Heuristic decision making in medicine

The Effects of Safe Zone Badges in Physicians' Online Biographies: Evidence from an Experimental Study

Earning digital badges to showcase a person's expertise or knowledge are becoming increasingly popular. A healthcare provider's displaying of a Safe Zone badge within their online profile may offer prospective patients a cue as to the kind of care they might receive if they selected that particular provider. Prior research indicates LGBTQ+ individuals are looking for these types of cues within providers' biographies to make their selections. A between subjects, 2 (Safe Zone badge present/absent) x 2 (male/female doctor) online experiment was conducted (n = 658). Results revealed a main effect for the presence of the Safe Zone badge. Participants had greater anticipated satisfaction, liking, were more likely to view the provider as approachable, and were more willing to schedule an appointment with the provider displaying a Safe Zone badge.

Judgement and Decision Making in Clinical and Return-to-Sports Decision Making: A Narrative Review

Making return-to-sport decisions can be complex and multi-faceted, as it requires an evaluation of an individual's physical, psychological, and social well-being. Specifically, the timing of progression, regression, or return to sport can be difficult to determine due to the multitude of information that needs to be considered by clinicians. With the advent of new sports technology, the increasing volume of data poses a challenge to clinicians in effectively processing and utilising it to enhance the quality of their decisions. To gain a deeper understanding of the mechanisms underlying human decision making and associated biases, this narrative review provides a brief overview of different decision-making models that are relevant to sports rehabilitation settings. Accordingly, decisions can be made intuitively, analytically, and/or with heuristics. This narrative review demonstrates how the decision-making models can be applied in the context of return-to-sport decisions and shed light on strategies that may help clinicians improve decision quality.

Clinical reasoning in real-world practice: a primer for medical trainees and practitioners

Clinical reasoning is a crucial skill and defining characteristic of the medical profession, which relates to intricate cognitive and decision-making processes that are needed to solve real-world clinical problems. However, much of our current competency-based medical education systems have focused on imparting swathes of content knowledge and skills to our medical trainees, without an adequate emphasis on strengthening the cognitive schema and psychological processes that govern actual decision-making in clinical environments. Nonetheless, flawed clinical reasoning has serious repercussions on patient care, as it is associated with diagnostic errors, inappropriate investigations, and incongruent or suboptimal management plans that can result in significant morbidity and even mortality. In this article, we discuss the psychological constructs of clinical reasoning in the form of cognitive 'thought processing' models and real-world contextual or emotional influences on clinical decision-making. In addition, we propose practical strategies, including pedagogical development of a personal cognitive schema, mitigating strategies to combat cognitive bias and flawed reasoning, and emotional regulation and self-care techniques, which can be adopted in medical training to optimize physicians' clinical reasoning in real-world practice that effectively translates learnt knowledge and skill sets into good decisions and outcomes.

Ten misconceptions regarding decision-making in critical care

Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system. Patient complexity, illness severity, and the urgency in initiating proper treatment all contribute to decision-making errors. Clinician-related factors such as fatigue, cognitive overload, and inexperience further interfere with effective decision-making. Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error. This evidence-based review discusses ten common misconceptions regarding critical care decision-making. By understanding how practitioners make clinical decisions and examining how errors occur, strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.

Prognostication in Neurocritical Care

OBJECTIVE

This article synthesizes the current literature on prognostication in neurocritical care, identifies existing challenges, and proposes future research directions to reduce variability and enhance scientific and patient-centered approaches to neuroprognostication.

LATEST DEVELOPMENTS

Patients with severe acute brain injury often lack the capacity to make their own medical decisions, leaving surrogate decision makers responsible for life-or-death choices. These decisions heavily rely on clinicians' prognostication, which is still considered an art because of the previous lack of specific guidelines. Consequently, there is significant variability in neuroprognostication practices. This article examines various aspects of neuroprognostication. It explores the cognitive approach to prognostication, highlights the use of statistical modeling such as Bayesian models and machine learning, emphasizes the importance of clinician-family communication during prognostic disclosures, and proposes shared decision making for more patient-centered care.

ESSENTIAL POINTS

This article identifies ongoing challenges in the field and emphasizes the need for future research to ameliorate variability in neuroprognostication. By focusing on scientific methodologies and patient-centered approaches, this research aims to provide guidance and tools that may enhance neuroprognostication in neurocritical care.

Evaluating Aboriginal and Torres Strait Islander Social and Emotional Wellbeing services: A collective case study in Far North Queensland

BACKGROUND

Access to a coordinated range of strengths-based, culturally appropriate community-led primary mental health and Social and Emotional Wellbeing services is critical to the mental health and wellbeing of young Aboriginal and Torres Strait Islander people, and is a policy commitment of the Australian government. However, complex and fragmented service networks and a lack of standardised service data are barriers in identifying what services are available and what care they provide.

METHOD

A standardised service classification tool was used to assess the availability and characteristics of Social and Emotional Wellbeing services for young Aboriginal and Torres Strait Islander people in two regions in Queensland, Australia.

RESULTS

We identified a complex pattern of service availability and gaps in service provision. Non-Indigenous non-governmental organisations provided a significant proportion of services, particularly 'upstream' support, while Aboriginal Community Controlled Organisations were more likely to provide 'downstream' crisis type care. Most services provided by the public sector were through Child Safety and Youth Justice departments.

CONCLUSIONS

Our findings demonstrate the complexity of current networks, and show that non-Indigenous organisations are disproportionately influential in the care received by young Aboriginal and Torres Strait Islander people, despite community goals of self-determination, and government commitment to increasing capacity of Aboriginal Community Controlled Organisations to support their local communities. These findings can be used to support decision making and planning.

