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Classics and Emerging Classics

To help our readers navigate the tremendous breadth of the PSNet Collection, AHRQ PSNet editors and advisors have given the designation of “Classic” to review articles, empirical studies, government and stakeholder reports, commentaries, and books of lasting importance to the patient safety field. These items have the potential to impact how providers approach care practice and are regularly referenced in the literature. More information on the selection process.

 

The “Emerging Classics” designation identifies those resources that may not have met the level of a “Classic” yet due to limited citation in the published literature or in the level of impact/contribution to the environment, but these are resources which our patient safety subject matter experts believe have the potential to drive change in the field.

Popular Classics

All Classics and Emerging Classics (1051)

Published Date
PSNet Publication Date
Displaying 1 - 20 of 1051 Results
Measurement Tool/Indicator
Classic
Agency for Healthcare Research and Quality
The AHRQ Patient Safety Indicators (PSIs) represent quality measures that make use of a hospital's available administrative data. The PSIs reflect the quality of inpatient care but also focus on preventable complications and iatrogenic events. Investigators have found PSIs to be a useful tool for understanding adverse events and identifying possible areas of improvement within health care delivery systems. Although relying on administrative data has clear limitations, select PSIs have been shown to accurately identify certain accidental inpatient injuries. The AHRQ Web site offers publicly available comparative data, along with resources and tools. Patient safety measurement methods are discussed in an AHRQ WebM&M perspective. Originally released in 2005, the PSI were most recently updated in August 2023.
Fact Sheet/FAQs
Classic
Horsham, PA; Institute for Safe Medication Practices: July 2023.
Drawing on information gathered from the ISMP Medication Errors Reporting Program, this fact sheet provides a comprehensive list of commonly confused medication names, including look-alike and sound-alike name pairs. Drug name confusion can easily lead to medication errors, and the ISMP has recommended interventions such as the use of tall man lettering in order to prevent such errors. An error due to sound-alike medications is discussed in this AHRQ WebM&M commentary.
Department of Health and Human Services, Agency for Healthcare Research and Quality, Department of Defense.
Effective teamwork plays an essential role in providing safe patient care. The Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) program was developed inititally in collaboration by the United States Department of Defense and AHRQ in order to support effective communication and teamwork in health care. The 3.0 version of the widely implemented program is organized around 5 key strategies: patient focus, integrated platform, modular course design, active adult learning and emergent team challenges and opportunities. It provides new tools to measure its impact, supports increased emphasis on the role of patients in teams, and includes a new pocket guide. A PSNet WebM&M commentary discussed how improved teamwork and shared decision-making might have prevented a missed diagnosis of sepsis that lead to the death of a patient.
Measurement Tool/Indicator
Classic
Rockville MD: Agency for Healthcare Research and Quality; 2020.
Culture has been described as a key to establishing high reliability organizations. The National Quality Forum's Safe Practices for Healthcare and the Leapfrog Group both mandate hospitals to regularly assess their safety culture. This AHRQ Web site provides validated safety culture survey tools (Hospital, Medical Office, Nursing Home, Community Pharmacy, Ambulatory Surgery Center), user guides health care organizations can use to implement the surveys and a bibliography of articles discussing the use of SOPS in the field. Organizations can also use the AHRQ database to compare their Surveys on Patient Safety Culture™ (SOPS®) results. In addition, reports are available that summarize the benchmarking data across cohorts nationwide. An AHRQ WebM&M perspective discussed how to establish a safety culture.
Nutbeam D, Lloyd JE. Annu Rev Public Health. 2021;42:159-173.
Health literacy is a social determinant of health and can affect the ways people understand and interact with the health system. This review describes categories of health literacy, how it functions as a social determinant of health, and interventions to improve health literacy at system, community, and individual levels.
Special or Theme Issue
Emerging Classic
Health Informatics J. 2020;26:181-189;576-591;683-718;1017-1042;2295-2299;3123-3162.
This special collection examines the use of novel health information technology (HIT) to promote patient safety and challenges in examining the impact of those technologies. Articles featured in this issue include a focus on qualitative approaches to evaluating the impact of HIT on patient safety, particularly through a sociotechnical lens.
Alqenae FA, Steinke DT, Keers RN. Drug Saf. 2020;43:517-537.
This systematic review of 54 studies found that over half of adult and pediatric patients experienced a medication error post-discharge, and that these errors regularly involved common drug classes such as antibiotics, antidiabetics, analgesics, and cardiovascular drugs. The authors suggest that future research examine the burden of post-discharge medication errors, particularly in pediatric populations.
Tschandl P, Rinner C, Apalla Z, et al. Nat Med. 2020;26:1229-1234.
This study explored the use of artificial intelligence (AI)-based support in clinical decision-making in dermatology. The authors propose a framework for future research on image-based diagnostics to improve AI use in clinical practice.
McCradden MD, Joshi S, Anderson JA, et al. J Am Med Info Asso. 2020;27:2024-2027.
The authors discuss the challenges social inequalities pose to machine learning models, provide several recommendations for adopting ethical principles for the delivery of machine learning-assisted health care.
Burke JR, Downey C, Almoudaris AM. J Patient Saf. 2022;18:e140-e155.
This systematic review identified three critical points that can contribute to “failure to rescue” among inpatients with serious complications – (1) failure to recognize the complications; (2) failure to relay information regarding the complications to the care team, and; (3) failure to react in a timely and appropriate manner to the patient’s deterioration. Effective tools and interventions which can be implemented during each timepoint are discussed, including increased nurse staffing, rapid response teams, checklists, and early warning score systems.
Landrigan CP, Rahman SA, Sullivan JP, et al. N Engl J Med. 2020;382:2514-2523.
This multicenter cluster randomized trial explored the impact of eliminating extended-duration  work schedules (shifts in excess of 24 hours) on serious medical errors made by residents in the pediatric intensive care unit (ICU). The authors found that residents in ICUs which eliminated extended shifts in favor of day and night shifts of 16 hours or less made significantly more serious errors than residents assigned to extended-duration work schedules. The authors observed that the resident-to-patient ratio was higher during schedules which eliminated extended shifts, but also that these results might have been confounded by concurrent increases in workload in ICUs eliminating extended shifts.
Haghani M, Bliemer MCJ, Goerlandt F, et al. Safety Sci. 2020;129:104806.
This review discusses the most common research on COVID-19 and safety issues to date (e.g., occupational safety of heath professionals, patient transport safety) and identifies several safety issues attributable to the pandemic which have been relatively understudied, including issues around supply-chain safety and occupational safety of non-healthcare essential workers.
Decamp M, Lindvall C. J Am Med Inform Assoc. 2020;27:2020-2023.
This article discusses challenges related to latent bias in artificial intelligence (AI) algorithms in medicine and proposes several ways to manage these biases through proactive approaches, regulatory frameworks, and stakeholder engagement in AI design and implementation.
Neves AL, Freise L, Laranjo L, et al. BMJ Qual Saf. 2020;29:1019-1032.
This systematic review evaluated the impact of providing patients with access to electronic health records (EHR) on measures of quality of care (i.e., patient-centeredness, effectiveness, efficiency, timeliness, equity, and safety). Meta-analysis found that sharing EHRs with patients is effective in reducing HbA1c levels; the included studies generally found positive effects on patient-centeredness, health outcomes, and adherence to preventative services. However, the authors concluded that more methodologically robust studies are necessary to quantitatively assess the impact of sharing EHRs with patients.  
Vyas DA, Eisenstein LG, Jones DS. N Engl J Med. 2020;383(9):874-882.
Physicians commonly use diagnostic algorithms and practice guidelines to individualize risk assessment and guide clinical decisions. The authors discuss the possible dangers of using race-adjusted algorithms due to their potential to lead to diagnostic errors and delays in care.
Rangachari P, L. Woods J. Int J Environ Res Public Health. 2020;17:4267.
This article discusses the impact of the lack of healthcare worker support on resilience, patient safety, and staff retention during the COVID-19 pandemic and provides recommendations for better supporting psychological safety among healthcare workers. 
Bell SK, Delbanco T, Elmore JG, et al. JAMA Netw Open. 2020;3:e205867.
This study surveyed over 22,800 patients across three health care organizations to assess how often patients who read open ambulatory visit notes perceive mistakes in the notes. The analysis found that 4,830 patients (21%) perceived a mistake in one or more notes in the past 12 months and that 42% of those patients considered the mistake to be somewhat or very serious. The most common very serious mistakes involved incorrect diagnoses; medical history; allergy or medication; or tests, procedures, or results. Older and sicker patients were more likely to report a serious error compared to younger and healthier patients. Using open notes and encouraging patient engagement can improve record accuracy and prevent medical errors

