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The American Journal of Managed Care February 2015
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A Multidisciplinary Intervention for Reducing Readmissions Among Older Adults in a Patient-Centered Medical Home
Paul M. Stranges, PharmD; Vincent D. Marshall, MS; Paul C. Walker, PharmD; Karen E. Hall, MD, PhD; Diane K. Griffith, LMSW, ACSW; and Tami Remington, PharmD
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Amresh D. Hanchate, PhD; Arlene S. Ash, PhD; Ann Borzecki, MD, MPH; Hassen Abdulkerim, MS; Kelly L. Stolzmann, MS; Amy K. Rosen, PhD; Aaron S. Fink, MD; Mary Jo V. Pugh, PhD; Priti Shokeen, MS; and Michael Shwartz, PhD
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Julie Zissimopoulos, PhD; Geoffrey F. Joyce, PhD; Lauren M. Scarpati, MA; and Dana P. Goldman, PhD
Health Literacy and Cardiovascular Disease Risk Factors Among the Elderly: A Study From a Patient-Centered Medical Home
Anil Aranha, PhD; Pragnesh Patel, MD; Sidakpal Panaich, MD; and Lavoisier Cardozo, MD
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A Multidisciplinary Intervention for Reducing Readmissions Among Older Adults in a Patient-Centered Medical Home

Paul M. Stranges, PharmD; Vincent D. Marshall, MS; Paul C. Walker, PharmD; Karen E. Hall, MD, PhD; Diane K. Griffith, LMSW, ACSW; and Tami Remington, PharmD
A collaborative practice model to reduce hospital readmissions from an outpatient environment.
ABSTRACT
Objectives

To evaluate the effectiveness of a multidisciplinary practice model consisting of medical providers, clinical pharmacists, and social workers on reducing 30-day all-cause readmissions.

Study Design
Retrospective cohort study.

Methods
This study included adults 60 years or older discharged from a large academic medical center. Patients were grouped as either receiving the primary care-based transitional care program (intervention group) or usual care (control group) after an index hospitalization. Only 1 index hospitalization was included per patient. All-cause 30-day readmission rates between propensity score matched study groups were analyzed by intention-to-treat, per protocol, and as-treated methods. Secondary outcomes included time to readmission, subgroup analysis, process measures, and cost avoidance influence of covariates on chance of readmission measured by logistic regression.

Results
Over 27 months, 19,169 unique patients had 18,668 index hospitalizations and 572 interventions scheduled after discharge. Among matched subjects, 30-day readmission rates were not significantly different between those scheduled for the intervention and those never scheduled (21% vs 17.3%, respectively; P = .133). However, when those completing the intervention (n = 217) were examined, readmission rates were significantly reduced (11.7% vs 17.3%, respectively; P <.001). Likewise, time to readmission was significantly longer among those receiving the intervention (18 ± 9 days compared with 12 ± 9 days with usual care; P = .015) and potential cost avoidance was observed only when the intervention was completed.

Conclusions
A community-based multidisciplinary transitional care program may reduce hospital readmissions among older adults.

Am J Manag Care. 2015;21(2):106-113
A patient-centered medical home (PCMH)-based post hospital discharge intervention with a clinical pharmacist, social worker, and primary care provider may reduce readmission rates among older patients when performed soon after discharge.
  • Older adults are at high risk for hospital readmission.
  • A PCMH-based intervention allows collaboration between the outpatient team and promotes responsive care to the patients’ evolving needs.
  • A multidisciplinary intervention may identify more threats to recovery among a high-risk older population than any single discipline alone.
  • PCMHs and other coordinated care models offer opportunities to implement effective transitions of care interventions.
Older adults are an exceptionally vulnerable population during transitions of care. Nearly one-fifth of hospitalized Medicare beneficiaries are rehospitalized within 30 days, with fewer than half having a physician visit between the time of discharge and rehospitalization.1 These rehospitalizations have been estimated to account for roughly $44 billion per year in hospital costs2—three-fourths of which are viewed as potentially avoidable.3