The impact of cognitive resource constraints on goal prioritization

Many decisions we face daily entail deliberation about how to coordinate resources shared between multiple, competing goals. When time permits, people appear to approach these goal prioritization problems by analytically considering all goal-relevant information to arrive at a prioritization decision. However, it is not yet clear if this normative strategy extends to situations characterized by resource constraints such as when deliberation time is scarce or cognitive load is high. We evaluated the questions of how limited deliberation time and cognitive load affect goal prioritization decisions across a series of experiments using a gamified experimental task, which required participants to make a series of interdependent goal prioritization decisions. We fit several candidate models to experimental data to identify decision strategy adaptations at the individual subject-level. Results indicated that participants tended to opt for a simple heuristic strategy when cognitive resources were constrained rather than making a general tradeoff between speed and accuracy (e.g., the type of tradeoff that would be predicted by evidence accumulation models). The most common heuristic strategy involved disproportionately weighing information about goal deadlines compared to other goal-relevant information such as the goal's difficulty and the goal's subjective value.

Unveiling the interplay between evidence, values and cognitive biases. The case of the failure of the AstraZeneca COVID-19 vaccine

This paper depicts a Covid science case, that of the AstraZeneca Vaxzevria vaccine, with specific focus on what happened in Italy. Given that we believe acknowledging the role of non-evidential factors in medicine is an important insight into the recent philosophy of science, we illustrate how in the case of Vaxzevria, the interplay between facts, values (both epistemic and non-epistemic) and cognitive biases may have possibly led to different institutional decisions based on the same evidence. The structure of the paper is as follows. First, we provide a glossary of the relevant terms involved, that is to say, epistemic values, non-epistemic values and cognitive biases. Second, we sketch a timeline of Vaxzevria's approvals and suspensions by relevant institutional healthcare authorities with special focus on Italy and the Italian Medicines Agency. Then we show the interplay between the evidence base, epistemic as well as non-epistemic values and cognitive biases using a narrative review of political decisions along with newspaper and social media content pertaining to Vaxzevria. We briefly compare Italy with other European countries to show that different political decisions were made on the basis of the same evidence.

Development and validation of a clinical prediction rule for acute appendicitis in children in primary care

BACKGROUND

Recognising acute appendicitis in children presenting with acute abdominal pain in primary care is challenging. General practitioners (GPs) may benefit from a clinical prediction rule.

OBJECTIVES

To develop and validate a clinical prediction rule for acute appendicitis in children presenting with acute abdominal pain in primary care.

METHODS

In a historical cohort study data was retrieved from GP electronic health records included in the Integrated Primary Care Information database. We assigned children aged 4-18 years presenting with acute abdominal pain (≤ 7 days) to development (2010-2012) and validation (2013-2016) cohorts, using acute appendicitis within six weeks as the outcome. Multiple logistic regression was used to develop a prediction model based on predictors with > 50% data availability derived from existing rules for secondary care. We performed internal and external temporal validation and derived a point score to stratify risk of appendicitis into three groups, i.e. low-risk, medium-risk and high-risk.

RESULTS

The development and validation cohorts included 2,041 and 3,650 children, of whom 95 (4.6%) and 195 (5.3%) had acute appendicitis. The model included male sex, pain duration (<24, 24-48, > 48 h), nausea/vomiting, elevated temperature (≥ 37.3 °C), abnormal bowel sounds, right lower quadrant tenderness, and peritoneal irritation. Internal and temporal validation showed good discrimination (C-statistics: 0.93 and 0.90, respectively) and excellent calibration. In the three groups, the risks of acute appendicitis were 0.5%, 7.5%, and 41%.

CONCLUSION

Combined with further testing in the medium-risk group, the prediction rule could improve clinical decision making and outcomes.

What is important to the GP in recognizing acute appendicitis in children: a delphi study

BACKGROUND

For diagnostic research on appendicitis in registration data, insight is needed in the way GPs generate medical records. We aimed to reach a consensus on the features that GPs consider important in the consultation and medical records when evaluating a child with suspected appendicitis.

METHODS

We performed a three-round Delphi study among Dutch GPs selected by purposive sampling. An initial feature list was created based on a literature search and features in the relevant Dutch guideline. Finally, using a vignette describing a child who needed later reassessment, we asked participants to complete an online questionnaire about which consultation features should be addressed and recorded.

RESULTS

A literature review and Dutch guideline yielded 95 consultation features. All three rounds were completed by 22 GPs, with the final consensus list containing 26 symptoms, 29 physical assessments and signs, 2 additional tests, and 8 further actions (including safety-netting, i.e., informing the patient about when to contact the GP again). Of these, participants reached consensus that 37 should be actively addressed and that 20 need to be recorded if findings are negative.

CONCLUSIONS

GPs agreed that negative findings do not need to be recorded for most features and that records should include the prognostic and safety-netting advice given. The results have implications in three main domains: for research, that negative findings are likely to be missing; for medicolegal purposes, that documentation cannot be expected to be complete; and for clinical practice, that safety-netting advice should be given and documented.

Effect of age-based left-digit bias on stroke diagnosis: Regression discontinuity design

BACKGROUND

Little is known about how left-digit bias- where humans tend to discretely categorize their decisions based on the left-most digit of the continuous variables-based on patients' age affects the initial diagnosis of stroke patients. The aim of this study is to examine whether there is a discontinuous change in the ordering of imaging tests for stroke at the age threshold of 40 years old, which is indicative of left-digit bias, and whether the effect varies by patient sex.

METHODS

We conducted a cohort study by regression discontinuity design (RDD). We analyzed the claims database from a nationwide working-age health insurance plan in Japan. Patients who had after-hours hospital visits from January 2014 through December 2019 were included in our analysis. The exposure is patients' age, and the primary outcome was physicians' ordering imaging tests (CT or MRI) to diagnose stroke during the index visit.

RESULTS

Of 293,390 total visits, 48,598 visits within data-driven optimal bandwidths of 6.0 years from the cut-off of 40 years were included for the RDD analysis (mean age 40.8 years [standard deviation 3.4], female 50.5%). The baseline probability of receiving imaging tests for stroke diagnosis was 0.9%. Physicians had a higher likelihood of ordering imaging tests when patients' age was above 40 years compared with when patients' age was just below 40 years (adjusted difference, +0.51 percentage points [pp], 95%CI, +0.13 to +1.07 pp; P = 0.01). We found a significant discontinuous change in the ordering of imaging tests for stroke at 40 years for male patients (+0.84 pp, 95%CI, +0.24 to +1.69 pp; P = 0.009) but not for female patients.

