The Interdisciplinary Home-bAsed Reablement Program (I-HARP) integrates evidence-based rehabilitation strategies into a dementia-specific person-centred, time-limited, home-based, interdisciplinary rehabilitation package. I-HARP was a 4-month model of care, incorporated into community aged care services and hospital-based community geriatric services. I-HARP involved: 8-10 individually tailored home visits by occupational therapist and registered nurse; 2-4 optional other allied health sessions; up to A$1,000 minor home modifications and/or assistive devices; and three individual carer support sessions. The aim of the study was to determine the effectiveness of I-HARP on the health and wellbeing of people living with dementia and their family carers.

A multi-centre pragmatic parallel-arm randomised controlled trial compared I-HARP to usual care in community-dwelling people with mild to moderate dementia and family carers in Sydney, Australia (2018-22). Assessments of the client’s daily activities, mobility and health-related quality of life, caregiver burden and quality of life were conducted at baseline, 4- and 12-month follow-up. Changes from baseline were compared between groups.

Of 260 recruited, 232 (116 dyads of clients and their carers, 58 dyads per group) completed the trial to 4-month follow-up (89% retention). Clients were: aged 60-97 years, 63% female, 57% with mild dementia and 43% with moderate dementia. The I-HARP group had somewhat better mean results for most outcome measures than usual care at both 4 and 12 months, but the only statistically significant difference was a reduction in home environment hazards at 4 months (reduction: 2.29 on Home Safety Self-Assessment Tool, 95% CI: 0.52, 4.08; p=.01, effect size [ES] 0.53). Post-hoc sub-group analysis of 66 clients with mild dementia found significantly better functional independence in the intervention group: 11.2 on Disability Assessment for Dementia (95% CI: 3.4, 19.1; p=.005; ES 0.69) at 4 months and 13.7 (95% CI: 3.7, 23.7; p=.007; ES 0.69) at 12 months.

The I-HARP model enhanced functional independence of people with mild dementia only but not significantly in people with moderate dementia, so did not result in better outcomes in the group overall. A different type of rehabilitation model or strategies may be required as dementia becomes more severe.

Research exploring the longitudinal course of posttraumatic stress disorder (PTSD) symptoms has documented four modal trajectories (low, remitting, high, and delayed), with proportions varying across studies. Heterogeneity could be due to differences in trauma types and patient demographic characteristics.

This analysis pooled data from six longitudinal studies of adult survivors of civilian-related injuries admitted to general hospital emergency departments (EDs) in six countries (pooled N = 3083). Each study included at least three assessments of the clinician-administered PTSD scale in the first post-trauma year. Latent class growth analysis determined the proportion of participants exhibiting various PTSD symptom trajectories within and across the datasets. Multinomial logistic regression analyses examined demographic characteristics, type of event leading to the injury, and trauma history as predictors of trajectories differentiated by their initial severity and course.

Five trajectories were found across the datasets: Low (64.5%), Remitting (16.9%), Moderate (6.7%), High (6.5%), and Delayed (5.5%). Female gender, non-white race, prior interpersonal trauma, and assaultive injuries were associated with increased risk for initial PTSD reactions. Female gender and assaultive injuries were associated with risk for membership in the Delayed (v. Low) trajectory, and lower education, prior interpersonal trauma, and assaultive injuries with risk for membership in the High (v. Remitting) trajectory.

The results suggest that over 30% of civilian-related injury survivors admitted to EDs experience moderate-to-high levels of PTSD symptoms within the first post-trauma year, with those reporting assaultive violence at increased risk of both immediate and longer-term symptoms.

This study aimed to examine factors associated with receipt of post-disaster support from network (eg, family or friends) and non-network (eg, government agencies) sources.

Participants (n=409) were from a population-based sample of Hurricane Sandy survivors surveyed 25-28 months post-disaster. Survivors were asked to imagine a future disaster and indicate how much they would depend on network and non-network sources of support. In addition, they reported on demographic characteristics, disaster-related exposure, post-traumatic stress, and depression. Information on the economic and social resources in survivors’ communities was also collected.

Multilevel multivariable regression models found that lack of insurance coverage and residence in a neighborhood wherein more persons lived alone were associated with survivors anticipating less network and non-network support. In addition, being married or cohabiting was significantly associated with more anticipated network support, whereas older age and having a high school education or less were significantly associated with less anticipated network support.

