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Preventing Medication Errors (2007)

Chapter: Appendix D Medication Errors: Prevention Strategies

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Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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D
Medication Errors: Prevention Strategies

Many organizations and researchers have recommended specific interventions for preventing medication errors (See Box D-1). This appendix reviews the empirical evidence in support of these interventions in three care settings (hospital, nursing home, and community care), in pediatric and psychiatric care, and in relation to over-the-counter (OTC) and complementary and alternative medications.

PREVENTION STRATEGIES FOR HOSPITAL CARE

The committee reviewed published error reduction strategies of 10 organizations (see Box D-1). The methods used by these organizations for selecting and supporting their recommended interventions varied from those based on expert opinion to more rigorous evaluation of the literature; some organizations did not explicitly state the method used. Most proposed interventions are based on expert opinion.

The most evidence-based summaries were produced by the Agency for Healthcare Research and Quality (AHRQ). These summaries of specific practices were derived from a rigorous review of the published literature using strict article inclusion criteria and a standardized hierarchy for rating the strength of evidence for any particular intervention. These recommendations have been criticized, however, because of issues related to applying the usual evidence criteria to safety interventions (Leape et al., 2002). The National Quality Forum followed a rigorous process of interpreting the AHRQ recommendations to develop standards using an expert panel.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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BOX D-1

Organizations with Published Prevention Strategies for Hospital Care

  • Agency for Healthcare Research and Quality (Shojania et al., 2001)

  • American Society of Health-System Pharmacists (American Society of Health-System Pharmacists, 1996)

  • Institute for Healthcare Improvement (IHI, 2005)

  • Institute of Medicine (IOM, 2000)

  • Institute for Safe Medication Practices (ISMP, 2005b),

  • Joint Commission on Accreditation of Healthcare Organizations (JCAHO, 2005a)

  • Massachusetts Coalition for the Prevention of Medical Errors (MCPME, 1999)

  • National Quality Forum (NQF, 2003)

  • National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP, 2005b)

  • Pathways for Medication Safety (Pathways for Medication Safety, 2002)

  • U.S. Pharmacopeia (USP, 2005)

The Joint Commission on Accreditation of Healthcare Organizations (JCAHO) selects its patient safety goals from a pool of recommendations that are first identified by members of the Sentinel Event Advisory Group. These recommendations are selected because they are considered either evidence-based or, much more typically, consensus-based or practical. Similarly, the Institute for Safe Medication Practices generally develops its guidelines based on careful analysis of reported errors. These recommendations are then peer-reviewed prior to their release.

Recommendations for preventing medication errors are made by the National Coordinating Council for Medication Error Reporting and Prevention’s committee of experts in the field. The Massachusetts Coalition for the Prevention of Medical Errors developed best-practice recommendations for the prevention of medication errors based on a special consensus panel. The American Society of Hospital Pharmacists (ASHP) convened a

multidisciplinary conference on preventing medication errors. Recommendations from the ASHP derive largely from these expert panels. Along with the ASHP, both the American Medical Association and the American Nurses Association participated in this multidisciplinary conference.

Recommended Approaches

Table D-1 summarizes the error reduction strategies recommended by the organizations listed in Box D-1. In general, most organizations

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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TABLE D-1 Recommendations for the Prevention of Medication Errors in Hospital Care

Recommended Practice

Recommending Body

Strength of Evidence Supporting Efficacy

Technological Interventions

Implement computerized provider order entry (CPOE)

IOM, NCCMERP, MCPME, ASHP, IHI, NQF, PMS, AHRQ

Medium strength

Implement bar coding technology at the point of care

NCCMERP, MCPME, ASHP, PMS, AHRQ

Limited evidence

Ensure availability of pharmaceutical decision support

IOM, MCPME, ASHP

Limited evidence

Use pharmaceutical software

IOM, MCPME, ASHP

Lower strength

Use automated medication dispensing devices

AHRQ

Lower strength

Ensure free-flow protection on all general-use and patient-controlled analgesia (PCA) intravenous (IV) infusion pumps

NCCMERP, JCAHO

Limited evidence

Interventions Utilizing Clinical Pharmacists

Have a central pharmacist supply high-risk IV medications and pharmacy-based admixture systems

IOM, MCPME, PMS

Limited evidence

Include a pharmacist during rounds of patient care units

IOM, MCPME, ASHP, AHRQ

Medium strength

Utilize pharmacist counseling of patients

NCCMERP

Limited evidence

Have a pharmacist available on call after hours of pharmacy operation

MCPME

Medium strength

Have a pharmacist review all medication orders before first doses

ASHP, NQF

Limited evidence

Interventions Related to the Medication-Use Process

Establish a controlled formulary in which the selected medications are based more on safety than on cost

PMS

Limited evidence

Standardize prescription writing and prescription rules, and eliminate certain abbreviations and dose expressions

IOM, NCCMERP, ASHP, IHI, ISMP, NQF, JCAHO, USP

Limited evidence

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

Recommended Practice

Recommending Body

Strength of Evidence Supporting Efficacy

Limit and formally structure verbal communication of medication prescriptions

NCCMERP, ASHP, NQF, JCAHO

Limited evidence

Implement unit dosing

IOM, MCPME, NQF, AHRQ

Lower strength

Implement standard processes for medication doses, dose timing, and dose scales in a given patient care unit

IOM, IHI, ISMP, USP

Limited evidence

Monitor for look-alike and sound-alike medications

IHI, ISMP, JCAHO, USP

Limited evidence

Limit the number of different kinds of common equipment

IOM

Limited evidence

Do not store concentrated solutions of hazardous medications on patient care units, and limit the number of drug concentrations available in the organization

IOM, MCPME, JCAHO, ISMP

Limited evidence

Employ special procedures and written protocols for the use of high-risk IV and oral medications

OM, MCPME, IHI, INQF, PMS, ISMP, AHRQ, USP

Medium strength

Institute policies and procedures regarding labeling of all medications

NCCMERP, NQF, ISMP, JCAHO, USP

Limited evidence

Miscellaneous Nontechnological Interventions

Adopt a systems-oriented approach to medication error reduction

IOM, NCCMERP, MCPME, ASHP, IHI, PMS, ISMP, USP

Limited evidence

Use improved communication practices, such as always resolving medication discrepancies prior to administration

NCCMERP, ASHP, IHI, JCAHO

Limited evidence

Take steps to reduce workplace fatigue, such as planned naps, careful scheduling, or light therapy

IHI, ISMP, USP

Lower strength

Create a culture of safety

NCCMERP, ASHP, IHI, NQF, PMS, ISMP, USP

Limited evidence

Collect a medication history, and reconcile the list with the patient and other providers during care transitions

ISMP, JCAHO, USP

Limited evidence

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

Recommended Practice

Recommending Body

Strength of Evidence Supporting Efficacy

Improve the work environment for medication preparation, dispensing, and administration

IOM, ASHP, IHI, NQF

Limited evidence

Improve error detection and reporting, and promote a nonpunitive atmosphere

NCCMERP, MCPME, ASHP, NQF, PMS

Limited evidence

Make relevant patient information available at the point of care

IOM, MCPME, IHI

Indirectly supported through evidence on CPOE, electronic medication administration record (MAR), and bar coding

Use failure modes and effects analysis or other strategies for risk management

NCCMERP, PMS, ISMP

Limited evidence

Improve patients’ knowledge about their treatment

IOM, MCPME, IHI, PMS

Limited evidence

NOTE: AHRQ = Agency for Healthcare Research and Quality; ASHP = American Society of Hospital Pharmacists; IHI = Institute for Healthcare Improvement; IOM = Institute of Medicine; ISMP = Institute for Safe Medication Practices; JCAHO = Joint Commission on Accreditation of Healthcare Organizations; MCPME = Massachusetts Coalition for the Prevention of Medical Errors; NCCMERP = National Coordinating Council for Medication Error Reporting and Prevention; NQF = National Quality Forum; PMS = Pathways for Medication Safety; USP = U.S. Pharmacopeia.

