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Abstract
Objectives To apply a human factors framework to understand whether checklists to reduce clinical diagnostic error have (1) gaps in composition; and (2) components that may be more likely to reduce errors.
Design Systematic review.
Data sources PubMed, EMBASE, Scopus and Web of Science were searched through 15 February 2022.
Eligibility criteria Any article that included a clinical checklist aimed at improving the diagnostic process. Checklists were defined as any structured guide intended to elicit additional thinking regarding diagnosis.
Data extraction and synthesis Two authors independently reviewed and selected articles based on eligibility criteria. Each extracted unique checklist was independently characterised according to the well-established human factors framework: Systems Engineering Initiative for Patient Safety 2.0 (SEIPS 2.0). If reported, checklist efficacy in reducing diagnostic error (eg, diagnostic accuracy, number of errors or any patient-related outcomes) was outlined. Risk of study bias was independently evaluated using standardised quality assessment tools in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
Results A total of 30 articles containing 25 unique checklists were included. Checklists were characterised within the SEIPS 2.0 framework as follows: Work Systems subcomponents of Tasks (n=13), Persons (n=2) and Internal Environment (n=3); Processes subcomponents of Cognitive (n=20) and Social and Behavioural (n=2); and Outcomes subcomponents of Professional (n=2). Other subcomponents, such as External Environment or Patient outcomes, were not addressed. Fourteen checklists examined effect on diagnostic outcomes: seven demonstrated improvement, six were without improvement and one demonstrated mixed results. Importantly, Tasks-oriented studies more often demonstrated error reduction (n=5/7) than those addressing the Cognitive process (n=4/10).
Conclusions Most diagnostic checklists incorporated few human factors components. Checklists addressing the SEIPS 2.0 Tasks subcomponent were more often associated with a reduction in diagnostic errors. Studies examining less explored subcomponents and emphasis on Tasks, rather than the Cognitive subcomponents, may be warranted to prevent diagnostic errors.
- Key Words
- checklists
- diagnostic error
- human factors
Data availability statement
No data are available.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
This is the first review to use a human factors framework to study checklists aimed at reducing diagnostic error.
The search’s broadness and inclusiveness help in finding trends among the checklists literature that’s still in its infancy.
Despite its broadness and inclusiveness, elements outside Systems Engineering Initiative for Patient Safety 2.0 (SEIPS 2.0) may also be important in evaluating diagnostic checklists.
Characterising clinical diagnosis checklists according to SEIPS 2.0 can be subjective.
Introduction
Diagnostic error is a leading cause of mortality in the USA.1–3 As a preventable source of patient harm, errors in diagnosis represent a key opportunity to improve patient safety.1–4 Diagnostic errors are multifactorial in aetiology—individual aspects such as faulty reasoning and cognitive biases as well as system processes related to data retrieval and distractions are all posited to be associated with errors.5–7 To reduce patient harm, several system (eg, trigger alerts in times at high risk) and individual interventions (eg, training against common biases) have been tested.8–10 Yet, to date, successful interventions to reduce diagnostic error remain elusive.
Beyond diagnostic errors, one approach shown to be efficacious in preventing errors and improving safety is the checklist.11 Used in myriad fields including military, agriculture and aviation,12–15 checklists organise processes into sequential, step-by-step tasks, thus simplifying complex work. In similar fashion, human factors, a discipline established in most safety critical industries, uses knowledge about human behaviour to design safer systems.16 In medicine, integration of checklists and human factors engineering have been shown to improve safety in multiple domains including central line-associated bloodstream infections and surgical time-outs.17 18 However, whether these tools affect diagnostic outcomes remains unclear.19
While several checklists to reduce diagnostic errors have been published,20–22 whether and how human and systems factors are integrated within current checklist contents remains unknown. Challenges within cognitive, systems and patient factors have been identified as important root causes for diagnostic error.23–26 One may hypothesise that checklists may reduce diagnostic error by targeting all of these root causes; conversely those that focus on one or none of these issues are less likely to be successful. Alternatively, a single component of these checklists may represent the ‘active ingredient’, and therefore, may be a high-yield target for future research. To date, this empiric question has not been answered. Therefore, in this systematic review, we examined checklists aimed at decreasing diagnostic errors by utilising an established human factors framework: the Systems Engineering Initiative for Patient Safety 2.0 (SEIPS 2.0).27 The SEIPS 2.0 model has been widely adopted in healthcare research to advance patient safety and quality improvement.28–30 We used SEIPS 2.0 to study available clinical diagnosis checklists and understand which human factors are more associated with reducing diagnostic error.
