Clinical decision support (CDS) for electronic health records (EHR) and prescribing systems has been promoted to improve patient outcomes. One type of CDS are drug-drug interaction (DDI) alerts. The Office of the National Coordinator for Health IT meaningful use criteria includes the implementation of DDI detection and warnings to physicians and other healthcare professionals. Nearly all healthcare organizations rely on DDI alerts generated from commercial drug knowledge databases. Warnings are currently generated using simple drug combination rules, ignoring drug attributes and the wealth of information available in the EHR that could make the warnings specific to the patient. As a result, providers are bombarded with useless warnings and often miss important ones. Our approach is to change the framework for DDI alerting from basic look-up tables to a more complex, but meaningful, clinical algorithms. Our plan is innovative because it will: 1) eliminate alerts for DDIs that are not clinically important given the patient and drug context; 2) develop implementable and tested algorithms using existing and new evidence; and 3) support the dissemination, implementation, and evaluation of these algorithms across the spectrum of healthcare facilities and organizations. The central hypothesis of this project is that individualizing DDI alerts to specific patient circumstances will result in a much greater proportion of alerts that physicians, pharmacists, and other healthcare providers will be more likely to heed. We will accomplish our objectives and test our hypothesis by pursuing the following aims:
Specific Aim 1 : Design sharable evidence-based individualized DDI algorithms that capitalize on the wealth of patient data located within electronic health records;
Specific Aim 2 : Validate the function of newly designed DDI algorithms using electronic health record data;
and Specific Aim 3 : Conduct a prospective evaluation of DDI algorithms in a variety of healthcare environments including ambulatory and institutional settings. This project will greatly improve CDS for DDIs by incorporating contextual factors into evidence-based and validated alert algorithms, which will reduce alert fatigue and result in more meaningful CDS. Our approach, involving partners across multiple organizations and environments and experts in drug interaction and biomedical informatics, will result in safer healthcare with respect to the use of medications.

Public Health Relevance

The promise of computer systems to improve patient safety has remained largely unfulfilled with respect to drug interaction warnings. Current alerts are simplistic and fail to include specific patient factors, leading to excessive warnings about interactions that are not relevant and healthcare facilities need assistance to implement evidenced-based clinical decision support. This project will develop computer rules that will provide relevant warnings about drug interactions that have been tailored to the specific patient and seek to implement the rules in over 50 healthcare facilities across the United States.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Project (R01)
Project #
5R01HS025984-05
Application #
10163218
Study Section
Healthcare Information Technology Research (HITR)
Program Officer
Gamache, Roland
Project Start
2018-05-01
Project End
2022-02-28
Budget Start
2021-03-01
Budget End
2022-02-28
Support Year
5
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of Utah
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112