Background The goal of this study was to assess systems and processes involved in the operating room (OR) to intensive care unit (ICU) handoff in an attempt to understand the criticality of specific steps of the handoff. Methods We performed a failure modes, effects and criticality analysis (FMECA) of the OR to ICU handoff of deceased donor liver transplant recipients using in-person observations and descriptions of the handoff process from a multidisciplinary group of clinicians. For each step in the process, failures were identified along with frequency of occurrence, causes, potential effects and safeguards. A risk priority number (RPN) was calculated for each failure (Frequency x Potential effect x Safeguard; range 1-least risk to 1000-most risk). Results The FMECA identified 37 individual steps in the OR to ICU handoff process. In total, 81 process failures were identified, 22 of which were determined to be critical and 36 of which relied on weak safeguards such as informal human verification. Process failures with the highest risk of harm were lack of preliminary OR to ICU communication (RPN 504), team member absence during handoff communication (RPN 480) and transport equipment malfunction (RPN 448). Conclusions Based on the analysis, recommendations were made to reduce potential for patient harm during OR to ICU handoffs. These included automated transfer of OR data to ICU clinicians, enhanced ICU team member notification processes and revision of the postoperative order sets. The FMECA revealed steps in the OR to ICU handoff that are high risk for patient harm and are currently being targeted for process improvement.
Background— Although best practices have been developed for achieving door-to-needle (DTN) times ≤60 minutes for stroke thrombolysis, critical DTN process failures persist. We sought to compare these failures in the Emergency Department at an academic medical center and a community hospital. Methods and Results— Failure modes effects and criticality analysis was used to identify system and process failures. Multidisciplinary teams involved in DTN care participated in moderated sessions at each site. As a result, DTN process maps were created and potential failures and their causes, frequency, severity, and existing safeguards were identified. For each failure, a risk priority number and criticality score were calculated; failures were then ranked, with the highest scores representing the most critical failures and targets for intervention. We detected a total of 70 failures in 50 process steps and 76 failures in 42 process steps at the community hospital and academic medical center, respectively. At the community hospital, critical failures included (1) delay in registration because of Emergency Department overcrowding, (2) incorrect triage diagnosis among walk-in patients, and (3) delay in obtaining consent for thrombolytic treatment. At the academic medical center, critical failures included (1) incorrect triage diagnosis among walk-in patients, (2) delay in stroke team activation, and (3) delay in obtaining computed tomographic imaging. Conclusions— Although the identification of common critical failures suggests opportunities for a generalizable process redesign, differences in the criticality and nature of failures must be addressed at the individual hospital level, to develop robust and sustainable solutions to reduce DTN time.
These results suggest that the simplified method of scoring and ranking failures identified by an FMEA can be a useful tool for healthcare organisations with limited access to FMEA expertise. However, the simplified method does not result in the same degree of discrimination in the ranking of failures offered by the traditional method.
Wrong Site Surgery (WSS) is a rare event that occurs to hundreds of patients each year. Despite national implementation of the Universal Protocol over the past decade, development of effective interventions remains a challenge. We performed a systematic review of the literature reporting root causes of WSS, and used the results to perform a fault tree analysis in order to assess the reliability of the system in preventing (WSS) and identify high-priority targets for interventions aimed at reducing WSS. Process components where a single error could result in WSS were labeled with OR gates; process aspects reinforced by verification were labeled with AND gates. The overall redundancy of the system was evaluated based on prevalence of AND gates and OR gates. In total, 37 studies described risk factors for Wrong Site Surgery. The fault tree contains 35 faults, the majority of which fall into five main categories. Despite the Universal Protocol mandating patient verification, surgical site signing and a brief timeout, a large proportion of the process relies on human transcription and verification. Fault Tree Analysis provides a standardized perspective of errors or faults within the system of surgical scheduling and site confirmation. It can be adapted by institutions or specialties to lead to more targeted interventions to increase redundancy and reliability within the preoperative process.
Background Patients with acute stroke at non‐ or primary stroke centers (PSCs) are transferred to comprehensive stroke centers for advanced treatments that reduce disability but experience significant delays in treatment and increased adjusted mortality. This study reports the results of a proactive, systematic, risk assessment of the door‐in‐door‐out process and its application to solution design. Methods and Results A learning collaborative (clinicians, patients, and caregivers) at 2 PSCs and 3 comprehensive stroke centers in Chicago, Illinois participated in a failure modes, effects, and criticality analysis to identify steps in the process; failures of each step, underlying causes; and to characterize each failure’s frequency, impact, and safeguards using standardized scores to calculate risk priority and criticality numbers for ranking. Targets for solution design were selected among the highest‐ranked failures. The failure modes, effects, and criticality analysis process map and risk table were completed during in‐person and virtual sessions. Failure to detect severe stroke/large‐vessel occlusion on arrival at the PSC is the highest‐ranked failure and can lead to a 45‐minute door‐in‐door‐out delay caused by failure to obtain a head computed tomography and computed tomography angiogram together. Lower risk failures include communication problems and delays within the PSC team and across the PSC comprehensive stroke center and paramedic teams. Seven solution prototypes were iteratively designed and address 4 of the 10 highest‐ranked failures. Conclusions The failure modes, effects, and criticality analysis identified and characterized previously unrecognized failures of the door‐in‐door‐out process. Use of a risk‐informed approach for solution design is novel for stroke and should mitigate or eliminate the failures.
ObjectivesDescribe the application of a risk assessment to identify failures in the hospital discharge process of a high-risk patient group, liver transplant (LT) recipients with diabetes mellitus (DM) and/or hyperglycaemia who require high-risk medications.DesignA Failure Modes, Effects and Criticality Analysis (FMECA) of the hospital discharge process of LT recipients with DM and/or hyperglycaemia who required DM education and training before discharge was conducted using information from clinicians, patients and data extraction from the electronic health records (EHR). Failures and their causes were identified and the frequency and characteristics (harm, detectability) of each failure were assigned using a score of low/best (1) to high/worst (10); a Criticality Index (CI=Harm×Frequency) and a Risk Priority Number (RPN=Harm×Frequency×Detection) were also calculated.SettingAn academic, tertiary care centre in Chicago, Illinois.ParticipantsHealthcare providers (N=31) including physicians (n= 6), advanced practice providers (n=12), nurses (n=6), pharmacists (n= 4), staff (n=3) and patients (n=6) and caregivers (n=3) participated in the FMECA; EHR data for LT recipients with DM or hyperglycaemia (N=100) were collected.ResultsOf 78 identified failures, the most critical failures (n=15; RPNs=700, 630, 560; CI=70) were related to variability in delivery of diabetes education and training, care coordination and medication prescribing patterns of providers. Underlying causes included timing of patient education, lack of assessment of patients’ knowledge and industry-level design failures of healthcare products (eg, EHR, insulin pen).ConclusionMost identified critical failures are preventable and suggest the need for the design of interventions, informed by the failures identified by this FMECA, to mitigate safety risks and improve outcomes of high-risk patient populations.
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