Subscribe to RSS
Implementing Black Box Warnings (BBWs) in Health Information SystemsAn Organizing Taxonomy Identifying Opportunities and Challenges
18 December 2011
accepted: 24 February 2012
16 December 2017 (online)
Objective: To develop a practical approach for implementing clinical decision support (CDS) for medication black box warnings (BBWs) into health information systems (HIS).
Methods: We reviewed all existing medication BBWs and organized them into a taxonomy that identifies opportunities and challenges for implementing CDS for BBWs into HIS.
Results: Of the over 400 BBWs that currently exist, they can be organized into 4 categories with 9 sub-categories based on the types of information contained in the BBWs, who should be notified, and potential actions to that could be taken by the person receiving the BBW. Informatics oriented categories and sub-categories of BBWs include – interactions (13%) (drug-drug (4%) and drug-diagnosis (9%)), testing (21%) (baseline (9%) and on-going (12%)), notifications (29%) (drug prescribers (7%), drug dispensers (2%), drug administrators (9%), patients (10%), and third parties (1%)), and non-actionable (37%). This categorization helps identify BBWs for which CDS can be easily implemented into HIS today (such as drug-drug interaction BBWs), those that cannot be easily implemented into HIS today (such as non-actionable BBWs), and those where advanced and/ or integrated HIS need to be in place to implement CDS for BBWs (such a drug dispensers BBWs).
Conclusions: HIS have the potential to improve patient safety by implementing CDS for BBWs. A key to building CDS for BBWs into HIS is developing a taxonomy to serve as an organizing roadmap for implementation. The informatics oriented BBWs taxonomy presented here identified types of BBWs in which CDS can be implemented easily into HIS currently (a minority of the BBWs) and those types of BBWs where CDS cannot be easily implemented today (a majority of BBWs).
- 1 21 code of Federal Regulations paragraph 201.57(e) (2000).
- 2 Generali J. Black Box Warning. www.formularyproductions.com/blackbox. Accessed May 2011.
- 3 Wagner AK, Chan KA, Dashevsky I MA. FDA drug prescribing warnings: Is the black box half empty or half full?. Pharmacoepidemiol Drug Saf 2006; 15 (06) 369-386.
- 4 Raeble MA, Lyons EE, Andreade SE, Chan KA, Chester EA, Davis RL. et al. Laboratory monitoring of drugs at initiation of therapy in ambulatory care. J Gen Intern Med 2005; 20: 1120-1126.
- 5 Lasser KE, Seger DL, Yu DT, Karson AS, Fiskio JM, Seger AC. et al. Adherence to black box warnings for prescription medications in outpatients. Arch Intern Med 2006; 166 (03) 338-344.
- 6 Horlen C, Malone R, Bryant B, Dennis B, Carey T, Pignone M. et al. Frequency of inappropriate metformin prescriptions. JAMA 2002; 287: 2504-2505.
- 7 Smalley W, Shatin D, Wysowski DK, Gurwitz J, Andreade SE, Goodman M. et al. Contraindicated use of cisapride: impact of FDA Regulatory Action. JAMA 2000; 284: 3036-3039.
- 8 Guo JJ, Curkendall S, Jones JK, Fife D, Goehring E, She D. Impact of cisapride label changes on codispensing of contraindicated medications. Pharmacoepidemiol Drug Safe 2003; 12: 295-301.
- 9 Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14 (01) 29-40.
- 10 Kuperman GJ, Teich JM, Gandhi TK, Bates DW. Patient safety and computerized medication ordering at Brigham and Women’s Hospital. Jt Comm J Qual Improv 2001; 27 (10) 509-521.
- 11 Bates DW, Kuperman GJ, Wang S, Gandhi T, Kittler A, Volk L. et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc 2003; 10 (06) 523-530.
- 12 Thompson, CA. Hospital inspectors eye black-box warnings. AM J Health Syst Pharm 2008; 65: 890-894.
- 13 Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14 (01) 29-40.
- 14 Wright A, Phansalkar S, Bloomrosen M, Jenders RA, Bobb AM, Halamka JD. et al. Best practices in clinical decision support: the case of preventive care reminders. Appl Clin Inform 2010; 1 (03) 331-345.
- 15 Osheroff JA, Teich JM, Levick D, Saldana L, Velasco FT, Sittig DF. et al. Improving outcomes with clinical decision support: An implementer’s guide. Second edition. HIMSS.. 2012.
- 16 Ahmadian L, van Engen-Verheul M, Bakhshi-Raiez F, Peek N, Cornet R, and de Keizer NF. The role of standardized data and terminology systems in the computerized clinical decision support systems: literature review and survey. Int J Med Inform 2011; 80 (02) 81-93.
- 17 Food and Drug Administration. Guidance for industry –warnings and precautions, contraindications, and boxed warning sections of labeling for human prescription drug and biological products –content and format. Food and Drug Administration. October 2011.
- 18 MedDRA Maintenance and Support Services Organization. Introductory guide to MedDRA Version 14.0. Chantilly, Virginia. March, 2011
- 19 Harpaz R, Chase HS, and Friedman C. Mining multi-item drug adverse effect associations in spontaneous reporting systems. BMC Bioinformatics 2010; 11 (Suppl. 09) S7.
- 20 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG. et al. Use of electronic health records in U. S. hospitals. N Engl J Med 2009; 360 (16) 1628-1638.
- 21 Jha AK, Bates DW, Jenter C, Orav EJ, Zheng J, Cleary P. et al. Electronic health records: use, barriers and satisfaction among physicians who care for black and Hispanic patients. J Eval Clin Pract 2009; 15 (01) 158-163.
- 22 Kawamoto K, Houklihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005; 330 7494 765.
- 23 Damiana G, Pinnarelli L, Colosimo SC, Almiento R, Sicuro L, Galasso R. et al. The effectiveness of computerized clinical guidelines in the process of care: a systematic review. BMC Health Serv Res 2010; 10: 2.