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Pain Med. 2019 Jan 1;20(1):103-112. doi: 10.1093/pm/pnx304.

Implementing Electronic Health Record Default Settings to Reduce Opioid Overprescribing: A Pilot Study.

Author information

Mathematica Policy Research, Michigan.
Department of Veterans Affairs, Center for Clinical Management Research, Ann Arbor, Michigan.
Department of Psychiatry, University of Michigan Medical School, Ann Arbor, Michigan.
Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services, Washington, District of Columbia.
Community Health Center, Inc., Middletown, Connecticut.
WVU Medicine, Morgantown, West Virginia, USA.



To pilot test the effectiveness, feasibility, and acceptability of instituting a 15-pill quantity default in the electronic health record for new Schedule II opioid prescriptions.


A mixed-methods pilot study in two health systems, including pre-post analysis of prescribed opioid quantity and focus groups or interviews with prescribers and health system administrators.


We implemented a 15-pill electronic health record default for new Schedule II opioids and assessed opioid quantity before and after implementation using electronic health record data on 6,390 opioid prescriptions from 448 prescribers. We then analyzed themes from focus groups and interviews with four staff members and six prescribers.


The proportion of opioid prescriptions for 15 pills increased at both sites after adding an electronic health record default, with one reaching statistical significance (from 4.1% to 7.2% at CHC, Pā€‰=ā€‰0.280, and 15.9% to 37.2% at WVU, Pā€‰<ā€‰0.001). The proportion of 15-pill prescriptions increased among high-prescribing departments and among most high- and low-frequency prescribers, except for low-frequency prescribers at CHC. Sites reported limited challenges in instituting the default, although ease of implementation varied by electronic health record vendor. Most prescribers were not aware of the default change and stated that they made prescribing decisions based on patient clinical characteristics rather than defaults.


This pilot provides initial evidence that changing default settings can increase the number of prescriptions at the default level. This low-cost and relatively simple intervention could have an impact on opioid overprescribing. However, default settings should be selected carefully to avoid unintended consequences.


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