CONCLUSIONS

Physicians have a cognitive bias in estimating stroke risk and, consistent with a left-digit bias, treat male patients aged 40 and just below differently. This pattern was observed only among male patients.

Age and postoperative opioid use in women undergoing pelvic organ prolapse surgery

INTRODUCTION

Our objective was to explore the relation between patient age and postoperative opioid use up to 24 hours following pelvic organ prolapse (POP) surgery.

MATERIAL AND METHODS

We conducted a prospective cohort study following 335 women ranging in age from 26 to 82 years who underwent surgery for multi-compartment POP at a tertiary center in Alberta, Canada. Patient characteristics were measured using baseline questionnaires. Perioperative data were collected from medical chart review during and up to 24 hours following surgery. We used logistic regression to analyze the odds of being opioid-free and linear regression to analyze mean differences in opioid dose, measured as total morphine equivalent daily dose, exploring for a potential non-linear effect of age. Adjusted models controlled for preoperative pain, surgical characteristics and patient health factors.

RESULTS

Overall, age was positively associated with greater odds of being opioid-free in the first 24 hours after surgery (adjusted odds ratio per increasing year of age = 1.07, 95% confidence interval [CI] 1.04-1.09, n = 332 women). Among opioid users, age was inversely associated with total opioid dose (adjusted mean difference per increasing year of age = 0.71 mg morphine equivalent daily dose, 95% CI -0.99 to -0.44, n = 204 women). There was no evidence of a non-linear relation between age and postoperative opioid use or dose.

CONCLUSIONS

In the context of POP surgery, we found that younger women were more likely to use opioids after surgery and to use a higher dose in the first 24 hours when compared with older women. These findings support physicians to consider age when counseling POP patients regarding pain management after surgery, and to direct resources aimed at opioid-free pain control towards younger patients.

A Practical Approach to Preventing Contrast-Associated Renal Complications in the Catheterization Laboratory

Contrast media use is ubiquitous in the catheterization laboratory. Contrast-associated acute kidney injury (CA-AKI) is a key concern among patients undergoing coronary angiography and percutaneous coronary interventions. The risk of CA-AKI can be minimized by careful attention to hydration status and renal function-based contrast dosing in all patients. In patients with Stage IV chronic kidney disease, ultra low contrast procedure (contrast dose ≤ GFR) may be especially beneficial.

Past Adversity Influencing Now (PAIN): perspectives on the impact of temporal language on the persistence of pain

Persistent pain is a significant healthcare issue, often unresponsive to traditional treatments. We argue for incorporating non-biomedical perspectives in understanding pain, promoting more comprehensive solutions. This article explores how language, specifically time-related terms, may affect the persistence (stickiness) of pain. We delve into how language influences one's experience of the world, especially in understanding pain through spatial metaphors. Notably, time perceptions differ across languages and cultures and there is no absolute construct of temporal pain experience. In English, time is viewed linearly as past, present, and future. We introduce a framework called Past Adversity Influencing Now (PAIN) which includes various temporal phases of pain; Past Perfect, Past Imperfect, Present, Future Imperfect, and Future Perfect. We suggest that past negative memories (emotional memory images) can "trap" individuals in a "sticky" pain state. We speculate that the process of diagnosing pain as "chronic" may solidify this "stickiness", drawing from the ancient Greek idea of "logos", where pain communicates a message across time and space needing recognition. Our PAIN framework encourages examining pain through a temporal lens, guiding individuals towards a more positive future.

Differences in decisions affected by cognitive biases: examining human values, need for cognition, and numeracy

A better understanding of factors that can affect preferences and choices may contribute to more accurate decision-making. Several studies have investigated the effects of cognitive biases on decision-making and their relationship with cognitive abilities and thinking dispositions. While studies on behaviour, attitude, personality, and health worries have examined their relationship with human values, research on cognitive bias has not investigated its relationship to individual differences in human values. The purpose of this study was to explore individual differences in biased choices, examining the relationships of the human values self-direction, conformity, power, and universalism with the anchoring effect, the framing effect, the certainty effect, and the outcome bias, as well as the mediation of need for cognition and the moderation of numeracy in these relationships. We measured individual differences and within-participant effects with an online questionnaire completed by 409 Brazilian participants, with an age range from 18 to 80 years, 56.7% female, and 43.3% male. The cognitive biases studied consistently influenced choices and preferences. However, the biases showed distinct relationships with the individual differences investigated, indicating the involvement of diverse psychological mechanisms. For example, people who value more self-direction were less affected only by anchoring. Hence, people more susceptible to one bias were not similarly susceptible to another. This can help in research on how to weaken or strengthen cognitive biases and heuristics.

Predicting mortality risk after a fall in older adults using health care spending patterns: a population-based cohort study

OBJECTIVE

To develop a prognostic model of 1-year mortality for individuals aged 65+ presenting at the emergency department (ED) with a fall based on health care spending patterns to guide clinical decision-making.

DESIGN

Population-based cohort study (n = 35,997) included with a fall in 2013 and followed 1 year.

METHODS

Health care spending indicators (dynamical indicators of resilience, DIORs) 2 years before admission were evaluated as potential predictors, along with age, sex and other clinical and sociodemographic covariates. Multivariable logistic regression models were developed and internally validated (10-fold cross-validation). Performance was assessed via discrimination (area under the receiver operating characteristic curve, AUC), Brier scores, calibration and decision curve analysis.

