Unplanned hospital admissions and readmissions have become a major focus of efforts to improve the value of healthcare given that these potentially preventable events exert substantial burden on patients, caregivers, health systems, and the economy.1 The percentage of patients who are rehospitalized within 30 days have decreased from 20%-21% at the start of the Accountable Care Act and readmission penalties to approximately 18%.2-5 Rehospitalization rates are 33% at 90 days and approach 40% at six months.6,7 Readmissions cost Medicare more than $26 billion annually,4 with one in five Medicare beneficiaries readmitted within 30 days of hospital discharge.8 Centers for Medicare and Medicaid Services and other payers use condition-specific and all-cause 30-day unplanned readmission rates and potentially preventable admissions among patients with complex or multiple comorbidities for public reporting, value-based purchasing, and performance-based reimbursement.9,10 Consequently, medical groups and hospitals have begun to place an increasing emphasis on improving the transitions of care following hospitalization with the goal of reducing unplanned readmissions.11 Care transitions programs have been shown to decrease readmission rates, mortality, and emergency department (ED) visits.12
Care transitions programs vary greatly in their scope of intervention and target groups, as well as in their efficacy in reducing readmissions.13,14 The Mayo Clinic Care Transition Program, hereafter referred to as CTP, was launched in 2011. This program was modeled after other successful programs and involves home visits by a nurse practitioner (NP) and telephonic support and triage provided by a registered nurse (RN). It is offered to high-risk community-dwelling patients during their hospitalization and begins within a week of hospital discharge.
Although the CTP reduces 30-day readmissions from 20% to 17%,7 it is a highly resource-intensive, multimodal, multidisciplinary program. Moreover, whether some components of the CTP are more critical than others remains unknown. Prior studies that examined the individual components of successful CTPs have suggested that a multipronged approach that includes close patient and caregiver support is most predictive of program efficacy.13 Long-term program sustainability would benefit from optimization of the most critical components of the program while reducing or eliminating resource-intensive factors that have negligible effects on program success. We therefore examined our CTP to identify whether and which program components are most critical for preventing 30-day readmissions and whether any patient characteristics contribute risk within this complex population.
Study Design and Setting
This study is a retrospective cohort study of patients who were enrolled in the care transitions program of Mayo Clinic Rochester during the period January 1, 2010 to June 30, 2013. Patient demographic and clinical data were obtained from electronic health records (EHR), and information regarding CTP processes and interventions was obtained from a prospectively maintained program database. The study complied with the principles of the Declaration of Helsinki and was approved by the Mayo Clinic Institutional Review Board.
The study aimed to describe the performance and utilization of a multidisciplinary care transitions program that has been successful in reducing readmissions for high-risk patients. The study also sought to identify patient and/or program factors associated with failure to prevent readmission within 30 days of program enrollment.
Patients who were enrolled in the CTP following hospital discharge and seen for a posthospital in-home visit prior to hospital readmission (for those readmitted) were included. Patients discharged to a skilled nursing facility were excluded. Patients were eligible for CTP enrollment if they were hospitalized for any cause, community dwelling (including assisted living) prior to hospitalization, and ≥60 years old with an Elder Risk Assessment (ERA) score ≥16.7 The ERA incorporates information regarding previous hospital days, age, and comorbid health burden and has been shown to predict 30-day readmissions, mortality, and critical illness (
Detailed descriptions of the CTP have been previously published.7,17 Patients meeting enrollment criteria are enrolled into the CTP by a RN prior to or immediately after hospital discharge. The patient is then seen at home within one to five business days of discharge and again the following week by a NP who performs medication reconciliation; chronic illness management; and acute illness, mobility, safety, and cognition assessments. The NP also provides patient education on self-care and advance care planning. Patient and caregiver support and liaisons with community resources are provided. Home visits by an NP or MD are continued as needed for at least one month. A RN case manager performs weekly phone calls to assess changes in the patient’s clinical status and is available for phone triage of acute health issues. An interdisciplinary team composed of MDs, NPs, RNs, and pharmacists review patient management at weekly meetings. Although after-hours or weekend coverage for home visits are unavailable, an on-call primary care physician is available by phone at all times.
