224 related articles for article (PubMed ID: 21836158)
1. Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors.
Scott GP; Shah P; Wyatt JC; Makubate B; Cross FW
J Am Med Inform Assoc; 2011; 18(6):789-98. PubMed ID: 21836158
[TBL] [Abstract][Full Text] [Related]
2. Can an electronic prescribing system detect doctors who are more likely to make a serious prescribing error?
Coleman JJ; Hemming K; Nightingale PG; Clark IR; Dixon-Woods M; Ferner RE; Lilford RJ
J R Soc Med; 2011 May; 104(5):208-18. PubMed ID: 21558099
[TBL] [Abstract][Full Text] [Related]
3. Junior doctors' prescribing work after-hours and the impact of computerized decision support.
Jaensch SL; Baysari MT; Day RO; Westbrook JI
Int J Med Inform; 2013 Oct; 82(10):980-6. PubMed ID: 23891565
[TBL] [Abstract][Full Text] [Related]
4. Reducing prescribing errors through creatinine clearance alert redesign.
Melton BL; Zillich AJ; Russell SA; Weiner M; McManus MS; Spina JR; Russ AL
Am J Med; 2015 Oct; 128(10):1117-25. PubMed ID: 26087048
[TBL] [Abstract][Full Text] [Related]
5. A systematic review of the effectiveness of interruptive medication prescribing alerts in hospital CPOE systems to change prescriber behavior and improve patient safety.
Page N; Baysari MT; Westbrook JI
Int J Med Inform; 2017 Sep; 105():22-30. PubMed ID: 28750908
[TBL] [Abstract][Full Text] [Related]
6. A randomized trial of the effectiveness of on-demand versus computer-triggered drug decision support in primary care.
Tamblyn R; Huang A; Taylor L; Kawasumi Y; Bartlett G; Grad R; Jacques A; Dawes M; Abrahamowicz M; Perreault R; Winslade N; Poissant L; Pinsonneault A
J Am Med Inform Assoc; 2008; 15(4):430-8. PubMed ID: 18436904
[TBL] [Abstract][Full Text] [Related]
7. What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior?
Schedlbauer A; Prasad V; Mulvaney C; Phansalkar S; Stanton W; Bates DW; Avery AJ
J Am Med Inform Assoc; 2009; 16(4):531-8. PubMed ID: 19390110
[TBL] [Abstract][Full Text] [Related]
8. Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation.
Russ AL; Zillich AJ; Melton BL; Russell SA; Chen S; Spina JR; Weiner M; Johnson EG; Daggy JK; McManus MS; Hawsey JM; Puleo AG; Doebbeling BN; Saleem JJ
J Am Med Inform Assoc; 2014 Oct; 21(e2):e287-96. PubMed ID: 24668841
[TBL] [Abstract][Full Text] [Related]
9. Prescriber response to computerized drug alerts for electronic prescriptions among hospitalized patients.
Zenziper Straichman Y; Kurnik D; Matok I; Halkin H; Markovits N; Ziv A; Shamiss A; Loebstein R
Int J Med Inform; 2017 Nov; 107():70-75. PubMed ID: 29029694
[TBL] [Abstract][Full Text] [Related]
10. Overrides of medication-related clinical decision support alerts in outpatients.
Nanji KC; Slight SP; Seger DL; Cho I; Fiskio JM; Redden LM; Volk LA; Bates DW
J Am Med Inform Assoc; 2014; 21(3):487-91. PubMed ID: 24166725
[TBL] [Abstract][Full Text] [Related]
11. Medication safety alert fatigue may be reduced via interaction design and clinical role tailoring: a systematic review.
Hussain MI; Reynolds TL; Zheng K
J Am Med Inform Assoc; 2019 Oct; 26(10):1141-1149. PubMed ID: 31206159
[TBL] [Abstract][Full Text] [Related]
12. The influence of computerized decision support on prescribing during ward-rounds: are the decision-makers targeted?
Baysari MT; Westbrook JI; Richardson KL; Day RO
J Am Med Inform Assoc; 2011; 18(6):754-9. PubMed ID: 21676939
[TBL] [Abstract][Full Text] [Related]
13. Optimising interruptive clinical decision support alerts for antithrombotic duplicate prescribing in hospital.
Sundermann M; Clendon O; McNeill R; Doogue M; Chin PKL
Int J Med Inform; 2024 Jun; 186():105418. PubMed ID: 38518676
[TBL] [Abstract][Full Text] [Related]
14. Validity of a clinical decision rule-based alert system for drug dose adjustment in patients with renal failure intended to improve pharmacists' analysis of medication orders in hospitals.
Boussadi A; Caruba T; Karras A; Berdot S; Degoulet P; Durieux P; Sabatier B
Int J Med Inform; 2013 Oct; 82(10):964-72. PubMed ID: 23831104
[TBL] [Abstract][Full Text] [Related]
15. Optimising computerised alerts within electronic medication management systems: A synthesis of four years of research.
Baysari MT; Westbrook JI; Richardson K; Day RO
Stud Health Technol Inform; 2014; 204():1-6. PubMed ID: 25087519
[TBL] [Abstract][Full Text] [Related]
16. Failure to utilize functions of an electronic prescribing system and the subsequent generation of 'technically preventable' computerized alerts.
Baysari MT; Reckmann MH; Li L; Day RO; Westbrook JI
J Am Med Inform Assoc; 2012; 19(6):1003-10. PubMed ID: 22735616
[TBL] [Abstract][Full Text] [Related]
17. Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation.
Kesselheim AS; Cresswell K; Phansalkar S; Bates DW; Sheikh A
Health Aff (Millwood); 2011 Dec; 30(12):2310-7. PubMed ID: 22147858
[TBL] [Abstract][Full Text] [Related]
18. The effect of provider characteristics on the responses to medication-related decision support alerts.
Cho I; Slight SP; Nanji KC; Seger DL; Maniam N; Fiskio JM; Dykes PC; Bates DW
Int J Med Inform; 2015 Sep; 84(9):630-9. PubMed ID: 26004341
[TBL] [Abstract][Full Text] [Related]
19. Identification of strategies to reduce computerized alerts in an electronic prescribing system using a Delphi approach.
Baysari MT; Westbrook JI; Egan B; Day RO
Stud Health Technol Inform; 2013; 192():8-12. PubMed ID: 23920505
[TBL] [Abstract][Full Text] [Related]
20. Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record.
Wright A; Aaron S; Seger DL; Samal L; Schiff GD; Bates DW
J Gen Intern Med; 2018 Nov; 33(11):1868-1876. PubMed ID: 29766382
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]