-patient relationship, and family support. PCPs were receptive to a decision support tool to inform and communicate LCS appropriateness decisions if easy to use and integrated into clinical workflows. Conclusions: Our study suggests knowledge gaps and attitudes may drive decisions to offer screening despite LLE, a behavior counter to guideline recommendations. Integrating a LCS decision support tool that incorporates life expectancy within the electronic medical record and existing clinical workflows may be one acceptable solution to improve guideline concordance and increase confidence in selecting high benefit patients for LCS. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is an autoimmune disease with a variable course with unpredictable flares. Identifying predictors of these flares is essential for monitoring and timely hospital care. To characterize the prevalence of flares within the first five years of SLE diagnosis and determine the clinical and immunological characteristics associated with flare development among patients attending the Rheumatology Clinic at Tikur Anbesa Specialized Hospital (TASH) and Lancet General Hospital. A multicenter, cross-sectional study was conducted from May 2023 to November 2023 at TASH and Lancet General Hospital. The data was collected from electronic medical records and analyzed using SPSS version 26. Logistic regressions were used to determine factors associated with lupus flare. Most patients with SLE were female (95.4%). The most common clinical presentations were musculoskeletal (71.8%), cutaneous (55%), and constitutional (22%). Almost half (44.3%) of the patients had comorbidity illness. Positive ANA test was found in 96.5% of the patients, whereas only 55% had positive anti-dsDNA test. The prevalence of SLE flare in the first five years of SLE diagnosis was 38.9%, and most flares occurred within the first year of diagnosis. Patients with the following characteristics were more likely to have flare-ups: younger age at diagnosis (less than 25 years old), initial presentation with vasculitis, renal flare, and being on low-dose prednisolone. The most common clinical presentations were musculoskeletal, dermatologic, and constitutional manifestations. Age < 25 years at diagnosis, initial clinical presentation with renal manifestation, and being on low-dose prednisolone were predictors of SLE flare. Key Points • This study found a significant gender disparity, with 95% female. • Nearly 39% of patients experienced an SLE flare within the first five years of diagnosis. • Over three-quarters (77%) of flares occurred within the first year of diagnosis. • Age less than 25 years, initial presentation with vasculitis, renal involvement, and being on low-dose prednisolone were identified as predictors of flares. [ABSTRACT FROM AUTHOR]

Background: Excessive tension at the anastomosis contributes to anastomotic leakage (AL) in low anterior resection (LAR). However, the specific tension has not been measured. We assessed whether "Bridging," characterized by the proximal colon resembling a suspension bridge above the pelvic floor, is a significant risk factor for AL following LAR for rectal cancer. Methods: This retrospective study reviewed the medical records and laparoscopic videos of 102 patients who underwent laparoscopic LAR using the double stapling technique at Yachiyo Hospital between January 2014 and December 2023. Patients were classified based on whether they had Bridging (tight or sagging) or were in a Resting state of the proximal colon, and the association between Bridging and AL was examined. Results: AL occurred in 31.3% of the Tight Bridging group, 20% of the Sagging Bridging group, and 2.2% of the Resting group (P = 0.002). The incidence of AL was significantly higher in patients with Bridging than in those without (23.2% vs. 2.2%, P = 0.003). Multivariate analysis revealed that Bridging is an independent risk factor for AL (odds ratio = 6.97; 95% confidence interval: 1.45–33.6; P = 0.016). Conclusions: The presence of Bridging is a significant risk factor for AL following LAR for rectal cancer, suggesting the need for implementing preventive measures in patients with this condition. [ABSTRACT FROM AUTHOR]

Objective: This retrospective longitudinal study analyzed the demographic profile, insulin usage pattern, and outcomes of insulin-naive adults with type 2 diabetes mellitus (T2DM) who initiated insulin glargine. Methods: The study included 1006 insulin naive T2DM individuals aged ≥ 18 years, treated with any insulin type between January 2016 and December 2018, using electronic medical records. Results: Majority of participants were men (55.8%) with a mean age of 59.8 ± 11.9 years and average T2DM duration of 12.0 ± 6.6 years. Insulin glargine was the most commonly used insulin (66.9%), followed by insulin aspart (16.4%), insulin degludec (15.1%), human insulin (11.1%), and insulin isophane (9.2%). At baseline, the mean glycated hemoglobin (HbA1c) was 8.9 ± 1.9%, mean fasting plasma glucose (FPG) was 190 ± 59 mg/dL, and mean post-prandial plasma glucose (PPG) was 264 ± 78 mg/dL. In the insulin glargine group, baseline HbA1c was 9.0 ± 1.7%, FPG was 196 ± 62 mg/dL, and PPG was 283 ± 81 mg/dL. Throughout the study, there was an improvement in HbA1c, FPG, and PPG levels in the insulin glargine group. Body weight remained relatively stable, and the number of hypoglycemic events was minimal and non-life-threatening. Conclusion: The REALITY study in India demonstrated that initiating basal insulin treatment in insulin-naive individuals with T2DM led to improved glycemic parameters over a 12-month period. [ABSTRACT FROM AUTHOR]

Introduction: Discharge "against medical advice" (AMA) in the obstetric population is overall under-studied but disproportionally affects marginalized populations and is associated with worse perinatal outcomes. Reasons for discharges AMA are not well understood. The objective of this study is to identify the obstacles that prevent obstetric patients from accepting recommended care and highlight the structural reasons behind AMA discharges. Methods: Electronic health records of patients admitted to antepartum, peripartum, or postpartum services between 2008 and 2018 who left "AMA" were reviewed. Progress notes from clinicians and social workers were extracted and analyzed. Reasons behind discharge were categorized using qualitative thematic analysis. Results: Fifty-seven (0.12%) obstetric patients were discharged AMA. Reasons for discharge were organized into two overarching themes: extrinsic (50.9%) and intrinsic (40.4%) obstacles to accepting care. Eleven participants (19.3%) had no reason documented for their discharge. Extrinsic obstacles included childcare, familial responsibilities, and other obligations. Intrinsic obstacles included disagreement with provider regarding medical condition or plan, emotional distress, mistrust or discontent with care team, and substance use. Discussion: The term "AMA" casts blame on individual patients and fails to represent the systemic barriers to staying in care. Obstetric patients were found to encounter both extrinsic and intrinsic obstacles that led them to leave AMA. Healthcare providers and institutions can implement strategies that ameliorate structural barriers. Partnering with patients to prevent discharges AMA would improve maternal and infant health and progress towards reproductive justice. Significance: What is Already Known on this Subject?: Obstetric patients who leave "against medical advice (AMA)" have worse perinatal outcomes and often are from marginalized communities. The term, AMA, is also stigmatizing, placing blame on individual decision making rather than systemic barriers to access. Reasons for leaving AMA are not well understood in the obstetric population. What does this Study add?: We reframe the discussion around leaving AMA by describing obstacles in accepting care. Patients experienced both extrinsic and intrinsic obstacles to accepting medical care, from childcare issues to disagreement with treatment plan. Partnering with patients to overcome these obstacles would improve maternal and infant health and increase equity and reproductive justice. [ABSTRACT FROM AUTHOR]

