Incorrect Patient Identification Research Articles

Sample Management Errors in a Multispecialty Hospital-based Blood Bank

ABSTRACT Background and Objectives: Specimen labeling errors along with incorrect patient identification have been described as among the most complex and demanding occurrences in laboratory diagnostics. The study aimed to describe the rates of sample identification and labeling errors in the blood center of a multispecialty hospital and identify possible measures to reduce them. Methods: A retrospective document review and analysis of sample identification and labeling errors were conducted in a Blood Bank Laboratory in Saudi Arabia for 4 years. The quality assurance database from the laboratory information system was used to access and review all relevant information. The one-way analysis of variance was employed to check the statistical differences between the laboratory errors and other variables in the study. The significance level was set at P < 0.05. Results: Overall, 74,279 samples and laboratory requests were received, with over 3107 canceled requests and rejected samples. An error rate of 0.43% was due to incorrect identification and labeling. This accounts for 10.2% of the total canceled tests. The annual labeling error ranges from 0.26% to 0.73%. Primarily, the errors were due to incomplete data (0.37%) and were noted as the leading type of error in all the departments. More than half (51.3%) of the errors happened in type and screen tests, whereas a significant proportion was also noted in crossmatch red blood cells (31.9%). Conclusions: The rate of sample identification and labeling errors in this study was comparable to established data and was primarily due to incomplete data or labels. Identification and labeling errors are most common in type and screen testing and crossmatch. Carefully monitoring specimen labeling quality continually can lower specimen labeling errors and determine improvements.

A-378 Clinical Evaluation and Implementation of Rapid COVID-19 Antigen Test in Qatar

Abstract Background In March, the World Health Organization (WHO) declared COVID-19 as a global public health emergency. To curb the spread of virus, timely detection of infected patients and screening of suspected cases in massive population posed a challenge for the healthcare system. Rapid antigen tests (RAT) were high in demand as a fast, accurate and cost-effective screening tool to increasing the testing capacity. In this crucial timing, clinical evaluation and procurement of available COVID-19 RAT following the World Health Organization (WHO) guidelines was a huge challenge for Point of Care testing (POCT) department. The aim of this study is to highlight the challenges overcame in establishing a Point-of-care COVID-19 testing system including personnel training and building a compatible Laboratory Information System (LIS) upholding Hamad Medical Corporation (HMC) cyber security regulation. Methods Three regulatory approved RATs were evaluated against real-time polymerase chain reaction (RT-PCR) and analytical performance were verified. Maintaining the Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathologist (CAP) standards for COVID-19 waived testing, POCT team initiated to conduct practical and educational training vastly through online platforms and face to face sessions. We utilized the extendable LIS functionality for fast medical decisions in hospitals and enabled “reason of testing” feature in Qatar's COVID-19 tracking application. Results Our performance verification showed 98.0% sensitivity and 100% specificity for PanbioTM COVID-19 RAT, 98.0% sensitivity and 100% specificity for Quidel SOFIA2 COVID-19 RAT and Roche COVID-19 RAT yielded a sensitivity of 97.0% and specificity of 100%. Total of 291 training sessions were conducted for 9710 clinical staffs across 17 HMC facilities and 185 private clinics. Using LIS and POC middleware features, obvious increment in RAT of more than 509 tests per day has been reported in a single emergency unit. Overall, 5.5% decrement in incorrect patient identification data using QUIDEL SOFIA2 automated device and LIS functions was recorded in laboratory quality indicator data. COVID-19 tracking application was linked to antigen results for contact tracing, isolating, and breaking the chain of transmission. Conclusion The methods established for the COVID-19 implementation showed acceptable performance fulfilling the elements of HMC product procurement specification and CAP Accreditation standards. Synergic actions of HMC-POCT with supportive laboratory management aided prompt decision making to optimize patient management and added efficiency to the public health control measures in Qatar.

Associations of wrong surgery with other critical healthcare quality and patient safety challenges: a cross-sectional nationwide study of 100 general hospitals in Spain.

Wrong surgery (wrong-site, wrong-procedure, or wrong-patient surgery) is among the most feared patient safety problems in hospitals. We aimed to evaluate associations between numeric assessment of risk assigned to wrong surgery with that of other healthcare quality and patient safety challenges. This nationwide study collected information from healthcare quality experts in charge of a clinical quality and/or patient safety department in general hospitals of ≥ 150 beds in Spain. Out of the 100 included hospitals, the highest strength of associations were observed with risk priority number (RPN) for hospital-acquired pressure ulcers, RPN for venous thromboembolism in hospitalized patients, RPN for incorrect patient identification, RPN for lack of informed consent for diagnostic or therapeutic procedures, RPN for catheter-related bacteremia, and RPN for adverse events and injuries due to medical devices related to use and/or design. These results are of potential interest for designing combined and coordinated strategies to improve patient safety in hospitals.

