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Preventing Medication Errors C Medication Errors: Incidence Rates This appendix reviews estimates of the rates of medication errors and adverse drug events (ADEs) in three care settings (hospital, nursing home, and ambulatory care) and in pediatric and psychiatric care. Where possible, error rates for the five stages of the medication-use system and at the interface between care settings are documented separately. INCIDENCE OF MEDICATION ERRORS IN HOSPITAL CARE Selection and Procurement of the Drug by the Pharmacy No studies were identified that specifically identified medication errors of this type. It is possible that these types of errors were included in studies of general medication error rates. Prescription and Selection of the Drug for the Patient: Errors of Commission Rates of prescribing errors (for example, dosing errors, prescribing medications to which the patient was allergic, prescribing inappropriate dosage forms) vary considerably from study to study and are quoted in several different ways—errors per 1,000 admissions, errors per 1,000 orders, errors per 100 opportunities for error, and preventable ADEs per 1,000 admissions (see Table C-1):
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Preventing Medication Errors TABLE C-1 Hospital Care: Prescription and Selection Errors of Commission Error rates Per 1,000 admissions—detection method 12.3 (Lesar, 2002a)—pharmacist review of written orders 29 (Winterstein et al., 2004)—prompted reporting 52.9 (Lesar et al., 1997)—pharmacist review of written orders 190 (LaPointe and Jollis, 2003)—clinical pharmacist directly participating in clinical care 1,400 (Bates et al., 1995a)—prompted reporting, chart review, review of medication orders Per 1,000 orders—detection methods 0.61 (Lesar, 2002a)—pharmacist review of written orders 2.87 (Lesar et al., 1997)—pharmacist review of written orders 3.13 (Lesar et al., 1990)—pharmacist review of written orders 53 (Bates et al., 1995a)—prompted reporting, chart review, review of medication orders Per 100 opportunities for error—detection method 1.5 (Dean et al., 2002)—pharmacist review of written orders 6.2 (Bobb et al., 2004)—pharmacist review of written orders 6.7 (Lisby et al., 2005)—direct observation, unannounced control visits, chart review 9.9 (van den Bemt et al., 2002)—pharmacist review of written orders Preventable ADEs rates Per 1,000 admissions—detection method 3.7 (Hardmeier et al., 2004)—chart review 3.9 (Bates et al., 1995b)—prompted reporting, chart review 84.1 (Nebeker et al., 2005)—review of electronic record Prescribing errors totaled 12.3 to 1,400.0 per 1,000 patient admissions: (1) 12.3 in a study of 32,683 admissions in a tertiary care hospital in New York State (Lesar, 2002a); (2) 29 in a study of about 6,000 patients in a tertiary care hospital in Florida (Winterstein et al., 2004); (3) 52.9 in a study of 211,635 admissions in a tertiary care hospital in New York State (Lesar et al., 1997); (4) 190.0 in a study of 24,538 patients in a tertiary care hospital in North Carolina (LaPointe and Jollis, 2003); and (5) 1,400 in a study of 379 patients in an urban tertiary care hospital in Massachusetts (Bates et al., 1995a). Prescribing errors occurred per order at rates ranging from 0.6 to 53 per 1,000 orders (Lesar et al., 1990; Bates et al., 1995a; Lesar et al., 1997; Lesar, 2002a). Errors per 100 opportunities for error ranged from 1.5 to 9.9 (van den Bemt et al., 2002; Dean et al., 2002; Bobb et al., 2004; Lisby et al., 2005).
