Detecting pregnancy use of non-hormonal category X medications in electronic medical records

Journal of the American Medical Informatics Association

Volumn 18, Issue SUPPL. 1, 2011, Pages 81-86

  Strom, Brian L ^a   Schinnar, Rita ^a   Jones, Joshua ^b   Bilker, Warren B ^a   Weiner, Mark G ^a   Hennessy, Sean ^a   Leonard, Charles E ^a   Cronholm, Peter F ^a   Pifer, Eric ^c  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c EL CAMINO HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; DRUG EXPOSURE; ELECTRONIC MEDICAL RECORD; FEMALE; HUMAN; MEDICAL RECORD REVIEW; PREGNANCY; PRESCRIPTION; ENVIRONMENTAL EXPOSURE; HOSPITAL INFORMATION SYSTEM; INAPPROPRIATE PRESCRIBING; PREGNANCY COMPLICATION; PREGNANCY TEST;

TERATOGENIC AGENT;

ALGORITHMS; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; INAPPROPRIATE PRESCRIBING; MATERNAL EXPOSURE; MEDICAL ORDER ENTRY SYSTEMS; PREGNANCY; PREGNANCY COMPLICATIONS; PREGNANCY TESTS; TERATOGENS;

EID: 84863552304     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2010-000057     Document Type: Article

References (28)

1. Briggs GG, Freeman RK, Jaffe SJ, eds. Drugs in Pregnancy and Lactation, 7th edn. Philadelphia, PA: Lippincott, Williams and Wilkins, 2005.
2. Cooper WO, Hickson GB, Ray WA. Prescriptions for contraindicated category X drugs in pregnancy among women enrolled in TennCare. Paediatr Perinat Epidemiol 2004;18:106-11.
3. Andrade SE, Gurwitz JH, Davis RL, et al. Prescription drug use in pregnancy. Am J Obstet Gynecol 2004;191:398-407.
4. Hardy JR, Leaderer BP, Holford TR, et al. Safety of medications prescribed before and during early pregnancy in a cohort of 81,975 mothers from the UK General Practice Research Database. Pharmacoepidemiol Drug Saf 2006;15:555-64.
5. Yang T, Walker MC, Krewski D, et al. Maternal characteristics associated with pregnancy exposure to FDA category C, D, and X drugs in a Canadian population. Pharmacoepidemiol Drug Saf 2008;17:270-7.
6. Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998;280:1311-16.
7. Berger RG, Kichak JP. Computerized physician order entry: helpful or harmful? J Am Med Inform Assoc 2004;11:100-3.
8. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005;293:1197-203.
9. Anderson JG, Jay SJ, Anderson M, et al. Evaluating the capability of information technology to prevent adverse drug events: a computer simulation approach [see comment]. J Am Med Inform Assoc 2002;9:479-90.
10. Teich JM, Merchia PR, Schmiz JL, et al. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000;160:2741-7.
11. Potts AL, Barr FE, Gregory DF, et al. Computerized physician order entry and medication errors in a pediatric critical care unit. Pediatrics 2004;113:59-63.
12. Terrell KM, Perkins AJ, Dexter PR, et al. Computerized decision support to reduce potentially inappropriate prescribing to older emergency department patients: a randomized, controlled trial. J Am Geriatr Soc 2009;57:1388-94.
13. van Doormaal JE, van den Bemt PM, Zaal RJ, et al. The influence of computerized prescribing on medication errors and preventable adverse drug events: an interrupted time series study. J Am Med Inform Assoc 2009;16:816-25.
14. Fernando B, Savelyich BS, Avery AJ, et al. Prescribing safety features of general practice computer systems: evaluation using simulated test cases. BMJ 2004;328:1171-2.
15. Eslami S, Abu-Hanna A, de Keizer NF, et al. Errors associated with applying decision support by suggesting default doses for aminoglycosides. Drug Saf 2006;29:803-9.
16. Demakis JG, Beauchamp C, Cull WL, et al. Improving residents' compliance with standards of ambulatory care: results from the VA Cooperative Study on Computerized Reminders [see comment]. JAMA 2000;284:1411-16.
17. Weingart SN, Toth M, Sands DZ, et al. Physicians' decisions to override computerized drug alerts in primary care. Arch Intern Med 2003;163:2625-31.
18. van der Sijs H, Mulder A, van Gelder T, et al. Drug safety alert generation and overriding in a large Dutch university medical centre. Pharmacoepidemiol Drug Saf 2009;18:941-7.
19. EPIC Systems Corp. EPIC Inpatient Clinical 2011. http://www.epic.com/softwareinpatient. php (accessed 3 Nov 2011).
20. Anon. Physicians' Desk Reference, 59th edn. Montvale, NJ: Thompson PDR, 2005.
21. McCullagh P, Nelder J. Generalized Linear Models. London: Chapman and Hall, 1989.
22. Wen SW, Yang T, Krewski D, et al. Patterns of pregnancy exposure to prescription FDA C, D and X drugs in a Canadian population. J Perinatol 2008;28:324-9.
23. Raebel MA, Carroll NM, Kelleher JA, et al. Randomized trial to improve prescribing safety during pregnancy. J Am Med Inform Assoc 2007;14:440-50.
24. Solti I, Aaronson B, Fletcher G, et al. Building an automated problem list based on natural language processing: lessons learned in the early phase of development. AMIA Annu Symp Proc 2008;2008:687-91.
25. Meystre S, Haug PJ. Natural language processing to extract medical problems from electronic clinical documents: performance evaluation. J Biomed Inform 2006;39:589-99.
26. Chen ES, Wright A, Maloney FL, et al. Enhancing clinical problem lists through data mining and natural language processing. AMIA Annu Symp Proc 2008;2008:901.
27. Van Vleck TT, Wilcox A, Stetson PD, et al. Content and structure of clinical problem lists: a corpus analysis. AMIA Annu Symp Proc 2008;2008:753-7.
28. Poissant L, Taylor L, Huang A, et al. Assessing the accuracy of an inter-institutional automated patient-specific health problem list. BMC Med Inform Decis Mak 2010;10:10.