BACKGROUND/RATIONALE:
Less than 25% of primary care patients achieve optimum benefit from their medications. As experts in drug therapy, clinical pharmacists are positioned to improve the quality of medication use in VHA primary care. Under the Patient Aligned Care Team (PACT) model, however, a single pharmacist is assigned to more than 5,000 patients and cannot possibly review each patient's medication regimen at each visit. Thus, the effort of PACT pharmacists must be targeted to patients most likely to benefit. In response to this need, we developed the Triage Algorithm for PACT Pharmacy Services (TAPPS), a novel health informatics tool that provides PACT pharmacists with concise reports to facilitate triage decision-making.

OBJECTIVE(S):
To test the utility of TAPPS in a controlled setting and to examine the effectiveness of TAPPS in real-world clinical practice using a mixed methods approach.

METHODS:
Aim 1 will test the utility of TAPPS by independently evaluating its 3 key innovations in 3 separate projects. Aim 2 will determine TAPPS effectiveness using a stepped wedge cluster randomized trial design, including 25 PACT pharmacists across 5 medical centers. All pharmacists will begin in the control condition (no TAPPS access) and randomly selected pharmacist groups will be switched to the intervention condition (full TAPPS access) in successive 10-week time blocks. Aim 3 will gather qualitative interviews from PACT pharmacists involved in the trial to assess both positive and negative effects of TAPPS on patient care and identify potential barriers to implementation.

FINDINGS/RESULTS:
Several important findings have emerged from Aim 1 projects.
-We determined that 2 or more hours of pharmacist time is required to replicate the information provided by a typical TAPPS report. Further, that PACT pharmacists currently spend approximately 30-35 minutes gathering data and making triage decisions during a typical clinic day. Together, these findings indicate that pharmacists using TAPPS would gain access to a wider array of clinical data for triage decision-making, and may recover up to 30 minutes per day to redirect toward direct patient care activities.
-We further examined the validity of the TAPPS priority ranking algorithm. On a series of clinic days, patients (N=75) were randomly selected from the lowest, middle, and highest quintile groups based on TAPPS priority scores (TPS) and reviewed by a blinded clinical pharmacist to identify drug-related problems. Patients from the highest TPS quintile had significantly higher drug-related problem scores (13.9) than patients from the middle quintile (9.4) (p=0.001). Thus, targeting patients with higher TPS scores would identify patients with more significant drug-related problems and thus more likely to benefit from pharmacist intervention. We confirmed this finding in a separate replication study involving 60 patients.
-We further contrasted patients identified by high TPS scores with patients referred for clinical pharmacy services by providers (e.g. anticoagulation clinic). Mean drug-related problem scores did not differ between these two patient groups (15.1 vs 14.9, respectively; p=0.88), indicating that patients identified by TAPPS are as appropriate for clinical pharmacy services as patients currently identified by direct provider referral.

IMPACT:
TAPPS has the potential for significant impact on the health of veterans by enabling PACT pharmacists to minimize risk for adverse drug events and seek the full benefit of prescription medications. If proven effective, national implementation of TAPPS could affect all VHA primary care patients, with particular benefits for rural veterans. Our experience with TAPPS also has important implications outside VHA, including how medication therapy management services are delivered to Medicare Part D beneficiaries.

---

External Links for this Project

NIH Reporter

Grant Number: I01HX001544-01A2
Link: https://reporter.nih.gov/project-details/8980947

---

PUBLICATIONS:

None at this time.

DRA: Health Systems
DRE: Treatment - Implementation
Keywords: Care Management Tools, Decision Support, Medication Management
MeSH Terms: none