BACKGROUND/RATIONALE:
Roughly 1.5 million preventable adverse drug events occur in the US annually at a cost in excess of $4 billion. Many of these events result from inappropriate prescribing and efforts to improve prescribing practices would have a major impact on outcomes. This is particularly true for the many older adult veterans who suffer from multiple comorbid conditions and require complex medication regimens. The ability to improve prescribing depends on valid methods for measuring medication appropriateness.

OBJECTIVE(S):
The goal of this CDA-2 award was to build the applicant's methodological skills in several key areas related to the development of prescribing quality indicators. A series of incremental studies was conducted to examine the frequency and validity of these measures, and used to develop an investigator-initiated grant to determine the utility of an automated triage algorithm for targeting clinical pharmacy services.

METHODS:
The career development goals of this CDA were to develop expertise in the following areas: 1) theoretical frameworks and practical approaches to health care quality measurement; 2) advanced biostatistics and multivariable risk adjustment methods; 3) instrumental variable methods for addressing selection bias in observational studies; 4) grantsmanship and scientific writing; and 5) intervention research design and implementation.

Research Aim 1 used national VA data from 2003 to 2012 to determine the prevalence and incidence of a selected panel of prescribing quality indicators, including drugs to avoid, drug-drug interactions, therapeutic duplication, and noncompliance. Aim 2 identified sources of variation in prescribing quality indicator violations, with variables selected according to a conceptual framework based on the Donabedian quality model of structure, process and outcome. Aim 3 compared the performance of prevalence and incidence-based prescribing quality indicators in predicting adverse outcomes, adjusting for patient complexity using traditional multivariable regression and propensity scores approaches. Aim 4 determined the impact of selection bias on the relationship between prescribing quality indicators and adverse health outcomes using instrumental variable methods.

FINDINGS/RESULTS:
Not yet available.

IMPACT:
We anticipate the results of this study will have three specific impacts. First, our findings provide a detailed characterization of prescribing quality in VA across multiple clinical domains, over time, and between regions and facilities. Second, we have established a methodological framework for examining the validity of prescribing quality in VA, with a particular emphasis on incident prescribing events, as opposed to prevalent events. Most importantly, these findings were used to inform the development of a healthcare informatics tool called the Triage Algorithm for PACT Pharmacy Services (TAPPS). TAPPS was designed to help PACT pharmacists efficiently target primary care patients most likely to benefit from clinical pharmacy series. The effectiveness of this tool is currently being studied in an HSR&D funded Merit grant.

---

External Links for this Project

NIH Reporter

Grant Number: IK2HX000761-01A1
Link: https://reporter.nih.gov/project-details/8275333

---

PUBLICATIONS:

None at this time.

DRA: Health Systems Science
DRE: Prevention, Technology Development and Assessment
Keywords: none
MeSH Terms: none