Potentially inappropriate medications in nursing homes and the community older adults using the French health insurance databases.

PURPOSE: Potentially inappropriate medications (PIMs) have become a major issue in improving prescribing practices and reducing the risk of adverse drug events in older people. However, very few studies have compared exposition to PIMs controlling for differences in demographic and health between nursing home residents (NHRs) and community-dwelling older adults (CDOAs). This study aimed to assess the prescribing pattern of PIMs between NHRs and CDOAs. METHODS: We conducted a cross-sectional study over three months in 2019 using the French Health Insurance databases. The study population included 274 971 NHRs and 4 893 721 CDOAs aged 75 years or over. The prevalence ratio (PR) between NHRs and CDOAs of 17 PIM indicators, based on the Beers and STOPP criteria lists, was assessed using multivariable robust Poisson regression adjusted for age, sex, diseases, and polypharmacy. RESULTS: During the study period, 54% of NHRs and 29% of CDOAs received at least one PIM. After adjustment, the prevalence of PIMs was 33% higher among NHRs compared to CDOAs (aPR = 1.33; 95% CI [1.33-1.34]). NHRs received PIMs related to benzodiazepines (aPR = 1.43; 95% CI [1.42-1.43]), anticholinergic drugs (aPR = 1.29; 95% CI [1.27-1.31]), and at least three central nervous system-active drugs (aPR = 1.94; 95% CI [1.92-1.96]) more frequently. Prevalence of PIMs related to non-steroidal anti-inflammatory drugs (aPR = 0.50; 95% CI [0.48-0.52]) and long-acting benzodiazepines (aPR = 0.84; 95% CI [0.82-0.85]) was lower among NHRs. CONCLUSION: The NHRs were at greater risk for PIM than CDOAs, although differences exist according to the category of PIMs. As the population is aging, it is essential to promote and evaluate interventions in NHs and the community to enhance medication optimization.

A Postacute Care Function Process Quality Measure for the Collection of Standardized Self-Care and Mobility Data: Development, Implementation, and Quality Measure Scores.

OBJECTIVE: To describe the development of and quality measure scores for the cross-setting postacute care function process quality measure that requires the collection of standardized self-care and mobility data at admission and discharge and at least 1 function goal. DESIGN: Description of the development and implementation of the quality measure and the associated standardized self-care and mobility data elements. Descriptive analyses of quality measure scores for the first calendar year using data from the Minimum Data Set, the Inpatient Rehabilitation Facility Patient Assessment Instrument, the Long-Term Care Hospitals (LTCH) Continuity Assessment Record and Evaluation Data Set, and Outcome and Assessment Information Set. SETTING: 15,127 skilled nursing facilities (SNFs), 1129 inpatient rehabilitation facilities (IRFs), 414 LTCHs, and 10,352 home health agencies (HHAs) in the United States. PARTICIPANTS: In total there were 9,216,943 stays/quality episodes (N = 9,216,943), including 2,084,774 SNF Medicare fee-for-service patient stays, 493,209 IRF Medicare patient stays, 161,714 patient stays, and 6,477,246 Medicare and Medicaid quality episodes. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Scores for the cross-setting postacute care function process quality measure. RESULTS: The mean process quality measure scores for SNFs, IRFs, LTCHs, and HHAs were 95.5%, 99.7%, 99.1%, and 95.8, respectively. The 10th percentile scores for SNFs, IRFs, LTCHs, and HHAs were 88.5%, 99.3%, 98.4%, and 89.4, respectively, indicating that at least 90% of postacute care providers submitted the standardized data for a large proportion of their patients. Mean quality measure scores did not vary by provider characteristics. CONCLUSIONS: Most SNFs, IRFs, LTCHs, and HHAs submitted the self-care and mobility data, resulting in high quality measure scores during the first year of implementation. The availability of the standardized self-care and mobility data across postacute care settings offers the opportunity to compare the characteristics and functional outcomes of patients treated in postacute care.

Feasibility of ecological momentary assessment to study depressive symptoms among cancer caregivers.

