Electronic Medical Record System Research Articles

Comparison of the efficacy and safety of domestically produced tislelizumab, camrelizumab, and imported pembrolizumab in the treatment of advanced NSCLC: a real-world retrospective study.

Since the imported PD-1 inhibitor pembrolizumab was listed in China in 2018, China has opened up the era of immunotherapy for malignant tumors, with several domestically produced PD-1 inhibitors coming onto the market one after another. To find out whether there are differences in the efficacy and safety of domestic and imported PD-1 inhibitors in patients with advanced non-small cell lung cancer, we conducted this retrospective study in two tertiary hospitals in China. Patients with advanced NSCLC treated with tislelizumab or camrelizumab or pembrolizumab who met the inclusion criteria were screened through the electronic medical record system. A total of 259 patients were screened, but due to the unbalanced baseline, we performed propensity score matching and finally included 149 patients in three groups: pembrolizumab (n = 38), tislelizumab (n = 38), and camrelizumab (n = 73), which had very balanced baseline characteristics in each group after propensity score matching treatment. The results showed that the median progression-free period was 11.3m vs 10.1m vs 8.9m; p = 0.754; and the objective response rate was 63.2% vs 50% vs 57.5%; P = 0.510 for pembrolizumab, tislelizumab, and carrelizumab, respectively. There was no significant difference in median PFS between PD-L1 expression subgroups. In terms of safety, only skin toxicity of any grade of carrelizumab was higher than that of the other two groups (p = 0.034), and the incidence of grade ≥ 3 adverse reactions was not statistically significant among the three groups. In this real-world study, the efficacy and safety of the domestically produced tislelizumab, camrelizumab, and the imported pembrolizumab were comparable.

Dermatological emergencies and determinants of hospitalization in Switzerland: A retrospective study.

Dermatologic conditions are estimated to account worldwide for approximately 8% of all visits at emergency departments (EDs). Although rarely life-threatening, several dermatologic emergencies may have a high morbidity. Little is known about ED consultations of patients with dermatological emergencies and their subsequent hospital disposal. We explore determinants and clinical variables affecting patients' disposal and hospitalization of people attending the ED at a Swiss University Hospital, over a 56-month observational period, for a dermatological problem. De-identified patients' information was extracted from the hospital electronic medical record system. Generalized estimating equations were used to explore determinants of patient's disposition. Out of 5096 consecutive patients with a dermatological main problem evaluated at the ED, 79% of patients were hospitalized after initial assessment. In multivariable analyses, factors which were significantly associated with an increased admission rate included length of ED stay, age ≥ 45 years, male sex, distinct vital signs, high body mass index, low oxygen saturation, admission time in the ED and number and type of dermatological diagnoses. Only 2.2% of the hospitalized patients were admitted to a dermatology ward, despite the fact that they had dermatological diagnoses critically determining the diagnostic related group (DRG) payment. The number of patients managed by dermatologists during in-patient treatment significantly decreased over the study period. Our study identifies a number of independent predictors affecting the risk of hospital admission for patients with dermatological conditions, which may be useful to improve patients' disposal in EDs. The results indicate that the dermatological specialty is becoming increasingly marginalized in the management of patients in the Swiss hospital setting. This trend may have significant implications for the delivery of adequate medical care, outcomes and cost-effectiveness. Dermatologists should be more engaged to better position their specialty and to effectively collaborate with nondermatologists to enhance patient care.

Endobiogenic Biology of Function Indices in a Cohort of Kidney Transplant Recipients.

Background and Objectives: Endobiogeny is a global systems approach to human biology based on the concept that the endocrine system manages the metabolism. Biology of function (BoF) indices are diagnostic tools in endobiogenic medicine that reflect the action of the endocrine system on the cells and the metabolic activity of an organism. Kidney transplant recipients are a very specific patient population due to their constant use of immunosuppressive agents such as steroids and anamnesis of chronic kidney disease. The aim of this study was to assess the tendencies of endobiogenic BoF indices in a kidney transplant recipient population and to determine the relationship between BoF index values and histology-proven kidney transplant rejection. Materials and Methods: A total of 117 kidney transplant recipients undergoing surveillance or indication allograft biopsy were included in this study. Endobiogenic BoF indices were calculated from complete blood count tests taken before the kidney biopsy. Histology samples were evaluated by an experienced pathologist according to the Banff classification system. Clinical and follow-up data were collected from an electronic patient medical record system. Results: Overall, <35% of the patients had BoF index values assumed to be normal, according to the general population data. Additionally, >50% of the patients had lower-than-normal adaptation, leucocyte mobilization, genital, and adjusted genital ratio indices, while the Cata-Ana, genito-thyroid ratio, adrenal gland, and cortisol indices were increased in >50% of the transplant recipients. The adaptation index was significantly higher in patients with biopsy-proven transplant rejection and demonstrated an AUC value of 0.649 (95%CI 0.540-0.759) for discriminating rejectors from patients without transplant rejection. Conclusions: Most of the kidney transplant recipients had abnormal BoF index values, reflecting increased corticotropic effects on their cells. The adaptation index distinguished patients with biopsy-proven transplant rejection from those without it.

