The Relationship Between Nursing Home Staffing and Health Outcomes Revisited.

OBJECTIVE: Nursing homes make staffing decisions in conjunction with choosing quality goals, potentially leading to endogeneity bias between staffing and quality. We use instrumental variables (IVs) to explore it. DESIGN: Retrospective statistical analysis of 2017-2019 Payroll-Based Journal, Minimum Data Set, Nursing Home Care Compare, and Long-Term Care Focus. SETTINGS AND PARTICIPANTS: A total of 11,261 nursing homes nationally. METHODS: We estimated separate models for each of 6 quality measures as dependent variables, and registered nurses (RNs), certified nurse assistants (CNAs), and licensed practical nurses (LPNs) as independent variables, including other control variables associated with quality. The models were estimated using both ordinary least squares (OLS) and 2-stage least squares (2SLS) methods, the latter accounting for endogeneity. The IVs were defined as the average staffing of competing nursing homes in the same market as the index facility. RESULTS: Estimated coefficients for the quality measures in the 2SLS models were up to 5 times larger than in the OLS models. The 2SLS estimates for antipsychotic medications use increased with higher RN staffing (0.279 [0.004 to 0.553]) and decreased with higher CNAs (-0.125 [-0.198 to -0.052]). Hospitalizations decreased with more RNs (-1.328 [-1.673 to -0.983]) and LPN staffing (-0.483 [-0.755 to -0.211] and increased with CNA (0.201 [0.109 to 0.293]) staffing. Emergency room visits decreased with higher RNs (-1.098 [-1.500 to -0.696]) and increased with CNAs (0.191 [0.084 to 0.298]). Long-stay activities of daily living (-0.313 [-0.416 to -0.209]) and short-stay functioning (-0.481 [-0.598 to -0.364]) improved only with higher CNA staffing and pressure sores improved only with increased RN staffing (-0.436 [-0.836 to -0.035]). CONCLUSIONS AND IMPLICATIONS: Our findings demonstrate the importance of accounting for endogeneity in studies of staffing and quality. Endogeneity changes conclusions about significance, direction, and magnitude of the relationship between staffing and specific quality measures. These findings highlight the need to further study and understand the nuanced relationship between different staffing types and different health outcomes such as the difference between the relationship of RN and CNA hours per resident day to antipsychotic quality measures.

Dementia, nurse staffing, and health outcomes in nursing homes.

OBJECTIVE: To estimate and contrast the relationships between nurse staffing and health outcomes in nursing homes with low and high dementia census, to understand the association of staffing hours with dementia care quality. DATA SOURCES AND STUDY SETTING: A national sample of nursing homes during 2017-2019 (pre-COVID). Data included the Payroll-Based Journal, Medicare Claims, Nursing Home Care Compare, and Long-Term Care Focus. STUDY DESIGN: Retrospective, regression analyses. We estimated separate linear models predicting six long-term facility-level outcomes. Independent variables included staffing hours per resident-day (HPRD) interacted with the facility percentage of dementia residents, controlling for other resident and facility characteristics. DATA COLLECTION/EXTRACTION METHODS: Hospital-based nursing homes, those with fewer than 30% dementia residents, and missing data were excluded. PRINCIPAL FINDINGS: We found that registered nurses and certified nurse assistants HPRDs were likely to exhibit positive returns in terms of outcomes throughout most of the range of HPRD for both high and low-census dementia facilities, although, high- and low-dementia facilities differed in most outcome rates at all staffing levels. Average predicted antipsychotics and activities of daily living as functions of HPRD were worse in higher dementia facilities, independent movement, and hospitalizations did not differ significantly, and Emergency Rooms and pressure sores were worse in lower dementia facilities. Average marginal effects were not statistically different [CI included zero] between the high and low dementia facilities for any outcome. CONCLUSIONS: These findings suggest that increasing staffing will improve outcomes by similar increments in both low- and high-dementia facilities for all outcomes. However, at any given level of staffing, absolute differences in outcomes between low- and high-dementia facilities remain, suggesting that additional staffing alone will not suffice to close these gaps. Further studies are required to identify opportunities for improvement in performance for both low- and high-dementia census facilities.

