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The American Journal of Managed Care March 2017
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Impact of a Pharmacy-Based Transitional Care Program on Hospital Readmissions
Weiyi Ni, PhD; Danielle Colayco, PharmD, MS; Jonathan Hashimoto, PharmD; Kevin Komoto, PharmD, MBA; Chandrakala Gowda, MD, MBA; Bruce Wearda, RPh; and Jeffrey McCombs, PhD
Private Sector Accountable Care Organization Development: A Qualitative Study
Ann Scheck McAlearney, ScD; Brian Hilligoss, PhD; and Paula H. Song, PhD
Scaling Lean in Primary Care: Impacts on System Performance
Dorothy Y. Hung, PhD; Michael I. Harrison, PhD; Meghan C. Martinez, MPH; and Harold S. Luft, PhD
Patient Experience Midway Through a Large Primary Care Practice Transformation Initiative
Kaylyn E. Swankoski, MA; Deborah N. Peikes, PhD, MPA; Stacy B. Dale, MPA; Nancy A. Clusen, MS; Nikkilyn Morrison, MPPA; John J. Holland, BS; Timothy J. Day, MSPH; and Randall S. Brown, PhD
A Better Way: Leveraging a Proven and Utilized System for Improving Current Medication Reconciliation Processes
Ajit A. Dhavle, PharmD, MBA; Seth Joseph, MBA; Yuze Yang, PharmD; Chris DiBlasi, MBA; and Ken Whittemore, RPh, MBA
Effects of an Enhanced Primary Care Program on Diabetes Outcomes
Sarah L. Goff, MD; Lorna Murphy, MA, MPH; Alexander B. Knee, MS; Haley Guhn-Knight, BA; Audrey Guhn, MD; and Peter K. Lindenauer, MD, MSc
Consumer-Directed Health Plans: Do Doctors and Nurses Buy In?
Lucinda B. Leung, MD, MPH, and José J. Escarce, MD, PhD
Improvements in Access and Care Through the Affordable Care Act
Julie A. Schmittdiel, PhD; Jennifer C. Barrow, MSPH; Deanne Wiley, BA; Lin Ma, MS; Danny Sam, MD; Christopher V. Chau, MPH; Susan M. Shetterly, MS
Does Paid Versus Unpaid Supplementary Caregiving Matter in Preventable Readmissions?
Hsueh-Fen Chen, PhD; Taiye Oluyomi Popoola, MBBS, MPH; and Sumihiro Suzuki, PhD

Impact of a Pharmacy-Based Transitional Care Program on Hospital Readmissions

Weiyi Ni, PhD; Danielle Colayco, PharmD, MS; Jonathan Hashimoto, PharmD; Kevin Komoto, PharmD, MBA; Chandrakala Gowda, MD, MBA; Bruce Wearda, RPh; and Jeffrey McCombs, PhD
Patients receiving postdischarge care from pharmacists had a 28% lower risk of readmission at 30 days and a 31.9% lower risk at 180 days compared with usual care.
After controlling for confounders, the multivariate logistic regression analysis on 30-day readmissions showed that the SPS TOC intervention was associated with a statistically significant 28% reduction in 30-day readmissions (odds ratio [OR], 0.720; 95% confidence interval [CI], 0.526-0.985) (Table 2). Other factors associated with an increased risk of 30-day readmissions were prior inpatient stays (OR, 1.930; 95% CI, 1.255-2.969) and longer LOS (OR, 1.054; 95% CI, 1.018-1.091). Patients who were hospitalized for AMI, COPD, digestive diseases, infectious and parasitic diseases, and neoplasms had a higher likelihood of 30-day readmissions. In addition, patients with prescription claims for antiepileptic drugs, dialysis solutions, and dietary supplements (including intravenous nutrition) also had higher 30-day readmission rates. 

The 180-day analysis indicated that the TOC intervention reduced readmissions at 6 months by 31.9% (OR, 0.681; 95% CI, 0.507-0.914) (Table 3). Patients with a prior hospitalization, COPD, and infectious and parasitic diseases were more likely to be readmitted within 180 days. Patients hospitalized for blood disorders and diabetes were more likely to be readmitted within 180 days, but not within 30 days. Use of dialysis solutions and dietary supplements, including intravenous nutrition, was associated with higher risk for 180-day readmissions, consistent with the 30-day outcomes.

The sensitivity analyses demonstrated that the SPS TOC service was associated with a reduction in the number of hospitalizations. The TOC program reduced the number of readmissions by 6 per 100 patients within 30 days and 19 per 100 patients within 180 days compared with patients receiving usual care (eAppendix Table A [eAppendices available at www.ajmc.com]). 

Time to readmission was analyzed by the Cox proportional hazards model on the 30-day ITT population. After adjusting for all demographics and clinical characteristics, the model illustrated that patients receiving TOC services had a 25% lower hazard of readmission compared with patients receiving usual care (hazard ratio, 0.749; 95% CI, 0.566-0.992) (Table 4). 

DISCUSSION

This study estimated the impact of a community pharmacist-based TOC initiative on 30-day and 180-day readmission rates in a managed Medicaid population. Both the logistic regression and Cox proportional hazard models found that the TOC services at SPS were associated with significantly lower all-cause readmissions at 30 days and 180 days compared with usual discharge care. Accordingly, this study adds to the body of literature on the effects of TOC and the role of the pharmacist in TOC. Whereas previous studies have largely focused on TOC services within academic centers or closed systems, such as the Veterans’ Health Administration, this study evaluates the impact of a stand-alone ambulatory care pharmacy-based TOC service. In addition, prior research on the impact of the pharmacist has focused on medication reconciliation prior to discharge. The SPS TOC program has demonstrated that medication-related problems often persist after discharge, which requires further interventions by pharmacists for the 30-day period after discharge. More details on these interventions will be described in future publications. 

