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The American Journal of Managed Care March 2014
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Collaborative DTM Reduces Hospitalization and Healthcare Costs in Patients With Diabetes Treated With Polypharmacy
Lauren Brophy, PharmD, FAHM; Amanda Williams, PharmD; Eric J. Berman, DO, MS; David Keleti, PhD; Karen E. Michael, RN, MSN, MBA; Margaret Shepherd, RPh, FAHM; Scott A. Fox, MS, MEd; Christine Jacobs, MA; Susan Tan-Torres, MD, MPH; Andrea D. Gelzer, MD; and Mesfin Tegenu, MS, RPh
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Walid F. Gellad, MD, MPH; Phillip Choi, BS; Margaret Mizah, PharmD; Chester B. Good, MD, MPH; and Aaron S. Kesselheim, MD, JD, MPH

Collaborative DTM Reduces Hospitalization and Healthcare Costs in Patients With Diabetes Treated With Polypharmacy

Lauren Brophy, PharmD, FAHM; Amanda Williams, PharmD; Eric J. Berman, DO, MS; David Keleti, PhD; Karen E. Michael, RN, MSN, MBA; Margaret Shepherd, RPh, FAHM; Scott A. Fox, MS, MEd; Christine Jacobs, MA; Susan Tan-Torres, MD, MPH; Andrea D. Gelzer, MD; and Mesfin Tegenu, MS, RPh
Drug therapy management implementation in 2 health plans resulted in significant cost savings and modest to significant reductions in emergency department visits and inpatient admissions among patients with diabetes.
Objectives: To evaluate the effects of a collaborative pharmacy benefits manager (PBM)/ health plan–administered drug therapy management (DTM) program on healthcare utilization and costs in patients with diabetes treated with polypharmacy.

Study Design: Retrospective quasi-experimental design with comparison group.

Methods: This DTM program was a collaborative effort between the PBM, PerformRx, and the care management departments of Keystone First (KF) and AmeriHealth Caritas Pennsylvania (ACP) care management departments, targeting patients with diabetes using >15 medications. Pharmacists reviewed member profiles and made evidencebased prescriber and patient interventions, working directly with prescribers and indirectly with members, via care managers. Care managers provided additional services not otherwise within the scope of DTM. The study group consisted of 954 DTM participants reviewed by a pharmacist between November 1, 2010, and July 31, 2011. The control group consisted of 810 matched DTM participants not reviewed by a pharmacist.

Results: Intervention acceptance rates for KF and ACP were 33% and 26%, respectively. The study group demonstrated lower inpatient admissions and emergency department utilization rates, although only the KF study group inpatient admission rate achieved statistical significance (76.4%; P = .0002). The study groups realized statistically significant total cost savings (pharmacy + medical) compared with their corresponding control groups (47.8% KF, P = .0039; 50.7% ACP, P = .0497) despite non-statistically significant increases in pharmacy costs.

Conclusions: A collaborative pharmacist-driven DTM program with a care manager–executed patient outreach component results in reduced hospital utilization and significant healthcare cost savings.

Am J Manag Care. 2014;20(3):e72-e81
A collaborative drug therapy management (DTM) program with modest acceptance rates effectively reduces inpatient admissions and generates significant cost savings.
  • Overall acceptance rates for pharmacist-recommended DTM interventions are likely to range from 26% to 33%.
  • Hospital utilization can be substantially reduced in a successful DTM program.
  • Pharmacy-related costs would be expected to increase with the implementation of a successful DTM program but are outweighed by medical cost savings.
According to the American Pharmacists Association, drug therapy management (DTM) is a service that optimizes therapeutic outcomes by way of pharmaceutical interventions intended to (1) elicit changes in drug regimens; (2) reduce the incidence of adverse drug events; and (3) improve adherence. Formerly an underutilized component of the healthcare team approach to treating patients, implementation of DTM services has been facilitated by a payment framework created by the Medicare Prescription Drug, Improvement, and Modernization Act of 2003.