In 2 recent reviews of published research on transitions-of-care activities,4,5 no universal intervention was found to be effective at reducing 30-day readmission rates in either older or younger adults. However, shared characteristics of many successful interventions include activities taking place before, during, and after discharge provided by multiple members of the allied health professional team.4,5 Care coordination in older adults is especially challenging due to complex medical and social needs.6 Many transitions of care interventions have provided reduced readmissions in this high-risk population.7-14 Koehler found that the most successful of these interventions in older adults are ones that continue in the outpatient setting.15 Despite cost and quality concerns with poor transitions of care, however, traditional reimbursement models have disincentivized institutions from implementing high-quality care coordination efforts until recent federal healthcare reform.16

With value-based hospital payment penalties now in place for excessive 30-day readmission rates, and a call for improved care coordination by the Affordable Care Act, improved models of care are necessary.17,18 Patient-centered medical homes (PCMHs) are designed to achieve the triple aim of higher quality, improved satisfaction, and lower costs through patient-centered, coordinated primary care. The PCMH structure is well suited to implement care coordination activities for patients in the outpatient setting. While evidence for PCMHs accomplishing the triple aim is mostly favorable, some studies have found increased costs, and the volume of high-quality evidence is limited.19-21 Comparison among high-quality evaluations is difficult due to the varying design of programs, incorporation of PCMH components, and different target populations. Additional evaluations of PCMH interventions have been called for.19,20 The purpose of this retrospective cohort study was to describe the characteristics and feasibility of implementing a multidisciplinary PCMH-based post discharge intervention, and to determine the effect of the intervention on the rate of all-cause 30-day readmissions.

METHODS

Study Setting

This study was conducted within the academic health system, whose physician group practices began participating in a Medicare prototype accountable care organization demonstration project in 2005.22 The Transitional Care Program (TCP) is one of numerous programs created to improve care and contain costs. The study protocol was reviewed and approved by the health system institutional review board.

Transitional Care Program

The TCP is operated from a geriatrics clinic as part of a large academic health system. The geriatrics center is a community-based PCMH providing comprehensive, multidisciplinary primary and specialty care for patients 60 years or older. Although completely conducted in the community setting, the TCP is considered complementary to inpatient care coordination activities. All hospitalized patients receive comprehensive discharge planning, medication reconciliation, and high-risk medication education. The TCP is scheduled for patients upon recommendation from consulted inpatient geriatrician services or for those receiving primary care at the geriatrics center. Appointments are ideally scheduled within 1 week after discharge, coordinated with assistance from discharge planners, and included in discharge paperwork.

The TCP team consists of medical providers (board-certified geriatric medicine physicians and nurse practitioners), clinical pharmacists, and social workers; the program was developed to assist patients transitioning to the community after unscheduled hospitalizations, long-term-care facility stays, or emergency department (ED) visits. The primary goal is to prevent rehospitalization. TCP aims to do so by addressing the multidimensional needs of this complex population (medical, social, psychological, functional domains) and ensure that treatment plans are personalized and implemented optimally using a team-based approach.

The TCP begins with a pharmacist’s phone call. This telephonic encounter is scheduled to occur 2 to 4 days after discharge, and serves 3 purposes: to provide a preliminary medical assessment, reconcile medications, and perform a comprehensive medication review. Medication obtainment, adherence, efficacy, tolerability, safety, monitoring, and cost are all assessed. The pharmacist also assesses patient symptoms, stability, and self-monitoring at home, as appropriate. Issues requiring immediate attention are addressed, and findings, recommendations, and the up-to-date medication list are provided to the team prior to the clinic visit via electronic medical record documentation.

The patient is then seen in clinic, ideally within 1 week of discharge, by a social worker and medical provider. Social workers assess the patient’s living situation, transportation, medication obtainment, activities of daily living, mental health and/or substance abuse, and in-home assistance with caregivers. Interventions include assisting with accessing community resources, long-term-care planning, and the establishment of advanced directives. The social worker reviews the use of available urgent appointments and the clinic after-hours on-call service to avoid sudden ED visits; home visits and intensive follow-up for up to 3 months are provided as needed.

