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DAVID BATES to Decision Support Systems, Clinical

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This is a "connection" page, showing publications DAVID BATES has written about Decision Support Systems, Clinical.
DAVID BATES
Connection Strength
21.395
Decision Support Systems, Clinical
  1. A Calculated Risk: Evaluation of QTc Drug-Drug Interaction (DDI) Clinical Decision Support (CDS) Alerts and Performance of the Tisdale Risk Score Calculator. Drug Saf. 2024 Dec; 47(12):1235-1243.
    View in: PubMed
    Score: 0.708
  2. Using the Electronic Health Record User Context in Clinical Decision Support Criteria. Appl Clin Inform. 2022 08; 13(4):910-915.
    View in: PubMed
    Score: 0.626
  3. Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial. J Am Med Inform Assoc. 2022 07 12; 29(8):1416-1424.
    View in: PubMed
    Score: 0.616
  4. Development of a Perioperative Medication-Related Clinical Decision Support Tool to Prevent Medication Errors: An Analysis of User Feedback. Appl Clin Inform. 2021 10; 12(5):984-995.
    View in: PubMed
    Score: 0.590
  5. Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts. J Am Med Inform Assoc. 2021 06 12; 28(6):1081-1087.
    View in: PubMed
    Score: 0.572
  6. Comparison of Medication Alerts from Two Commercial Applications in the USA. Drug Saf. 2021 06; 44(6):661-668.
    View in: PubMed
    Score: 0.560
  7. Evaluation of a Patient-Centered Fall-Prevention Tool Kit to Reduce Falls and Injuries: A Nonrandomized Controlled Trial. JAMA Netw Open. 2020 11 02; 3(11):e2025889.
    View in: PubMed
    Score: 0.548
  8. The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support. J Am Med Inform Assoc. 2020 08 01; 27(8):1252-1258.
    View in: PubMed
    Score: 0.539
  9. Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence. Ann Intern Med. 2020 06 02; 172(11 Suppl):S137-S144.
    View in: PubMed
    Score: 0.533
  10. High-priority drug-drug interaction clinical decision support overrides in a newly implemented commercial computerized provider order-entry system: Override appropriateness and adverse drug events. J Am Med Inform Assoc. 2020 06 01; 27(6):893-900.
    View in: PubMed
    Score: 0.533
  11. Behavioral Economics Interventions in Clinical Decision Support Systems. Yearb Med Inform. 2018 Aug; 27(1):114-121.
    View in: PubMed
    Score: 0.471
  12. Medication-related clinical decision support alert overrides in inpatients. J Am Med Inform Assoc. 2018 05 01; 25(5):476-481.
    View in: PubMed
    Score: 0.461
  13. Improving medication-related clinical decision support. Am J Health Syst Pharm. 2018 02 15; 75(4):239-246.
    View in: PubMed
    Score: 0.454
  14. Prospective evaluation of medication-related clinical decision support over-rides in the intensive care unit. BMJ Qual Saf. 2018 09; 27(9):718-724.
    View in: PubMed
    Score: 0.454
  15. Comparison of Overridden Medication-related Clinical Decision Support in the Intensive Care Unit between a Commercial System and a Legacy System. Appl Clin Inform. 2017 Aug 23; 8(3):866-879.
    View in: PubMed
    Score: 0.439
  16. Evaluation of medication-related clinical decision support alert overrides in the intensive care unit. J Crit Care. 2017 06; 39:156-161.
    View in: PubMed
    Score: 0.424
  17. Using the Electronic Health Record to Understand and Minimize Overuse. JAMA. 2017 01 17; 317(3):257-258.
    View in: PubMed
    Score: 0.422
  18. Methods for Detecting Malfunctions in Clinical Decision Support Systems. Stud Health Technol Inform. 2017; 245:1385.
    View in: PubMed
    Score: 0.420
  19. Clinical reasoning in the context of active decision support during medication prescribing. Int J Med Inform. 2017 01; 97:1-11.