Public Health England. London, UK: Crown Copyright; 2020.

The COVID-19 pandemic has revealed weaknesses in health care systems worldwide that have affected drug distribution, worker safety and health equity. This report provides a stakeholder analysis of societal conditions affecting patients with coronavirus in the United Kingdom. The authors conclude that racism and discrimination must be considered to correct inequities that impact safe care for Black Asian Minority Ethnic (BAME) patients to effectively respond to COVID-19.    
Dennerlein JT, Burke L, Sabbath EL, et al. Hum Factors. 2020;62:689–696.
The authors reviewed emerging workplace recommendations for reducing workers’ exposures to COVID-19 and, using human factors and ergonomic principles, proposed an approach for supporting worker safety, health and well-being during the pandemic. The recommended approach includes six key characteristics: (1) leadership commitment; (2) policies, programs and practices fostering supportive working conditions; (3) stakeholder participation at every level of the organization; (4) comprehensive and collaborative strategies; (5) adherence to state and federal regulations, as well as ethical norms, and; (6) commitment to data-driven change and continuous improvement. 
Leveson N, Samost A, Dekker SWA, et al. J Patient Saf. 2020;16:162-167.
This article describes the use of a new accident analysis technique (CAST, or Causal Analysis based on Systems Theory), an alternative approach to root cause analysis. The CAST approach is based on the principle that accidents are not only the result of individual system component failures or errors but more generally result due to inadequate enforcement of constraints on the behavior of the system components (i.e., safety constraints enforced by controls, such as checklists).  Many adverse events (AEs) appear to be related to the design of the system involved and not attributable to unsafe individual behavior. This technique can be useful in identifying causal factors to help health care systems learn from mistakes and design systems-level changes to prevent future AEs.