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Medication safety in acute care in Australia: where are we now? Part 1: a review of the extent and causes of medication problems 2002–2008

Medication safety in acute care in Australia: where are we now? Part 1: a review of the extent... Background: This paper presents Part 1 of a two-part literature review examining medication safety in the Australian acute care setting. This review was undertaken for the Australian Commission on Safety and Quality in Health Care to update a previous national report on medication safety conducted in 2002. This first part of the review examines the extent and causes of medication incidents and adverse drug events in acute care. Methods: A literature search was conducted to identify Australian studies, published from 2002 to 2008, on the extent and causes of medication incidents and adverse drug events in acute care. Results: Studies published since 2002 continue to suggest approximately 2%–3% of Australian hospital admissions are medication-related. Results of incident reporting from hospitals show that incidents associated with medication remain the second most common type of incident after falls. Omission or overdose of medication is the most frequent type of medication incident reported. Studies conducted on prescribing of renally excreted medications suggest that there are high rates of prescribing errors in patients requiring monitoring and medication dose adjustment. Research published since 2002 provides a much stronger Australian research base about the factors contributing to medication errors. Team, task, environmental, individual and patient factors have all been found to contribute to error. Conclusion: Medication-related hospital admissions remain a significant problem in the Australian healthcare system. It can be estimated that 190,000 medication-related hospital admissions occur per year in Australia, with estimated costs of $660 million. Medication incidents remain the second most common type of incident reported in Australian hospitals. A number of different systems factors contribute to the occurrence of medication errors in the Australian setting. result in the desired outcome, medicines are not without Background Use of medications is central to modern health care, and risk, and problems or unexpected outcomes may arise. nearly all patients visiting a hospital will receive one or more medicines during their hospital stay or upon dis- As medicines are taken so commonly, sometimes prob- charge. While in the majority of cases medicines use will lems can occur in their prescription, dispensing and Page 1 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 administration which can be termed "medication inci- and progress in research on contributing factors to these dents". A proportion of these medication incidents result problems. There was also a need to review more recent in patient harm and are called "adverse drug events" developments in research examining the implementation (ADEs). Some ADEs result from the manner in which the of, and evidence base for, strategies to improve medica- medication is used (such as an error or system failure). tion safety in the Australian setting. Other ADEs are termed "adverse drug reactions" and can result from the pharmacological properties of the medica- This paper presents Part 1 of this two-part review. Part 1 tion itself when it is taken alone or in combination with examines the extent and causes of medication incidents other medications. Adverse events associated with medi- and adverse drug events in acute care in Australia to 2008. cations are common, affect a substantial number of peo- It is hoped this information will inform policy makers, ple and contribute a significant burden to health care health care professionals, managers and researchers about costs. the areas in which significant problems with medication safety continue. In 2000, the Australian Council for Safety and Quality in Health Care was established by the Australian Health Part 2 examines the evidence for practices to improve Ministers to provide a focus of national leadership in tack- safety in the Australian setting, barriers and facilitators to ling the issues of patient safety. As part of its work, in 2002 the implementation of these strategies and priorities for the Council commissioned a literature review of medica- further research and policy-development. Part 2 is pre- tion safety in the Second National Report on Patient Safety sented as a separate paper. Report – Improving Medication Safety [1]. Amongst the find- ings of the review was that 2–3% of all hospital admis- Methods sions in Australia were medication-related. A range of Search strategy errors and system failures including errors in prescribing, A literature search was undertaken to identify studies con- administration and dispensing were found to occur in ducted in the acute health care setting in Australia since hospitals in Australia. There was limited Australian the time of publication of the former Australian Council research on the causes of these errors although it was rec- for Safety and Quality in Health Care Second National ognised that most errors resulted from a series of system Report on Patient Safety – Improving Medication Safety [1]. failures rather than the actions of particular individuals. Searches were primarily undertaken by the New South Some commonly associated factors identified included a Wales (NSW) Medicines Information Centre St Vincent's lack of robust systems for prescription or ordering of med- Hospital, Darlinghurst, NSW. ications and problems in the transfer of patient informa- tion between hospital and community settings. Evidence The search strategy for Part 1 of the review was designed was found to support the use of a range of strategies to to identify studies undertaken in Australia from 2002 to improve medication safety including computerised (elec- 2008 on the extent and causes of medication incidents tronic) prescribing with decision support, adverse drug and adverse drug events in acute care. event alerting systems, bar coding, clinical pharmacist services, services to improve information transfer between Searches were conducted in March and April 2008 in different settings and individual patient medication sup- Medline (1950 – March Week 1 2008), EMBASE (1980 – ply in hospitals. Careful implementation of computerised March Week 1 2008), Pre-Medline and CINAHL (1982 – prescribing with clinical decision support systems in Aus- April Week 2 2008) using criteria relevant to the general tralia was identified as a priority. However, it was recog- headings in the former Council's Second National Report on nised that there was an urgent need for more research Patient Safety – Improving Medication Safety [1]. All searches examining the implementation and effectiveness of the were limited to 2002–2008. various strategies in the Australian setting. Search terms used included adverse drug event, adverse In 2006, the former Council was replaced by the Austral- drug reaction, Australia, Australian, drug, error, event, exp ian Commission on Safety and Quality in Health Care. adverse drug reaction reporting systems, exp Australia, exp The Commission's roles include the leadership and coor- drug surveillance program, exp drug therapy, exp hospital, dination of strategies to improve safety and quality in exp hospitalization, exp hospitals, exp medication error, health care through identifying issues and policy direc- exp medication systems, exp patient safety, exp physi- tions, providing recommendations for action and advice cian's practice patterns, exp quality assurance, exp safety to Health Ministers and publicly disseminating informa- management, healthcare, hospital, incident, medication tion on safety and quality [2]. errors, medication:, medication?, medicine:, medicine?, misadventure, mishap, mistake, problem. The exp The current Commission required an updated review to (explode) function was used in the relevant databases to examine current trends in medication safety problems search for the subject heading as well as any more specific Page 2 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 terms related to that subject heading. This expanded the identified at the time of admission, but not treated. A fur- results to include records about the broader topic and ther 1.2% of admissions were associated with an adverse related topics. drug reaction that occurred during hospital stay [3]. Use of morbidity records alone is likely to under-estimate the The database search was supplemented with review of rel- incidence of these events as it has been demonstrated that evant reports and resources on the Australian Commis- while accurate, the adverse drug reaction codes are under- sion on Safety and Quality in Health Care website http:// reported [5]. The second study assessed the incidence of www.safetyandquality.gov.au/ including publications of adverse drug reactions in oncology patients [4]. It the former Australian Council for Safety and Quality in included both adverse drug reactions present on admis- Health Care and incident reports from State Government sion and occurring during hospital stay, finding that 74% sites. of oncology admissions were associated with an adverse drug reaction, with a median of 2 adverse drug reactions Selection of studies for review per admission. Overall 47% were potentially preventable. This review focussed on the acute care setting in Australia, Patients were asked to rate the impact of the adverse drug studies undertaken in the community setting were reaction on a scale from 0 (no impact at all) to 6 (totally excluded. Studies included in examining the extent and changed my life). Fifty three percent of patients rated the causes of medication incidents and adverse drug events at reaction at four or above with 19% rating the adverse drug the systems level were: reaction as "totally changed my life" [4]. - adverse drug event monitoring studies; The inclusion of these studies with the results from the previous Second National Report on Patient Safety Improving - medication incident monitoring studies (including Medication Safety [1] (See table S1 – Additional file 1) still studies where medication incidents were reported on suggests an overall rate of medicine related hospital as a subset); admissions in Australia of between 2% and 3%. - quantitative reports of medication incidents (includ- Attendances to the emergency department have also been ing prescription errors, dispensing errors, administra- included (See table S1 – Additional file 1). Since 2002, tion errors); there has been one new study undertaken in the paediatric population [6] and one study in the adult population [7]. - qualitative studies that examined causes of medica- Results from the general population of 8.3% of adult tion incidents (prescribing, administration and medi- emergency attendances (not admitted) being medicine cation management deficiencies). related [8] pertain to data collected in 1993. A more recent study found an adverse drug reaction rate of 1.4% in Where appropriate summary data tables from the former emergency department attendances (including those sub- Council's Second National Report on Patient Safety – Improv- sequently admitted) and another 18 adverse drug events ing Medication Safety [1] were updated with information documented [7], but an overall incidence rate of emer- from new studies and included in the review. gency department attendances due to medication related problems was not able to be calculated. The emergency Case reports of medication errors leading to near misses department attendance rate of medicine-related attend- or adverse drug events were excluded, as were adverse ances is not dissimilar to the community estimates that events or incidents specific to only one type of medicine. 