    View in: PubMed
    Score: 0.412
  20. Analysis of clinical decision support system malfunctions: a case series and survey. J Am Med Inform Assoc. 2016 11; 23(6):1068-1076.
    View in: PubMed
    Score: 0.399
  21. Acceptability and feasibility of the Leapfrog computerized physician order entry evaluation tool for hospitals outside the United States. Int J Med Inform. 2015 Sep; 84(9):694-701.
    View in: PubMed
    Score: 0.376
  22. The effect of provider characteristics on the responses to medication-related decision support alerts. Int J Med Inform. 2015 Sep; 84(9):630-9.
    View in: PubMed
    Score: 0.375
  23. Understanding physicians' behavior toward alerts about nephrotoxic medications in outpatients: a cross-sectional analysis. BMC Nephrol. 2014 Dec 15; 15:200.
    View in: PubMed
    Score: 0.365
  24. Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA. Appl Clin Inform. 2014; 5(2):571-88.
    View in: PubMed
    Score: 0.352
  25. Evaluation of medication alerts in electronic health records for compliance with human factors principles. J Am Med Inform Assoc. 2014 Oct; 21(e2):e332-40.
    View in: PubMed
    Score: 0.349
  26. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc. 2014 May-Jun; 21(3):487-91.
    View in: PubMed
    Score: 0.337
  27. Return on investment for vendor computerized physician order entry in four community hospitals: the importance of decision support. Jt Comm J Qual Patient Saf. 2013 Jul; 39(7):312-8.
    View in: PubMed
    Score: 0.330
  28. Overrides of clinical decision support alerts in primary care clinics. Stud Health Technol Inform. 2013; 192:923.
    View in: PubMed
    Score: 0.319
  29. Understanding responses to a renal dosing decision support system in primary care. Stud Health Technol Inform. 2013; 192:931.
    View in: PubMed
    Score: 0.319
  30. High-priority drug-drug interactions for use in electronic health records. J Am Med Inform Assoc. 2012 Sep-Oct; 19(5):735-43.
    View in: PubMed
    Score: 0.304
  31. Usability of a novel clinician interface for genetic results. J Biomed Inform. 2012 Oct; 45(5):950-7.
    View in: PubMed
    Score: 0.303
  32. Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial. J Am Med Inform Assoc. 2012 Jul-Aug; 19(4):555-61.
    View in: PubMed
    Score: 0.297
  33. Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems--I-MeDeSA. J Am Med Inform Assoc. 2011 Dec; 18 Suppl 1:i62-72.
    View in: PubMed
    Score: 0.291
  34. Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support. J Am Med Inform Assoc. 2011 Jul-Aug; 18(4):479-84.
    View in: PubMed
    Score: 0.284
  35. Commentary: nursing and health information technology. Nurs Outlook. 2008 Sep-Oct; 56(5):237.
    View in: PubMed
    Score: 0.236
  36. Impact of computerized decision support on blood pressure management and control: a randomized controlled trial. J Gen Intern Med. 2008 Apr; 23(4):429-41.
    View in: PubMed
    Score: 0.229
  37. Assessment of education and computerized decision support interventions for improving transfusion practice. Transfusion. 2007 Feb; 47(2):228-39.
    View in: PubMed
    Score: 0.211
  38. Assessing Medication CDS Usability: Pilot Results from 10 Outpatient Clinics. Appl Clin Inform. 2025 08; 16(4):879-891.
    View in: PubMed
    Score: 0.191
  39. Computerized physician order entry and medication errors: finding a balance. J Biomed Inform. 2005 Aug; 38(4):259-61.
    View in: PubMed
    Score: 0.190
  40. Allergy alerting and overrides for opioid analogues across two health systems. BMJ Health Care Inform. 2025 May 25; 32(1).
    View in: PubMed
    Score: 0.188
  41. User Actions within a Clinical Decision Support Alert for the Management of Hypertension in Chronic Kidney Disease. Appl Clin Inform. 2025 05; 16(3):595-603.
