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      Checking it twice: an evaluation of checklists for detecting medication errors at the bedside using a chemotherapy model

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          Abstract

          Objective

          To determine what components of a checklist contribute to effective detection of medication errors at the bedside.

          Design

          High-fidelity simulation study of outpatient chemotherapy administration.

          Setting

          Usability laboratory.

          Participants

          Nurses from an outpatient chemotherapy unit, who used two different checklists to identify four categories of medication administration errors.

          Main outcome measures

          Rates of specified types of errors related to medication administration.

          Results

          As few as 0% and as many as 90% of each type of error were detected. Error detection varied as a function of error type and checklist used. Specific step-by-step instructions were more effective than abstract general reminders in helping nurses to detect errors. Adding a specific instruction to check the patient's identification improved error detection in this category by 65 percentage points. Matching the sequence of items on the checklist with nurses' workflow had a positive impact on the ease of use and efficiency of the checklist.

          Conclusions

          Checklists designed with explicit step-by-step instructions are useful for detecting specific errors when a care provider is required to perform a long series of mechanistic tasks under a high cognitive load. Further research is needed to determine how best to assist clinicians in switching between mechanistic tasks and abstract clinical problem solving.

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          Most cited references5

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          Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality.

          To determine the excess length of stay, extra costs, and mortality attributable to adverse drug events (ADEs) in hospitalized patients. Matched case-control study. The LDS Hospital, a tertiary care health care institution. All patients admitted to LDS Hospital from January 1, 1990, to December 31, 1993, were eligible. Cases were defined as patients with ADEs that occurred during hospitalization; controls were selected according to matching variables in a stepwise fashion. Controls were matched to cases on primary discharge diagnosis related group (DRG), age, sex, acuity, and year of admission; varying numbers of controls were matched to each case. Matching was successful for 71% of the cases, leading to 1580 cases and 20,197 controls. Crude and attributable mortality, crude and attributable length of stay, and cost of hospitalization. ADEs complicated 2.43 per 100 admissions to the LDS Hospital during the study period. The crude mortality rates for the cases and matched controls were 3.5% and 1.05%, respectively (P<.001). The mean length of hospital stay significantly differed between the cases and matched controls (7.69 vs 4.46 days; P<.001) as did the mean cost of hospitalization ($10,010 vs $5355; P<.001). The extra length of hospital stay attributable to an ADE was 1.74 days (P<.001). The excess cost of hospitalization attributable to an ADE was $2013 (P<.001). A linear regression analysis for length of stay and cost controlling for all matching variables revealed that the occurrence of an ADE was associated with increased length of stay of 1.91 days and an increased cost of $2262 (P<.001). In a similar logistic regression analysis for mortality, the increased risk of death among patients experiencing an ADE was 1.88 (95% confidence interval, 1.54-2.22; P<.001). The attributable lengths of stay and costs of hospitalization for ADEs are substantial. An ADE is associated with a significantly prolonged length of stay, increased economic burden, and an almost 2-fold increased risk of death.
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            Getting teams to talk: development and pilot implementation of a checklist to promote interprofessional communication in the OR.

            Pilot studies of complex interventions such as a team checklist are an essential precursor to evaluating how these interventions affect quality and safety of care. We conducted a pilot implementation of a preoperative team communication checklist. The objectives of the study were to assess the feasibility of the checklist (that is, team members' willingness and ability to incorporate it into their work processes); to describe how the checklist tool was used by operating room (OR) teams; and to describe perceived functions of the checklist discussions. A checklist prototype was developed and OR team members were asked to implement it before 18 surgical procedures. A research assistant was present to prompt the participants, if necessary, to initiate each checklist discussion. Trained observers recorded ethnographic field notes and 11 brief feedback interviews were conducted. Observation and interview data were analyzed for trends. The checklist was implemented by the OR team in all 18 study cases. The rate of team participation was 100% (33 vascular surgery team members). The checklist discussions lasted 1-6 minutes (mean 3.5) and most commonly took place in the OR before the patient's arrival. Perceived functions of the checklist discussions included provision of detailed case related information, confirmation of details, articulation of concerns or ambiguities, team building, education, and decision making. Participants consistently valued the checklist discussions. The most significant barrier to undertaking the team checklist was variability in team members' preoperative workflow patterns, which sometimes presented a challenge to bringing the entire team together. The preoperative team checklist shows promise as a feasible and efficient tool that promotes information exchange and team cohesion. Further research is needed to determine the sustainability and generalizability of the checklist intervention, to fully integrate the checklist routine into workflow patterns, and to measure its impact on patient safety.
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              Programming errors contribute to death from patient-controlled analgesia: case report and estimate of probability.

              To identify the factors that threaten patient safety when using patient-controlled analgesia (PCA) and to obtain an evidence-based estimate of the probability of death from user programming errors associated with PCA. A 19-yr-old woman underwent Cesarean section and delivered a healthy infant. Postoperatively, morphine sulfate (2 mg bolus, lockout interval of six minutes, four-hour limit of 30 mg) was ordered, to be delivered by an Abbott Lifecare 4100 Plus II Infusion Pump. A drug cassette containing 1 mg.mL(-1) solution of morphine was unavailable, so the nurse used a cassette that contained a more concentrated solution (5 mg.mL(-1)). 7.5 hr after the PCA was started, the patient was pronounced dead. Blood samples were obtained and autopsy showed a toxic concentration of morphine. The available evidence is consistent with a concentration programming error where morphine 1 mg.mL(-1) was entered instead of 5 mg.mL(-1). Based on a search of such incidents in the Food and Drug Administration MDR database and other sources and on a denominator of 22,000,000 provided by the device manufacturer, mortality from user programming errors with this device was estimated to be a low likelihood event (ranging from 1 in 33,000 to 1 in 338,800), but relatively numerous in absolute terms (ranging from 65-667 deaths). Anesthesiologists, nurses, human factors engineers, and device manufacturers can work together to enhance the safety of PCA pumps by redesigning user interfaces, drug cassettes, and hospital operating procedures to minimize programming errors and to enhance their detection before patients are harmed.
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                Author and article information

                Journal
                Qual Saf Health Care
                qshc
                qhc
                Quality & Safety in Health Care
                BMJ Group (BMA House, Tavistock Square, London, WC1H 9JR )
                1475-3898
                1475-3901
                19 August 2010
                December 2010
                19 August 2010
                : 19
                : 6
                : 562-567
                Affiliations
                [1 ]Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, Toronto, Canada
                [2 ]Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, University of Toronto, Mount Sinai Hospital, Toronto, Canada
                [3 ]Princess Margaret Hospital, University Health Network, Toronto, Canada
                [4 ]Institute for Safe Medication Practices Canada, Toronto, Canada
                Author notes
                Correspondence to Ms Rachel E White, Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, 4th Floor, R Fraser Elliott Building, 190 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada; rachel.white@ 123456uhn.on.ca
                Article
                qhc32862
                10.1136/qshc.2009.032862
                3002832
                20724398
                00ab8a77-90aa-4bc1-ae32-63db222ee0f7
                © 2010, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

                History
                : 4 January 2010
                Categories
                Error Management
                1506

                Health & Social care
                double check,medication safety,error detection,medication error,checklist
                Health & Social care
                double check, medication safety, error detection, medication error, checklist

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