10.4% of people attending a general practitioner had had an adverse drug event in the previous six months [9]. Results and Discussion The extent of medication-related hospital admissions Preventability estimates for medication-related hospital Medication-related hospital admissions represent prob- admissions and adverse drug reactions associated with lems with medications which may originate either within hospitalisation suggest between one third and three quar- the community or within a hospital. Previous studies had ters are potentially preventable (Table 1). indicated between 2% and 3% of all admissions were medication-related. Two new studies, published since Two other studies give insight into adverse drug reactions 2002 give additional insight into the incidence of medi- during hospitalization, but not incidence figures. These cine-related hospital admissions in Australia [3,4]. One used the hospital morbidity coding records for Western used the hospital morbidity records to determine the inci- Australia [10,11]. One found the trend over time in dence of adverse drug reactions, finding 1.3% of admis- adverse drug reactions associated with hospital admis- sions were associated with an adverse drug reaction at the sions had increased five-fold between 1981–2002, from time of the admission and that required treatment [3]. 2.5 per 1000 person years to 12.9 per 1000 per years [10]. Another 0.3% of admissions had an adverse drug reaction This is similar to what was reported from South Australia Page 3 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 1: Preventability of adverse medicine events associated with hospitalisation or admissions due to medication-related problems Total number of Percentage Percentage Percentage medicine-related considered considered considered problems or definitely avoidable probably or probably not or admissions possibly avoidable definitely unavoidable Titchen et al., 2005 Hospital Paediatric 25 36% [35] NSAID ADRs Easton et al., 2004 Paediatric admissions 81 46.9% 30.9% [36] Easton-Carter et al., Paediatric emergency 187 51.3% 36.9% 2003 [6] department attendances Chan et al., 2001 [37] Geriatric admissions 73 53.4 23.3 23.3 Lau et al., 2004 [4] Hospital Oncology 454 1.6% 46.1% 53.4% ADRs Dartnell et al 1996 General admissions 55* 5% 60% 35% [38] Sarkawi et al, 1995 Medical admissions 35* 23% 46% 31% [39] Easton 1998 [40] Paediatric admissions 48* #67% 29% Ng 1996 [41] Geriatric admissions 31 3% 29% 68% * – overdose excluded; # – category not used; + – 2 cases not assessable. ADRs = adverse drug reactions; NSAID = non-steroidal anti- inflammatory drug. Note: estimates of adverse drug event preventability in the community from one study were 23% [9]. [1], with the South Australian results showing a strong Overall, these data suggest medication-related hospital correlation with medication use [12], suggesting the admissions still represent a significant burden on the Aus- increase is related to changes in medication use rather tralian community. Based on annual hospital admissions than an increased incidence of events. The second study data for 2006–07 in which there were 7.6 million separa- reported "repeat" adverse drug reactions, finding that tions, it can be estimated that there are approximately "repeat" adverse drug reaction-related hospitalisations 190,000 medicine related hospital admissions in Aus- increased at a faster rate than the overall rate of adverse tralia each year with an estimated cost of $660 million. drug reaction hospitalisations, with estimates that repeat adverse reaction hospitalisations accounted for 30% of all Adverse events associated with intra-hospital transfers adverse drug reaction hospitalisations by 2003 [11]. This Evidence also highlights the potential problem of medica- result should be interpreted cautiously. "Repeat" adverse tion errors occurring as a result of intra-hospital transfer, drug reactions included another admission for an adverse particularly after hours. A 2006 study assessing adverse drug reaction not a repeat admission for the same adverse events occurring within 72 hours of discharge from the drug reaction. Further, the results have not been adjusted intensive care unit found 17 (10%) of 167 discharges were for length of follow-up. Cytotoxics and hormones associated with an adverse event, with 52% preventable. accounted for a larger proportion of repeat admissions While not focused specifically on medications, 47% of the than first admissions [11], which may indicate that treat- adverse events were related to fluid management. Eighty- ment patterns for the underlying diseases impacted on the two percent of the discharges associated with adverse overall population available for repeat admissions. High events were discharges that occurred after hours or at rates of adverse drug reactions in the oncology population weekends [13]. have been reported [4]. Page 4 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Medication incidents in acute care monly implicated. The peak time of day for medication Incident reporting from Western Australia and New South incidents is at 0800 – 0900 hours and 2000 – 2100 hours Wales has been compared with that from South Australia in both WA and NSW. Nurses reported the majority of reported in the Second National Report on Patient Safety- incidents. Improving Medication Safety (Table 2). Medication inci- dents remain the second most frequent incident reported, A South Australian survey of 186 doctors and 587 nurses with falls being the predominant incident. As a propor- (70.7% and 73.6% response rate respectively) found that tion of all incidents, medication incidents were similar 100% of nurses stated they always reported a medicine across WA and SA, with a lower percentage reported in error that required giving a patient corrective treatment, NSW. Omission and overdose remain the most common compared to only 40% of the doctors, while less than 20% type of medication incident, with failure to read or mis- of each group stated they reported near miss medication reading the chart and failure to follow protocol the most errors [14]. Lack of feedback, the form taking too long to commonly cited causes. The majority of medication inci- complete, the perception that the incident was trivial and dents cause no harm or only minor harm. Analgesics and the ward being busy, were the most common reasons anticoagulants appear to be the medicines most com- cited for not reporting an incident [14]. Table 2: Medication incident reports, SA, WA and NSW SA (pre 2002) [1] WA 03/04 [42] WA 04/05 [43] WA 05/06 [44] NSW 05/06 [45] Number of 26999 23189 21693 20799 123404 incidents # # Medication 7155 (26.5%) 23.5% 24.0% 5068 (24.4%) 17367 (14.1%) incidents Outcome No injury 69% 87.0% 85.0% 85.0% 82%* Most common type of medication incident Omission 27.9% 36.0% 36.0% 37.0% Overdose 19.5% 18.0% 17.0% 19.0% Prescription or 14.0% order error Unclear or 6.0% incomplete order Dispensing error 3.3% 2.0% Most common reason cited for medication incident Failure to read or 52% 49.0% 36.0% misread Failure to follow 23.0% 26.0% policy Medicines implicated Cardiovascular; Analgesics; Anticoagulants Analgesics; Analgesics; Analgesics, CNS, Diuretics; Respiratory; Anticoagulants; Anticoagulants; Endocrine, Antibiotics Proton Pump inhibitors Diuretics; Steroids Insulins; Diuretics @ = none or minor; # = estimated from graph; * = Severity Assessment Code (SAC) 3 or SAC 4 Page 5 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Three other published studies which give some insight While not assessing errors, one study assessed the quality into medication incident rates in specific areas of practice of opioid prescribing, finding that 90% of prescribing are summarised in Table 3. These studies were conducted orders did not comply with at least one of 13 quality state- in anaesthetics, intensive care and in a district hospital set- ments that had been developed to assess performance ting. [18]. It should be noted that not all of the quality state- ments would necessarily be judged as inappropriate pre- Prescribing errors in acute care scribing, however, the study does highlight that Incidence of prescribing errors documentation of opioid prescribing could be improved. Since 2002, one new study has assessed the overall inci- dence of prescribing errors on discharge prescriptions, Two other relevant studies included one that assessed comparing hand written discharge medication prescrip- whether patients were weighed in hospital prior to pre- tions with computer generated discharge prescriptions, scription of renally excreted medicines [19] and another finding much higher rates of error with computerised sys- looking at the dosage of medicines in people with renal tems (11.6%) compared with hand written systems (5%) failure [20]. Failure to weigh patients who are prescribed (p < 0.001) (Table 4). Additional errors which appeared renally excreted medicines has been identified as a risk for to be associated with computer systems were excessive medication error. The NSW study included patients duration (primarily associated with antibiotic durations admitted over a three month period to one medical ward extended because of the default quantity in the prescrib- and one surgical ward. Only 26% of the 38 persons pre- ing software), dosing errors and inclusion of medicines scribed renally excreted medicines were weighed prior to intended to be ceased [15]. prescription. Although only small numbers, the study also reported a significant increase in bleeds amongst those One study was located that assessed documentation of prescribed anticoagulants who were not weighed com- medicines by emergency department doctors compared to pared to those who were weighed (p = 0.03) [19]. the medication history taken by a pharmacy researcher, finding very high rates of discrepancy. Emergency depart- A retrospective study of 192 patients admitted to a ment doctors documented only 16% of the medicines Queensland hospital over a four month period with a cre- subsequently documented by the pharmacist researcher. atinine clearance of 40 ml/min or less found that 45% of This was primarily due to the fact that when the emer- prescriptions for renally excreted medicines had an inap- gency department doctor had documented on the emer- propriately high dose, with the majority of these being gency department admission form "see accompanying present on admission [20]. medication