Background:
Defined approaches to reducing rates of hospital readmissions rates assume that patients are invested in their healthcare and in preventing readmissions. However, the extent to which patients believe that readmission is a “bad” outcome and feel that it is inevitable have not been defined. Further, the ability of patients to anticipate their own readmissions is unknown. Understanding these attitudes may help us tailor interventions toward patients who are at high risk for readmission based on disengagement or fatalistic attitudes. Here we report preliminary results of an ongoing prospective study of medicine inpatients on the day of hospital discharge about their attitudes regarding readmissions.
Methods:
We provided a self-administered questionnaire to patients at discharge; we focus here on 3 questions related to attitudes about readmissions. These included (1) “How likely is it that you will be admitted to any hospital again within the next 30 days after you leave the hospital this time?” Responses were based on a Likert scale ranging from ‘very likely’ to ‘very unlikely’ (2) “How would you feel about being re-hospitalized in the next month?”, responses ranging from ‘very happy or relieved’ to ‘very sad, frustrated or disappointed’; (3) “How much do you think that you personally can control whether or not you will be re-hospitalized?”, responses ranging ‘I have complete control’ to ‘I have no control’. For analyses, responses were dichotomized. Same hospital readmissions were determined via administrative data. Expected readmission rates for each patient were defined using University Health System Consortium benchmarks to account for diagnosis and severity of illness. We used multivariable logistic regression to calculate adjusted odds ratios (aORs) for 30 day readmission rates with expected readmission rate, sex, age and race included as adjustor variables in all models.
Results:
438 patients provided an estimate of readmission risk and had available readmission data and were included in this analysis. Of these, 18% were readmitted within 30 days. After adjustment, the 20% who thought their readmission was likely had a significantly higher rate of readmission than those who thought it unlikely (aOR 2.0, 1.2-3.6). The 23% who did not indicate they would be unhappy to be readmitted had a similar readmission rate to those who would be unhappy (aOR 1.1, 0.6-1.9). The 37% who felt they had little or no control over whether they were readmitted had a non-significantly higher readmission risk than those who believed they had some control (aOR 1.4, 0.8-2.4). Race, age, and sex were not associated with perceived control, but women were significantly more likely than men to report they would be unhappy to be readmitted (aOR 1.9, 1.2-2.9).
Conclusions:
These data suggest that patients may be able to predict their own readmissions, even after adjusting for other factors. We did not find a significant association between readmissions and patient disempowerment in this preliminary analysis. Although most patients did not want to be readmitted, this attitude was not universal. Expanding our sample size with continued enrollment may clarify these findings. Regardless, these data highlight the potential importance of understanding patient attitudes, beliefs and preferences when undertaking readmission reduction initiatives.