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BACKGROUND/RATIONALE:
In 2001, the VA Maryland Health Care System (VAMHCS) implemented a re-engineered pharmacy process that translates key scientific evidence into software tools programmed into the Veterans Administrations (VA) Computerized Patient Record System (CPRS). These tools, called MUEs (for Medication Use Evaluation), interpose computerized decision support (CDS) at the time of an electronic prescription (eRx). It is our long-term objective to promote safe and effective drug utilization by integrating CDS into VAs pharmacotherapeutic process, so that nationally developed drug criteria-for-use (CFU) can be seamlessly applied to individual eRx.
OBJECTIVE(S):
Our immediate objective is to evaluate the long-term effectiveness of MUEs aimed at reducing overutilization of antibiotics in outpatients with uncomplicated acute upper respiratory infections (AURI). Our main hypothesis is that MUE can adjust antibiotic utilization toward consensus guidelines for the treatment of outpatients with AURI. To test this hypothesis, we propose studies aimed at answering the following three specific research questions:
1) Do MUEs targeting azithromycin and gatifloxacin adjust utilization of these drugs toward guideline recommendations for acute bronchitis, acute sinusitis and non-specific upper respiratory tract infections?
2) Did the introduction of MUEs aimed at only two antibiotics improve the overall antibiotic utilization for AURI?
3) Following the MUE introduction, what are the predictors of adherence or non-adherence with the guidelines?
METHODS:
This work uses a retrospective observational case-control study, designed to determine the differences in congruence to national antibiotics use guidelines for AURI, prior to and after MUE implementation. The intervention site is VA Maryland Health Care System; the control site is the VA Salt Lake City Health Care System. The study period begins in 2002, after guideline publication and one year prior to MUE implementation in 2003, and continues for four years post MUE implementation (2003 2006).
The project takes advantage of extensive existing relational databases at both study sites and from already developed AURI case-finding algorithms to identify the study population and candidate records for manual chart review. AURI cases will be identified using a structured manual chart review, and classified using explicit case definitions taken from the guidelines themselves. Data analysis includes a variety of statistical tests and appoaches, including chi-square, binomial test for proportion, and multivariate regressions.
FINDINGS/RESULTS:
This is an initial abstract. There are no results at this time.
IMPACT:
The potential impact of this project extends well beyond evaluating an approach to modify antibiotics utilization for outpatients with AURI. The project represents only one of the many evaluation steps that we anticipate will be required to systematically evolve an efficient, effective and safe pharmacotherapeutic management system that integrates CDS at VA. As it stands, and reflecting a bias toward system tolerability, the current MUE process design mandates guideline exposure on a minority of drugs within a (drug class)-disease interaction, and then neither impose nor validate guideline adherence. By measuring the performance of this design at effecting guideline adherence and by highlighting factors that contribute to failures or successes toward that key goal, the proposed study will give important insight on how to prioritize future evaluative and/or redesign interventions.
PUBLICATIONS:
None at this time.
DRA:
Health Services and Systems
DRE:
none
Keywords:
none
MeSH Terms:
none
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