list", rather than rewriting the medicines on to the form, the medication was classified as omitted [16]. Factors contributing to prescribing errors While this method is not directly comparable to studies There have been a number of studies assessing factors con- that have used chart review to compare histories taken by tributing to prescribing error resulting in a much stronger different health professionals, the results of this study Australian evidence base for the contribution of systems highlight the potential for error in the emergency depart- factors to medication errors. ment due to poor documentation and potential for forms and lists to be separated. Another study, also undertaken A qualitative study undertaken in Queensland examining in the emergency department, assessing medication errors reasons for 21 prescribing errors by hospital interns found prior to an intervention, found 88 errors amongst 56 causation was multifactorial with a median of four (range patients over a five day period. On average the patients 2–5) types of factors contributing to error [21]. Environ- were prescribed 7.2 medicines, suggesting a very high mental factors contributed in 19 (90%) cases; team factors error rate of 22% [17]. contributed in 16 (76%) cases; individual factors contrib- uted in 16 (76%) cases; task factors contributed in 16 Table 3: Medication incident rates in specific practice areas Type of incident Denominator Medication incidents (n) Rate Freestone et al., 2006 [46] Anaesthetic incidents 4441 procedures 10 0.2% of procedures Chacko et al., 2007 [47] Critical incidents in intensive 8346 ICU days 42 0.5 per 100 ICU days care Parke 2006 [48] Medication use in a district 24174 medication dispensings 425 1.8% hospital Page 6 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 4: Types of errors: Prescription errors: Australian hospitals 1985–2007 Reference Number of prescriptions or No. of errors detected (rate) Major findings charts audited Discharge prescriptions Coombes et al. 2004 [15] 605 medications on 100 hand 30 (5.0% of medications) The most common types of errors were written prescriptions omissions (2.6%) and dosing errors (0.8%). Coombes et al. 2004 [15] 700 medications on 100 computer 81 errors (11.6% of medications) The most common types of errors were generated prescriptions dosing errors (3.6%), duration errors (1.9%), medication not required on discharge (2.1%) and omissions (1.7%). Inpatient and discharge prescriptions from medical and surgical wards assessed Coombes et al., 2001 [49] 2978 prescriptions 71 (2.4%)errors with potential to The most common error types found were cause an ADE wrong or ambiguous dose (1.0% of prescriptions), dose absent from prescription (0.6% of prescriptions), frequency absent from prescription (0.4% of prescriptions*) Medication charts in a paediatric department assessed Dawson et al., 1993 [50] 212 medication charts 52 major errors** The most common error types were dose (24.5% of med'n charts) errors (12.3% of charts reviewed), error of administration frequency (5.7% of charts reviewed), error of administration route (5.2% of charts reviewed), error in drug name/formulation (1.4% of charts reviewed). Dawson et al., 1993 [50] 325 medication charts 35 major errors** The most common error types were dose (10.8% of med'n charts) errors (4.9% of charts reviewed), error of administration route (2.5% of charts reviewed), error of administration frequency (1.8% of charts reviewed), error in drug name/formulation (1.5% of charts reviewed). Errors in medical, surgical, children's wards and a critical care unit assessed Leversha, 1991 [51] 6641 medication chart checks 241 (3.6% of chart checks) Prescribing errors detected were incorrect dose (1.2% of chart checks), no strength specified (1.0%), insufficient information (0.2%). It was also found that failure to record the patient's current (ongoing) medication on the chart occurred in 69 cases (1.0% of chart checks) Prescriptions presenting to pharmacy department assessed Fry et al., 1985 [52] 10 562 prescriptions 574 (5.4%), Included assessment of legal requirements, (eg patient name and address, doctor's signature) as well as clinical requirements (eg dose, frequency,) The strength was missing or incorrect in 0.7%, the directions inappropriate or omitted in 0.4%, and the wrong drug in 0.06%. * Percentage of prescriptions for regular and 'as required" medications only; ** Major errors included errors in drug name, dose, formulation, route or frequency of administration; Note: unit of analysis is medication chart, which may include one or more prescriptions. Page 7 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 (76%) cases and patient factors contributed in 13 (62%) mented, with most documented as withheld (84 cases), cases. As the study was qualitative these percentages refused (63 cases), unable to accept (51 cases) and fasting should be considered indicative only. Environmental fac- (33 cases). One hundred and twenty cases were assessed tors included issues such as staffing levels, skill mix, work- for severity on a scale from zero to 10 where zero = no load, workflow design, administrative and managerial harm and 10 = death. The majority of cases were scored at support. Task factors included issues such as the medica- two or less [24]. tion chart design, protocols and availability and accuracy of test results. Individual factors included knowledge and A study made 687 observations of 639 intravenous fluid skills, motivation, and individual health. Team factors administrations in 3 surgical wards across a four week included issues such as communication, supervision and period in 2003. Observations were made between 0900 structure, while patient factors included patient condition and 1600 as well as 2000 to 0300. Eighteen percent of and communication ability [21]. observations were associated with a medication error. Of these, 79% of errors were incorrect administration rate. These results were confirmed in a Western Australian The predominant factor associated with increased error study which explored 29 medication errors, with 21 of rate was the presence of a peripheral line (OR 3.5, 95%CI these errors being due to a slip/lapse error [22]. The 11 1.9–6.5), while IV infusion control devices (OR 0.12, administration or dispensing errors were all slip/lapse 95%CI 0.06–0.25), nasogastric feeds (OR 0.09, 95% CI errors; 10 of the prescribing errors were slip/lapse and 0.01–0.64) and permanent staff (OR 0.48, 95% CI 0.31– eight were knowledge based errors. Individual, team, 0.76) were predominant factors associated with decreased patient and environmental factors were all implicated in risk [25]. contributing to the error. The authors noted "errors were more likely to occur during tasks being carried out after One observational study assessing 195 insulin adminis- hours by busy, distracted staff, often in relation to unfa- trations over two months found blood glucose testing was miliar patients" [22]. Communication problems and dif- undertaken within 30 minutes of the insulin dose in only ficulty accessing information were noted to contribute to 22% of cases for rapid acting insulin and 41% of cases for prescribing errors [22]. conventional insulin, while 94% of rapid acting insulin doses were administered within an acceptable time of the The contribution of the delivery of information has also meal delivery, compared to only 43% of conventional been assessed in a Victorian study, which found that it was insulin doses [26]. This study excluded long acting insu- not the availability of the information that was the prob- lins, incomplete or illegible records and all those in palli- lem but inaccessibility to on-line information and lack of ative care. connectivity between applications that caused problems [23]. In this study, electronic prescribing, ordering and Two studies assessed "when required" medication admin- dispensing systems were available as were electronic clin- istration orders finding that documentation was often ical and scheduling management systems and electronic inadequate [28]. One study assessing paracetamol orders systems for managing test and radiology results, again in children found that lack of documentation resulted in highlighting the contribution of environmental factors to miscommunication between doctors and nurses, with dif- error. ferent understandings of the intention for use and when to use [28]. Another study assessing psychotropic medica- Administration errors in acute care tion use amongst 43 patients in a psychiatric unit found Incidence of administration errors on 9% of occasions no reason for use was recorded, on There were no new studies located since 2002 that 39% of occasions it could not be determined who initi- assessed the overall incidence of administration errors, ated the request for medicine and on 41% of occasions no however, one study analysed rates of omitted medicines outcome of the effect was recorded [27]. [24] and another assessed error rates for IV administration [25] (Table 5). Other studies of administration errors that Factors contributing to administration errors were located relate to insulin administration [26], and As with prescribing errors, there are now studies assessing administration of "when required" medicines [27,28]. factors contributing to administration errors resulting in a much stronger Australian evidence base for the contribu- A small study involving 67 inpatients with a total of 4887 tion of systems factors to medication errors. medication administrations found an omission of medi- cine rate of 7.6% (369 cases). Omission was defined as One Victorian study surveyed 154 registered nurses complete omission (i.e. the dose was not given before the employed in regional hospitals, with 79 (51%) respond- next dose of medicine was due). Nurse initiated and when ents [29]. Interruptions and distractions were the most required doses were excluded. In the majority of cases, common environmental factors cited by 25% as contrib- 74% (273 cases), the reason for omission was docu- uting to error, followed by poor communication (13%). Page 8 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 5: Medication administration errors: Australian hospitals 1988–2007 Total Error rate Type of medication error opportunities (excluding minor for error timing errors) Timing error Wrong dose Omission Wrong formul'n Other or route WARD STOCK-BASED SYSTEMS Stewart et al., 1991 2017 369 (18.3%) 75 (3.7%) 46 (2.3%) 82 (4.1%) 6 (0.3%) 160 (7.9%) [53] McNally et al., 494 76 (15.4%) 22* (4.5%) 20 (4.0%) 13 (2.6%) 2 (0.4%) 19 (3.8%) 1997 [54] Lawler et al. 2004 4887 Omission only 369 (7.6%) [24] assessed COMBINATION SYSTEMS Rippe and Hurley, 312 52 (16.7%) 24 (7.7%) 6 (1.9%) 12 (3.8%) 3 (0.96%) 7 (2.2%) 1988 [55] † ‡ ‡ ‡ ‡ Camac et al., 1996 370 47 (12.7%) 25 (6.8%) N/G N/G N/G N/G [56] INDIVIDUAL PATIENT SUPPLY de Clifford et al., 164 10 (6.1%) 1 (0.6%) 2 (1.2%) 5 (3.0%) 0 2 (1.2%) 1994 [57] McNally et al., 502 24 (4.8%) 12* (2.4%) 2 (0.4%) 7 (1.4%) 0 3 (0.6%) 1997 [54] Thornton and 242 20 (8.3%) 2 (0.8%) 0 13 (5.4%) 0 5 (2.1%) Koller 1994 [58] IV FLUID ADMINISTRATIONS Han et al., 2005 687 