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Infection prevention is a high priority for home healthcare (HHC) but tools are lacking to identify patients at highest risk for 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 non-experimental study using secondary data was conducted. The Outcome and Assessment Information Set linked with relevant clinical data from 112,788 HHC admissions in 2014 were used for model development (70% of data) and testing (30%). A total of 1,908 patients (1.69%) were hospitalized or received emergency care associated with infection. Stepwise logistic regression models discriminated between individuals with and without infections. Our final model, when classified by highest risk of infection, identified a high portion of those who were hospitalized or received emergent care for an infection while also correctly categorizing 90.5% of patients without infection. The risk model can be used by clinicians to inform care planning. This is the first study to develop a tool for predicting infection risk that can be used to inform how to direct additional infection control intervention resources on high-risk patients, potentially reducing infection related hospitalizations, emergency department visits, and costs.

To describe racial/ethnic group differences in pain presentation and the prevalence of psychosocial factors among patients admitted to home health care, and to determine the extent of racial/ethnic group differences in the association of psychosocial factors with pain intensity and pain-related disability. We analyzed cross-sectional data on 588 patients with activity-limiting pain admitted to home care for physical therapy. Three psychosocial factors were assessed: depressive symptoms, pain self-efficacy, and health literacy. Statistical methods included estimation of general linear models of pain intensity and pain-related disability. Hispanics and non-Hispanic blacks report a greater number of pain sites, worse pain intensity, and higher levels of pain-related disability than non-Hispanic whites and others. Racial/ethnic minority group patients also have a higher prevalence of adverse psychosocial factors than others, with evidence that race/ethnicity interacts with pain self-efficacy and depressive symptoms in their association with mean pain intensity and pain-related disability, respectively. The substantial racial/ethnic difference in the psychosocial profiles of older adults with activity-limiting pain highlights the importance of screening for these modifiable risk factors and tailoring interventions accordingly. Direct attention to the psychosocial needs of patients could help to address racial/ethnic disparities in pain outcomes.

Activity-limiting pain is common among older home care patients and pain management is complicated by the high prevalence of physical frailty and multimorbidity in the home care population. A comparative effectiveness study was undertaken at a large urban home care agency to examine an evidence-based pain self-management program delivered by physical therapists (PTs). This article focuses on PT training, methods implemented to reinforce content after training and to encourage uptake of the program with appropriate patients, and therapists' fidelity to the program. Seventeen physical therapy teams were included in the cluster randomized controlled trial, with 8 teams (155 PTs) assigned to a control and 9 teams (165 PTs) assigned to a treatment arm. Treatment therapists received interactive training over two sessions, with a follow-up session 6 months later. Additional support was provided via emails, e-learning materials including videos, and a therapist manual. Program fidelity was assessed by examining PT pain documentation in the agency's electronic health record. PT feedback on the program was obtained via semistructured surveys. There were no between-group differences in the number of PTs documenting program elements with the exception of instruction in the use of imagery, which was documented by a higher percentage of intervention therapists (p = 0.002). PTs felt comfortable teaching the program elements, but cited time as the biggest barrier to implementing the protocol. Possible explanations for study results suggesting limited adherence to the program protocol by intervention-group PTs include the top-down implementation strategy, competing organizational priorities, program complexity, competing patient priorities, and inadequate patient buy-in. Implications for the implementation of complex new programs in the home healthcare setting are discussed.

The aging population and the associated rise in the prevalence of chronic conditions suggest that the home health population is increasingly complex and challenging to manage. The purpose of this study was to use national administrative data (Outcome and Assessment Information Set assessments of persons discharged in 2004 and 2005) to examine the clinical complexity of older adults admitted to home healthcare. Our descriptive analyses confirm that multiple chronic conditions and cognitive impairment are common and result in longer lengths of stay. The findings support the need for geriatric home healthcare practices that effectively address multiple morbidities and cognitive function.

Computerized drug utilization review (DUR) can potentially reduce adverse drug events. We examined automated DUR for home healthcare patients with diabetes or hypertension. Sixty-eight percent of diabetes patients and 50.7% of hypertension patients triggered severe, moderate, or duplicative alerts. Among diabetes patients, 74.3% of duplicative alerts were trivial or inappropriate, compared with 3.9% among hypertension patients. Experts judged that 40.5% of high-risk diabetes patients and 53.6% of hypertension patients had alerts requiring nurse follow-up. Adequate follow-up was significantly lower for the former. The relationship between inappropriate alerts and poorer follow-up reinforces the need for more specific alert systems to focus clinicians' attention on clinically important alerts.