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Preventing Medication Errors In the subset of studies that evaluated preventable ADEs, prescription errors associated with patient injuries ranged from 3.7 to 84.1 per 1,000 admissions (Bates et al., 1995b; Hardmeier et al., 2004; Nebeker et al., 2005). Preparation and Dispensing of the Drug Preparation and dispensing errors occurred at a rate of 2.6 per 1,000 admissions in a tertiary care hospital in Florida (Winterstein et al., 2004) (see Table C-2). Two studies focused exclusively on intravenous (IV) medications. One study, at one U.K. and two German hospitals, found a rate of preparation errors of 26 percent per observed preparation (88 preparation errors out of 337 observations) (Wirtz et al., 2003). The other study, at a tertiary and a community hospital in the United Kingdom, found a rate of preparation errors of 49 percent per observed preparation (212 preparation and administration errors out of 430 doses) (Taxis and Barber, 2003). Preparation and dispensing errors were associated with preventable ADEs at rates of 0.6 per 1,000 admissions in a Swiss study of 6,383 patients (Hardmeier et al., 2004); 1.1 per 1,000 admissions in a study of 4,031 patients at two tertiary hospitals in Boston, Massachusetts (Bates et al., 1995b); and 1.6 per 1,000 admissions in a study of 937 admissions at a tertiary hospital in Salt Lake City, Utah (Nebeker et al., 2005). Administration of the Drug As with prescribing error rates, rates of administration errors varied widely in medical and surgical units (See Table C-3). Rates per opportunity TABLE C-2 Hospital Care: Preparation and Dispensing Errors Error rates: general medications Per 1,000 admissions—detection method 2.6 (Winterstein et al., 2004)—prompted reports Error rates: intravenous (IV) medications Per preparation—detection method 26 percent (Wirtz et al., 2003) (U.K. and German study)—direct observation 49 percent (Taxis and Barber, 2003) (U.K. study)—direct observation Preventable ADEs Per 1,000 admissions—detection method 0.6 (Hardmeier et al., 2004) (Swiss study)—chart review 1.1 (Bates et al., 1995b)—prompted reporting, chart review 1.4 (Nebeker et al., 2005)—review of electronic medical record
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Preventing Medication Errors TABLE C-3 Hospital Care: Administration Errors Error rates: general medications Per 100 opportunities/doses—detection method 2.4 (Taxis et al., 1999) (German part, unit dose system)—direct observation 3 (Dean et al., 1995) (U.K. part)—direct observation 5.1 (Taxis et al., 1999) (German part, traditional system)—direct observation 6.7 (Lisby et al., 2005) (Danish study)—direct observation 6.9 (Dean et al., 1995) (U.S. part)—direct observation 8 (Taxis et al., 1999) (U.K. part)—direct observation 10.8 (Barker et al., 2002)—direct observation 14.9 (Tissot et al., 2003) (French study)—direct observation Error rates: general medications Per 1,000 admissions—detection method 5.8 (Winterstein et al., 2004)—prompted reports Error rates in intensive care units (ICUs) Per opportunity/dose—detection method 3.3 percent (Calabrese et al., 2001)—direct observation 6.6 percent (Tissot et al., 1999)—direct observation Error rates: IV medications only Per opportunity/dose—detection method 34 percent (Wirtz et al., 2003) (U.K. and German study)—direct observation 49 percent (Taxis and Barber, 2003) (U.K. study) (includes both preparation and administration)—direct observation Preventable ADEs Per 1,000 admissions—detection method 2.1 (Bates et al., 1995b)—prompted reporting, chart review 17.9 (Nebeker et al., 2005)—review of electronic medical record for error or dose ranged from 2.4 to 14.9 percent: (1) 2.4 percent in a German hospital using a unit dose system (1,318 opportunities for error) (Taxis et al., 1999); (2) 3 percent in a U.K. tertiary hospital (2,756 opportunities for error) (Dean et al., 1995); (3) 5.1 percent in a German hospital using a traditional system (973 opportunities for error) (Taxis et al., 1999); (4) 6.7 percent in a Danish tertiary hospital (2,467 opportunities for error) (Lisby et al., 2005); (5) 6.9 percent in a U.S. tertiary hospital (919 opportunities for error) (Dean et al., 1995); (6) 8 percent in a U.K. hospital using a ward pharmacy system (842 opportunities for error) (Taxis et al., 1999); (7) 10 percent (excluding wrong time errors) in 24 hospitals in Georgia and Colorado (2,765 medication doses) (Barker et al., 2002); and (8) 11 percent (excluding wrong-time errors) (Tissot et al., 2003) in a French tertiary hospital (523 opportunities for error).