    View in: PubMed
    Score: 0.186
  42. A controlled trial of smart infusion pumps to improve medication safety in critically ill patients. Crit Care Med. 2005 Mar; 33(3):533-40.
    View in: PubMed
    Score: 0.185
  43. Development of a drug allergy alert tiering algorithm for penicillins and cephalosporins. Int J Med Inform. 2025 Mar; 195:105789.
    View in: PubMed
    Score: 0.183
  44. Clinical Decision Support for Hypertension Management in Chronic Kidney Disease: A Randomized Clinical Trial. JAMA Intern Med. 2024 May 01; 184(5):484-492.
    View in: PubMed
    Score: 0.175
  45. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc. 2003 Nov-Dec; 10(6):523-30.
    View in: PubMed
    Score: 0.166
  46. Refining Clinical Phenotypes to Improve Clinical Decision Support and Reduce Alert Fatigue: A Feasibility Study. Appl Clin Inform. 2023 05; 14(3):528-537.
    View in: PubMed
    Score: 0.165
  47. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med. 2003 Jun 23; 163(12):1409-16.
    View in: PubMed
    Score: 0.165
  48. A multi-site randomized trial of a clinical decision support intervention to improve problem list completeness. J Am Med Inform Assoc. 2023 04 19; 30(5):899-906.
    View in: PubMed
    Score: 0.163
  49. Multicomponent intervention to improve blood pressure management in chronic kidney disease: a protocol for a pragmatic clinical trial. BMJ Open. 2021 12 22; 11(12):e054065.
    View in: PubMed
    Score: 0.148
  50. Low Efficacy of Medication Shortage Clinical Decision Support Alerts. Appl Clin Inform. 2021 10; 12(5):1144-1149.
    View in: PubMed
    Score: 0.148
  51. How can information technology improve patient safety and reduce medication errors in children's health care? Arch Pediatr Adolesc Med. 2001 Sep; 155(9):1002-7.
    View in: PubMed
    Score: 0.145
  52. National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018. JAMA Netw Open. 2020 05 01; 3(5):e205547.
    View in: PubMed
    Score: 0.132
  53. Evaluation of Harm Associated with High Dose-Range Clinical Decision Support Overrides in the Intensive Care Unit. Drug Saf. 2019 04; 42(4):573-579.
    View in: PubMed
    Score: 0.123
  54. The national cost of adverse drug events resulting from inappropriate medication-related alert overrides in the United States. J Am Med Inform Assoc. 2018 09 01; 25(9):1183-1188.
    View in: PubMed
    Score: 0.118
  55. Clinical decision support alert malfunctions: analysis and empirically derived taxonomy. J Am Med Inform Assoc. 2018 05 01; 25(5):496-506.
    View in: PubMed
    Score: 0.115
  56. Evaluation of 'Definite' Anaphylaxis Drug Allergy Alert Overrides in Inpatient and Outpatient Settings. Drug Saf. 2018 03; 41(3):297-302.
    View in: PubMed
    Score: 0.114
  57. Clinical decision support models and frameworks: Seeking to address research issues underlying implementation successes and failures. J Biomed Inform. 2018 02; 78:134-143.
    View in: PubMed
    Score: 0.112
  58. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces. J Am Med Inform Assoc. 2017 Nov 01; 24(6):1111-1115.
    View in: PubMed
    Score: 0.111
  59. Screening for medication errors using an outlier detection system. J Am Med Inform Assoc. 2017 03 01; 24(2):281-287.
    View in: PubMed
    Score: 0.106
  60. User Requirements for a Chronic Kidney Disease Clinical Decision Support Tool to Promote Timely Referral. Int J Med Inform. 2017 05; 101:50-57.
    View in: PubMed
    Score: 0.106
  61. Recommendations for selecting drug-drug interactions for clinical decision support. Am J Health Syst Pharm. 2016 Apr 15; 73(8):576-85.