RESULTS

The AUC of age and sex for mortality was 72.5% [95% confidence interval 71.8 to 73.2]. The best model included age, sex, number of medications and health care spending DIORs. It exhibited high discrimination (AUC: 81.1 [80.5 to 81.6]), good calibration and potential clinical benefit for various threshold probabilities. Overall, health care spending patterns improved predictive accuracy the most while also exhibiting superior performance and clinical benefit.

CONCLUSIONS

Patterns of health care spending have the potential to significantly improve assessments on who is at high risk of dying following admission to the ED with a fall. The proposed methodology can assist in predicting the prognosis of fallers, emphasising the added predictive value of longitudinal health-related information next to clinical and sociodemographic predictors.

Cognitive perspectives on maintaining physicians' medical expertise: II. Acquiring, maintaining, and updating cognitive skills

Over the course of training, physicians develop significant knowledge and expertise. We review dual-process theory, the dominant theory in explaining medical decision making: physicians use both heuristics from accumulated experience (System 1) and logical deduction (System 2). We then discuss how the accumulation of System 1 clinical experience can have both positive effects (e.g., quick and accurate pattern recognition) and negative ones (e.g., gaps and biases in knowledge from physicians' idiosyncratic clinical experience). These idiosyncrasies, biases, and knowledge gaps indicate a need for individuals to engage in appropriate training and study to keep these cognitive skills current lest they decline over time. Indeed, we review converging evidence that physicians further out from training tend to perform worse on tests of medical knowledge and provide poorer patient care. This may reflect a variety of factors, such as specialization of a physician's practice, but is likely to stem at least in part from cognitive factors. Acquired knowledge or skills gained may not always be readily accessible to physicians for a number of reasons, including an absence of study, cognitive changes with age, and the presence of other similar knowledge or skills that compete in what is brought to mind. Lastly, we discuss the cognitive challenges of keeping up with standards of care that continuously evolve over time.

Heuristics and biases in medical decision-making under uncertainty: The case of neuropronostication for consciousness disorders

Neuropronostication for consciousness disorders can be very complex and prone to high uncertainty. Despite notable advancements in the development of dedicated scales and physiological markers using innovative paradigms, these technical progressions are often overshadowed by factors intrinsic to the medical environment. Beyond the scarcity of objective data guiding medical decisions, factors like time pressure, fatigue, multitasking, and emotional load can drive clinicians to rely more on heuristic-based clinical reasoning. Such an approach, albeit beneficial under certain circumstances, may lead to systematic error judgments and impair medical decisions, especially in complex and uncertain environments. After a brief review of the main theoretical frameworks, this paper explores the influence of clinicians' cognitive biases on clinical reasoning and decision-making in the challenging context of neuroprognostication for consciousness disorders. The discussion further revolves around developing and implementing various strategies designed to mitigate these biases and their impact, aiming to enhance the quality of care and the patient safety.

Using care pathways for cancer diagnosis in primary care: a qualitative study to understand family physicians' mental models

BACKGROUND

Care pathways are tools that can help family physicians navigate the complexities of the cancer diagnostic process. Our objective was to examine the mental models associated with using care pathways for cancer diagnosis of a group of family physicians in Alberta.

METHODS

We conducted a qualitative study using cognitive task analysis, with interviews in the primary care setting between February and March 2021. Family physicians whose practices were not heavily oriented toward patients with cancer and who did not work closely with specialized cancer clinics were recruited with the support of the Alberta Medical Association and leveraging our familiarity with Alberta's Primary Care Networks. We conducted simulation exercise interviews with 3 pathway examples over Zoom, and we analyzed data using both macrocognition theory and thematic analysis.

RESULTS

Eight family physicians participated. Macrocognitive functions (and subthemes) related to mental models were sense-making and learning (confirmation and validation, guidance and support, and sense-giving to patients), care coordination and diagnostic decision-making (shared understanding). Themes related to the use of the pathways were limited use in diagnosis decisions, use in guiding and supporting referral, only relevant and easy-to-process information, and easily accessible.

INTERPRETATION

Our findings suggest the importance of designing pathways intentionally for streamlined integration into family physicians' practices, highlighting the need for co-design approaches. Pathways were identified as a tool that, used in combination with other tools, may help gather information and support cancer diagnosis decisions, with the goals of improving patient outcomes and care experience.

Difficult diagnosis in the ICU: making the right call but beware uncertainty and bias

Dealing with an uncertain or missed diagnosis is commonplace in the intensive care unit setting. Affected patients are subject to a potential decrease in quality of care and a greater risk of a poor outcome. The diagnostic process is a complex task that starts with information gathering, followed by integration and interpretation of data, hypothesis generation and, finally, confirmation of a (hopefully correct) diagnosis. This may be particularly challenging in the patient who is critically ill where a good history may not be forthcoming and/or clinical, laboratory and imaging features are non-specific. The aim of this narrative review is to analyse and describe common causes of diagnostic error in the intensive care unit, highlighting the multiple types of cognitive bias, and to suggest a diagnostic framework. To inform this review, we performed a literature search to identify relevant articles, particularly those pertinent to unclear diagnoses in patients who are critically ill. Clinicians should be cognisant as to how they formulate diagnoses and utilise debiasing strategies. Multidisciplinary teamwork and more time spent with the patient, supported by effective and efficient use of electronic healthcare records and decision support resources, is likely to improve the quality of the diagnostic process, patient care and outcomes.

A Clinical Decision Tree to Support Keratoconus Patients Considering Corneal Cross-Linking Combined with Refractive Treatment

BACKGROUND

To develop a fast and frugal decision tree to identify keratoconus patients most likely to benefit visually from the combination of corneal cross-linking (CXL) with topography-guided photorefractive keratectomy ("CXL plus").

PATIENTS AND METHODS

The outcome of interest was an improvement in uncorrected distance visual acuity (UDVA) by at least two lines at the 12-month follow-up. Preoperative and 12-month follow-up data from patients who received CXL plus (n = 96) and CXL only (n = 96) were used in a recursive partitioning approach to construct a frugal tree with three variables (corneal thickness [>/< 430 um], patient interest in CXL plus [yes/no], and tomographic cylinder [</> 3 D]). In addition, we estimated the probability of the outcome from a multivariate logistic regression model for each combination of variables used in the decision tree.