124 (18%) [25] * Major timing errors included, minor timing errors excluded – a deviation of 2 or more hours from the ordered time. All other studies define a 'timing error' as a deviation of one or more hours from the ordered time. † Total data using two different storage sites – ward bay medication drawer and patient's bedside locker. ‡ N/G – insufficient data given to calculate rate of individual error types The most common human factor cited was stress/high affected by factors such as organizational climate and workload (25%) followed by fatigue/lack of sleep (17%). quality of work life [31], again emphasizing the impor- Twenty nine percent of respondents agreed with the state- tance of the system to error prevention. Information flow ment "I need further training in medication administra- was found to be a problem for nurses in a qualitative tion" [29]. These results were confirmed in a Queensland study involving paediatric nurses, with difficulty using study also involving nurses working in rural or remote computers and physically accessing computer terminals areas [30]. High workloads, low staffing levels and high because of their location and number identified as an doctor expectations were all associated with a higher rate issue [32]. Similarly, policy adherence was reported to be of errors, while higher levels of knowledge were found to affected by the busyness of the ward, with less policy be protective against errors [30]. A further study demon- adherence when wards were busiest [32]. Another qualita- strated how individual distress impacted on violations tive study found that nurses were more likely to assess (deviation from rules) which in turn impacted on error patients prior to medication administration rather than rates [31]. Individual distress however, was in turn after administration, with assessment of the effect of the Page 9 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 medication more likely to be limited to symptomatic ther- ple factors that contribute to medication errors and other apy (eg pain relief) than other therapies [33], and that this problems with medicines within this setting. Understand- was often poorly documented [34]. ing the contributing system factors that underlie medica- tion errors can assist the development of strategies and policies that tackle these factors on a variety of levels. Conclusion Approximately 2%–3% of Australian hospital admissions There is an ongoing need for strong leadership and com- are medication related. This represents an estimated mitment from governments, health care managers and 190,000 medication related hospital admissions per year, professionals and consumers to make improved medica- with estimated costs of $660 million. Of the studies that tion safety a priority in Australia. There is a need to sup- have assessed preventability, estimates remain relatively port strategic research which continues to monitor the consistent with approximately 50% potentially preventa- rates of medication problems in the Australian setting as ble. There are now data suggesting that adverse events new strategies are implemented and which will help to associated with within hospital transfer are also high. identify new issues as they arise. Part two of this review examines the Australian evidence base for the use of vari- Results of incident reporting from hospitals show consist- ous approaches which may help to build safer systems ent results in South Australia, Western Australia and New and reduce medication problems. South Wales. Medication remains the second most com- mon type of incident reported. Omission or overdose of Abbreviations medication is the most frequent type of medication inci- ADR: (adverse drug reaction); ADE: (adverse drug event); dent reported and analgesics and anticoagulants are the CI: (confidence interval); CNS: (central nervous system); medicines most commonly implicated. OR: (odds ratio); N/A: (not assessed); NSAID: (non-ster- oidal anti-inflammatory drug); NSW: (New South Wales); One new study since 2002 assessed the overall incidence SA: (South Australia); WA: (Western Australia). of prescribing errors on discharge prescriptions finding an error rate of 11.6% for computer generated prescriptions Competing interests compared with 5.0% for hand written prescriptions. The The authors declare that they have no competing interests. findings suggest that computerised prescribing systems without decision support may not reduce prescribing Authors' contributions errors. Similarly, systems studies suggest implementation EER was the main author of Part 1 of this review and was of computer systems without attention to connectivity, involved in reviewing the literature, summarising study work flow and staff training will not resolve errors. Studies findings and synthesis of the findings with those from the conducted on prescribing of renally excreted medications previous medication safety review. SJS was responsible for suggest that there are high rates of prescribing errors in the drafting and editing of this paper and contributed to patients requiring monitoring and medication dose the review of the relevant literature. adjustment. There were no new studies located that assessed overall administration or dispensing error rates Authors' information in acute care. EER is an Associate Professor and co-director in the Qual- ity Use of Medicines and Pharmacy Research Centre In comparison to 2002, there is now a much stronger Aus- (QUMPRC), Sansom Institute, University of South Aus- tralian research base demonstrating that systems factors tralia. SS is a Research Fellow in the QUMPRC. EER and SS are contributing to medication errors, with team, task, were the primary authors of the Second National Report on environmental, individual and patient factors contribut- Patient Safety Report – Improving Medication Safety for the ing to error. Environmental factors include issues such as Australian Council for Safety and Quality in Health Care staffing levels, skill mix, workload, workflow design, in 2002. administrative and managerial support. Task factors include issues such as the medication chart design, proto- Additional material cols and availability and accuracy of test results. Individ- ual factors include knowledge and skills, motivation, and Additional file 1 individual health. Team factors include issues such as Additional file table S1; Medication-related hospital admissions or communication, supervision and structure, while patient readmissions: Australia 1988 – 2007. Table showing the medication- factors include condition and communication ability. related hospital admissions or readmissions in Australia from 1988 – Click here for file Overall, data from this review indicate that problems with [http://www.biomedcentral.com/content/supplementary/1743- medication safety in the acute care setting still represent a 8462-6-18-S1.doc] major challenge to the Australian health care system. As has been recognised from earlier research, there are multi- Page 10 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 21. Coombes ID, Stowasser DA, Coombes JA, Mitchell C: Why do Acknowledgements interns make prescribing errors? A qualitative study. Med J The authors wish to acknowledge staff of the New South Wales (NSW) Aust 2008, 188(2):89-94. Medicines Information Centre, St Vincent's Hospital for conducting the 22. Nichols P, Copeland TS, Craib IA, Hopkins P, Bruce DG: Learning database search for the literature review. The review was conducted with from error: identifying contributory causes of medication errors in an Australian hospital. Med J Aust 2008, financial support from the Australian Commission on Safety and Quality in 188(5):276-279. Health Care. The Commission initiated the decision to submit the manu- 23. Lederman RM, Parkes C: Systems failure in hospitals – using script for publication. Both authors have read and approved the final man- Reason's model to predict problems in a prescribing infor- uscript. mation system. J Med Syst 2005, 29(1):33-43. 24. Lawler C, Welch SA, Brien JA: Omitted medication doses: fre- quency and severity. J Pharm Pract Res 2004, 34:174-177. References 25. Han PY, Coombes ID, Green B: Factors predictive of intrave- 1. 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Burgess CL, Holman DJ, Satti A: Adverse drug reactions in older 34. Aitken R, Manias E, Dunning T: Documentation of medication Australians: 1981–2002. MJA 2005. management by graduate nurses in patient progress notes: a 11. Zhang M, Holman CD, Preen DB, Brameld K: Repeat adverse drug way forward for patient safety. Collegian 2006, 13(4):5-11. reactions causing hospitalization in older Australians: a pop- 35. Titchen T, Cranswick N, Beggs S: Adverse drug reactions to non- ulation-based longitudinal study 1980–2003. Br J Clin Pharmacol steroidal anti-inflammatory drugs, COX-2 inhibitors and 2007, 63(2):163-170. paracetamol in a paediatric hospital. Br J Clin Pharmacol 2005, 12. Runciman WB, Roughead EE, Semple SJ, Adams RJ: Adverse drug 59(6):718-723. events and medication errors in Australia. Int J Qual Health 36. Easton KL, Chapman CB, Brien JA: Frequency and characteristics Care 2003, 15(Suppl 1):i49-59. of hospital admissions associated with drug-related prob- 13. McLaughlin N, Leslie GD, Williams TA, Dobb GJ: Examining the lems in paediatrics. Br J Clin Pharmacol 2004, 57(5):611-615. occurrence of adverse events within 72 hours of discharge 37. Chan M, Nicklason F, Vial JH: Adverse drug events as a cause of from the intensive care unit. Anaesth Intensive Care 2007, hospital admission in the elderly. Intern Med J 2001, 35(4):486-493. 31(4):199-205. 14. Evans SM, Berry JG, Smith BJ, Esterman A, Selim P, O'Shaughnessy J, 38. Dartnell JG, Anderson RP, Chohan V, Galbraith KJ, Lyon ME, Nestor DeWit M: Attitudes and barriers to incident reporting: a col- PJ, Moulds RF: Hospitalisation for adverse events related to laborative hospital study. Qual Saf Health Care 2006, 15(1):39-43. drug therapy: incidence, avoidability and costs. Med J Aust 15. Coombes ID, Stowasser DA, Mitchell CA, Varghese P: Effect of 1996, 164(11):659-662. computerised prescribing on use of antibiotics. Medical Journal 39. 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Jenkins BG, Tuffin PH, Choo CL, Schug SA: Opioid prescribing: an Report on WA data collected by the advanced incident man- assessment using quality statements. J Clin Pharm Ther 2005, agement system (AIMS) 2003–2004. Perth: Department of 30(6):597-602. Health, Government of Western Australia; 2004. 19. Hilmer SN, Rangiah C, Bajorek BV, Shenfield GM: Failure to weigh 43. Office of Safety and Quality in Health Care: Annual Report. patients in hospital: a medication safety risk. Intern Med J 2007, Report on WA data collected by the advanced incident man- 37(9):647-650. agement system (AIMS) 2004–2005. Perth: Department of 20. Pillans PI, Landsberg PG, Fleming AM, Fanning M, Sturtevant JM: Eval- Health, Government of Western Australia; 2005. uation of dosage adjustment in patients with renal impair- 44. Office of Safety and Quality in Health Care: Annual Report. ment. Intern Med J 2003, 33(1–2):10-13. Report on WA data collected by the advanced incident man- Page 11 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 agement system (AIMS) 2005–2006. Perth: Department of Health, Government of Western Australia; 2006. 