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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 5 of 5 Research Studies DisplayedSong J, Min SH, Chae S
Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.
The purpose of this study was to characterize risk factor patterns documented in home health care (HHC) clinical notes and explore their relationships with hospitalizations or emergency department (ED) visits. The researchers analyzed data for 73,350 episodes of care from one large HHC organization utilizing dynamic time warping and hierarchical clustering analysis to characterize the patterns of risk factors over time documented in clinical notes. The study found that six temporal clusters emerged, reflecting varying patterns in how risk factors were documented. Patients with a sharp increase in documented risk factors over time had a 3 times greater probability of hospitalization or ED visit than patients with no documented risk factors. The majority of risk factors were found in the physiological domain, and a minority were found in the environmental domain.
AHRQ-funded; HS027742.
Citation: Song J, Min SH, Chae S .
Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.
J Am Med Inform Assoc 2023 Oct 19; 30(11):1801-10. doi: 10.1093/jamia/ocad101..
Keywords: Emergency Department, Hospitalization, Home Healthcare, Risk
Min SH, Song J, Evans L
Home healthcare patients with distinct psychological, cognitive, and behavioral symptom profiles and at-risk subgroup for hospitalization and emergency department visits using latent class analysis.
The purpose of this study was to explore subgroups of older adults receiving home healthcare services with similar psychological, cognitive, and behavioral symptom profiles and an at-risk subgroup for future hospitalization and emergency department visits as an indicator of underdiagnosis or undertreatment. The three-class model applied in the study consisted of Class 1: "Moderate psychological symptoms without behavioral issues," Class 2: "Severe psychological symptoms with behavioral issues," and Class 3: "Mild psychological symptoms without behavioral issues." The study found that Class 1 patients had 1.14 higher odds and Class 2 patients had 1.26 higher odds of being hospitalized or visiting emergency departments compared to Class 3. The researchers discovered significant differences in individual characteristics such as age, gender, race/ethnicity, and insurance.
AHRQ-funded; HS027742.
Citation: Min SH, Song J, Evans L .
Home healthcare patients with distinct psychological, cognitive, and behavioral symptom profiles and at-risk subgroup for hospitalization and emergency department visits using latent class analysis.
Clin Nurs Res 2023 Sep; 32(7):1021-30. doi: 10.1177/10547738231183026..
Keywords: Home Healthcare, Emergency Department, Hospitalization, Elderly
Song J, Chae S, Bowles KH
The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.
The purpose of this retrospective cohort study was to identify risk factor clusters in home health care and assess whether the clusters are related with hospitalizations or emergency department visits. The researchers included 61,454 patients associated with 79,079 episodes receiving home health care from one of the largest home health care organizations in the U.S. The study found that a total of 11.6% of home health episodes resulted in hospitalizations or emergency department visits. Three clusters were formed by the risk factors: 1) Cluster 1- a combination of risk factors related to situations where patients may experience increased pain ("impaired physical comfort with pain"). 2) Cluster 2 - characterized by multiple comorbidities or other risks for hospitalization (e.g., prior falls, called "high comorbidity burden"). 3) Cluster 3 - "impaired cognitive/psychological and skin integrity" which includes dementia or skin ulcer. The risk of hospitalizations or emergency department visits increased by 1.95 times for Cluster 2 and by 2.12 times for Cluster 3 when compared to cluster 1. The study concluded that Varying combinations of risk factors affected the likelihood of negative outcomes.
AHRQ-funded; HS027742.
Citation: Song J, Chae S, Bowles KH .
The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.
J Adv Nurs 2023 Feb; 79(2):593-604. doi: 10.1111/jan.15498..
Keywords: Emergency Department, Hospitalization, Home Healthcare, Risk
Topaz M, Woo K, Ryvicker M
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
About 30% of home healthcare patients are hospitalized or visit an emergency department (ED) during a home healthcare (HHC) episode. Novel data science methods are increasingly used to improve identification of patients at risk for negative outcomes. The aim of the study was to identify patients at heightened risk hospitalization or ED visits using HHC narrative data (clinical notes).
AHRQ-funded; HS027742.
Citation: Topaz M, Woo K, Ryvicker M .
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
Nurs Res 2020 Nov/Dec;69(6):448-54. doi: 10.1097/nnr.0000000000000470..
Keywords: Elderly, Home Healthcare, Emergency Department, Hospitalization, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Shang J, Russell D, Dowding D
A predictive risk model for infection-related hospitalization among home healthcare patients.
Infection prevention is a high priority for home healthcare (HHC), but tools are lacking to identify patients at highest risk of developing infections. The purpose of this study was to develop and test a predictive risk model to identify HHC patients at risk of an infection-related hospitalization or emergency department visit. A nonexperimental study using secondary data was conducted.
AHRQ-funded; HS024723.
Citation: Shang J, Russell D, Dowding D .
A predictive risk model for infection-related hospitalization among home healthcare patients.
J Healthc Qual 2020 May/Jun;42(3):136-47. doi: 10.1097/jhq.0000000000000214..
Keywords: Elderly, Home Healthcare, Infectious Diseases, Community-Acquired Infections, Risk, Hospitalization, Emergency Department