The primary outcome was all-cause hospital readmission within 30 days of the first CTP home visit, indicating successful program enrollment. Hospitalization was determined on the basis of billing codes from Mayo Clinic hospitals; this approach is 99% reliable in detecting readmissions for this population.18
Secondary Outcome Measures
Secondary outcome measures included six-month mortality and hospitalizations, as well as the number of hospital and ICU days and home, ED, primary care, and specialty office visits within 180 days after index hospitalizations as per the EHR. ED visits were counted only when they did not result in a hospital admission.
Patient characteristics and clinical variables were retrieved from the EHR and included patient age, sex, and marital status. Comorbidities, ERA score,19 and Charlson comorbidity index (CCI)20 within two years of program enrollment were determined by using ICD-9 billing codes. The frequencies of primary care and specialty visits within six months of the index hospitalization were also ascertained using the EHR. Mobility limitations and cognitive impairment were categorized as binary variables (yes/no) and were assessed at the first home visit by the NP. The presence of mobility limitations was defined as a Barthel’s score of <7521,22 or Timed up and Go time of >20 seconds.23 Cognitive impairment was established as Kokmen below the normal cutoff for patient’s age group,24 Mini-Cog ≤2,25or AD8 ≥2.26 If these measures were not specifically documented during the first visit, clinical notes were queried for the description of pertinent cognitive and/or mobility limitations. Dementia diagnosis billing codes (ICD9 Code 290.*) were also included. High medication use was defined as >14 given the reported average medication number ranges from 8-13 in this population.27
As previously published, fidelity measures were abstracted from clinical notes by a trained nurse abstractor within 30 days of program enrollment and prior to a readmission.7 The five program fidelity measures included medication reconciliation, home service evaluation, advanced directives discussion, action plan for acute and chronic disease, safety plan, and discussion of community resources. The presence of advanced care planning was determined on the basis of visit medical notes and/or change of code status within the EHR, the identification or scanning of written advanced directives or “provider order for life-sustaining treatment,” and documentation of the discussion of resuscitation status. It was abstracted in duplicate by a nurse abstractor with physician adjudication for disagreement. Moreover, whether the initial visit met the goal of being within five days of discharge was determined by using billing data.
The contribution of each independent variable to 30-day readmission was first directly assessed by using a univariate logistic regression model. Five patients died within 30 days without being admitted. These deaths, however, were not censored given that home death (as opposed to hospital death) was considered a positive outcome of the CTP. Multivariable modeling was performed through log rank test with backwards elimination and included all independent variables with P < .05. Variables with P values between .05 and >.1 were tested for interaction with age and sex. Age was categorized as <80 or ≥80 years. The length of hospital stay was categorized as <3 days (not qualifying for a Medicare skilled nursing facility), 3-13 days, or ≥14 days.
This study had 30% power to detect a reduction of 5% in the rates of hospital admissions; 5% is the median absolute risk reduction reported by previous randomized studies on care transitions programs previously reported.10 All analyses were performed using SAS 6.01 (SAS Inc., Cary, North Carolina).
The study cohort included 315 patients who met the inclusion criteria (Fig 1). The demographic and clinical characteristics of the participants were ascertained at the time of CTP enrollment and are shown in Table 1. Patients were, on average, 82.5 (SD, 8.2) years old and had multiple comorbidities with a mean CCI score of 6.2 and ERA score of 18.5. Almost half of the patients (43.2%) exhibited cognitive impairment and more than half (51.7%) had mobility limitations. Among the patients, 42.9% had been hospitalized at least once in the 180 days prior to their CTP-qualifying hospitalization and 14.2% had ≥2 hospitalizations prior to their CTP-qualifying hospitalization. Similarly, 32.4% had at least one emergency department (ED) visit, and 3.5% had ≥3 ED visits. The majority of patients had frequent outpatient visits, with 30.8% having ≥4 office visits in primary care and 32.4% having ≥4 specialty office visits in the preceding six months.
Readmissions, Mortality, ED, and Outpatient Visits
Of the 315 patients, 54 (17.1%) had a readmission within 30 days and seven (2%) had >1 readmission. Among the patients, 126 (40.0%) were readmitted at least once within 180 days with 55 (17.5%) having more than one readmission. A total of 41 patients (13.1%) died during the six-month follow-up period. The need for both office and ED visits was reduced compared to the 180 days prior to admission with the biggest difference in ED visits: 72 (22.9%) of patients needed visits within 180 days of enrollment, as opposed to 102 (32.4%) before enrollment.