OBJECTIVE: Ecological momentary assessment (EMA) may help with the development of more targeted interventions for caregivers' depression, yet the use of this method has been limited among cancer caregivers. This study aimed to demonstrate the feasibility of EMA among cancer caregivers and the use of EMA data to understand affective correlates of caregiver depressive symptoms. METHODS: Caregivers (N = 25) completed a depressive symptom assessment (Patient Health Questionnaire-8) and then received eight EMA survey prompts per day for 7 days. EMA surveys assessed affect on the orthogonal dimensions of valence and arousal. Participants completed feedback surveys regarding the EMA protocol at the conclusion of the week-long study. RESULTS: Of 32 caregivers approached, 25 enrolled and participated (78%), which exceeded the a priori feasibility cutoff of 55%. The prompt completion rate (59%, or 762 of 1,286 issued) did not exceed the a priori cutoff of 65%, although completion was not related to caregivers' age, employment status, physical health quality of life, caregiving stress, or depressive symptoms or the patients' care needs (ps > 0.22). Caregivers' feedback about their study experience was generally positive. Mixed-effects location scale modeling showed caregivers' higher depressive symptoms were related to overall higher reported negative affect and lower positive affect, but not to affective variability. CONCLUSIONS: Findings from this feasibility study refute potential concerns that an EMA design is too burdensome for distressed caregivers. Clinically, findings suggest the potential importance of not only strategies to reduce overall levels of negative affect, but also to increase opportunities for positive affect.

Variation in mortality rates after admission to long-term acute care hospitals for ventilator weaning.

PURPOSE: We sought to examine variation in long-term acute care hospital (LTACH) quality based on 90-day in-hospital mortality for patients admitted for weaning from mechanical ventilation. METHODS: We developed an administrative risk-adjustment model using data from Medicare claims. We validated the administrative model against a clinical model using data from LTACHs participating in a 2002 to 2003 clinical registry. We then used our validated administrative model to assess national variation in 90-day in-hospital mortality rates in LTACHs from 2013. RESULTS: The administrative risk-adjustment model was derived using data from 9447 patients admitted to 221 LTACHs in 2003. The model had good discrimination (C statistic=0.72) and calibration. Compared to a clinically derived model using data from 1163 patients admitted to 14 LTACHs, the administrative model generated similar performance estimates. National variation in risk-adjusted mortality was assessed using data from 20,453 patients admitted to 380 LTACHs in 2013. LTACH-specific risk-adjusted mortality rates varied from 8.4% to 48.1% (median: 24.2%, interquartile range: 19.7%-30.7%). CONCLUSIONS: LTACHs vary widely in mortality rates, underscoring the need to better understand the sources of this variation and improve the quality of care for patients requiring long-term ventilator weaning.

ICU Telemedicine and Critical Care Mortality: A National Effectiveness Study.

BACKGROUND: Intensive care unit (ICU) telemedicine is an increasingly common strategy for improving the outcome of critical care, but its overall impact is uncertain. OBJECTIVES: To determine the effectiveness of ICU telemedicine in a national sample of hospitals and quantify variation in effectiveness across hospitals. RESEARCH DESIGN: We performed a multicenter retrospective case-control study using 2001-2010 Medicare claims data linked to a national survey identifying US hospitals adopting ICU telemedicine. We matched each adopting hospital (cases) to up to 3 nonadopting hospitals (controls) based on size, case-mix, and geographic proximity during the year of adoption. Using ICU admissions from 2 years before and after the adoption date, we compared outcomes between case and control hospitals using a difference-in-differences approach. RESULTS: A total of 132 adopting case hospitals were matched to 389 similar nonadopting control hospitals. The preadoption and postadoption unadjusted 90-day mortality was similar in both case hospitals (24.0% vs. 24.3%, P=0.07) and control hospitals (23.5% vs. 23.7%, P<0.01). In the difference-in-differences analysis, ICU telemedicine adoption was associated with a small relative reduction in 90-day mortality (ratio of odds ratios=0.96; 95% CI, 0.95-0.98; P<0.001). However, there was wide variation in the ICU telemedicine effect across individual hospitals (median ratio of odds ratios=1.01; interquartile range, 0.85-1.12; range, 0.45-2.54). Only 16 case hospitals (12.2%) experienced statistically significant mortality reductions postadoption. Hospitals with a significant mortality reduction were more likely to have large annual admission volumes (P<0.001) and be located in urban areas (P=0.04) compared with other hospitals. CONCLUSIONS: Although ICU telemedicine adoption resulted in a small relative overall mortality reduction, there was heterogeneity in effect across adopting hospitals, with large-volume urban hospitals experiencing the greatest mortality reductions.