SOURCE: ASHP, 1993; No Author, 1996; MCPME, 1999; IOM, 2000; Shojania et al., 2001; PMS, 2002; NQF, 2003; IHI, 2005; ISMP, 2005b; JCAHO, 2005a; NCCMERP, 2005b.

recommend implementing computerized provider order entry (CPOE) and bar coding at the bedside, although the evidence supporting bar coding remains weak. Other specific interventions supported by multiple groups include involving clinical pharmacists in patient rounds, implementing and utilizing unit dosing, standardizing prescription writing and prescription rules and eliminating certain abbreviations, utilizing special written protocols for high-risk medications, and limiting as well as standardizing verbal medication orders. Additional general recommendations embraced by most organizations include adopting a systems-oriented approach to medication errors, creating a culture of safety, and improving medication error identification and reporting.

For studies of interventions to reduce medication errors, inclusion criteria derived from AHRQ-sponsored analysis of patient safety practices were used (Shojania et al., 2001). Only studies with the following study design

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

were included: (1) randomized controlled trial; (2) nonrandomized controlled trial; (3) observational studies with controls. The same grading scale was modified to indicate the strength of evidence supporting a particular intervention: greatest, high, medium, lower, limited. This approach results in an overly conservative assessment of the evidence supporting a particular procedure, and these limitations have been well characterized previously (Leape et al., 2002).

Most of the recommendations have limited evidence to support their efficacy. The evidence appears strongest for recommendations to implement CPOE, include pharmacists in medication-intensive areas in the hospital, and use standardized written protocols for high-risk medications.

Evaluation of Recommended Approaches

Interventions to reduce medication errors can be divided into four categories: CPOE and decision-support systems, use of clinical pharmacists, automated medication dispensing systems, and a final category that includes all other proposed strategies.

Computerized Provider Order Entry and Decision-Support Systems

Ten studies evaluated CPOE and decision-support systems for medication error reduction. Two of these studies were randomized controlled trials, and the remaining eight used a before–after design. All ten studies demonstrated a statistically significant reduction in medication errors. Rates of medication errors were reduced by 13–86 percent, and rates of preventable adverse drug events (ADEs) by 17–62 percent.

Two studies at Brigham and Women’s Hospital, Boston, Massachusetts, examined the impact of CPOE with clinical decision support on medications errors and ADEs. The first found that nonintercepted serious medication errors decreased by 55 percent, from 10.7 to 4.86 events per 1,000 patient-days (p = 0.01). Preventable ADEs declined by 17 percent, but this was not statistically significant (Bates et al., 1998). The second study, consisting of a baseline period followed by the implementation of CPOE with decision support and then three study periods, demonstrated significant reductions in all medication errors (excluding missed-dose errors) and nonintercepted serious medication errors (Bates et al., 1999). The non-missed-dose medication error rate fell 81 percent, from 142 per 1,000 patient-days in the baseline period to 26.6 per 1,000 patient days in period 3 (p <0.0001). The nonintercepted serious medication error rate declined 86 percent over the same time frame (p = 0.0003). However, the decline in ADEs/1,000 patient days from 14.7 to 9.6 was not statistically significant.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Neither study was sufficiently powered to detect a difference in the preventable ADE rate.

The remaining eight studies examined more focused aspects of the medication-use process. Another study at Brigham and Women’s Hospital studied the impact of the implementation of a range of clinical decision-support tools for improving physician prescribing practices. Following the implementation of computerized decision support, use of the recommended histamine2-blocker rose from 15.6 to 81.3 percent of orders (p <0.001); the standard deviation of drug doses decreased by 11 percent (p <0.001); the proportion of doses that exceeded the maximum decreased from 2.1 to 0.6 percent (p <0.001); use of the approved dosing frequency for ondansetron hydrochloride increased from 6 to 75 percent of orders (p <0.001); and use of subcutaneous heparin for thrombosis prophylaxis in patients on bed rest increased from 24 to 46 percent of eligible cases (p <0.001).

At the Regenstrief Institute for Health Care, Indianapolis, Indiana, a study investigated the impact of computerized reminders on physician test-ordering behavior (Overhage et al., 1997). During a 6-month trial, reminders about corollary orders were presented to 48 intervention physicians and withheld from 41 control physicians. Intervention physicians executed the suggested corollary orders in 46.3 percent of instances when they received a reminder, compared with 21.9 percent among control physicians (p <0.0001).

Two studies were carried out at LDS Hospital, Salt Lake City, Utah. The first compared a computerized antibiotic selection consultant with physician antibiotic selection (Evans et al., 1994). The antibiotic consultant suggested an antibiotic regimen to which all isolated pathogens were shown to be susceptible for 453 out of 482 culture results (94 percent), while physicians ordered an antibiotic regimen to which all isolated pathogens were susceptible for 369 out of 482 culture results (77 percent) (p <0.001). The second study found that computer-assisted decision support for ordering antibiotics in an intensive care unit (ICU) resulted in improved quality of care (Evans et al., 1998). During the intervention period, all 545 patients admitted were cared for with the aid of the anti-infectives management program. Measures of processes and outcomes were compared with those for the 1,136 patients admitted to the same unit during the 2 years before the intervention period. Use of the program led to significant reductions in orders for drugs to which the patients had reported allergies (35 versus 146 during the preintervention period, p <0.01), excess drug dosages (87 versus 405, p <0.01), and antibiotic-susceptibility mismatches (12 versus 206, p <0.01). There were also marked reductions in adverse events caused by anti-infective agents (4 versus 28, p <0.02).

A study at Brigham and Women’s Hospital, Boston, Massachusetts, examined a computerized decision-support system for prescribing drugs

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

that adjusted drug dose and frequency based on the patient’s renal insufficiency. The proportion of prescriptions deemed appropriate by dose increased from 54 to 67 percent after the intervention (p <0.001), and by frequency increased from 35 to 59 percent (p <0.001) (Chertow et al., 2001).

The Section of General Internal Medicine, University of Illinois at Chicago, investigated the impact of computer alerts relating to the appropriate monitoring and use of digoxin (Galanter et al., 2004). Checking for unknown serum values rose after implementation from 6 to 19 percent for digoxin levels, 9 to 57 percent for potassium, and 12 to 40 percent for magnesium (p <0.01 for all comparisons).

A study at the Division of General Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, examined the impact of a CPOE system with clinical decision support designed to adjust medication doses of psychotropic medications in geriatric patients (Peterson et al., 2005). The intervention increased prescription of the recommended daily dose from 19 to 29 percent (p <0.001), reduced the incidence of ten-fold dosing from 5 to 2.8 percent (p <0.001), and reduced the prescription of nonrecommended drugs from 10.8 to 7.6 percent of total orders (p <0.001). Patients in the intervention group had a lower in-hospital fall rate—0.28 falls per 100 patient-days as compared with 0.64 falls per 100 patient-days (p = 0.001).

Researchers at the Mount Sinai Medical Center, New York, New York, investigated the impact of a CPOE system with clinical decision support linked to pharmacist and nurse feedback, designed to adjust medication doses in patients with renal insufficiency (Nash et al., 2005). The baseline rate of excessive dosing was 23.2 percent of administered medications requiring adjustment for renal insufficiency given to patients with renal impairment on the participating units. The rate fell to 17.3 percent with nurse feedback and 16.8 percent with pharmacist feedback in the participating units (p <0.05 for each, relative to baseline). The rates of excessive dosing for the rest of the hospital were largely unchanged over the same time periods.

One recent critique (Berger and Kichak, 2004) of two key studies on the medication-related safety benefits of CPOE (Bates et al., 1998, 1999) suggested that while CPOE (with decision support) has the potential to deliver benefits, there was some question as to whether these benefits had been adequately demonstrated since the 1998 study did not show that the preventable ADE rate had been reduced. The problem with this argument is that the studies that have been conducted were powered to detect a difference not in the preventable ADE rate, but in the serious medication error rate; no adequately powered studies of the preventable ADE rate have been

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

carried out. A number of subsequent studies have also found that CPOE can reduce medication error rates in the inpatient setting.

