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Principles of Electronic Prescribing pp 69–95Cite as

EP Systems as a Risk Management Tool

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Abstract

The practice of medicine is an inherently risky activity. It is to be hoped that many therapeutic interventions are beneficial when used in the appropriate clinical situation. However, the majority of medical treatment interventions – and indeed some diagnostic or monitoring interventions – carry with them an element of risk. An important aspect of the healthcare professional’s job is risk management – to evaluate the risks associated with any particular therapeutic or diagnostic intervention and to follow working practices that reduce the risks involved. The clinical professional evaluates risk on the basis of documented evidence, together with clinical judgment, arising from his or her own professional experience.

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Notes

  1. 1.

    Concordance is the principle of a patient taking a course of treatment. Concordance is distinct from the notion of compliance, which suggests that the patient takes the treatment in order to follow the clinician’s instructions and without full commitment to the beneficial possibilities of the treatment.

References

  1. Bates DW, Gawande AA. Improving Safety with Information Technology. N Engl J Med. 2003;348:2525–34.

    Article  Google Scholar 

  2. Reason J. Human Error: Models and Management. Br Med J. 2000;320:768–70.

    Article  CAS  Google Scholar 

  3. Bates DW, Leape L, et al. Effect of Computerised Physician Order Entry and a Team Intervention on Prevention of Serious Medication Errors. J Am Med Assoc. 1998;280:1311–6.

    Article  CAS  Google Scholar 

  4. Bates DW, Teich JM, et al. The impact of computerised physician order entry on medication error prevention. J Am Med Inform Assoc. 1999;6:313–21.

    Article  PubMed  CAS  Google Scholar 

  5. Bobb A, Gleason K, et al. The epidemiology of prescribing errors: the potential impact of computerised physician order entry. Arch Intern Med. 2004;164:785–92.

    Article  PubMed  Google Scholar 

  6. Stone WM, Smith BE, Shaft JD, Nelson RD, Money SR. Impact of a computerised physician order entry system. J Am Coll Surg. 2009;208:960–7.

    Article  PubMed  Google Scholar 

  7. Nebeker J, Hoffman JM, et al. High Rates of Adverse Drug Events in a Highly Computerised Hospital. Arch Intern Med. 2005;165:1111–6.

    Article  PubMed  Google Scholar 

  8. Dodd C. Assessing pharmacy interventions at Salisbury Healthcare NHS Trust. Hosp Pharm. 2003;10:451–6.

    Google Scholar 

  9. Farrar K. Accountability, prescribing and hospital pharmacy in an electronic, automated age. Pharm J. 1999;263:496–501.

    Google Scholar 

  10. Farrar K. In: Smith J, editor. Building a safer NHS for patients: improving medication safety. London: Department of Health; August 2004.

    Google Scholar 

  11. Fowlie F, Bennie M, et al. Evaluation of an electronic prescribing and administration system in a British Hospital. Pharm J. 2000;265(Suppl):R16.

    Google Scholar 

  12. Shulman R, Singer M, et al. Medication errors: a prospective cohort study of handwritten and computerised physician order entry in the intensive care unit. Crit Care. 2005;9:R516–21.

    Article  PubMed  Google Scholar 

  13. Franklin BD, O’Grady K, et al. 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.

    Article  PubMed  Google Scholar 

  14. Beard R, Candlish C. Does Electronic Prescribing contribute to Clinical Governance? Br J Healthc Comput. 2004;21:27–9.

    Google Scholar 

  15. Abdel Qader DH, Harper L, Cantrill JA, Tully MP. Pharmacists’ interventions in prescribing errors at hospital discharge: an observational study in the context of an electronic prescribing system in a UK teaching hospital. Drug Saf. 2010;33:1027–44.

    Article  PubMed  Google Scholar 

  16. Van Doormaal JE, van den Bemt PM, et al. The influence that electronic prescribing has on medication errors and preventable adverse drug events: an interrupted time-series study. J Am Med Inform Assoc. 2009;16:816–25.

    Article  PubMed  Google Scholar 

  17. Bonnabry P, Despont-Gros C, et al. A risk analysis method to evaluate the impact of a computerised provider order entry system on patient safety. J Am Med Inform Assoc. 2008;15:453–60.

    Article  PubMed  Google Scholar 

  18. Barber N. Electronic Prescribing – Safer, Faster, Better? J Health Serv Res Policy. 2010;15 Suppl 1:64–7.

    Article  PubMed  Google Scholar 

  19. Ghaleb MA, Barber N, et al. The incidence and nature of prescribing and medication administration errors in paediatric inpatients. Arch Dis Child. 2010;95:113–8.

    Article  PubMed  Google Scholar 

  20. Jani YH, Ghaleb MA, et al. Electronic prescribing reduced prescribing errors in a pediatric renal outpatient clinic. J Pediatr. 2008;152:214–8.

