Dataset Information

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

ABSTRACT: This study developed and validated a risk-scoring model, with a particular emphasis on medication-related factors, to predict emergency department (ED) visits among older Korean adults (aged 65 and older) undergoing anti-neoplastic therapy. Utilizing national claims data, we constructed two cohorts: the development cohort (2016-2018) with 34,642 patients and validation cohort (2019) with 10,902 patients. The model included a comprehensive set of predictors: demographics, cancer type, comorbid conditions, ED visit history, and medication use variables. We employed the least absolute shrinkage and selection operator (LASSO) regression to refine and select the most relevant predictors. Out of 120 predictor variables, 12 were integral to the final model, including seven related to medication use. The model demonstrated acceptable predictive performance in the validation cohort with a C-statistic of 0.76 (95% CI 0.74-0.77), indicating reasonable calibration. This risk-scoring model, after further clinical validation, has the potential to assist healthcare providers in the effective management and care of older patients receiving anti-neoplastic therapy.

SUBMITTER: Suh Y

PROVIDER: S-EPMC10794170 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

Suh Yewon Y Jeong Jonghyun J Park Soh Mee SM Heo Kyu-Nam KN Lee Mee Yeon MY Ah Young-Mi YM Kim Jin Won JW Kim Kwang-Il KI Lee Ju-Yeun JY

Scientific reports 20240117 1

This study developed and validated a risk-scoring model, with a particular emphasis on medication-related factors, to predict emergency department (ED) visits among older Korean adults (aged 65 and older) undergoing anti-neoplastic therapy. Utilizing national claims data, we constructed two cohorts: the development cohort (2016-2018) with 34,642 patients and validation cohort (2019) with 10,902 patients. The model included a comprehensive set of predictors: demographics, cancer type, comorbid co ...[more]

PMID: 38233529

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Project description:ObjectivesAdministrative claims data sets are often used for emergency care research and policy investigations of healthcare resource utilization, acute care practices, and evaluation of quality improvement interventions. Despite the high profile of emergency department (ED) visits in analyses using administrative claims, little work has evaluated the degree to which existing definitions based on claims data accurately captures conventionally defined hospital-based ED services. We sought to construct an operational definition for ED visitation using a comprehensive Medicare data set and to compare this definition to existing operational definitions used by researchers and policymakers.MethodsWe examined four operational definitions of an ED visit commonly used by researchers and policymakers using a 20% sample of the 2012 Medicare Chronic Condition Warehouse (CCW) data set. The CCW data set included all Part A (hospital) and Part B (hospital outpatient, physician) claims for a nationally representative sample of continuously enrolled Medicare fee-for-services beneficiaries. Three definitions were based on published research or existing quality metrics including: 1) provider claims-based definition, 2) facility claims-based definition, and 3) CMS Research Data Assistance Center (ResDAC) definition. In addition, we developed a fourth operational definition (Yale definition) that sought to incorporate additional coding rules for identifying ED visits. We report levels of agreement and disagreement among the four definitions.ResultsOf 10,717,786 beneficiaries included in the sample data set, 22% had evidence of ED use during the study year under any of the ED visit definitions. The definition using provider claims identified a total of 4,199,148 ED visits, the facility definition 4,795,057 visits, the ResDAC definition 5,278,980 ED visits, and the Yale definition 5,192,235 ED visits. The Yale definition identified a statistically different (p < 0.05) collection of ED visits than all other definitions including 17% more ED visits than the provider definition and 2% fewer visits than the ResDAC definition. Differences in ED visitation counts between each definition occurred for several reasons including the inclusion of critical care or observation services in the ED, discrepancies between facility and provider billing regulations, and operational decisions of each definition.ConclusionCurrent operational definitions of ED visitation using administrative claims produce different estimates of ED visitation based on the underlying assumptions applied to billing data and data set availability. Future analyses using administrative claims data should seek to validate specific definitions and inform the development of a consistent, consensus ED visitation definitions to standardize research reporting and the interpretation of policy interventions.