    View in: PubMed
    Score: 0.100
  62. Development of an algorithm to assess appropriateness of overriding alerts for nonformulary medications in a computerized prescriber-order-entry system. Am J Health Syst Pharm. 2016 Jan 01; 73(1):e34-45.
    View in: PubMed
    Score: 0.098
  63. Evaluating the Impact of Health IT on Medication Safety. Stud Health Technol Inform. 2016; 222:195-205.
    View in: PubMed
    Score: 0.098
  64. Computerised prescribing for safer medication ordering: still a work in progress. BMJ Qual Saf. 2016 May; 25(5):315-9.
    View in: PubMed
    Score: 0.097
  65. Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals. BMJ Open. 2015 Oct 26; 5(10):e008313.
    View in: PubMed
    Score: 0.097
  66. Provider variation in responses to warnings: do the same providers run stop signs repeatedly? J Am Med Inform Assoc. 2016 Apr; 23(e1):e93-8.
    View in: PubMed
    Score: 0.097
  67. The evolution of the market for commercial computerized physician order entry and computerized decision support systems for prescribing. J Am Med Inform Assoc. 2016 Mar; 23(2):349-55.
    View in: PubMed
    Score: 0.096
  68. Leveraging evidence across the care continuum. Jt Comm J Qual Patient Saf. 2015 Feb; 41(2):87-96.
    View in: PubMed
    Score: 0.092
  69. High Override Rate for Opioid Drug-allergy Interaction Alerts: Current Trends and Recommendations for Future. Stud Health Technol Inform. 2015; 216:242-6.
    View in: PubMed
    Score: 0.091
  70. Clinical decision support systems. Swiss Med Wkly. 2014; 144:w14073.
    View in: PubMed
    Score: 0.091
  71. Using electronic health record clinical decision support is associated with improved quality of care. Am J Manag Care. 2014 Oct 01; 20(10):e445-52.
    View in: PubMed
    Score: 0.090
  72. Evaluation of medium-term consequences of implementing commercial computerized physician order entry and clinical decision support prescribing systems in two 'early adopter' hospitals. J Am Med Inform Assoc. 2014 Oct; 21(e2):e194-202.
    View in: PubMed
    Score: 0.086
  73. Using EHR data to predict hospital-acquired pressure ulcers: a prospective study of a Bayesian Network model. Int J Med Inform. 2013 Nov; 82(11):1059-67.
    View in: PubMed
    Score: 0.083
  74. Computerised decision support systems for healthcare professionals: an interpretative review. Inform Prim Care. 2012; 20(2):115-28.
    View in: PubMed
    Score: 0.074
  75. Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation. Health Aff (Millwood). 2011 Dec; 30(12):2310-7.
    View in: PubMed
    Score: 0.074
  76. Opportunities and challenges in creating an international centralised knowledge base for clinical decision support systems in ePrescribing. BMJ Qual Saf. 2011 Jul; 20(7):625-30.
    View in: PubMed
    Score: 0.071
  77. Governance for clinical decision support: case studies and recommended practices from leading institutions. J Am Med Inform Assoc. 2011 Mar-Apr; 18(2):187-94.
    View in: PubMed
    Score: 0.070
  78. Impact of implementing alerts about medication black-box warnings in electronic health records. Pharmacoepidemiol Drug Saf. 2011 Feb; 20(2):192-202.
    View in: PubMed
    Score: 0.069
  79. The future of health information technology in the patient-centered medical home. Health Aff (Millwood). 2010 Apr; 29(4):614-21.
    View in: PubMed
    Score: 0.066
  80. What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior? J Am Med Inform Assoc. 2009 Jul-Aug; 16(4):531-8.
    View in: PubMed
    Score: 0.062
  81. Creating and sharing clinical decision support content with Web 2.0: Issues and examples. J Biomed Inform. 2009 Apr; 42(2):334-46.
    View in: PubMed
    Score: 0.059
  82. Adverse drug event detection in a community hospital utilising computerised medication and laboratory data. Drug Saf. 2007; 30(9):817-24.