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Preventing Medication Errors Another study, in a tertiary hospital in Florida, involving about 6,000 patients (the authors could not report precisely the number of patients involved), found an administration error rate of 5.8 per 1,000 admissions (Winterstein et al., 2004). Similar rates to those above have been observed in intensive care unit (ICU) studies. In a study focusing on high-alert medications administered in ICUs in five U.S. tertiary care teaching hospitals, an administration error rate of 3.3 percent was found (5,744 observations) (Calabrese et al., 2001). In another study, carried out in a medical ICU in a French hospital, an administration error rate of 6.6 percent was observed (2,009 medication administration interventions by nurses) (Tissot et al., 1999). Higher rates were seen in studies that focused exclusively on IV medications—34 percent (93 errors out of 278 observed administrations) (Wirtz et al., 2003) and 49 percent (212 preparation and administration errors out of 430 doses) (Taxis and Barber, 2003). Two studies looking at preventable ADEs occurring during the administration stage found rates of 2.1 per 1,000 admissions (in a study of 4,031 patients at two tertiary hospitals in Boston, Massachusetts [Bates et al., 1995b]) and 17.9 per 1,000 admissions (in a study of 937 admissions at a tertiary hospital in Salt Lake City, Utah [Bates et al., 1995b; Nebeker et al., 2005]). Monitoring of the Patient for Effect Rates of preventable ADEs resulting from errors in the monitoring of patients were reported in two studies as 0.6 per 1,000 admissions (Hardmeier et al., 2004) and 32 per 1,000 admissions (Hardmeier et al., 2004; Nebeker et al., 2005). (See Table C-4). ADEs during Hospitalization Five major studies examined the incidence of ADEs occurring during hospitalization (see Table C-5). Using hospital admissions during the period 1990–1993, investigators at LDS Hospital, Salt Lake City, Utah, found that 2,227 out of 91,574 patients experienced ADEs during hospitalization, a rate of 2.43 ADEs per 100 admissions (Classen et al., 1997). Almost 50 percent of the identified ADEs were thought to be preventable. Extrapolat- TABLE C-4 Hospital Care: Monitoring Errors Preventable ADEs Per 1,000 admissions—detection method 0.6 (Hardmeier et al., 2004) (Swiss study)—chart review 32 (Nebeker et al., 2005)—review of electronic medical record
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Preventing Medication Errors TABLE C-5 Hospital Care: ADE Incidence During Hospitalization Study ADEs per 100 Admissions ADEs per 1,000 Patient-Days Proportion of ADEs Preventable Classen et al., 1997 2.4 Not given About 50 percent (out of 2,227 ADEs in study) Senst et al., 2001 4.2 Not given 15 percent (out of 74 ADEs in the study Bates et al., 1995b 6.5 11.5 28 percent (out of 247 ADEs in study) Jha et al., 1998 Not given 21 27 percent (out of 617 ADEs in study) Nebeker et al., 2005 52 70 27 percent (out of 483 ADEs in study) ing these figures nationally and assuming 32 million admissions annually, the authors concluded that 770,000 hospital patients in America would experience an ADE annually. Another study, conducted at two tertiary care hospitals in Boston, involved 4,031 adult admissions. Carried out in 1993 under the Adverse Drug Events Prevention Study, this study found an overall ADE rate of 6.5 per 100 nonobstetric admissions (or 11.5 ADEs per 1,000 patient-days); of these, 28 percent were judged preventable (Bates et al., 1995b). Of the ADEs, 1 percent were fatal (none preventable), 12 percent life-threatening, 30 percent serious, and 57 percent significant. Of the life-threatening and serious ADEs, 42 percent were judged preventable. Assuming an ADE rate of 6.5 per 100 nonobstetric admissions and 25 million nonobstetric admissions to short-term hospitals annually, the authors estimated an annual rate of 1.6 million ADEs in U.S. hospitals. A third study, utilizing data on ADEs collected in the summer of 1998 from a four-hospital academic medical network, estimated the ADE rate during hospitalization to be 4.2 per 100 admissions (Senst et al., 2001). Fifteen percent of these ADEs were judged preventable. At a tertiary hospital in Boston, in a study carried out from October 1994 to May 1995, 617 ADEs were observed, 166 of which were judged preventable (Jha et al., 1998). After adjustment for the sampling scheme, the ADE rate was estimated to be 21 per 1,000 patient-days. Much higher ADE rates were observed in the most recent study, involving a highly computerized hospital that had implemented electronic health records (Nebeker et al., 2005). Computerized order checking was fully functional for allergies, many drug–drug interactions, and limited drug– disease interactions. The system did not, however, feature sophisticated decision-support algorithms. Among 937 hospital admissions, 483 clinically significant inpatients ADEs were identified—52 per 100 admissions,