It is clear as well that computer systems can introduce errors of their own (Ash et al., 2004; McDonald et al., 2004; Koppel et al., 2005), and may even worsen outcomes in some instances. A recent study that raises substantial concern observed an unexpected increase in mortality coincident with CPOE implementation (Han et al., 2005). Although this study had a number of methodological flaws, the increase in mortality was large, and the authors postulated that the increase may have been due to delays in care caused by policies related to the introduction of CPOE and the technology itself. The committee acknowledges that there can be unintended consequences if health care providers do not carefully plan and implement major clinical transformations such as CPOE (Phibbs et al., 2005). Successful implementation requires redesign of health care delivery processes (Levick, 2005) and continuous monitoring for problems during the implementation phase, followed by the rapid introduction of system fixes (Bates, 2005). Finally, high rates of ADEs may continue after the implementation of CPOE in the absence of decision support for drug selection, dosing, and monitoring (Nebeker et al., 2005).

Role of the Clinical Pharmacist

Three hospital-based studies evaluated the role of the clinical pharmacist. In two of these studies, a clinical pharmacist accompanied the medical team during daily rounds and was available throughout the day for consultation. One study, carried out in a medical ICU in a large urban teaching hospital, demonstrated a reduction in the preventable ADE rate of 66 percent, from 10.4 to 3.5 per 1,000 patient-days (p <0.001) (Leape et al., 1999). The pharmacist made 366 recommendations related to drug ordering, 362 of which (99 percent) were accepted by physicians. Another study, carried out in a general medicine unit, demonstrated a reduction of 78 percent in preventable ADEs, from 26.5 to 5.7 per 1,000 patient-days (Kucukarslan et al., 2003). There were 150 documented interventions recommended by the pharmacist during the rounding process, 147 (98 percent) of which were accepted by the team. A third study utilized a clinical pharmacist to review prescriptions for vancomycin to determine the appropriateness of use (Anglim et al., 1997). The proportion of inappropriate prescriptions written was reduced from 61 to 30 percent of orders (p <0.001).

An additional study did not study pharmacists, but evaluated the impact on medication errors of nurses with special medication safety education (Greengold et al., 2003). In this study, the dedicated medication safety nurses had no effect.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×
Automated Medication-Dispensing Systems

Four studies evaluated automated medication-dispensing devices. In the only randomized trial, now more than 20 years old, a bedside automatic medication-dispensing machine was associated with a statistically significant reduction in medication error rate from 15.9 percent within the control group (a decentralized unit dose system) to 10.6 percent within the intervention group (Barker et al., 1984). In another study, implementation of an automated drug-dispensing system led to a reduction in medication errors, largely those related to time of administration, from 16.9 to 10.4 percent (p <0.001) (Borel and Rascati, 1995). This result is consistent with that of a later study demonstrating that the introduction of an automated medication-dispensing device led to an increase in the number of medications administered as scheduled from 59 to 77 percent of doses (p = 0.02) (Shirley, 1999). The remaining study reported on the introduction of automated medication-dispensing devices into a cardiovascular surgery unit and a cardiovascular ICU. Medication error rates decreased for patients in the surgical unit but increased for patients in the cardiothoracic unit; neither difference was statistically significant (Schwarz and Brodowy, 1995).

The AHRQ-funded review of patient safety practices concluded that the evidence provided by the above studies does not support the use of automated dispensing devices to reduce medication errors (Shojania et al., 2001).

Other Studies

National disease registries have become an important mechanism for correcting both under- and overprescribing of medications in hospitals for certain important groups of patients—those with ST elevation and non–ST elevation acute coronary syndrome and acute heart failure (Ferguson et al., 2003; Peterson et al., 2004; Jha et al., 2005).

A randomized control trial in a cardiac surgical ICU tested the efficacy of smart IV infusion pumps (incorporating an integrated decision-support system)—the intervention period. In the control period, the decision-support software was inactive. Although many errors were found that would not otherwise have been detected, the rates of serious medication errors in the control and intervention periods were not different (Rothschild et al., 2005).

A randomized controlled trial evaluated a continuous quality improvement initiative designed to increase the use of preoperative beta-blockers in patients undergoing coronary artery bypass graft surgery (Ferguson et al., 2003). The intervention included a call to action to a physician leader at the study site; educational products; and periodic longitudinal, site-specific feed-

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

back benchmarked on national averages. Over a 2.5-year period, the use of beta-blockers increased by 7.3 percent in the intervention sites compared with 3.6 percent in the control sites (p = 0.04).

Two randomized controlled trials examined the impact of patient educational interventions on medication errors. In one study, geriatric patients either participated in a self-medication program or received standard care (Pereles et al., 1996). Participation in the self-medication program did not increase the proportion of patients who were able to self-medicate on discharge from the hospital. Adherence, however, was improved by the program. The self-medication group had made statistically significant fewer medication errors than the control group at 1-month follow-up. In the other trial, intervention patients received drug safety information and their medication list, and the control group received drug safety information only. There was a nonsignificant difference between intervention patients and controls in the ADE and close-call rates (Weingart et al., 2004).

A final study evaluated whether medical interns exposed to an ICU schedule designed to minimize sleep deprivation might make fewer medication errors (Landrigan et al., 2004). The intervention group schedule was designed to eliminate extended work shifts and reduced the number of hours worked per week. The control group followed the traditional ICU call schedule. The interns allocated to the traditional call schedule made more serious medication errors than the intervention group (99.7 versus 82.5 per 1,000 patient-days, p = 0.03). The interns on the traditional schedule also made more than five times as many serious diagnostic errors (18.6 versus 3.3 per 1,000 patient-days, p <0.001). The results of this study suggest that limiting extended work shifts can reduce the medication error rate.

PREVENTION STRATEGIES FOR NURSING HOME CARE

Interventions to prevent medication errors in nursing home care fall into five categories: regulation, education and academic detailing, profiling and feedback, medication therapy management, and the use of technology.

Regulation

Much of the research relevant to medication safety in nursing homes has focused on documenting the overuse of psychotropic drugs prior to 1990 and evaluating the factors that influenced changes, and in some cases improved use of these drugs. Federal regulation of the use of psychotropic drugs in Medicaid- and Medicare-certified nursing homes became law in 1987 as the Nursing Home Reform Amendments of the Omnibus Budget Reconciliation Act (OBRA) of 1987 (P.L. 100-203), also known as OBRA-

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

87. Guidelines were implemented for antipsychotic drug use in October 1990 and for anti-anxiety drug use in April 1992. OBRA-87 regulations required that for psychotropic drugs there be an appropriate diagnostic indication, dosages within established limits, documentation of target symptoms, documentation of effect on target symptoms, documentation of presence or absence of side effects, and documentation of behavioral interventions in addition to the use of psychotropic medications (Gurvich and Cunningham, 2000). In 1999, the regulations were expanded to include a modified version of the Beers criteria.

The committee identified several studies of the impact of regulation on the use of psychotropic drugs in nursing homes. These studies used different data sources, including chart reviews, Minimum Data Set (MDS) data, Online Survey Certification and Reporting (OSCAR) data, and pharmacy records.

Antipsychotic Drugs

Earlier research established that the use of psychotropic medications was widespread and excessive, as documented by a review (Kane et al., 1993) of studies conducted prior to OBRA. Studies in 1987 and 1988 using chart review and pharmacy records revealed that antipsychotic medications were received by 14.2 percent of 524 nursing home residents in one facility in New York (Lantz et al., 1996), 23 percent of residents of 372 nursing homes in Minnesota (Garrard et al., 1995), 24 percent of residents in 16 skilled nursing facilities in Wisconsin (Svarstad and Mount, 1991; Svarstad et al., 2001), and 26 percent of residents of 12 nursing homes in Massachusetts (Beers et al., 1988).

