medical order entry systems

Summary

Summary: Information systems, usually computer-assisted, that enable providers to initiate medical procedures, prescribe medications, etc. These systems support medical decision-making and error-reduction during patient care.

Top Publications

  1. Redwood S, Rajakumar A, Hodson J, Coleman J. 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. BMC Med Inform Decis Mak. 2011;11:29 pubmed publisher
  2. Strom B, Schinnar R. Evaluating health information technology's clinical effects. LDI Issue Brief. 2011;16:1-4 pubmed
    ..This rigorous test of a specific CPOE intervention shows that an electronic alert system can be effective in changing prescribing, but may also have unintended consequences for patient safety. ..
  3. Collins C, Elsaid K. Using an enhanced oral chemotherapy computerized provider order entry system to reduce prescribing errors and improve safety. Int J Qual Health Care. 2011;23:36-43 pubmed publisher
    ..CPOE is effective in reducing prescribing errors of oral chemotherapy and should be considered part of a fail-safe process to improve safety. ..
  4. Berdot S, Sabatier B, Gillaizeau F, Caruba T, Prognon P, Durieux P. Evaluation of drug administration errors in a teaching hospital. BMC Health Serv Res. 2012;12:60 pubmed publisher
    ..Medication administration errors are frequent. The identification of its determinants helps to undertake designed interventions. ..
  5. Phansalkar S, Edworthy J, Hellier E, Seger D, Schedlbauer A, Avery A, et al. A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems. J Am Med Inform Assoc. 2010;17:493-501 pubmed publisher
    ..We evaluate the limitations of current alerting philosophies and provide recommendations for improving acceptance of alerts by incorporating human factors principles in their design. ..
  6. Zheng K, Haftel H, Hirschl R, O REILLY M, Hanauer D. Quantifying the impact of health IT implementations on clinical workflow: a new methodological perspective. J Am Med Inform Assoc. 2010;17:454-61 pubmed publisher
    ..Through an empirical study, we demonstrate the potential value of these new methods in enriching workflow analysis in clinical settings. ..
  7. Coleman J, Nwulu U, Ferner R. Decision support for sensible dosing in electronic prescribing systems. J Clin Pharm Ther. 2012;37:415-9 pubmed publisher
    ..This will form a basis for the development of optimal schemes for adding decision support to prescribing systems. ..
  8. Weingart S, Seger A, Feola N, Heffernan J, Schiff G, Isaac T. Electronic drug interaction alerts in ambulatory care: the value and acceptance of high-value alerts in US medical practices as assessed by an expert clinical panel. Drug Saf. 2011;34:587-93 pubmed publisher
    ..The value of electronic drug interaction alerts is influenced heavily by clinicians' judgements about the clinical value of the alert. Expert judgement should be taken into account when developing electronic decision support. ..
  9. Rodríguez González C, Herranz Alonso A, Martin Barbero M, Durán García E, Durango Limarquez M, Hernández Sampelayo P, et al. Prevalence of medication administration errors in two medical units with automated prescription and dispensing. J Am Med Inform Assoc. 2012;19:72-8 pubmed publisher

More Information

Publications62

  1. Zachariah M, Phansalkar S, Seidling H, Neri P, Cresswell K, Duke J, et al. 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;18 Suppl 1:i62-72 pubmed publisher
  2. Day R, Roffe D, Richardson K, Baysari M, Brennan N, Beveridge S, et al. Implementing electronic medication management at an Australian teaching hospital. Med J Aust. 2011;195:498-502 pubmed
  3. Georgiou A, Westbrook J, Braithwaite J. An empirically-derived approach for investigating Health Information Technology: the Elementally Entangled Organisational Communication (EEOC) framework. BMC Med Inform Decis Mak. 2012;12:68 pubmed publisher
    ..The EEOC framework aims to account for the complex range of contextual factors and triggers that play a role in the success or otherwise of new HITs, and in the realisation of their innovation potential. ..
  4. Phansalkar S, van der Sijs H, Tucker A, Desai A, Bell D, Teich J, et al. Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records. J Am Med Inform Assoc. 2013;20:489-93 pubmed publisher
    ..Future efforts might include the development of a consortium to maintain this list over time. Such a list could also be used in conjunction with financial incentives tied to its adoption in EHR. ..
