The American Journal of Managed Care June 2015
Higher 30-Day and 60-Day Readmissions Among Patients Who Refuse Post Acute Care Services
On average, refusers were significantly younger than acceptors (aged 68 years vs 73 years, respectively; P <.001). Refusers were significantly more likely to be married (62% vs 46%; P <.001), have private or other insurance versus straight or managed Medicare or Medicaid (35% vs 18%; P <.001), be admitted electively (30% vs 14% emergently or transfer; P <.001), have lower risk of mortality/severity of illness (eg, 31% were in the “major/extreme risk” category vs 53%; P <.001) and have shorter lengths of hospital stay (4.8 days vs 7.5 days; P = .001) than acceptors. See Table 1 for more details.
Very little was documented about the reasons for refusal. Almost half of the refusers (46%) gave no explanation, 34% said they did not see the need for nursing services, and 8% said they would rely on their caregivers.
Quality of life. Refusers reported a higher overall quality-of-life index compared with acceptors (0.83 vs 0.73 respectively; P <.001) (Table 2). Refusers also experienced fewer limitations on almost all quality of life subscales, including fewer problems with mobility (44% vs 49%; P <.001), self-care (13% vs 30%; P <.001), and usual activities (39% vs 58%; P <.001), and they reported less pain and discomfort (33% vs 44%; P = .03).
Problems after discharge. Refusers reported significantly fewer problems, except for physical problems (82% vs 86% respectively; P = .29) (Table 3). For instance, refusers experienced fewer problems with personal care (14% vs 39%; P <.001), household activities (47% vs 75%; P <.001), mobility (52% vs 73%; P <.001), psychological issues (38% vs 55%; P <.001), and aids or equipment (2% vs 9%; P = .01) than acceptors.
Unmet needs. Refusers reported fewer unmet needs overall (6.6% vs 10.5% respectively; P <.001) and on almost all the unmet needs subscales (Table 4). For instance, only 5% of refusers reported 1 or more psychological unmet needs compared with 18% among acceptors (P <.001). Similar significant differences were found on the following subscales: personal care (3% vs 7%; P = .02); household activities (7% vs 18%, P <.001); mobility (3% vs 16%; P <.001); physical (14% vs 27%; P <.001); aids or equipment (3% vs 10%; P = .01); and instructions and directions for unmet needs (4% vs 14%; P <.001).
Association Between PAC Refusal and Risk For 30/60-Day Readmission
Nearly 21% (n = 29) of refusers experienced 30-day readmission compared with 16% (n = 56) of acceptors. Although this was a 5% clinically significant difference, the difference was not statistically significant (P = .17). At 60 days, 31% (n = 43) of refusers experienced readmission compared with 25% (n = 89) of acceptors (P = .18). Bivariate analysis (unadjusted; only significant associations reported) of 30-day readmission showed that readmitted patients had longer length of index hospital stay (9.7 days vs 6.2; P <.001); had higher incidence of hospital admissions within the last 6 months (35% were readmitted 2 or more times vs 24%; P = .01); and lower quality of life index scores (0.67 vs 0.78; P <.001). Bivariate analysis of 60-day readmission showed that readmitted patients were significantly younger (aged 69.4 years vs 71.8; P = .02); had longer length of index hospital stay (8.6 days vs 6.1; P <.001); had slightly higher number of prescribed medications (10.6 vs 9.1; P = .01); and had higher incidence of hospital admissions within the last 6 months (40% were readmitted 2 or more times vs 21%; P <.001).
In the logistic regression model of 30-day readmission adjusted for those factors and quality-of-life index, percent of problems, and percent of unmet needs, 4 significant factors emerged: 1) refusers were more than twice as likely to be readmitted (OR [odds ratio], 2.13; 95% CI, 1.21-3.75; P = .01) than acceptors; 2) patients with better quality of life (higher indices) were less likely to be readmitted (OR, 0.10; 95% CI, 0.02-0.43; P <.001); 3) patients with longer index hospitalization stays were more likely to be readmitted (OR, 1.03; 95% CI, 1.01-1.06; P = .01); and 4) patients with more previous overnight hospitalizations in the past 6 months were more likely to be readmitted (P = .04) (Table 5).
In the adjusted logistic regression model of 60-day readmission, 2 significant factors emerged: 1) refusers were almost twice as likely to be readmitted (OR, 1.80; 95% CI, 1.11-3.02; P = .02) than acceptors; and 2) patients with more previous overnight hospitalizations in the past 6 months were more likely to be readmitted (P <.001) (Table 5). Ad hoc power analysis confirmed that the sample size (n = 495) was adequate to provide 80% power to answer the study questions.25
This study showed that 28% of patients who were offered post acute care refused the services. This alarming finding validates other anecdotal reports on the high rates (6% to 27%) of PAC refusal.12-14 Typically, about 30% of hospitalized patients receive referrals for PAC,2 but in our study, 71% were offered a referral. This high rate was consistent across the 2 hospital sites and is either a reflection of the use of screening tools that highlighted high-risk patients, or over-referral due to efforts to deter readmissions by using PAC support.
In an attempt to better understand the characteristics of the PAC refusers, we identified that they were younger and more likely to be married and have private medical insurance. From the clinical perspective, refusers were less medically complex, had shorter index hospital stays, and were more likely to be admitted electively rather than by emergent admissions or transfer from other facilities. At 7 to 14 days after hospital discharge, refusers reported better quality of life and fewer health-related problems and unmet needs than acceptors.