DTM is frequently a stand-alone service consistent with a traditional, siloed approach to healthcare. Although an integrated approach to healthcare is preferred, DTM as a component of a segmented healthcare system has demonstrated impressive quality improvements and cost savings. The Minnesota Medicaid Medication Therapy Management program realized healthcare cost savings of $3768 per patient per year between 2006 and 2007.1 The North Carolina ChecKmeds medication therapy management program for more than 15,000 Part D seniors saved an estimated $13.2 million in healthcare costs in 2010.2 The Iowa Medicaid Pharmaceutical Case Management program demonstrated a significantly improved mean Medication Appropriateness Index score among participants compared with baseline (P <.001) over a 9-month period between 2000 and 2001.3 Managed care organizations (MCOs), occasionally employing pharmacy benefits managers (PBMs),4 have also increasingly incorporated DTM services into benefit offerings, demonstrating positive outcomes.5,6 While DTM service providers are primarily pharmacists, a pharmacist is not a prerequisite for a DTM program. In fact, in 10% of 2012 Medicare Part D programs, a case manager provided DTM-type services.4

Not all patients, however, benefit from DTM services, and intervention should focus on those at highest risk. Comorbidities such as cardiovascular disease, hypertension, and nephropathy7 frequently accompany a diagnosis of diabetes, and patients with multiple comorbidities are often managed with polypharmacy. Polypharmacy increases the risk of medication-related problems (MRPs), reducing population health and driving up health care costs, a problem complicated by the prescription of more medications than clinically warranted. Polypharmacy also promotes suboptimal adherence,8 resulting in underutilization of preventative, lower-cost primary care services and overutilization of higher-cost emergency department (ED) services.9,10 Thus, despite lower medication-related costs from low adherence and reduced pharmacy utilization, costs are transferred to the medical sphere via less effective emergency care, thereby increasing overall healthcare costs.

DTM is a valuable service proven to improve healthcare quality and reduce costs. Various DTM delivery models exist. A literature search revealed a lack of DTM programs that incorporate a care manager in addition to a pharmacist (see Table S1 in Appendix). The value of DTM services may be enhanced with an integrated approach that includes a care manager. This study was designed to evaluate the effects of a PBM/health plan–administered, collaborative DTM program that incorporates both a pharmacist and a care manager targeted to high-risk patients with diabetes treated with polypharmacy. We were primarily interested in determining whether the DTM program would reduce medical utilization and total costs (pharmacy + medical). We hypothesized that DTM intervention would reduce medical utilization, as measured by ED visits and inpatient admissions, and generate total cost savings, despite a predicted increase in pharmacy costs.


Population and Study Design

PerformRx, the fully owned PBM of AmeriHealth Caritas Family of Companies (ACFC), serves just under 3 million health plan members. Partnering Medicaid MCOs and fully owned ACFC subsidiaries Keystone First (KF) and Ameri- Health Caritas Pennsylvania (ACP) serve about 290,000 and just over 126,000 members, respectively, as of January 2014. These 3 entities jointly developed a collaborative, Utilization Review Accreditation Commission–accredited DTM program to improve member care. PerformRx was responsible for the pharmacy-based management component of the DTM program. KF and ACP supplied the DTM program participants and executed the care management (CM) component.

This retrospective study was designed as a quasi-experiment with comparison group. The targeted participants were patients with diabetes (International Classification of Diseases, Ninth Revision, codes for diabetes [250.xx] or 1 diabetes medication within the previous year) being treated with polypharmacy (unique generic code number count of >15). This patient population was selected because the likelihood of comorbidities with diabetes and polypharmacotherapy put these patients at high risk for MRPs and nonadherence.9

The study population analyzed consisted of 954 DTM participants (n = 690 KF, n = 264 ACP) reviewed by a pharmacist for DTM services. The matched control group consisted of 810 DTM participants (n = 600 KF, n = 210 ACP) not reviewed by a pharmacist for DTM services, but who may have received autonomous CM services. The baseline period (November 1, 2009-October 31, 2010) was followed by a 1-year measurement period (November 1, 2010-October 31, 2011). Members enrolled in the plan for less than 6 months during baseline or measurement periods were excluded. Additionally, members reviewed by a pharmacist in the final 3 months of the measurement period (August 1, 2011-October 31, 2011) were excluded because recommendations made during that time would not have had the standard 3-month time frame allowed for follow-up and outcome determination. Analysis was performed 6 months postmeasurement, allowing sufficient lag time to receive medical claims.