RESULTS

In the complete sample, 101/192 (52.6%) patients improved by at least two lines at the 12-month follow-up. Patients affirmative in all three answers had a 75.6% (34/45) probability of gaining at least two lines of improvement in UDVA by CXL plus. The statistical model estimated a 66.0% probability for a successful outcome.

CONCLUSION

A fast and frugal tree consisting of three variables can be used to select a patient group with a high likelihood to benefit from CXL plus. The tree is useful in the preoperative counseling of keratoconus patients contemplating the CXL plus option, an intervention that is not fully covered by many health insurances.

Addressing Cognitive Biases in Interpreting an Elevated Lactate in a Patient with Type 1 Diabetes and Thiamine Deficiency

We present the case of a young woman admitted for diabetic ketoacidosis with persistent, asymptomatic lactic acid (LA) elevation during the evolving COVID-19 pandemic. Cognitive biases in interpreting an elevated LA in this patient's care resulted in an extensive infectious workup instead of the low-cost and potentially diagnostic provision of empiric thiamine. We discuss clinical patterns and etiologies of LA elevation and the role of thiamine deficiency. We also address cognitive biases potentially affecting the interpretation of elevated lactate levels and provide guidance for clinicians to determine appropriate patients for empiric thiamine administration.

Diagnostic delays among COVID-19 patients with a second concurrent diagnosis

BACKGROUND

Little is known about the effect of a new pandemic on diagnostic errors.

OBJECTIVE

We aimed to identify delayed second diagnoses among patients presenting to the emergency department (ED) with COVID-19.

DESIGNS

An observational cohort Study.

SETTINGS AND PARTICIPANTS

Consecutive hospitalized adult patients presenting to the ED of a tertiary referral center with COVID-19 during the Delta and Omicron variant surges. Included patients had evidence of a second diagnosis during their ED stay.

MAIN OUTCOME AND MEASURES

The primary outcome was delayed diagnosis (without documentation or treatment in the ED). Contributing factors were assessed using two logistic regression models.

RESULTS

Among 1249 hospitalized COVID-19 patients, 216 (17%) had evidence of a second diagnosis in the ED. The second diagnosis of 73 patients (34%) was delayed, with a mean (SD) delay of 1.5 (0.8) days. Medical treatment was deferred in 63 patients (86%) and interventional therapy in 26 (36%). The probability of an ED diagnosis was the lowest for Infection-related diagnoses (56%) and highest for surgical-related diagnoses (89%). Evidence for the second diagnosis by physical examination (adjusted odds ratios [AOR] 2.35, 95% confidence interval [CI] 1.20-4.68) or by imaging (AOR 2.10, 95% CI 1.16-3.79) were predictors for ED diagnosis. Low oxygen saturation (AOR 0.38, 95% CI 0.18-0.79) and cough or dyspnea (AOR 0.48, 95% CI 0.25-0.94) in the ED were predictors of a delayed second diagnosis.

Optimizing Equity: Working towards Fair Machine Learning Algorithms in Laboratory Medicine

BACKGROUND

Methods of machine learning provide opportunities to use real-world data to solve complex problems. Applications of these methods in laboratory medicine promise to increase diagnostic accuracy and streamline laboratory operations leading to improvement in the quality and efficiency of healthcare delivery. However, machine learning models are vulnerable to learning from undesirable patterns in the data that reflect societal biases. As a result, irresponsible application of machine learning may lead to the perpetuation, or even amplification, of existing disparities in healthcare outcomes.

CONTENT

In this work, we review what it means for a model to be unfair, discuss the various ways that machine learning models become unfair, and present engineering principles emerging from the field of algorithmic fairness. These materials are presented with a focus on the development of machine learning models in laboratory medicine.

SUMMARY

We hope that this work will serve to increase awareness, and stimulate further discussion, of this important issue among laboratorians as the field moves forward with the incorporation of machine learning models into laboratory practice.

Exploring Bias in Restraint Use: Four Strategies to Mitigate Bias in Care of the Agitated Patient in the Emergency Department

Agitation is a routine and increasingly common presentation to the emergency department (ED). In the wake of a national examination into racism and police use of force, this article aims to extend that reflection into emergency medicine in the management of patients presenting with acute agitation. Through an overview of ethicolegal considerations in restraint use and current literature on implicit bias in medicine, this article provides a discussion on how bias may impact care of the agitated patient. Concrete strategies are offered at an individual, institutional, and health system level to help mitigate bias and improve care. Reprinted from Acad Emerg Med 2021; 28:1061-1066, with permission from John Wiley & Sons. Copyright © 2021.

Factors affecting women's decision between uterine-preserving versus hysterectomy-based surgery for pelvic organ prolapse

BACKGROUND

Given the prevalence of women seeking surgical treatment for pelvic organ prolapse (POP), there is a need to understand women's decision-making regarding uterine-preserving versus hysterectomy-based surgeries. Historically, hysterectomy-based surgeries have been the preferred treatment for pelvic organ prolapse; however, contemporary evidence supports uterine-preserving surgeries as equivalent. At present, the lack of information available to the general public and limited options presented at surgical consultation for pelvic organ prolapse may hinder women's autonomy as they navigate surgical treatment.

OBJECTIVES

To examine the factors affecting women's decision-making processes regarding uterine-preserving or hysterectomy-based surgery for pelvic organ prolapse.

DESIGN

This is a qualitative study.

METHODS

We conducted semi-structured, qualitative interviews with women seeking surgery for pelvic organ prolapse to explore the factors affecting women's decision-making between hysterectomy-based and uterine-preserving surgeries.

