OBJECTIVE: To evaluate the effects of providing appropriateness criteria through guideline-based electronic health record (EHR) decision support for high-tech diagnostic imaging (HTDI) procedures. STUDY DESIGN: Chart audits were performed on a random sample of adult primary care orders for 3 HTDI procedures (computed tomography [CT] and magnetic resonance imaging [MRI] of the head, and MRI of the lumbar spine) before and after implementation of an EHR decision support system. OUTCOME MEASURES: Level of appropriateness, abnormal findings, and apparent effects on patient care. RESULTS: A total of 299 eligible audits were performed. Decision support was associated with a 20% to 36% drop in spine MRI and head CT orders, but head MRI order volume was unaffected. Combined results for the 3 procedures showed that a larger proportion of studies ordered after implementing decision support (89.2% vs 79.5%, P = .02) fit appropriateness criteria, and more postimplementation studies had A ratings (highest utility rating) (81.8% vs 70%, P = .04). However, there were no differences in the proportion of tests with positive findings (42/132 vs 28/120, P = .16 among procedures that met definite criteria) or the proportion with a likely impact on patients (6.6% vs 10.8%, P = .07). CONCLUSIONS: These data support the feasibility of using chart audits to assess the relationship between appropriateness criteria and HTDI orders. Although introduction of EHR clinical decision support for diagnostic imaging orders was associated with reduced volume and increased appropriateness of orders, there was little apparent impact on either findings or patients.
OBJECTIVE: To evaluate the effects of providing appropriateness criteria through guideline-based electronic health record (EHR) decision support for high-tech diagnostic imaging (HTDI) procedures. STUDY DESIGN: Chart audits were performed on a random sample of adult primary care orders for 3 HTDI procedures (computed tomography [CT] and magnetic resonance imaging [MRI] of the head, and MRI of the lumbar spine) before and after implementation of an EHR decision support system. OUTCOME MEASURES: Level of appropriateness, abnormal findings, and apparent effects on patient care. RESULTS: A total of 299 eligible audits were performed. Decision support was associated with a 20% to 36% drop in spine MRI and head CT orders, but head MRI order volume was unaffected. Combined results for the 3 procedures showed that a larger proportion of studies ordered after implementing decision support (89.2% vs 79.5%, P = .02) fit appropriateness criteria, and more postimplementation studies had A ratings (highest utility rating) (81.8% vs 70%, P = .04). However, there were no differences in the proportion of tests with positive findings (42/132 vs 28/120, P = .16 among procedures that met definite criteria) or the proportion with a likely impact on patients (6.6% vs 10.8%, P = .07). CONCLUSIONS: These data support the feasibility of using chart audits to assess the relationship between appropriateness criteria and HTDI orders. Although introduction of EHR clinical decision support for diagnostic imaging orders was associated with reduced volume and increased appropriateness of orders, there was little apparent impact on either findings or patients.
Authors: Amanda Hall; Helen Richmond; Andrea Pike; Rebecca Lawrence; Holly Etchegary; Michelle Swab; Jacqueline Y Thompson; Charlotte Albury; Jill Hayden; Andrea M Patey; James Matthews Journal: Implement Sci Date: 2021-07-02 Impact factor: 7.327