Methods
We developed a review protocol (PROSPERO: CRD42019136830) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations for reporting our findings.31
Data sources and searches
A medical librarian (WT) performed serial literature searches between 30 April 2019 and 15 February 2022 for articles containing clinical diagnosis checklists. Databases were searched from inception and included PubMed, EMBASE, Scopus and Web of Science. Searches were designed for each database and included controlled vocabulary terms (eg, Medical Subject Headings), keywords to represent concepts, including “checklist,” “differential diagnosis” and “diagnostic errors.” No restrictions were placed on publication date, language or completion status. The full search strategy and code are available in the attached online supplemental file 1.
Supplemental material
Study selection
Articles were eligible for inclusion if they included one or more checklists aimed at improving the diagnostic process. To ensure rigour, in addition to articles where checklists were formally evaluated via experimental designs, we also included articles that proposed checklists without formal evaluation. Articles were excluded if they did not have an explicit checklist or if their checklists were solely for disease screening purposes; included checklists that were only intended to diagnose a specific disease (eg, melanoma); or if they focused on processes outside of diagnosis (eg, procedural/surgical safety checklists). If the same checklist was used in more than one study, each individual study was included provided that the study design and methods reporting checklist performance were substantively different. Checklists were defined broadly and included any multicomponent structured guide intended to elicit additional thinking regarding diagnosis. This included disease/symptom specific differential diagnosis checklists that incorporated a comprehensive list of items aimed at avoiding missing alternative diagnoses as well as general debiasing checklists aimed at avoiding missing basic steps in the diagnostic process (ie, checklists that lead to reproducible approach to diagnosis). Checklists did not necessitate physical box checking for inclusion, as only five published checklists included this requirement (online supplemental Table S1).
We considered peer-reviewed articles published in any language, but only included foreign language articles when an English translation was available. Two authors (JA-K and RFT) independently determined study eligibility; when necessary, differences were adjudicated by a third author (AG). Interrater agreement for study eligibility and data abstraction was assessed using the Cohen k coefficient.
Data extraction and quality assessment
Data were extracted from included articles independently and in duplicate by two authors (J.A. and RFT) using a template adopted from the Cochrane Collaboration32 (online supplemental file 1). Data on the study design, population, checklist content and study outcomes were extracted. Each study, when appropriate, was assessed for risk of bias (RoB) in its design, data synthesis and analysis, outcome-measuring and conclusion, by two authors using the following established and validated quality assessment tools: Cochrane’s RoB 2.0 tool for randomised studies,33 ROBINS-I tool for non-randomised quasi experimental studies,34 the Newcastle-Ottawa Scale for cohort studies (with control),35 and the National Institute of Health’s (NIH) Quality Assessment tool for pretest and post-test cohort studies without control (see online supplemental file 1 for references to those tools).36 Discrepancies in ratings were resolved after joint review and discussion.
Data synthesis and analysis
Checklist categorisation
We categorized elements targeted in diagnostic checklists using the SEIPS 2.0 framework. We chose SEIPS 2.0 as an organising structure to assess checklists because it considers clinical aspects, cognitive, human and system factors that can contribute to diagnostic errors and adverse events.37 The three primary components of SEIPS 2.0 include: Work System (including subcomponents of Person(s), Tasks, Internal Environment, External Environment, Tools and Technologies and Organisation), Processes (including subcomponents of Cognitive, Physical, and Social and Behavioural) and Outcomes (including subcomponents of Patient, Professional and Organisational).27
We examined included elements of each study checklist and assigned them to components or subcomponents of SEIPS 2.0. Within the Work System, checklist elements were characterised as Persons if they address factors such as clinicians’ level of clinical knowledge, clinicians or patients’ demeaner, or patient factors such as health status, age and level of education. Elements requesting that physicians perform actions to assist in the diagnostic process (eg, obtain history, order a test) were classified as Tasks. Checklist elements that focused on care setting (eg, location of care, workspace design and noise) were considered as targeting the Internal Environment, while those elements focused on the larger or the non-immediate environment (eg, leadership decisions and institutional policies) were categorised as targeting the External Environment. Elements advocating the use of tools (eg, digital aids) to assist in the diagnostic process were assigned to the Tools and Technology category. Finally, checklists that addressed factors, such as roles of providers, patient visit times or workload, were characterised as Organisation factors.