Combined aqupla, paclitaxel liposome, and docetaxel treatment: survival and biomarker outcomes in recurrent ovarian cancer patients.

As one lethal malignancy in women's reproductive systems, ovarian cancer (OC) is frequently detected at an advanced phase during diagnosis. when the disease has spread widely. The absence of obvious symptoms and powerful screening tools in the early stages makes treatment difficult and the prognosis poor. Despite the clinical remission that can be achieved in some patients after initial treatment, the recurrence rate is conspicuous, posing a considerable challenge in treating recurrent OC (ROC). In the retrospective analysis, we compared the effects of two treatment regimens, aqupla combined with paclitaxel liposome (NP group) versus aqupla combined with docetaxel (ND group), on survival and biomarkers in patients with ROC. The study included 121 OC patients, and clinical data were collected through an electronic medical record system, outpatient review records, and a follow-up record system. The results revealed a notably higher overall remission rate in the ND group than the NP group, but revealed no notable inter-group discrepancy in toxicities, implying that the aqupla combined with docetaxel regimen may be more effective in platinum-sensitive ROC patients. Additionally, post-treatment CA125 levels were lower in patients in the ND group, suggesting that the regimen may be more effective in reducing tumour load. Survival analysis further revealed that treatment regimen, FIGO stage, number of recurrent lesions, and pretreatment CA125 level were independent prognostic factors affecting patients' 5-year OS and PFS. Overall for ROC patients, especially platinum-sensitive patients, the aqupla in combination with docetaxel regimen provided an improved survival benefit with a comparable safety profile, highlighting the importance of individualised treatment strategies.

An Updated Case Study: Successful Implementation of an Electronic Medical Record System at BTFCC in Nepal

An Updated Case Study: Successful Implementation of an Electronic Medical Record System at BTFCC in Nepal

Epidemiology of Injuries Among National Basketball Association Players: 2013-2014 Through 2018-2019.

Understanding the epidemiology of injuries to athletes is essential to informing injury prevention efforts. The incidence and impact of basketball-related injuries among National Basketball Association (NBA) players from 2013-2014 through 2018-2019 is relatively stable over time. Descriptive epidemiology study. Level 3. Injuries from 2013-2014 through 2018-2019 were analyzed using the NBA Injury and Illness Database from an electronic medical record system. Descriptive statistics were calculated for injuries by season, game-loss, and onset. Incidence rates were estimated using Poisson models and linear trend tests. Between 552 and 606 players participated in ≥1 game per season during the study. Annual injury incidence ranged from 1550 to 1892, with 33.6% to 38.5% resulting in a missed NBA game. Game-loss injury rates ranged from 5.6 to 7.0 injuries per 10,000 player-minutes from 2014-2015 through 2018-2019 (P = 0.19); the rate was lower in 2013-2014 (5.0 injuries per 10,000 player-minutes), partly due to increased preseason injury rates and transition of reporting processes. The 6-year game-loss injury rate in preseason and regular season games was 6.9 (95% CI 6.0, 8.0) and 6.2 (95% CI 6.0, 6.5) injuries per 10,000 player-minutes; the rate in playoff games was lower (P < 0.01) at 2.8 (95% CI 2.2, 3.6). Most (73%) game-loss injuries had acute onset; 44.4% to 52.5% of these involved contact with another player. From 2013-2014 through 2018-2019, over one-third of injuries resulted in missed NBA games, with highest rates of game-loss injuries in preseason games and lowest rates in playoff games. Most game-loss injuries had acute onset, and half of those involved contact with another player. These findings - through reliable data reporting by team medical staff in an audited system - can guide evidence-based injury reduction strategies and inform player health priorities.