After the implementation of OBRA regulations for antipsychotic drugs, Garrard and colleagues (1995) noted an 8 percent decrease in the prevalence of antipsychotic medications. Lantz and colleagues (1996) found a modest 3.8 percent decline in use of antipsychotic drugs over a 10-year period in one nursing home, which was not statistically significant, possibly because of low baseline levels (12.4 percent). A mean reduction of 38 percent of antipsychotic drug use was found in 16 nursing homes post-OBRA, with a range of an 85 percent reduction to a 19 percent increase (Svarstad et al., 2001). A comparable magnitude of change (17.8 to 12.5 percent) was noted within 13 months of OBRA implementation in data collected by a large pharmacy consulting company (Kane et al., 1993). The number of patients requiring antipsyhotic drugs was essentially unchanged in a Veterans Affairs (VA) nursing home in Wisconsin, but the average haloperidol equivalent dose decreased over a 4-month period after OBRA from 12.5 to 7 mg per day (Slater and Glaser, 1995). In another study, in an academic nursing home in Chicago, OBRA was credited with discontinuation or lowered doses in 27.6 percent of residents with dementia diagnoses

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

only, 33.3 percent with psychiatric diagnosis only, and 36 percent with both diagnoses (Semla et al., 1994).

Similar improvements in antipsychotic drug use were found in the medical records of 99 clients in a Wisconsin intermediate care facility for mental retardation, including decreased antipsychotic dosage, decreased number of persons who used antipsychotics, decreased use of as-needed psychotropics, and increased use of other psychotropics (Howland, 1993). These results are significant, since OBRA-87 was initially directed to this population, as well as older institutional residents.

Kidder (1999) used a federal government study from 1974, studies in the literature, and OSCAR data to conclude that antipsychotic drug prescription decreased from a stable level of 33.65 percent pre-OBRA to 16.05 percent post-OBRA (Kidder, 1999). This Health Care Financing Administration (now Centers for Medicare and Medicaid Services [CMS]) official also concluded that fears of deleterious effects from limiting anti-psychotic drug use had not been realized, since MDS data and studies identified no decrement, and possible improvement, in behavior and activities of daily living among nursing home residents during the implementation of OBRA.

Anti-Anxiety Drugs

The impact of OBRA on anti-anxiety drug use is confounded by the staggered implementation of the OBRA guidelines for antipsychotic and anti-anxiety drugs, since many studies were conducted in the interval between implementation of the respective policies. Based on data prior to the passage of OBRA, Beers and colleagues (1988) reported that of those residents of 12 Massachusetts nursing homes receiving benzodiazepines, 30 percent were taking a long-acting agent, a category that had been associated with increased sedation, falls, and other adverse events. The typical dosage was relatively high for older patients, at 7.3 mg diazepam equivalent per day, which is nearly 50 percent higher than the geriatric dosage in the OBRA guidelines (Gurvich and Cunningham, 2000).

Kane and colleagues (1993) cited data from a large California pharmacy consulting company to introduce the concern that compensatory prescribing of benzodiazepines might replace antipsychotic use. The baseline routine prescribing rate prior to the OBRA antipsychotic guidelines increased from 5.25 to 7.6 percent in November 1991. Similar results were found in a study of one VA nursing home where prescription of benzodiazepines increased from 42 to 48 percent of residents coincident with the time of implementation of the OBRA antipsychotic guidelines (Slater and Glaser, 1995). Conversely, no change in benzodiazepine use was associated with the implementation of the OBRA antipsychotic guidelines in a follow-up study of 1,650

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

residents in 16 nursing facilities in Wisconsin published before the implementation of the anti-anxiety guidelines (Svarstad and Mount, 2001a) and in a study of 372 nursing homes in Minnesota (Garrard et al., 1995).

In a 6-year retrospective study in one private, nonprofit nursing home in Georgia conducted in 1994, the rate of anti-anxiety drug use of 22 percent immediately before the implementation of the psychotropic drug regulations (up from 15.5 percent in 1988) decreased significantly to 8.9 percent in 1994, 2 years after the implementation of the anti-anxiety drug regulations (Taylor et al., 2003). A 10-year follow-up study comparing 1984 and 1994 rates of prescription indicated that OBRA implementation coincided with a declined in the prescription of anxiolytic and sedative/ hypnotic medications from 12.1 to 6.4 percent (p <0.01) (Lantz et al., 1996). Comparison of the rates of prescription of benzodiazepines during 1986–1989 and those in 1993–1994 using a stratified random sample of 16 skilled nursing facilities in Wisconsin showed an increase from 18.1 to 22.8 percent, which was not statistically significant (Svarstad et al., 2001).

A comparison conducted of chronic benzodiazepine use by Medicaid residents in nursing homes before 1990 and during 1993–1994 to assess the impact of the OBRA guidelines documented a decline of only 3.9 percent, which was not statistically significant (Svarstad and Mount, 2001a). Only the ratio of licensed nurses to residents was associated with improvement in medication appropriateness. Using publications and national datasets, Kidder (1999) determined that following OBRA, national rates of anti-anxiety drug use increased slightly from 10.62 percent (or 13.1 percent if nonrepresentative data were excluded) to 14.29 percent, and hypnotic medication use decreased from 10.62 to 6.83 percent.

Use of Antidepressants

While the use of antipsychotic medication has decreased, the use of antidepressants has increased since the implementation of OBRA (Lantz et al., 1996; Svarstad et al., 2001; Taylor et al., 2003). This may be attributed to increased education about undertreatment of depression, availability of safer medications, and responsiveness of depression in older adults. Lapane and Hughes (2004) found that depression was more likely to be addressed in larger nursing facilities or facilities staffed with a full-time physician, whereas increased antipsychotic drug use was found in facilities that were government-owned, had more licensed nurses, and had more residents reliant on Medicaid funding. Kidder (1999) also noted that antidepressant use had increased from 12.64 to 24.9 percent during the implementation of OBRA, although he observed that the increase began pre-OBRA as safer agents emerged and probably was not due to substitution for drugs covered by the OBRA regulations.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Compliance with Regulations

Llorente and colleagues (1998) examined compliance with the OBRA regulations on psychotropic drugs. They found that none of the eight nursing homes examined were in full compliance with the regulations pertaining to these medications. Only three guidelines had compliance means greater than 70 percent: appropriate diagnosis, drug dosage within limits, and documentation for target symptoms of the psychotropic drug. Documented behavioral intervention had the lowest compliance of 44.5 percent (Llorente et al., 1998). The Office of Inspector General (OIG) found that 85 percent of psychotropic drug use in nursing homes was appropriate. Inappropriate psychotropic drug use was attributed to drug dose too high, drug not justified, lack of documented benefit of drug, wrong type of drug, or duplicated drug (OIG, 2001).

Education and Academic Detailing

Five studies of educational approaches, including academic detailing, were reviewed. One of the studies involved education of nursing staff only, two involved education of physicians only, and two involved education of both. Education of physicians generally included some form of academic detailing involving individual or small-group face-to-face drug therapy education, often in the physician’s office.

Education of Nursing Staff

In a single-group pretest–posttest design, 30 licensed nurses (registered and licensed practical nurses) in five nursing homes in North Carolina received a packet of educational materials describing appropriate drug administration techniques, prepared by the consultant pharmacist (Ruffin and Hodge, 1995). The outcome studied was medication administration errors as determined by observation and the clinical significance of errors as determined by guidelines published by the American Society of Consultant Pharmacists. The mean error rate decreased from 10.56 to 2.87 (p = 0.0026) for all routes. Significant differences were noted for the ophthalmic and oral routes, but not for metered dose inhalers or transdermal routes. In addition to the overall weaknesses of the single-group design, the lack of description of the intervention or measurement of the “dose” of the intervention is a major limitation of this study, since it is unknown how many of the nurses read the educational materials. No information was provided about the types of errors, although it appears that most were wrong-technique errors, which would be quite different from the findings of other observational studies.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Academic Detailing of Physicians

In an important randomized controlled trial, 435 physicians (Avorn and Soumerai, 1983; Soumerai and Avorn, 1987) who were Medicaid prescribers (including 208 who practiced in nursing homes) were assigned to one of three groups: control (no education, n = 165), print-only intervention group (received mailings of four-color brochures; n = 132), and face-to-face intervention group (offered two visits from clinical pharmacists trained in academic detailing, plus mailings; n = 141). Education focused on three drug targets: propoxyphene, vasodilators, and cephalexin. Prescribing outcomes consisted of the average number of prescriptions of the targeted drugs over a 9-month period before and after the intervention, extracted from Medicaid prescribing data. In this classic study, physicians who received the face-to-face intervention and mailings showed reduced prescribing of target drugs by 14 percent compared with controls (p <0.0001), and participation in the second visit was the best predictor of improvement. The extent of nursing home practice was not related to reduction of prescribing.

