There were 687,956 new admissions across 677 nursing homes over the 1998–2004 study period. These new admissions experienced 408,534 hospitalizations, of which 217,697 were first-time hospitalizations. The total number of distinct at-risk periods for hospitalization was 3,377,076 and the total number before or including the first hospitalization was 2,396,319. The proportions of residents who died in a hospital and in a nursing home were 8.27 percent and 17.52 percent, respectively; thus, 25.79 percent of residents died during the study period. shows the unadjusted means and standard deviations (for nonbinary variables) of the predictors for the four categories of at-risk periods corresponding to whether the first hospitalization had yet to occur at the start of the period and whether hospitalization terminated the period.
The Kaplan–Meier survival function (unadjusted for covariates) is displayed in as a function of the number of past hospitalizations. The average time until next hospitalization decreases markedly with the number of previous hospitalizations; the biggest drop is between the first and second hospitalizations; thereafter the decrements are smaller but of consistent magnitude. These observations are consistent with the use of a binary indicator of a past hospitalization from the nursing home both as a main and interaction effect predictor and the log of the number of past hospitalizations (if any) just as a main effect predictor in the time between hospitalization model.
Kaplan–Meier Curves of Time to Hospitalization by the Number of Past Hospitalizations
Time to First Hospitalization
The models in and were fit to the 50 percent training sample. A positive (negative) regression coefficient implies a longer (shorter) time to hospitalization. Male and married residents had shorter times to first hospitalization (). Of the daily life variables, medication count and receipt of a special treatment had the strongest associations with shorter time to hospitalization. Bladder incontinence was protective against hospitalization, while severe physical or cognitive functioning and use of a feeding tube or intravenous drip for nutrition were associated with less time to hospitalization. Partial restraint (bedrails alone or trunk, limb, and chair alone) was associated with a shorter time to hospitalization. Chronic conditions such as stage 2+ (pressure) ulcer, CHF, diabetes, unstable conditions, and cancer were also associated with shorter time to hospitalization. Interestingly, the only two chronic conditions that were protective against hospitalization, Alzheimer's/dementia and neurological disease, were both mental health conditions.
Effects on Time to First Hospitalization
Effects on Time between Hospitalizations
In terms of measures of changes in a resident's health status, the number of days physicians changed care needs orders and weight loss were associated with shorter times to hospitalization, while, as expected, residents more self-sufficient (i.e., with improved care needs) than at their last MDS assessment were associated with longer times to hospitalization. Residents less self-sufficient (i.e., having greater care needs) were hospitalized more frequently. Shortness of breath and vomiting were the symptoms associated with greatest risk of hospitalization. Recent fractures (especially hip) were generally protective against hospitalization, which may reflect the increased rehabilitative care and limited mobility following a fracture. An acute episode related to a chronic problem and infection had the strongest associations with shorter time to hospitalization among the acute condition predictors. Pneumonia was only moderately associated with time to hospitalization, although many cases of pneumonia (and other acute illnesses) are likely missed in the regular MDS assessment due to their sudden onset.
In terms of resident preferences, the presence of advance directives (in particular the “do-not-hospitalize” directive) was strongly protective of hospitalization. Among the financial predictors, residence in the nursing home for 100 days or more and payment by Medicaid (relative to private pay) were protective of hospitalization. Payment by Medicare was also associated with shorter times to hospitalization relative to private-pay status.
There was modest evidence that residents in nursing homes with more registered nurses per bed had a longer time to hospitalization (p=.10), while residents in nursing homes with greater deficiencies had shorter time to hospitalization. Higher facility-level CMI scores (indicating that patients are on average in worse health status) were associated with shorter times to hospitalization and the percentage of Medicare and Medicaid residents were associated with longer times to hospitalization, respectively. The hospitalization rates at government-owned facilities were much higher than at for-profit facilities, while the rates at nonprofit and for-profit facilities were similar.
Time between Hospitalizations Model
The predictors in the time to first hospitalization model had similar effects in the time to next hospitalization model (). Thus, to avoid redundancy, in this section we focus on the results for the main effects of past hospitalization and the log of the number of past hospitalizations (see Appendix SA2
for precise definition) and the interaction effect of other predictors with past hospitalization. The fact that the significant interactions are only with the binary indicator of any past hospitalization and not the log of the number of past hospitalizations reveals that although the effects of some predictors change substantially after first reentry to the nursing home from hospital, there is little additional modification thereafter.
The main effects of past hospitalization, −0.54, and the log of the number of the number of past hospitalizations, −2.67, are highly significant, implying that the time between hospitalizations decreases substantially after a resident has been hospitalized. The slope of the combined effect of these variables has a steep downward trajectory that flattens as the number of hospitalizations increases, consistent with the nonoverlapping Kaplan–Meier survival functions displayed in .
With the exception of more self-sufficient (i.e., resident has fewer care needs), all of the interaction effects with past hospitalization are positive, whereas their main effects are negative. In the case of more self-sufficient, the interaction effect is larger than the main effect; thus, more self-sufficient is a risk factor for further hospitalization among readmitted residents. The overall effect of number of days a physician changed a resident's orders, unstable condition, cancer, CHF, and shortness of breath were negative but closer to zero than their main effects.
The signs of all statistically significant effects in both models were generally the same across the training and test samples and cohered with our intuition. There was minimal evidence of overfitting or lack of face validity. In particular, given that one of the major contributions of this paper is to account for the effect of past hospitalizations on the time to next hospitalization, it is reassuring that the estimated interaction effects in the time between hospitalization model were among the most similar effects across samples.