45. Clinical excellence commission: Analysis of first year of IIMS data. Annual report 2005–2006. Sydney: Sydney Hospital; 2006. 46. Freestone L, Bolsin SN, Colson M, Patrick A, Creati B: Voluntary incident reporting by anaesthetic trainees in an Australian hospital. Int J Qual Health Care 2006, 18(6):452-457. 47. Chacko J, Raju HR, Singh MK, Mishra RC: Critical incidents in a multidisciplinary intensive care unit. Anaesth Intensive Care 2007, 35(3):382-386. 48. Parke J: Risk analysis of errors in prescribing, dispensing and administering medications within a district hospital. J Pharm Pract Res 2006, 36:21-24. 49. Coombes I, Pillans PI, Storie W, Radford J: Quality of medication ordering at a large teaching hospital. Aust J Hosp Pharm 2001, 31:102-106. 50. Dawson KP, Penna AC, Drummond D, Sharpe C: Prescription errors in a children's ward: audit and intervention. Aust J Hosp Pharm 1993, 23:326-328. 51. Lerversha A: An analysis of clinical pharmacist interventions and the role of clinical pharmacy at a regional hospital in Australia. Aust J Hosp Pharm 1991, 21:222-228. 52. Fry LM, Jones AN, Swan GT: Prescription writing: incidence of errors and their effect on pharmacy workload. Aust J Hosp Pharm 1985, 15:95-98. 53. Stewart RA, Naismith NW, Biro JM, Marinos Y, Woonton BW: Establishing the need for ward pharmacy: a survey of drug administration and medication errors in a public teaching hospital. Aust J Hosp Pharm 1991, 21:378-383. 54. McNally KM, Page MA, Sunderland VB: Failure-mode and effects analysis in improving a drug distribution system. Am J Health Syst Pharm 1997, 54(2):171-177. 55. Rippe ML, Hurley SF: A survey of medication errors in a com- munity hospital. Aust J Hosp Pharm 1988, 18:201-204. 56. Carmac KJ, Fisher MJ, Norris DE: Medication errors – a compar- ative study of drug storage sites. Aust J Hosp Pharm 1996, 26:234-37. 57. De Clifford J, Montalto M, Khoo S, Rowley D: Accuracy of medi- cation administration by nurses with sole responsibility for patients – pilot study of error rate measurement. Aust J Hosp Pharm 1994, 24:491-493. 58. Thornton PD, LJ K: An assessment of medication errors in a seven day issue individualised patient drug distribution sys- tem. Aust J Hosp Pharm 1994, 24:387-390. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." 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Medication safety in acute care in Australia: where are we now? Part 1: a review of the extent and causes of medication problems 2002–2008

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Springer Journals
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Copyright © 2009 by Roughead and Semple; licensee BioMed Central Ltd.
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Medicine & Public Health; Public Health; Social Policy
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1743-8462
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10.1186/1743-8462-6-18
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19671158
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Abstract

Background: This paper presents Part 1 of a two-part literature review examining medication safety in the Australian acute care setting. This review was undertaken for the Australian Commission on Safety and Quality in Health Care to update a previous national report on medication safety conducted in 2002. This first part of the review examines the extent and causes of medication incidents and adverse drug events in acute care. Methods: A literature search was conducted to identify Australian studies, published from 2002 to 2008, on the extent and causes of medication incidents and adverse drug events in acute care. Results: Studies published since 2002 continue to suggest approximately 2%–3% of Australian hospital admissions are medication-related. Results of incident reporting from hospitals show that incidents associated with medication remain the second most common type of incident after falls. Omission or overdose of medication is the most frequent type of medication incident reported. Studies conducted on prescribing of renally excreted medications suggest that there are high rates of prescribing errors in patients requiring monitoring and medication dose adjustment. Research published since 2002 provides a much stronger Australian research base about the factors contributing to medication errors. Team, task, environmental, individual and patient factors have all been found to contribute to error. Conclusion: Medication-related hospital admissions remain a significant problem in the Australian healthcare system. It can be estimated that 190,000 medication-related hospital admissions occur per year in Australia, with estimated costs of $660 million. Medication incidents remain the second most common type of incident reported in Australian hospitals. A number of different systems factors contribute to the occurrence of medication errors in the Australian setting. result in the desired outcome, medicines are not without Background Use of medications is central to modern health care, and risk, and problems or unexpected outcomes may arise. nearly all patients visiting a hospital will receive one or more medicines during their hospital stay or upon dis- As medicines are taken so commonly, sometimes prob- charge. While in the majority of cases medicines use will lems can occur in their prescription, dispensing and Page 1 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 administration which can be termed "medication inci- and progress in research on contributing factors to these dents". A proportion of these medication incidents result problems. There was also a need to review more recent in patient harm and are called "adverse drug events" developments in research examining the implementation (ADEs). Some ADEs result from the manner in which the of, and evidence base for, strategies to improve medica- medication is used (such as an error or system failure). tion safety in the Australian setting. Other ADEs are termed "adverse drug reactions" and can result from the pharmacological properties of the medica- This paper presents Part 1 of this two-part review. Part 1 tion itself when it is taken alone or in combination with examines the extent and causes of medication incidents other medications. Adverse events associated with medi- and adverse drug events in acute care in Australia to 2008. cations are common, affect a substantial number of peo- It is hoped this information will inform policy makers, ple and contribute a significant burden to health care health care professionals, managers and researchers about costs. the areas in which significant problems with medication safety continue. In 2000, the Australian Council for Safety and Quality in Health Care was established by the Australian Health Part 2 examines the evidence for practices to improve Ministers to provide a focus of national leadership in tack- safety in the Australian setting, barriers and facilitators to ling the issues of patient safety. As part of its work, in 2002 the implementation of these strategies and priorities for the Council commissioned a literature review of medica- further research and policy-development. Part 2 is pre- tion safety in the Second National Report on Patient Safety sented as a separate paper. Report – Improving Medication Safety [1]. Amongst the find- ings of the review was that 2–3% of all hospital admis- Methods sions in Australia were medication-related. A range of Search strategy errors and system failures including errors in prescribing, A literature search was undertaken to identify studies con- administration and dispensing were found to occur in ducted in the acute health care setting in Australia since hospitals in Australia. There was limited Australian the time of publication of the former Australian Council research on the causes of these errors although it was rec- for Safety and Quality in Health Care Second National ognised that most errors resulted from a series of system Report on Patient Safety – Improving Medication Safety [1]. failures rather than the actions of particular individuals. Searches were primarily undertaken by the New South Some commonly associated factors identified included a Wales (NSW) Medicines Information Centre St Vincent's lack of robust systems for prescription or ordering of med- Hospital, Darlinghurst, NSW. ications and problems in the transfer of patient informa- tion between hospital and community settings. Evidence The search strategy for Part 1 of the review was designed was found to support the use of a range of strategies to to identify studies undertaken in Australia from 2002 to improve medication safety including computerised (elec- 2008 on the extent and causes of medication incidents tronic) prescribing with decision support, adverse drug and adverse drug events in acute care. event alerting systems, bar coding, clinical pharmacist services, services to improve information transfer between Searches were conducted in March and April 2008 in different settings and individual patient medication sup- Medline (1950 – March Week 1 2008), EMBASE (1980 – ply in hospitals. Careful implementation of computerised March Week 1 2008), Pre-Medline and CINAHL (1982 – prescribing with clinical decision support systems in Aus- April Week 2 2008) using criteria relevant to the general tralia was identified as a priority. However, it was recog- headings in the former Council's Second National Report on nised that there was an urgent need for more research Patient Safety – Improving Medication Safety [1]. All searches examining the implementation and effectiveness of the were limited to 2002–2008. various strategies in the Australian setting. Search terms used included adverse drug event, adverse In 2006, the former Council was replaced by the Austral- drug reaction, Australia, Australian, drug, error, event, exp ian Commission on Safety and Quality in Health Care. adverse drug reaction reporting systems, exp Australia, exp The Commission's roles include the leadership and coor- drug surveillance program, exp drug therapy, exp hospital, dination of strategies to improve safety and quality in exp hospitalization, exp hospitals, exp medication error, health care through identifying issues and policy direc- exp medication systems, exp patient safety, exp physi- tions, providing recommendations for action and advice cian's practice patterns, exp quality assurance, exp safety to Health Ministers and publicly disseminating informa- management, healthcare, hospital, incident, medication tion on safety and quality [2]. errors, medication:, medication?, medicine:, medicine?, misadventure, mishap, mistake, problem. The exp The current Commission required an updated review to (explode) function was used in the relevant databases to examine current trends in medication safety problems search for the subject heading as well as any more specific Page 2 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 terms