  5. Nerich V, Limat S, DeMarchi M, Borg C, Rohrlich P, Deconinck E, et al. Computerized physician order entry of injectable antineoplastic drugs: an epidemiologic study of prescribing medication errors. Int J Med Inform. 2010;79:699-706 pubmed publisher
    ..Better pharmacist's analysis of prescribing medication order within the CPOE system could possibly minimize duplication of antineoplasic drugs and the vital clinical impact associated with overdosage. ..
  6. Ferner R, Coleman J. An algorithm for integrating contraindications into electronic prescribing decision support. Drug Saf. 2010;33:1089-96 pubmed publisher
    ..However, most contraindications relate to co-morbid conditions, and prescribing systems will only be able to display these in context if they have access to relevant clinical data. ..
  7. Bhardwaja B, Carroll N, Raebel M, Chester E, Korner E, Rocho B, et al. Improving prescribing safety in patients with renal insufficiency in the ambulatory setting: the Drug Renal Alert Pharmacy (DRAP) program. Pharmacotherapy. 2011;31:346-56 pubmed publisher
    ..The DRAP program was successful in reducing medication errors for patients with renal insufficiency in an ambulatory setting and was demonstrated to have sustainability after study completion. ..
  8. Nanji K, Rothschild J, Salzberg C, Keohane C, Zigmont K, Devita J, et al. Errors associated with outpatient computerized prescribing systems. J Am Med Inform Assoc. 2011;18:767-73 pubmed publisher
    ..The authors offer targeted recommendations on improving computerized prescribing systems to prevent errors. ..
  9. Leung A, Keohane C, Amato M, Simon S, Coffey M, Kaufman N, et al. Impact of vendor computerized physician order entry in community hospitals. J Gen Intern Med. 2012;27:801-7 pubmed publisher
    ..Our findings support the use of vendor CPOE systems as a means to reduce drug-related injury and harm. The potential ADE rate could be reduced by making refinements to the vendor applications and their associated decision support. ..
  10. Swanson Kazley A, Diana M. Hospital computerized provider order entry adoption and quality: An examination of the United States. Health Care Manage Rev. 2011;36:86-94 pubmed publisher
    ..Universal gains in quality are not guaranteed with CPOE adoption. ..
  11. Magrabi F, Li S, Day R, Coiera E. Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects. J Am Med Inform Assoc. 2010;17:575-83 pubmed publisher
    ..Further experiments are required to rule out any effect interruption might have on CPOE error rates. ..
  12. Longhurst C, Parast L, Sandborg C, Widen E, Sullivan J, Hahn J, et al. Decrease in hospital-wide mortality rate after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2010;126:14-21 pubmed publisher
    ..Implementation of a locally modified, commercially sold CPOE system was associated with a statistically significant reduction in the hospital-wide mortality rate at a quaternary care academic children's hospital. ..
  13. Singh D, Spiers S, Beasley B. Characteristics of CPOE systems and obstacles to implementation that physicians believe will affect adoption. South Med J. 2011;104:418-21 pubmed publisher
    ..1%). The majority of physicians believed CPOE would lead to a reduction of medical errors and more efficient patient care. However, physicians are highly concerned with how CPOE will affect their own work efficiency. ..
  14. Baysari M, Reckmann M, Li L, Day R, Westbrook J. Failure to utilize functions of an electronic prescribing system and the subsequent generation of 'technically preventable' computerized alerts. J Am Med Inform Assoc. 2012;19:1003-10 pubmed publisher
    ..Ongoing user training to support effective use of e-prescribing system functions and modifications to the mechanisms underlying alert generation are needed to ensure that prescribers are presented with fewer but more meaningful alerts. ..
  15. Kesselheim A, Cresswell K, Phansalkar S, Bates D, Sheikh A. Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation. Health Aff (Millwood). 2011;30:2310-7 pubmed publisher
    ..Even so, to limit liability in this area, we recommend stronger government regulation of clinical decision support systems and development of international practice guidelines highlighting the most important warnings. ..