Dementia Care Is Widespread In US Nursing Homes; Facilities With The Most Dementia Patients May Offer Better Care.

More than three million US nursing home residents were diagnosed with Alzheimer's disease and related dementias (ADRD) between 2017 and 2019. This number is expected to increase as the population ages and ADRD prevalence increases. People with ADRD require specialized care from trained staff. This study addressed two questions: Are residents with ADRD concentrated in nursing homes where they are the majority? If not, what are the implications for their quality of care and life? We answered the first question by determining the ADRD census for each nursing home in the country during the period 2017-19. Using the Minimum Data Set and Medicare claims, we compared characteristics of nursing homes with high and low ADRD census along several dimensions, including staffing, resident outcomes, and resident characteristics. We found that residents with ADRD were dispersed throughout all nursing homes, with fewer than half residing in nursing homes where residents with ADRD accounted for 60-90 percent of the census. Furthermore, only facilities exceeding 90 percent of residents with ADRD seemed to offer better care. These findings raise concerns about the quality of care and life for the majority of residents with ADRD, suggesting that current National Institutes of Health dementia research initiatives and the Biden administration's policies to improve nursing home care should be coordinated.

New Dimensions of Staffing Patterns in Nursing Homes and Nursing Home Quality: Comparing Staffing Instability to Staffing Turnover.

OBJECTIVE: This study examines how measures of staffing-turnover and instability-are associated with one another and how they independently contribute to quality of care in nursing homes. DESIGN: Cross-sectional analysis of 2021-2022 administrative data. Data included the Payroll Based Journal for daily staffing information, merged with Nursing Home Care Compare (NHCC) data for nursing home characteristics, total staffing turnover, and nursing home quality. SETTING AND PARTICIPANTS: A total of 11,840 nursing homes nationally reporting data on daily staffing and staffing turnover. METHODS: We explored correlations between measures of staffing and estimated facility-level regression models with robust standard errors. The dependent variables were indicators of nursing home quality included in the NHCC 5-star ratings. The independent variables of interest were average total staffing hours per resident-day, total staffing turnover, and total staffing instability. RESULTS: For the 11,840 nursing homes in the study, there was a weak positive correlation between turnover and instability, with some overlap between nursing homes with high instability and high turnover. Regression analysis revealed that staffing instability and turnover contributed independently to nursing home quality, with instability having a stronger association with some measures of quality and turnover with others. Staffing instability was positively and more strongly associated with long-stay residents' decline in activities of daily living levels and receipt of antipsychotic drugs and short-stay residents' functioning at discharge. Turnover was positively and more strongly associated with long-stay residents' prevalence of pressure ulcers and worsening mobility, and short-stay residents' hospitalizations. CONCLUSION AND IMPLICATIONS: Instability and turnover in total nursing home staffing independently contribute to nursing home quality. This suggests that adding measures of staffing instability to the existing measures of average staffing and staff turnover in NHCC may enhance the report card's value for providers engaged in quality improvement and consumers searching for high-quality nursing homes.

Association of Staffing Instability With Quality of Nursing Home Care.