RESULTS

Women (n = 26) used clinical and personal factors to determine which surgery was best. Women noted that the lack of evidence (clinical and/or anecdotal) available to them hindered their decision-making, causing them to rely more on their own interpretations of the evidence, what they perceived to be "normal," and what their surgeon recommended. Even with standardized discussion regarding the existing clinical equipoise between surgeries at the clinical consultation, some women still had misperceptions that hysterectomy-based surgery would convey the lowest risk of prolapse recurrence and be best for severe prolapse.

CONCLUSION

There is a need for more transparency in discussions about prolapse and the factors affecting women's decision-making for surgical repair of pelvic organ prolapse. Clinicians should be prepared to offer the option of hysterectomy-based or uterine-preserving surgeries and to clearly explain the clinical equipoise between these procedures.

Patterns of service provision in child and adolescent mental health care in Australia

Standard description of local care provision is essential for evidence-informed planning. This study aimed to map and compare the availability and diversity of current mental health service provision for children and adolescents in Australia. We used a standardised service classification instrument, the Description and Evaluation of Services and DirectoriEs (DESDE) tool, to describe service availability in eight urban and two rural health districts in Australia. The pattern of care was compared with that available for other age groups in Australia. Outpatient care was found to be the most common type of service provision, comprising 212 (81.2%) of all services identified. Hospital care (acute and non-acute) was more available in urban than in rural areas (20 services [9.7%] vs 1 [1.8%]). The level of diversity in the types of care available for children and adolescents was lower than that for the general adult population, but slightly higher than that for older people in the same areas. Standardised comparison of the pattern of care across regions reduces ambiguity in service description and classification, enables gap analysis and can inform policy and planning.

[Interinstitutional Command Mexico: organizational decision-making in the face of COVID-19]

Background

The third wave of COVID-19 in Mexico produced a high demand for hospital care, which is why it was created a multidisciplinary group to optimize decision-making: the Interinstitutional Command for the Health Sector (COISS, according to its initials in Spanish). So far, there is no scientific evidence of the COISS processes or their effect on the behavior of epidemiological indicators and the hospital care needs of the population in the context of COVID-19 in the entities involved.

Objectives

To analyze the trend on epidemic risk indicators throughout the COISS group's management in the third wave of COVID-19 in Mexico.

Material and methods

Mixed study: 1) non-systematic review of information from technical documents issued by COISS, 2) secondary analysis of open-access institutional databases through the description of healthcare needs of cases notified with COVID-19 symptoms, and an ecological analysis by each Mexican state on the behavior of hospital occupancy, RT-PCR positivity, and COVID-19 mortality in two-time points.

Results

The COISS activity in identifying states with epidemic risk generated actions aimed at a reduction in hospital occupancy of beds, positivity by RT-PCR, and mortality from COVID-19. Conclusions: The decisions of the COISS group reduced the indicators of epidemic risk. Continuing the work of the COISS group is an urgent need.

Conclusions

The decisions of the COISS group reduced the indicators of epidemic risk. Continuing the work of the COISS group is an urgent need.

An Ecological Account of Clinical Reasoning

PURPOSE

The prevailing paradigms of clinical reasoning conceptualize context either as noise that masks, or as external factors that influence, the internal cognitive processes involved in reasoning. The authors reimagined clinical reasoning through the lens of ecological psychology to enable new ways of understanding context-specific manifestations of clinical performance and expertise, and the bidirectional ways in which individuals and their environments interact.

METHOD

The authors performed a critical review of foundational and current literature from the field of ecological psychology to explore the concepts of clinical reasoning and context as presented in the health professions education literature.

RESULTS

Ecological psychology offers several concepts to explore the relationship between an individual and their context, including affordance, effectivity, environment, and niche. Clinical reasoning may be framed as an emergent phenomenon of the interactions between a clinician's effectivities and the affordances in the clinical environment. Practice niches are the outcomes of historical efforts to optimize practice and are both specialty-specific and geographically diverse.

CONCLUSIONS

In this framework, context specificity may be understood as fundamental to clinical reasoning. This changes the authors' understanding of expertise, expert decision making, and definition of clinical error, as they depend on both the expert's actions and the context in which they acted. Training models incorporating effectivities and affordances might allow for antiableist formulations of competence that apply learners' abilities to solving problems in context. This could offer both new means of training and improve access to training for learners of varying abilities. Rural training programs and distance education can leverage technology to provide comparable experience to remote audiences but may benefit from additional efforts to integrate learners into local practice niches.

Regional evolution of psychosocial services in Australia before and after the implementation of the National Disability Insurance Scheme

OBJECTIVES

This paper compares the evolution of the psychosocial sector in two Australian regions pre and post introduction of the National Disability Insurance Scheme - a major reform to the financing, planning and provision of disability services in Australia, intended to create greater competition and efficiency in the market, and more choice for service users.

METHODS

We used a standardised service classification instrument based on a health ecosystems approach to assess service availability and diversity of psychosocial services provided by non-government organisations in two Primary Health Network regions.

RESULTS

We identified very different evolutionary pathways in the two regions. Service availability increased in Western Sydney but decreased in the Australian Capital Territory. The diversity of services available did not increase in either Primary Health Network 4 years after the reform. Many services were experiencing ongoing funding uncertainty.

CONCLUSION

Assumptions of increased efficiency through organisational scaling up, and a greater diversity in range of service availability were not borne out.

IMPLICATIONS

This study shows the urgent need for evaluation of the effects of the NDIS on the provision of psychosocial care in Australia. Four years after the implementation of the NDIS at vast expense key objectives not been met for consumers or for the system as a whole, and an environment of uncertainty has been created for providers. It demonstrates the importance of standardised service mapping to monitor the effects of major reforms on mental health care as well as the need for a focus at the local level.

