Finding Diagnostic Errors in Children Admitted to the PICU

Davalos, Maria Caridad; Samuels, Kenya; Meyer, Ashley N. D.; Thammasitboon, Satid; Sur, Moushumi; Roy, Kevin; Al-Mutairi, Aymer; Singh, Hardeep

doi:10.1097/pcc.0000000000001059

Cited by 42 publications

(37 citation statements)

References 26 publications

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“…Studies have shown that diagnostic errors and incorrect evaluations by physicians and health practitioners can range from 12% to 35%. 25,26 In addition, multiple studies have observed intra- and interobserver clinical assessment correlations between physicians and specialty trained health professionals to range between 22% and 73%. 27–29 Such variability between health-care professionals also likely contributed to our inter-rater reliability kappa value analysis (Table 4), thus supporting the Gwet’s AC 1 approach as a more reliable inter-rater reliability analysis for this study design.…”

Section: Discussionmentioning

confidence: 99%

Development and Initial Validation of a Frontline Health Worker mHealth Assessment Platform (MEDSINC®) for Children 2–60 Months of Age

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McLaughlin²,

Scarpino

et al. 2019

The American Journal of Tropical Medicine and Hygiene

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. Approximately 3 million children younger than 5 years living in low- and middle-income countries (LMICs) die each year from treatable clinical conditions such as pneumonia, dehydration secondary to diarrhea, and malaria. A majority of these deaths could be prevented with early clinical assessments and appropriate therapeutic intervention. In this study, we describe the development and initial validation testing of a mobile health (mHealth) platform, MEDSINC ® , designed for frontline health workers (FLWs) to perform clinical risk assessments of children aged 2–60 months. MEDSINC is a web browser–based clinical severity assessment, triage, treatment, and follow-up recommendation platform developed with physician-based Bayesian pattern recognition logic. Initial validation, usability, and acceptability testing were performed on 861 children aged between 2 and 60 months by 49 FLWs in Burkina Faso, Ecuador, and Bangladesh. MEDSINC-based clinical assessments by FLWs were independently and blindly correlated with clinical assessments by 22 local health-care professionals (LHPs). Results demonstrate that clinical assessments by FLWs using MEDSINC had a specificity correlation between 84% and 99% to LHPs, except for two outlier assessments (63% and 75%) at one study site, in which local survey prevalence data indicated that MEDSINC outperformed LHPs. In addition, MEDSINC triage recommendation distributions were highly correlated with those of LHPs, whereas usability and feasibility responses from LHP/FLW were collectively positive for ease of use, learning, and job performance. These results indicate that the MEDSINC platform could significantly increase pediatric health-care capacity in LMICs by improving FLWs’ ability to accurately assess health status and triage of children, facilitating early life-saving therapeutic interventions.

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Section: Discussionmentioning

confidence: 99%

Development and Initial Validation of a Frontline Health Worker mHealth Assessment Platform (MEDSINC®) for Children 2–60 Months of Age

Finette

McLaughlin²,

Scarpino

et al. 2019

The American Journal of Tropical Medicine and Hygiene

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“…There is also an opportunity to leverage peer review programs to improve diagnostic self-assessment, feedback, and improvement [42]. Similarly, autopsy reports [43], diagnostic discrepancies at admission versus discharge [44,45], escalations of care [46,47], and malpractice claims [48][49][50][51] may be reviewed with special attention to opportunities to improve diagnosis. These data sources may not shed light on the frequency or scope of a problem, but they can help raise awareness of the impact and harm of diagnostic errors and, in some cases, specific opportunities for improvement.…”

Section: Learning From Known Incidents and Reportsmentioning

confidence: 99%

Operational measurement of diagnostic safety: state of the science

2020

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Reducing the incidence of diagnostic errors is increasingly a priority for government, professional, and philanthropic organizations. Several obstacles to measurement of diagnostic safety have hampered progress toward this goal. Although a coordinated national strategy to measure diagnostic safety remains an aspirational goal, recent research has yielded practical guidance for healthcare organizations to start using measurement to enhance diagnostic safety. This paper, concurrently published as an Issue Brief by the Agency for Healthcare Research and Quality, issues a “call to action” for healthcare organizations to begin measurement efforts using data sources currently available to them. Our aims are to outline the state of the science and provide practical recommendations for organizations to start identifying and learning from diagnostic errors. Whether by strategically leveraging current resources or building additional capacity for data gathering, nearly all organizations can begin their journeys to measure and reduce preventable diagnostic harm.

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“…1 There is now a solid—and growing—body of evidence showing that diagnostic errors occur with substantial frequency in inpatients, outpatients, and even children. 2–4 The causative factors contributing to diagnostic errors are both complex and increasingly understood across multiple contexts. Cognitive factors— related to both lack of and misapplication of knowledge as well as faulty cognition—contribute substantially to diagnostic errors as do factors related to the flawed “nonsystem” that is the US health care system.…”

mentioning

confidence: 99%