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Nishikawa RM, Schmidt RA, Linver MN, Edwards AV, Papaioannou J, Stull MA. AJR Am J Roentgenol. 2012;198:708-716.
Nishikawa RM ; Schmidt RA ; Linver MN; et al. Clinically missed cancer: how effectively can radiologists use computer-aided detection?. AJR Am J Roentgenol. 2012; 198: 708-716
A computerized clinical decision support system helped radiologists reduce diagnostic errors in mammogram interpretation. However, radiologists ignored more than two-thirds of the prompts provided by the system.
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer.
Ehteshami Bejnordi B, Veta M, Johannes van Diest P, et al; CAMELYON16 Consortium. JAMA. 2017;318:2199-2210.
Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.
Wright A, Ai A, Ash J, et al. J Am Med Inform Assoc. 2017 Oct 16; [Epub ahead of print].
What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation.
Liberati EG, Ruggiero F, Galuppo L, et al. Implement Sci. 2017;12:113.
Sophisticated digital aids could help determine what ails you.
Maron DF. Sci Am. July 21, 2017.
Clinical alerts to decrease high-risk medication use in older adults.
Lord-Adem W, Brandt NJ. J Gerontol Nurs. 2017;43:7-12.
The impact of a diagnostic decision support system on the consultation: perceptions of GPs and patients.
Porat T, Delaney B, Kostopoulou O. BMC Med Inform Decis Mak. 2017;17:79.
Deep learning is a black box, but health care won't mind.
Brouillette M. MIT Technol Rev. April 27, 2017.
Identifying and analyzing diagnostic paths: a new approach for studying diagnostic practices.
Rao G, Epner P, Bauer V, Solomonides A, Newman-Toker DE. Diagnosis. 2017;4:67-72.
Identifying hospitalized patients at risk for harm: a comparison of nurse perceptions vs. electronic risk assessment tool scores.
Stafos A, Stark S, Barbay K, et al. Am J Nurs. 2017;117:26-31.
A learning health care system using computer-aided diagnosis.
Cahan A, Cimino JJ. J Med Internet Res. 2017;19:e54.
Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis.
Prgomet M, Li L, Niazkhani Z, Georgiou A, Westbrook JI. J Am Med Inform Assoc. 2017;24:413-422.
Evaluation of medication-related clinical decision support alert overrides in the intensive care unit.
Wong A, Amato MG, Seger DL, et al. J Crit Care. 2017;39:156-161.
Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation.
Kostopoulou O, Porat T, Corrigan D, Mahmoud S, Delaney BC. Br J Gen Pract. 2017;67:e201-e208.
Clinical reasoning in the context of active decision support during medication prescribing.
Horsky J, Aarts J, Verheul L, Seger DL, van der Sijs H, Bates DW. Int J Med Inform. 2017;97:1-11.
Can computers help doctors reduce diagnostic errors?
Shryock T. Med Econ. December 5, 2016.
Clinical decision support for drug related events: moving towards better prevention.
Kane-Gill SL, Achanta A, Kellum JA, Handler SM. World J Crit Care Med. 2016;5:204-211.
Comparison of physician and computer diagnostic accuracy.
Semigran HL, Levine DM, Nundy S, Mehrotra A. JAMA Intern Med. 2016;176:1860-1861.
Sustained user engagement in health information technology: the long road from implementation to system optimization of computerized physician order entry and clinical decision support systems for prescribing in hospitals in England.
Cresswell KM, Lee L, Mozaffar H, Williams R, Sheikh A; NIHR ePrescribing Programme Team. Health Serv Res. 2017;52:1928-1957.
Effects of health information technology on patient outcomes: a systematic review.
Brenner SK, Kaushal R, Grinspan Z, et al. J Am Med Inform Assoc. 2016;23:1016-1036.
Context-sensitive decision support (infobuttons) in electronic health records: a systematic review.
Cook DA, Teixeira MT, Heale BSE, Cimino JJ, Del Fiol G. J Am Med Inform Assoc. 2017;24:460-468.
Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England.
Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. BMJ Qual Saf. 2017;26:530-541.
Analysis of clinical decision support system malfunctions: a case series and survey.
Wright A, Hickman TT, McEvoy D, et al. J Am Med Inform Assoc. 2016;23:1068-1076.
Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study.
Donsa K, Beck P, Höll B, et al. Int J Med Inform. 2016;90:58-67.
The frequency of inappropriate nonformulary medication alert overrides in the inpatient setting.
Her QL, Amato MG, Seger DL, et al. J Am Med Inform Assoc. 2016;23:924-933.
A cross-sectional observational study of high override rates of drug allergy alerts in inpatient and outpatient settings, and opportunities for improvement.
Slight SP, Beeler PE, Seger DL, et al. BMJ Qual Saf. BMJ Qual Saf 2017;26:217-225.
PSNET: Patient Safety Network
PSNet is produced for the Agency for Healthcare Research and Quality by a team of editors at the University of California, San Francisco with guidance from a prominent Technical Expert/Advisory Panel. The AHRQ PSNet site was designed and implemented by Silverchair.
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