The PSNet Collection: All Content

The AHRQ PSNet Collection comprises an extensive selection of resources relevant to the patient safety community. These resources come in a variety of formats, including literature, research, tools, and Web sites. Resources are identified using the National Library of Medicine’s Medline database, various news and content aggregators, and the expertise of the AHRQ PSNet editorial and technical teams.

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Displaying 1 - 20 of 1642 Results

Remote Response Team and Customized Alert Settings Help Improve Management of Sepsis

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Patient Safety Innovation May 31, 2023

Seeking a sustainable process to enhance their hospitals’ response to sepsis, a multidisciplinary team at WellSpan Health oversaw the development and implementation of a system that uses customized electronic health record (EHR) alert settings and a team of remote nurses to help frontline staff identify and respond to patients showing signs of sepsis. When the remote nurses, or Central Alerts Team (CAT), receive an alert, they assess the patient’s information and collaborate with the clinical care team to recommend a response.

Reducing errors resulting from commonly missed chest radiography findings.

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Gefter WB, Hatabu H. Chest. 2023;163:634-649.

Cognitive bias, fatigue, and shift work can increase diagnostic errors in radiology. This commentary recommends strategies to reduce these errors in diagnostic chest radiography, including checklists and improved technology (e.g., software, artificial intelligence). In addition, the authors offer practical step-by-step recommendations and a sample checklist to assist radiologists in avoiding diagnostic errors.

Use of technology to improve the adherence to surgical safety checklists in the operating room.

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Pati AB, Mishra TS, Chappity P, et al. Jt Comm J Qual Patient Saf. 2023;Epub Apr 22.

The World Health Organization (WHO) Surgical Safety Checklist is widely used, but implementation challenges remain. This article describes the development of an electronic version of the surgical safety checklist adapted for use on a personal device, and compared its use against the traditional paper-based checklist. The electronic checklist had 100% use (compared to 98% for the traditional checklist) and significantly higher frequency of completion (100% vs. 27%).

Clinical Investigation Booking Systems Failures: Written Communications in Community Languages.

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Farnborough, UK: Healthcare Safety Investigation Branch; April 2023.

Gaps in patient information processes can result in missed care opportunities that contribute to harm. This report examines language discordance in National Health Service written scheduling communications and its contribution to patients being lost to follow up. The primary improvement recommendation is to enhance the ability of providers to recognize primary languages of patients and provide written instructions accordingly.

Danger in discharge summaries: abbreviations create confusion for both author and recipient.

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Coghlan A, Turner S, Coverdale S. Intern Med J. 2023;53:550-558.

Use of abbreviations in electronic health records increases risk of misunderstandings, particularly between providers of different specialties. In this study, junior doctors and general practitioners were asked about their understanding of common, uncommon, and rare abbreviations used in hospital discharge notes. No abbreviation was interpreted in the same way by all respondents, and nearly all respondents left at least one abbreviation blank or responded that they didn't know.

Interorganizational health information exchange-related patient safety incidents: a descriptive register-based qualitative study.

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Hyvämäki P, Sneck S, Meriläinen M, et al. Int J Med Inform. 2023;174:105045.

Insufficient or incorrect transfer of patient information, whether caused by human or organizational factors, can result in adverse events during transitions of care. This study used four years of incident reports to identify the types, causes, and consequences of health information exchange- (HIE) related patient safety incidents in emergency care, (ED) emergency medical services (EMS), or home care. The two main kinds of HIE-related incidents were (1) inadequate documentation and inadequate use of information (e.g., deficiencies in content), and (2) causes related to the health professional or organization; consequences were adverse events or additional actions to prevent, avoid, and correct adverse events.

AI may be on its way to your doctor’s office, but it’s not ready to see patients.

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Tahir D. KFF Health News. May 12, 2023.

Real-time use of artificial intelligence (AI) in health care settings continues to cause concern despite its potential to improve care. This article examines current efforts to develop AI applications for health care and the reasons for oversight to protect privacy, reduce bias, and prevent misinformation.

Qualitative perspectives of emergency nurses on electronic health record behavioral flags to promote workplace safety.

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Seeburger EF, Gonzales R, South EC, et al. JAMA Netw Open. 2023;6:e239057.

Verbal or physical violence towards healthcare workers can result in harm of both staff and patients. Based on semi-structured interviews with 25 registered nurses working in the emergency department (ED) at one large academic health system, the authors explored nursing perspectives on how EHR-based behavioral flags – used to identify incidents of workplace violence – can promote clinician safety. Participants identified benefits of the flags as well as concerns (e.g., introduction of bias, potential damage to the patient-clinician relationship), highlighted necessary system improvements, and how related challenges in the ED (e.g., unmet mental health needs of patients, COVID-19-related burnout) can contribute to workplace violence.

Improving safety during transitions of care through the use of electronic referral loops to receive and reconcile health information.

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Allen G, Setzer J, Jones R, et al. Jt Comm J Qual Patient Saf. 2023;49:247-254.