The medical provider visit is the final component of the TCP. The medical provider performs a modified geriatrics assessment with focus on the reason for hospital admission, and in collaboration with the social worker, assesses the patient’s living situation, rehabilitation plan, caregiver network, and social support; patients’ self-care abilities and nutritional status are also assessed. Providers then review the goals of care with the patient, family, and caregivers. Lastly, follow-up appointments and referrals are coordinated. if patients receive primary care at the geriatrics center, primary care provider continuity is prioritized when scheduling appointments.

Study Population

All patients 60 years and older discharged from the health system’s primary hospital to home or assisted living from November 1, 2009, to January 31, 2012, were eligible for inclusion. This study window corresponds to a time frame in which the TCP was unchanged. To reduce bias, index hospitalizations were defined as the first hospitalization meeting inclusion criteria per patient. Patients were placed in cohorts as determined by TCP visit status within 30 days of discharge from index hospitalization, and analyzed using 3 different methods. First, all patients scheduled for the TCP, whether completed or not, were compared with those not scheduled (intention-to-treat). Second, only those completing the intervention were compared with those not scheduled (per protocol). Third, all patients completing the TCP were compared with those who did not receive the TCP either by not being scheduled or never completing a scheduled TCP (as-treated).

Data Collection

Data related to patient demographics (age, sex, and race), index admission (admission and discharge diagnoses, length of stay, and medication count at discharge), and descriptions of medical comorbidities were collected. Comorbidities were identified by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code and categorized according to the High-Risk Diagnoses in the Elderly Scale (HRDES) and the Charlson/Deyo Comorbidity Index (not adjusted for age), which have been associated with risk of hospitalization, morbidity, and mortality.23-26 Race was collected as 8 distinct categories; however, due to a large proportion reporting as Caucasian and small numbers in the remaining categories, the variables were collapsed into 2 categories: Caucasian and non-Caucasian. Date and status (completed or cancelled) of TCP components (pharmacist, social worker, and medical provider) were also collected. Identification of variables, outcomes, and TCP appointment status was completed using the health system’s clinical data repository and systemwide scheduling system.

Outcome Measures

The primary outcome measure was nonelective all-cause 30-day readmissions. Thirty-day readmissions were defined as a hospital admission occurring within 30 days of the index hospitalization discharge date; readmission rates were calculated as the percentage of discharges with a 30-day readmission. Admissions were excluded as outcomes if the admit diagnosis was for a planned procedure and/or aftercare (based on ICD-9-CM codes V50-59.xx).27 Secondary outcomes were readmission rate by subgroup, time-to-event analysis, time to receive TCP components, and cost avoidance. All outcomes were evaluated first in intention-to-treat groups. Cost avoidance was calculated by multiplying a predicted difference in readmissions among patients receiving the TCP by the average cost of hospital stays for Medicare beneficiaries in 2009, adjusted to 2012 US dollars.28,29

Statistical Analysis

Data were analyzed using descriptive statistics, univariate, and multivariate analyses. Logistic regression was used to test the effect of the intervention on 30-day readmissions and was adjusted for possible confounders using the enter method. Model goodness of fit was verified with the Hosmer-Lemeshow test and residual value analyses. Propensity score (PS) matching by logistic regression and Mahalanobis distance was used to match intervention to control subjects in a 1:1 ratio30; matching criteria included age, sex, race, length of stay, number of medications at discharge, and comorbidity index scores. Time-to-readmission analysis was performed using Kaplan-Meier and log rank tests, censored at 30 days. A total of 880 subjects were needed to provide 90% power to detect an 8% difference in readmission rates between groups with an a priori 2-sided alpha of 0.05.31 Data analysis was performed using SPSS version 20.1 (IBM Corp, Armonk, New York), SAS version 9.3 (SAS Institute Inc, Cary, North Carolina), and R version 2.15.2 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

 
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