From the patient perspective, refusers may also see themselves as less medically complex. Chart review of the documentation of the reasons for refusal revealed that the most frequently reported reasons were, “I don’t need it” and “My wife will take care of me.” If we can better understand the barriers to PAC acceptance, we can tailor interventions to overcome those barriers. The reasons for refusal also indicate the importance of including the caregivers in the conversations or confirming the patient’s responses to make sure the patient’s caregiver really agrees and is capable of meeting the patient’s healthcare needs. In nearly half the refusals, no details were documented as to why the service was refused. Understanding the reasons for refusals and patient preferences regarding care after discharge will help clinicians to better match services to what patients and caregivers will accept. Clinicians must probe to make sure patients and caregivers understand what is offered and why it is offered, and they must document why patients and caregivers are refusing.
Patients may refuse services because they do not understand the value of those services. Gregory26 studied stroke patients during hospitalization to assess their preferences about rehabilitation. Eighty-five percent preferred rehabilitation in their homes to inpatient rehabilitation or skilled nursing facility care, even though more aggressive inpatient rehabilitation may result in improved functional outcomes.26 Three explanations for disparities in patients’ acceptance of rehabilitation services were found: 1) a lack of financial or functional eligibility, 2) a failure to recognize the need for services during the acute care stay, and 3) a patient’s preference to return home and not pursue therapy elsewhere. Further research is needed to validate the reasons for PAC refusal on a larger patient sample and to match services to patient preferences.
Refusers were more likely to be readmitted. Since we did not find other studies examining the characteristics and readmission rates of PAC refusers, further research to validate these results is warranted. We may discover that factors such as adherence, health literacy, and level of engagement are as important as clinical risk factors in identifying which patients are likely to fail after discharge.27,28 While the appearance of refusers may seem to be healthier, and their reassurances that they can manage their post acute needs with only informal supports are convincing, our data have shown that they suffer more readmissions and therefore we need to understand why.
Our findings also showed that patients with better self-reported quality of life after discharge were less likely to experience 30-day readmission. Those results match current reports of the positive association of quality of life and health outcomes.29-32 This finding indicates the need to carefully evaluate and support any unmet needs in pain management, self-care, and activities of daily living functions to optimize quality of life. In agreement with several recent studies,33-35 we found that shorter hospital stays were not associated with higher readmission rates. On the contrary, patients with longer hospital stays had higher odds of 30-day readmission, even when controlling for several indicators of clinical severity. Lastly, our finding of a positive association between previous overnight hospitalizations in the last 6 months and 30- and 60-day readmission is not new; several other studies have reported the same.36-38
Among acceptors, the high levels of problems, unmet needs, and quality-of-life issues reported are notable. Twenty-seven percent, 44%, and 49% reported quality-of-life issues with anxiety or depression, pain, and mobility, respectively, and 74% had unmet information needs. This may indicate that discharge plans or post acute care settings are not adequately meeting their needs, or perhaps our assessment was too early in the episode to show improvement. Nonetheless, instruments such as the PADQ-E and EQ-5D appear helpful to PAC providers to focus on the exact problems and unmet needs patients are experiencing.
One limitation of this cross-sectional study is our limited ability to control for the quality/quantity of the PAC services offered to acceptors, which may have influenced readmission rates. The study was limited to medical units of 2 large urban academic hospitals in the northeast United States.
We found that patients identified as high risk for poor discharge outcomes and referred for PAC services, who nonetheless refused such post acute services as home care, experienced 5% higher readmission rates and were twice as likely to experience readmission at 30 and 60 days than patients who accepted the services—despite the fact that acceptors had higher severity-of-illness scores, lower quality of life, and more problems and unmet needs after discharge. These findings suggest the powerful effect of post acute care support in preventing readmission, and lead us to call for more research into the reasons for service refusal, and for why refusers are readmitted more often although they appear to be less in need of post acute support.
Author Affiliations: Harvard Medical School & Brigham Women’s Health Hospital (MT), Boston; University of Pennsylvania School of Nursing (YK, KHB), Philadelphia; Hospital of the University of Pennsylvania (KR), Philadelphia; Mayo Clinic Department of Nursing, College of Medicine (DEH), Rochester, MN; Langone Medical Center, New York University (BO), New York, NY.
Source of Funding: The investigators acknowledge grant support from the National Institute of Nursing Research (RO1-NR07674); this grant supported the original development of the D2S2. The Edna G. Kynett Foundation, the NewCourtland Center for Transitions and Health, the Leonard Davis Institute of Health Economics, and the Frank Morgan Jones Fund all supported data collection and data analyses for the primary study. The Center for Integrative Science in Aging (University of Pennsylvania School of Nursing) provided funding for the secondary analysis.
Author Disclosures: Dr Bowles owns equity in RightCare Solutions, a company that commercialized some aspects of this work. The original study was conducted and completed before the equity was obtained. The University of Pennsylvania conflict of interest committee reviewed the study and assigned a management plan that required an independent statistician complete the study analysis and lead the interpretation of study results. The plan was followed exactly. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (KHB, DEH); analysis and interpretation of data (MT, YK); drafting of the manuscript (MT, YK); critical revision of the manuscript for important intellectual content (MT, KHB, YK, DEH, BO, KR); statistical analysis (MT, YK); and supervision (KB).
Address correspondence to: Kathryn H. Bowles, PhD, RN, FAAN, FACMI, University of Pennsylvania School of Nursing, Philadelphia, PA 19104. E-mail: email@example.com.REFERENCES
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