Exploration of Medical Trajectories of Stroke Patients Based on Group-Based Trajectory Modeling

Abstract

A high mortality rate is an issue with acute cerebrovascular disease (ACVD), as it often leads to a high medical expenditure, and in particular to high costs of treatment for emergency medical conditions and critical care. In this study, we used group-based trajectory modeling (GBTM) to study the characteristics of various groups of patients hospitalized with ACVD. In this research, the patient data were derived from the 1 million sampled cases in the National Health Insurance Research Database (NHIRD) in Taiwan. Cases who had been admitted to hospitals fewer than four times or more than eight times were excluded. Characteristics of the ACVD patients were collected, including age, mortality rate, medical expenditure, and length of hospital stay for each admission. We then performed GBTM to examine hospitalization patterns in patients who had been hospitalized more than four times and fewer than or equal to eight times. The patients were divided into three groups according to medical expenditure: high, medium, and low groups, split at the 33rd and 66th percentiles. After exclusion of unqualified patients, a total of 27,264 cases (male/female = 15,972/11,392) were included. Analysis of the characteristics of the ACVD patients showed that there were significant differences between the two gender groups in terms of age, mortality rate, medical expenditure, and total length of hospital stay. In addition, the data were compared between two admissions, which included interval, outpatient department (OPD) visit after discharge, OPD visit after hospital discharge, and OPD cost. Finally, the differences in medical expenditure between genders and between patients with different types of stroke—ischemic stroke, spontaneous intracerebral hemorrhage (sICH), and subarachnoid hemorrhage (SAH)—were examined using GBTM. Overall, this study employed GBTM to examine the trends in medical expenditure for different groups of stroke patients at different admissions, and some important results were obtained. Our results demonstrated that the time interval between subsequent hospitalizations decreased in the ACVD patients, and there were significant differences between genders and between patients with different types of stroke. It is often difficult to decide when the time has been reached at which further treatment will not improve the condition of ACVD patients, and the findings of our study may be used as a reference for assessing outcomes and quality of care for stroke patients. Because of the characteristics of NHIRD, this study had some limitations; for example, the number of cases for some diseases was not sufficient for effective statistical analysis.

Longitudinal patterns and predictors of healthcare utilization among cancer patients on home-based palliative care in Singapore: a group-based multi-trajectory analysis

“…First, we determined trajectories for the number of ED visits, hospitalizations, and outpatient visits separately using group-based trajectory modelling (GBTM), with extensions to account for non-random patient attrition due to death [22,45]. GBTM uses maximum likelihood to identify latent subgroups of individuals with similar trajectories for a variable and has been used to describe healthcare trajectories in other populations [46][47][48]. Details of the trajectory analyses are in the additional file.…”

Short-Term Effects of Low-Level Ambient Air NO2 on the Risk of Incident Stroke in Enshi City, China

“…In this study, the subgroup analysis of age and sex revealed that males and the elderly were more susceptible to stroke when exposed to low-level ambient NO 2 in the air. Similarly, a study about hospital admissions in China found that the elderly were more susceptible to stroke than the non-elderly [ 46 ]; another study found that male stroke patients were more susceptible to changes in NO 2 concentrations than female patients [ 47 ]. However, some previous studies found different results regarding the susceptibility of age to stroke.…”

Diseases That Occur Prior to Spontaneous Intracerebral Hemorrhage: Identification of Predisposing and Risk Factors Using Lag Sequential Analysis

“…LSA is also employed to evaluate sequential and lag patterns of subjects with probabilities [14]. e Taiwan NHIRD contains longitudinal data, which have been used to support many epidemiology studies in different fields [1,2,8,9,22,23,25,26]. Recently, manifestations of the longitudinal data in the NHIRD were found.…”