Various clinical manifestations of 223 patients with IgE deficiency in a tertiary hospital in China: A cross-sectional study.

High Immunoglobulin E(IgE) levels associated with hypersensitivity or parasitic infection were well established, but the clinical significance of ultra-low IgE was largely unknown. Previous studies indicated these patients have an elevated risk of cancer, but large-scale epidemiological studies on the prevalence and clinical manifestations of these ultra-low IgE patients are still lacking. A total of 62,997 patients who were admitted to the First Affiliated Hospital of Wenzhou Medical University and had IgE level tests from January 2010 to March 2020 were included. Patients with serum IgE levels < 2 IU/mL were defined to have ultra-low IgE. And the clinical characteristics of these patients were retrospectively analyzed based on electronic medical record system and follow-up. A total of 223 patients (223/62,997, 0.35%) had ultra-low IgE were documented in 62,997 patients who had IgE tests. Among the clinical manifestations of these 223 ultra-low IgE patients, infection ranked first (125/223, 56.05%), following allergic diseases (51/223, 22.87%), hematological disorders (37/223, 16.59%), tumor (27/223, 12.11%) and autoimmune diseases (23/223, 10.31%). To the best of our knowledge, we first reported that the prevalence and clinical characteristics of 223 ultra-low IgE patients in China. The most common comorbidities were infection, allergic diseases, hematological disorders, tumor and autoimmune diseases.

Quantitative prediction of postpartum hemorrhage in cesarean section on machine learning

BackgroundCesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive prevention when predicting PPH occurrence in advance. However, current works on PPH prediction focus on whether PPH occurs rather than assessing PPH amount. To this end, this work studies quantitative PPH prediction with machine learning (ML).MethodsThe study cohort in this paper was selected from individuals with PPH who were hospitalized at Shijiazhuang Obstetrics and Gynecology Hospital from 2020 to 2022. In this study cohort, we built a dataset with 6,144 subjects covering clinical parameters, anesthesia operation records, laboratory examination results, and other information in the electronic medical record system. Based on our built dataset, we exploit six different ML models, including logistic regression, linear regression, gradient boosting, XGBoost, multilayer perceptron, and random forest, to automatically predict the amount of bleeding during cesarean section. Eighty percent of the dataset was used as model training, and 20%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} was used for verification. Those ML models are constantly verified and improved by root mean squared error(RMSE) and mean absolute error(MAE). Moreover, we also leverage the importance of permutation and partial dependence plot (PDP) to discuss their feasibility.ResultThe experiment results show that random forest obtains the highest accuracy for PPH amount prediction compared to other ML methods. Random forest reaches the mean absolute error of 21.7, less than 5.4%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} prediction error. It also gains the root mean squared error of 33.75, less than 9.3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} prediction error. On the other hand, the experimental results also disclose indicators that contributed most to PPH prediction, including Ca, hemoglobin, white blood cells, platelets, Na, and K.ConclusionIt effectively predicts the amount of PPH during a cesarean section by ML methods, especially random forest. With the above insight, ML predicting PPH amounts provides early warning for clinicians, thus reducing complications and improving cesarean sections’ safety. Furthermore, the importance of ML and permutation, complemented by incorporating PDP, promises to provide clinicians with a transparent indication of individual risk prediction.

Gastrointestinal tract perforation after radiofrequency ablation for hepatic tumor: Incidence and risk factors

ObjectiveWe analyzed the incidence and mortality rate of gastrointestinal (GI) tract perforation after radiofrequency ablation (RFA) for hepatic tumors and assess its risk factors. MethodsThis retrospective cohort study included 4799 patients with malignant tumors who underwent RFA (n = 7206). Sixty-nine cases of thermal injury to the GI tract were identified via a search of the electronic medical record system using index terms and divided into two groups according to the thermal injury with (n = 8) or without (n = 61) GI tract perforation based on follow-up CT reports. The risk factors for GI tract perforation were identified via multivariable logistic regression analysis using clinical, technical, and follow-up CT findings. ResultsThe incidence of thermal injury to the GI tract and GI tract perforation was 0.96 % (69/7206) and 0.11 % (8/7206), respectively. The type of adjacent GI tract and history of diabetes mellitus differed significantly between the two groups (p < 0.05). The index tumor being located around the small intestine was the only significant risk factor for GI tract perforation after ablation (Odds ratio, 22.69; 95 % confidence interval, 2.59–198.34; p = 0.005 [reference standard, stomach]). All perforations were not identified on CT images immediately after RFA. The median time to detection was 20 days (range, 3–41 days). Two patients (25 %, 2/8) died due to perforation-related complications. ConclusionGI tract perforation after RFA for hepatic tumors is rare; however, it is associated with high mortality. Thus, careful follow-up is required after RFA if the index tumor is located around the small intestine.