Project description:Background and objectivesMany older adults adopt equipment to address physical limitations and reduce dependence on others to complete basic activities of daily living. Although a few prior studies have considered injuries associated with assistive devices for older adults, those studies focused on older adults' health and functional risks for injury. There is limited analysis of older adult injuries involving defective or malfunctioning assistive devices.Research design and methodsData from this study are from the National Electronic Surveillance System All Injury Program which collected data on consumer product-related injuries from a probability sample of 66 hospital Emergency Departments across the United States. Data from 30 776 older adult Emergency Department (ED) injury narratives from 2016 to 2020 were coded according to the assistive device involved and whether malfunctioning led to the injury. The study team manually examined all narratives in which the assistive device was coded to have malfunctioned.ResultsA total of 10 974 older adult ED cases were treated for 12 488 injuries involving a defective device. Injuries included 4 212 head and neck injuries (eg, concussion), 4 317 trunk injuries (eg, hip fractures), and 3 959 arm or leg injuries (eg, leg fracture). Of these patients, 4 586 were admitted to a hospital ward for further evaluation and treatment. Seventy percent of these patients were injured while using a walker; in contrast, wheelchairs were implicated in only 4% of the above cases. Design flaws were identified in 8 158 cases and part breakage/decoupling incidents in 2 816 cases.Discussion and implicationsOur findings provide evidence that assistive devices are actively involved in older adult injuries. Further research is needed to reduce injuries associated with assistive devices by educating patients and their careproviders about device use and assembly and developing effective methods for informing manufacturers about malfunctioning devices.

Project description:BackgroundUnscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs.ObjectiveThis aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs.MethodsWe used stratified and randomized data from Taiwan's National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records.ResultsThe decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED.ConclusionsMedical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.

Project description:Background and objectivesIn 2011, there were approximately 131 million visits to an emergency department in the United States. Emergency department visits have increased over time, far outpacing growth of the general population. There is a paucity of data evaluating emergency department visits among kidney transplant recipients. We sought to evaluate the incidence and risk factors for emergency department visits after initial hospital discharge after transplantation in the United States.Design, setting, participants, & measurementsWe identified 10,533 kidney transplant recipients from California, New York, and Florida between 2009 and 2012 using the State Inpatient and Emergency Department Databases included in the Healthcare Cost and Utilization Project. We used multivariable Poisson and Cox proportional hazard models to evaluate adjusted incidence rates and time to emergency department visits after transplantation.ResultsThere were 17,575 emergency department visits over 13,845 follow-up years (overall rate =126.9/100 patient-years; 95% confidence interval, 125.1 to 128.8). The cumulative incidences of emergency department visits at 1, 12, and 24 months were 12%, 40%, and 57%, respectively, with median time =19 months; 48% of emergency department visits led to hospital admission. Risk factors for higher emergency department rates included younger age, women, black and Hispanic race/ethnicity, public insurance, depression, diabetes, peripheral vascular disease, and emergency department use before transplant. There was wide variation in emergency department visits by individual transplant center (10th percentile =70.0/100 patient-years; median =124.6/100 patient-years; and 90th percentile =187.4/100 patient-years).ConclusionsThe majority of kidney transplant recipients will visit an emergency department in the first 2 years post-transplantation, with significant variation by patient characteristics and individual centers. As such, coordination of care through the emergency department is a critical component of post-transplant management, and specific acumen of transplant-related care is needed among emergency department providers. Additional research assessing best processes of care for post-transplant management and health care expenditures and outcomes associated with emergency department visits for transplant recipients are warranted.