Using a Patient Identification Checklist: How to Make This a Never Safety Event in Perioperative Services

<h3>Background Information</h3> Patient identification is one of the Joint Commission National Patient Safety Goals. Positive patient identification involves accuracy, verification and two-way communication. Occasionally, patient armbands did not match patient labels or paperwork, leading to incorrect patient identification. Safety Events were placed and reviewed at the executive level as high-risk safety events that achieved institutional support. Preoperatively, errors in patient identification can lead to potentially serious errors. The check-in area was able to identify workflow inconsistencies, interview techniques and equipment locations as opportunities for improvement. The focus was on patient wristbands during check in, leading to the development of a checklist and subsequent audits to measure compliance. <h3>Objectives of Project</h3> To maintain a trend of overall reported patient ID events, to sustain no high harm and reduce patient ID reported procedures events, as they relate to safety culture and accountability by 25% six months after training in Just Culture and accountability. <h3>Process of Implementation</h3> A review of current workflow and observation audits were completed prior to beginning the pilot. A Patient Identification Checklist supporting hospital policy was developed. Education to staff and 50 in-person audits were completed to observe the wristband check-in process, using an electronic audit. The checklist was laminated and posted at eye level of the Patient Service Coordinator (PSC). The wristband and label printer were relocated closer to the workstation for ease of use. The patient charts filing order was changed from OR room number to alphabetical order (by last name) to reduce chart adjustments. The level of lighting was also adjusted to improve visualization by patients and staff. <h3>Statement of Successful Practice</h3> The baseline data included five patient ID safety events for PACU/Preop and the implementation of the new workflow resulted in zero patient ID events after the pilot. The patient ID wristband checklist helped reduce the number of patient ID events related to wristbands but is dependent on the employee adhering to the checklist. <h3>Implications for Advancing the Practice of Perianesthesia Nursing</h3> Not verifying patient information is a top causal factor for patient ID overall. Reminding staff about the importance of adhering to the checklist and following best practice standards for patient identification can help ensure this becomes a Never Event in Perioperative Services.

How can we better identify patients with rectal bleeding who are at high risk of colorectal cancer? An observational study.

PurposeRectal bleeding is a common symptom of colorectal cancer. In this paper, we describe and evaluate the operation of a central access and triage system for patients with rectal bleeding, which uses a “high-risk”/ “low-risk” designation based on the referring doctor’s subjective designation and a 10-item symptom checklist.MethodsA total of 1846 patients, referred between February 1, 2016, and December 31, 2018, were included. Exclusion criteria were the following: incorrect patient identification number, duplicate records, and pre-diagnosed gastrointestinal cancer. Data was obtained by chart review. Sensitivity, specificity, and positive and negative predictive values were calculated for each item on the symptom checklist.ResultsEight hundred seventy-nine (48%) patients received endoscopy, and 37 (2%) were found to have cancer. Five hundred eighty-two (32%) patients were deemed high-risk. Twenty-nine (78%) of the patients with cancer were in the high-risk group. Patients in the high-risk group had a higher incidence of cancer (5.0% vs 0.6%, p < 0.001) and shorter waits to endoscopy (201 vs 292 days). Patients designated as high-risk by the referring physician had a relative risk of 22.3 compared to those designated as low-risk. Patients deemed high-risk by the symptom checklist had a relative risk of 3.5 compared to low-risk patients.ConclusionOur system stratified 29/37 (78%) of the patients found to have cancer as high-risk. A total of 8/37 (22%) patients with cancer were deemed low-risk. Our research has identified two variables (weight loss and anemia) which have been added to our referral symptom checklist. This study helped us identify areas for refinement of our triage system. These findings are of interest to physicians who treat colorectal cancer.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00384-021-04063-w.

Implementation and operational feasibility of SAMBA I HIV-1 semi-quantitative viral load testing at the point-of-care in rural settings in Malawi and Uganda.