Objective: Child neglect is a public health concern with negative consequences that impact children, families, and society. While neglect is involved with many pediatric hospitalizations, few studies explore characteristics associated with neglect types, social needs, and post-discharge care. Methods: Data on neglect type, sociodemographics, social needs, inpatient consultations, and post-discharge care were collected from the electronic medical record for children aged 0–5 years who were hospitalized with concern for neglect during 2016–2020. Frequencies and percentages were calculated to determine sample characteristics. The Chi-square Test for Independence was used to evaluate associations between neglect type and other variables. Results: The most common neglect types were inadequate nutrition (40%), inability to provide basic care (37%), intrauterine substance exposure (25%), combined types (23%), and inadequate medical care (10%). Common characteristics among neglect types included age less than 1 year, male sex, Hispanic ethnicity, public insurance, past involvement with Child Protective Services, and inpatient consultation services (social work, physical therapy, and occupational therapy), and post-discharge recommendations (primary care, physical therapy, and regional center). Neglect type groups varied by child medical history, social needs, and discharge recommendations. Statistically significant associations supported differences per neglect type. Conclusions: Our findings highlight five specific types of neglect seen in an impoverished and ethnically diverse geographic region. Post-discharge care needs should focus on removing social barriers and optimizing resources, in particular mental health, to mitigate the risk of continued neglect. Future studies should focus on prevention strategies, tailored interventions, and improved resource allocations per neglect type and discharge location. Significance: What is already known about the topic?: Child neglect is the most common type of child maltreatment in the United States. Previous research using child welfare system data support the existence of different types of neglect. However, the majority of hospital-based studies rarely focus on neglect and conceptualize child neglect as a broad concept. What this article adds to the literature?: Findings from this study suggest that characteristics, social needs, and post discharge care vary per neglect subtype. This has important implications for improving hospital-based responses and prevention strategies that address child neglect. [ABSTRACT FROM AUTHOR]

We aimed to evaluate if circulating plasma cells (CPC) detected by flow cytometry could add prognostic value of R2-ISS staging. We collected the electronic medical records of 336 newly diagnosed MM patients (NDMM) in our hospital from January 2017 to June 2023. The median overall survival (OS) for patients and R2-ISS stage I-IV were not reached (NR), NR, 58 months and 53 months, respectively. There was no significant difference in OS between patients with stage I and patients with stage II (P = 0.309) or between patients with stage III and patients with stage IV (P = 0.391). All the cases were re-classified according to R2-ISS stage and CPC numbers ≥ 0.05% (CPC high) or<0.05% (CPC low) into four new risk groups: Group 1: R2-ISS stage I + R2-ISS stage II and CPC low, Group 2: R2-ISS stage II and CPC high + R2-ISS stage III and CPC low, Group 3: R2-ISS stage III and CPC high + R2-ISS stage IV and CPC low, Group 4: R2-ISS stage IV and CPC high. The median OS were NR, NR, 57 months and 32 months. OS of Group 1 was significantly longer than that of Group 2 (P = 0.033). OS in Group 2 was significantly longer than that of Group 3 (P = 0.007). OS in Group 3 was significantly longer than that of Group 4 (P = 0.041). R2-ISS staging combined with CPC can improve risk stratification for NDMM patients. [ABSTRACT FROM AUTHOR]

Interoperability plays a crucial role in facilitating seamless data sharing across system boundaries, necessitating collaborative efforts among multiple systems. To achieve this, the presence of a common reference model for data exchange and dedicated interfaces is essential. However, the current state of Health Information Systems (HIS) often falls short in providing effective design elements that enable smooth and continuous data exchange across diverse domains. To address this challenge, a comprehensive investigation of the technical, syntactic, semantic, and other important aspects of interoperability interfaces is necessary, both in theory and practice. This article aims to address the design challenges associated with interoperability interfaces in Electronic Medical Record (EMR) systems. We commence by establishing theoretical guidelines that serve as foundation for designing effective interfaces. These guidelines encompass key considerations for the usability of interoperability interfaces, such as importing and exporting data of EMRs. Building upon this theoretical framework, we evaluate the interoperability interfaces within OpenMRS, a widely used EMR system. By aligning the evaluations with the established theoretical guidelines, we propose a set of generic interoperability interfaces designed to enhance the seamless exchange of data across different domains. To assess their usability, we employ a predictive usability inspection, providing valuable insights into the practical aspects of these interfaces. Through this research, we aim to contribute to the improvement of interoperability interfaces in EMR systems, bridging the gap between theoretical guidelines and practical implementation. By addressing the design challenges, conducting evaluations, and proposing interoperability interfaces, we strive to enhance data exchange design and promote a more integrated and collaborative healthcare system. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the safety and efficacy of endovascular treatment of unruptured pancreatic arcade aneurysms in a single-center series. Materials and Methods: The electronic medical records of patients who underwent endovascular treatment for unruptured pancreatic arcade aneurysms between 2011 and 2022 at our tertiary center were retrospectively reviewed. The presence of celiac artery stenosis/occlusion; aneurysm number, location, and size; endovascular technique; procedure-related complication incidence; and clinical outcomes were assessed. Results: Twenty-three patients (12 men and 11 women; mean [range] age, 63.8 [45–84] years) with 33 unruptured pancreatic arcade aneurysms were identified. Celiac artery stenosis/occlusion coexisted in 17 (74%) patients. Five (21%) patients had multiple aneurysms. The median aneurysm size was 9.3 mm (range, 4–18 mm). Seven, 6, 6, 5, 4, 3, and 2 aneurysms were located in the gastroduodenal, dorsal pancreatic, anterior superior pancreaticoduodenal, inferior pancreaticoduodenal, posterior inferior pancreaticoduodenal, posterior superior pancreaticoduodenal, and anterior inferior pancreaticoduodenal arteries, respectively. Four (15%) and 22 (85%) aneurysms were treated with endosaccular packing alone and coil embolization with endosaccular packing and parent artery occlusion, respectively, with resulting exclusion from arterial circulation. The remaining 7 aneurysms coexisting with larger aneurysms in other peripancreatic arteries were observed without embolization because they were small and for preserving collateral blood flow to the celiac artery. The treated aneurysms did not rupture or recur during the follow-up period (median, 40 months). Conclusion: Endovascular treatment is a safe and effective treatment for unruptured pancreatic arcade aneurysms. Level of Evidence: 3, non-controlled retrospective cohort study. [ABSTRACT FROM AUTHOR]