Project description:Background/objectiveEmergency department (ED) visits have declined while excess mortality, not attributable to COVID-19, has grown. It is not known whether older adults are accessing emergency care differently from their younger counterparts. Our objective was to determine patterns of ED visit counts for emergent conditions during the COVID-19 pandemic for older adults.DesignRetrospective, observational study.SettingObservational analysis of ED sites enrolled in a national clinical quality registry.ParticipantsOne hundred and sixty-four ED sites in 33 states from January 1, 2019 to November 15, 2020.Main outcome and measuresWe measured daily ED visit counts for acute myocardial infarction (AMI), stroke, sepsis, fall, and hip fracture, as well as deaths in the ED, by age categories. We estimated Poisson regression models comparing early and post-early pandemic periods (defined by the Centers for Disease Control and Prevention) to the pre-pandemic period. We report incident rate ratios to summarize changes in visit incidence.ResultsFor AMI, stroke, and sepsis, the older (75-84) and oldest old (85+ years) had the greatest decline in visit counts initially and the smallest recovery in the post-early pandemic periods. For falls, visits declined early and partially recovered uniformly across age categories. In contrast, hip fractures exhibited less change in visit rates across time periods. Deaths in the ED increased during the early pandemic period, but then fell and were persistently lower than baseline, especially for the older (75-84) and oldest old (85+ years).ConclusionsThe decline in ED visits for emergent conditions among older adults has been more pronounced and persistent than for younger patients, with fewer deaths in the ED. This is concerning given the greater prevalence and risk of poor outcomes for emergent conditions in this age group that are amenable to time-sensitive ED diagnosis and treatment, and may in part explain excess mortality during the COVID-19 era among older adults.

Project description:Background Identification of stroke patients at increased risk of emergency department (ED) visits or hospital admissions allows implementation of mitigation strategies. We evaluated the ability of the Patient-Reported Outcomes Information Measurement System (PROMIS) patient-reported outcomes (PROs) collected as part of routine care to predict 1-year emergency department (ED) visits and admissions when added to other readily available clinical variables. Methods and Results This was a cohort study of 1696 patients with ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage, or transient ischemic attack seen in a cerebrovascular clinic from February 17, 2015, to June 11, 2018, who completed the following PROs at the visit: Patient Health Questionnaire-9, Quality of Life in Neurological Disorders cognitive function, PROMIS Global Health, sleep disturbance, fatigue, anxiety, social role satisfaction, physical function, and pain interference. A series of logistic regression models was constructed to determine the ability of models that include PRO scores to predict 1-year ED visits and all-cause and unplanned admissions. In the 1 year following the PRO encounter date, 1046 ED visits occurred in 548 patients; 751 admissions occurred in 453 patients. All PROs were significantly associated with future ED visits and admissions except PROMIS sleep. Models predicting unplanned admissions had highest optimism-corrected area under the curve (range, 0.684-0.724), followed by ED visits (range, 0.674-0.691) and then all-cause admissions (range, 0.628-0.671). PROs measuring domains of mental health had stronger associations with ED visits; PROs measuring domains of physical health had stronger associations with admissions. Conclusions PROMIS scales improve the ability to predict ED visits and admissions in patients with stroke. The differences in model performance and the most influential PROs in the prediction models suggest differences in factors influencing future hospital admissions and ED visits.

Project description:BackgroundOlder adults receiving home care have a higher risk of visiting the emergency department (ED) than community-dwelling older adults not receiving home care. This may result from a higher incidence of comorbidities and reduced functional autonomy in home care recipients. Since people receive different types of home care because of their different comorbidities and autonomy profiles, it is possible that distinguishing between the form of home care can help identify subpopulations with different risks for ED visits and help develop targeted interventions. This study aimed to compare the risk of visiting the ED in older adults receiving different forms of home care with those living at home without receiving home care in a national cohort in one year.MethodsA retrospective cohort study using claims data collected in 2019 on the Dutch population aged ≥ 65 years (N = 3,314,440) was conducted. Participants were classified as follows: no claimed home care (NO), household help (HH), personal care (PC), HH + PC, and nursing home care at home (NHH). The primary outcome was the number of individuals that visited the ED. Secondary outcomes were the number of individuals whose home care changed, who were institutionalized, or who died. Exploratory logistic regression was applied.ResultsThere were 2,758,093 adults in the NO group, 131,260 in the HH group, 154,462 in the PC group, 96,526 in the HH + PC group, and 34,612 in the NHH group. More ED visits were observed in the home care groups than in the NO group, and this risk increased to more than two-fold for the PC groups. There was a significant change to a more intensive form of home care, institutionalization, or death in all groups.ConclusionsDistinguishing between the form of home care older adults receive identifies subpopulations with different risks for ED visits compared with community-dwelling older adults not receiving home care on a population level. Home care transitions are frequent and mostly involve more intensive care or death. Although older adults not receiving home care have a lower risk of ED visits, they contribute most to the absolute volume of ED visits.

Dataset Information

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

Publications

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

Similar Datasets

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