Importance: Recent work suggests that instability in nursing home staffing levels may be an important marker of nursing home quality. Whether that association holds when controlling for average staffing levels is unknown. Objective: To examine whether staffing instability, defined as the percentage of days below average staffing levels, is associated with nursing home quality when controlling for average staffing levels. Design, Setting, and Participants: This quality improvement study of 14 717 nursing homes used the merged Centers for Medicare & Medicaid Services Payroll Based Journal, Minimum Data Set, Nursing Home Care Compare, and Long-Term-Care Focus data for fiscal years 2017 to 2019. Statistical analysis was performed from February 8 to November 14, 2022. Main Outcomes and Measures: Linear, random-effect models with state fixed effects and robust SEs were estimated for 12 quality indicators as dependent variables, percentage of below-average staffing days as independent variables, controlling for average staffing hours per resident-day for registered nurses, licensed practical nurses, and certified nurse aides. Below-average staffing days were defined as those 20% below the facility average, by staffing type. Quality indicators included deficiency citations; long-stay residents receiving an antipsychotic; percentage of high-risk long-stay residents with pressure ulcers (2 different measures for pressure ulcers were used); and percentage of long-stay residents with activities of daily living decline, mobility decline, emergency department visits, and hospitalizations; and short-stay residents with new antipsychotic medication, mobility decline, emergency department visits, and rehospitalizations. Results: For the 14 717 nursing homes in this study, the mean (SD) percentage of days with below-average staffing was 30.2% (12.0%) for registered nurses, 16.4% (11.3%) for licensed practical nurses, and 5.1% (5.3%) for certified nurse aides. Mean (SD) staffing hours per resident-day were 0.44 (0.40) for registered nurses, 0.80 (0.32) for licensed practical nurses, and 2.20 (0.50) for certified nurse aides. In regression models that included average staffing, a higher percentage of below-average staffing days was significantly associated with worse quality for licensed practical nurses in 10 of 12 models, with the largest association for decline of activities of daily living among long-stay residents (regression coefficient, 0.020; P < .001). A higher percentage of below-average staffing days was significantly associated with worse quality for certified nurse aides in 9 of 12 models, with the largest association for short-stay functioning (regression coefficient, 0.030; P = .01). Conclusions and Relevance: This study suggests that holding average staffing levels constant, day-to-day staffing stability, especially avoiding days with low staffing of licensed practical nurses and certified nurse aides, is a marker of better quality of nursing homes. Future research should investigate the causes and potential solutions for instability in staffing in all facilities, including those that may appear well-staffed on average.

Associations Between Daily Nurse Staffing Levels and Daily Hospitalizations and ED Visits in Nursing Homes.

OBJECTIVES: Although many prior studies have shown that high average levels of nurse staffing in nursing homes are associated with fewer hospitalizations, some studies have not, suggesting that the average nursing level may mask a more complex relationship. This study examines this issue by investigating the associations of daily staffing patterns and daily hospitalizations and emergency department (ED) visits. DESIGN: Retrospective analyses of national Payroll Based Journal (PBJ) staffing data merged with the Minimum Data Set. SETTING AND PARTICIPANTS: A total of 15,718 nursing homes nationally reporting PBJ data during 2017-2019, their staff, and residents. METHODS: We estimated facility-day-level models as conditional facility fixed-effect Poisson regressions with robust standard errors. The dependent variables were daily numbers of hospitalization and ED visits and the independent variables of interest were the number of registered nurse (RN), licensed practical nurse (LPN), and certified nurse assistant (CNA) hours on the same and prior days. RESULTS: The daily number of hospital transfers averaged 0.28 (SD 0.21). Daily total direct-care staffing hours averaged 288.7 (SD 188.2), with RNs accounting for 35.0, LPNs for 68.7, and CNAs for 185.0. Higher staffing was associated with more hospitalizations on the concurrent day. Higher staffing on the day prior was associated with fewer hospitalizations. The effect size was larger for RNs and LPNs (same day = ∼2%; prior day = approximately -0.7% to -0.9%) than for CNAs (same day <1%; prior day < -0.5%). ED visits not leading to hospitalizations, and analyses for subsamples exhibited similar findings. CONCLUSIONS AND IMPLICATIONS: Our findings suggest that staff can address developing problems and prevent admissions the next day and identify emergent problems and hospitalize the same day. They also underscore the complex array of nursing home factors involved in hospitalization and ED visits, including the influence of daily staffing variation, suggesting the need for further research to better understand the associations between staffing and appropriate resident transfers to the hospital or the ED, and the potential implications for quality metrics in these domains.

Daily Variation in Nursing Home Staffing and Its Association With Quality Measures.

