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Cost-Effectiveness of Pharmacist Postdischarge Follow-Up to Prevent Medication-Related Admissions
Brennan Spiegel, MD, MSHS; Rita Shane, PharmD; Katherine Palmer, PharmD; and Duong Donna Luong, PharmD

Cost-Effectiveness of Pharmacist Postdischarge Follow-Up to Prevent Medication-Related Admissions

Brennan Spiegel, MD, MSHS; Rita Shane, PharmD; Katherine Palmer, PharmD; and Duong Donna Luong, PharmD
A multivariable sensitivity analysis conducted on a pharmacy follow-up program of high-risk patients demonstrated cost savings to hospitals in 98.3% of head-to-head trials across 1000 hypothetical hospitals.
DISCUSSION

This quality improvement study focused on high-risk patients being followed by hospitalist services. Approximately 50% of these patients were determined to be high risk based on our study criteria. During the study period, although predischarge medication reconciliation was documented as part of usual care in an average of 90% of patients, prescriber-related DRPs were identified during the postdischarge calls. The findings of prescriber-related DRPs post discharge are consistent with published observations that documentation of discharge medication reconciliation does not necessarily mean that the process was performed completely and accurately.22-24 Comprehensive predischarge medication reconciliation would ensure timely resolution of DRPs and prevent potentially harmful errors from occurring post discharge.

Extensive research indicates that when pharmacists perform postdischarge medication reconciliation and education, there are fewer readmissions and better outcomes.14,17-19 In addition to these benefits, we also evaluated whether pharmacists could save costs in a real-world application. Using data directly obtained from a quality improvement initiative in a large community-based academic medical center, we found that the pharmacist postdischarge follow-up program was cost-saving, using a population health model in which the organization is responsible for hospitalization and readmissions. Depending on how many people are eligible for the program and the reach of the pharmacy team, hospitals can expect to save between hundreds of thousands to millions of dollars in direct costs per year, according to our ROI lookup table (Table 3). Furthermore, because high-risk patients in the study were older than 65 years and some had conditions for admission that are included in the CMS readmission penalty program (ie, congestive heart failure and pneumonia), this model could help organizations reduce readmission penalties.

The pharmacist program appears cost-effective under a wide range of scenarios; it was not highly sensitive to the precise estimates in the model or to our local base-case results. As long at least 34 patients are served per month, and assuming the pharmacists can contact at least 21% of eligible patients (90% were contacted in our experience), the program is likely to pay for itself. These are low thresholds that should be exceeded in most implementations; we found that 98.3% of hospitals will realize cost savings if the program is equally effective as achieved in our pilot program. The program does not need to be overwhelmingly effective to pay for itself; it must only reduce readmissions by a relative 9%. In pilot testing at CSMC, the program reduced readmissions by 25% relative to usual care (21.5% vs 16.2% absolute readmission rates). Previous research in other hospitals has shown similar results, with effect sizes ranging from a relative 14.2% to 56.2% in published studies.14,23-26

The base-case estimates used in the model were based on our local experience implementing the pharmacy program at CSMC in a quality improvement project focused on high-risk patients who were followed by hospitalist physicians. Other hospitals may bear different costs and realize different benefits. To address this, we tested a wide range of values for both cost and effectiveness in 1-way sensitivity and Monte Carlo analyses. We found that the cost-effectiveness ranking was robust to sensitivity analyses and that the intervention is likely to be cost-saving in just about every hospital that can successfully implement the program, even if it is only modestly effective.

Limitations

This quality improvement project did not demonstrate a statistically significant reduction in readmissions, likely due to the small size of the usual care group that did not receive postdischarge follow up by a pharmacist due to staffing limitations. However, extensive literature already indicates that these programs result in statistically significant reductions in 7-, 14-, and 30-day readmission rates14,19 and in preventable adverse drug events,18 and that they are cost-effective. 20 Here, we focused on direct real-world costs and benefits in an applied implementation of existing science. The assumption is that the hospital is responsible for the cost in this model, which is based on capitated reimbursements. Nonetheless, by conducting a Monte Carlo analysis over 1000 simulated trials using our base-case results as the base-case estimate, we found that the resulting 95% CIs did not cross unity; this is consistent with the existing literature.

In addition, our findings may not be generalizable to all high-risk patients. We studied inpatients receiving more than 10 chronic medications, having a diagnosis of pneumonia or congestive heart failure, and/or receiving anticoagulants. We cannot be sure whether these results are repeatable in other populations, although this cohort includes a prevalent and high-risk group reflective of many inpatient medical services. By using common conditions in the base-case model, we attempted to generate results that are relevant to most settings in which the program might be implemented, with particular focus on the highest-risk individuals.

CONCLUSIONS

This analysis revealed that a pharmacist postdischarge program is likely cost-saving to hospitals in a population health model. Hospitals may use these thresholds and lookup tables to project cost savings and help determine whether to fund and implement similar programs.

Acknowledgments

The authors would like to thank and acknowledge Lydia Noh, PharmD, for her support and contributions to this project.

Author Affiliations: Department of Medicine, Division of Health Services Research (BS), and Department of Pharmacy Services (RS, DDL, KP), Cedars-Sinai Health System, Los Angeles, CA; Department of Health Policy and Management, UCLA Fielding School of Public Health (BS), Los Angeles, CA; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE) (BS), Los Angeles, CA.

Source of Funding: None.

Author Disclosures: The 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 (RS, KP, DDL); acquisition of data (RS, KP, DDL); analysis and interpretation of data (RS, KP, DDL); drafting of the manuscript (BS, RS, KP, DDL); critical revision of the manuscript for important intellectual content (BS, RS); administrative, technical, or logistic support (RS, KP, DDL); and supervision (BS, RS, KP, DDL).

Send Correspondence to: Brennan Spiegel, MD, MSHS, Cedars-Sinai Health System, Cedars-Sinai Health System Pacific Theaters Building, 116 North Robertson Blvd, 4th Fl, Los Angeles, CA 90048. Email: Brennan.Spiegel@cshs.org.
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