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Published on 1 July 2004

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Using IT for medication safety: an introduction

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Rainu Kaushal
MD MPH
Brigham and Women’s Hospital and Harvard Medical School
Boston, MA
Department of Public Health
Cornell Weill Medical College
Ithaca, NY
USA
E:rkaushal@partners.org

Research in several countries has documented the problem of medical errors and their associated injuries.(1–4) In the state of New York, the 1984 Harvard Medical Practice Study (MPS) found that 3.7% of inpatients suffered needless harm during their hospitalisation from their medical care.(1) Medications were the most common cause of these injuries, accounting for nearly 20%. Importantly, 69% of all injuries were judged to be preventable.

Several studies have further documented the frequency and consequences of medication errors and adverse drug events (ADEs) in hospitalised adults.(5–11) Medication errors are defined as any mistake in the medication use process from ordering, transcribing, dispensing, administering or monitoring, while ADEs are actual harm resulting from medication use. Only about one-third of ADEs are caused by errors, while many are nonpreventable.

The Adverse Drug Event Prevention Study found 6.5 ADEs per 100 adult admissions.(5) Other studies documented the significant cost and clinical consequences of ADEs.(7,8) Medication errors were even more common, at a rate of 5 per 100 medication orders or 1.4 per admission.(9) Of these errors, 7 in 100 posed significant potential for patient harm.(10) A paediatric study documented that children were at similar risk for medication errors, but at a threefold higher risk of potentially harmful errors compared with adults.(11) Even though 75% of office visits to general practitioners and internists in the USA involve medication prescribing,(12) much less is known about errors in this setting. A recent study found that 24% of patients reported an ADE, of which 11% were preventable and 28% were ameliorable.(13) Another study in New Zealand found that 31.5% of patients recently discharged from a hospital reported an ADE.(14)

This review includes the major IT modalities that have been demonstrated to improve medication safety. It focuses on the US experience, although international literature exists regarding IT and medication safety, as the basic principles remain the same regardless of the healthcare setting.

Medication error prevention: the systems approach
Widespread experience from many fields, including the aviation industry, demonstrates that error proofing is most effectively targeted towards changing a system as errors most commonly result from limitations of human performance in complex environments without sufficient checks.(15–20) Many steps are required to create safer patient environments, beginning with the creation of a blame-free organisational culture focused on safety. IT can then be introduced to simplify and standardise the system, often intercepting errors before they reach the patient.

Medication error and ADE detection
A first step in preventing medication errors is detecting and characterising their epidemiology. Most data regarding medication errors have relied on spontaneous reporting, which detects only a small number of ADEs and an even smaller number of medication errors. The most comprehensive data on the epidemiology of medication errors and ADEs come from chart review studies. However, these studies are very expensive and time-consuming, precluding use as a routine monitoring strategy. IT can be utilised to routinely monitor for ADEs.(21) ADE monitors and natural language processing are particularly effective. The former are information systems that detect ADEs based on triggers such as the high serum drug levels or the use of an antidote,(22,23) while the latter are information systems that search electronic data for terms that suggest an adverse event.(24)

Medication error prevention and IT
A variety of information technologies have the potential to reduce the frequency of medication errors, including computerised physician order entry (CPOE) with clinical decision support systems (CDSS), computerised medication administration records, robots, automated pharmacy systems, barcoding, “smart” intravenous devices, computerised discharge prescriptions and instructions, and personalised web pages.

Computerised physician order entry (CPOE)
Since many errors occur at the stage of drug ordering, automating this process is an effective technique to reduce errors. CPOE allows orders to be entered electronically rather than by hand, thereby ensuring that they are standardised, complete and legible. Most systems are combined with computerised decision support of some variety. Such decision support can check for issues such as drug dose, route, frequency, drug interactions and allergies. Ideally, CPOE is part of an electronic health record with computerised laboratory and radiological systems, to allow more elements of electronic decision support. CDSS can also provide feedback about appropriateness and costs of medications and tests, operationalise clinical pathways and improve quality measurement, coding and billing. CPOE has been demonstrated to decrease medication errors by 83% at Brigham and Women’s Hospital (Boston, MA).(25)

Clinical decision support systems (CDSS)
CDSS can be implemented as part of CPOE or as standalone interventions. Sophisticated CDSS may incorporate patient- or pathogen-specific information and provide advice to physicians, such as the LDS Hospital antibiotic assistant.(26,27) After using the stand-alone CDSS, the physician handwrites an order. One LDS study demonstrated a 70% decrease in antibiotic-associated ADEs after the implementation of this CDSS.(27)

Computerisation of the medication administration record
The transcribing stage is another process susceptible to medication errors. Ideally, CPOE can be combined with a computerised medication administration record, thereby greatly decreasing medication errors. An important attribute of such systems is cumulative dose checking, especially for drugs such as chemotherapeutics or narcotics that are administered on a per-need basis.

Automated dispensing
Robots can be used to perform simple, routine tasks such as recognising medications through barcodes or delivering medications to the intensive care unit in a timely manner.
A robot decreased dispensing errors from 2.9 to 0.6% in one adult hospital.(28)

Automated drug distribution systems
One of the earliest IT interventions was automated drug distribution systems that package, dispense and distribute medications electronically. An early study of these systems showed that a medication profile-linked dispensing envelope system decreased drug administration errors from 13% to 1.9%,(29) while a later study of a bedside dispensing device, which restricted access to required medications and alerted nursing staff when medications were due for administration, also significantly reduced errors.(30)

However, a third device, which allows access to all drugs for all patients on the nursing unit, actually increased errors due to decreased vigilance on the part of the nursing staff.(31) This experience highlights the importance of routine checking of all forms of information technologies for their impact on patient safety. IT interventions need to be iteratively modified and refined.