  16. McKibbon K, Lokker C, Handler S, Dolovich L, Holbrook A, O Reilly D, et al. The effectiveness of integrated health information technologies across the phases of medication management: a systematic review of randomized controlled trials. J Am Med Inform Assoc. 2012;19:22-30 pubmed publisher
    ..This large body of literature, although instructive, is not uniformly distributed across settings, people, medication phases, or outcomes. ..
  17. Georgiou A, Prgomet M, Markewycz A, Adams E, Westbrook J. The impact of computerized provider order entry systems on medical-imaging services: a systematic review. J Am Med Inform Assoc. 2011;18:335-40 pubmed publisher
  18. Georgiou A, Westbrook J, Braithwaite J. Time matters--a theoretical and empirical examination of the temporal landscape of a hospital pathology service and the impact of e-health. Soc Sci Med. 2011;72:1603-10 pubmed publisher
    ..The use of qualitative methods longitudinally provided key insights into the way that temporal factors operate within pathology laboratories and their interrelationship with the performance, distribution and allocation of work. ..
  19. McCoy A, Waitman L, Lewis J, Wright J, Choma D, Miller R, et al. A framework for evaluating the appropriateness of clinical decision support alerts and responses. J Am Med Inform Assoc. 2012;19:346-52 pubmed publisher
    ..More work can determine the generalizability of the framework for use in other settings and other alert types. ..
  20. Phansalkar S, Desai A, Bell D, Yoshida E, Doole J, Czochanski M, et al. High-priority drug-drug interactions for use in electronic health records. J Am Med Inform Assoc. 2012;19:735-43 pubmed publisher
    ..A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list. ..
  21. Scott G, Shah P, Wyatt J, Makubate B, Cross F. Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors. J Am Med Inform Assoc. 2011;18:789-98 pubmed publisher
    ..This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes. ..
  22. Andersson M, Bottiger Y, Lindh J, Wettermark B, Eiermann B. Impact of the drug-drug interaction database SFINX on prevalence of potentially serious drug-drug interactions in primary health care. Eur J Clin Pharmacol. 2013;69:565-71 pubmed publisher
    ..Further studies are needed to demonstrate the effectiveness of drug-drug interaction warning systems. ..
  23. Jaspers M, Smeulers M, Vermeulen H, Peute L. Effects of clinical decision-support systems on practitioner performance and patient outcomes: a synthesis of high-quality systematic review findings. J Am Med Inform Assoc. 2011;18:327-34 pubmed publisher
    ..These outcomes may be explained by the fact that these types of CDSS require a minimum of patient data that are largely available before the advice is (to be) generated: at the time clinicians make the decisions. ..
  24. Georgiou A, Prgomet M, Paoloni R, Creswick N, Hordern A, Walter S, et al. The effect of computerized provider order entry systems on clinical care and work processes in emergency departments: a systematic review of the quantitative literature. Ann Emerg Med. 2013;61:644-653.e16 pubmed publisher
    ..Multimethod research approaches (including qualitative research) can contribute to understanding of the multiple dimensions of ED care delivery, not as separate entities but as essential components of a highly integrated system of care. ..
  25. Riedmann D, Jung M, Hackl W, Stühlinger W, van der Sijs H, Ammenwerth E. Development of a context model to prioritize drug safety alerts in CPOE systems. BMC Med Inform Decis Mak. 2011;11:35 pubmed publisher
    ..The outcome of this work can be used to develop future tailored drug safety alerting in CPOE systems. ..
  26. Baysari M, Westbrook J, Richardson K, Day R. The influence of computerized decision support on prescribing during ward-rounds: are the decision-makers targeted?. J Am Med Inform Assoc. 2011;18:754-9 pubmed publisher
    ..If confirmed, the findings reported here present a specific focus and user group for designers of medication decision support. ..
  27. Taylor J, Loan L, Kamara J, Blackburn S, Whitney D. Medication administration variances before and after implementation of computerized physician order entry in a neonatal intensive care unit. Pediatrics. 2008;121:123-8 pubmed publisher
    ..However, even with the use of computerized physician order entry, variances were noted for >11% of all medication administrations, which suggests that additional methods may be needed to improve neonatal patient safety. ..