Within the Processes component, checklist elements targeting cognitive functions (eg, listing differential diagnosis, pausing to consider cognitive biases) were categorised as Cognitive Processes, whereas elements incorporating physical factors to aid diagnosis (eg, having to a computer to access patient charts readily) were categorised as Physical Processes. Elements advocating clinician communication with either team members or patients were categorised as Social and Behavioural subcomponents. Finally, within the Outcomes SEIPS 2.0 component, checklist elements were described as incorporating Patient (eg, patient satisfaction and quality of care), Professional (eg, clinicians’ fatigue and burnout), or Organisational (eg, employee turnover, staffing difficulties and compliance with regulations) Outcomes.
As most checklists on diagnostic errors focus on the cognitive contributions to error,20 we further described the cognitive components of included checklists as follows: (1) those that posed a list of differential diagnoses; (2) those that focused on urgent medical conditions; (3) those that included history, physical exam or tests and (4) those that highlighted common diagnostic pitfalls. These categories were created following a prospective review of selected checklists for factors known to reduce diagnostic error. For example, recognising diagnostic pitfalls and systematically narrowing down differential diagnoses are cognitive strategies to reduce diagnostic error.38 39 Given substantial heterogeneity within the included studies, formal metanalysis was not performed.
Checklist effectiveness in reducing diagnostic error
Articles that evaluated and reported outcomes (eg, diagnostic accuracy, number of diagnostic errors and any patient-related outcomes) on checklists effectiveness in reducing diagnostic error were categorised according to their study design and their outcomes. Those checklists were further classified based on inclusion of SEIPS 2.0 components for the purpose of identifying checklist components that may be associated with success or failure in reducing error.
Patient and public involvement
No patient was involved in this study.
Results
Search results and study details
The serial searches yielded 5761 citations, of which 2575 were duplicates and were removed. After title and abstract screening, 69 articles underwent full-text review (1 of which)40 was found in a systematic review.41 Of these 69 articles, a total of 30 met all inclusion criteria. Five articles included more than one checklist. Ten articles included previously published checklists, but in each article, the checklists were evaluated using different study designs. These studies were therefore retained. After excluding duplicate checklists, a total of 25 unique checklists described within 30 articles were examined (figure 1). Within the 30 included articles, 18 formally evaluated and reported outcomes related to checklist use whereas 12 articles featured checklists that were not formally evaluated. Inter-rater agreement for study eligibility for full text review was high (kappa=0.97).
Study flow diagram.
Included checklists covered each of the three major framework components of the SEIPS 2.0 model: Work System (n=15 checklists), Processes (n=20) and Outcomes (n=2). Many checklists targeted one (n=13) or two (n=10) framework components; only two checklists targeted all three SEIPS 2.0 components (table 1). Checklists are listed with examples of how their components fit into SEIPS categories in online supplemental Table S2.
Categorisation of checklists components based on SEIPS 2.0*
Checklists targeting work systems
Fifteen out of the 25 checklists addressed Work Systems.20 22 42–53 Two of those checklists addressed the Persons subcomponent,45 46 13 addressed Tasks,20 22 42 43 45 47–53 and 3 addressed Internal Environment (table 1).44–46 Notably, no checklists focused on Tools and Technologies, or External Environment. Only one checklist examined factors within Organisation.45 Checklists elements incorporating the Persons subcomponent typically addressed clinicians or patients’ demeanour or attitude during a clinical encounter. For example, Ely’s checklist for mental pause addressed factors such as physician being ‘angry’ or patient being ‘hostile’.45 whereas Graber’s checklist prompted the clinician to consider, ‘is this a patient I don’t like?’