From Bayes-optimal to heuristic decision-making in a two-alternative forced choice task with an information-theoretic bounded rationality model

Bayes optimal and heuristic decision-making schemes are often considered fundamentally opposed to each other as a framework for studying human choice behavior, although recently it has been proposed that bounded rationality may provide a natural bridge between the two when varying information-processing resources. Here, we investigate a two-alternative forced choice task with varying time constraints, where subjects have to assign multi-component symbolic patterns to one of two stimulus classes. As expected, we find that subjects' response behavior becomes more imprecise with more time pressure. However, we also see that their response behavior changes qualitatively. By regressing subjects' decision weights, we find that decisions allowing for plenty of decision time rely on weighing multiple stimulus features, whereas decisions under high time pressure are made mostly based on a single feature. While the first response pattern is in line with a Bayes-optimal decision strategy, the latter could be considered as an instantiation of heuristic decision-making with cue discounting. When fitting a bounded rational decision model with multiple feature channels and varying information-processing capacity to subjects' responses, we find that the model is able to capture subjects' behavioral change. The model successfully reflects the simplicity of heuristics as well as the efficiency of optimal decision making, thus acting as a bridge between the two approaches.

The potential existence of ‘Small Individual Formulary’ in prescribing behaviour: a qualitative semi-structured interview study

Objectives

There is a widely held but previously unsubstantiated belief that prescribers tend to consider and use a limited set of medications when making prescribing decisions. This study aimed to enhance understanding of the process of prescribing decision making in a real-world context.

Methods

Using constructivist grounded theory methodology, we conducted semi-structured interviews with 11 healthcare providers in Georgia state. The providers, most of whom are physicians of different specialties, shared their perspectives about prescribing decision making and their perceptions about using a limited set of medications in daily practice.

Key findings

Three themes emerged from the qualitative analysis: (1) prescribers recognized the existence of ‘small individual formularies’ and considered it helpful in simplifying prescribing decision making; (2) healthcare providers employed an algorithm to initiate and step up drug therapy for patients; (3) formulary and patient affordability played a vital role in prescribing.

Conclusions

Physicians and other prescribers consider and use a limited set of prescription drugs based on their internal prescribing behaviour algorithm. Strategies could be developed to help stakeholders use this information to improve medication use.

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: To adopt what we call the "i-frame," rather than the "s-frame." The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contribute to public policy is by employing their skills to develop and implement value-creating system-level change.

A discrete choice model implementing gist-based categorization of alternatives, with applications to patient preferences for cancer screening and treatment

The rational microeconomic decision model is hard-coded into usual econometric specifications such as the Multinomial Logit and Probit models, inter alia. There is a very tight link between utility maximization and the apparatus of welfare theory that underlies economic policy analysis, which creates a tension around the possibility of representing other decision rules. We propose a less restrictive model of choice, built on the concept of gist-based categorization judgments that are assumed to precede (thus, condition) the maximization-driven selection process in decision making. This categorization facilitates decision making by allowing adoption of certain simpler decision rules under appropriate conditions, the drivers of which are endogenously determined. We demonstrate that the proposed model provides better fit than traditional choice models, using cancer screening and treatment choice data from two discrete choice experiments. In addition, we show that the model provides a deeper, more nuanced and insightful perspective on (healthcare) decision making.

A distinct four-value blood signature of pyrexia under combination therapy of malignant melanoma with dabrafenib and trametinib evidenced by an algorithm-defined pyrexia score

Pyrexia is a frequent adverse event of BRAF/MEK-inhibitor combination therapy in patients with metastasized malignant melanoma (MM). The study’s objective was to identify laboratory changes which might correlate with the appearance of pyrexia. Initially, data of 38 MM patients treated with dabrafenib plus trametinib, of which 14 patients developed pyrexia, were analysed retrospectively. Graphical visualization of time series of laboratory values suggested that a rise in C-reactive-protein, in parallel with a fall of leukocytes and thrombocytes, were indicative of pyrexia. Additionally, statistical analysis showed a significant correlation between lactate dehydrogenase (LDH) and pyrexia. An algorithm based on these observations was designed using a deductive and heuristic approach in order to calculate a pyrexia score (PS) for each laboratory assessment in treated patients. A second independent data set of 28 MM patients, 8 with pyrexia, was used for the validation of the algorithm. PS based on the four parameters CRP, LDH, leukocyte and thrombocyte numbers, were statistically significantly higher in pyrexia patients, differentiated between groups (F = 20.8; p = <0.0001) and showed a significant predictive value for the diagnosis of pyrexia (F = 6.24; p = 0.013). We provide first evidence that pyrexia in patients treated with BRAF/MEK-blockade can be identified by an algorithm that calculates a score.

Modeling fast-and-frugal heuristics

Heuristics are simple rules that experts and laypeople rely on to make decisions under uncertainty as opposed to situations with calculable risk. The research program on fast-and-frugal heuristics studies formal models of heuristics and is motivated by Herbert Simon's seminal work on bounded rationality and satisficing. In this article, we first introduce the major theoretical principles (e.g., ecological rationality) and research approaches (e.g., competitive testing) that have been adopted in this research program, and then illustrate these principles and approaches with two heuristics: take-the-best and fast-and-frugal trees. We describe conditions under which simple heuristics predict as accurately as or better than more complex models, despite requiring less effort. We close by pointing out several issues that need to be further studied and better understood in the research on fast-and-frugal heuristics.

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support

Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in these records to improve clinical decision-making, in comparison to manual clinician search and clinical judgment alone. However, these systems have delivered marginal practical utility and are rarely deployed into healthcare settings, leading to proposals for technical and structural improvements. In this paper, we argue that this reflects a violation of Friedman's "Fundamental Theorem of Biomedical Informatics," and that a deeper epistemological change must occur in the cNLP field, as a parallel step alongside any technical or structural improvements. We propose that researchers shift away from designing cNLP systems independent of clinical needs, in which cNLP tasks are ends in themselves-"tasks as decisions"-and toward systems that are directly guided by the needs of clinicians in realistic decision-making contexts-"tasks as needs." A case study example illustrates the potential benefits of developing cNLP systems that are designed to more directly support clinical needs.