Comparing Hospital Length of Stay Between Persons With LEP and English-Speaking Patients in a Large Rural Academic Medical Center.

Patients with limited English proficiency that are hospitalized without regular access to professional medical interpreters have a longer length of stay (LOS).1 The authors studied the difference in LOS between English-speaking patients and patients with limited English proficiency in New Hampshire's only academic trauma medical center. The authors also examined race, ethnicity, and distance of residence from hospital. Retrospective data were queried from EPIC, the electronic medical record system used by the authors. Queried data focused on inpatient hospitalizations between January 1, 2019, and December 31, 2021. Patient primary language was grouped into English, Spanish, and other non-English language. Spanish-speaking patients live on average 39.6 miles farther from a hospital than English-speaking patients and have a 0.34 lower case mix index. After English, Spanish is the second-most frequently spoken language. Regression analyses found language to be a significant factor in LOS, LOS variance, and case mix index. A 2.34-day longer LOS for Spanish-speaking patients demonstrates an important health care disparity warranting further attention.

Combined nutritional status and activities of daily living disability is associated with one-year mortality after hip fracture surgery for geriatric patients: a retrospective cohort study

ObjectiveWe aimed to explore the association combined nutritional status and activities of daily living disability with all-cause mortality of older adults with hip fracture in the first year after hospitalization.MethodsThis is a single-center retrospective cohort study in older adults with hip fracture patients. Clinical data and laboratory results were collected from electronic medical record system of our hospital (2014–2021). The endpoint of this study was all-cause mortality in the first year after hospitalization.ResultsA total of 303 older adults were enrolled and all-cause mortality was 21.8%. The study population was categorized by CONUT score. Patients in CONUT score 5–12 had a higher age, ASA status, CRP and creatinine level, more patients with history of fracture, pneumonia and delirium, meanwhile, lower BMI and ADL score, lower hemoglobin, lymphocyte, total protein, albumin, triglyceride, total cholesterol and one year survival than those in CONUT score 0–4 (all P < 0.05). Multivariable Cox analysis showed that BMI, ADL score and CONUT score were independent risk factors for all-cause mortality of hip fracture in older adults (HR (95% CI):2.808(1.638, 4.814), P < 0.001; 2.862(1.637, 5.003), P < 0.001; 2.322(1.236, 4.359), P = 0.009, respectively). More importantly, the combined index of CONUT and ADL score had the best predictive performance based on ROC curve (AUC 0.785, 95% CI: 0.734–0.830, P < 0.0001). Kaplan-Meier survival curves for all-cause mortality showed that patients with CONUT score increase and ADL score impairment had a higher mortality rate at 1 year compared to CONUT score decrease and ADL score well (Log Rank χ2 = 45.717, P < 0.0001).ConclusionsCombined CONUT and ADL score is associated with one-year mortality after hip fracture surgery for geriatric patients.

Efficient and Secure EMR Storage and Sharing Scheme Based on Hyperledger Fabric and IPFS

This study examines the issues of privacy protection, data security, and query efficiency in blockchain-based electronic medical record (EMR) sharing. It proposes a secure storage and sharing scheme for EMR based on Hyperledger Fabric and the InterPlanetary File System (IPFS). To mitigate the privacy risks of data mining that could reveal patient identities, we establish an attribution channel in Hyperledger Fabric to store EMR ownership information and a data channel to store the storage location, digest, and usage records of medical data. Encrypted medical data are stored in the IPFS. To improve query efficiency in the blockchain, we integrate queryable medical data attributes into a composite key for conditional queries, avoiding complex data filtering processes. Additionally, we use a zero-knowledge proof combined with smart contracts for decentralized identity verification, eliminating reliance on third-party centralized verification services and enhancing system security. We also integrate AES and proxy re-encryption techniques to ensure data security during sharing. This scheme provides a more secure, efficient, and privacy-preserving approach for EMR systems, with significant practical implications and broad application potential.

Risk Factors for Ten-Year Risk of Osteoporosis in Type 2 DM Patients Attending Tikur Anbessa Specialized Hospital Diabetic Center Cross-sectional Study

&amp;lt;i&amp;gt;Background&amp;lt;/i&amp;gt;: Type 2 diabetes mellitus (T2DM) is a major contributing factor to osteoporotic fractures via different mechanisms. This study assessed the ten-year risk of osteoporosis and associated factors for osteoporotic fractures in T2DM patients. &amp;lt;i&amp;gt;Methods&amp;lt;/i&amp;gt;: Data from 175 type diabetes mellites (T2DM) patients over 40 years attending a diabetes clinic at Tikur Anbessa Specialized Hospital (TASH) were collected. Demographic information, diabetic complications, blood sugar levels, and other medical illnesses were collected by a structured questionnaire and from an electronic medical record system. The 10-year fracture risk assessment (FRAX) tool was used without bone mineral density (BMD) measurement. multivariate logistic regression was used to analyze factors associated with fragility fractures. &amp;lt;i&amp;gt;Results&amp;lt;/i&amp;gt;: Half the participants were female, with a median age of 60. Most were married, well-educated, and urban residents. The median duration of diabetes was 11 years. The median FRAX score indicated a moderate 10-year risk of hip fracture (≥3%) and a high risk of major osteoporotic fracture (≥20%). Overall, 30.9% of patients had a high 10-year risk of osteoporotic fracture. The majority (78.3%) had macrovascular complications, with neuropathy, retinopathy, and nephropathy being the common ones. Higher FBS, higher HbA1c, and the presence of macrovascular complications were significantly associated with a higher risk of fractures. &amp;lt;i&amp;gt;Conclusion&amp;lt;/i&amp;gt;: This study found a high prevalence (30.9%) of a 10-year risk of osteoporotic fractures in T2 DM patients. Poor glycemic control (higher HbA1c and FBS) and the presence of macrovascular complications were significantly associated with an increased 10-year osteoporotic fracture risk.

Inpatient case characteristics of SGLT2 inhibitor-associated diabetic ketoacidosis: a retrospective study

ObjectivesDiabetic ketoacidosis (DKA) is a serious complication in patients treated with sodium-glucose co-transporter 2 inhibitors (SGLT2i). The aim of this study was to investigate the relationship between SGLT2i and the...

Early predictive value of lipocalin-type prostaglandin D synthase for 28-day mortality in cardiac arrest patients: study protocol for a prospective study

IntroductionPublic training in cardiopulmonary resuscitation and treatment in emergency and intensive care unit have made tremendous progress. However, cardiac arrest remains a major health burden worldwide, with brain damage being...

Telehealth With Comprehensive Live-Fed Real-World Data as a Patient Care Platform for Lung Cancer: Implementation and Evaluation Study.

Telehealth has emerged as a popular channel for providing outpatient services in many countries. However, the majority of telehealth systems focus on operational functions and offer only a sectional patient journey at most. Experiences with incorporating longitudinal real-world medical record data into telehealth are valuable but have not been widely shared. The feasibility and usability of such a telehealth platform, with comprehensive, real-world data via a live feed, for cancer patient care are yet to be studied. The primary purpose of this study is to understand the feasibility and usability of cancer patient care using a telehealth platform with longitudinal, real-world data via a live feed as a supplement to hospital electronic medical record systems specifically from physician's perspective. A telehealth platform was constructed and launched for both physicians and patients. Real-world data were collected and curated using a comprehensive data model. Physician activities on the platform were recorded as system logs and analyzed. In February 2023, a survey was conducted among the platform's registered physicians to assess the specific areas of patient care and to quantify their before and after experiences, including the number of patients managed, time spent, dropout rate, visit rate, and follow-up data. Descriptive and inferential statistical analyses were performed on the data sets. Over a period of 15 months, 16,035 unique users (13,888 patients, 1539 friends and family members, and 174 physician groups with 608 individuals) registered on the platform. More than 382,000 messages including text, reminders, and pictures were generated by physicians when communicating with patients. The survey was completed by 78 group leaders (45% of the 174 physician groups). Of the participants, 84% (65.6/78; SD 8.7) reported a positive experience, with efficient communication, remote supervision, quicker response to questions, adverse event prevention, more complete follow-up data, patient risk reduction, cross-organization collaboration, and a reduction in in-person visits. The majority of the participants (59/78, 76% to 76/78, 97.4%) estimated improvements in time spent, number of patients managed, the drop-off rate, and access to medical history, with the average ranging from 57% to 105%. When compared with prior platforms, responses from physicians indicated better experiences in terms of time spent, the drop-off rate, and medical history, while the number of patients managed did not significantly change. This study suggests that a telehealth platform, equipped with comprehensive, real-world data via a live feed, is feasible and effective for cancer patient care. It enhances inpatient management by improving time efficiencies, reducing drop-off rates, and providing easy access to medical history. Moreover, it fosters a positive experience in physician-patient interactions.