This study also adds to the body of literature on the impact of pharmacist-based TOC services. Many TOC interventions have shown the benefits of close postdischarge care coordination on readmission rates and healthcare utilization.8,12-24 However, these studies either focused only on specific disease conditions or only evaluated the effects over a short period of time. O’Dell et al reported that clinical pharmacist services for cardiac patients with unstable angina were associated with lower readmission rates compared with usual care. However, the results were not significant in the larger pool of all cardiac patients.23 Koehler et al designed a randomized clinical trial and showed that pharmacist-led interventions reduced 30-day readmissions but did not affect 60-day readmissions.24 Kirkman et al also found that telephonic follow-up by pharmacists reduced 30-day readmissions; their regression analysis demonstrated that the 30-day readmission OR for patients who received usual care was 1.53.15 When the reference category was reversed, the OR was comparable to our result of 0.72. To our knowledge, our 180-day analysis exceeds the follow-up period of existing studies. 

All patients referred to the TOC services (the ITT population)—including those who did not qualify for services (6.7%), patients who could not be contacted (4.7%), and patients who declined services (2.4%)—were analyzed in this study. Thus, the results estimate the effects of TOC services on the entire referred population. The corresponding percentages in the 180-day population were 3.4%, 2.2% and 5%, respectively. There were many possible reasons for patients refusing services or being unreachable by phone, including the “cold call” nature of the phone call from SPS, the perception that the TOC services were unnecessary, disconnected phone numbers, homelessness, or refusal to discuss their healthcare with a professional other than their own physician. Despite the inclusion of all of these patients in the analysis, the results demonstrated a significant reduction in readmissions associated with the intervention—an effect that may have been even larger had we excluded them from the analysis. 

In addition to evaluating the impact of the SPS TOC program on readmission rates, this study explored the potential factors associated with higher readmission rates. In both the 30-day and 180-day analyses, prior hospitalizations within 6 months, COPD and infectious and parasitic diseases were significantly associated with increased risk of readmission. Similarly, using medications for electrolyte imbalance and dietary supplementation was shown to be related to higher readmission rates. It is possible that use of these prescriptions may be indicators for chronic illnesses, such as renal failure and/or gastrointestinal disorders. Although the current results described many factors that could potentially affect readmissions, future stand-alone studies focusing on causal relationships with readmissions would be warranted. Once those factors are successfully identified, future TOC services may be designed to target the appropriate patient groups for whom they would be most effective. 

Limitations

Our study was limited by several factors. First, the study used a nonrandomized design, selecting patients discharged from intervention and control hospitals. Although we matched the intervention and control populations using the number of prior hospitalizations and the LOS of the index hospitalization, the healthcare utilization in the intervention group was still higher than that of the control group, possibly indicating that the intervention group’s health status was worse than that of the control group (Table 1). After controlling for these imbalances between the groups in the multivariate regression models, the intervention was still shown to have a significant impact on readmission rates. Second, the generalizability of our results may be limited because this study focused on the rural population of Bakersfield, California. Finally, an observational study cannot establish the causality of factors affecting the risk of readmission investigated in the current study. Future studies would be necessary to answer this research question. 

CONCLUSIONS

Compared with usual discharge care, the ambulatory care pharmacy-based TOC program significantly reduced readmission rates by 28% at 30 days and 31.9% at 180 days. These are likely conservative estimates of the treatment effect, as all referred patients were included in the intent-to-treat analysis.

Acknowledgments

The authors would like to thank the staff at SPS, including Cristina Aldaco, Lirio Medina, Stephanie Pimentel, Paula Reyes, Dr Brian Komoto, PharmD, CEO at SPS, and Dr Carolyn Dam, PharmD, former clinical pharmacist at SPS. In addition, the authors thank their colleagues at Kern Health Systems (KHS), including Jeff Pollock, Utilization Management Program manager; Pavan Tirumalasetty, data analyst; Deborah Murr, RN, administrative director of Health Services; Douglas Hayward, chief executive officer; and Dr John Fisher, MD, MBA, former chief medical officer at KHS.

Author Affiliations: Department of Pharmaceutical and Health Economics, School of Pharmacy, University of Southern California (WN, JM), Los Angeles, CA; Synergy Pharmacy Solutions (DC, JH, KK), Bakersfield, CA; Kern Health Systems (CG, BW), Bakersfield, CA.

Source of Funding: Komoto Family Foundation Fellowship.

Author Disclosures: Drs Colayco, Hashimoto, and Komoto are employed by Synergy Pharmacy Solutions, which provides the Transition of Care program described in this paper. Dr Komoto also owns stock in Synergy Pharmacy Solutions. Dr McCombs is a board member of the Komoto Family Foundation and supervises the Komoto Fellowship. 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 (WN, DC, BW, JM); acquisition of data (WN, DC); analysis and interpretation of data (WN, DC, CG, BW, JM); drafting of the manuscript (WN, DC, JH, KK, CG, JM); critical revision of the manuscript for important intellectual content (WN, DC, JH, KK, CG, BW, JM); statistical analysis (WN, DC, JM); provision of patients or study materials (DC, JH, KK); obtaining funding (DC, JM); administrative, technical, or logistic support (DC, BW); and supervision (DC, JM).

Address Correspondence to: Weiyi Ni, PhD, University of Southern California, 635 Downey Way, VPD Ste 210, Los Angeles, CA 90089-3333. E-mail: weiyini@usc.edu. 
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