Barcoding
Barcoding of medications, patients and even staff is another potential method of decreasing medication errors. The healthcare industry has been comparatively slow to adopt this technology; however, adoption in the USA is accelerating rapidly. Although few studies to date have studied this intervention, Concord Hospital in New Hampshire introduced barcoding and found an 80% decrease in administration errors (D DePiero, personal communication).

“Smart” intravenous devices
“Smart” intravenous devices are fairly new interventions that utilise computerised checks and programming to decrease errors. Few studies to date have evaluated such systems.(32)

Computerised discharge prescriptions and instructions
IT can standardise the exchange of patient information at handoffs between shifts, and particularly at transition between settings such as discharge from the hospital. Often, electronic health records can automatically generate discharge prescriptions and instructions. In addition, integrated electronic health records can be viewed from multiple settings such as the hospital, office and emergency department.

Personalised web pages
Personalised web pages can be created by healthcare institutions and used by patients as long as confidentiality issues are appropriately addressed. In addition, internet-based drug information can improve patient education and medication administration (see Resources).

Conclusion
Patient safety, particularly involving medications, is an important issue in healthcare today. IT-based interventions are potentially powerful tools to reduce medication errors. Healthcare organisations should address issues of medication safety by analysing and improving their organisational cultures and medication use systems, including the implementation of IT interventions. These interventions should be carefully monitored for their effects on medication safety.

References

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  2. Taxis K, Dean B, Barber N. Hospital drug distribution systems in the UK and Germany – a study of medication errors. Pharm World Sci 1999;21:25-31.
  3. Runciman WB, Roughead EE, Semple SJ, et al. Adverse drug events and medication errors in Australia. Int J Qual Health Care 2003;15 Suppl 1:i49-59.
  4. Thomas EJ, Studdert DM, Burstin HR, et al. Incidence and types of adverse events and negligent care in Utah and Colorado. Med Care 2000;38:261-71.
  5. Bates DW, Cullen D, Laird N, et al. Incidence of adverse drug events and potential adverse drug events: implications for prevention. JAMA 1995;274:29-34.
  6. Leape LL, Bates DW, Cullen DJ, et al. Systems analysis of adverse drug events. JAMA 1995;274:35-43.
  7. Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug events in hospitalized patients. JAMA 1997;277:307-11.
  8. Classen DC, Pestotnik SL, Evans RS, et al. Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA 1997;277:301-6.
  9. Bates DW, Leape LL, Petrycki S. Incidence and preventability of adverse drug events in hospitalized adults. J Gen Intern Med 1993;8,:289-94.
  10. Bates DW, Boyle DL, Vander Vliet MB, et al. Relationship between medication errors and adverse drug events. J Gen Intern Med 1995:10:199-205.
  11. Kaushal R, Bates DW, Landrigan C, et al Medication errors and adverse drug events in pediatric inpatients. JAMA 2001;285:2114-20.
  12. Cypress BW. Drug utilization in office visits to primary care physicians: National Ambulatory Medical Care Survey, 1980. Department of Health and Human Services publication (PHS) 82-1250. Public Health Service; 1982.
  13. Gandhi TK, Weingart SN, Borus J, et al. Adverse drug events in ambulatory care. N Engl J Med 2003;348:1556-64.
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  19. Berwick DM. Continuous improvement as an ideal in health care. N Engl J Med 1989;320:53-6.
  20. Glauber J, Goldmann DA, Homer CJ, et al. Reducing medical error through systems improvement: the management of febrile infants [comment]. Pediatrics 2000;105:1330-2.
  21. Bates DW, Ebell M, Gotlieb E, et al. A proposal for electronic medical records in US primary care. J Am Med Inform Assoc 2003;10:1-10.
  22. Classen DC, Pestotnik SL, Evans RS, et al. Computerized surveillance of adverse drug events in hospital patients. JAMA 1991;266:2847-51.
  23. Jha AK, Kuperman GJ, Teich JM, et al. Identifying adverse drug events: development of a computer-based monitor and comparison with chart review and stimulated voluntary report. J Am Med Inform Assoc 1998;5:305-14.
  24. Murff HJ, Forster AJ, Peterson JF, et al. Electronically screening discharge summaries for adverse medical events. J Gen Intern Med 2001;17 Suppl 1:A205.
  25. Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998;280:1311-6.
  26. Evans RS, Classen DC, Pestonik SL, et al. Improving empiric antibiotic selection using computer decision support. Arch Intern Med 1994;154:878-84.
  27. Evans RS, Pestotnik SL, Classen DC, et al. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med 1998:338:232-8.
  28. Weaver PE. Random sampling for quality assurance of the RxOBOT dispensing system.ASHP Conference, Las Vegas (NV), USA; 1998.
  29. Barker KN. The effects of an experimental medication system on medication errors and costs. I. Introduction and errors study. Am J Hosp Pharm 1969;26:324-33.
  30. Barker KN, Pearson RE, Hepler CD, et al. Effect of an automated bedside dispensing machine on medication errors. Am J Hosp Pharm 1984;41:1352-8.
  31. Barker KN, Allan EL. Research on drug-use-system errors. Am J Health Syst Pharm 1995;52:400-3.
  32. Rothschild JM, Keohane CA, Thompson S, et al. Intelligent intravenous infusion pumps to improve medication administration safety (abstract). Proc AMIA Symp 2003:992.

Resource
Gawande AA, Bates DW. The use of information technology in improving medical performance Part III. Patient-support tools. W:www.medscape.com



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