Introduction: Niraparib first-line maintenance (1LM) therapy has demonstrated clinical benefit for patients with ovarian cancer (OC) in clinical trial and real-world settings, but data on factors associated with real-world patient outcomes remain limited. This analysis identified patient characteristics associated with time to next treatment (TTNT), a proxy for real-world progression-free survival, in patients with OC treated with 1LM niraparib monotherapy. Methods: This retrospective observational study used a USA nationwide electronic health record-derived deidentified database and included adult patients diagnosed with OC who initiated 1LM niraparib monotherapy after first-line platinum-based chemotherapy. Patients were followed until the earliest occurrence of last clinical activity, death, or end of study period. TTNT was measured from 1LM niraparib initiation to the start of second-line treatment or death. Cox proportional hazards models assessed univariable and multivariable associations between baseline characteristics and TTNT. Results: Of 7872 patients diagnosed with OC, 526 met the eligibility criteria and were included in this analysis. Median (IQR) duration of follow-up was 14.1 (7.4–23.6) months. In univariable analyses, age, BRCA/homologous recombination deficiency (HRD) status, socioeconomic status, stage at initial diagnosis, cytoreductive surgery type, and residual disease status were significantly associated with observed TTNT and were introduced into the multivariable model with other clinically relevant variables. In the multivariable analysis, BRCA/HRD status, cytoreductive surgery type, and residual disease status were significantly associated with observed TTNT after covariate adjustment. Conversely, age, Eastern Cooperative Oncology Group performance status, disease stage, niraparib starting dose status, and first-line bevacizumab use were not associated with observed TTNT. Conclusion: This real-world, retrospective, observational analysis offers valuable insights on prognostic factors associated with TTNT in patients with OC treated with 1LM niraparib monotherapy after first-line platinum-based chemotherapy. Future studies are needed to examine how additional patient characteristics associated with clinical outcomes may guide treatment decisions and improve outcomes. [ABSTRACT FROM AUTHOR]

Introduction: A dynamic molecular biomarker that can identify early efficacy of immune checkpoint inhibitor (ICI) therapy remains an unmet clinical need. Here we evaluate if a novel circulating tumor DNA (ctDNA) assay, xM, used for treatment response monitoring (TRM), that quantifies changes in ctDNA tumor fraction (TF), can predict outcome benefits in patients treated with ICI alone or in combination with chemotherapy in a real-world (RW) cohort. Methods: This retrospective study consisted of patients with advanced cancer from the Tempus de-identified clinical genomic database who received longitudinal liquid-based next-generation sequencing. Eligible patients had a blood sample ≤ 40 days prior to the start of ICI initiation and an on-treatment blood sample 15–180 days post ICI initiation. TF was calculated via an ensemble algorithm that utilizes TF estimates derived from variants and copy number information. Patients with molecular response (MR) were defined as patients with a ≥ 50% decrease in TF between tests. In the subset of patients with rw-imaging data between 2 and 18 weeks of ICI initiation, the predictive value of MR in addition to rw-imaging was compared to a model of rw-imaging alone. Results: The evaluable cohort (N = 86) was composed of 14 solid cancer types. Patients received either ICI monotherapy (38.4%, N = 33) or ICI in combination with chemotherapy (61.6%, N = 53). Patients with MR had significantly longer rw-overall survival (rwOS) (hazard ratio (HR) 0.4, P = 0.004) and rw-progression free survival (rwPFS) (HR 0.4, P = 0.005) than patients with molecular non-response (nMR). Similar results were seen in the ICI monotherapy subcohort; HR 0.2, P = 0.02 for rwOS and HR 0.2, P = 0.01 for rwPFS. In the subset of patients with matched rw-imaging data (N = 51), a model incorporating both MR and rw-imaging was superior in predicting rwOS than rw-imaging alone (P = 0.02). Conclusions: xM used for TRM is a novel serial quantitative TF algorithm that can be used clinically to evaluate ICI therapy efficacy. [ABSTRACT FROM AUTHOR]