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Preventing Medication Errors or 70 per 1,000 patient-days. Medication errors contributed to 27 percent of the ADEs. Of all the ADEs, 9 percent resulted in serious harm, 22 percent in additional monitoring and interventions, 32 percent in interventions alone, and 11 percent in monitoring alone; 27 percent should have resulted in additional interventions or monitoring. Three smaller studies found similar ADE rates. A 37-day study at a Boston tertiary hospital found 27 ADEs (15 considered preventable), for a rate of 6.4 ADEs per 100 admissions or 9.1 ADEs per 1,000 patient-days (Bates et al., 1993). Another small study at the same hospital found 25 ADEs (5 considered preventable), for a rate of 6.6 ADEs per 100 admissions or 14.7 ADEs per 1,000 patient-days (Bates et al., 1995a). In a study of 157 hospitalized patients aged 70 and older, 28 probable ADEs were observed, for a rate of 17.8 ADEs per 100 admissions (Gray et al., 1998). Just over half the ADEs were considered preventable. Prescription and Selection of the Drug for the Patient: Errors of Omission Errors of omission occur when a medication necessary for the appropriate care of hospitalized individuals is not prescribed. After reviewing the published literature on medication errors of omission within acute care, the committee identified three broad categories of studies: studies on treatment of acute coronary syndromes, on antibiotic prophylaxis, and on thrombosis prophylaxis (see Table C-6). TABLE C-6 Hospital Care: Prescription and Selection Errors of Omission Patients discharged with diagnosis of acute myocardial infarction Percentage of patients given aspirin within 24 hours of hospitalization 84.9 (Roe et al., 2005) (NSTEMI) 88 (Roe et al., 2005) (STEMI) 92.4 (Granger et al., 2005) 93 (Sanborn et al., 2004) Percentage of patients prescribed aspirin at discharge 53 (Krumholz et al., 2003) 76.8 (Petersen et al., 2001) 83.8 (Roe et al., 2005) (NSTEMI) 84.8 (Petersen et al., 2003) 85.6 (Alexander et al., 1998) 88.9 (Roe et al., 2005) (STEMI) 93.4 (Granger et al., 2005)
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Preventing Medication Errors Percentage of patients given beta-blockers within 24 hours of hospitalization 66 (Sanborn et al., 2004) 72.2 (Roe et al., 2005) (NSTEMI) 77.8 (Roe et al., 2005) (STEMI) 78 (Granger et al., 2005) Percentage of patients prescribed beta-blockers at discharge 53 (Krumholz et al., 2003) 56.1 (Petersen et al., 2001) 59.1 (Alexander et al., 1998) 67.3 (Petersen et al., 2003) 78.3 (Roe et al., 2005) (NSTEMI) 78.9 (Granger et al., 2005) 83.4 (Roe et al., 2005) (STEMI) Percentage of patients prescribed angiotensin-converting enzyme (ACE) inhibitors at discharge 51.2 (Roe et al., 2005) (NSTEMI) 51.7 (Alexander et al., 1998) 58 (Roe et al., 2005) (78) (STEMI) 58.5 (Petersen et al., 2001) 67.6 (Petersen et al., 2003) 73.1 (Granger et al., 2005) Rates of antibiotic prophylaxis within surgical studies Percentage of procedures in which patients prescribed antibiotics 70 (Vaisbrud et al., 1999) 74 (Heineck et al., 1999) 92 (Gupta et al., 2003) 95 (Bedouch et al., 2004) 97 (van Kasteren et al., 2003) 97.5 (Quenon et al., 2004) Rates of thromboembolic prophylaxis within surgical studies Percentage of procedures in which thromboembolic prophylaxis carried out 5 at high risk, 23.0 at medium risk (Ahmad et al., 2002) 22 (Aujesky et al., 2002) 29 (Scott et al., 2003) 31.5 at the highest risk, 81 at high risk, 93 at moderate risk (Tan and Tan, 2004) 46.4 (Ageno et al., 2002) 49.4 (Chopard et al., 2005) 71 (Learhinan and Alderman, 2003) 81 (Freeman et al., 2002) 90 (Campbell et al., 2001) NOTE: STEMI = acute ST-segment elevation myocardial infarction; NSTEMI = non-STEMI.