The persistent benefits of decreasing default pill counts for postoperative narcotic prescriptions.

In 2017, a university-based academic healthcare system changed the opioid default pill count from 30 to 12 pills. Modifying the electronic default pill count influences short-term clinician prescribing practices. We sought to understand the long-term impact on postoperative opioid prescribing habits after an opioid default pill count reduction. A retrospective electronic medical record system (EMRS) review was conducted in a healthcare system comprised of seven affiliated hospitals. Patients who underwent a surgical procedure and were prescribed an opioid on discharge between 2017-2021 were evaluated. All prescriptions were converted into morphine equivalents (MME). Analyses were performed with the chi-square test and Bonferonni adjusted t-test. 191,379 surgical procedures were studied. The average quantity of opioids prescribed decreased from 32 oxycodone 5 mg tablets in 2017 to 21 oxycodone 5 mg tablets in 2021 (236 MME to 154 MME, p<0.001). The percentage of patients obtaining a refill within 90 days of surgery varied between 18.3% and 19.9% (p<0.001). Patients with a pre-existing opioid prescription and opioid-naïve patients both had significant reductions in prescription quantities above the default MME (79.7% to 60.6% vs. 65.3% to 36.9%, p<0.001). There was no significant change in refills for both groups (pre-existing 36.7% to 38.3% (p = 0.1) vs naïve 15.0% to 15.3% (p = 0.29)). The benefits of decreasing the default opioid pill count continue to accumulate long after the original change. Physician uptake of small changes to default EMRS practices represents a sustainable and effective intervention to reduce the quantities of postoperative opioids prescribed without deleterious effects on outpatient opiate requirements.

Artificial intelligence–aided lung cancer screening in routine clinical practice: A pilot of LungFlag at Geisinger.

e13604 Background: Use of low-dose computed tomography (LDCT) in lung cancer screening is recommended for early detection and can reduce mortality. LungFlag (Medial-EarlySign) is a machine-learning risk prediction model that identifies individuals at high risk of non-small cell lung cancer so their care team may recommend LDCT screening. The LungFlag model was developed using data from Kaiser Permanente Southern California and is being implemented in a pilot at Geisinger. Here we provide an overview of the clinical workflow for the LungFlag pilot. Methods: Geisinger has implemented LungFlag into routine clinical practice via integration with the electronic medical record system. This pilot is examining the performance and clinical impact of LungFlag in the first year. LungFlag runs every month to provide risk evaluation for individuals 50 to 80 years old who are eligible for annual lung cancer screening according to US Preventive Services Task Force recommendations. Eligible individuals have a 20 pack-year smoking history, no lung cancer history, and currently smoke or quit within the past 15 years. Patients with cancer history in the past 5 years and those screened or scheduled for screening in the past year are excluded. LungFlag identifies the top 30 individuals with the highest LungFlag scores per month (high-risk patients) and refers them for targeted outreach from a lung cancer screening program nurse navigator. A positive LungFlag result prompts nurse navigator chart review, patient outreach, and coordination with the primary care provider. Flagged individuals are contacted (up to 3 phone calls) and encouraged to receive lung cancer screening. Individuals not flagged by the model (non–high-risk patients) receive usual care consisting of reminders for lung cancer screening during primary care visits without additional targeted outreach and high-risk prioritization. Results: The LungFlag pilot was initiated in August 2023 and will continue until August 2024. As of January 2024, risk profiles of &gt;12,000 patients were analyzed and 180 high-risk patients were identified. Conclusions: This pilot is the first evaluation of the implementation process for the LungFlag model in routine clinical practice. After the pilot, a retrospective observational study is planned to further assess the impact of LungFlag and the associated clinical workflow in identifying high-risk individuals and increasing compliance with LDCT screening among high-risk individuals.