Background: For patients with metastatic non-small cell lung cancer, timely molecular testing is essential to determine the appropriate course of therapy. Initial treatment with platinum chemotherapy and/or an immune checkpoint inhibitor (ICI) is the standard of care for patients without actionable genomic alterations. Objective: We aimed to assess treatment patterns and clinical outcomes among patients with metastatic non-small cell lung cancer, no actionable genomic alterations, and with prior ICI and platinum-based chemotherapy in a community oncology setting. Methods: This retrospective observational study examined electronic health records from adult patients with an initial metastatic non-small cell lung cancer diagnosis without actionable genomic alterations from 2017 to 2019. Patients had received a subsequent line of therapy (LOT) [index] after discontinuing platinum-based chemotherapy plus an ICI in the previous one or two LOTs. Patient demographics and clinical characteristics were analyzed descriptively. Clinical outcomes were evaluated using Kaplan–Meier analyses. Results: Among the study population (n = 961), the most common index LOT regimens were non-platinum-based chemotherapies (57.3%), platinum-based chemotherapies (12.9%), ICI-based chemotherapies (12.7%), platinum + ICI-based chemotherapies (9.4%), and other (7.7%). The most common post-index LOT regimens were non-platinum based (61.2%), ICI based (15.3%), platinum based (10.7%), platinum + ICI based (3.2%), and other (2.5%). Median time to treatment discontinuation, time to next treatment, and overall survival were numerically longest with index LOT ICI-based regimens (6.5, 9.9, and 18.9 months, respectively) and shortest with platinum-based regimens (2.8, 5.3, and 8.0 months, respectively) and non-platinum-based regimens (2.6, 5.0, and 7.8 months, respectively). Conclusions: Among patients with metastatic non-small cell lung cancer without actionable genomic alterations previously treated with platinum + ICIs, non-platinum chemotherapy agents were most commonly prescribed in the index LOT. Clinical outcomes including time to treatment discontinuation, time to next treatment, and overall survival were short, highlighting the unmet need for more effective later-line treatments. [ABSTRACT FROM AUTHOR]

Tensor decomposition has recently been gaining attention in the machine learning community for the analysis of individual traces, such as Electronic Health Records. However, this task becomes significantly more difficult when the data follows complex temporal patterns. This paper introduces the notion of a temporal phenotype as an arrangement of features over time and it proposes SWoTTeD (Sliding Window for Temporal Tensor Decomposition), a novel method to discover hidden temporal patterns. SWoTTeD integrates several constraints and regularizations to enhance the interpretability of the extracted phenotypes. We validate our proposal using both synthetic and real-world datasets, and we present an original usecase using data from the Greater Paris University Hospital. The results show that SWoTTeD achieves at least as accurate reconstruction as recent state-of-the-art tensor decomposition models, and extracts temporal phenotypes that are meaningful for clinicians. [ABSTRACT FROM AUTHOR]

Congenital long QT syndrome (LQTS) diagnosis is complicated by limited genetic testing at scale, low prevalence, and normal QT corrected interval in patients with high-risk genotypes. We developed a deep learning approach combining electrocardiogram (ECG) waveform and electronic health record data to assess whether patients had pathogenic variants causing LQTS. We defined patients with high-risk genotypes as having ≥1 pathogenic variant in one of the LQTS-susceptibility genes. We trained the model using data from United Kingdom Biobank (UKBB) and then fine-tuned in a racially/ethnically diverse cohort using Mount Sinai BioMe Biobank. Following group-stratified 5-fold splitting, the fine-tuned model achieved area under the precision-recall curve of 0.29 (95% confidence interval [CI] 0.28–0.29) and area under the receiver operating curve of 0.83 (0.82–0.83) on independent testing data from BioMe. Multimodal fusion learning has promise to identify individuals with pathogenic genetic mutations to enable patient prioritization for further work up. [ABSTRACT FROM AUTHOR]

Clostridioides difficile infection (CDI) is a major cause of antibiotic-associated diarrhea and colitis. It is recognized as one of the most significant hospital-acquired infections. Although CDI can develop severe complications and spores of Clostridioides difficile can be transmitted by the fecal-oral route, CDI is occasionally overlooked in clinical settings. Thus, it is necessary to monitor high CDI risk groups, particularly those undergoing antibiotic treatment, to prevent complications and spread. We developed and validated a deep learning-based model to predict the occurrence of CDI within 28 days after starting antibiotic treatment using longitudinal electronic health records. For each patient, timelines of vital signs and laboratory tests with a 35-day monitoring period and a patient information vector consisting of age, sex, comorbidities, and medications were constructed. Our model achieved the prediction performance with an area under the receiver operating characteristic curve of 0.952 (95% CI: 0.932–0.973) in internal validation and 0.972 (95% CI: 0.968–0.975) in external validation. Platelet count and body temperature emerged as the most important features. The risk score, the output value of the model, exhibited a consistent increase in the CDI group, while the risk score in the non-CDI group either maintained its initial value or decreased. Using our CDI prediction model, high-risk patients requiring symptom monitoring can be identified. This could help reduce the underdiagnosis of CDI, thereby decreasing transmission and preventing complications. [ABSTRACT FROM AUTHOR]

The purpose of this scoping review is to identify and evaluate studies that examine the effectiveness and implementation strategies of Electronic Health Record (EHR)-integrated digital technologies aimed at improving medication-related outcomes and promoting health equity among hospitalised adults. Using the Consolidated Framework for Implementation Research (CFIR), the implementation methods and outcomes of the studies were evaluated, as was the assessment of methodological quality and risk of bias. Searches through Medline, Embase, Web of Science, and CINAHL Plus yielded 23 relevant studies from 1,232 abstracts, spanning 11 countries and from 2008 to 2022, with varied research designs. Integrated digital tools such as alert systems, clinical decision support systems, predictive analytics, risk assessment, and real-time screening and surveillance within EHRs demonstrated potential in reducing medication errors, adverse events, and inappropriate medication use, particularly in older patients. Challenges include alert fatigue, clinician acceptance, workflow integration, cost, data integrity, interoperability, and the potential for algorithmic bias, with a call for long-term and ongoing monitoring of patient safety and health equity outcomes. This review, guided by the CFIR framework, highlights the importance of designing health technology based on evidence and user-centred practices. Quality assessments identified eligibility and representativeness issues that affected the reliability and generalisability of the findings. This review also highlights a critical research gap on whether EHR-integrated digital tools can address or worsen health inequities among hospitalised patients. Recognising the growing role of Artificial Intelligence (AI) and Machine Learning (ML), this review calls for further research on its influence on medication management and health equity through integration of EHR and digital technology. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index. Methods: A retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong's algorithm. Models were validated externally using an international database. Results: Of 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p < 0.001, respectively). In the external validation population, the area under the curve (AUC) of the ROX index was 0.683 (accuracy 63%), the AIC model showed an AUC of 0.703 (accuracy 69%), and the lowest AIC model with significant p values had an AUC of 0.725 (accuracy 79%). Conclusions: In the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19. ClinicalTrials.gov identifier: NCT05663528. [ABSTRACT FROM AUTHOR]