Relative risk scores quantify financial implications of morbidity based on prior healthcare utilization.11 Prospective risk scores were assigned to participants based on previous claims, gender, and age, and used to randomly select a comparison group with a comparable risk score. Since risk scores are continuous variables, 1:1 matching of study-to-control group risk scores was impossible. Therefore, we applied stratified random sampling of risk scoring from the 10th percentiles of the study group as strata. Cutoff points for these 10th percentiles were applied to the control groups to create 10 strata. An equal number of cases from each of the 10 strata was randomly selected, generating a comparable distribution of risk scores in control and study groups. The comparability of these groups was validated with an independent, 2-sample t test.

Implementation Process

The DTM process flow is displayed in Figure S1 (available in Appendix). DTM pharmacists reviewed adherence, gaps in care (GICs), and First DataBank (FDB) clinical decision-support modules, and prepared prescriber and member interventions. Adherence was assessed for both short-term (eg, member overdue refilling medication) and long-term (eg, member frequently misses doses over an extended time frame) issues. Interventions to improve adherence included recommendations to simplify regimens and reduce side effects and drug interactions.12 GICs are proprietary algorithms that identify when members have not met standard-of-care guidelines (eg, diabetic not self-monitoring blood glucose [SMBG]). FDB modules identify safety concerns such as drug interactions, duplicate therapies, and improper dosing.

Pharmacists provided evidence-based recommendations directly to prescribers and indirectly to members via care managers, referring to a list of medications considered "urgent," jointly compiled by PerformRx and KF/ACP. Urgent interventions directed to prescribers received a phone call in addition to the standard letter/fax, and those directed to members received expedited care manger outreach within 1 day compared with the standard 20 days. KF and ACP employ the same style of CM—a blended model of CM and disease management managed by a single care manager. Care managers provided additional services not otherwise within the scope of DTM, such as health coaching, education, transportation assistance, and prescription refill/transfer/authorization assistance. Members actively engaged in CM were counseled by their respective care managers, thereby leveraging existing care manager–member relationships and streamlining contact efforts. Members not actively engaged in CM were counseled by an urgent response care manager, thereby expanding available resources to include CM services. DTM pharmacists were available to assist care managers with counseling.

After 20 days from the date a member intervention was identified, and 90 days from the date a prescriber intervention was identified, the pharmacist and technician, respectively, followed up to determine the outcome of the outreach. Pharmacists reviewed care manager outreach notes and technicians reviewed claims data to determine outcomes. Outcomes were flagged as Accepted, Not Accepted, Rejected, Unknown, or Not Applicable. In the event a recommendation to add or change therapy was accepted, the pharmacist conducted an additional review for medication appropriateness and adherence and tasked a member outreach to the care manager to assess efficacy and side effects.

Statistical Analysis

Dependent variables examined to demonstrate the effectiveness of the DTM program included number of ED visits and inpatient admissions per 1000 members, as well as per member per month (PMPM) pharmacy, medical, and total costs. These variables were populated with the health plans’ claims data. The independent variable analyzed was percent participation in the DTM program.

Because variations in risk can be important cost and utilization confounders, Diagnostic Cost Group (DxCG, Boston, Massachusetts) models were applied using risk adjustment methodology to establish an empirically valid measure of expected resource use. Mean risk scores for KF study and matched control groups were 695 and 702, respectively. Mean risk scores for ACP study and matched control groups were 660 and 643, respectively (Table 1).

For each member, the dependent variables during baseline and measurement periods were summed separately and divided by the number of member months in the corresponding time period. Healthcare utilization and costs for study and control populations comparing baseline and measurement time periods were evaluated using the nonparametric Wilcoxon signed-rank test, selected because the data were matched pairs and the variables were not normally distributed.

Difference-in-differences (DID) analyses were used to compare program effects on utilization and costs study and control groups. Statistical significance was set at α = .05. Data manipulation and analysis were performed using SAS EG 5.1 (SAS Institute, Cary, North Carolina).


Study Cohorts

The percentages of KF and ACP study group members that received pharmacist intervention were 92.3% and 95%, respectively. Pharmacists reviewed without intervening on a subset of study group subjects who had no MRPs. The control group did not receive pharmacist review. Study, control, and total plan population demographic data are displayed in Table 1. The total number of diabetic members in KF and ACP were 11,372 and 3655, respectively.

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