We monitored a large-scale implementation of the Simple Amplification-Based Assay semi-quantitative viral load test for HIV-1 version I (SAMBA I Viral Load=SAMBA I VL) within Médecins Sans Frontières' HIV programmes in Malawi and Uganda, to assess its performance and operational feasibility. Descriptive analysis of routine programme data between August 2013 and December 2016. The dataset included samples collected for VL monitoring and tested using SAMBA I VL in five HIV clinics in Malawi (four peripheral health centres and one district hospital), and one HIV clinic in a regional referral hospital in Uganda. SAMBA I VL was used for VL testing in patients who had been receiving ART for between 6months and ten years, to determine whether plasma VL was above or below 1000 copies/mL of HIV-1, reflecting ART failure or efficacy. Randomly selected samples were quantified with commercial VL assays. SAMBA I instruments and test performance, site throughput, and delays in communicating results to clinicians and patients were monitored. Between August 2013 and December 2016 a total of 60889 patient samples were analysed with SAMBA I VL. Overall, 0.23% of initial SAMBA I VL results were invalid; this was reduced to 0.04% after repeating the test once. Global test failure, including instrument failure, was 1.34%. Concordance with reference quantitative testing of VL was 2620/2727, 96.0% (1338/1382, 96.8% in Malawi; 1282/1345, 95.3% in Uganda). For Chiradzulu peripheral health centres and Arua Hospital HIV clinic, where testing was performed on-site, same-day results were communicated to clinicians for between 91% and 97% of samples. Same-day clinical review was obtained for 84.7% across the whole set of samples tested. SAMBA I VL testing is feasible for monitoring cohorts of 1000 to 5000 ART-experienced patients. Same-day results can be used to inform rapid clinical decision-making at rural and remote health facilities, potentially reducing time available for development of resistance and conceivably helping to reduce morbidity and mortality.

Protecting the patient is our protection

Optimization and securing of medical practices and procedures has always been very challenging in medicine. However, the real-life clinical settings continue to pose various hazards that may lead medical professionals to unintended mistakes. Pathologists feel particularly responsible and are very concerned about diagnostic discrepancies or even mistakes, since these depend on their interpretive skills and diagnostic expertise. However, a majority of mistakes in daily practice are related to laboratory procedural errors, involving transportation of the specimens, labeling, contamination, cutting, typing, and various others [1]. In contrast to general belief, errors in diagnostic interpretation account for only 25% of the overall failures in surgical pathology practice, with most of the remaining 75% resulting from defective specimens, incorrect patient identification, mislabeling and/or inadequate reports [2]. Dermatopathology is considered to be the pathology subspecialty associated with higher medico-legal risk [3]. It is well known that the most serious problems in dermatopathology emanate from the incorrect interpretation of melanocytic lesions. However, diagnostic limitations are not the only weakness in dermatopathology practice. Although underestimated, the handling of large numbers of small, similar-looking bioptic specimens results very often in unpredictable mistakes. The latter risk is scarcely reported in the literature and has rarely been investigated, since its objective quantification is not easy. There are many vulnerable steps in the routine of a pathology lab, from the initial access to the lab until the final report and communication with the patient’s physician. Errors pervade all levels of the pre-analytical, analytical, and post-analytical phases, especially in labs that accept a high volume of specimens [3]. The pre-analytical phase, from the arrival at the lab to the commencement of the analysis, is considered the most vulnerable to faults [4]. Receiving the specimen, incorporating the tissue in paraffin blocks and tissue cutting are procedures susceptible to random mistakes and should be systematically controlled [4]. It is generally accepted that the risk of mistakes increases with the number of samples and with the complexity of the required procedure to establish a definite diagnosis. The routine use of immunohistochemical techniques and the increasing interest in new biomolecular markers, which influence management decisions, complicate further this already complex scenario. The article by Weyers included in this issue analyzes the step-by-step process carried out in a pathology lab, outlining the handling of samples and the risk of specimen mix-up. According to the author, a dermatopathology lab could be likened to a factory production line, as it continuously processes and reports on many skin specimens; and in this context, lab mechanisms are particularly susceptible to faults. The author describes all the pathways a biopsy routinely takes, highlighting the pitfalls and recommending preventive strategies for every stage of the procedure. In the era of targeted therapies, when a molecular biology test can be therapeutically strategic, it is crucial to ensure the optimal quality of tissue samples by securing every diagnostic step. Addressing pathology errors and eliminating potential sources of mistakes go hand-in-hand with the right of the patients and their caregivers to a complete, correct, and timely diagnosis. Apart from the aforementioned issues, protecting the patient is also achieved by the accurate and effectivequality checks throughout the system, which in turn protects the physician against malpractice claims while working in the difficult, sometimes under-recognized, but always wonderful, job of dermatopathology.

