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Search All Research Studies
Topics
- Clinical Decision Support (CDS) (1)
- Communication (1)
- Community-Acquired Infections (2)
- Cultural Competence (1)
- Elderly (2)
- Electronic Health Records (EHRs) (2)
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- Healthcare-Associated Infections (HAIs) (1)
- Health Information Technology (HIT) (2)
- (-) Home Healthcare (10)
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- (-) Risk (10)
AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 10 of 10 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
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
Hobensack M, Ojo M, Barrón Y
Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
The objectives of this study were to identify risk factors that home healthcare clinicians associate with patient deterioration and to understand clinicians’ response to and documentation of these risk factors. The authors interviewed multidisciplinary home healthcare clinicians and used directed content analysis to identify risk factors for deterioration. A total of 79 risk factors were identified by the clinicians, who responded most often by communicating with the prescribing provider or following up with patients and caregivers. Clinicians also acknowledged that social factors played a role in deterioration risk. The authors noted that, since most risk factors were documented in clinical notes, methods such as natural language processing are needed to extract them. They concluded that by providing a comprehensive list of risk factors grounded in clinician expertise and mapped to standardized terminologies, the results of their study supported the development of an early warning system for patient deterioration.
AHRQ-funded; HS027742.
Citation: Hobensack M, Ojo M, Barrón Y .
Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
J Am Med Inform Assoc 2022 Apr 13;29(5):805-12. doi: 10.1093/jamia/ocac023..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Home Healthcare, Risk, Hospitalization
Squires A, Ma C, Miner S
Assessing the influence of patient language preference on 30 day hospital readmission risk from home health care: a retrospective analysis.
In home health care, language barriers are understudied. Language barriers between patients and providers are known to affect a variety of patient outcomes. How a patient's language preference influences hospital readmission risk from home health care has yet to be determined. The objective of this retrospective cross-sectional study was to determine if home care patients' language preference is associated with their risk for hospital readmission from home health care within 30 days of hospital discharge.
AHRQ-funded; HS023593.
Citation: Squires A, Ma C, Miner S .
Assessing the influence of patient language preference on 30 day hospital readmission risk from home health care: a retrospective analysis.
Int J Nurs Stud 2022 Jan;125:104093. doi: 10.1016/j.ijnurstu.2021.104093..
Keywords: Cultural Competence, Home Healthcare, Hospital Readmissions, Risk, Communication
Song J, Woo K, Shang J
Predictive risk models for wound infection-related hospitalization or ED visits in home health care using machine-learning algorithms.
Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, in this paper, the authors created a more accurate description of a patient's condition by extracting risk factors from clinical notes to build predictive models to identify a patient's risk of wound infection in HHC.
AHRQ-funded; HS024915.
Citation: Song J, Woo K, Shang J .
Predictive risk models for wound infection-related hospitalization or ED visits in home health care using machine-learning algorithms.
Adv Skin Wound Care 2021 Aug;34(8):1-12. doi: 10.1097/01.Asw.0000755928.30524.22..
Keywords: Home Healthcare, Injuries and Wounds, Risk, Hospitalization
Russell D, Dowding D, Trifilio M
Individual, social, and environmental factors for infection risk among home healthcare patients: a multi-method study.
This paper is a study of nurse perceptions of individual, social, and environmental factors for infection risk among home healthcare (HHC) patients and also identifies the frequency of environmental barriers to infection prevention and control in HHC. Data were collected in 2017-2018 from qualitative interviews with 50 HHC nurses and structured observations of nurse visits to patients’ homes (n = 400). Perceived infection risk among patients was characterized as being influenced by knowledge of and attitudes towards infection prevention and engagement in hygiene practices, receipt of support from informal caregivers and nurse interventions aimed at cultivating infection control knowledge and practices, and the home environment. Frequent environmental barriers observed during visits to patients included clutter (39.5%), poor lighting (38.8%), dirtiness (28.5%), and pets (17.2%).
AHRQ-funded; HS024723.
Citation: Russell D, Dowding D, Trifilio M .
Individual, social, and environmental factors for infection risk among home healthcare patients: a multi-method study.
Health Soc Care Community 2021 May;29(3):780-88. doi: 10.1111/hsc.13321..
Keywords: Home Healthcare, Community-Acquired Infections, Risk, Provider: Nurse, Provider
Dowding D, Russell D, McDonald MV
"A catalyst for action": factors for implementing clinical risk prediction models of infection in home care settings.
This study looked at how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses. It was a qualitative study using semi-structured interviews with 50 home care nurses. The interviews were audio-taped and transcribed with data evaluation using thematic analysis. Findings indicated that the nurses would find a clinical risk prediction model useful, as long as it provided both context around the reasons why a patient was deemed to be high risk and provided some guidance for action.
AHRQ-funded; HS024723.
Citation: Dowding D, Russell D, McDonald MV .
"A catalyst for action": factors for implementing clinical risk prediction models of infection in home care settings.
J Am Med Inform Assoc 2021 Feb 15;28(2):334-41. doi: 10.1093/jamia/ocaa267..
Keywords: Home Healthcare, Nursing, Risk, Healthcare-Associated Infections (HAIs), Prevention, Provider: Nurse, Provider
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
McDonald MV, Feldman PH, Barron-Vaya Y
Outcomes of clinical decision support (CDS) and correlates of CDS use for home care patients with high medication regimen complexity: a randomized trial.
The researchers assessed the outcomes of a clinical decision support (CDS) intervention designed for home care patients with high medication regimen complexity (MRC) and examined correlates of CDS use. They found that eighty-two percent of intervention nurses used the CDS but for only 42 percent of their patients. Among intervention patients, CDS use (vs. non-use) was associated with reduced MRC and hospitalization.
AHRQ-funded; HS017837.
Citation: McDonald MV, Feldman PH, Barron-Vaya Y .
Outcomes of clinical decision support (CDS) and correlates of CDS use for home care patients with high medication regimen complexity: a randomized trial.
J Eval Clin Pract 2015 May 26;22(1):10-19. doi: 10.1111/jep.12383.
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Keywords: Clinical Decision Support (CDS), Home Healthcare, Medication, Risk