Adoption and de-adoption of drotrecogin alfa for severe sepsis in the United States.

PURPOSE: Drotrecogin alfa was a landmark drug for treatment of severe sepsis, yet little is known about how it was adopted and de-adopted during its 10-year period of availability. METHODS: We used hospitalization data on fee-for-service Medicare beneficiaries from 2002 to 2011 to characterize trends in the use of drotrecogin alfa in the United States. RESULTS: Drotrecogin alfa use peaked at 5.87 per 1000 severe sepsis hospitalizations in 2003 and then steadily declined to 0.94 administrations per 1000 severe sepsis hospitalizations in 2010. Large teaching hospitals were more likely to use drotrecogin alfa than small, nonteaching hospitals. The addition of "add-on payments" to hospitals for using drotrecogin alfa in 2002 was associated with significantly increased use (P < .0001), and the withdrawal of those payments in 2004 was associated significantly decreased use (P < .0001). Neither the publication of international sepsis guidelines with favorable drotrecogin alfa recommendations (in 2004 and 2008) nor the publication of a clinical trial focused on drotrecogin alfa (in 2005) were associated with consistent changes use (P > .05). CONCLUSIONS: Drotrecogin alfa use declined over time, with marked changes in use associated with drug-specific financial incentives but not the publication of clinical practice guidelines or clinical trials.

A Comparison of Free-Standing versus Co-Located Long-Term Acute Care Hospitals.

BACKGROUND: Long-term acute care hospitals (LTACs) provide specialized treatment for patients with chronic critical illness. Increasingly LTACs are co-located within traditional short-stay hospitals rather than operated as free-standing facilities, which may affect LTAC utilization patterns and outcomes. METHODS: We compared free-standing and co-located LTACs using 2005 data from the United States Centers for Medicare & Medicaid Services. We used bivariate analyses to examine patient characteristics and timing of LTAC transfer, and used propensity matching and multivariable regression to examine mortality, readmissions, and costs after transfer. RESULTS: Of 379 LTACs in our sample, 192 (50.7%) were free-standing and 187 (49.3%) were co-located in a short-stay hospital. Co-located LTACs were smaller (median bed size: 34 vs. 66, p <0.001) and more likely to be for-profit (72.2% v. 68.8%, p = 0.001) than freestanding LTACs. Co-located LTACs admitted patients later in their hospital course (average time prior to transfer: 15.5 days vs. 14.0 days) and were more likely to admit patients for ventilator weaning (15.9% vs. 12.4%). In the multivariate propensity-matched analysis, patients in co-located LTACs experienced higher 180-day mortality (adjusted relative risk: 1.05, 95% CI: 1.00-1.11, p = 0.04) but lower readmission rates (adjusted relative risk: 0.86, 95% CI: 0.75-0.98, p = 0.02). Costs were similar between the two hospital types (mean difference in costs within 180 days of transfer: -$3,580, 95% CI: -$8,720 -$1,550, p = 0.17). CONCLUSIONS: Compared to patients in free-standing LTACs, patients in co-located LTACs experience slightly higher mortality but lower readmission rates, with no change in overall resource use as measured by 180 day costs.

The epidemiology of chronic critical illness in the United States*.

OBJECTIVES: The epidemiology of chronic critical illness is not well characterized. We sought to determine the prevalence, outcomes, and associated costs of chronic critical illness in the United States. DESIGN: Population-based cohort study using data from the United States Healthcare Costs and Utilization Project from 2004 to 2009. SETTING: Acute care hospitals in Massachusetts, North Carolina, Nebraska, New York, and Washington. PATIENTS: Adult and pediatric patients meeting a consensus-derived definition for chronic critical illness, which included one of six eligible clinical conditions (prolonged acute mechanical ventilation, tracheotomy, stroke, traumatic brain injury, sepsis, or severe wounds) plus at least 8 days in an ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Out of 3,235,741 admissions to an ICU during the study period, 246,151 (7.6%) met the consensus definition for chronic critical illness. The most common eligibility conditions were prolonged acute mechanical ventilation (72.0% of eligible admissions) and sepsis (63.7% of eligible admissions). Among patients meeting chronic critical illness criteria through sepsis, the infections were community acquired in 48.5% and hospital acquired in 51.5%. In-hospital mortality was 30.9% with little change over the study period. The overall population-based prevalence was 34.4 per 100,000. The prevalence varied substantially with age, peaking at 82.1 per 100,000 individuals 75-79 years old but then declining coincident with a rise in mortality before day 8 in otherwise eligible patients. Extrapolating to the entire United States, for 2009, we estimated a total of 380,001 cases; 107,880 in-hospital deaths and $26 billion in hospital-related costs. CONCLUSIONS: Using a consensus-based definition, the prevalence, hospital mortality, and costs of chronic critical illness are substantial. Chronic critical illness is particularly common in the elderly although in very old patients the prevalence declines, in part because of an increase in early mortality among potentially eligible patients.