Another quasi-experimental study using a single-group time-series design in one large academic long-term care facility included serial interventions to reduce inappropriate use of H2-receptor blockers (Gurwitz et al., 1992). Group discussions with all members of the medical staff emphasizing unsubstantiated indications of H2-receptor blockers and printed educational materials constituted the first intervention. When the frequency of prescriptions reached a predetermined threshold, a booster intervention of additional small-group discussion and a list of patients under the physician’s care receiving the drugs was provided. The outcome measures were prevalence of H2-receptor blocker therapy, estimated cost savings, and estimated resource costs. There was a sudden reduction (maximal 59.1 percent) in prescriptions for H2-receptor blockers after the first intervention, which persisted for 11 months, and a return to baseline in 19 months. More modest reductions (32.1 percent) occurred with the second intervention, with substantial cost savings from the overall program.

Education of Nurses and Physician Staff

In an intervention aimed at reducing the use of psychotropic medications in nursing homes, six matched pairs of nursing homes were randomly assigned to an educational program in geriatric psychopharmacology for physicians, nurses, and aids or to a no-treatment control group. Experimental homes had significantly better scores on an index of inappropriateness of psychoactive prescribing (−27 versus −6 percent), as well as greater discontinuation of antipsychotics (32 versus 14 percent), benzodiazepines (20 versus 9 percent), and antihistamine hypnotics (45 versus 21 percent).

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Residents in experimental homes showed less deterioration in cognitive functioning.

Jones and colleagues (Jones et al., 2004, 2005; Hutt et al., 2006) conducted a quasi-experimental study of six matched pairs of nursing homes (N = 12) randomly assigned to receive a multifaceted intervention or control condition. The intervention focused primarily on the nursing home staff, with educational and behavioral components. The physicians were provided an academic detailing intervention in small groups. Control facilities received only a pain resource binder. The outcome measures were based on knowledge testing of nursing staff and quarterly interviews of a 20 percent sample of the residents regarding pain symptoms, with oversampling of Hispanic residents, supplemented by chart review of medication use and collection of MDS data. There were improvements in staff knowledge in some intervention homes, but attitudes were not changed. A measure of appropriateness of prescribing of pain medication improved among residents not in pain (indicating improved prescribing) and in homes where nursing staff’s knowledge improved. Instability in staff and leadership impacted the consistent delivery of the intervention in some intervention homes. Resistance of residents to requesting or taking medication was a significant barrier to improving pain outcomes.

Profiling and Feedback

While profiling and feedback have been used as a component of multifactorial educational interventions (Gurwitz et al., 1992; Jones et al., 2004, 2005; Hutt et al., 2006), use of triplicate prescription programs is an intervention that relies primarily on profiling prescribing patterns and monitoring physician prescribing. One copy of the prescription is forwarded to a regulatory agency for monitoring purposes, while one copy goes to the pharmacist, and one is retained by the prescriber. This intervention originated in New York to reduce the abuse and misuse of Schedule II drugs (medically useful drugs with a high abuse potential) in the state.

Zullich and colleagues (1993) reported that the number of benzodiazepine prescriptions written under the triplicate prescribing policy decreased from 80 to 53 percent, depending on the population, but there was concern that benzodiazepines were being replaced by other psychoactive agents in long-term care settings. This descriptive study of residents in 10 nursing homes in western New York who discontinued use of benzodiazepines included chart review and incident report analysis. The decrease in benzodiazepine use was accompanied by a steady increase in the number of orders for alternative agents, including chloral hydrate, diphenhydramine, and phenobarbital. There was no change in the number of adverse events, although statistical power may have been insufficient to detect such changes.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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In addition, it is unclear how the relative use of the different classes of medications was quantified.

Another study using the Systematic Assessment of Geriatric drug use via Epidemiology (SAGE) database compared benzodiazepine prescribing in 1994–1995 in New York under a triplicate prescription policy with prescribing in states without a similar policy (VanHaaren et al., 2001). Residents of New York facilities were less likely to be receiving benzodiazepines (4.9 versus 13 percent; odds ratio = 0.42). This study found no increases in substitute drugs.

Castle (2003) compared the use of restraints and psychotropic drugs in a sample of 120 nursing homes that received mailed reports providing feedback on six quality indicators and in 1,171 facilities that did not receive the reports. Use of physical restraints and psychotropic medications was lower in facilities that received the feedback.

Medication Therapy Management

In a randomized cluster trial, the impact of a clinical pharmacy program involving development of professional relationships, nurse education, and individualized drug review by clinical pharmacists was tested in a sample of 905 residents in 13 intervention nursing homes and 2,325 residents in 39 control homes in Australia (Roberts et al., 2001). Use of several drug groups (nonsteroidal anti-inflammatory drugs [NSAIDs], laxatives, H2-receptor blockers, and antacids) was decreased. Overall, drug use was decreased by 14.6 percent relative to controls. Lack of significance in resident outcomes was attributed to inadequate power. No rationale was given for the mechanism(s) whereby the intervention was expected to improve the outcomes, nor was the relationship aspect of the intervention adequately described.

Another Australian study (Crotty et al., 2004) was a randomized controlled trial of a multidisciplinary case conference intervention on medication appropriateness and resident behavior, compared with external and internal control groups. The intervention consisted of two case conferences including the geriatrician, the pharmacist, residential care staff, and a representative of the Alzheimer’s Association to discuss nonpharmacologic management. The medication appropriateness index for benzodiazepines improved during the study in the intervention versus the external control group, while resident behavior was unchanged. Improved medication appropriateness did not extend to the control group of residents in the same facility. The investigators attributed their success compared with a previous unsuccessful trial to direct participation of the physician and selection of the residents by the staff based on behavior problems.

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Use of Technology

Four studies describe or evaluate technology interventions in the nursing home setting. Although some are represented as research, the articles are largely experiential and anecdotal. One covers the key issues involved in implementation of CPOE in a Canadian nursing home (Rochon et al., 2005). In a review of bar coded medication administration in a Veterans Administration (VA) facility, 1 recommendation is unique to nursing homes out of 15 relevant to all settings: development of a reliable method to ensure periodic replacement of wristbands was advised to retain scanability, since nursing home patients have extended stays (Patterson et al., 2004). A survey of nurses’ perceptions in a Canadian nursing home found strong resistance to the use of an automated dispensing system (Novek et al., 2000). The fourth study describes the use of Geriatric Risk Assessment MedGuide (GRAM) software, which employs MDS data to help detect ADEs (Feinberg et al., 2004).

PREVENTION STRATEGIES FOR COMMUNITY CARE

Interfaces Between Care Settings

Strategies tested for reducing medication errors at the interfaces between care settings include medication education programs and a medication reconciliation process.

Medication Self-Care Education

Two studies that included strategies such as a self-administered medication program or a medication discharge planning program showed significantly improved medication knowledge among patients, reduced medication errors, and lowered hospital readmission rates. A Canadian study compared the effectiveness of a medication education program in the hospital followed by self-administered medications at home (n = 178) versus nurse-administered medications at home (n = 172) (Jensen, 2003). The self-administered medication group had significantly fewer medication errors and medication-related problems compared with the nurse-administered medication group. There was no statistically significant difference between the groups in medication adherence. In another study employing a medication self-care educational program as an intervention, there was a statistically significant difference in the hospital readmission rate within 31 days after discharge between the intervention group (7.7 percent) and the control group (28.6 percent) (p = 0.05) (Schneider et al., 1993).

