Patient identification mistakes can have serious consequences. Using the Systems Engineering for Patient Safety (SEIPS) framework, this qualitative study explored systems factors contributing to patient identification errors during intrahospital transfers. The authors found that patient identification was not completed according to hospital policy during any of the 60 observed patient transfer handoffs. Miscommunication and lack of key patient information were common factors contributing to identification errors.

Failure Mode, Effect and Criticality Analysis (FMECA) is a prospective method for identifying and preventing potential error risks. Using FMECA, public health medical residents calculated a Risk Priority Number (RPN), or criticality, for each possible failure mode in cancer treatment prescription and administration. Each phase of the cancer treatment process had at least one critical step identified, and actions were developed to reduce the likelihood of the error occurring and/or to increase the likelihood of the error being detected.

A missed or delayed diagnosis of stroke places patients at risk of permanent disability or death. This article describes how interdisciplinary teams used a failure modes, effects, and criticality analysis (FMECA) to create an acute stroke diagnostic process map, identify failures, and highlight existing safeguards. The FMECA process identified several steps in the diagnostic process as the most critical failures to address, including failure to screen patients for stroke soon after presentation to the Emergency Department (ED), failure to obtain an accurate history, and failure to consider a stroke diagnosis during triage.

Safety-I focuses on identifying factors that contribute to incidents or errors. Safety-II seeks to understand and learn from the many cases where things go right, including ordinary events, and emphasizes adjustments and adaptations to achieve safe outcomes. This commentary describes Safety-II and complementary positive strategies of patient safety, such as exnovation, appreciative inquiry, learning from excellence, and positive deviance.

Healthcare organizations use multiple proactive and reactive methods of investigating and preventing adverse events. This study combined proactive and reactive risk assessments into a Combined Proactive Risk Assessment (CPRA) to identify risks not detected by one method on its own. The four steps of CPRA are illustrated using the example of outpatient blood draws in the Veterans Health Administration.

High reliability organizations (HROs) are those that operate in highly complex domains, such as aviation, with no or very few significant errors. This commentary describes the relationship between error and uncertainty in HROs using the increased uncertainties brought on by the COVID-19 pandemic as an example.

Hospitals are increasingly creating and updating their emergency disaster response plans. This guide assists hospital executives, quality & safety professionals, and risk managers by assessing potential hazards or failures in radiology departments in the event of disaster. Disaster planning tools, checklists, and other recommendations are described.  

Air medical transport carries unique patient safety risks. In this study, researchers used simulation training and healthcare failure mode and effect analysis (HFMEA) to identify latent safety threats related to patient transport via helicopter. This approach identified 31 latent safety threats (18 were deemed critical) related to care coordination, facilities, equipment, and devices.

Chemotherapy administration errors can result in serious patient harm. Using failure mode and effects analysis (FMEA), researchers identified potential failures related to the medication process for intravenous chemotherapy. Common failures included incorrect patient information, non-standardized chemotherapy protocols, and problems related to supportive therapy.

Researchers in this study used healthcare failure mode and effect analysis (HFMEA) to identify and reduce errors during chemotherapy preparation. Nine potential failure modes were identified – wrong label, drug, dose, solvent, or volume; non-sterile preparation; incomplete control; improper packaging or labeling, and; break or spill – and the potential causes and effects. Potential approaches to reduce these failure modes include updating the Standard Operating Procedures (SOPs), implementing a bar code system, and using a weight-based control system.

Medication reconciliation is the process of reviewing a patient’s medication list for discrepancies and safety. Patients in nursing homes are at increased risk for medication discrepancies due to complexity of care and frequent transitions of care. By using Healthcare Failure Mode and Effect Analysis (FMEA), researchers uncovered several factors that contribute to medication discrepancies. Interventions to improve medication safety can be targeted to one or more of the contributing factors.

Failure mode and effect analysis (FMEA) is widely used to identify latent safety hazards. The authors of this study proposed combining healthcare failure mode and effect analysis (HFMEA) with computer simulation (HFMEA-CS) for prospective risk analysis of complex and potentially harmful processes. Use of HFMEA-CS to analyze medication processes during admission and discharge for patients with a rare adrenal tumor led to a reduction in drug delivery and system errors, as well as increased drug adherence.

Assessing risk and learning from adverse events are core components of patient safety improvement. The authors propose a method which leverages a radiation oncology incident learning system with a simplified failure mode and effects analysis (FMEA) to analyze safety events and monitor the success of workflow changes to improve patient safety and address high-risk errors.

Hospitals have needed to adapt workflow processes to optimize infection control in response to the COVID-19 pandemic. This article describes the use of healthcare failure mode and effects analysis (HFMEA) 4-step model to implement preventive risk assessment and workflow management for high-risk medical procedures during the pandemic and prevention of nosocomial infections.   

Failure mode and effect analysis (FMEA) is used to asses risk in various heath care processes. This study found that an algorithmic prediction of failure modes in healthcare (APFMH) is more effective in identifying hazards and uses fewer resources (time and human resource investment) than traditional FMEA.

The use of PRN (“as needed”) medications is a common source of medication errors. The authors describe the implementation of staff education and a pediatric intensive care unit (PICU) order set (with predefined PRN orders), which led to increased compliance with Joint Commission medication management standards. The related editorial discusses how investment in human factors and ergonomics can contribute to healthcare quality and safety improvements.

This article describes the experience of one hospital in eastern Massachusetts implementing rapid response capabilities in an innovative, hybrid acute care-intensive care unit. Health system leadership used failure modes and effect analysis, process mapping, and on-site walkthroughs to identify potential hazards and opportunities for risk mitigation, as well as in situ simulation drills to facilitate team training.