.46 Tasks were highlighted in Ely’s general debiasing checklist by prompting clinicians to ‘obtain…medical history’ and ‘perform a…physical exam’.20 Other examples where Tasks are emphasised include Bahrami’s radiology checklist (eg, asking providers to systematically assess different brains areas such as sulci and ventricles),42 Nedorost’s dermatitis checklist (eg, examine for signs of dermatomyositis),48 and Sibbald’s ECG checklist (eg, calculate the rate, check the intervals PR, QRS, QT).51 In contrast, Internal Environment was prominent in Chew’s TWED (Threat, Wrong/What else, Evidence, Dispositional factors) mnemonic (Dispositional factors, such as chaotic, busy work place).44 Finally, the Organisation subcomponent was emphasised in Ely’s general checklist, which asked the clinician about ‘external pressures’ (eg, time pressure), highlighting the impact of workload on clinical decision making.45
Checklists targeting processes framework
Most checklists (n=20) focused on the Cognitive subcomponent of Processes. No checklists addressed the Physical subcomponent and only two checklists addressed the Social and Behavioural subcomponent of Processes (table 1).48 50
Within the Cognitive subcomponent, checklists targeted various cognitive functions. Ten checklists included a list of differential diagnoses.20 22 53–60 For example, Hess’s lower extremity ulcer checklist linked broad areas such as ‘inflammatory disorders’ with related diagnoses: ‘granuloma annulare, necrobiosis lipoidica and pyoderma gangrenosum.’54 Kok’s checklist focused on assisting in radiography interpretation by listing ‘commonly missed diagnoses’ with images including ‘pneumothorax,’ ‘spinal cord compression’ and ‘surgical clips’.22
Six checklists emphasised broadening the history, physical exam or tests to aid in the diagnostic process.20 22 49 53 56 58 For example, Nordick’s Diagnostic and Reasoning Tool checklist contained an annotated flow chart that walks providers through ‘chief complaint,’ ‘history of present illness’ and ‘physical exam’ while providing broad diagnostic questions to consider while performing these steps.49 Similarly, Weber’s checklist for orbital or periorbital cellulitis outlined specific points in the history and physical (eg, ‘onset’ ‘catastrophic (hours))’ and followed by diagnoses in order of likelihood.58
Three checklists specifically pointed out commonly missed diagnoses or diagnostic pitfalls.20 22 61 For example, Ely’s disease-specific differential diagnosis checklist emphasised ‘commonly missed diagnosis’ with an asterisk.20 A disease-specific cognitive forcing checklist from the same paper emphasised common diagnostic pitfalls, such as missed peroneal tendon tear’ and ‘underappreciated ankle instability.’
Three checklists prompted clinicians to consider urgent or emergent conditions.20 44 57 For example, the TWED mnemonic from Chew 2016 includes ‘life-or-limb Threat’ as a cognitive forcing tool to rule out ‘worst-case scenario’s.44 Additionally, the condition-specific differential diagnosis checklist form Shimizu also highlighted ‘do-not-miss-diagnosis’ with a symbol.57
Checklists that addressed the Social and Behavioural subcomponents encouraged person-to-person communication to ensure adequate knowledge transfer. For example, Rush’s CARE mnemonic incorporated ‘C’ to represent ‘Communicate with your team and patient,’ while Nedorost’s checklist prompted physicians to consider ‘framing communication.’48 50
Checklists targeting outcomes
Two checklists target the Outcomes SEIPS 2.0 component,44 45 both of which addressed the Professional outcomes subcomponent (table 1). For example, Chew’s TWED mnemonic has ‘D’ for ‘Dispositional factors’ encompassing ‘emotional—sleepiness, tiredness, anger.’44 No checklists specifically address the Patient or Organisational subcomponents.
Effectiveness of checklists in reducing diagnostic error
Eighteen studies described outcomes related to the use of 14 unique clinical diagnosis checklists. Four of these studies (two pretest and post-test studies,46 47 one survey-based study48 and one study with a focus-group design)21 obtained user feedback when using a checklist. The remaining fourteen, including five pretest and post-test studies,51 52 57 62 63 six randomised controlled trials (RCTs),22 40 55 61 64 65 two quasi-experimental studies44 66 and one retrospective cohort study,56 evaluated whether checklists reduced diagnostic error. The main outcomes reported within those 14 studies included diagnostic accuracy, number of errors, number of abnormalities found on imaging and patient outcomes such as length of stay (tables 2 and 3). Any study-reported statistical significance associated with those outcomes is described in table 3.