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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Medication Reconciliation

The Institute for Safe Medication Practices suggests the following steps for implementing medication reconciliation, a 2006 JCAHO national patient safety goal (ISMP, 2005a; JCAHO, 2005c), at the interface between care settings: obtain the most accurate list of medications possible, plus information such as the dose, frequency, indication, and time of last dose for each medication; prescribe needed medications, taking into consideration the patient’s current medications; reconcile medications and resolve discrepancies; reconcile medications again upon each transfer and at discharge; fully resolve any medication discrepancy; share the list with all health care providers; give the list to patients; and encourage patients to share the list with their providers and pharmacists.

In a study in an adult surgical ICU, a medication reconciliation process was instituted. Medical and anesthesia records were reviewed, allergies and home medications were verified with patient/family, and the findings were compared with orders at the time of discharge from the ICU. In a sample of 33 patients, 31 (94 percent) had their discharge orders changed (Pronovost et al., 2003).

The Ambulatory Clinic Setting

Strategies proposed to reduce medication prescribing errors in the ambulatory clinic setting are varied and include prescription writing aids, electronic prescribing with standardized variable fields that prohibit the use of unsafe abbreviations for medication instructions, medication-related computer signals, clinical practice guidelines, in-service education for physician trainees, a physician–pharmacist collaborative medication therapy management service, patient-specific medication-management reports, and voluntary medication error reporting programs. Only a few of these strategies have been evaluated.

Prescription Writing Aids

An educational program for 12 family practice residents that involved evaluation of and feedback on prescription writing by a clinical pharmacist over a 2-year period helped reduce medication prescribing error rates from 14.4 to 6 percent during the last 6 months of the intervention (p = 0.0002) (Shaughnessy and D’Amico, 1994).

Eleven providers in an adult internal medicine clinic participated in a trial of a modified paper prescription form. This form contained prompts for medication name, form, strength, dose, route, frequency, refills, quantity, indication, and additional directions. Use of the modified form reduced

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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clinically important prescribing problems (p = 0.007) and decreased omission errors (p = 0.01) (Kennedy and Littenberg, 2004b).

An intervention in an outpatient clinic included a quality improvement review of prescriptions, the use of a self-inking name stamp, and an educational program that gave examples of poorly written prescriptions and emphasized legal requirements. A follow-up survey showed that 72 percent of local community pharmacies saw the stamps being used. When stamps were not used, illegible signatures continued to be a problem (Meyer, 2000).

Proposed strategies for reducing medication administration errors in the ambulatory clinic setting include failure modes and effects analysis, access to patient records for all health care professionals, use of appropriate abbreviations and formulations, standardized protocols, clearly labeled storage bins for medications, and educational training for staff and health care professionals.

Medication Administration

There are two sets of guidelines for medication administration in the ambulatory clinic—for vaccine administration and chemotherapeutic agent administration—but no studies evaluating these guidelines.

U.S. Pharmacopoeia (USP) has proposed the following guidelines for vaccine administration: (1) conduct a failure modes and effects analysis on the names, packaging, and labeling of the available vaccines in each facility; (2) review appropriate vaccine abbreviations and formulations; (3) establish clear protocols on the prescribing, documenting, dispensing, and administering of vaccinations; (4) use an adequate number of clearly labeled storage bins in the refrigerator; and (5) incorporate training sessions regarding the facility’s vaccine protocols into physician, pharmacy, and nursing staff meetings (USP, 2003).

The American Society of Health-System Pharmacists has produced guidelines on how to improve the antineoplastic medication-use system and error prevention programs for all care settings (ASHP, 2002). The American Society of Clinical Oncology has developed some specific guidance for outpatient chemotherapy (ASCO, 2003).

Medication Therapy Management

Pharmacist–physician collaborative medication therapy management services, which involve collaborative practice between physicians and pharmacists, have improved medication safety and achieved therapeutic goals. For example, during the period January 1999 through March 2002, the medication therapy management services in the Fairview Clinics System of Minneapolis–St. Paul resolved 5,780 drug therapy problems for 2,524 pa-

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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tients. During this period, the rate of therapeutic goals achieved increased from 74 percent at the time of patients’ initial pharmaceutical care encounters to 89 percent at patients’ latest encounters (Isetts et al., 2003).

Another collaborative model involving primary care physicians and clinical pharmacists was tested in a group of 197 hypertensive patients (Borenstein et al., 2003). Patients were randomized to an intervention group (physician–pharmacist comanagement) and a control group (physician-only care). Better blood pressure control was achieved in the comanagement group (60 percent) than in the control group (43 percent) (p = 0.02). Furthermore, the investigators found that the average provider visit costs/ patient were higher in the usual-care group ($195) than in the comanagement group ($160) (p = 0.02).

In a population-based cohort study between 1996 and 1997, 19,368 physicians were made aware of 24,266 (56 percent) medication alerts via a computerized drug utilization database linked to a telepharmacy intervention that triggered phone calls to physicians by pharmacists. The result was the change of 2,860 (24 percent) medications to a more appropriate therapeutic agent (Monane et al., 1998).

Successful collaborations between pharmacists and physicians can also be achieved with bidirectional communication, collaborative care of mutual patients, identification of a “win–win” opportunity, attention to physician convenience, and balanced dependence between the pharmacist and the physician (Brock and Doucette, 2004).

Medication Monitoring

Retrospective drug utilization reviews have been promoted as a useful tool for detecting and reducing medication errors (Lyles et al., 1998). However, a recent longitudinal ecologic and cohort study of six Medicaid programs that used the same review software in the mid-1990s did not find a reduction in the rate of exceptions to established medication-use criteria or any reduction in the incidence of hospitalization (Hennessy et al., 2003).

In a 5-month prospective observational study carried out in 2001, 215 drug reviews were conducted with 63 patients being treated at an outpatient hemodialysis center. The reviews found 113 drug discrepancies. Electronic drug records were discrepant by one drug record for 60 percent of patients, two drug records for 26 percent of patients, and more than two drug records for 14 percent of patients. Fifty percent of the 113 drug discrepancies put patients at risk for ADEs (Manley et al., 2003).

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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The Community Pharmacy Setting

Strategies that have been proposed for reducing dispensing errors in the community pharmacy setting include the following:

  • A quality working environment (Buchanan et al., 1991; Flynn et al., 1996, 1999)

  • Checking of work by another person (Davis, 1990)

  • Quality assurance tools at the point of care, such as bar coding equipment (Davis, 1990) and computer tools to screen for drug interactions (Murphy et al., 2004; Malone et al., 2004)

  • Access to patient profiles (Davis, 1990)

  • Pharmacist training (Davis, 1990)

  • Pharmaceutical case management service (Vivian, 2002; Cranor et al., 2003; Curtiss et al., 2004; Chrischilles et al., 2004)

  • Patient counseling (Davis, 1990; Rupp et al., 1992; Rupp, 1992; Kuyper, 1993; Grissinger et al., 2003; Becker et al., 2004)

  • A quality assurance program and error reporting system (Davis, 1990; Kennedy and Littenberg, 2004a)

  • Assessment of the quality of medication safety of community/ ambulatory pharmacies—a tool designed by the Institute for Safe Medication Practices and cosponsored by the American Pharmaceutical Association Foundation and the National Association of Chain Drug Stores (ISMP, 2001)

Some of these strategies have been evaluated empirically.

A Quality Working Environment

Good illumination and limited interruptions help reduce error rates. The relationship between the level of illumination and the prescription-dispensing error rate was investigated in a high-volume U.S. Army outpatient pharmacy. The final sample consisted of 10,888 prescriptions dispensed by five pharmacists. An illumination level of 146 foot-candles was associated with a significantly lower error rate (2.6 percent) than the level of 45 foot-candles (3.8 percent) (Buchanan et al., 1991).