Geospatial analysis of the distribution of uveal melanoma patients at a referral center in the United States.

e21566 Background: Approximately 2500 new uveal melanoma (UM) cases (5.2 cases per million population) are diagnosed yearly in the United States. We previously identified three unique geospatial accumulations of UM in North Carolina, Alabama, and New York based on our clinical experience. Such unexpected findings prompted us to conduct a more systematic evaluation of geospatial accumulations of UM patients at our institution. Methods: Through the electronic medical record system, we identified patients seen at our institution with a diagnosis of UM. Identified living patients and family of deceased patients were either sent an e-mail or paper letter with an internet link to a survey. The survey asked for the patient’s name, date of birth, sex, date of primary UM diagnosis, address at time of UM diagnosis and number of years at that address, and all previous addresses and dates of residence prior to the UM diagnosis. Using these addresses, ArcGIS and R software was used to analyze the geospatial distribution of our UM patients. The data was supplemented with 2020 American Community Survey census estimates at the state, county, and census tract level to estimate population-based rates of UM. Results: We identified 2718 UM patients in our clinical database, and a total of 726 participants completed the survey with a total of 2939 US addresses. The majority of addresses were precise to the street address level (77.9%). At the time of UM diagnosis, patients had lived at their current address for a median of 16 years. Pennsylvania and the neighboring states expectedly made up the majority (63.6%) of our patients, but about 1/3 of our patients resided in other states at the time of their UM diagnosis (total of 42 different states). Several counties presented elevated rates of UM with ≥5 case per 100,000 persons. We observed a group of counties in central Pennsylvania, at the border of Pennsylvania and New York, and in upper New York by the Finger Lakes with notably elevated rates of UM, which was consistent with our clinical observations at our institution. Several neighboring counties in Kentucky and Virginia also presented elevated rates. Conclusions: Through this pilot project, we have demonstrated that it is possible to collect lifetime residency information from UM patients in order to map their geospatial distribution in the US. Furthermore, although institutional bias toward referring physicians should be considered, our geospatial analysis identified accumulations of UM in areas similar to our clinical concerns. The results of our study warrant further investigations into environmental influences on UM development. Our future goal is to extend our approach through national and international collaborations to increase the number of participants in the analysis and to minimize institutional bias.

Temporal dynamics and prognostic significance of cancer free status in patients with intermediate stage hepatocellular carcinoma: A multicenter cohort study.

e16236 Background: A proportion of patients with intermediate stage hepatocellular carcinoma (HCC) can achieve cancer free status (CFS) during treatment, the prognostic value of CFS across the period of dynamic surveillance and treatment remained unknown. Methods: This longitudinal cohort study examined data from the electronic medical record system of four hospitals in China between January 1, 2007 to May 31, 2019. The data from Sun Yat-sen University Cancer Center served as the derivation cohort and other centers as testing cohort. The time-series data were converted into data of time slices, with an interval of three months. Image CFS is defined as patients with no evidence of disease based on imaging exams after treatment and Image-Bio CFS is defined as achievement of Image CFS, together with normal AFP level. Based on the dynamic changes of disease during treatment, patients at specific time slice were classified into either “Arrive”, “Maintain”, or “Not reached” CFS subgroups. The correlations between CFS subgroups and overall survival (OS) were determined by Cox regression. Results: A total of 945 (42.2%) and 741 (33.1%) patients in derivation cohort reached Image CFS and Image-Bio CFS during treatment, respectively. The corresponding rates for Image CFS and Image-Bio CFS in testing cohort were 155 (37.4%) and 130 (31.4%), respectively. Maintaining Image CFS or Image-Bio CFS, rather than just arrive Image CFS or Image-Bio CFS, had stable predictive value for improved OS across different time slices. The merged Hazard ratio of Maintain Image-Bio CFS was 0.23 (95%CI, 0.20-0.25, P &lt; 0.001). The patients achieved Image-Bio CFS could be further classified into three subgroups with differential prognosis based on duration of CFS (≤ 4.5months; 4.5-18.0 months; &gt; 18.0 months). Maintaining Image-Bio CFS for more than 18.0 months predicted long term survival (5-year OS: 91.2% in derivation cohort, 94.7% in testing cohort). Conclusions: Maintaining CFS, rather than just arrive CFS, is a key marker of favorable survival during dynamic management of intermediate stage HCC. A duration of Image-Biochemical CFS for more than eighteen months predicts long-term survival.