    Article  PubMed  Google Scholar 

  21. Warrick C, Naik H, Avis S, Fletcher P, Franklin BD, Inwald D. A clinical information system reduced medication errors in paediatric intensive care. Intensive Care Med. 2011;37:691–4.

    Article  PubMed  Google Scholar 

  22. Kazemi A, Fors UG, Tofighi S, Tessma M, Ellenius J. Physician order entry or nurse order entry? Comparison of two implementation strategies for computerised order entry system aimed at reducing dosing medication errors. J Med Internet Res. 2010;12:e5.

    Article  PubMed  Google Scholar 

  23. Holdsworth MT, Fichtl RE, et al. Impact of computerized prescriber order entry on the incidence of adverse drug events in pediatric inpatients. Pediatrics. 2007;120:1058–66.

    Article  PubMed  Google Scholar 

  24. Jani YH, Barber N, Wong IC. Paediatric dosing errors before and after electronic prescribing. Qual Saf Health Care. 2010;19:337–40.

    Article  PubMed  Google Scholar 

  25. Audit Commission. A spoonful of sugar – medicines management in NHS hospitals. London: Audit Commission; 2001.

    Google Scholar 

  26. Beard R, Candlish C. Is electronic prescribing the best system for preventing pharmacy dispensing errors Br. J Healthc Comput. 2007;24:15–8.

    Google Scholar 

  27. Adcock H. European Association of Hospital Pharmacy Congress: RFID raises issues associated with privacy and data collision. Hosp Pharm. 2006;13:138.

    Google Scholar 

  28. Spencer DC, Leininger A, et al. Effect of a computerised prescriber order entry system on reported medication errors. Am J Health Syst Pharm. 2005;62:416–9.

    PubMed  Google Scholar 

  29. Koppel R, Metlay JD, et al. Role of computerised physician order entry systems in faciliating medical errors. J Am Med Assoc. 2005;293:1197–203.

    Article  CAS  Google Scholar 

  30. Flebbe E, Jensen T, Andersen P. Does electronic medicine prescription cause new types of errors? Ugeskr Laeger. 2009;171:2260–4.

    PubMed  Google Scholar 

  31. Magrabi F, Li SY, Day RO, 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.

    Article  PubMed  Google Scholar 

  32. Reckmann MH, Westbrook JI, Koh Y, Lo C, Day RO. Does computerised provider order entry reduce prescribing errors for hospital inpatients? A systematic review. J Am Med Inform Assoc. 2009;16:613–23.

    Article  PubMed  Google Scholar 

  33. Gray S, Smith J. Practice report – electronic prescribing in Bristol. Healthc Pharm. 2004; August:20–2.

    Google Scholar 

  34. Hunteman L, Ward L, et al. Analysis of allergy alerts within a computerised prescriber order entry system. Am J Health Syst Pharm. 2009;66:373–7.

    Article  PubMed  Google Scholar 

  35. Nightingale PG, Adu D, Richards NT, Peters M. Implementation of rules-based computerised bedside prescribing and administration: intervention study. Br Med J. 2000;320:750–3.

    Article  CAS  Google Scholar 

  36. Strom BL, Schinnar R, Aberra F, Bilker W, Hennessy S, Leonard CE, Pifer E. Unintended effects of a computerised physician order entry nearly hard stop alert to prevent a drug interaction. Arch Intern Med. 2010;170:1578–83.

    Article  PubMed  Google Scholar 

  37. Ferner RE, Coleman JJ. An algorithm for integrating contraindications into electronic prescribing decision support. Drug Saf. 2010;33:1089–96.

    Article  PubMed  Google Scholar 

  38. Seidling HM, Schmitt SP, Bruckner T, Kaltschmidt J, Pruszydlo MG, Senger C, Bertsche T, Walter-Sack I, Haefeli WE. Patient specific electronic decision support reduces prescription of excessive doses. Qual Saf Health Care. 2010;19:E15.

    PubMed  CAS  Google Scholar 

  39. Ross SM, Papshev D, Murphy EL, Sternberg DJ, Taylor J, Barg R. Effects of electronic ­prescribing on formulary compliance and generic drug utilisation in the ambulatory care setting: a retrospective analysis of administrative claims data. J Manag Care Pharm. 2005;11:418–9.

    Google Scholar 

  40. Went K, Antoniewicz P, et al. Reducing prescribing errors: can a well-designed electronic system help? J Eval Clin Pract. 2010;16:556–9.

    PubMed  Google Scholar 

  41. Fischer MA, Vogeli C, et al. Effect of electronic prescribing with formulary decision support on medication use and cost. Arch Intern Med. 2008;168:2433–9.

    Article  PubMed  Google Scholar 

  42. Stenner SP, Chen Q, Johnson KB. Impact of generic substitution decision support on electronic prescribing behaviour. J Am Med Inform Assoc. 2010;17:681–8.

    Article  PubMed  Google Scholar 

  43. Teich JM, et al. Effects of computerised physician order entry on prescribing practices. Arch Intern Med. 2000;160(18):2741–7.