In a study to identify the impact of interruptions and distractions on dispensing error rates, 5,072 prescriptions were analyzed and 164 errors detected, for an overall error rate of 3.23 percent. During the study, a total of 2,022 interruptions (2.99 per half-hour per subject) and 2,457 distractions (3.80 per half-hour per subject) were detected. The error rate for sets of prescriptions with one or more interruptions was 6.65 percent and for

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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sets during which one or more distractions occurred was 6.55 percent (Flynn et al., 1999).

The associations between ambient sounds and the accuracy of pharmacists’ prescription-filling performance in a pharmacy have been studied. The results suggest that the quality of pharmacists’ performance may not be adversely affected by ambient sound: as sound levels increased, the error rate increased to a point, then decreased. Unpredictable sounds, controllable sounds, and noise had a significant effect on pharmacists’ performance, resulting (somewhat surprisingly) in a decreased dispensing error rate (Flynn et al., 1996).

Pharmaceutical Case Management Service

The Iowa Medicaid pharmaceutical case management (PCM) program evaluated the effect of PCM on medication safety and health care utilization (Chrischilles et al., 2004). The participants were 2,211 noninstitutionalized Medicaid patients taking four or more chronic medications. Of these, 524 received PCM services and 1,687 did not. In the PCM group, at least one medication problem occurred with nearly one-half (46.1 percent) of medications and 92.1 percent of patients before the PCM program started. By the end of the program, mean medication appropriateness index scores had improved significantly compared with the starting position among PCM recipients (p <0.001). For those aged 65 and older, the percentage of PCM recipients (n = 175) using high-risk medications decreased significantly (p = 0.032) compared with those who did not receive the service (n = 366). No difference in health care utilization or charges was observed between PCM recipients and PCM eligibles who did not receive PCM services, even after reimbursements for those services were included.

The use of medication therapy management has provided benefits on several levels for two large self-insured employers in North Carolina. These employers compensated pharmacists on a fee-for-service basis for providing advisory services to employees with diabetes mellitus (the Asheville Project). As a result, hemoglobin A1c levels were better controlled, and employer total mean medical costs decreased by $1,622 per patient to $3,356 per patient per year (Cranor et al., 2003). Both employers have permanently added the benefit to their health plans.

Another study examining the impact of pharmacy care services for patients with diabetes also produced good results (Garrett and Bluml, 2005). Eighty community pharmacists in five states were reimbursed for pharmacy care services, including scheduled consultations with patients, clinical goal setting, and referrals to diabetes educators. Over the initial year of the program, the group of 256 patients participating in the study showed significant

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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improvements in clinical indicators and higher rates of self-management. Mean total health costs (including the medication therapy costs) were $918 per patient per year less than employers’ expected total costs.

A group of 56 patients in a hypertension clinic at the VA medical center in Philadelphia, Pennsylvania, participated in a trial to see whether the intervention of clinical pharmacists improved blood pressure control. Twenty-one patients out of 27 (81 percent) in the intervention group (monthly meetings with a clinical pharmacist) and 8 patients out of 29 (28 percent) in the control group (standard care from physicians) attained their blood pressure goal (p <0.0001) (Vivian, 2002).

Patient Counseling

Outpatient prescription errors at an Indian Health Service pharmacy were reviewed. Mistakes detected after pharmacists had signed off on prescription accuracy were recorded. The review of errors showed that of 323 reported mistakes, 286 (89 percent) had been detected during patient counseling and subsequently corrected (Kuyper, 1993).

The Home Care Setting

Strategies proposed to reduce medication errors in the home care setting have included an intervention in which a nurse, a clinical pharmacist, and physicians collaborated in monitoring the medications of the studied patients (Ahrens et al., 2002; Ahrens, 2003); home visits by pharmacy staff (No Author, 2000); and the implementation of a medication management model (Meredith et al., 2002).

A randomized controlled trial was used to test the efficacy of a medication-use improvement program developed specifically for home health agencies for patients aged 65 and over (Meredith et al., 2002). The intervention group (n = 130) received the usual care (the patients’ home care nurses) supported by a clinical pharmacist, while the control group (n = 129) received the usual care. Medication use improved for 50 percent of intervention patients and 38 percent of control patients, an attributable improvement of 12 patients per 100 (p = 0.051). The intervention effect was greatest for therapeutic duplication, with improvement for 71 percent of intervention patients and 24 percent of control patients, an attributable improvement of 47 patients per 100 (p = 0.003).

The Self-Care Setting

Strategies to reduce medication errors in this setting include educational programs and multisystem interventions (e.g., telecommunications plus edu-

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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cational programs). Some educational programs have been successful in increasing medication knowledge and self-efficacy among patients. In a self-management program, asthmatic patients who were taught the appropriate use of inhalers were able to demonstrate the devices’ correct use when tested (van der Loos, 1989). In another program, patients who were taking nonaspirin NSAIDs improved the recall of their medication use after being shown lists and pictures of their medications (Kimmel et al., 2003). A telephone system for monitoring and counseling patients with hypertension helped improve medication adherence for 18 percent of the 133 patients who used the system and for 12 percent of the 134 patients in the control group (p = 0.03), and decreased diastolic blood pressure (5.2 mm Hg in telephone users versus 0.8 mm Hg in controls, p = 0.02) (Friedman et al., 1996).

A systematic review of published randomized controlled trials on interventions to improve patients’ adherence to prescribed medications (McDonald et al., 2002) found that 49 percent of the interventions tested (19 of 39 interventions in 33 studies) were associated with increases in adherence, while 17 were associated with reported improvement in outcomes. Two studies found that dosing once a day led to higher adherence than dosing twice a day, but not better clinical outcomes (Baird et al., 1984; Girvin et al., 1999). A third study found that dosing twice a day resulted in higher adherence than dosing four times a day and better clinical outcomes as well (Brown et al., 1997). In general, however, the investigators (McDonald et al., 2002) found that the most effective interventions for long-term care were complex; these interventions included more convenient care, information, counseling, reminders, self-monitoring, reinforcement, family therapy, and other forms of supervision. However, the investigators concluded that even the most effective interventions had modest effects.

The School Setting

The website of the Center for Health and Health Care in Schools provides information on state policies regarding the administration of medications in schools (Health in Schools, 2004). The center has also identified a set of issues that a school medication management policy might include, for example, the responsibility for medication use the school is willing to assume, the responsibilities required of the patient and parents, the rules for self-medication, and feedback mechanisms so that parents can learn about a medication’s effect (Robinson, 2004). The American Academy of Pediatrics (Committee on School Health, 2003) has also developed a set of guidelines for the administration of medications in schools. Of more practical help, the Florida Society of Health-Systems Pharmacists has developed a resource manual for medication use in schools (Johnson et al., 2003). The

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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committee is not aware of any study evaluating the procedures included in these documents.

PREVENTION STRATEGIES FOR PEDIATRIC CARE

The committee reviewed published error reduction strategies of 10 organizations: the Pediatric Pharmacy Advocacy Group (Levine, 2001), American Academy of Pediatrics/National Initiative for Children’s Healthcare Quality (NICHQ, 2005), Institute for Safe Medication Practices (ISMP, 2005b), American Hospital Association (AHA, 2005), National Quality Forum (NQF, 2003), Massachusetts Hospital Association/Massachusetts Coalition for the Prevention of Medical Errors (MCPME, 1999), National Coordinating Council for Medication Errors Reporting and Prevention (NCCMERP, 2005b), AHRQ (Shojania et al., 2001), JCAHO (JCAHO, 2005a), and Institute of Medicine (IOM, 2000).