Characteristics of studies evaluating effectiveness of checklists
Categorisation of checklists that did and did not (italics) improve diagnostic error
Four of the five pretest and post-test studies reported significant improvement in diagnostic accuracy with their checklists (tables 2 and 3).51 52 57 63 For example, Sibbald’s study using an ECG interpretation checklist reported a reduction in errors from 279 to 70 following implementation of the checklist (p=0.01).51 In another study of the ECG interpretation checklist by Sibbald, an average of 1.6 mistakes on ECG interpretation were fixed with checklist use (p=0.001).63 Sibbald’s cardiac exam checklist reported 51% accuracy with checklist use vs 46% diagnostic accuracy without (p=0.04)52; and Shimizu’s symptom-specific checklists reported 67% diagnostic accuracy with the checklist vs 60% without (p<0.05).57 One study (Kilian’s ACT mnemonic) reported no significant improvements in postchecklist diagnostic accuracy.62
Only two of the six RCTs included in our review reported significant improvement in diagnostic accuracy. For example, Kok’s radiograph interpretation checklist assisted clinicians in finding 50.1% of abnormalities on X-rays with multiple abnormalities, compared with 41.9% when the checklist was not used (p=0.04).22 Sibbald’s ECG interpretation and diagnostic pause checklist reported that 27% of ECG interpretation errors were corrected with checklist use, vs only 4% without use (p=0.01).64 Four of the six RCTs did not demonstrate significant reduction in diagnostic errors.40 55 61 65
Of the quasi-experimental studies, Chew’s TWED checklist tested diagnostic accuracy using five case scenarios and reported higher scores (18.5 vs 12.5 out of 50, p=0.001) with use of the checklist.44 However, a similar study using 10 case scenarios showed no improvement in diagnostic accuracy.66 Finally, Pan’s retrospective cohort study assessing an abdominal pain checklist demonstrated significant improvement in diagnostic accuracy with checklist use (94.8% vs 82% diagnostic accuracy, p=0.034, in one subgroup; and 95.3% vs 86%, p=0.001 in another subgroup).56
Within the 14 studies testing checklists, most checklists targeted the Cognitive subcomponent (n=10)22 40 44 55–57 61 62 65 66 followed by Tasks (n=7)22 51 52 57 63–65 (table 3). Two studies targeted the Internal Environment and the Professional Outcomes subcomponents.44 66 None of the included checklists targeted the Persons, External Environment, Tools and Technology, Organisation, Physical or Social and Behavioural subcomponents. Though the Cognitive subcomponent was the most emphasised, only four out of the 10 studies demonstrated reduction in diagnostic error,22 44 56 57 with 1 of those four studies showing mixed results (ie, 1 checklist demonstrating reduction in diagnostic error and another failing to reduce error).57 Conversely, five out of the seven studies targeting Tasks demonstrated significant reduction in diagnostic error (table 3).22 51 52 63 64 In examination of the four unique checklists included in the seven studies targeting Tasks, three checklists were found to reduce diagnostic error,22 51 52 (though one failed to reduce diagnostic error in one study,65 but was shown to reduce diagnostic error in several other studies),51 63 64 and one checklist failed to reduce diagnostic error (table 3).57
Quality assessment
Three of the six RCTs were at ‘Low Risk’ of bias,22 55 64 while the other three RCTs had ‘Some Concerns’.40 61 65 The two quasi experimental studies were found to be at ‘Low Risk’ of study bias (online supplemental Table S3).44 66
Out of the five pre–post studies, two were rated as ‘good’ quality’,52 63 two were found to be ‘fair,’51 57 and one was rated as ‘poor’ quality.62 Finally, Pan’s retrospective cohort was assessed to be ‘good quality’56 (online supplemental Table S3).
Discussion
Reducing diagnostic error is of paramount importance in medicine as it is a significant, yet preventable, source of mortality. Prior reviews on interventions intended to reduce diagnostic error describe cognitive and system-related interventions, but included small numbers of published clinical diagnosis checklists in this field.67 68 Since then, a plethora of additional studies targeting diagnostic error using checklists have been published. Despite this fact, the importance of checklists within the realm of diagnostic error remains unclear. In this study, we included 30 studies and 25 unique checklists, characterised each checklist based on SEIPS 2.0 framework, and assessed which human factors may have a role in influencing diagnostic errors. The cognitive subcomponent of SEIPS 2.0 was targeted most frequently (20 checklists), followed by tasks (13 checklists). Other SEIPS 2.0 subcomponents were either minimally or not at all represented. When examining efficacy, checklists targeting Tasks appeared to be most associated with reductions in diagnostic errors. Taken together, these findings highlight an opportunity to further examine the effect of task-based checklists on diagnostic error. In addition, other human factors subcomponents (eg, Persons, External Environment, Tools and Technology, Organisation, Physical, or Social and Behavioural) remain unaddressed in available checklists, suggesting that more research in these areas is necessary.