Background: Treatment of asymptomatic Abdominal Aortic Aneurysms (AAA) presents a clinical challenge, requiring a delicate balance between rupture risk, patient comorbidities, and intervention-related complications. International guidelines recommend intervention for specific AAA size thresholds, but these are based on historical trials with limited female representation. We aimed to analyse disease characteristics, AAA size at rupture, and intervention outcomes in patients with ruptured AAA from 2009 to 2023 to investigate the gap between guidelines and local realities. Methods: This single-centre retrospective cohort study analysed electronic health records of patients treated for a ruptured AAA, excluding those who were managed palliatively. The study assessed patients' demographics, risk factors, comorbidities, clinical presentation, radiological characteristics, and outcomes. Results: Of 164 patients (41 females, 123 males, median age 73.5), 93.3% presented with abdominal or back pain. The median AAA size at rupture was 8.0 cm in males and 7.6 cm in females. No significant correlations were found between demographic characteristics, risk factors, AAA size, repair modality, and outcomes. Trends show a decline in AAA prevalence and rupture rates, aligning with global health initiatives. Post-intervention survival rates at 30 days were 70.7% (67.5% in males and 80.0% in females), and at 2 years were 65.85% (61.7% in males and 70.0% in females). Conclusion: Evolving AAA trends and improved post-intervention survival rates warrant a critical reassessment of existing intervention recommendations. Adjusting intervention thresholds to larger sizes may be justified to optimise the risk-benefit ratio. [ABSTRACT FROM AUTHOR]

This retrospective cohort study used Taussig Cancer Center's Myeloma Patient Registry to identify adults with multiple myeloma diagnosed between January 2017-December 2021. Electronic health records data captured time from diagnosis to initial prescription fill for oral antimyeloma medications and initiation of facility administered or oral antimyeloma treatment. We identified 720 patients with a mean age at diagnosis of 67 years ±11; 55% were male, 77% White, 22% Black, 1% other races, covered by private insurance (36%), traditional Medicare (29%), Medicare Advantage (25%), and Medicaid (8.3%). Over a third of patients (37%) resided in an area in the most disadvantaged area deprivation index (ADI) quartile. The median available follow-up was 765 days. Seventy-five percent of the cohort filled an oral antimyeloma medication prescription (excluding corticosteroids), with a median time to fill of 28 days (IQR, 15–61). In the multivariable Cox regression model, Black race (vs. White, adjusted hazard ratio [aHR], 0.61, 95% CI, 0.42–0.87), older age at diagnosis (aHR per 1 year, 0.97, 95% CI, 0.95–0.98), diagnosis during an inpatient admission (aHR, 0.63, 95% CI, 0.43–0.92), and estimated glomerular filtration rate ≤29 ml/min/1.73 m2 (vs. ≥60, aHR, 0.46, 95% CI, 0.29–0.73) were negatively associated with prescription fill for oral antimyeloma medication at 30 days, while insurance type and ADI were not significant predictors. [ABSTRACT FROM AUTHOR]

Background: Addressing Patient Reported Outcomes (PROs) is essential for patient-centred care, shared decision making and improved health outcomes. Value-based health care systems in New South Wales (NSW) have a growing focus on collecting and using PROs that matter most to patients to improve their healthcare outcomes. Developing oral health patient reported outcomes measures (OH-PROM) is a first step towards value-based oral health care. This paper describes the development process of an adult and child OH-PROM tool that can be piloted for NSW public dental patients. Methods: An expert panel was assembled to undertake a systematic process of developing OH-PROMs for NSW Health. Key methodological considerations included: (1) forming an expert panel to specify the target population and context of implementation, (2) rapid literature review and environmental scan to identify existing validated OH-PROM tools for adults and children. (3) consensus gathering with the expert panel (4) consumer feedback, and (5) finalisation of the tool for electronic oral health record (eOHR) integration to establish a set of questions, that were relevant, context-appropriate, and important to oral healthcare outcomes for patients using public dental services. Results: The panel considered a total of 59 questions from two child (15), and four adult (44) Oral Health Related Quality of Life (OHRQoL) questionnaires used to collect OH-PROMs. These questions were mapped to the four key dimensions of OHRQoL for OH-PROMs: Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact. The consensus resulted in seven questions that aligned with these four dimensions to form two new NSW OH-PROM tools: one for adults and one for children. The tools were tested with consumers for understandability and usefulness before being incorporated into the electronic oral health record system, in readiness for future pilot testing. Conclusion: The process for developing new OH-PROMs for NSW public dental services took a pragmatic approach that combined literature appraisal, expert consensus, and consumer consultation. Future work will assess the implementation of the OH-PROM tool and test its validity for broader use as an outcome measure for value-based oral healthcare. [ABSTRACT FROM AUTHOR]

Missed appointments, or no-shows, disrupt healthcare delivery, exacerbating chronic disease management and leading to worse health outcomes. Telehealth has surged as a viable solution to reduce no-shows and improve healthcare accessibility, especially during the COVID-19 pandemic. However, telehealth disparities and its long-term efficacy across various medical specialties remain understudied. To address this, we performed a retrospective analysis of electronic health records from a heterogenous network of hospitals in Illinois, examining telehealth use and no-shows across among 444,752 adult patients with 1,973,098 outpatient encounters across nine specialties during the sustained pandemic phase (i.e., January 1, 2021 to July 1, 2022). Among them, 84,290 (4.27%) were no-shows, and telehealth constituted 202,933 (10.3%) of the total encounters. Telehealth use during the sustained phase varied significantly by specialty type. Overall, telehealth encounters were associated with reduced no-show odds compared to in-person encounters (OR, 0.28; 95% CI, 0.26–0.29). Black and Hispanic patients, as well as those with Medicaid, had higher no-show odds relative to their counterparts, even when using telehealth. Mental health specialty had the highest telehealth usage rate and the highest no-show odds (OR, 2.99; 95% CI, 2.84–3.14) relative to other specialties included in the study. Moreover, specialty type had differential effects on no-shows for telehealth. These results underscore the variability in telehealth use by specialty type and pervasive disparities telehealth use and no-shows. As we move beyond the pandemic, our findings can inform policymakers to tailor policies and incentives to reach different patient groups as well as specialties, with varying needs, to promote equitable telehealth utilization. [ABSTRACT FROM AUTHOR]

