The role of a best practice alert in the electronic medical record in reducing repetitive lab tests

Abstract

BackgroundThe recommendations of the American Board of Internal Medicine Foundation’s “Choosing Wisely®” initiative recognize the importance of improving the appropriateness of testing behavior and reducing the number of duplicate laboratory tests.ObjectiveTo assess the effectiveness of an electronic medical record Best Practice Alert (BPA or “pop up”) intervention aimed at reducing duplicate laboratory tests and hospital costs.DesignComparison of the number of duplicated laboratory tests performed on inpatients before and after the intervention.SettingUniversity of Florida Health Shands Hospital, Gainesville, FL, USA, during 2014–2017.InterventionThe electronic medical record intervention was a BPA pop-up alert that informed the ordering physician if a recent identical order already existed along with the “ordering time”, “collecting time”, “resulting time”, and the result itself.Main outcome measuresPercentage change in the number of inpatient duplicate orders of selected clinical biochemistry tests and cost savings from reduction of the duplicates. Student’s t-test and beta-binomial models were used to analyze the data.ResultsResults from the beta-binomial model indicated that the intervention reduced the overall duplicates by 18% (OR=0.82, standard error=0.016, P-value<0.000). Percent reductions in 9 of the 17 tests were statistically significant: serum hemoglobin A1C level, vitamin B12, serum erythrocyte sedimentation rate, serum folate, serum iron, lipid panel, respiratory viral panel, serum thyroid stimulating hormone level, and Vitamin D. Additionally, important cost savings were realized from the reduction of duplicates for each lab test (with the exception of CRP) with an estimated overall savings of $72,543 over 17 months in the post-intervention period.ConclusionsThe present study included all hospital inpatients and covered 17 clinical laboratory tests. This rather simple and low-cost intervention resulted in significant reductions in percentage duplicates of several tests and resulted in cost savings. The study also highlights the role of hospitalists in quality improvement.

Economic impact of clinical decision support interventions based on electronic health records

“…An overview of the characteristics of the included studies is listed in Table 2. Generally, twenty-two studies (81%) [5,[13][14][15][16]18,[20][21][22][23][24][25][28][29][30][31]32,[34][35][36][37][38] out of the included twenty-seven studies report cost savings after implementing an EHR based CDS intervention. Four studies (15%) [17,26,27,33] report a rise in cost expenditure.…”

“…In the majority of included studies the main cost outcome measures were related to laboratory test cost. [15][16][17]20,21,25,28,29,31,32,38] Exploration of different front-end CDS intervention categories According to the taxonomy by Wright et al [12], we identi ed ten (37%) studies [5,13,15,20,22,23,26,[36][37][38] which explored EHR based CDS interventions based on point-of-care alerts or reminders (category 3). Three interventions (11%) [17,27,34] were order facilitators (category 2).…”

“…Lastly, ve studies [20,29,31,32,38] report on the potential to reduce duplicate orders, e.g., duplicate laboratory tests, using hard-stops [32] or order frequency rules. [20] Order frequency rules prevent ordering the same test within a speci ed timeframe. Reducing duplicate laboratory tests resulted in savings of $3,395 after three months for a small patient size cohort [38], and up to $315,565 within twenty-four month for a large patient size cohort.…”

Modifying Provider Vitamin D Screening Behavior in Primary Care

“…While our finding contradicts other studies that found that EHR interventions modified provider behavior, this may be explained by some differences specific to our intervention. [15][16][17] It is likely that the EHR intervention here was not robust enough. Instead of ordering vitamin D test using the quick order screen, providers still had the option to order the test using a customized "favorites" screen, "powerplan" screens designed for specific conditions, or 16 (7.4% and 2.4%) while our IM pre-and postintervention rates are higher (9.88% and 7.98% posteducation memo).…”

“…14 In previous studies, various combinations of behavioral modification tools including provider education, electronic health record (EHR) based interventions (eg, clinical decision support, alerting), choice architecture modifications (eg, removal from ordering lists), and peer comparison reports have each been applied to help modify providers' ordering behaviors. [15][16][17][18][19][20] In prepost cross-sectional descriptive analyses, Felcher et al 16 found that vitamin D screening rates decreased nearly 70% after implementation of a bundle of 3 clinical decision support tools: educating providers about new screening guidelines, a hard-stop alert (ie, order prevented, justification required to override), and laboratory order list modifications. The authors, however, could not isolate the effect of the education intervention from EHR components.…”