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Transitions from one electronic health record (EHR) system to another can increase the risk of patient safety events. Using the principles of requisite imagination, this article outlines six recommendations for safe EHR transitions through proactive approaches, process improvement and support for healthcare workers.

Early warning systems (EWS) use patient data from the electronic health record to alert clinicians to potential patient deterioration. Twelve months after a new EWS was implemented in one hospital, nurses were interviewed to gather their perspectives on the program experience, utility, and implementation. Six themes emerged: timeliness, lack of accuracy, workflow interruptions, actionability of alerts, underappreciation of core nursing skills, and opportunity cost.

Clinical decision support (CDS) systems are designed to improve diagnosis. Researchers surveyed emergency department physicians about their evaluation of human factors-based CDS systems to improve diagnosis of pulmonary embolism. Although perceived usability was high, use of the CDS tool in the real clinical environment was low; the authors identified several barriers to use, including lack of workflow integration.

Alert fatigue contributes to task burden and can threaten patient safety. In this study, researchers at one academic medical center found that machine learning techniques could enable intelligent filtering of medication alerts and reduce alert volume by 54%.

Comprehensive implementation of reporting and learning systems (RLS, also known as incident reporting systems) is important for its successful use as a patient safety improvement tool. This study aimed to develop a set of “implementation patient safety indicator(s) sets” to monitor the extent to which an RLS has been implemented in hospitals. Implementation outcomes include acceptability, adoption, appropriateness, implementation costs, feasibility, fidelity, penetration, and sustainability. Study participants rated acceptability and sustainability as most relevant to successful implementation.

Electronic health records (EHR) can improve patient care and safety but are not without potential risks. A cyberattack led to a 25-day shutdown of a hospital’s EHR that necessitated a rapid shift to manual processes. This article outlines the laboratory service’s processes during the shutdown, including patient safety and error reduction, billing, and maintaining compliance with regulatory policies.

Electronic health record (EHR) workarounds arise when users bypass safety features to increase efficiency. This scoping review aimed to validate, refine, and enrich the Sociotechnical EHR Workaround Analysis (SEWA) framework. Multidisciplinary teams (e.g. leadership, providers, EHR developers) can now use the refined SEWA framework to identify, analyze and resolve unsafe workarounds, leading to improved quality and efficiency of care.

Hospitals in the US can evaluate the safety of their computerized provider order entry using a simulation tool such as the one provided by the Leapfrog Group. This study developed a similar simulation tool for use in the UK. Study participants rated 178 clinical scenarios for likelihood of occurrence, level of associated harm, and likelihood of harm. One hundred and thirty-one extreme or high-risk prescribing scenarios were developed and will be used to create the evaluation tool.

Clinical decision support systems (CDSS) can help identify potential drug-drug interactions (DDI), but they can lead to alert fatigue and threaten patient safety. Based on an analysis of DDI alerts and survey data regarding physician experience using the DDI module in the CDSS, researchers identified barriers (i.e., lack of patient-specific characteristics and DDI-specific screening intervals) that contribute to false-positive alerts and alert fatigue.

Clinical decision support (CDS) helps clinicians select appropriate medications, arrive at a correct diagnosis, and improve intraoperative decision making. Through interviews with health system executives, clinicians, and artificial intelligence (AI) experts, this study presents multiple perspectives on selection and adoption of AI-CDS in healthcare. Four emerging trends are presented: (1) AI must solve a priority problem; (2) the tool must be tested with the health system’s patient population; (3) it should generate a positive return on investment; and (4) it should be implemented efficiently and effectively.

Computerized decision support alerts for drug-drug interactions are commonly overridden by clinicians. This study examined fifteen well-known drug-drug interactions and identified risk factors that could reduce risk in the majority of interactions (e.g., medication order timing, medication dose, and patient factors).

Failure to follow up on abnormal diagnostic test results can cause delays in patients receiving appropriate care. This hospital used an artificial intelligence natural language processing system to identify radiology reports requiring follow-up. The system triggered automated notifications to the patient and ordering provider, and tracked follow-ups to completion. System development, deployment and next steps are detailed.

Voluntary error reporting remains underutilized in many clinical settings despite its importance for organizational learning and improved patient safety. This pediatric health system implemented a new safety event management system (SEMS) aimed at increased usability, de-centralized event follow-up, and closed-loop communication. The new SEMS resulted in more event reporting and less staff time spent on each report.

The COVID pandemic has increased demand and acceptance of remote care modalities. This commentary suggests that home monitoring is a promising telehealth approach and that its application could improve value while enhancing safety for hospital-at-home and other levels of home-based care patients.

Advanced technology – such as radiofrequency identification (RFID), sensors, or mobile apps – is increasingly used to improve patient safety. This study explored whether the use of “internet of things” (i.e., network of physical objects – “things” – that are embedded with sensors, software or other technology to connect and exchange data with other devices, such as RFID technology) is effective at reducing patient falls and improving hand-hygiene compliance.

The OpenNotes concept is positioned  to increase patient engagement in their care through error correction and communication enhancement. This commentary highlights concerns associated with privacy involving certain conditions and patient groups that participate in open notes programs. The authors provide recommendations to ensure safety while enabling effective information sharing with all patient populations.

Failure to communicate abnormal test results to patients can lead to significant health complications and medical malpractice claims. This study aimed to increase patient engagement in asking their provider about previously obtained diagnostic test results. Reminders to follow up with their provider about test results were sent to the patient via the after-visit summary and patient portal. Patients receiving reminders were up to 20 times more likely to ask their providers about their test results, compared to patients who did not receive reminders.