Background: Fluid administration is the first line treatment in intensive care unit (ICU) patients with sepsis and septic shock. While fluid boluses administration can be titrated by predicting preload dependency, the amount of other forms of fluids may be more complex to be evaluated. We conducted a retrospective analysis in a tertiary hospital, to assess the ratio between fluids given as boluses and total administered fluid intake during early phases of ICU stay, and to evaluate the impact of fluid strategy on ICU mortality. Data related to fluid administration during the first four days of ICU stay were exported from an electronic health records system (ICCA®, Philips Healthcare). Demographic data, severity score, norepinephrine dose at ICU admission, overall fluid balance and the percentage of different fluid components of the overall volume administered were included in a multivariable logistic regression model, evaluating the association with ICU survival. Results: We analyzed 220 patients admitted with septic shock and sepsis-induced hypotension from 1st July 2021 to 31st December 2023. Fluid boluses and maintenance represented 49.3% ± 22.8 of the overall fluid intake, being balanced solution the most represented (40.4% ± 22.0). The fluid volume for drug infusion represented 34.0% ± 2.9 of the total fluid intake, while oral or via nasogastric tube fluid intake represented 18.0% ± 15.7 of the total fluid intake. Fluid volume given as boluses represented 8.6% of the total fluid intake over the four days, with a reduction from 25.1% ± 24.0 on Day 1 to 4.8% ± 8.7 on Day 4. A positive fluid balance [OR 1.167 (1.029–1.341); p = 0.021] was the most important factor associated with ICU mortality. Non-survivors (n = 66; 30%) received a higher amount of overall inputs than survivors only on Day 1 [2493 mL vs. 1855 mL; p = 0.022]. Conclusions: This retrospective analysis of fluids given over the early phases of septic shock and sepsis-induced hypotension showed that the overall volume given by boluses ranges from about 25% on Day 1 to about 5% on Day 4 from ICU admission. Our data confirms that a positive fluid balance over the first 4 days of ICU is associated with mortality. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis is a chronic inflammatory disease, and interstitial lung disease is one of the important extra-articular manifestations. There is limited evidence comparing abatacept (ABA) and tumor necrosis factor inhibitors (TNFi) regarding the risk of mortality among patients with rheumatoid arthritis associated interstitial lung disease (RA-ILD). The aim of this study is to investigate the risk of mortality in patients with RA-ILD treated with ABA compared to TNFi. This retrospective cohort study utilized TriNetX electronic health record database. We enrolled patients who were diagnosed with RA-ILD and had received a new prescription for either ABA or TNFi. Patients were categorized into two cohorts based on their initial prescription. The primary outcome was all-cause mortality, and secondary outcomes were healthcare utilizations, including hospitalization, critical care services, and mechanical ventilation. Subgroup analyses were performed on age, presence of anti-citrullinated peptide antibodies (ACPA), and cardiovascular risk. Among 34,388 RA-ILD patients, 895 were selected for each group (ABA and TNFi) following propensity score matching. The ABA group exhibited a higher all-cause mortality risk. (HR 1.296, 95% CI 1.006–1.671). Subgroup analysis showed a heightened risk of receiving mechanical ventilation in ABA-treated patients aged 18–64 years old (HR 1.853, 95% CI 1.002–3.426), and those with cardiovascular risk factors (HR 2.015, 95% CI 1.118–3.630). Another subgroup analysis indicated a higher risk of mortality among ABA-treated patients with positive-ACPA. (HR 4.138 95% CI 1.343–12.75). This real-world data research demonstrated a higher risk of all-cause mortality in RA-ILD patients treated with ABA compared to TNFi, particularly those aged 18–64 years, lacking cardiovascular risk factors, and positive-ACPA. ABA was associated with an increased risk of mechanical ventilation in patients aged 18–64 years and those with cardiovascular risk factors. [ABSTRACT FROM AUTHOR]

Medical records are transmitted between medical institutions using cloud-based Electronic health record (EHR) systems, which are intended to improve various medical services. Due to the potential of data breaches and the resultant loss of patient data, medical organizations find it challenging to employ cloud-based electronic medical record systems. EHR systems frequently necessitate high transmission costs, energy use, and time loss for physicians and patients. Furthermore, EHR security is a critical concern that jeopardizes patient privacy. Compared to a single system, cloud-based EHR solutions may bring extra security concerns as the system architecture gets more intricate. Access control strategies and the development of efficient security mechanisms for cloud-based EHR data are critical. For privacy reasons, the Dynamic constrained message authentication (DCMA) technique is used in the proposed system to encrypt the outsourced medical data by using symmetric key cryptography, which uses the Seagull optimization algorithm (SOA) to choose the best random keys for encryption and then resultant data is hashed using the SHA-256 technique. The results of the proposed model are evaluated using performance metrics, and the model attained a security of about 98.58%, which is proven to be superior because it adopts advanced random secret key generation, which adds more security to the system. [ABSTRACT FROM AUTHOR]

The quick Sequential Organ Failure Assessment (qSOFA) system identifies an individual's risk to progress to poor sepsis-related outcomes using minimal variables. We used Support Vector Machine, Learning Using Concave and Convex Kernels, and Random Forest to predict an increase in qSOFA score using electronic health record (EHR) data, electrocardiograms (ECG), and arterial line signals. We structured physiological signals data in a tensor format and used Canonical Polyadic/Parallel Factors (CP) decomposition for feature reduction. Random Forests trained on ECG data show improved performance after tensor decomposition for predictions in a 6-h time frame (AUROC 0.67 ± 0.06 compared to 0.57 ± 0.08, p = 0.01 ). Adding arterial line features can also improve performance (AUROC 0.69 ± 0.07, p < 0.01 ), and benefit from tensor decomposition (AUROC 0.71 ± 0.07, p = 0.01 ). Adding EHR data features to a tensor-reduced signal model further improves performance (AUROC 0.77 ± 0.06, p < 0.01 ). Despite reduction in performance going from an EHR data-informed model to a tensor-reduced waveform data model, the signals-informed model offers distinct advantages. The first is that predictions can be made on a continuous basis in real-time, and second is that these predictions are not limited by the availability of EHR data. Additionally, structuring the waveform features as a tensor conserves structural and temporal information that would otherwise be lost if the data were presented as flat vectors. [ABSTRACT FROM AUTHOR]

