Challenges and opportunities from the Agency for Healthcare Research and Quality (AHRQ) research summit on improving diagnosis: a proceedings review

Henriksen, K; Dymek, Chris; Harrison, Michael I.; Brady, Paul; Arnold, Sharon B.

doi:10.1515/dx-2017-0016

Cited by 19 publications

(13 citation statements)

References 38 publications

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“…This directly addresses a major patient safety and public health need 19 which we believe could be transformational for improving diagnosis in healthcare by surfacing otherwise hidden diagnostic errors. The SPADE approach leverages symptom-disease pairs and uses statistically controlled inferential analyses of large data sets to construct operational outcome metrics that could be incorporated into diagnostic performance dash-boards.…”

Section: Discussionmentioning

confidence: 99%

“…9 A major advantage of SPADE is that the core, essential administrative data are already being collected and could be easily used to track diagnostic performance without significant financial burdens. Because these data are also available from past years, internal performance trend lines could be readily constructed.…”

Section: Using Spade To Measure Diagnostic Performance and Impact Of mentioning

confidence: 99%

“…Valid operational measures are badly needed to surface this problem so that it can be quantified, monitored and tracked. 9 Existing measures of diagnostic error that rely on manual chart review to confirm diagnostic errors suffer from problems of poor chart documentation, 1011 low inter-rater reliability, 1213 hindsight bias 14 and the high costs of human labour needed for chart abstraction. Additionally, reliance on chart review alone will likely lead to an underestimation of diagnostic error since key clinical features necessary to identify errors are preferentially missing from charts where errors occur.…”

Section: Introductionmentioning

confidence: 99%

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Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data

Liberman

Newman‐Toker

2018

BMJ Qual Saf

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Background The public health burden associated with diagnostic errors is likely enormous, with some estimates suggesting millions of individuals are harmed each year in the USA, and presumably many more worldwide. According to the US National Academy of Medicine, improving diagnosis in healthcare is now considered ‘a moral, professional, and public health imperative.’ Unfortunately, well-established, valid and readily available operational measures of diagnostic performance and misdiagnosis-related harms are lacking, hampering progress. Existing methods often rely on judging errors through labour-intensive human reviews of medical records that are constrained by poor clinical documentation, low reliability and hindsight bias. Methods Key gaps in operational measurement might be filled via thoughtful statistical analysis of existing large clinical, billing, administrative claims or similar data sets. In this manuscript, we describe a method to guantify and monitor diagnostic errors using an approach we call ‘Symptom-Disease Pair Analysis of Diagnostic Error’ (SPADE). Results We first offer a conceptual framework for establishing valid symptom-disease pairs illustrated using the well-known diagnostic error dyad of dizziness-stroke. We then describe analytical methods for both look-back (casecontrol) and look-forward (cohort) measures of diagnostic error and misdiagnosis-related harms using ‘big data’. After discussing the strengths and limitations of the SPADE approach by comparing it to other strategies for detecting diagnostic errors, we identify the sources of validity and reliability that undergird our approach. Conclusion SPADE-derived metrics could eventually be used for operational diagnostic performance dashboards and national benchmarking. This approach has the potential to transform diagnostic quality and safety across a broad range of clinical problems and settings.

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Section: Discussionmentioning

confidence: 99%

Section: Using Spade To Measure Diagnostic Performance and Impact Of mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data

Liberman

Newman‐Toker

2018

BMJ Qual Saf

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“…Other factors related to diagnostic error, such as the presence of patient harm (e.g., clear evidence of harm versus "near-misses"), preventability, and actionability, may also be important to define in advance so that the selected measurement strategy aligns with the learning and improvement goals. Nevertheless, the science of understanding the complex mix of cognitive and sociotechnical contributory factors and implementing effective solutions based on these data still needs additional development [100][101][102].…”

Section: Synthesizing Data and Enhancing Confidence In Measurementmentioning

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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“…[3][4][5] However, substantial research gaps remain that limit diagnostic error reduction. [6][7][8] This is not surprising because the diagnostic process is inherently complex and involves decisionmaking under uncertain conditions and limited time. [9][10][11] The science of reducing diagnostic error remains underdeveloped and requires newer approaches, especially because the current medical research funding largely adopts a diseasefocused approach, whereas the diagnostic process cuts across thousands of diseases.…”

Section: Introductionmentioning

confidence: 99%

Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise

et al. 2021

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Background Diagnostic errors are a major source of preventable harm but the science of reducing them remains underdeveloped. Objective To identify and prioritize research questions to advance the field of diagnostic safety in the next 5 years. Participants Ninety-seven researchers and 42 stakeholders were involved in the identification of the research priorities. Design We used systematic prioritization methods based on the Child Health and Nutrition Research Initiative (CHNRI) methodology. We first invited a large international group of expert researchers in various disciplines to submit research questions while considering five prioritization criteria: (1) usefulness, (2) answerability, (3) effectiveness, (4) potential for translation, and (5) maximal potential for effect on diagnostic safety. After consolidation, these questions were prioritized at an in-person expert meeting in April 2019. Top-ranked questions were subsequently reprioritized through scoring on the five prioritization criteria using an online questionnaire. We also invited non-research stakeholders to assign weights to the five criteria and then used these weights to adjust the final prioritization score for each question. Key Results Of the 207 invited researchers, 97 researchers responded and 78 submitted 333 research questions which were then consolidated. Expert meeting participants (n = 21) discussed questions in different breakout sessions and prioritized 50, which were subsequently reduced to the top 20 using the online questionnaire. The top 20 questions addressed mostly system factors (e.g., implementation and evaluation of information technologies), teamwork factors (e.g., role of nurses and other health professionals in the diagnostic process), and strategies to engage patients in the diagnostic process. Conclusions Top research priorities for advancing diagnostic safety in the short-term include strengthening systems and teams and engaging patients to support diagnosis. High-priority areas identified using these systematic methods can inform an actionable research agenda for reducing preventable diagnostic harm.

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Challenges and opportunities from the Agency for Healthcare Research and Quality (AHRQ) research summit on improving diagnosis: a proceedings review

Cited by 19 publications

References 38 publications

Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data

Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data

Operational measurement of diagnostic safety: state of the science

Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise

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