Identification of Serious Drug–Drug Interactions: Results of the Partnership to Prevent Drug–Drug Interactions

doi:10.1331/154434504773062591

Journal of the American Pharmacists Association

Volume 44, Issue 2, March–April 2004, Pages 142-151

https://doi.org/10.1331/154434504773062591 Get rights and content

ABSTRACT

Objective

To develop a list of clinically important drug–drug interactions (DDIs) likely to be encountered in community and ambulatory pharmacy settings and detected by a computerized pharmacy system.

Design

Cross-sectional, one-time evaluation.

Setting

United States in fall 2001.

Participants

An expert panel comprising two physicians, two clinical pharmacists, and an expert on DDIs.

Interventions

Systematic review of drug interaction compendia and published literature, ratings (on a 1 to 10 scale) of various clinical aspects of DDIs (e.g., clinical importance, quality and quantity of evidence, causal relationship, risk of morbidity and mortality), and a modified Delphi consensus-building process.

Main Outcome Measure

Panelists’ opinions about clinical importance of DDIs.

Results

The expert panel considered 56 DDIs. Of these, 28 had a mean clinical importance score of 8.0 or more. The ratings for clinical importance ranged from 3.2 to 9.6, with a mean ± SD of 7.5 ± 1.5 across the combinations examined. The mean score for the quality of literature suggesting the interaction exists ranged from 1.0 to 9.6, with a mean ± SD of 5.8 ± 2.5. In terms of substantiation of the interactions evaluated, the mean ± SD rating was 6.3 ± 2.2, with a range from 1.4 to 9.2. Through the modified Delphi process, the panel determined that 25 interactions were clinically important.

Conclusion

Using an expert panel and a standard evaluation tool, 25 clinically important drug interactions that are likely to occur in the community and ambulatory pharmacy settings were identified. Pharmacists should take steps to prevent patients from receiving these interacting medications, and computer software vendors should focus interaction alerts on these and similarly important DDIs.

Section snippets

Objectives

The purpose of this study was to develop a list of the clinically important DDIs that are likely to be encountered in community and ambulatory pharmacy settings and detected by a computerized pharmacy system.

Methods

A three-stage process was undertaken to identify DDIs of the highest clinical importance. Clinically important interactions were defined as those interactions most likely to cause harm if not detected. This process began with the selection of candidate interactions from a review of drug interaction compendia followed by a systematic literature review and the development of an evidence report for each candidate DDI. These evidence reports were then evaluated and rated by an expert panel using a

Results

Table 1 lists the number of severe or major interactions identified in each compendium. The listed interactions were then aggregated at the medication class level when appropriate. Sixty-two DDIs were found in at least 3 out of the 4 compendia. As detailed below, 18 DDIs were excluded from further consideration for one of the five reasons for exclusion presented in the Methods.

Eight DDIs were excluded because at least one of the medications was no longer available in the United States (the

Discussion

We used a systematic evaluation of the literature and an expert-panel process to identify clinically important DDIs. Our panel evaluated 54 DDIs and assigned a mean score for clinical importance of 7.5 on a 1 to 10 scale. After excluding products that were not on the U.S. market, products not likely to be used in an outpatient setting, and combinations that can be used for therapeutic benefit, a total of 25 clinically important DDIs were identified.

Hundreds of drug interactions are listed in

Limitations

The reader should keep several limitations in mind when interpreting our findings, most notably the use of an expert panel to rate the DDIs. Expert panels make subjective judgments based on the best evidence available, but these conclusions may be imperfect. The results are likely to differ depending upon the membership of the panel. By using a modified Delphi approach, we were able to minimize the potential for coalescence around one or two members' opinions and to ensure that all members were

Conclusion

Using an expert panel and a standard evaluation tool, we identified 25 drug interactions deemed to be clinically important and likely to occur in the community and ambulatory pharmacy settings. These interactions represent a subset of all interactions that have been noted by drug interaction compendia as being of high severity or major importance. We encourage pharmacists to take steps to prevent patients from receiving these interacting medications and computer software vendors to focus

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Disclosure: Dr. Hansten is an editor of and declares financial interests in the textbook, Hansten and Horn's Drug Interaction Analysis and Management. Dr. Lipton has financial interests in AdvancePCS, and as noted above, Ms. Van Bergen is a former employee and Dr. Duncan-Edgar is a current employee of that firm. The other authors declare no conflicts of interest or financial interests in any product or service mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria.

Funding: Supported by the Centers for Disease Control and Prevention, Contract 2001-N-08014.

Acknowledgment: The authors would like to thank John Palmer, MD, for participating on the expert panel used in this study.

Presented previously at the Academy of Managed Care Pharmacy Annual Meeting, Minneapolis, Minn., April 10, 2003, and the American Academy of Family Physicians National Ambulatory Primary Care Research & Education Conference on Patient Safety, Chicago, Ill., September 18, 2003.

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RESEARCHIdentification of Serious Drug–Drug Interactions: Results of the Partnership to Prevent Drug–Drug Interactions

ABSTRACT

Objective

Design

Setting

Participants

Interventions

Main Outcome Measure

Results

Conclusion

Section snippets

Objectives

Methods

Results

Discussion

Limitations

Conclusion

J Am Pharm Assoc.

Lancet.

J Am Pharm Assoc.

J Am Pharm Assoc.

Curr Opin Chem Biol.

Curr Ther Res.

To err is human

Drug-related morbidity and mortality. A cost- of-illness model

Arch Intern Med

IMS health reports 14.9 percent growth in US prescription sales to $145 billion in 2000 [news release]

The economic consequences of a drug-drug interaction

J Clin Psychopharmacol.

The role of pharmacy computer systems in preventing medication errors

J Am Pharm Assoc.

Evaluation of online prospective DUR programs in community pharmacy practice

J Manag Care Pharm.

Collecting and analyzing expert group judgment data

The Hearst Corporation

Drug interaction facts

Drug interactions: analysis and management

DRUG-REAX system

RESEARCH
Identification of Serious Drug–Drug Interactions: Results of the Partnership to Prevent Drug–Drug Interactions