Introduction: Biologic therapies are licensed for both psoriasis (PsO) and psoriatic arthritis (PsA) with some electronic medical record data suggest that IL (Interleukin)-23 blockers might be more protective in PsA prevention than TNF blockers; however, the findings have been inconsistent. Higher Psoriasis Area and Severity Index (PASI) scores have also been linked to an increased PsA risk. To clarify these unresolved issues we investigated biologic agents, methotrexate, phototherapy, and topical therapy for PsA prevention in patients with psoriasis. Methods: This retrospective cohort study analyzed data from 58,671 patients with psoriasis from the Israeli Meuhedet Health Services Organization database was evaluated for incident PsA. Patients were categorized on the basis of treatment: group 1, topical therapy; group 2, phototherapy; group 3, conventional disease-modifying antirheumatic drugs (cDMARDs; methotrexate); group 4, biologic DMARDs which was also stratified according to biologic class. Results: The PsA incidence rate was lower in the biologic agents' group versus the methotrexate group (HR 0.46 [95% CI 0.35–0.62]). The incidence rates per 100 person-years varied across biologic treatment groups, with the anti‑IL‑12/23 or anti‑IL‑23p19 group at 4.57, the anti-IL-17 group at 4.35, and the TNF inhibitor group at 2.55. No differences were found between various biological agents in terms of preventing PsA. The phototherapy group exhibited a higher PsA development rate than the topical therapy group (HR 1.85 [95% CI 1.65–2.07]). Conclusion: Biological agents are more effective than methotrexate in reducing incident PsA in patients with psoriasis. This lower rate of PsA on topical therapy compared to phototherapy supports the importance of psoriasis severity as a risk factor. [ABSTRACT FROM AUTHOR]

Purpose: Clinical decision support systems (CDSS) are used to identify drugs with potential need for dose modification in patients with renal impairment. ChatGPT holds the potential to be integrated in the electronic health record (EHR) system to give such dosing advices. In this study, we aim to evaluate the performance of ChatGPT in clinical rule-guided dose interventions in hospitalized patients with renal impairment. Methods: This cross-sectional study was performed at Tergooi Medical Center, the Netherlands. CDSS alerts regarding renal dysfunction were collected from the electronic health record (EHR) during a 2-week period and were presented to ChatGPT and an expert panel. Alerts were presented with and without patient variables. To evaluate the performance, suggested medication interventions were compared. Results: In total, 172 CDDS alerts were generated for 80 patients. Indecisive responses by ChatGPT to alerts were excluded. For alerts presented without patient variables, ChatGPT provided "correct and identical" responses to 19.9%, "correct and different" responses to 26.7%, and "incorrect responses to 53.4% of the alerts. For alerts including patient variables, ChatGPT provided "correct and identical" responses to 16.7%, "correct and different" responses to 16.0%, and "incorrect responses to 67.3% of the alerts. Accuracy was better for newer drugs such as direct oral anticoagulants. Conclusion: The performance of ChatGPT in clinical rule-guided dose interventions in hospitalized patients with renal dysfunction was poor. Based on these results, we conclude that ChatGPT, in its current state, is not appropriate for automatic integration into our EHR to handle CDSS alerts related to renal dysfunction. [ABSTRACT FROM AUTHOR]

Background: Postpartum readmission for preeclampsia is a difficult predicament for patients which creates financial, psychosocial, and physical stress. It is often a challenge to predict postpartum preeclampsia and therefore identify patients that may be at risk prior to discharge. This study aims to identify risk factors in patients that are at high risk for readmission due to preeclampsia. The identification of these risk factors may also lead to enhanced education and counseling prior to discharge. Methods: Researchers conducted a case–control study using a data set collected from 2015 to 2022 looking at obstetric readmissions within 6 weeks of delivery and then stratified these patients for preeclampsia diagnosis. A control set was created within the healthcare system's electronic medical record's search tools for patients diagnosed with preeclampsia who were not readmitted to the hospital. This study evaluates 78 patients who were readmitted with a diagnosis of preeclampsia and compared to 77 patients who were diagnosed with preeclampsia who were not readmitted. Again, the aim of this study was to investigate risk factors for readmission among patients with preeclampsia. Results: A multivariable logistic regression model was used to assess predictors which revealed that older age (OR 1.13, CI 1.03–1.24), no history of preeclampsia with or without severe features within pregnancy before delivery (OR 15.29, CI 5.56–41.98 and 13.58, CI 4.46–12.85), no aspirin use in pregnancy (OR 4.38, CI 2.02–9.48), and number of triage visits related to hypertension during prenatal care were all significant predictors for readmission due to preeclampsia. Conclusion: With these risk factors in mind, better counseling and preventative surveillance can be provided to patients. Future studies are needed to evaluate the effectiveness of predictive models developed using these found risk factors. [ABSTRACT FROM AUTHOR]

