Implementing an Evidence-Based Algorithm for the Diagnosis and Evaluation of Iron Deficiency Anemia (IDA) in Female Basic Military Training Recruits
Abstract
Background: Approximately 25% of United States Air Force (USAF) Basic Military Training (BMT) female recruits entering BMT are anemic, mostly due to iron deficiency (ID) and iron deficiency anemia (IDA), with rates as high as 77% in other military female recruit cohorts. Currently, a standardized, evidence-based algorithm is not used at the Reid Medical Clinic (RMC) to diagnose and evaluate ID/IDA, contributing to an overuse of diagnostic studies, erroneous medical diagnosis, and poor follow-up. Clinical Question: Can the use of an evidence-based educational platform to educate Reid Clinic Providers result in an 11% improved adherence rate to the American Academy of Family Physicians (AAFP) algorithm for the evaluation and diagnosis of IDA among reproductive-aged female BMT recruits compared with current practice? Design: The RE-AIM framework guided a three-month retrospective chart review comparing providers current evaluation and diagnostic practices to the AAFP IDA algorithm recommendations. An interactive, provider-centered educational class with case studies, pre/post-tests, handouts, monthly staff meetings, selected project champions, and three months of post-workshop biweekly chart audits were completed. Analysis of the Results: Comparison of a three-month retrospective chart review containing 126 records with a three-month post-implementation chart review containing 170 records revealed a 43.75% increase in compliance to the AAFP algorithm. There was a reduction in diagnostic studies post-implementation which resulted in an estimated savings of $105,248.00 annually, if fully adopted. Organizational Impact/Implications for Practice: The RMC shows increased compliance with algorithm utilization, with a continued rise anticipated. Sustainability is maintained by selecting a change champion as well as acquiring a mandated policy letter from the Medical Director, enforcing the AAFP algorithm.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 28, 2020
- Accession Number
- AD1182691
Entities
People
- Matthew Simmons
- Melissa Everage
- Nicholas Robertson
- Virgina Frazier
Organizations
- Uniformed Services University of the Health Sciences