Impact of Patient Clinical Variables on Readmission Risk
Readmitted patients were less likely to exhibit cognitive impairment (29.6% vs 46.0%; P = .03) and were more likely to have high medication use (59.3% vs 44.4%; P = .047) than patients without readmission (Table 1). Readmitted patients had a higher frequency of visits to primary care (4.0 vs 3.0; P =.02) in the six months prior to admission and more hospital days in the prior year (4.6 vs 2.5; P = .04) than those without readmission.
Multivariable analysis, which included the cognitive status of the patient; the high use of medication; and the number of ED visits, primary care visits, and hospital days in the previous six months, provided a C statistic of 0.665. After backwards elimination, only the cognitive status of the patient and number of ED visits remained predictive of readmission risk.
Impact of Program Interventions on Readmission Risk
The completion of the CTP fidelity measures drastically varied with completion rates between 29.5% (community resource evaluation) and 87.0% (home visit within five days of hospital discharge; Table 2). Only 12.1% of patients received all components of the CTP at the first home visit. Readmission rates among patients who received all program components (13.2%) were lower than those among patients who did not receive all program components. This difference, however, failed to reach statistical significance. No single program component significantly reduced readmission risk. The completion rate of program fidelity measures increased with time (Figure 2). The present findings did not change even after performing sensitivity analysis that excluded the first program year. The overall agreement between chart abstractors on determining whether advance care planning occurred was 69.5% but the Cohens Kappa was only 18.4. This result was largely ascribed to the following: One abstractor counted the presence of a shorthand template used to document the delivery of an advance care planning document as discussion, whereas the other abstractor required further documentation or corroborating evidence (ie, change of code status). The majority of patients required multiple home visits to address ongoing medical needs (mean 2.7; SD = 1.3) over the first 30 days. Among these patients, only 17.1% received one visit, and 54.6% of patients received ≥3 visits. Eleven (3.5%) patients transitioned to a palliative homebound program that we began offering toward the end of this study to meet patient needs.28
The present study met our objective of identifying individual patient factors that are predictive of the success of our CTP. Cognitively impaired patients were less likely to be readmitted than cognitively intact patients. This finding is particularly important because patients with dementia constitute a subgroup that is at an increased risk of readmission after hospitalization29 and often suffer burdensome transitions at the end of life.30,31 High medication use and high number of visits to primary care and number of hospital days in the six months leading up to enrollment increase the likelihood of readmission and are plausible measures of disease severity or multi-morbidity that have been identified in previous studies.32,33 No one program intervention was found to be significantly associated with readmission. This result is consistent with prior works that demonstrated the need for multifaceted and intensive interventions to reduce readmission risk among highly complex and multimorbid patients.13,14
Our findings suggest that the provision of an alternative to stressful hospitalization to cognitively impaired patients and their caregivers may be an important benefit of care transitions programs. Having a trusted team to consult in acute situations may have enabled early intervention and crisis avoidance. Avoiding hospitalizations and ED visits may also have been in line with their goals of care.34,35 Given that program intensity varied on the basis of the discretion of the clinical team, patients with cognitive impairment and their caregivers may also have received more intensive support than cognitively intact patients.
In contrast to recent systematic reviews, our study did not find that advance directive discussion had significant effects on reductions in readmission.36,37 The lack of discussion surrounding the goals of care for patients with serious illnesses was also listed as one of four factors that are strongly associated with preventability in a national cohort of readmitted general medicine patients.38 The lack of power and incomplete documentation may have contributed to our null findings. Trust building must also occur before any meaningful discussion of the goals of care could be achieved, and follow-up time may have to be extended. Toward the end of this study, we developed an extension of our program for patients with limited life expectancy and conservative goals of care. In this extension, reductions in hospitalizations were observed among patients who had multiple goals of care discussions.28
Previous studies have shown that readmissions reduced with timely follow up among patients with heart failure.39 Our results showed no difference in readmission rate based on whether or not our patients were visited within five days from discharge, but we may have been underpowered to detect this difference. In addition, we may have missed readmissions that occurred before the enrollment visit.