Effect of public reporting on intensive care unit discharge destination and outcomes.

RATIONALE: Public reporting of hospital performance is designed to improve healthcare outcomes by promoting quality improvement and informing consumer choice, but these programs may carry unintended consequences. OBJECTIVE: To determine whether publicly reporting in-hospital mortality rates for intensive care unit (ICU) patients influenced discharge patterns or mortality. METHODS: We performed a retrospective cohort study taking advantage of a natural experiment in which California, but not other states, publicly reported hospital-specific severity-adjusted ICU mortality rates between 2007 and 2012. We used multivariable logistic regression adjusted for patient, hospital, and regional characteristics to compare mortality rates and discharge patterns between California and states without public reporting for Medicare fee-for-service ICU admissions from 2005 through 2009 using a difference-in-differences approach. MEASUREMENTS AND MAIN RESULTS: We assessed discharge patterns using post-acute care use and acute care hospital transfer rates and mortality using in-hospital and 30-day mortality rates. The study cohort included 936,063 patients admitted to 646 hospitals. Compared with control subjects, admission to a California ICU after the introduction of public reporting was associated with a reduced odds of post-acute care use in post-reform year 2 (ratio of odds ratios [ORs], 0.94; 95% confidence interval [CI], 0.91-0.96) and increased odds of transfer to another acute care hospital in both post-reform years (year 1: ratio of ORs, 1.08; 95% CI, 1.01-1.16; year 2: ratio of ORs, 1.43; 95% CI, 1.33-1.53). There were no significant differences in in-hospital or 30-day mortality. CONCLUSIONS: Public reporting of ICU in-hospital mortality rates was associated with changes in discharge patterns but no change in risk-adjusted mortality.

Hospital factors associated with discharge bias in ICU performance measurement.

OBJECTIVE: Performance assessments based on in-hospital mortality for ICU patients can be affected by discharge practices such that differences in mortality may reflect variation in discharge patterns rather than quality of care. Time-specific mortality rates, such as 30-day mortality, are preferred but are harder to measure. The degree to which the difference between 30-day and in-hospital ICU mortality rates-or "discharge bias"-varies by hospital type is unknown. The aim of this study was to quantify variation in discharge bias across hospitals and determine the hospital characteristics associated with greater discharge bias. DESIGN: Retrospective cohort study. SETTING: Nonfederal Pennsylvania hospital discharges in 2008. PATIENTS: Eligible patients were 18 years old or older and admitted to an ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used logistic regression with hospital-level random effects to calculate hospital-specific risk-adjusted 30-day and in-hospital mortality rates. We then calculated discharge bias, defined as the difference between 30-day and in-hospital mortality rates, and used multivariable linear regression to compare discharge bias across hospital types. A total of 43,830 patients and 134 hospitals were included in the analysis. Mean (SD) risk-adjusted hospital-specific in-hospital and 30-day ICU mortality rates were 9.6% (1.3) and 12.7% (1.5), respectively. Hospital-specific discharge biases ranged from -1.3% to 6.6%. Discharge bias was smaller in large hospitals compared with small hospitals, making large hospitals appear comparatively worse from a benchmarking standpoint when using in-hospital mortality instead of 30-day mortality. CONCLUSIONS: Discharge practices bias in-hospital ICU mortality measures in a way that disadvantages large hospitals. Accounting for discharge bias will prevent these hospitals from being unfairly disadvantaged in public reporting and pay-for-performance.