Importance: Average staffing measures are a focus of nursing homes' quality assessments and reporting. They may, however, mask daily variation in staffing, additional information that could be important for understanding nursing home quality and relative ranking. Objective: To examine daily variation in staffing, its association with quality, and whether daily variation provides information regarding quality ranking of nursing homes over and above the information provided by average staffing levels. Design, Setting, and Participants: This quality improvement study included registered nurses (RNs) and certified nurse aide (CNAs) at 13 339 certified nursing homes throughout the United States during 2017 to 2018. Retrospective analyses of the Payroll-Based Journal, Medicare Cost Reports, and Nursing Home Care Compare were conducted. Data were analyzed from January 2017 to December 2018. Main Outcomes and Measures: Three measures of daily variation, ie, coefficient of variation (COV), total outlier days (TOD), and low outlier days (LOD), were calculated for RNs and CNAs. The association between these measures and quality rankings and other facility characteristics were evaluated. Results: A total of 13 339 nursing homes were included in this study, with 9476 (71%) for-profit facilities. The mean (SD) hours-per-resident-day were 0.41 (0.29) for RNs and 2.16 (0.49) for CNAs, and a mean (SD) 55% (26%) of residents were Medicaid beneficiaries. Outcome measures were as follows: mean (SD) COV, 0.5 (0.6) for RNs and 0.1 (0.1) for CNAs; mean (SD) TOD, 220 (69) for RNs and 44 (45) for CNAs; and mean (SD) LOD, 116 (45) for RNs and 22 (24) for CNAs. All 3 variation measures, for both RNs and CNAs, were significantly associated with both the 5-Star Quality Measures (COV among RNs, -0.014 [95% CI, -0.021 to -0.007]; P < .001; COV among CNAs: -0.004 [95% CI, -0.006 to -0.003]; P < .001; TOD among RNs, -3.79 [95% CI, -4.59 to -2.99]; P < .001; TOD among CNAs, -2.52 [95% CI, -3.08 to -1.96]; P < .001; LOD among RNs, -2.46 [95% CI, -3.03 to -1.88]; P < .001; LOD among CNAs, -1.29 [95% CI, -1.58 to -0.99]; P < .001) and the 5-Star Survey rankings (COV among RNs,-0.026 [95% CI, -0.033 to -0.019]; P < .001; COV among CNAs: -0.006 [95% CI, -0.007 to -0.004]; P < .001; TOD among RNs, -5.10 [95% CI, -5.97 to -4.23]; P < .001; TOD among CNAs, -4.16 [95% CI, -4.77 to -3.55]; P < .001; LOD among RNs, -3.04 [95% CI, -3.65 to -2.44]; P < .001; LOD among CNAs, -1.97 [95% CI, -2.29 to -1.65]; P < .001) published in Nursing Home Care Compare. Low κ values, ranging from 0.23 to 0.63, indicated that the variation measures add information about ranking to the information provided by average staffing measure. Conclusions and Relevance: These findings highlight the importance of reporting daily variation in staffing to improve understanding of the relationship between staffing and quality. They suggest that 2 facilities with the same average staffing achieve different quality of resident care and survey ratings in association with on the day-to-day variation in staffing. Measures of daily staffing may enhance the value of Nursing Home Care Compare for nursing homes and others engaged in quality improvement and consumers searching for high quality nursing homes.

Who Visits Relatives in Nursing Homes? Predictors of at Least Weekly Visiting.

OBJECTIVES: Within the context of a single study, assess the relative importance of the 6 factors identified in a 2019 systematic review as associated with the likelihood that family members will visit nursing home residents. DESIGN: Retrospective statistical analysis of an existing survey data set. SETTINGS AND PARTICIPANTS: A national survey conducted with 4350 relatives of long-term nursing home residents. METHODS: Probit models of the probability of visiting a family member at least once weekly, stratified by age of the visitor, were estimated. To account for possible endogeneity of respondent involvement in the choice of nursing home and visit rate, visit rates were estimated using 2-stage residual inclusion in which the first stage explained involvement in nursing home choice. RESULTS: Involvement in nursing home choice has a substantively and statistically significant positive effect on visit probability for all age groups of respondents. Travel time has a substantively and statistically significant negative association on visit probability for all age groups. Younger women are more likely to visit than younger men. For all but the oldest respondents, higher income and full-time employment contribute to involvement in nursing home choice as does being Black or Hispanic. CONCLUSIONS AND IMPLICATIONS: As in previous research, travel time is an important determinant of visit rates. The strong association of involvement in nursing home choice with visit probability suggests a strong psychological motivation for visiting. To improve visiting, future research should focus on better understanding of the psychological factors that are associated with it and rely on better data and improved statistical methods. Our findings also suggest that nursing home administrators should consider adopting initiatives to facilitate and empower family members' involvement in nursing home choice, which in turn may lead to increased visitations.