related to that subject heading. This expanded the identified at the time of admission, but not treated. A fur- results to include records about the broader topic and ther 1.2% of admissions were associated with an adverse related topics. drug reaction that occurred during hospital stay [3]. Use of morbidity records alone is likely to under-estimate the The database search was supplemented with review of rel- incidence of these events as it has been demonstrated that evant reports and resources on the Australian Commis- while accurate, the adverse drug reaction codes are under- sion on Safety and Quality in Health Care website http:// reported [5]. The second study assessed the incidence of www.safetyandquality.gov.au/ including publications of adverse drug reactions in oncology patients [4]. It the former Australian Council for Safety and Quality in included both adverse drug reactions present on admis- Health Care and incident reports from State Government sion and occurring during hospital stay, finding that 74% sites. of oncology admissions were associated with an adverse drug reaction, with a median of 2 adverse drug reactions Selection of studies for review per admission. Overall 47% were potentially preventable. This review focussed on the acute care setting in Australia, Patients were asked to rate the impact of the adverse drug studies undertaken in the community setting were reaction on a scale from 0 (no impact at all) to 6 (totally excluded. Studies included in examining the extent and changed my life). Fifty three percent of patients rated the causes of medication incidents and adverse drug events at reaction at four or above with 19% rating the adverse drug the systems level were: reaction as "totally changed my life" [4]. - adverse drug event monitoring studies; The inclusion of these studies with the results from the previous Second National Report on Patient Safety Improving - medication incident monitoring studies (including Medication Safety [1] (See table S1 – Additional file 1) still studies where medication incidents were reported on suggests an overall rate of medicine related hospital as a subset); admissions in Australia of between 2% and 3%. - quantitative reports of medication incidents (includ- Attendances to the emergency department have also been ing prescription errors, dispensing errors, administra- included (See table S1 – Additional file 1). Since 2002, tion errors); there has been one new study undertaken in the paediatric population [6] and one study in the adult population [7]. - qualitative studies that examined causes of medica- Results from the general population of 8.3% of adult tion incidents (prescribing, administration and medi- emergency attendances (not admitted) being medicine cation management deficiencies). related [8] pertain to data collected in 1993. A more recent study found an adverse drug reaction rate of 1.4% in Where appropriate summary data tables from the former emergency department attendances (including those sub- Council's Second National Report on Patient Safety – Improv- sequently admitted) and another 18 adverse drug events ing Medication Safety [1] were updated with information documented [7], but an overall incidence rate of emer- from new studies and included in the review. gency department attendances due to medication related problems was not able to be calculated. The emergency Case reports of medication errors leading to near misses department attendance rate of medicine-related attend- or adverse drug events were excluded, as were adverse ances is not dissimilar to the community estimates that events or incidents specific to only one type of medicine. 10.4% of people attending a general practitioner had had an adverse drug event in the previous six months [9]. Results and Discussion The extent of medication-related hospital admissions Preventability estimates for medication-related hospital Medication-related hospital admissions represent prob- admissions and adverse drug reactions associated with lems with medications which may originate either within hospitalisation suggest between one third and three quar- the community or within a hospital. Previous studies had ters are potentially preventable (Table 1). indicated between 2% and 3% of all admissions were medication-related. Two new studies, published since Two other studies give insight into adverse drug reactions 2002 give additional insight into the incidence of medi- during hospitalization, but not incidence figures. These cine-related hospital admissions in Australia [3,4]. One used the hospital morbidity coding records for Western used the hospital morbidity records to determine the inci- Australia [10,11]. One found the trend over time in dence of adverse drug reactions, finding 1.3% of admis- adverse drug reactions associated with hospital admis- sions were associated with an adverse drug reaction at the sions had increased five-fold between 1981–2002, from time of the admission and that required treatment [3]. 2.5 per 1000 person years to 12.9 per 1000 per years [10]. Another 0.3% of admissions had an adverse drug reaction This is similar to what was reported from South Australia Page 3 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 1: Preventability of adverse medicine events associated with hospitalisation or admissions due to medication-related problems Total number of Percentage Percentage Percentage medicine-related considered considered considered problems or definitely avoidable probably or probably not or admissions possibly avoidable definitely unavoidable Titchen et al., 2005 Hospital Paediatric 25 36% [35] NSAID ADRs Easton et al., 2004 Paediatric admissions 81 46.9% 30.9% [36] Easton-Carter et al., Paediatric emergency 187 51.3% 36.9% 2003 [6] department attendances Chan et al., 2001 [37] Geriatric admissions 73 53.4 23.3 23.3 Lau et al., 2004 [4] Hospital Oncology 454 1.6% 46.1% 53.4% ADRs Dartnell et al 1996 General admissions 55* 5% 60% 35% [38] Sarkawi et al, 1995 Medical admissions 35* 23% 46% 31% [39] Easton 1998 [40] Paediatric admissions 48* #67% 29% Ng 1996 [41] Geriatric admissions 31 3% 29% 68% * – overdose excluded; # – category not used; + – 2 cases not assessable. ADRs = adverse drug reactions; NSAID = non-steroidal anti- inflammatory drug. Note: estimates of adverse drug event preventability in the community from one study were 23% [9]. [1], with the South Australian results showing a strong Overall, these data suggest medication-related hospital correlation with medication use [12], suggesting the admissions still represent a significant burden on the Aus- increase is related to changes in medication use rather tralian community. Based on annual hospital admissions than an increased incidence of events. The second study data for 2006–07 in which there were 7.6 million separa- reported "repeat" adverse drug reactions, finding that tions, it can be estimated that there are approximately "repeat" adverse drug reaction-related hospitalisations 190,000 medicine related hospital admissions in Aus- increased at a faster rate than the overall rate of adverse tralia each year with an estimated cost of $660 million. drug reaction hospitalisations, with estimates that repeat adverse reaction hospitalisations accounted for 30% of all Adverse events associated with intra-hospital transfers adverse drug reaction hospitalisations by 2003 [11]. This Evidence also highlights the potential problem of medica- result should be interpreted cautiously. "Repeat" adverse tion errors occurring as a result of intra-hospital transfer, drug reactions included another admission for an adverse particularly after hours. A 2006 study assessing adverse drug reaction not a repeat admission for the same adverse events occurring within 72 hours of discharge from the drug reaction. Further, the results have not been adjusted intensive care unit found 17 (10%) of 167 discharges were for length of follow-up. Cytotoxics and hormones associated with an adverse event, with 52% preventable. accounted for a larger proportion of repeat admissions While not focused specifically on medications, 47% of the than first admissions [11], which may indicate that treat- adverse events were related to fluid management. Eighty- ment patterns for the underlying diseases impacted on the two percent of the discharges associated with adverse overall population available for repeat admissions. High events were discharges that occurred after hours or at rates of adverse drug reactions in the oncology population weekends [13]. have been reported [4]. Page 4 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Medication incidents in acute care monly implicated. The peak time of day for medication Incident reporting from Western Australia and New South incidents is at 0800 – 0900 hours and 2000 – 2100 hours Wales has been compared with that from South Australia in both WA and NSW. Nurses reported the majority of reported in the Second National Report on Patient Safety- incidents. Improving Medication Safety (Table 2). Medication inci- dents remain the second most frequent incident reported, A South Australian survey of 186 doctors and 587 nurses with falls being the predominant incident. As a propor- (70.7% and 73.6% response rate respectively) found that tion of all incidents, medication incidents were similar 100% of nurses stated they always reported a medicine across WA and SA, with a lower percentage reported in error that required giving a patient corrective treatment, NSW. Omission and overdose remain the most common compared to only 40% of the doctors, while less than 20% type of medication incident, with failure to read or mis- of each group stated they reported near miss medication reading the chart and failure to follow protocol the most errors [14]. Lack of feedback, the form taking too long to commonly cited causes. The majority of medication inci- complete, the perception that the incident was trivial and dents cause no harm or only minor harm. Analgesics and the ward being busy, were the most common reasons anticoagulants appear to be the medicines most com- cited for not reporting an incident [14]. Table 2: Medication incident reports, SA, WA and NSW SA (pre 2002) [1] WA 03/04 [42] WA 04/05 [43] WA 05/06 [44] NSW 05/06 [45] Number of 26999 23189 21693 20799 123404 incidents # # Medication 7155 (26.5%) 23.5% 24.0% 5068 (24.4%) 17367 (14.1%) incidents Outcome No injury 69% 87.0% 85.0% 85.0% 82%* Most common type of medication incident Omission 27.9% 36.0% 36.0% 37.0% Overdose 19.5% 18.0% 17.0% 19.0% Prescription or 14.0% order error Unclear or 6.0% incomplete order Dispensing error 3.3% 2.0% Most common reason cited for medication incident Failure to read or 52% 49.0% 36.0% misread Failure to follow 23.0% 26.0% policy Medicines implicated Cardiovascular; Analgesics; Anticoagulants Analgesics; Analgesics; Analgesics, CNS, Diuretics; Respiratory; Anticoagulants; Anticoagulants; Endocrine, Antibiotics Proton Pump inhibitors Diuretics; Steroids Insulins; Diuretics @ = none or minor; # = estimated from graph; * = Severity Assessment Code (SAC) 3 or SAC 4 Page 5 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Three