  28. van der Sijs H, Aarts J, van Gelder T, Berg M, Vulto A. Turning off frequently overridden drug alerts: limited opportunities for doing it safely. J Am Med Inform Assoc. 2008;15:439-48 pubmed publisher
  29. Hollingworth W, Devine E, Hansen R, Lawless N, Comstock B, Wilson Norton J, et al. The impact of e-prescribing on prescriber and staff time in ambulatory care clinics: a time motion study. J Am Med Inform Assoc. 2007;14:722-30 pubmed
    ..4 minutes/hour; 0.0, 10.7 CI). E-prescribing was not associated with an increase in combined computer and writing time for prescribers. If carefully implemented, e-prescribing will not greatly disrupt workflow. ..
  30. Luna D, Otero V, Canosa D, Montenegro S, Otero P, de Quiros F. Analysis and redesign of a knowledge database for a drug-drug interactions alert system. Stud Health Technol Inform. 2007;129:885-9 pubmed
  31. Franklin B, O Grady K, Donyai P, Jacklin A, Barber N. The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study. Qual Saf Health Care. 2007;16:279-84 pubmed
    ..Time spent on medication-related tasks increased. ..
  32. Crosson J, Isaacson N, Lancaster D, McDonald E, Schueth A, DiCicco Bloom B, et al. Variation in electronic prescribing implementation among twelve ambulatory practices. J Gen Intern Med. 2008;23:364-71 pubmed publisher
    ..Practice leaders should plan implementation carefully, ensuring that practice members prepare for the effective integration of this technology into clinical workflow. ..
  33. Classen D, Avery A, Bates D. Evaluation and certification of computerized provider order entry systems. J Am Med Inform Assoc. 2007;14:48-55 pubmed
    ..The increasing role of CPOE systems in health care has invited much more scrutiny about the effectiveness of these systems in actual practice which has the potential to improve their ultimate performance. ..
  34. Callen J, Westbrook J, Braithwaite J. The effect of physicians' long-term use of CPOE on their test management work practices. J Am Med Inform Assoc. 2006;13:643-52 pubmed
    ..In the current mixed media environment, physicians' use of manual and computerized information systems for sourcing and recording information impacts on efficiency and patient safety. ..
  35. Georgiou A, Ampt A, Creswick N, Westbrook J, Braithwaite J. Computerized Provider Order Entry--what are health professionals concerned about? A qualitative study in an Australian hospital. Int J Med Inform. 2009;78:60-70 pubmed publisher
    ..Acknowledging and addressing people's concerns can contribute to the establishment of durable channels of negotiation and communication. Further research informed by the findings of this study will help advance this process. ..
  36. Khajouei R, Jaspers M. The impact of CPOE medication systems' design aspects on usability, workflow and medication orders: a systematic review. Methods Inf Med. 2010;49:3-19 pubmed publisher
    ..This paper provides general recommendations for CPOE (re)design based on the characteristics of CPOE design aspects found. ..
  37. van der Sijs H, Lammers L, van den Tweel A, Aarts J, Berg M, Vulto A, et al. Time-dependent drug-drug interaction alerts in care provider order entry: software may inhibit medication error reductions. J Am Med Inform Assoc. 2009;16:864-8 pubmed publisher
  38. Beuscart R, McNair P, Brender J. Patient safety through intelligent procedures in medication: the PSIP project. Stud Health Technol Inform. 2009;148:6-13 pubmed
    ..This knowledge will be implemented in a PSIP-Platform independent of existing ICT applications. ..
  39. Aarts J, Ash J, Berg M. Extending the understanding of computerized physician order entry: implications for professional collaboration, workflow and quality of care. Int J Med Inform. 2007;76 Suppl 1:S4-13 pubmed
  40. Walsh K, Landrigan C, Adams W, Vinci R, Chessare J, Cooper M, et al. Effect of computer order entry on prevention of serious medication errors in hospitalized children. Pediatrics. 2008;121:e421-7 pubmed publisher
    ..Several human-machine interface problems, particularly surrounding selection and dosing of pediatric medications, were identified. Additional refinements could lead to greater effects on error rates. ..
  41. Grimsmo A. [Electronic prescriptions--without side-effects?]. Tidsskr Nor Laegeforen. 2006;126:1740-3 pubmed
    ..New systems have to be thoroughly tested and evaluated as closely as other new technology and drugs when implemented. ..