The committee identified a total of 26 unique recommendations from these organizations for strategies to reduce medication errors in pediatric care (see Table D-2). These recommendations included equipment/software tools, representation of personnel on groups making decisions on pediatric medications, training and competency of personnel, policies, clear labeling, continuous quality improvement efforts, clear and accurate documentation, standardization, patient education, and teamwork improvement. As Table D-2 indicates, none of these recommendations is based on published evidence of effectiveness in children. The vast majority are based on expert opinion (n = 22), with the remainder being based on studies in adult populations (n = 4). No recommendations have supporting pediatric-specific evidence on efficacy, cost-effectiveness, feasibility, appropriateness in different settings, and institutional barriers or risks.

PREVENTION STRATEGIES FOR PSYCHIATRIC CARE

Within psychiatry, no studies have been carried out to evaluate the efficacy of any error prevention strategies. Examples of strategies likely to be relevant to inpatient psychiatry include short-term approaches (for example, medication ordering protocols, unit-dose distribution systems, and patient education) and computerized interventions (for example, CPOE and automated dispensing devices).

PREVENTION STRATEGIES FOR THE USE OF OTC AND COMPLEMENTARY AND ALTERNATIVE MEDICATIONS

The use of OTC and complementary and alternative medications is largely beyond the health care worker’s domain, although many of these

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
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TABLE D-2 Recommendations for the Prevention of Medication Errors in Pediatric Care

Recommended Practice

Recommending Body

Evidence Specific to Children

Source of Supporting Evidence

Computerized provider order entry

PPAG, ISMP, AHA, AHRQ, IOM, NQF, MHA, NCCMERP, AAP/NICHQ

None

Adult data/ expert opinion

Automated medication-dispensing devices

PPAG, ISMP, AHA, AHRQ

None

Adult data/ expert opinion

Pediatric presence with formulary management

PPAG, ISMP, AHA, AAP/NICHQ

None

Expert opinion

Appropriate and competent pharmacy personnel and environment

PPAG, ISMP, AHA, NQF, NCCMERP, AAP/NICHQ

None

Expert opinion

Pharmacist available on call when pharmacy is closed

PPAG, ISMP, AHA, MHA

None

Expert opinion

Policies on verbal orders

PPAG, ISMP, AHA, NQF, NCCMERP, AAP/NICHQ, JCAHO

None

Expert opinion

Clear and accurate labeling of medications

PPAG, ISMP, AHA, NQF, NCCMERP

None

Expert opinion

Quality improvement efforts with drug-use evaluation and medication error reporting and review

PPAG, ISMP, AHA, MHA, NCCMERP, AAP/NICHQ

None

Expert opinion

Access of health care workers to current clinical information and references

PPAG, ISMP, AHA, IOM, MHA, NCCMERP, AAP/NICHQ

None

Expert opinion

Emergency medication dosage calculation tools

PPAG, ISMP

None

Expert opinion

Accurate documentation of medication administration

PPAG, ISMP, MHA, NCCMERP

None

Expert opinion

Medication standardization and appropriate storage

ISMP, AHA, IOM, NCCMERP, JCAHO

None

Expert opinion

Training of all health care providers in appropriate medication prescribing, labeling, dispensing, monitoring, and administration

PPAG, ISMP, IOM, NQF, MHA, NCCMERP, AAP/NICHQ, JCAHO

None

Expert opinion

Patient education on medications

ISMP, AHA, IOM, MHA, NCCMERP, AAP/NICHQ

None

Expert opinion

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

Recommended Practice

Recommending Body

Evidence Specific to Children

Source of Supporting Evidence

Direct participation of pharmacists in clinical care

AHRQ, IOM, NQF

None

Expert opinion

Computer detection/alert systems for adverse drug events (ADEs)

AHRQ

None

Adult studies

Reduction of ADEs related to anticoagulants

AHRQ

None

Adult studies

Unit-dose drug distribution systems

AHA, AHRQ, NQF, MHA

None

Adult studies/ expert opinion

Special procedures and written protocols for high-alert medications

AHA, IOM, NQF, MHA, JCAHO

None

Expert opinion

Use of pharmaceutical software

AHA, IOM

None

Expert opinion

Pharmacy-based intravenous (IV) admixture systems

MHA

None

Expert opinion

Use of bar coding for medication administration

MHA, NCCMERP

None

Expert opinion

Standardized equipment (e.g., pumps, weight scales)

AAP/NICHQ

None

Expert opinion

Standardized measurement systems (kilograms)

AAP/NICHQ

None

Expert opinion

Standardized order sheets including areas for weight and allergies

AAP/NICHQ

None

Expert opinion

Team environment for review of orders among nurses, pharmacists, prescribers

AAP/NICHQ

None

Expert opinion

NOTE: AAP/NICHQ = American Academy of Pediatrics/National Initiative for Children’s Healthcare Quality (Berlin et al., 1998; Lannon et al., 2001; Gorman et al., 2003; NICHQ, 2005); AHA = American Hospital Association (AHA, 2002, 2005); AHRQ = Agency for Healthcare Research and Quality, report on Making Healthcare Safer (Shojania et al., 2001; AHRQ, 2005); IOM = Institute of Medicine (IOM, 2000); ISMP = Institute for Safe Medication Practices (ISMP, 2005b); JCAHO = Joint Commission on Accreditation of Healthcare Organizations (JCAHO, 2005a,b); MHA = Massachusetts Hospital Association/Massachusetts Coalition for the Prevention of Medical Errors (MCPME, 2005a,b); NCCMERP = National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP, 2005a,b); NQF = National Quality Forum (NQF, 2003, 2005); PPAG = Pediatric Pharmacy Advocacy Group (Levine, 2001; ISMP, 2002, 2005b).

Suggested Citation:"Appendix D Medication Errors: Prevention Strategies ." Institute of Medicine. 2007. Preventing Medication Errors. Washington, DC: The National Academies Press. doi: 10.17226/11623.
×

medications are taken on the advice of physicians. It is up to consumers to diagnose their problem properly, select the best medical product if it is necessary, read and understand the instructions for its use, take it properly, and know when it is time to terminate the treatment. Many OTC medication errors are due to misdosing or adverse drug–drug interactions. Patients need to understand that OTCs are drugs and, like prescription medications, have both therapeutic value and potential side effects.

A key approach for reducing OTC medication errors is the Food and Drug Administration’s (FDA) labeling requirements, mentioned in Chapter 2, which provide information on active ingredients, what the drug is for, dosing levels, and warnings about use. The information requirements on the packaging of complementary and alternative medications are more limited.

Patient self-education is the other major prevention strategy. Much information to improve patient awareness of OTC and complementary and alternative medications is currently available from the Internet, television, books, magazines, and newspapers.

In addition, there are specialized packaging technologies designed to decrease the chances of misuse, such as tamper-resistant and childproof containers and blister packaging that numbers each pill to help the user remember whether the product was taken. Pillboxes divided by time of day and day of week are another low-technology solution.

Still another approach is for the pharmacist to ask those picking up prescription drugs whether they are using any OTC or vitamin/mineral products and to advise them of any issues involved. For example, people taking blood thinners should be advised to speak to their doctor before taking vitamin E.

The committee could find no study on the efficacy of any of the above strategies for preventing medication errors in the use of OTC and complementary and alternative medications.

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In 1996 the Institute of Medicine launched the Quality Chasm Series, a series of reports focused on assessing and improving the nation’s quality of health care. Preventing Medication Errors is the newest volume in the series. Responding to the key messages in earlier volumes of the series—To Err Is Human (2000), Crossing the Quality Chasm (2001), and Patient Safety (2004)—this book sets forth an agenda for improving the safety of medication use. It begins by providing an overview of the system for drug development, regulation, distribution, and use. Preventing Medication Errors also examines the peer-reviewed literature on the incidence and the cost of medication errors and the effectiveness of error prevention strategies. Presenting data that will foster the reduction of medication errors, the book provides action agendas detailing the measures needed to improve the safety of medication use in both the short- and long-term. Patients, primary health care providers, health care organizations, purchasers of group health care, legislators, and those affiliated with providing medications and medication- related products and services will benefit from this guide to reducing medication errors.

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