other published studies which give some insight While not assessing errors, one study assessed the quality into medication incident rates in specific areas of practice of opioid prescribing, finding that 90% of prescribing are summarised in Table 3. These studies were conducted orders did not comply with at least one of 13 quality state- in anaesthetics, intensive care and in a district hospital set- ments that had been developed to assess performance ting. [18]. It should be noted that not all of the quality state- ments would necessarily be judged as inappropriate pre- Prescribing errors in acute care scribing, however, the study does highlight that Incidence of prescribing errors documentation of opioid prescribing could be improved. Since 2002, one new study has assessed the overall inci- dence of prescribing errors on discharge prescriptions, Two other relevant studies included one that assessed comparing hand written discharge medication prescrip- whether patients were weighed in hospital prior to pre- tions with computer generated discharge prescriptions, scription of renally excreted medicines [19] and another finding much higher rates of error with computerised sys- looking at the dosage of medicines in people with renal tems (11.6%) compared with hand written systems (5%) failure [20]. Failure to weigh patients who are prescribed (p < 0.001) (Table 4). Additional errors which appeared renally excreted medicines has been identified as a risk for to be associated with computer systems were excessive medication error. The NSW study included patients duration (primarily associated with antibiotic durations admitted over a three month period to one medical ward extended because of the default quantity in the prescrib- and one surgical ward. Only 26% of the 38 persons pre- ing software), dosing errors and inclusion of medicines scribed renally excreted medicines were weighed prior to intended to be ceased [15]. prescription. Although only small numbers, the study also reported a significant increase in bleeds amongst those One study was located that assessed documentation of prescribed anticoagulants who were not weighed com- medicines by emergency department doctors compared to pared to those who were weighed (p = 0.03) [19]. the medication history taken by a pharmacy researcher, finding very high rates of discrepancy. Emergency depart- A retrospective study of 192 patients admitted to a ment doctors documented only 16% of the medicines Queensland hospital over a four month period with a cre- subsequently documented by the pharmacist researcher. atinine clearance of 40 ml/min or less found that 45% of This was primarily due to the fact that when the emer- prescriptions for renally excreted medicines had an inap- gency department doctor had documented on the emer- propriately high dose, with the majority of these being gency department admission form "see accompanying present on admission [20]. medication list", rather than rewriting the medicines on to the form, the medication was classified as omitted [16]. Factors contributing to prescribing errors While this method is not directly comparable to studies There have been a number of studies assessing factors con- that have used chart review to compare histories taken by tributing to prescribing error resulting in a much stronger different health professionals, the results of this study Australian evidence base for the contribution of systems highlight the potential for error in the emergency depart- factors to medication errors. ment due to poor documentation and potential for forms and lists to be separated. Another study, also undertaken A qualitative study undertaken in Queensland examining in the emergency department, assessing medication errors reasons for 21 prescribing errors by hospital interns found prior to an intervention, found 88 errors amongst 56 causation was multifactorial with a median of four (range patients over a five day period. On average the patients 2–5) types of factors contributing to error [21]. Environ- were prescribed 7.2 medicines, suggesting a very high mental factors contributed in 19 (90%) cases; team factors error rate of 22% [17]. contributed in 16 (76%) cases; individual factors contrib- uted in 16 (76%) cases; task factors contributed in 16 Table 3: Medication incident rates in specific practice areas Type of incident Denominator Medication incidents (n) Rate Freestone et al., 2006 [46] Anaesthetic incidents 4441 procedures 10 0.2% of procedures Chacko et al., 2007 [47] Critical incidents in intensive 8346 ICU days 42 0.5 per 100 ICU days care Parke 2006 [48] Medication use in a district 24174 medication dispensings 425 1.8% hospital Page 6 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 4: Types of errors: Prescription errors: Australian hospitals 1985–2007 Reference Number of prescriptions or No. of errors detected (rate) Major findings charts audited Discharge prescriptions Coombes et al. 2004 [15] 605 medications on 100 hand 30 (5.0% of medications) The most common types of errors were written prescriptions omissions (2.6%) and dosing errors (0.8%). Coombes et al. 2004 [15] 700 medications on 100 computer 81 errors (11.6% of medications) The most common types of errors were generated prescriptions dosing errors (3.6%), duration errors (1.9%), medication not required on discharge (2.1%) and omissions (1.7%). Inpatient and discharge prescriptions from medical and surgical wards assessed Coombes et al., 2001 [49] 2978 prescriptions 71 (2.4%)errors with potential to The most common error types found were cause an ADE wrong or ambiguous dose (1.0% of prescriptions), dose absent from prescription (0.6% of prescriptions), frequency absent from prescription (0.4% of prescriptions*) Medication charts in a paediatric department assessed Dawson et al., 1993 [50] 212 medication charts 52 major errors** The most common error types were dose (24.5% of med'n charts) errors (12.3% of charts reviewed), error of administration frequency (5.7% of charts reviewed), error of administration route (5.2% of charts reviewed), error in drug name/formulation (1.4% of charts reviewed). Dawson et al., 1993 [50] 325 medication charts 35 major errors** The most common error types were dose (10.8% of med'n charts) errors (4.9% of charts reviewed), error of administration route (2.5% of charts reviewed), error of administration frequency (1.8% of charts reviewed), error in drug name/formulation (1.5% of charts reviewed). Errors in medical, surgical, children's wards and a critical care unit assessed Leversha, 1991 [51] 6641 medication chart checks 241 (3.6% of chart checks) Prescribing errors detected were incorrect dose (1.2% of chart checks), no strength specified (1.0%), insufficient information (0.2%). It was also found that failure to record the patient's current (ongoing) medication on the chart occurred in 69 cases (1.0% of chart checks) Prescriptions presenting to pharmacy department assessed Fry et al., 1985 [52] 10 562 prescriptions 574 (5.4%), Included assessment of legal requirements, (eg patient name and address, doctor's signature) as well as clinical requirements (eg dose, frequency,) The strength was missing or incorrect in 0.7%, the directions inappropriate or omitted in 0.4%, and the wrong drug in 0.06%. * Percentage of prescriptions for regular and 'as required" medications only; ** Major errors included errors in drug name, dose, formulation, route or frequency of administration; Note: unit of analysis is medication chart, which may include one or more prescriptions. Page 7 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 (76%) cases and patient factors contributed in 13 (62%) mented, with most documented as withheld (84 cases), cases. As the study was qualitative these percentages refused (63 cases), unable to accept (51 cases) and fasting should be considered indicative only. Environmental fac- (33 cases). One hundred and twenty cases were assessed tors included issues such as staffing levels, skill mix, work- for severity on a scale from zero to 10 where zero = no load, workflow design, administrative and managerial harm and 10 = death. The majority of cases were scored at support. Task factors included issues such as the medica- two or less [24]. tion chart design, protocols and availability and accuracy of test results. Individual factors included knowledge and A study made 687 observations of 639 intravenous fluid skills, motivation, and individual health. Team factors administrations in 3 surgical wards across a four week included issues such as communication, supervision and period in 2003. Observations were made between 0900 structure, while patient factors included patient condition and 1600 as well as 2000 to 0300. Eighteen percent of and communication ability [21]. observations were associated with a medication error. Of these, 79% of errors were incorrect administration rate. These results were confirmed in a Western Australian The predominant factor associated with increased error study which explored 29 medication errors, with 21 of rate was the presence of a peripheral line (OR 3.5, 95%CI these errors being due to a slip/lapse error [22]. The 11 1.9–6.5), while IV infusion control devices (OR 0.12, administration or dispensing errors were all slip/lapse 95%CI 0.06–0.25), nasogastric feeds (OR 0.09, 95% CI errors; 10 of the prescribing errors were slip/lapse and 0.01–0.64) and permanent staff (OR 0.48, 95% CI 0.31– eight were knowledge based errors. Individual, team, 0.76) were predominant factors associated with decreased patient and environmental factors were all implicated in risk [25]. contributing to the error. The authors noted "errors were more likely to occur during tasks being carried out after One observational study assessing 195 insulin adminis- hours by busy, distracted staff, often in relation to unfa- trations over two months found blood glucose testing was miliar patients" [22]. Communication problems and dif- undertaken within 30 minutes of the insulin dose in only ficulty accessing information were noted to contribute to 22% of cases for rapid acting insulin and 41% of cases for prescribing errors [22]. conventional insulin, while 94% of rapid acting insulin doses were administered within an acceptable time of the The contribution of the delivery of information has also meal delivery, compared to only 43% of conventional been assessed in a Victorian study, which found that it was insulin doses [26]. This study excluded long acting insu- not the availability of the information that was the prob- lins, incomplete or illegible records and all those in palli- lem but inaccessibility to on-line information and lack of ative care. connectivity between applications that caused problems [23]. In this study, electronic prescribing, ordering and Two studies assessed "when required" medication admin- dispensing systems were available as were electronic clin- istration orders finding that documentation was often ical and scheduling management systems and electronic inadequate [28]. One study assessing paracetamol orders systems for managing test and radiology results, again in children found that lack of