  42. Zhan C, Hicks R, Blanchette C, Keyes M, Cousins D. Potential benefits and problems with computerized prescriber order entry: analysis of a voluntary medication error-reporting database. Am J Health Syst Pharm. 2006;63:353-8 pubmed
    ..However, it may provide valuable information on the specific types of errors related to CPOE systems. ..
  43. Voeffray M, Pannatier A, Stupp R, Fucina N, Leyvraz S, Wasserfallen J. Effect of computerisation on the quality and safety of chemotherapy prescription. Qual Saf Health Care. 2006;15:418-21 pubmed
    ..Errors in chemotherapy prescription nearly disappeared after implementation of CPOE. The safety of chemotherapy prescription was markedly improved. ..
  44. Shulman R, Singer M, Goldstone J, Bellingan G. Medication errors: a prospective cohort study of hand-written and computerised physician order entry in the intensive care unit. Crit Care. 2005;9:R516-21 pubmed
    ..Moderate and major errors, however, remain a significant concern with CPOE. ..
  45. Westbrook J, Braithwaite J, Georgiou A, Ampt A, Creswick N, Coiera E, et al. Multimethod evaluation of information and communication technologies in health in the context of wicked problems and sociotechnical theory. J Am Med Inform Assoc. 2007;14:746-55 pubmed
  46. Grizzle A, Mahmood M, Ko Y, Murphy J, Armstrong E, Skrepnek G, et al. Reasons provided by prescribers when overriding drug-drug interaction alerts. Am J Manag Care. 2007;13:573-8 pubmed
    ..This brings into question how computerized physician order entry systems should be designed. ..
  47. Wolfstadt J, Gurwitz J, Field T, Lee M, Kalkar S, Wu W, et al. The effect of computerized physician order entry with clinical decision support on the rates of adverse drug events: a systematic review. J Gen Intern Med. 2008;23:451-8 pubmed publisher
    ..Few studies have measured the effect of CPOE with CDS on the rates of ADEs, and none were randomized controlled trials. Further research is needed to evaluate the efficacy of CPOE with CDS across the various clinical settings. ..
  48. Tamblyn R, Huang A, Taylor L, Kawasumi Y, Bartlett G, Grad R, et al. A randomized trial of the effectiveness of on-demand versus computer-triggered drug decision support in primary care. J Am Med Inform Assoc. 2008;15:430-8 pubmed publisher
    ..New strategies are needed to maximize the use of drug decision support systems to reduce drug-related morbidity. ..
  49. Gurwitz J, Field T, Rochon P, Judge J, Harrold L, Bell C, et al. Effect of computerized provider order entry with clinical decision support on adverse drug events in the long-term care setting. J Am Geriatr Soc. 2008;56:2225-33 pubmed publisher
    ..Alert burden, limited scope of the alerts, and a need to more fully integrate clinical and laboratory information may have affected efficacy. ..
  50. Schedlbauer A, Prasad V, Mulvaney C, Phansalkar S, Stanton W, Bates D, et al. What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior?. J Am Med Inform Assoc. 2009;16:531-8 pubmed publisher
    ..None of the studies evaluated features that might make alerts and prompts more effective. Details of an updated search run in Jan 2009 are included in the supplement section of this review. ..
  51. Seidling H, Schmitt S, Bruckner T, Kaltschmidt J, Pruszydlo M, Senger C, et al. Patient-specific electronic decision support reduces prescription of excessive doses. Qual Saf Health Care. 2010;19:e15 pubmed publisher
    ..During the 90-day study, implementation of a highly specific algorithm-based CDSS substantially improved prescribing quality with a high acceptance rate compared with previous studies. ..
  52. Jha A, Laguette J, Seger A, Bates D. Can surveillance systems identify and avert adverse drug events? A prospective evaluation of a commercial application. J Am Med Inform Assoc. 2008;15:647-53 pubmed publisher
    ..A commercially available, computer-based ADE detection tool was effective at identifying ADEs. When used as part of an active surveillance program, it can have an impact on preventing or ameliorating ADEs. ..
  53. Chaffee B, Zimmerman C. Developing and implementing clinical decision support for use in a computerized prescriber-order-entry system. Am J Health Syst Pharm. 2010;67:391-400 pubmed publisher