Evanescence of Endometrial Carcinomas in Hysterectomy Specimens: Observations on the "Vanishing Cancer" Phenomenon.

The phenomenon of vanishing carcinomas, first described in context of prostatic carcinomas, has been documented in endometrial carcinomas as well. The archives of the department were searched for case files of endometrial carcinoma diagnosed on endometrial curetting/biopsy but which did not reveal any cancer on the subsequent hysterectomy specimen. Clinical and pathological correlation was established. A total of 5 cases were retrieved with biopsy-diagnosed endometrial carcinomas, 4 endometrioid and 1 serous type, which on subsequent hysterectomies did not reveal any tumor. These 5 cases represented 1.56% of total hysterectomies in our series. All were Stage Ia tumors, which on follow-up (mean = 18.2 months) did not show any local reoccurrence. Adjuvant therapy was instituted in 1 case in the form of pelvic irradiation in view of the serous histology. In all cases, the primary diagnosis was reconfirmed and any remote possibility of incorrect patient identification, laboratory errors, and institution of hormonal therapy were adequately ruled out along with an extensive endometrial sampling in hysterectomy. The recognition of "vanishing endometrial carcinoma" as a distinct entity is of utmost importance to avoid mislabeling them as medical errors.

Collecting Infectious Disease Data from LARS and Improving Data Quality in Taiwan

ObjectiveTo improve data quality and sustain a good quality data collectedby Laboratory Automated Reporting System (LARS), we use a Three-stage Data Quality Correction (3DQC) strategy to ensure data accuracy.IntroductionTo immediately monitor disease outbreaks, the application oflaboratory-based surveillance is more popular in recent years.Taiwan Centers for Disease Control (TCDC) has developed LARS tocollect the laboratory-confirmed cases caused by any of 20 pathogensdaily via automated submitting of reports from hospital laboratoryinformation system (LIS) to LARS since 2014 [1]. LOINC is usedas standardized format for messaging inspection data [1, 2]. Thereare 37 hospitals have joined LARS, coverage rate about 59% of allhospitals in Taiwan. Recently, more than 10,000 of data are collectedweekly and used in monitoring pathogen activity [3]. Therefore, itis important to ensure data quality that the data will lead to valuableinformation for public health surveillance.MethodsA 3DQC strategy was designed to improve data accuracy andcarried out by teamwork among TCDC, Taiwan Association forMedical Informatics (TAMI) and IT Company (Figure 1). In the firststage of 3DQC, IT Company checked data format. In the second stage,TCDC verified information between hospital inspection reports anddata receiving in LARS. In the third stage, TAMI evaluated LOINCmapping and TCDC monitored stability of data transmission. Aftercorrecting the data, hospitals were approved to join LARS.ResultsDuring the first stage of 3DQC, we observed that some problemswith syntax error in data (e.g. incorrect patient identification number,or lack of residence codes). Because some data were stored in Hospitalinformation system (HIS) but not in LIS, an error may occur whilehospital accessed records from HIS. In the second stage, 50-70%of inspection reports provided by each hospital had problems withsemantic information error. For example, a positive result of influenzaA on a screening flu test recorded in LIS but hospital transferred thewrong result with influenza B positive into LARS. In the third stage,we found that 20-30% of terms mismatched to LOINC code. Thisstudy categorized these terms into two groups (1) the Exceptioncodes, which were considered reasonable and (2) the Error codes, andalso reviewed Error codes and made a modified advice for hospitalsto improve LOINC mapping. Through 3DQC strategy, the LOINCmapping rate raised from 40 to 80%, Exception codes mapping was20%, and the total mapping rate was near 95-99% (Figure 2). Sofar, most hospitals have maintained a good quality data even theyformally participate in LARS.ConclusionsThis study suggested that 3DQC can effectively detect problemsand reduce errors of data collected from LARS, and indicated thateffect of 3DQC can be maintained even hospital formally participatesin LARS. Future research will focus on development of automaticprogramming of 3DQC to ensure high-quality data.Figure 1. A Three-stage Data Quality Correction strategy

Caracterización de los errores asociados a la etapa preanalítica del proceso de biopsias en un hospital docente asistencial de Chile

