AHRQ Patient Safety Network

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The Collection

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Safety Target

•Device-related Complications (88)

•Diagnostic Errors (141)

•Identification Errors (62)

•Discontinuities, Gaps, and Hand-Off Problems (305)

•Fatigue and Sleep Deprivation (60)

•Medication Safety (961)

•Medical Complications (283)

•Nonsurgical Procedural Complications (46)

•Surgical Complications (307)

•Transfusion Complications (13)

•Psychological and Social Complications (89)

Origin/Sponsor

•Africa (3)

•Asia (60)

•Australia and New Zealand (86)

•Central and South America (8)

•Europe (382)

•North America (1958)

Resource Types
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Study

Error Types

•Epidemiology of Errors and Adverse Events (1250)

•Active Errors (361)

•Latent Errors (103)

•Near Miss (62)

Approach to Improving Safety

•Quality Improvement Strategies (500)

•Legal and Policy Approaches (104)

•Error Reporting and Analysis (787)

•Communication Improvement (516)

•Human Factors Engineering (251)

•Teamwork (175)

•Specialization of Care (181)

•Logistical Approaches (198)

•Culture of Safety (217)

•Technologic Approaches (564)

•Education and Training (405)

Clinical Areas

•Allied Health Services (5)

Target Audience

•Health Care Providers (1823)

•Health Care Executives and Administrators (2068)

•Non-Health Care Professionals (946)

•Patients (26)

Setting of Care

•Hospitals (1737)

•Psychiatric Facilities (11)

•Residential Facilities (63)

•Ambulatory Care (292)

•Outpatient Surgery (17)

•Patient Transport (23)

1 - 20 of 2493

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STUDY

Critical drug–drug interactions for use in electronic health records systems with computerized physician order entry: review of leading approaches.

Classen DC, Phansalkar S, Bates DW. J Patient Saf. 2011;7:61-65.

STUDY

Identifying causes of adverse events detected by an automated trigger tool through in-depth analysis.

Muething SE, Conway PH, Kloppenborg E, et al. Qual Saf Health Care. 2010;19:435-439.

STUDY

Medication errors with electronic prescribing (eP): two views of the same picture.

Savage I, Cornford T, Klecun E, Barber N, Clifford S, Franklin BD. BMC Health Serv Res. 2010;10:135.

STUDY

Predictive value of alert triggers for identification of developing adverse drug events.

Moore C, Li J, Hung CC, Downs J, Nebeker JR. J Patient Saf. 2009;5:223-228.

STUDY

Comparison of computerized surveillance and manual chart review for adverse events.

Tinoco A, Evans RS, Staes CJ, Lloyd JF, Rothschild JM, Haug PJ. J Am Med Inform Assoc. 2011;18:491-497.

STUDY

The relationship between computerized physician order entry and pediatric adverse drug events: a nested matched case-control study.

Yu F, Salas M, Kim YI, Menachemi N. Pharmacoepidemiol Drug Saf. 2009;18:751-755.

STUDY

Preventing potentially inappropriate medication use in hospitalized older patients with a computerized provider order entry warning system.

Mattison MLP, Afonso KA, Ngo LH, Mukamal KJ. Arch Intern Med. 2010;170:1331-1336.

STUDY

Outpatient adverse drug events identified by screening electronic health records.

Gandhi TK, Seger AC, Overhage JM, et al. J Patient Saf. 2010;6;91-96.

STUDY

Effect of bar-code technology on the safety of medication administration.

Poon EG, Keohane CA, Yoon CS, et al. N Engl J Med. 2010;362:1698-1707.

STUDY

Comparison of methods for identifying patients at risk of medication-related harm.

van Doormaal JE, Rommers MK, Kosterink JGW, Teepe-Twiss IM, Haaijer-Ruskamp FM, Mol PGM. Qual Saf Health Care. 2010;19:e26.

STUDY

Does the implementation of an electronic prescribing system create unintended medication errors? A study of the sociotechnical context through the analysis of reported medication incidents.

Redwood S, Rajakumar A, Hodson J, Coleman JJ. BMC Med Inform Decis Mak. 2011;11:29.

STUDY

An unintended consequence of electronic prescriptions: prevalence and impact of internal discrepancies.

Palchuk MB, Fang EA, Cygielnik JM, et al. J Am Med Inform Assoc. 2010;17:472-476.

STUDY

Utilising improvement science methods to optimise medication reconciliation.

White CM, Schoettker PJ, Conway PH, et al. BMJ Qual Saf. 2011;20:372-380.

STUDY

Electronic health records and adverse drug events after patient transfer.

Boockvar KS, Livote EE, Goldstein N, Nebeker JR, Siu A, Fried T. Qual Saf Health Care. 2010;19:e16.

STUDY

Medication errors resulting from computer entry by nonprescribers.

Santell JP, Kowiatek JG, Weber RJ, Hicks RW, Sirio CA. Am J Health Syst Pharm. 2009;66:843-853.

STUDY

Effect of computerized provider order entry with clinical decision support on adverse drug events in the long-term care setting.

Gurwitz JH, Field TS, Rochon P, et al. J Am Geriatr Soc. 2008;56:2225-2233.

STUDY

Impact of health information technology on detection of potential adverse drug events at the ordering stage.

Roberts LL, Ward MM, Brokel JM, Wakefield DS, Crandall DK, Conlon P. Am J Health Syst Pharm. 2010;67:1838-1846.

STUDY

Characteristics of medication errors and adverse drug events in hospitals participating in the California Pediatric Patient Safety Initiative.

Takata GS, Taketomo CK, Waite S; for the California Pediatric Patient Safety Initiative. Am J Health Syst Pharm. 2008;65:2036-2044.

STUDY

National study on the frequency, types, causes, and consequences of voluntarily reported emergency department medication errors.

Pham JC, Story JL, Hicks RW, et al. J Emerg Med. 2011;40:485-492.

STUDY

Physician order entry or nurse order entry? Comparison of two implementation strategies for a computerized order entry system aimed at reducing dosing medication errors.

Kazemi A, Fors UG, Tofighi S, Tessma M, Ellenius J. J Med Internet Res. 2010;12:e5.

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