    Article  PubMed  CAS  Google Scholar 

  44. Hunt DL, Haynes B, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. J Am Med Assoc. 1998;280(15):1339–46.

    Article  CAS  Google Scholar 

  45. Evans RS, Pestotnik SL, Classen DC. A computer-assisted management program for antibiotics and other antiinfective agents. N Eng J Med. 1998;338:232–8.

    Article  CAS  Google Scholar 

  46. Clemens E, Cutler T, et al. Prescriber non-compliance with a new computerised insulin ­guideline for non critically ill adults. Ann Pharmacother. 2011.http://www.ncbi.nlm.nih.gov/pubmed?term=Clemens%20compliance%20insulin. Accessed in May 2012.

  47. Bourgeois FC, Linder J, et al. Impact of a computerized template on antibiotic prescribing for acute respiratory infections in children and adolescents. Clin Pediatr (Phila). 2010;49:976–83.

    Article  Google Scholar 

  48. Papaioannou A, Kennedy CC, et al. A team-based approach to warfarin management in long term care: a feasibility study of the MEDeINR electronic decision support system. BMC Geriatr. 2010;10:38.

    Google Scholar 

  49. Trafton JA, Martins SB, et al. Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain. Implement Sci. 2010;5:26.

    Article  PubMed  Google Scholar 

  50. Milner KK, Healy D, et al. State mental health policy: implementation of computerized medication prescribing algorithms in a community mental health system. Psychiatr Serv. 2009;60:1010–2.

    Article  PubMed  Google Scholar 

  51. Tang MB, Tan ES, et al. Electronic e-isotretinoin prescription chart: improving physicians’ adherence to isotretinoin prescription guidelines. Australas J Dermatol. 2009;50:107–12.

    Google Scholar 

  52. Field TS, Rochon P, et al. Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency. J Am Med Inform Assoc. 2009;16:480–5.

    Article  PubMed  Google Scholar 

  53. Lesprit P, Duong T, et al. Impact of a computer-generated alert system prompting review of antibiotic use in hospitals. J Antimicrob Chemother. 2009;63:1058–63.

    Article  PubMed  CAS  Google Scholar 

  54. Buising KL, Thursky KA, et al. Electronic antibiotic stewardship—reduced consumption of broad-spectrum antibiotics using a computerized antimicrobial approval system in a hospital setting. J Antimicrob Chemother. 2008;62:608–16.

    Article  PubMed  CAS  Google Scholar 

  55. Cooley T. Presented at the Guild of Healthcare Pharmacists & UK Clinical Pharmacy Association Joint Conference 2009. Clin Pharm. 2009;1:291.

    Google Scholar 

  56. Teich JM, Osheroff JA, Pifer EA, The CDS Expert Review Panel. Clinical Decision Support in Electronic Prescribing: Recommendations and an Action Plan. J Am Med Inform Assoc. 2005;12:365–76.

    Article  PubMed  Google Scholar 

  57. Wang CJ, Marken RS, Meili RC, et al. Functional characteristics of electronic prescribing systems: a field study. J Am Med Inform Assoc. 2005;12:346–56.

    Article  PubMed  Google Scholar 

  58. Miller RA, Gardner RM, Johnson KB, Hripcsak G. Clinical Decision Support and Electronic Prescribing Systems: A Time for Responsible Thought and Action. J Am Med Inform Assoc. 2005;12:403–9.

    Article  PubMed  Google Scholar 

  59. Ammenwerth E, Schnell-Inderst P, et al. The effect of electronic prescribing on medication errors and adverse drug events: a systematic review. J Am Med Inform Assoc. 2008;15:585–600.

    Article  PubMed  Google Scholar 

  60. Summers V. Association of Scottish Chief Pharmacists. Electronic Prescribing – the way ­forward. Pharm J. 2000;265:834.

    Google Scholar 

  61. Trent Rosenbloom S. Approaches to evaluating electronic prescribing. J Am Med Inform Assoc. 2006;13:399–401.

    Article  PubMed  Google Scholar 

  62. Savage I, Cornford T, Klecun E, Barber N, Clifford S, Franklin BD. Medication errors with ­electronic prescribing (EP): Two views of the same picture. BMC Health Serv Res. 2010;10:135.

    Article  PubMed  Google Scholar 

  63. Green C. Look to the future and see the opportunities. Clin Pharm. 2011;3:34.

    Google Scholar 

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Authors and Affiliations

  1. Cert Clin Pharm, MRPharmS, SGS PharmaSolutions, Chedworth, Gloucestershire, UK

    Stephen Goundrey-Smith MSc

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  1. Stephen Goundrey-Smith MSc
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© 2012 Springer-Verlag London

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Goundrey-Smith, S. (2012). EP Systems as a Risk Management Tool. In: Principles of Electronic Prescribing. Health Informatics. Springer, London. https://doi.org/10.1007/978-1-4471-4045-0_4

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  • DOI: https://doi.org/10.1007/978-1-4471-4045-0_4

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