ObjectiveIdentify errors in the pre-analytical stage of the biopsy process. Detect critical points and blind spots in the biopsy process. Material and methodLongitudinal, prospective, descriptive study. The authors analyzed the records of 11,145 samples taken during 2012, as well as hospital log books of sample rejections and incidents. The quality of the epidemiological information in the records was evaluated (patient identification, type of sample, origin of sample, referring physician, and legibility). The data were analyzed using descriptive statistics. This research complied with all international ethical norms for this type of study. ResultsErrors occurred mainly during the pre-analytical and analytical stages. Critical points of vulnerability to error included physician order entry and daily deliveries of batches of samples. Transfers of samples between units during the pre-analytical and analytical phases were also critical points. The unit reports an error rate of 2.0% for all biopsies, according to passive observation. However, this analysis revealed an 18.95% error rate for all biopsy orders in 2012, including missing or illegible identification of the referring physician (35.93%), illegible or incorrect patient identification (26.33%), missing information on sample origin or type (13.12%), incorrect or missing clinical record number (12.15%), and incorrect or missing social identity card number (10.99%). ConclusionsOur biopsy error analysis indicates that mistakes occur most frequently during the analytical and pre-analytical stages, with 18.95% of all entries containing some type of error. It is urgent that the unit redesign aspects of the biopsy ordering process such as sample identification and epidemiological data entry. This type of error not only delays the analysis but also creates a significant risk of misdiagnosis and therefore incorrect treatment.

STAHLOS: Scanner Terminal for Assisting and HeLp in Oncology Sector

Background: During radiotherapy incorrect patient identification can have serious consequences. Our main goal was to develop an application that supports the radiotherapists during their workflow and to improve patient safety by the use of scanner terminals. Methods: The system development was evolutionary. Expert reviews and multiple interviews with target users were held. Results: A prototype to identify patients during their radiation therapy was made in collaboration with the Radiation Oncology Department of the University Hospital Basel. The result is a fully functional prototype that can be integrated into the existing system landscape. Conclusions: The system has been successfully implemented and evaluated positively by the customer. It could be tested in the future in a pilot study.

Patient complaints as predictors of patient safety incidents

Patients remain an underused resource in efforts can provide valuable insights into the care they receive. This study aimed to establish whether high incidents (HLIs) were predictable from preceding complaints, e study complaints received from November 2011 through June 2012 and HLI incident reports from April through September 2012 were examined. Complaints and HLIs were categorised according to location or themes they included. Data were analysed to look for correlations between number of complaints and HLIs in a given area. A qualitative analysis was carried out to determine whether any complaints contained information that, if acted upon earlier, could have prevented later HLIs. correlation was established between location of HLIs and complaints. Complaints commonly focused on staff attitude, diagnostic problems and delayed treatment. HLIs most often arose from failure to recognise a patient’s deterioration and escalate appropriately or incorrect patient identification. Most HLIs were not preceded by similar complaints. However, in two instances complaints did signpost futur act as an early warning system. There is a need to devise reliable means of identifying the minority of complaints that do precede serious incidents.

A red‐flag‐based approach to risk management of EHR‐related safety concerns

Although electronic health records (EHRs) have a significant potential to improve patient safety, EHR-related safety concerns have begun to emerge. Based on 369 responses to a survey sent to the memberships of the American Society for Healthcare Risk Management and the American Health Lawyers Association and supplemented by our previous work in EHR-related patient safety, we identified the following common EHR-related safety concerns: (1) incorrect patient identification; (2) extended EHR unavailability (either planned or unplanned); (3) failure to heed a computer-generated warning or alert; (4) system-to-system interface errors; (5) failure to identify, find, or use the most recent patient data; (6) misunderstandings about time; (7) incorrect item selected from a list of items; and (8) open or incomplete orders. In this article, we present a "red-flag"-based approach that can be used by risk managers to identify potential EHR safety concerns in their institutions. An organization that routinely conducts EHR-related surveillance activities, such as the ones proposed here, can significantly reduce risks associated with EHR implementation and use.

Is It Possible to Eliminate Patient Identification Errors in Medical Imaging?

