Mitesh S. Patel, MD, MBA, MS *; Susan Day, MD, MPH; Dylan S. Small, PhD; John T. Howell III, MD; Gillian L. Lautenbach, MD; Eliot H. Nierman, MD; Kevin G. Volpp, MD, PhD
Grant Support: Dr. Patel was supported by the Department of Veteran Affairs and the Robert Wood Johnson Foundation.
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-3001.
Reproducible Research Statement:Study protocol: Available from Dr. Patel (e-mail, email@example.com). Statistical code: Parts available from Dr. Patel (e-mail, firstname.lastname@example.org). Data set: Not available.
Requests for Single Reprints: Mitesh S. Patel, MD, MBA, MS, Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, 423 Guardian Drive, 12th Floor, Blockley Hall, Philadelphia, PA 19104; e-mail, email@example.com.
Current Author Addresses: Dr. Patel: Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, 423 Guardian Drive, 12th Floor Blockley Hall, Philadelphia, PA 19104.
Drs. Day, Lautenbach, and Nierman: Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, 3701 Market Street, 7th Floor, Philadelphia, PA 19104.
Dr. Small: Department of Statistics, The Wharton School at the University of Pennsylvania, 464 Huntsman Hall, 3730 Walnut Street, Philadelphia, PA 19104.
Dr. Howell: Office of the Chief Medical Information Officer at the University of Pennsylvania, 3001 Market Street, 4th Floor, Philadelphia, PA 19104.
Dr. Volpp: Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, 1120 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021.
Author Contributions: Conception and design: M.S. Patel, S. Day, J.T. Howell, G.L. Lautenbach, E.H. Nierman, K.G. Volpp.
Analysis and interpretation of the data: M.S. Patel, S. Day, D.S. Small, K.G. Volpp.
Drafting of the article: M.S. Patel, S. Day.
Critical revision of the article for important intellectual content: M.S. Patel, S. Day, D.S. Small, K.G. Volpp.
Final approval of the article: M.S. Patel, E.H. Nierman, K.G. Volpp.
Provision of study materials or patients: M.S. Patel, S. Day, G.L. Lautenbach.
Statistical expertise: M.S. Patel, D.S. Small.
Obtaining of funding: M.S. Patel.
Administrative, technical, or logistic support: M.S. Patel, S. Day, K.G. Volpp.
Collection and assembly of data: M.S. Patel.
Low-value services, such as prescribing brand-name medications that have existing generic equivalents, contribute to unnecessary health care spending.
To evaluate the association of an intervention by using the electronic health record with provider prescription of generic-equivalent medications.
General internal medicine (IM) (n = 2) and family medicine (FM) (n = 2) clinics at the University of Pennsylvania from June 2011 to September 2012.
Attending physicians (IM, n = 38; FM, n = 17) and residents (IM, n = 166; FM, n = 34).
In January 2012, the default in the electronic health record was changed for IM providers from displaying brand and generic medications to displaying initially only generics, with the ability to opt out.
Monthly prescriptions of brand-name and generic-equivalent β-blockers, statins, and proton-pump inhibitors.
During the preintervention period, FM providers had slightly higher rates of generic medication prescribing (range, 80.8% to 85.5%) than did IM providers (range, 75.4% to 79.6%), but both groups had similar trends. In the postintervention period relative to the preintervention period, IM providers had an increase in generic prescribing compared with FM providers for all 3 medications combined (5.4 percentage points [95% CI, 2.2 to 8.7 percentage points]; P < 0.001), β-blockers (10.5 percentage points [CI, 5.8 to 15.2 percentage points]; P < 0.001), and statins (4.0 percentage points [CI, 0.4 to 7.6 percentage points]; P = 0.002). Results for proton-pump inhibitors (2.1 percentage points [CI, −3.7 to 8.0 percentage points]; P = 0.47) were not significant. Subset analyses revealed similar findings for attending physicians. Among residents, however, results
were imprecise, with wide CIs.
Observational single-center evaluation, comparison groups that represented different specialties, and a small subset of medication classes studied.
The use of default options was an effective method to increase the odds of prescribing generic medication equivalents for β-blockers and statins.
U.S. Department of Veterans Affairs and Robert Wood Johnson Foundation.
Example of medication prescriber results before the intervention.
Resulting medication dosing options before the intervention for internal medicine and family medicine providers when a search for “Coreg” was conducted. Brand-name options are listed first, followed by generic-equivalent options.
Example of medication prescriber results after the intervention.
Resulting medication dosing options after the intervention for internal medicine providers when a search for “Coreg” was conducted. Only the generic-equivalent options are listed; users have the ability to opt out and choose the brand-name if warranted.
Table 1. Sample Provider and Prescription Characteristics in the Pre- and Postintervention Periods
Table 2. Estimated Probabilities of Prescribing Generic Medication Equivalents for General IM Providers Compared With FM Providers, by Medication Class
Table 3. Estimated Probabilities of Increased Prescribing of Generic Medication Equivalents for General IM Attendings Compared With FM Attendings, by Medication Class
Table 4. Estimated Probabilities of Increased Prescribing of Generic Medication Equivalents for General IM Residents Compared With FM Residents, by Medication Class
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Patel MS, Day S, Small DS, Howell JT, Lautenbach GL, Nierman EH, et al. Using Default Options Within the Electronic Health Record to Increase the Prescribing of Generic-Equivalent Medications: A Quasi-experimental Study. Ann Intern Med. ;161:S44–S52. doi: 10.7326/M13-3001
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Published: Ann Intern Med. 2014;161(10_Supplement):S44-S52.
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