Reconciling medication lists at transitions of care is a widely recognized safety strategy; however, other parts of the electronic health record (EHR) - allergies and problem lists - also need reconciliation. This article describes an academic medical system's quality improvement project to increase rates of complete reconciliation of problems, medications, and allergies in the EHR. Twenty-six cycles of Plan-Do-Study-Act increased completion rates from 20% to 80%.

Factors contributing to preventing operating room "never events": a machine learning analysis.

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Arad D, Rosenfeld A, Magnezi R. Patient Saf Surg. 2023;17:6.

Surgical never events are rare but devastating for patients. Using machine learning, this study identified 24 contributing factors to two types of surgical never events - wrong site surgery and retained items. Communication, the number and type of staff present, and the type and length of surgery were identified contributing factors.

Curated Libraries

Implementation of Patient Safety Projects Curated Library

May 4, 2023

The implementation of effective patient safety initiatives is challenging due to the complexity of the health care environment. This curated library shares resources summarizing overarching ideas and strategies that can aid in successful program execution, establishment, and sustainability.

VA pauses $16B Oracle Cerner EHR deployments indefinitely to address error-ridden early rollout.

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Muoio D. Fierce Healthcare. April 21, 2023.

Notable problems have occurred during the testing of the new electronic health records (EHR) system being designed for use in Veterans Affairs hospitals. This news article discusses the temporary halt of the project as the Department reassesses issues that have arisen during test rollouts in several United States hospitals.

More than algorithms: an analysis of safety events involving ML-enabled medical devices reported to the FDA.

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Lyell D, Wang Y, Coiera E, et al. J Am Med Inform Assoc. 2023;Epub Apr 18.

Patients and healthcare providers rely on devices that use artificial intelligence or machine learning in diagnostics, treatment, and monitoring. This study utilizes adverse event reports submitted to the FDA's Manufacturer and Use Facility Device Experience (MAUDE) database for machine learning-enabled devices. Mammography was implicated in 69% of reports, and the majority were near-miss events.

Optimizing measurement of misdiagnosis-related harms using symptom-disease pair analysis of diagnostic error (SPADE): comparison groups to maximize SPADE validity.

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Liberman AL, Wang Z, Zhu Y, et al. Epub Apr 5. 2023.

Symptom–Disease Pair Analysis of Diagnostic Error (SPADE) is a framework to measure diagnostic errors using existing databases, such as electronic health records or administrative claims. The original developers of the SPADE framework provide additional guidance on types of comparator groups, how to select the appropriate group, and what inferences can be drawn from the analysis.

Identifying electronic health record contributions to diagnostic error in ambulatory settings through legal claims analysis.

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Krevat S, Samuel S, Boxley C, et al. JAMA Netw Open. 2023;6:e238399.

The majority of healthcare providers use electronic health record (EHR) systems but these systems are not infallible. This analysis used closed malpractice claims from the CRICO malpractice insurance database to identify whether the EHR contributes to diagnostic error, the types of errors, and where in the diagnostic process errors occur. EHR contributed to diagnostic error in 61% of claims, the majority in outpatient care, and 92% at the testing stage.

APSF Stoelting Conference.

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Anesthesia Patient Safety Foundation. September 6–7, 2023; Red Rock Casino Resort and Spa, Las Vegas, NV.

Anesthesia is a high-risk activity that has achieved safety successes. This hybrid conference will explore topics related to the theme of “Emerging Medical Technologies – A Patient Safety Perspective on Wearables, Big Data and Remote Care.”

Surveillance Monitoring to Improve Patient Safety in Acute Hospital Care Units

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Perspective on Safety April 26, 2023

This piece discusses surveillance monitoring of patients in low-acuity units of the hospital to prevent failure to rescue events, its difference from high-acuity continuous monitoring, and its potential applications in other settings.

In Conversation with Susan McGrath, PhD and George Blike, MD about Surveillance Monitoring

Drs. Susan McGrath and George Blike discuss surveillance monitoring and its challenges and opportunities.

The Danger of 10% Intravenous Calcium Chloride Extravasation.

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WebM&M Case April 26, 2023

This case represents a known but generally preventable complication of calcium chloride infusion, eventually necessitating surgical amputation of the patient’s left fourth (ring) finger. The commentary discusses the importance of correctly identifying IV fluids as irritants or vesicants, risks associated with the use of vesicants such as calcium chloride, and the role of early recognition of infiltration and extravasation and symptom management to minimize tissue damage and accelerate healing.

Understanding complexity in a safety critical setting: a systems approach to medication administration.

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Stevens EL, Hulme A, Goode N, et al. Appl Ergon. 2023;110:104000.

Medication administration is a complex process with many opportunities for error. Using the Event Analysis of Systemic Teamwork (EAST) model, researchers identified opportunities to improve medication administration system performance and promote patient safety. The authors discuss the networks involved in medication administration (e.g., task network, social network, information network) and how the complexities involved in each network contribute to medication administration errors.

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

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Damiani G, Altamura G, Zedda M, et al. BMJ Open. 2023;13:e065301.

Artificial intelligence (AI) is increasingly used to identify and prevent patient safety threats. This review focuses on AI used to reduce medication errors in the primary care setting. Most studies targeted the prescribing stage, and the main category of AI was computerized decision support system.

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