Background: The ability to classify patients' goals of care (GOC) from clinical documentation would facilitate serious illness communication quality improvement efforts and pragmatic measurement of goal-concordant care. Feasibility of this approach remains unknown. Objective: To evaluate the feasibility of classifying patients' GOC from clinical documentation in the electronic health record (EHR), describe the frequency and patterns of changes in patients' goals over time, and identify barriers to reliable goal classification. Design: Retrospective, mixed-methods chart review study. Participants: Adults with high (50–74%) and very high (≥ 75%) 6-month mortality risk admitted to three urban hospitals. Main Measures: Two physician coders independently reviewed EHR notes from 6 months before through 6 months after admission to identify documented GOC discussions and classify GOC. GOC were classified into one of four prespecified categories: (1) comfort-focused, (2) maintain or improve function, (3) life extension, or (4) unclear. Coder interrater reliability was assessed using kappa statistics. Barriers to classifying GOC were assessed using qualitative content analysis. Key Results: Among 85 of 109 (78%) patients, 338 GOC discussions were documented. Inter-rater reliability was substantial (75% interrater agreement; Cohen's kappa = 0.67; 95% CI, 0.60–0.73). Patients' initial documented goal was most frequently "life extension" (N = 37, 44%), followed by "maintain or improve function" (N = 28, 33%), "unclear" (N = 17, 20%), and "comfort-focused" (N = 3, 4%). Among the 66 patients whose goals' classification changed over time, most changed to "comfort-focused" goals (N = 49, 74%). Primary reasons for unclear goals were the observation of concurrently held or conditional goals, patient and family uncertainty, and limited documentation. Conclusions: Clinical notes in the EHR can be used to reliably classify patients' GOC into discrete, clinically germane categories. This work motivates future research to use natural language models to promote scalability of the approach in clinical care and serious illness research. [ABSTRACT FROM AUTHOR]

Background: Early trials of dihydropyridine calcium channel blockers (DCCBs) suggest a detrimental effect on intraglomerular pressure and an association with albuminuria. Objective: We sought to evaluate the associations of DCCB initiation with albuminuria and kidney failure with replacement therapy (KFRT) and to determine whether renin-angiotensin system (RAS) blockade modified these associations. Design: We conducted a target trial emulation study using a new user, active comparator design and electronic health record data from Geisinger Health. Participants: We included patients without severe albuminuria or KFRT who were initiated on a DCCB or thiazide (active comparator) between January 1, 2004, and December 31, 2019. Main Measures: Using inverse probability of treatment weighting, we performed doubly robust Cox proportional hazards regression to estimate the association of DCCB initiation with incident severe albuminuria (urine albumin to creatinine ratio > 300 mg/g) and KFRT, overall and stratified by RAS blocker use. Key Results: There were 11,747 and 26,758 eligible patients initiating a DCCB and thiazide, respectively, with a weighted baseline mean age of 60 years, systolic blood pressure of 143 mm Hg, and eGFR of 86 mL/min/1.73 m2, and with a mean follow-up of 8 years. Compared with thiazides, DCCBs were significantly associated with the development of severe albuminuria (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.16–1.43), with attenuation of risk in the presence of RAS blockade (P for interaction < 0.001). The risk of KFRT was increased among patients without RAS blockade (HR, 1.66; 95% CI, 1.19–2.31), but not with RAS blockade (P for interaction = 0.005). Conclusions: DCCBs were associated with increased risk of albuminuria and, in the absence of RAS blockade, KFRT. These findings suggest coupling DCCB therapy with RAS blockade may mitigate adverse kidney outcomes. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Background: Neonatal acute kidney injury (AKI) is a common yet underdiagnosed condition in neonates with significant implications for long-term kidney health. Lack of timely recognition and documentation of AKI contributes to missed opportunities for nephrology consultation and follow-up, potentially leading to adverse outcomes. Methods: We conducted a quality improvement (QI) project to address this by incorporating an automated real-time electronic medical record (EMR)-AKI alert system in the Neonatal Intensive Care Unit (NICU) at Le Bonheur Children's Hospital. Our primary objective was to improve documentation of neonatal AKI (defined as serum creatinine (SCr) > 1.5 mg/dL) by 25% compared to baseline levels. The secondary goal was to increase nephrology consultations and referrals to the neonatal nephrology clinic. We designed an EMR-AKI alert system to trigger for neonates with SCr > 1.5 mg/dL, automatically adding AKI diagnosis to the problem list. This prompted physicians to consult nephrology, refer neonates to the nephrology clinic, and consider medication adjustments. Results: Our results demonstrated a significant improvement in AKI documentation after implementing the EMR-AKI alert, reaching 100% compared with 7% at baseline (p < 0.001) for neonates with SCr > 1.5 mg/dL. Although the increase in nephrology consultations was not statistically significant (p = 0.5), there was a significant increase in referrals to neonatal nephrology clinics (p = 0.005). Conclusions: Integration of an EMR alert system with automated documentation offers an efficient and economical solution for improving neonatal AKI diagnosis and documentation. This approach enhances healthcare provider engagement, streamlines workflows, and supports QI. Widespread adoption of similar approaches can lead to improved patient outcomes and documentation accuracy in neonatal AKI care. [ABSTRACT FROM AUTHOR]

The aim of this research was to describe the epidemiology, presentation and healthcare use in primary care for foot and ankle problems in children and young people (CYP) across England. We undertook a population-based cohort study using data from the Clinical Practice Research Datalink Aurum database, a database of anonymised electronic health records from general practices across England. Data was accessed for all CYP aged 0–18 years presenting to their general practitioner between January 2015 and December 2021 with a foot and/or ankle problem. Consultation rates were calculated and used to estimate numbers of consultations in an average practice. Hierarchical Poisson regression estimated relative rates of consultations across sociodemographic groups and logistic regression evaluated factors associated with repeat consultations. A total of 416,137 patients had 687,753 foot and ankle events, of which the majority were categorised as "musculoskeletal" (34%) and "unspecified pain" (21%). Rates peaked at 601 consultations per 10,000 patient-years among males aged 10–14 years in 2018. An average practice might observe 132 (95% CI 110 to 155) consultations annually. Odds for repeat consultations were higher among those with pre-existing diagnoses including juvenile arthritis (OR 1.73, 95% CI 1.48 to 2.03). Conclusions: Consultations for foot and ankle problems were high among CYP, particularly males aged 10 to 14 years. These data can inform service provision to ensure CYP access appropriate health professionals for accurate diagnosis and treatment. What is Known: • Foot and ankle problems can have considerable impact on health-related quality of life in children and young people (CYP). • There is limited data describing the nature and frequency of foot and ankle problems in CYP. What is New: • Foot and ankle consultations were higher in English general practice among CYP aged 10 to 14 years compared to other age groups, and higher among males compared to females. • The high proportion of unspecified diagnoses and repeat consultations suggests there is need for greater integration between general practice and allied health professionals in community-based healthcare settings. [ABSTRACT FROM AUTHOR]