By having survivors anticipate a future disaster scenario, this study provides insight into predictors of post-disaster receipt of network and non-network support. Further research is needed to examine how these findings correspond to survivors’ received support in the aftermath of future disasters. (Disaster Med Public Health Preparedness. 2018;12:711-717)

Risk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.

Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.

Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.

Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.

Infect Control Hosp Epidemiol 2017;38:1019–1024

Inappropriate use of antipsychotic medications to manage Behavioral and Psychological Symptoms of Dementia (BPSD) continues despite revised guidelines and evidence for the associated risks and side effects. The aim of the Halting Antipsychotic Use in Long-Term care (HALT) project is to identify residents of long-term care (LTC) facilities on antipsychotic medications, and undertake an intervention to deprescribe (or cease) these medicines and improve non-pharmacological behavior management.

LTC facilities will be recruited across Sydney, Australia. Resident inclusion criteria will be aged over 60 years, on regular antipsychotic medication, and without a primary psychotic illness or very severe BPSD, as measured using the Neuropsychiatric Inventory (NPI). Data collection will take place one month and one week prior to commencement of deprescribing; and 3, 6 and 12 months later. During the period prior to deprescribing, training will be provided for care staff on how to reduce and manage BPSD using person-centered approaches, and general practitioners of participants will be provided academic detailing. The primary outcome measure will be reduction of regular antipsychotic medication without use of substitute psychotropic medications. Secondary outcome measures will be NPI total and domain scores, Cohen-Mansfield Agitation Inventory scores and adverse events, including falls and hospitalizations.

While previous studies have described strategies to minimize inappropriate use of antipsychotic medications in people with dementia living in long-term care, sustainability and a culture of prescribing for BPSD in aged care remain challenges. The HALT project aims to evaluate the feasibility of a multi-disciplinary approach for deprescribing antipsychotics in this population.

We aimed to explore how individually experienced disaster-related stressors and collectively experienced community-level damage influenced perceived need for mental health services in the aftermath of Hurricane Sandy.

In a cross-sectional study we analyzed 418 adults who lived in the most affected areas of New York City at the time of the storm. Participants indicated whether they perceived a need for mental health services since the storm and reported on their exposure to disaster-related stressors (eg, displacement, property damage). We located participants in communities (n=293 census tracts) and gathered community-level demographic data through the US Census and data on the number of damaged buildings in each community from the Federal Emergency Management Agency Modeling Task Force.

A total of 7.9% of participants reported mental health service need since the hurricane. Through multilevel binomial logistic regression analysis, we found a cross-level interaction (P=0.04) between individual-level exposure to disaster-related stressors and community-level building damage. Individual-level stressors were significantly predictive of individual service needs in communities with building damage (adjusted odds ratio: 2.56; 95% confidence interval: 1.58-4.16) and not in communities without damage.

Individuals who experienced individual stressors and who lived in more damaged communities were more likely to report need for services than were other persons after Hurricane Sandy. (Disaster Med Public Health Preparedness. 2016;10:428–435)

To demonstrate a spatial epidemiologic approach that could be used in the aftermath of disasters to (1) detect spatial clusters and (2) explore geographic heterogeneity in predictors for mental health and general wellness.

We used a cohort study of Hurricane Ike survivors (n=508) to assess the spatial distribution of postdisaster mental health wellness (most likely resilience trajectory for posttraumatic stress symptoms [PTSS] and depression) and general wellness (most likely resilience trajectory for PTSS, depression, functional impairment, and days of poor health) in Galveston, Texas. We applied the spatial scan statistic (SaTScan) and geographically weighted regression.

We found spatial clusters of high likelihood wellness in areas north of Texas City and spatial concentrations of low likelihood wellness in Galveston Island. Geographic variation was found in predictors of wellness, showing increasing associations with both forms of wellness the closer respondents were located to Galveston City in Galveston Island.

Predictors for postdisaster wellness may manifest differently across geographic space with concentrations of lower likelihood wellness and increased associations with predictors in areas of higher exposure. Our approach could be used to inform geographically targeted interventions to promote mental health and general wellness in disaster-affected communities. (Disaster Med Public Health Preparedness. 2016;10:261–273)