documentation resulted in highlighting the contribution of environmental factors to miscommunication between doctors and nurses, with dif- error. ferent understandings of the intention for use and when to use [28]. Another study assessing psychotropic medica- Administration errors in acute care tion use amongst 43 patients in a psychiatric unit found Incidence of administration errors on 9% of occasions no reason for use was recorded, on There were no new studies located since 2002 that 39% of occasions it could not be determined who initi- assessed the overall incidence of administration errors, ated the request for medicine and on 41% of occasions no however, one study analysed rates of omitted medicines outcome of the effect was recorded [27]. [24] and another assessed error rates for IV administration [25] (Table 5). Other studies of administration errors that Factors contributing to administration errors were located relate to insulin administration [26], and As with prescribing errors, there are now studies assessing administration of "when required" medicines [27,28]. factors contributing to administration errors resulting in a much stronger Australian evidence base for the contribu- A small study involving 67 inpatients with a total of 4887 tion of systems factors to medication errors. medication administrations found an omission of medi- cine rate of 7.6% (369 cases). Omission was defined as One Victorian study surveyed 154 registered nurses complete omission (i.e. the dose was not given before the employed in regional hospitals, with 79 (51%) respond- next dose of medicine was due). Nurse initiated and when ents [29]. Interruptions and distractions were the most required doses were excluded. In the majority of cases, common environmental factors cited by 25% as contrib- 74% (273 cases), the reason for omission was docu- uting to error, followed by poor communication (13%). Page 8 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 Table 5: Medication administration errors: Australian hospitals 1988–2007 Total Error rate Type of medication error opportunities (excluding minor for error timing errors) Timing error Wrong dose Omission Wrong formul'n Other or route WARD STOCK-BASED SYSTEMS Stewart et al., 1991 2017 369 (18.3%) 75 (3.7%) 46 (2.3%) 82 (4.1%) 6 (0.3%) 160 (7.9%) [53] McNally et al., 494 76 (15.4%) 22* (4.5%) 20 (4.0%) 13 (2.6%) 2 (0.4%) 19 (3.8%) 1997 [54] Lawler et al. 2004 4887 Omission only 369 (7.6%) [24] assessed COMBINATION SYSTEMS Rippe and Hurley, 312 52 (16.7%) 24 (7.7%) 6 (1.9%) 12 (3.8%) 3 (0.96%) 7 (2.2%) 1988 [55] † ‡ ‡ ‡ ‡ Camac et al., 1996 370 47 (12.7%) 25 (6.8%) N/G N/G N/G N/G [56] INDIVIDUAL PATIENT SUPPLY de Clifford et al., 164 10 (6.1%) 1 (0.6%) 2 (1.2%) 5 (3.0%) 0 2 (1.2%) 1994 [57] McNally et al., 502 24 (4.8%) 12* (2.4%) 2 (0.4%) 7 (1.4%) 0 3 (0.6%) 1997 [54] Thornton and 242 20 (8.3%) 2 (0.8%) 0 13 (5.4%) 0 5 (2.1%) Koller 1994 [58] IV FLUID ADMINISTRATIONS Han et al., 2005 687 124 (18%) [25] * Major timing errors included, minor timing errors excluded – a deviation of 2 or more hours from the ordered time. All other studies define a 'timing error' as a deviation of one or more hours from the ordered time. † Total data using two different storage sites – ward bay medication drawer and patient's bedside locker. ‡ N/G – insufficient data given to calculate rate of individual error types The most common human factor cited was stress/high affected by factors such as organizational climate and workload (25%) followed by fatigue/lack of sleep (17%). quality of work life [31], again emphasizing the impor- Twenty nine percent of respondents agreed with the state- tance of the system to error prevention. Information flow ment "I need further training in medication administra- was found to be a problem for nurses in a qualitative tion" [29]. These results were confirmed in a Queensland study involving paediatric nurses, with difficulty using study also involving nurses working in rural or remote computers and physically accessing computer terminals areas [30]. High workloads, low staffing levels and high because of their location and number identified as an doctor expectations were all associated with a higher rate issue [32]. Similarly, policy adherence was reported to be of errors, while higher levels of knowledge were found to affected by the busyness of the ward, with less policy be protective against errors [30]. A further study demon- adherence when wards were busiest [32]. Another qualita- strated how individual distress impacted on violations tive study found that nurses were more likely to assess (deviation from rules) which in turn impacted on error patients prior to medication administration rather than rates [31]. Individual distress however, was in turn after administration, with assessment of the effect of the Page 9 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 medication more likely to be limited to symptomatic ther- ple factors that contribute to medication errors and other apy (eg pain relief) than other therapies [33], and that this problems with medicines within this setting. Understand- was often poorly documented [34]. ing the contributing system factors that underlie medica- tion errors can assist the development of strategies and policies that tackle these factors on a variety of levels. Conclusion Approximately 2%–3% of Australian hospital admissions There is an ongoing need for strong leadership and com- are medication related. This represents an estimated mitment from governments, health care managers and 190,000 medication related hospital admissions per year, professionals and consumers to make improved medica- with estimated costs of $660 million. Of the studies that tion safety a priority in Australia. There is a need to sup- have assessed preventability, estimates remain relatively port strategic research which continues to monitor the consistent with approximately 50% potentially preventa- rates of medication problems in the Australian setting as ble. There are now data suggesting that adverse events new strategies are implemented and which will help to associated with within hospital transfer are also high. identify new issues as they arise. Part two of this review examines the Australian evidence base for the use of vari- Results of incident reporting from hospitals show consist- ous approaches which may help to build safer systems ent results in South Australia, Western Australia and New and reduce medication problems. South Wales. Medication remains the second most com- mon type of incident reported. Omission or overdose of Abbreviations medication is the most frequent type of medication inci- ADR: (adverse drug reaction); ADE: (adverse drug event); dent reported and analgesics and anticoagulants are the CI: (confidence interval); CNS: (central nervous system); medicines most commonly implicated. OR: (odds ratio); N/A: (not assessed); NSAID: (non-ster- oidal anti-inflammatory drug); NSW: (New South Wales); One new study since 2002 assessed the overall incidence SA: (South Australia); WA: (Western Australia). of prescribing errors on discharge prescriptions finding an error rate of 11.6% for computer generated prescriptions Competing interests compared with 5.0% for hand written prescriptions. The The authors declare that they have no competing interests. findings suggest that computerised prescribing systems without decision support may not reduce prescribing Authors' contributions errors. Similarly, systems studies suggest implementation EER was the main author of Part 1 of this review and was of computer systems without attention to connectivity, involved in reviewing the literature, summarising study work flow and staff training will not resolve errors. Studies findings and synthesis of the findings with those from the conducted on prescribing of renally excreted medications previous medication safety review. SJS was responsible for suggest that there are high rates of prescribing errors in the drafting and editing of this paper and contributed to patients requiring monitoring and medication dose the review of the relevant literature. adjustment. There were no new studies located that assessed overall administration or dispensing error rates Authors' information in acute care. EER is an Associate Professor and co-director in the Qual- ity Use of Medicines and Pharmacy Research Centre In comparison to 2002, there is now a much stronger Aus- (QUMPRC), Sansom Institute, University of South Aus- tralian research base demonstrating that systems factors tralia. SS is a Research Fellow in the QUMPRC. EER and SS are contributing to medication errors, with team, task, were the primary authors of the Second National Report on environmental, individual and patient factors contribut- Patient Safety Report – Improving Medication Safety for the ing to error. Environmental factors include issues such as Australian Council for Safety and Quality in Health Care staffing levels, skill mix, workload, workflow design, in 2002. administrative and managerial support. Task factors include issues such as the medication chart design, proto- Additional material cols and availability and accuracy of test results. Individ- ual factors include knowledge and skills, motivation, and Additional file 1 individual health. Team factors include issues such as Additional file table S1; Medication-related hospital admissions or communication, supervision and structure, while patient readmissions: Australia 1988 – 2007. Table showing the medication- factors include condition and communication ability. related hospital admissions or readmissions in Australia from 1988 – Click here for file Overall, data from this review indicate that problems with [http://www.biomedcentral.com/content/supplementary/1743- medication safety in the acute care setting still represent a 8462-6-18-S1.doc] major challenge to the Australian health care system. As has been recognised from earlier research, there are multi- Page 10 of 12 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:18 http://www.anzhealthpolicy.com/content/6/1/18 21. Coombes ID, Stowasser DA, Coombes JA, Mitchell C: Why do Acknowledgements interns make prescribing errors? A qualitative study. Med J The authors wish to acknowledge staff of the New South Wales (NSW) Aust 2008, 188(2):89-94. Medicines Information Centre, St Vincent's Hospital for conducting the 22. 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Rippe ML, Hurley SF: A survey of medication errors in a com- munity hospital. Aust J Hosp Pharm 1988, 18:201-204. 56. Carmac KJ, Fisher MJ, Norris DE: Medication errors – a compar- ative study of drug storage sites. Aust J Hosp Pharm 1996, 26:234-37. 57. De Clifford J, Montalto M, Khoo S, Rowley D: Accuracy of medi- cation administration by nurses with sole responsibility for patients – pilot study of error rate measurement. Aust J Hosp Pharm 1994, 24:491-493. 58. Thornton PD, LJ K: An assessment of medication errors in a seven day issue individualised patient drug distribution sys- tem. Aust J Hosp Pharm 1994, 24:387-390. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." 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