The aim of this article is to review a system that validates and documents the process of ensuring the correct patient, correct site and side, and correct procedure (commonly referred to as the 3 C's) within medical imaging. A 4-step patient identification and procedure matching process was developed using health care and aviation models. The process was established in medical imaging departments after a successful interventional radiology pilot program. The success of the project was evaluated using compliance audit data, incident reporting data before and after the implementation of the process, and a staff satisfaction survey. There was 95% to 100% verification of site and side and 100% verification of correct patient, procedure, and consent. Correct patient data and side markers were present in 82% to 95% of cases. The number of incidents before and after the implementation of the 3 C's was difficult to assess because of a change in reporting systems and incident underreporting. More incidents are being reported, particularly "near misses." All near misses were related to incorrect patient identification stickers being placed on request forms. The majority of staff members surveyed found the process easy (55.8%), quick (47.7%), relevant (51.7%), and useful (60.9%). Although identification error is difficult to eliminate, practical initiatives can engender significant systems improvement in complex health care environments.

Automated categorisation of clinical incident reports using statistical text classification

ObjectivesTo explore the feasibility of using statistical text classification techniques to automatically categorise clinical incident reports.MethodsStatistical text classifiers based on Naïve Bayes and Support Vector Machine algorithms were trained and...

Foutieve resultaten van veneuze bloedafname in het klinisch laboratorium

Faulty clinical laboratory results Despite the high quality performance of numerous clinical laboratories, laboratory errors still exert negative effects on patient outcome. Many pre-analytical, analytical and post-analytical variables which are frequently beyond the control of the laboratory, can influence the final results. Most of the identifiable errors can be traced in the pre-analytical phase: incorrect patient identification, inadequate phlebotomy technique, improper sample handling. During the analytical phase, assay interference can have a considerable effect on the results, but may remain difficult to identify. Inaccuracy of reference values can constitute an important post-analytical problem causing an incorrect interpretation of the laboratory data

Adverse events experienced while transferring the critically ill patient from the emergency department to the intensive care unit

Objectives: To determine the incidence and nature of adverse events and delay to patient transfer from emergency department to intensive care unit (ICU) in a metropolitan tertiary hospital. Method: A...

Radiopharmaceutical maladministrations in New South Wales

Errors in medicine are being increasingly highlighted. There is potential for harm in nuclear medicine. To evaluate the frequency, type, causes and adverse effects of nuclear medicine radiopharmaceutical maladministrations reported to the New South Wales Environment Protection Authority. We reviewed reports received by the New South Wales Environment Protection Authority over a 5-year period. The number and type of maladministrations, contributing factors and any adverse effects were recorded. Comparison was made with the total number of medicare-paid diagnostic and therapeutic nuclear medicine services undertaken in New South Wales for the same period. Fifty-seven maladministrations were reported to the New South Wales Environment Protection Authority. There were 666 179 nuclear medicine procedures recorded in New South Wales for the same period. Of the 57 reported maladministrations, the majority (n=34; 61%) were a result of incorrect radiopharmaceutical dispensing. Incorrect reading of labels attached to the syringe (n=8; 14%) and incorrect patient identification (n=7; 12%) accounted for most of the rest of the accidents. Most (n=48; 84%) involved 99mTc-based radiopharmaceuticals for diagnostic use, with three cases involving I for therapeutic use. In 96% of cases - those which involved diagnostic radiopharmaceuticals - there were no immediate adverse clinical outcomes. However, one subject developed unintended hypothyroidism as a result of the maladministration of 131I for therapy. Nuclear medicine maladministrations in New South Wales are uncommon, with approximately 8-9 incidents per 100 000 procedures. Most maladministrations are the consequence of incorrect radiopharmaceutical dispensing. All those which involved diagnostic radiopharmaceuticals resulted in no immediate adverse effects from the radiation exposure.

Problems before Induction of Anaesthesia: An Analysis of 2000 Incident Reports

The first 2000 incidents reported to the Australian Incident Monitoring study (AIMS) were examined to identify those incidents which occurred preoperatively (defined as occurring prior to the commencement of general or regional anaesthesia). The 35 incidents, representing 1.7% of the total, which occurred in this time period were analysed with a view to identifying areas in which current practice could be improved. Almost all incidents led to significant delays in operating lists, and 9 resulted in cancellation of surgery. A number of areas of concern specific to the preoperative period were identified. Inadequate coordination between surgical and anaesthetic staff in patient preparation was a frequent cause of preoperative incidents. Improvement in this area may reduce surgical delays and patient morbidity. Problems with premedication drugs resulted in 8 of the 35 incidents, and care must be taken in the prescription and administration of these drugs to minimise adverse effects on patients. Only 2 cases of incorrect patient identification were reported. However, in view of its disastrous consequences, vigilance in patient identification by all members of the operating team, including the anaesthetist, is essential.