Although promising, the notion that diagnostic checklists can help improve diagnostic safety has come under scrutiny.15 Sceptics suggest that, unlike other successful patient safety checklists that target specific tasks of execution (eg, procedure time-out checklists), diagnostic safety checklists are too broad or nonspecific when they target cognitive processes.15 19 Furthermore, diagnostic checklists may be unable to provide sufficient content assistance to help with errors of planning, and may have potential negative effects, such as added time pressure and risk of overdiagnosis.19 Lack of a clear link between diagnostic checklists and reduction in errors may also represent limitations with study design and quality. Indeed, when examining risk of study bias, half of the RCTs (n=3) included in this review were rated as having ‘Some Concerns’, due to differences in baseline characteristics or limitations in the analyses to estimate the effect of the checklist intervention. In addition, three of the five pre–post test studies were rated as either ‘fair’ or ‘poor’, due to lack of clear selection criteria of study population, the sample being insufficient, or otherwise not representative of the general population (online supplemental Table S1). Furthermore, most checklists were tested in a non-clinical ‘experimental’ setting, limiting applicability to the clinical realm.
Our systematic review is an important step forward in understanding the current state of checklists and advances the science in several ways. First, the finding that task-based checklists perform better suggests promise for this approach in domains where critical sequential steps (eg, interpreting ECGs and radiographic images) are needed. Larger scale implementation of these tools using rigorous study designs is therefore important. Second, the fact that only a few studies that used cognitive checklists led to improved diagnosis argues that attempts to inform complex, multifaceted decisions via a rigid checklist may not be possible. Third, we found that multiple aspects relevant to diagnosis including Tools, Technology, and External Environment Work Systems, Physical Processes, and Patient and Organisational Outcomes were not targeted by current checklists. Future iterations of checklists in diagnostic errors may explore these areas to enhance effectiveness. For example, should efforts to curb diagnostic error at the clinician level be coupled with interventions targeting hospital leadership or the environment in which clinicians work? If so, how might checklists be helpful in those domains?
Our review has limitations. First, while the human factors framework (SEIPS 2.0) is broad and inclusive in its categorisation, elements not included in this structure may also be important in evaluating diagnostic checklists. Furthermore, components of SEIPS 2.0 have not been tested or validated in the setting of clinical diagnosis; therefore, our findings should be viewed as preliminary and hypothesis generating for future evaluations. Second, while all authors were involved in categorising the checklists’ content according to SEIPS 2.0 as objectively as possible, the categorisation process was inherently subjective. Different reviewers may come up with different categorisations. Third, many of the included checklists were not formally evaluated to determine their impact on diagnosis outcomes. While inclusion of these pre-evaluative studies allows for a more comprehensive review, studies implementing these checklists are needed and may influence our findings.
The findings of our review should spur investigators interested in addressing diagnostic error to focus checklist-based research in specific ways. Specifically, greater focus on task-based checklists appears warranted. Such approach may prioritise focusing on stepwise strategies in evaluating clinical data over the differential diagnosis of such data, such as stepwise approach to reading ECGs or chest X-rays, or evaluating a rash. Additionally, broadening checklist-based research to include unaddressed SEIPS 2.0 areas, such as the Environment, and Tools and Technologies appears necessary. These types of studies may help advance the discovery of novel opportunities, reduce error, and improve effectiveness of diagnosis.
Conclusion
Checklists could hold great potential to reduce clinical diagnostic error; therefore, a comprehensive understanding of their landscape is crucial for further development. Organisation of checklists by the SEIPS 2.0 is highly illustrative of the current state-highlighting areas of strength of current checklists as well as blind spots that remain poorly addressed. Generally, current published checklists emphasise very few SEIPS 2.0 elements, mainly the Task and Cognitive subcomponents, while leaving others entirely unused. Tasks-focused checklists seem to be more associated with a significant reduction in diagnostic error. Understanding the impact of incorporating less explored SEIPS 2.0 subcomponents within checklists for diagnostic error warrants evaluation. Further, studies examining the ability of task-oriented checklists to reduce diagnostic error may ultimately facilitate improved diagnosis.
Data availability statement
No data are available.
Ethics statements
Patient consent for publication
References
Supplementary materials
Supplementary Data
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Footnotes
Twitter @JawadKhafaji
Correction notice This article has been corrected since it first published. Author name 'Ryan F Townshend' has been updated.
Contributors JA-K: contributed to study design, literature review, data gathering, data analysis and manuscript writing; and he is the guarantor of this study. RFT: contributed to study design, literature review, data gathering, data analysis and manuscript writing. WT: performed literature search. VC: provided guidance and advice on study design, literature review, data gathering, data analysis, and contributed to manuscript writing. AG: provided guidance and advice on study design, literature review, data gathering, data analysis, and contributed to manuscript writing.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.