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Preventing Medication Errors Acute Coronary Syndromes The committee reviewed seven studies on quality of care for acute myocardial infarction. Six of these studies determined prescription rates for indicated medications at discharge (Alexander et al., 1998; Petersen et al., 2001; Krumholz et al., 2003; Petersen et al., 2003; Roe et al., 2005; Granger et al., 2005). For patients discharged with a diagnosis of acute myocardial infarction, aspirin was prescribed to 53 to 93.4 percent of ideal candidates (those with no known contraindication). Beta-blockers were prescribed to 53 to 83.4 percent of ideal candidates, and angiotensin converting enzyme (ACE) inhibitors to 58.5 to 83.4 percent of ideal candidates. Three studies described rates of aspirin and beta-blocker use within the first 24 hours of hospitalization (Sanborn et al., 2004; Roe et al., 2005; Granger et al., 2005). Within the first 24 hours of hospitalization for a myocardial infarction, 66 to 78 percent of patients had received beta-blockers and 84.9 to 93 percent aspirin. Antibiotic Prophylaxis The committee identified six studies that described rates of antibiotic prophylaxis for surgical procedures (Heineck et al., 1999; Vaisbrud et al., 1999; van Kasteren et al., 2003; Gupta et al., 2003; Bedouch et al., 2004; Quenon et al., 2004). Rates of antibiotic prophylaxis ranged from 70 to 98 percent within the surgical studies. Although the rates of prescribing any antibiotic were high, antibiotic prophylaxis for surgical procedures requires that the appropriate antibiotic be selected, that the appropriate dose be prescribed, that the drug be administered at the appropriate time, and that the duration of therapy be correct. Absolute compliance with all of these elements of drug therapy was much lower—as low 3 percent in one study (Gupta et al., 2003). Thrombosis Prophylaxis The committee identified nine studies that determined rates of thromboembolic prophylaxis in at-risk hospitalized patients (Campbell et al., 2001; Ageno et al., 2002; Ahmad et al., 2002; Aujesky et al., 2002; Freeman et al., 2002; Learhinan and Alderman, 2003; Scott et al., 2003; Tan and Tan, 2004; Chopard et al., 2005). Thromboembolic prophylaxis includes both mechanical means, such as lower-extremity compression hose, and pharmacological means, such as subcutaneous heparin. Because medications are recommended in individuals at high risk for thrombosis, the committee included these studies.
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Preventing Medication Errors Rates of thromboembolic prophylaxis varied widely—from 5 to 81 percent. Rates of appropriate thromboembolic prophylaxis tended to be higher in surgical patients and in those at lower risk for thrombosis. One study also noted that thromboembolic prophylaxis was prescribed inappropriately in 38 percent of patients without risk factors for thrombosis (Aujesky et al., 2002). INCIDENCE OF MEDICATION ERRORS IN NURSING HOMES Studies on the incidence of medication errors and ADEs in nursing homes use a number of different definitions, measures, and metrics. Hence, as with hospital studies, it is difficult to compare the results across studies. Drug Procurement and Dispensing Drug procurement and dispensing in the nursing home differ from hospital practice because the pharmacy is generally offsite. Handler and colleagues (2004) identified several aspects of drug delivery: (1) issues of packaging (e.g., patient-specific unit-dose packaging, patient-specific blister packages, 7-day strips of medication, color-coded drug administration devices, or medication bottles similar to usual community practice); (2) access to urgent medications, such as stock drugs in an emergency box; and (3) drug delivery when medications are added or changed, which may require hours to days (Handler et al., 2004). There is minimal research on how the approaches to addressing these issues affect medication safety. When several pharmacies provide medications to a single nursing facility, staff must learn to use numerous systems, a practice that violates the fundamental safety principle of standardization. An evaluation of the medication-use system in one nursing home found that the facility’s 72 patients were served by seven pharmacies, and the consultant pharmacist had no relationship with any of them (Cooper, 1987). The charge nurse verifying refill needs required 8–12 hours per 100 beds per month. Qualitative data underscore the issues of time and error associated with this refill process (Vogelsmeier et al., 2005). Gupta and colleagues (1996a,b) noted that only 8.4 percent of the 19,932 Medicaid patients they studied used a single pharmacy, and the number of pharmacies used was associated with mortality rates (Gupta et al., 1996a,b). Administration Errors The committee identified a few studies that measured the incidence of medication administration errors in nursing homes (see Table C-7). A well-known early study using direct observation of medication administration in