The elements of the CTP were evidence based. Fidelity to program goals improved over time and reached high levels with program maturity. Only 12% of the patients received all program components at the first home visit. Patients that had all pillars addressed and documented showed a nonsignificant trend toward reduced readmission rates. NPs were given discretion as to how many visits were required to stabilize a patient and achieve program objectives. Heart failure management was driven by protocol with input from cardiology. Medication reconciliation and clinical assessment with action plan were prioritized at the first visit and thus allowed for the completion of other goals at a subsequent visit if time was insufficient. These decisions were deliberated at weekly physician-led multidisciplinary meetings. This variability allowed the team to meet chronic and urgent needs but further confounded the interpretation of our results. One possible way to interpret the lack of significant predictors of success is that through clinical assessment and flexibility, we were able to tailor our program to meet the needs of this complex multi-morbid population.
This study has important limitations. Given that it is a retrospective cohort study, we were unable to include patients who were enrolled but were either readmitted or dropped out before the first program visit. In addition, because of our study’s limited sample size and readmission rate, we had limited power to detect other potential predictor variables and test for confounding and interaction. While we included numerous variables in our analyses, we lacked information on mental health and the social determinants of health, which are known to influence readmission risk.40,41 Similarly, we lacked patient self-reported measures of health and information regarding caregiver support, which are important.42,43 Several of our predictive measures (cognitive impairment, mobility limitations, and program objective completion) were dependent on supplementing billing codes with heterogeneous data abstracted from usual clinical care as opposed to standardized research protocols. Neither method is completely accurate, nor can the combination of the two be assumed to be without inaccuracies. Failure to adequately document the clinical interventions performed by the clinical team is possibly a major confounder as evidenced by the considerable lack of agreement by our trained abstractors in determining whether advance care planning took place. The generalizability of our results is also a concern because the local population is largely white and highly educated, although our experience tells us that many of our program patients have limited means and thus may more closely resemble the general US population.44 The strength of our study is that it uses real, practice-based data that can be directly translated to practice.
This study focused on a successful high-intensity CTP. Results showed that compared with patients without dementia, patients with dementia were more likely to avoid hospitalizations as a result of enrollment in the investigated CTP. This study, however, failed to identify specific programmatic components critical for the success of the CTP. These findings support the current hypothesis that multidisciplinary, multimodal, and highly intensive interventions are necessary to care for complex and multi-morbid patients. They also suggest that compared with cognitively functional patients, cognitively impaired patients with conservative goals of care may be more likely to avoid burdensome hospitalizations when provided with early intervention in their home.
B.T. conceived and designed the study, interpreted the data, drafted and provided final revisions to the manuscript. P.Y.T, N.D.S., and J.M.N obtained funding, contributed to the conception and design of the study, analysis, and interpretation of the data, and provided critical revisions to the manuscript. P.A.R., R.G.M, and G.J.H., contributed to the conception and design of the study, analysis, and interpretation of the data, and provided critical revisions to the manuscript. S.M.P. Assisted with data acquisition and interpretation, performed the data analysis, and drafted parts of the manuscript. C.Y.Y.C, L.J.H., A.L, A.C., L.B., and R.H. helped with methodologic questions and data interpretation, and provided critical revisions to the manuscript.
All authors read and approved the final manuscript and the decision to submit the manuscript for publication.
We thank Donna Lawson, RN for her help with data abstraction and Annika Beck and Anna Jones in Mayo Clinic Biomedical Ethics Research Program for her help in preparing this manuscript for publication.
The authors declare no conflicts of interest.
This publication was supported by the Mayo Clinic, Robert D and Patricia E. Center for the Science of Health Care Delivery (B.T., R.H., R.G.M, L.J.H), by the Extramural Grant Program by Satellite Healthcare, a not-for-profit renal care provider (L.J.H., B.T.), and by the National Institute of Health (NIH) National Institute Of Diabetes And Digestive And Kidney Diseases grant K23 DK109134 (L.J.H.) K23DK114497 (RGM) and National Institute on Aging grant K23 AG051679 (B.T.). Additional support was provided by the National Center for Advancing Translational Sciences grant UL1 TR000135. Study contents are the sole responsibility of the authors and do not necessarily represent the official views of NIH.
The sponsors had no role in the design, execution, or reporting of this study.
Part of this data was presented in poster format at the American Geriatrics Society meeting in Washington DC 2015.