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AHRQ Research Studies Date
Topics
- Central Line-Associated Bloodstream Infections (CLABSI) (2)
- Elderly (1)
- Electronic Health Records (EHRs) (2)
- Emergency Department (3)
- Healthcare-Associated Infections (HAIs) (2)
- Health Information Technology (HIT) (2)
- (-) Home Healthcare (9)
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- Hospital Readmissions (1)
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- Quality of Care (1)
- Risk (2)
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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.
Results
1 to 9 of 9 Research Studies DisplayedWatnick S, Blake PG, Mehrotra R
System-level strategies to improve home dialysis: policy levers and quality initiatives.
This article discusses trends in home dialysis use, reviews the evolving understanding of what constitutes high quality care for the home dialysis population (as well as how this can be measured), and discusses policy and advocacy efforts that continue to shape the care of US patients, and compares with experiences in other countries. The authors conclude by discussing future directions for quality and advocacy efforts.
AHRQ-funded; HS028684.
Citation: Watnick S, Blake PG, Mehrotra R .
System-level strategies to improve home dialysis: policy levers and quality initiatives.
Clin J Am Soc Nephrol 2023 Dec; 18(12):1616-25. doi: 10.2215/cjn.0000000000000299..
Keywords: Home Healthcare, Kidney Disease and Health, Policy, Quality Improvement, Quality of Care
Keller SC, Hannum SM, Weems K
Implementing and validating a home-infusion central-line-associated bloodstream infection surveillance definition.
Researchers tested the validity of a home-infusion central-line-associated bloodstream infection (CLABSI) surveillance definition and the feasibility and acceptability of its implementation. Their study was conducted in large home-infusion agencies in a CLABSI prevention collaborative in 14 states and the District of Columbia and included semistructured interviews with staff performing home-infusion CLABSI surveillance. The results showed that the home-infusion CLABSI surveillance definition was valid and would be feasible to implement.
AHRQ-funded; HS027819.
Citation: Keller SC, Hannum SM, Weems K .
Implementing and validating a home-infusion central-line-associated bloodstream infection surveillance definition.
Infect Control Hosp Epidemiol 2023 Nov; 44(11):1748-59. doi: 10.1017/ice.2023.70..
Keywords: Home Healthcare, Central Line-Associated Bloodstream Infections (CLABSI), Healthcare-Associated Infections (HAIs)
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.
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
Squires A, Engel P, Ma C
Continuity of care versus language concordance as an intervention to reduce hospital readmissions from home health care.
The purpose of this study was to examine the relative effectiveness of continuity of care and language concordance as alternative or complementary interventions to improve health outcomes of people with limited English proficiency. Participants included over 22,000 non-English-speaking patients from the New York City area who were admitted to their home health site following hospital discharge. Findings revealed that high continuity of care and high language concordance significantly decreased readmissions, along with high continuity of care and low language concordance; low continuity of care and high language concordance did not significantly impact readmissions. The authors concluded that enhancing continuity of care for those with language barriers the US home health system may help to address disparities and reduce hospital readmission rates.
AHRQ-funded; HS023593.
Citation: Squires A, Engel P, Ma C .
Continuity of care versus language concordance as an intervention to reduce hospital readmissions from home health care.
Med Care 2023 Sep; 61(9):605-10. doi: 10.1097/mlr.0000000000001884..
Keywords: Hospital Readmissions, Transitions of Care, Home Healthcare
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
Oladapo-Shittu O, Hannum SM, Salinas AB
The need to expand the infection prevention workforce in home infusion therapy.
This study looked at the prevalence of formal surveillance and infection prevention training for home infusion staff. The authors interviewed home infusion staff who perform surveillance activities about barriers to and facilitators for central line-associated bloodstream infection (CLABSI) surveillance and identified barriers to training in CLABSI surveillance. Their findings showed a lack of formal surveillance training which can be addressed by by adapting existing training resources to the home infusion setting.
AHRQ-funded; HS027819.
Citation: Oladapo-Shittu O, Hannum SM, Salinas AB .
The need to expand the infection prevention workforce in home infusion therapy.
Am J Infect Control 2023 May; 51(5):594-96. doi: 10.1016/j.ajic.2022.11.008.AHRQ-funded; HS027819..
Keywords: Healthcare-Associated Infections (HAIs), Prevention, Home Healthcare, Central Line-Associated Bloodstream Infections (CLABSI)
Hobensack M, Song J, Chae S
Capturing concerns about patient deterioration in narrative documentation in home healthcare.
This study aimed to build machine learning algorithms to identify “concerning” narrative notes of home healthcare (HHC) patients and identify emergency themes to support early identification of patients at risk for deterioration. Six algorithms were applied to 4000 narrative notes from a HHC agency to classify notes as either "concerning" or "not concerning." Emerging themes were identified using Latent Dirichlet Allocation bag of words topic modeling. Emerging themes of concern included patient-clinician communication, HHC services provided, gait challenges, mobility concerns, wounds, and caregivers. Most of these themes had already been identified in previous literature as increasing risk for adverse events.
AHRQ-funded; HS027742.
Citation: Hobensack M, Song J, Chae S .
Capturing concerns about patient deterioration in narrative documentation in home healthcare.
AMIA Annu Symp Proc 2023 Apr 29; 2022:552-59..
Keywords: Home Healthcare, Electronic Health Records (EHRs), Health Information Technology (HIT)
Hobensack M, Song J, Scharp D
Machine learning applied to electronic health record data in home healthcare: a scoping review.
This literature review aimed to synthesize and appraise the literature describing the application of machine learning to predict adverse outcomes (e.g., hospitalization, mortality) using electronic health record (EHR) data in the home healthcare (HHC) setting. The secondary aim was to evaluate the comprehensiveness of predictors used in the machine learning algorithms guided by the Biopsychosocial Model. Studies were included if they 1) described services provided in the HHC setting, 2) applied machine learning algorithms to predict adverse outcomes, defined as outcomes related to patient deterioration, 3) used EHR data and, 4) focused on the adult population. Predictors were mapped to the Biopsychosocial Model. The final sample included 20 studies, of which 18 used predictors from standardized assessments integrated in the EHR. The most common outcome was hospitalization (55%), followed by mortality (25%). About 35% of studies excluded psychological predictors. Most studies (75%) demonstrated high or unclear risk of bias with tree based algorithms most frequently applied (75%).
AHRQ-funded; HS027742.
Citation: Hobensack M, Song J, Scharp D .
Machine learning applied to electronic health record data in home healthcare: a scoping review.
Int J Med Inform 2023 Feb; 170:104978. doi: 10.1016/j.ijmedinf.2022.104978..
Keywords: Home Healthcare, Electronic Health Records (EHRs), Health Information Technology (HIT)
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