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Preventing Medication Errors TABLE C-7 Nursing Home: Administration Errors Error rates Per 100 opportunities/doses—detection method 6 (Cooper et al., 1994)—direct observation 12.2 (Barker et al., 1982)—direct observation 14.7 (Barker et al., 2002)—direct observation 20 (Baldwin, 1992)—direct observation 58 nursing homes identified a mean error rate of 12.2 percent (range 0–59 percent over the 58 nursing homes), where an error was defined as a dose administered or omitted that deviates from the physician’s orders (Barker et al., 1982). The direct observation procedure used in this study detects primarily errors in transcribing and administration. If out-of-date and unsigned orders were excluded, the error rate was 8 percent. The most common error types were unauthorized drug (44.8 percent) and omission (41.5 percent), followed by wrong dose (11 percent), wrong route (2 percent), and wrong form (0.4 percent). Most of the errors involving unauthorized drugs were due to out-of-date orders. Wrong-time errors were not recorded in this study. Because an error is defined as a discrepancy between the drug ordered and the drug received, errors detected by observation may be due to transcription or administration error, but observational studies do not distinguish the phase in which the error originates. In a 2-year study apparently using observation in one nursing home, Cooper (1987) also concluded that omissions were the most common type of administration error (65 percent of errors). Many of the omissions were caused by patient refusal or sleeping, but the charting often implied that the drug had been administered. A later study of error rates in skilled nursing facilities and hospitals found an average rate of 21.6 percent in 12 skilled nursing facilities in Georgia and Colorado, using the same direct observation method of error detection and defining an error as a discrepancy between the dose ordered and the dose received. The range of error rates across the 12 nursing facilities was 5.7 to 49.5 percent. The average error rate was not statistically different from the 14.4 percent rate for hospitals (Barker et al., 2002). Excluding wrong-time errors, the rate was 14.7 percent for skilled nursing facilities and 9.9 percent for hospitals. About 7 percent of the errors were judged by a physician panel to be potential ADEs. The rank order of error types was wrong time (9.9 percent of doses, 45.4 percent of errors), omission (7 percent of doses, 32.4 percent of errors), and wrong dose (3.1 percent of doses, 14.2 percent of errors). Using similar observational methods, Baldwin (1992) detected a 20 percent medication administration error rate in a study of 733 residents of 35 domiciliary homes in North Carolina (error rate range 3–44 percent
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Preventing Medication Errors 2.3 per 100 admissions or 6.6 per 1,000 patient days; 19 percent of the ADEs were considered preventable. A later prospective study analyzed 1,197 consecutive admissions (corresponding to 922 patients and 10,164 patient days) at a general pediatric unit and a pediatric ICU in a metropolitan medical center (Holdsworth et al., 2003). Seventy-six ADEs were identified—6 per 100 admissions or 7.5 per 1,000 patient days. INCIDENCE OF MEDICATION ERRORS IN PSYCHIATRIC CARE Many studies of medication errors associated with psychotropic medication were conducted as part of either larger general medical–surgical studies or ADE-reporting databases or were limited to geriatric populations in settings not restricted to psychiatric care, such as nursing homes and ambulatory clinics. General Medical–Surgical Studies An 18-month study in a tertiary care hospital used computerized monitoring to identify 701 ADEs, including 18 due to psychotropic drugs (2.4 percent) (Classen et al., 1991). A study using several active detection approaches, including daily chart review, among 4,031 medical–surgical inpatients found 247 ADEs (6.5 per 100 admissions) (Bates et al., 1993). Psychotropic medications represented 7 percent of all medication errors. A more recent study of hospitalized patients found that psychotropic drugs accounted for 0.41 percent of serious medication errors (Bates et al., 1998). After CPOE and a team intervention to prevent ADEs were implemented, this rate fell to 0.16 percent. A study using pharmacist detection of prescribing errors with potential for harm in a teaching hospital found that among 11,186 errors, 146 (1.3 percent) were associated with psychotropic medications (Lesar et al., 1997). Geriatric Populations in Settings Not Restricted to Psychiatric Care Older patients may be particularly vulnerable to the harmful effects of psychotropic medications (Monette et al., 1995). A 1-year study of 18 nursing homes reported that among 546 ADEs (1.89 per 100 resident-months), 193 (35 percent) were due to psychotropic medications (Gurwitz et al., 2000). A greater proportion of ADEs due to psychotropic medications (63 percent), as compared with all other drug classes (43 percent), was judged to be preventable. One study found that psychotropic medications represented 23 percent of inappropriate medication orders prescribed in nursing homes (Beers et