Home Health Care Quality, Its Costs and Implications for Home Health Value-Based Purchasing.

The Home Health Value-based Purchasing (HHVBP) demonstration, incorporating a payment formula designed to incentivize both high-quality care and quality improvement, is expected to become a national program after 2022, when the demonstration ends. This study investigated the relationship between costs and several quality dimensions, to inform HHVBP policy. Using Medicare cost reports, OASIS and Home Health Compare data for 7,673 home health agencies nationally, we estimated cost functions with instrumental variables for quality. The estimated net marginal costs varied by composite quality measure, baseline quality, and agency size. For four of the five composite quality measures, the net marginal cost was negative for low-quality agencies, suggesting that quality improvement was cost saving for this agency type. As the magnitude of the net marginal cost is commensurate with the payment incentive planned for HHVBP, it should be considered when designing the incentives for HHVBP, to maximize their effectiveness.

Identifying Associations between Quality Initiatives and Quality Measures among Home Health Agencies: Findings from a National Study.

Home health performance gained visibility with the publication of Home Health Compare and the Home Health Value-Based Payment demonstration. Both provide incentives for home health agencies (HHA) to invest in quality improvements. The objective of this study is to identify the association between quality initiatives adopted by HHAs and improved performance. A 2018 national survey of 7459 HHAs, yielding a sample of 1192 eligible HHAs, provided information about 23 quality initiatives, which was linked to 5 composite Super Quality Measures (SQMs): ADL/pain, self-treatment, timely care, hospitalizations, and patient experience. Exclusions for missing data and outliers yielded a final analytical sample of 903 HHAs. Regression models estimated associations between quality initiatives and SQMs. The relationships between sixteen of the SQM/quality initiative pairs were positively associated with improvement and 7 were negatively associated. Web-based technologies for staff and care-givers improved performance but deteriorated patient experience. Web support-groups for staff and review of HHC rankings reduced hospitalization rates. While this study offers insights for quality improvement, a limitation may be a lack of sensitivity to the nuances of quality improvement implementation. Therefore, this study should be viewed as hypothesis-generating concerning initiatives likely to have the greatest potential meriting further investigation.

Families' and Residents' Perspectives of the Quality of Nursing Home Care: Implications for Composite Quality Measures.

OBJECTIVES: To assess (1) the relationship of consumers' assessment of overall nursing home quality to their assessment of specific dimensions of quality; and (2) the implications of this relationship for composite quality measures in Nursing Home Compare. DESIGN: A survey conducted in 2017 elicited respondents' assessments of the quality of overall care and 13 specific dimensions of care. SETTINGS AND PARTICIPANTS: The sample consisted of 4449 respondents who either resided in a nursing home or had a family member who resided in a nursing home during the 6 months before the survey. METHODS: We estimated regression models to infer the relationship between consumers' assessments of overall quality and 13 specific dimensions of quality. The regression coefficients, indicating the implicit importance/weight assigned by respondents to each dimension as a component of the consumers' assessment of overall quality, were used to create a prototype composite quality measure. RESULTS: For long-stay residents, 8 of the 13 quality dimensions were significantly associated with their overall ratings of quality. Five dimensions achieved significance for short-stay residents. The magnitude of importance weights varied substantially across dimensions of care. CONCLUSIONS AND IMPLICATIONS: Our findings suggest that Nursing Home Compare could be improved by augmenting the technical information in the 5-Star composite measure with consumers' assessments of the additional, nontechnical dimensions of quality.

Comparison of Consumer Rankings With Centers for Medicare & Medicaid Services Five-Star Rankings of Nursing Homes.

Importance: The Centers for Medicare & Medicaid Services (CMS) Five-Star measure for nursing homes is designed with input from expert panels about the importance of multiple quality indicators. Consumers may assign different values to these indicators, creating different 5-star ratings. Objective: To compare nursing homes' rankings based on the CMS Five-Star measure with rankings based on consumers' judgment about the importance of the same quality indicators. Design, Setting, and Participants: In this quality improvement study, CMS Five-Star data were linked with a measure calculated from CMS quality indicators and consumer values obtained from a national survey. Data covered the last quarter of 2016 and the first three quarters of 2017. The study included 10 676 nursing homes, comprising 69.8% of those with reported Five-Star measures. The national survey included adults, either nursing home residents or their family members who reported being familiar with the quality of care their relative received. Data analysis was performed from January 2019 to February 2020. Main Outcomes and Measures: The contingent valuation method was administered via the survey to obtain consumers' relative values of the quality indicators, and statistical analyses were used to create the contingent valuation measure. Agreement in nursing home rankings was assessed using the Five-Star measure, which is based on weights developed by expert panels, compared with rankings based on the contingent valuation measure. Results: Among 10 676 study nursing homes with a mean (SD) of 119.4 (59.4) beds, 7845 (73.5%) were for profit, 6424 (61.8%) were part of a chain, and 8009 (75.0%) were urban. The 4310 survey respondents (mean [SD] age, 39.9 [15.6] years; 1143 [26.5%] men; 3448 [80%] white) included mostly family members (3879 participants [90.0%]). The Pearson correlation coefficient (0.65) and weighted κ statistics (0.48) indicated only moderate agreement between ranking of nursing homes' performance by the 2 measures and disagreement on ranking for approximately one-half of the nursing homes. Conclusions and Relevance: Current nursing home report cards might not reflect consumers' values and the relative importance consumers place on each of the quality indicators that compose the overall Five-Star measure. Quality report cards might be more relevant to consumers by augmenting the Five-Star measure with a measure reflecting consumers' preferences. It is unknown whether these conclusions are generalizable to other report cards, such as Hospital and Home Health Compare, without conducting similar studies for these report cards.

Certificate of need and the cost of competition in home healthcare markets.

We used 2010-16 Medicare Cost Reports for 10,737 freestanding home health agencies (HHAs) to examine the impact of home health (HH) and nursing home (NH) certificate-of-need (CON) laws on HHA caseload, total and per-patient variable costs. After adjusting for other HHA characteristics, total costs were higher in states with only HH CON laws ($2,975,698), only NH CON laws ($1,768,097), and both types of laws ($3,511,277), compared with no CON laws ($1,538,536). Higher costs were driven by caseloads, as CON reduced per-patient costs. Additional research is needed to distinguish whether this is due to skimping on quality vs. economies of scale.

Using contingent valuation to develop consumer-based weights for health quality report cards.

OBJECTIVE: The current 5-Star composite measure for nursing homes uses expert-driven weights to combine elements of quality into a single score. We assessed the feasibility of using the contingent valuation method (CVM) to derive consumers' preference-based weights for the Nursing Home Compare report card as a potential alternative approach. DATA SOURCES: Survey of 4310 adults with nursing home experience (residents or family members of a resident) administered between September 25 and October 9, 2017. STUDY DESIGN: Contingent valuation method based on respondents' answers to questions about willingness-to-trade (WTT) visit travel time for better quality in seven quantitative indices included in Nursing Home Compare. We calculated WTT amounts per standard deviation change in quantitative indices to derive weights. DATA COLLECTION METHODS: Web-based survey. PRINCIPAL FINDINGS: Contingent valuation method results are consistent with respondents making economically rational trade-offs between quality and travel time. Estimates of mean WTT vary across quantitative quality indices. They also vary in terms of respondent status and behavioral factors. Weights based on mean WTT per standard deviation vary substantially across indices, with the largest weights for inspections and staffing. CONCLUSIONS: Contingent valuation method has promise as a method for deriving weights for use in summary measures that incorporate consumer preferences.

Patients' preferences over care settings for minor illnesses and injuries.

OBJECTIVES: To identify consumers' preferences over care settings, such as physicians' offices, emergency rooms (ERs), urgent care centers, retail clinics, and virtual physicians on smartphones, for minor illnesses. DATA SOURCES: A survey conducted between 9/27/16 and 12/7/16 emailed to all University of California, Irvine employees. STUDY DESIGN: Participants were presented with 10 clinical scenarios and asked to choose the setting in which they wanted to receive care. We estimated multinomial conditional logit regression models, conditioning the choice on out-of-pocket costs, wait time, travel time, and chooser characteristics. DATA COLLECTION: 5451 out of 21 037 employees responded. PRINCIPAL FINDINGS: Out-of-pocket costs and wait time had minimal impact on patient's preference for site of care. Choices were driven primarily by the clinical scenario and patient characteristics. For chronic conditions and children's well-visits, the doctor's office was the preferred choice by a strong majority, but for most acute conditions, either the ER (for high severity) or urgent care clinics (for lower severity) were preferred to the office setting, particularly among younger patients and those with less education. CONCLUSIONS: Patients have several alternatives to traditional physicians' offices and ERs. The low impact of out-of-pocket costs suggests that insurers interested in encouraging increased utilization of alternatives would need to consider substantial changes to benefit structure.

Hospital Discharge and Selecting a Skilled Nursing Facility: A Comparison of Experiences and Perspectives of Patients and Their Families.

PURPOSE OF STUDY: A currently proposed rule by the Centers for Medicare & Medicaid Services would require providers to devote more resources to discharge planning from hospitals to ensure the prioritization of patient preferences and goals in the discharge planning process. Annually, more than 3 million persons enter a nursing home in the United States, with the vast majority of patients coming directly from hospitals. Although early evidence suggests more family involvement than patient involvement in the discharge process, most of this work has relied on retrospective reports of the decision-making process postplacement. This article seeks to examine and compare the experiences and perspectives of patients and others involved in the selection of the nursing home (predominately adult children and spouses). PRIMARY PRACTICE SETTING: Large academic medical hospital with patients being discharged to a skilled nursing facility. METHODOLOGY AND SAMPLE: A total of 225 patients or their family members and involved others who completed an exit survey assessing their experiences and perspectives in selecting a skilled nursing home and in experiencing the discharge process more generally. RESULTS: Patients were the primary decision makers about 23% of the time but were often involved in the decision even when family members/involved others were primarily making decisions in the discharge process. Although patients were involved in the selection of the nursing home to a lesser degree than involved others, their level of satisfaction with the decision to be discharged to a skilled nursing home and their level of satisfaction with their personal level of involvement with the selection of the specific nursing home did not differ from the satisfaction ratings of the involved others. Furthermore, their confidence in the decision and their satisfaction with the decision did not differ from ratings provided by family members/involved others. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE: Recommendations for case management practice include (1) encouraging patients and their families to take an active role in the discharge process; (2) incorporating technology into the discharge process that promotes this active level of engagement; and (3) facilitating access to data to promote discharge to the highest quality nursing homes available.

Impact of Nursing Home Palliative Care Teams on End-of-Life Outcomes: A Randomized Controlled Trial.

BACKGROUND: Deficits in end-of-life care in nursing homes (NHs) are reported, but the impact of palliative care teams (PCTeams) on resident outcomes remains largely untested. OBJECTIVE: Test the impact of PCTeams on end-of-life outcomes. RESEARCH DESIGN: Multicomponent strategy employing a randomized, 2-arm controlled trial with a difference-in-difference analysis, and a nonrandomized second control group to assess the intervention's placebo effect. SUBJECTS: In all, 25 New York State NHs completed the trial (5830 decedent residents) and 609 NHs were in the nonrandomized group (119,486 decedents). MEASURES: Four risk-adjusted outcome measures: place of death, number of hospitalizations, self-reported moderate-to-severe pain, and depressive symptoms. The Minimum Data Set, vital status files, staff surveys, and in-depth interviews were employed. For each outcome, a difference-in-difference model compared the pre-post intervention periods using logistic and Poisson regressions. RESULTS: Overall, we found no statistically significant effect of the intervention. However, independent analysis of the interview data found that only 6 of the 14 treatment facilities had continuously working PCTeams throughout the study period. Decedents in homes with working teams had significant reductions in the odds of in-hospital death compared to the other treatment [odds ratio (OR), 0.400; P<0.001), control (OR, 0.482; P<0.05), and nonrandomized control NHs (0.581; P<0.01). Decedents in these NHs had reduced rates of depressive symptoms (OR, 0.191; P≤0.01), but not pain or hospitalizations. CONCLUSIONS: The intervention was not equally effective for all outcomes and facilities. As homes vary in their ability to adopt new care practices, and in their capacity to sustain them, reforms to create the environment in which effective palliative care can become broadly implemented are needed.

Personalizing Nursing Home Compare and the Discharge from Hospitals to Nursing Homes.

OBJECTIVE: To test whether use of a personalized report card, Nursing Home Compare Plus (NHCPlus), embedded in a reengineered discharge process, can lead to better outcomes than the usual discharge process from hospitals to nursing homes. DATA SOURCES/SETTING: Primary data collected in the Departments of Medicine and Surgery at a University Medical Center between March 2014 and August 2015. STUDY DESIGN: A randomized controlled trial in which patients in the intervention group were given NHCPlus. Participants included 225 patients or their family members/surrogates. DATA COLLECTION: Key strokes of NHCPlus users were recorded to obtain information about usage. Users were surveyed about usability and satisfaction with NHCPlus. All participants were surveyed at discharge from the hospital. Survey data were merged with medical records. PRINCIPAL FINDINGS: About 85 percent of users indicated satisfaction with NHCPlus. Compared to controls, intervention patients were more satisfied with the choice process (by 40 percent of the standard deviation p < .01), more likely to go to higher ranked five-star nursing homes (OR = 1.8, p < .05), traveled to further nursing homes (IRR = 1.27, p < .10), and had shorter hospital stays (IRR = 0.84, p < .05). CONCLUSIONS: Personalizing report cards and reengineering the discharge process may improve quality and may lower costs compared to the usual discharge process.

Prototype End-of-Life Quality Measures Based on MDS 3 Data.

BACKGROUND: The Nursing Home Compare (NHC) report card does not include end-of-life (EOL) quality measures (QMs). OBJECTIVES: To develop and examine the properties of EOL QMs. SUBJECTS: A total of 39,590 nursing home decedents in 626 facilities in New York State in fiscal year 2012. DESIGN: Statistical analyses of Minimum Data Set 3 data, including multivariable regression analyses and descriptive statistics. MEASURES: Death in the hospital, number of hospitalizations, pain, and depression during the last 90 days before death. RESULTS: Overall, 32% of residents died in the hospital. They averaged 0.49 hospitalizations in the last 90 days before death, 10% reported moderate to severe pain, and 17% had depressive symptoms. The EOL QMs exhibited variation across facilities similar to that observed for other QMs. They showed low or moderate correlations. The pain and depression QMs were significantly better among nursing homes ranked by NHC as 4 and 5 stars compared with those ranked as 1 and 2 stars for most dimensions. The hospitalizations QMs were significantly better among nursing homes ranked by NHC as 4 and 5 stars compared with those ranked as 1 and 2 stars only when compared on the staffing dimension. CONCLUSIONS: The Minimum Data Set 3 includes much information that can be used to assess quality of EOL care in nursing homes. The prototype measures we developed could be improved if information about advance directives and the nonclinical aspects of care, such as comfort and emotional support for both the resident and the family and respect for resident and family preferences, were collected.