    View in: PubMed
    Score: 0.053
  83. Return on investment for a computerized physician order entry system. J Am Med Inform Assoc. 2006 May-Jun; 13(3):261-6.
    View in: PubMed
    Score: 0.050
  84. Acute infections in primary care: accuracy of electronic diagnoses and electronic antibiotic prescribing. J Am Med Inform Assoc. 2006 Jan-Feb; 13(1):61-6.
    View in: PubMed
    Score: 0.048
  85. Computerized physician order entry with clinical decision support in the long-term care setting: insights from the Baycrest Centre for Geriatric Care. J Am Geriatr Soc. 2005 Oct; 53(10):1780-9.
    View in: PubMed
    Score: 0.048
  86. Performance and improvement strategies for adapting generative large language models for electronic health record applications: A systematic review. Int J Med Inform. 2026 Jan; 205:106091.
    View in: PubMed
    Score: 0.048
  87. A complex ePrescribing antimicrobial stewardship-based (ePAMS+) intervention for hospitals: mixed-methods feasibility trial results. BMC Med Inform Decis Mak. 2024 Oct 11; 24(1):301.
    View in: PubMed
    Score: 0.045
  88. Improving safety with information technology. N Engl J Med. 2003 Jun 19; 348(25):2526-34.
    View in: PubMed
    Score: 0.041
  89. Information technology and medication safety: what is the benefit? Qual Saf Health Care. 2002 Sep; 11(3):261-5.
    View in: PubMed
    Score: 0.039
  90. Artificial intelligence in oncology: Path to implementation. Cancer Med. 2021 06; 10(12):4138-4149.
    View in: PubMed
    Score: 0.036
  91. Effects of computerized physician order entry on prescribing practices. Arch Intern Med. 2000 Oct 09; 160(18):2741-7.
    View in: PubMed
    Score: 0.034
  92. Improving allergy alerting in a computerized physician order entry system. Proc AMIA Symp. 2000; 2-6.
    View in: PubMed
    Score: 0.032
  93. Using information systems to improve practice. Schweiz Med Wochenschr. 1999 Dec 11; 129(49):1913-9.
    View in: PubMed
    Score: 0.032
  94. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc. 1999 Jul-Aug; 6(4):313-21.
    View in: PubMed
    Score: 0.031
  95. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998 Oct 21; 280(15):1311-6.
    View in: PubMed
    Score: 0.030
  96. Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review. J Am Med Inform Assoc. 2018 05 01; 25(5):575-584.
    View in: PubMed
    Score: 0.029
  97. An informatics research agenda to support patient and family empowerment and engagement in care and recovery during and after hospitalization. J Am Med Inform Assoc. 2018 02 01; 25(2):206-209.
    View in: PubMed
    Score: 0.028
  98. High-priority and low-priority drug-drug interactions in different international electronic health record systems: A comparative study. Int J Med Inform. 2018 03; 111:165-171.
    View in: PubMed
    Score: 0.028
  99. The frequency of inappropriate nonformulary medication alert overrides in the inpatient setting. J Am Med Inform Assoc. 2016 09; 23(5):924-33.
    View in: PubMed
    Score: 0.025
  100. A Single-Center Multidisciplinary Initiative to Reduce Catheter-Associated Urinary Tract Infection Rates: Quality and Financial Implications. Health Care Manag (Frederick). 2015 Jul-Sep; 34(3):218-24.
    View in: PubMed
    Score: 0.024
  101. How many medication orders are entered through free-text in EHRs?--a study on hypoglycemic agents. AMIA Annu Symp Proc. 2012; 2012:1079-88.
    View in: PubMed
    Score: 0.020
  102. Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J Am Med Inform Assoc. 2004 Nov-Dec; 11(6):482-91.
    View in: PubMed
    Score: 0.011
  103. Design and implementation of a comprehensive outpatient Results Manager. J Biomed Inform. 2003 Feb-Apr; 36(1-2):80-91.
    View in: PubMed
    Score: 0.010
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The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.