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Preventing Medication Errors al., 1992). Two other studies found that older adults in ambulatory settings received even higher proportions of inappropriate psychotropic medications—27 percent (Aparasu and Fliginger, 1997) and 44 percent (Mort and Aparasu, 2000). Psychiatric Hospitals The committee identified two studies that examined the incidence of medication errors in a mental health setting (see Table C-25). The more recent of these retrospectively studied 31 state psychiatric inpatients over 2 months of care, for a total of 1,448 patient-days (Grasso et al., 2003). Nine errors were self-reported using the usual incident reporting process, whereas an independent multidisciplinary review team found 2,194 errors for the same 31 patients and episodes of care. There were 1,443 administration errors, accounting for more than half of the total (66 percent); 498 transcription errors (23 percent); 239 prescription errors (11 percent); and 14 dispensing errors (less than 1 percent). Nineteen percent of errors were rated as having a low risk of harm, 23 percent as having a moderate risk, and 58 percent as having a high risk. The other study of ADEs included both inpatient and outpatient settings and focused on the frequency, severity, causes, and costs of ADEs in an integrated system of care that included medical and psychiatric patients (Senst et al., 2001). In this setting, medication errors were implicated in 13.6 percent of psychiatric readmissions, with medication nonadherence (considered part of the usual lexicon of medication errors) being implicated in 69 percent of hospitalizations. The rate of ADEs during psychiatric hospitalization was 4.2 per 100 admissions. TABLE C-25 Psychiatric Care: Medication Errors Prescribing errors Errors per 1,000 patient-days—detection method 165 (Grasso et al., 2003)—chart review Transcription errors Errors per 1,000 patient-days—detection method 334 (Grasso et al., 2003)—chart review Administration errors Errors per 1,000 patient-days—detection method 997 (Grasso et al., 2003)—chart review Dispensing errors Errors per 1,000 patient-days—detection method 10 (Grasso et al., 2003)—chart review ADEs Errors per 100 admissions—detection method 4.2 (Senst et al., 2001)—chart review
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Preventing Medication Errors The committee’s literature review yielded no reports focused specifically on medication errors in outpatient mental health settings, nor have there been medication error incidence studies in settings where psychologists have prescriptive authority. Finally, no studies were found on the incidence and characteristics of medication errors in substance abuse settings, including all settings where medical detoxification of individuals treated for alcohol, sedative hypnotic, or opiate withdrawal occurs. All of these are areas in which data are badly needed. ERROR RATES: MUCH MORE NEEDS TO BE DONE Where incidence rates of medication errors have been systematically measured, such errors have been found to be common and at unacceptably high levels. Errors in the administration of IV medications appear to be particularly prevalent. Reasonably well-researched stages of the medication-use process include prescribing, dispensing, and administering in hospitals; prescribing in ambulatory clinics; dispensing in community pharmacies; prescribing in the home care setting; medication adherence in the self-care setting; and inappropriate use of psychotropic drugs. Where it is possible to compare the results of multiple studies, estimates of error rates vary widely. Much but not all of this variation can be explained by differences in definition and identification methods. Even when the definition of error is standardized and the same identification method is used, however, substantial variation in administration error rates by institution have been found (Barker et al., 2002). Taking account of this variability, the underlying error rates are unacceptably high. Over the past decade, much scholarly activity and substantial government resources have been directed at determining the extent and scope of medication errors. Yet there are still broad aspects of the medication-use process for which we have little or no understanding of error rates. These include the selection and procurement of medications, monitoring of the effectiveness of medications in all care settings, medication use in schools, medication use in psychiatric care, and the use of over-the-counter and complementary and alternative medications. The committee concludes that still greater effort is needed in all care settings to identify the incidence of medication errors—both to measure the extent and scope of such errors and to assess the impact of error prevention strategies. REFERENCES Ageno W, Squizzato A, Ambrosini F, Dentali F, Marchesi C, Mera V, Steidl L, Venco A. 2002. Thrombosis prophylaxis in medical patients: A retrospective review of clinical practice patterns. Haematologica 87(7):746–750.
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Representative terms from entire chapter: