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The American Journal of Managed Care November 2014
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Influence of Hospital and Nursing Home Quality on Hospital Readmissions
Kali S. Thomas, PhD; Momotazur Rahman, PhD; Vincent Mor, PhD; and Orna Intrator, PhD

Influence of Hospital and Nursing Home Quality on Hospital Readmissions

Kali S. Thomas, PhD; Momotazur Rahman, PhD; Vincent Mor, PhD; and Orna Intrator, PhD
This study examines the joint influence of the quality of the hospital and of the nursing home to which a patient was discharged on the likelihood of re-hospitalization.
This study employs a nonexperimental, retrospective, statistical association-based research design. We used cross-classified random effects models (CCREMs) estimated in SAS Proc Mixed28-31 to examine the influence of multiple contexts (NHs and hospitals) on rehospitalization, while simultaneously adjusting for the unmeasured variability attributable to each context. Because hospital and NH quality are analyzed simultaneously, results represent each care setting’s unique influence on rehospitalization. We performed initial assumption testing and confirmed the variables included in these models do not approach multicollinearity. Although we have a dichotomous outcome, we use a linear probability model for 3 reasons: a) given the size of the data, it is computationally intensive to estimate a logit model; b) linear probability models give interpretable coefficients directly, unlike logit models which require calculating marginal effects; and c) these types of models have been used when estimating hospitalization and rehospitalization.32-34 Linear probability models treat the zero-one outcomes as continuous, approximating the probability of observing a rehospitalization.35,36 Additional details about the CCREM used in this analysis are provided in eAppendix A. Use of these data was approved by the Brown University Institutional Review Board.

RESULTS

Twenty percent of our sample was rehospitalized within 30 days of hospital discharge. Table 1 presents the descriptive characteristics of the patient sample, the NHs, and the hospitals included in these analyses. The average resident in our sample was 80 years old with an average hospital stay of 9 days (median = 6). Most patients were white (87%) and female (65%). The most common diagnoses (either primary or comorbidities) were hypertension (55%), followed by fluid and electrolyte disorders (30%), and chronic pulmonary disease (22%). These patients had a low average cognitive performance scale score (mean = 1) indicating that they were, on average, cognitively intact, and had an average activities of daily living score of 16 (moderate impairment). Patients in our sample were discharged from 3683 hospitals, with 43%, 48%, and 46% having a 90th percentile score on their AMI, pneumonia, and CHF accountability measures, respectively. The patients in our sample were admitted to 15,356 NHs. The average proportion of nursing staff that were RNs was 86%. The average RN, LPN, and CNA staffing levels in the NHs were 0.40, 0.85, and 2.28 hours per resident day (HPRD), respectively, and the average weighted deficiency score was 76.5.

Approximately 5% of patients were discharged from higher-quality hospitals (those with AMI, CHF, and pneumonia scores greater than 90% and whose ratio of RNs to licensed nurses were greater than the mean) to higher-quality NHs (those with staffing ratios greater than the mean and weighted deficiency scores less than the mean). Approximately 59% of patients were discharged from lower-quality hospitals (those with AMI, CHF, and pneumonia scores less than 90% and whose ratio of RNs to licensed nurses were below the mean) to lower-quality NHs (those with staffing ratios less than the mean and weighted deficiency scores greater than the mean).

Relative Effects of Hospital Quality Versus Nursing Home Quality

Independent variables associated with hospital quality were significantly associated with 30-day rehospitalization rates. Specifically, a process score for AMI below 90% was associated with a statistically significant absolute increase of 0.37 percentage points in the likelihood of rehospitalization, representing a 2% relative increase over the unadjusted mean (20%). Residents discharged from hospitals with a lower proportion of total nurses who were RNs had an absolute increase of 0.59 percentage points in the likelihood of rehospitalization, representing a 3% relative increase over the unadjusted mean. In addition, patients that were discharged from an urban, nonprofit, non-JCAHO-accredited teaching hospital with a higher occupancy rate were at an increased likelihood of being rehospitalized within 30 days.

A number of NH characteristics were related to the likelihood of rehospitalization. Patients discharged to NHs with lower RN staffing levels, low occupancy levels, and a higher weighted deficiency score were at an increased risk of rehospitalization. Specifically, patients discharged to an NH with lower RN staffing levels and a higher weighted deficiency score experienced an absolute increase of rehospitalization of 0.19 percentage points and 0.16 percentage points, respectively. Being discharged to an NH with low occupancy rates was associated with a 0.55 percentage point increase in the likelihood of rehospitalization, representing a 3% relative increase over the unadjusted mean likelihood of rehospitalization. Patients who were discharged to freestanding, for-profit NHs with a higher proportion of Medicaid residents and a higher number of admissions per bed were associated with an increased likelihood of rehospitalization.

Variability in Rehospitalization

Our model also allows us to assess the variation in rehospitalization attributable to patient characteristics, hospital characteristics, and nursing home characteristics. Most variation in rehospitalization is explained by the patient characteristics included in the model (32.4%). Of those patient characteristics, 16.5% of the variation was attributable to the characteristics that are controlled for in the NQF measure of rehospitalization (age, gender, and comorbidities). Hospital quality measures explained an additional 1.7% of the variation in rehospitalization rates and NH quality measures contributed to an additional 1.3% of the variation.

DISCUSSION

This is among the first studies, to our knowledge, that examines the relative influence of hospital quality and NH quality on rehospitalizations for patients discharged to an NH. The underlying reasons for the high rates of NH rehospitalization are numerous and complicated, but our initial results suggest that patients discharged from higher-quality hospitals (as measured by a high RN-tototal-nurse ratio and a high score on the AMI process summary measure) to higher-quality NHs (as measured by higher RN staffing levels and a lower weighted deficiency score) experience significantly lower 30-day readmission rates. Our results build on previous research and confirm our hypotheses that both hospital and NH quality are related to rehospitalizations within 30 days of an acute hospital stay. These findings offer an important first step toward understanding the relative influence of both players, hospitals and nursing homes, in rehospitalization rates. Furthermore, our findings set the stage for additional, more sophisticated analyses required to better understand which entity is ultimately “more” accountable.

Our findings echo the perspective of others,37 in that much of what drives hospital readmission rates are patient-level factors that are well outside the hospital’s control. Specifically, most of the variation in rehospitalization in our model is attributable to patient characteristics, while NH quality and hospital quality account for only 2.8% of the explained variation. In the new healthcare environment, where quality and outcomes are increasingly linked to reimbursement and public reporting initiatives, it is important that rehospitalization rates be adequately adjusted for patients’ underlying risks of rehospitalization. The Hospital Readmissions Reduction Program accounts for age, gender, comorbidities, and selected medical history when risk-adjusting these rates.38 However, as our results show, there are many additional patient-level factors that contribute to a hospital’s readmission rate from an NH, including patients’ demographic characteristics, functional impairment, cognitive functioning, and even preferences as indicated by the strength of the variables indicating whether the patient had an advanced directive. It is important that these characteristics are taken into account when risk-adjusting rehospitalization, particularly for patients who are discharged to an NH.

NHs and hospitals are similar to suppliers and manufactures: manufacturers are dependent on the supplier for a high-quality product and the suppliers are dependent on the quality and success of manufacturers for business. If an organization and its supplier establish a relationship that benefits both sides, then the relationship will enhance “the ability of both to create value.”39 With the advent of the Total Quality Management philosophy of doing business, ways to assure quality performance—such as by establishing an atmosphere of trust, teamwork, and cooperation—become more important. Hospitals and NHs (like suppliers and manufacturers) working together as partners is the way both can assure quality products and outcomes. In addition to implementing quality improvement projects within the hospital, hospitals should track and observe trends to identify which NHs frequently readmit patients in an effort to partner with these NHs to identify opportunities for improvement and education, and to provide optimal patient care. Hospitals committed to reducing readmissions from NHs must assess their processes from admission (evaluating risk of readmission), to discharge planning, handoffs, and follow-up. In addition, it is important that hospital discharge planners are familiar with NHs to ensure that they are adept at matching patients with NHs that can best meet their continuing medical needs.

It is also in NHs’ best interests to work to improve their quality and lower readmission rates. The Medicare Payment Advisory Commission has advised Congress to impose penalties on NHs with high rehospitalization rates as well as to require public reporting of rehospitalization rates to consumers. Results from our study suggest that facilities with lower quality, based on nurse staffing and state survey citations, do indeed have higher rehospitalization rates. Increased attention and efforts to boost the quality of lower-performing NHs may have the added benefit of reducing the rehospitalization rate.

Limitations

Our study has several limitations worth noting. First, the only hospital quality measures related to the delivery of inpatient care came from the 3 condition-specific measures in Hospital Compare. While we selected items that measure the actual care delivered, have been linked to outcomes, have been endorsed by JCAHO, are used as resources for consumer decision making, and have been used in other studies related to quality, we must consider other processes of care that may be distinctly relevant to this unique population discharged to NHs. These include potentially focusing on frailty, symptom relief, and end-of-life issues. In addition, only 1 process summary measure was related to rehospitalizations. One explanation for this may be the robustness of this measure, as it is composed of 5 individual measures in relation to the other 2 summary measures for CHF and pneumonia (composed of 1 and 2 individual measures, respectively). In regards to our NH quality data, we did not have any measure of care coordination or the process of admitting patients from the hospital. Future research is needed to understand the impact of the relationship between hospitals and NHs on rehospitalizations.

 
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