How well do practicing radiologists interpret the results of CAD technology? A quantitative characterization

Many studies have shown that using a computer-aided detection (CAD) system does not significantly improve diagnostic accuracy in radiology, possibly because radiologists fail to interpret the CAD results properly. We tested this possibility using screening mammography as an illustrative example. We carried out two experiments, one using 28 practicing radiologists, and a second one using 25 non-professional subjects. During each trial, subjects were shown the following four pieces of information necessary for evaluating the actual probability of cancer in a given unseen mammogram: the binary decision of the CAD system as to whether the mammogram was positive for cancer, the true-positive and false-positive rates of the system, and the prevalence of breast cancer in the relevant patient population. Based only on this information, the subjects had to estimate the probability that the unseen mammogram in question was positive for cancer. Additionally, the non-professional subjects also had to decide, based on the same information, whether to recall the patients for additional testing. Both groups of subjects similarly (and significantly) overestimated the cancer probability regardless of the categorical CAD decision, suggesting that this effect is not peculiar to either group. The misestimations were not fully attributable to causes well-known in other contexts, such as base rate neglect or inverse fallacy. Non-professional subjects tended to recall the patients at high rates, even when the actual probably of cancer was at or near zero. Moreover, the recall rates closely reflected the subjects' estimations of cancer probability. Together, our results show that subjects interpret CAD system output poorly when only the probabilistic information about the underlying decision parameters is available to them. Our results also highlight the need for making the output of CAD systems more readily interpretable, and for providing training and assistance to radiologists in evaluating the output.

Identifying threshold concepts in postgraduate general practice training: a focus group, qualitative study

OBJECTIVE

To identify threshold concepts (TCs) for physicians undergoing postgraduate medical education (PGME) in general practice.

DESIGN

An explorative, qualitative study with 65 min focus group interviews and thematic analysis was used. Participants were asked to describe their most transformative learning experiences. Heuristical TCs were identified from the thematic analysis.

SETTING

Aotearoa/New Zealand (A/NZ).

PARTICIPANTS

Fifty participants, mostly comprising current trainees and educators from urban centres, and of NZ/European ethnicity.

RESULTS

Twenty TCs covering many aspects of postgraduate general practice experience were derived from themes identified in the data. Presented in medical proverbial form for ease of recollection, these included: Money makes the practice go round; Be a legal eagle; Manage time or it will manage you; Guidelines, GPs' little helpers; Right tool, right word, right place; The whole of the practice is greater than the sum of the parts; The personal enhances the professional; Beat biases by reflection; Chew the Complexity, Unpredictability, Diversity; Embrace the uncertainty; Not knowing is knowing; Seek and you shall find; Waiting and seeing, waiting and being; Look, listen, think between the lines; Treat the patient beyond the disease; No patient is an island; Words work wonders; Hearing is healing; Being you and being there; and; The relationship is worth a thousand consults. These TCs mapped onto core competencies in A/NZ's PGME in general practice curriculum.

CONCLUSIONS

Participants readily identified transformative and troublesome moments in their PGME in general practice. These findings confirmed evidence for a wide range of TCs with many newly identified in this study. All TCs were fundamentally based on the doctor-patient relationship, although often involving the context and culture of general practice. Actively incorporating and teaching these identified TCs in PGME in general practice may enable trainees to grasp these important learning thresholds earlier and more easily and aid in identity and role formation.

Recognising the deterioration of patients in acute care wards: a qualitative study

Background: Infrastructure, equipment and staff constraints are often cited as barriers to the recognition and rescue of deteriorating patients in resource-limited settings. The impact of health-system organisation, decision-making and organisational culture on recognition of deterioration is however poorly understood. This study explores how health care providers recognise deterioration of patients in acute care in Sri Lanka. Methods: In-depth interviews exploring decision making and care processes related to recognition of deterioration, were conducted with a purposive sample of 23 health care workers recruited from ten wards at a district hospital in Sri Lanka. Interviews were audio-recorded, transcribed and coded thematically, line-by-line, using a general inductive approach. Results: A legacy of initial assessment on admission and inimical organisational culture undermined recognition of deteriorating patients in hospital. Informal triaging at the time of ward admission resulted in patients presenting with red-flag diagnoses and vital sign derangement requiring resuscitation being categorised as "bad". The legacy of this categorisation was a series of decision-making biases anchored in the initial assessment, which remained with the patient throughout their stay. Management for patients categorised as "bad" was prioritised by healthcare workers coupled with a sense of fatalism regarding adverse outcomes. Health care workers were reluctant to deviate from the original plan of care despite changes in patient condition (continuation bias). Organisational culture - vertical hierarchy, siloed working and a reluctance to accept responsibility- resulted in omissions which undermined recognition of deterioration. Fear of blame was a barrier to learning from adverse events. Conclusions: The legacy of admission assessment and hospital organisational culture undermined recognition of deterioration. Opportunities for improving recognition of deterioration in this setting may include establishing formal triage and medical emergency teams to facilitate timely recognition and escalation.

Overcoming Decisional Gaps in High-Risk Prescribing by Junior Physicians Using Simulation-Based Training: Protocol for a Randomized Controlled Trial

BACKGROUND

Gaps between rational thought and actual decisions are increasingly recognized as a reason why people make suboptimal choices in states of heightened emotion, such as stress. These observations may help explain why high-risk medications continue to be prescribed to acutely ill hospitalized older adults despite widely accepted recommendations against these practices. Role playing and other efforts, such as simulation training, have demonstrated benefits to help people avoid decisional gaps but have not been tested to reduce overprescribing of high-risk medications.

OBJECTIVE

This study aims to evaluate the impact of a simulation-based training program designed to address decisional gaps on prescribing of high-risk medications compared with control.

METHODS

In this 2-arm pragmatic trial, we are randomizing at least 36 first-year medical resident physicians (ie, interns) who provide care on inpatient general medicine services at a large academic medical center to either intervention (simulation-based training) or control (online educational training). The intervention comprises a 40-minute immersive individual simulation training consisting of a reality-based patient care scenario in a simulated environment at the beginning of their inpatient service rotation. The simulation focuses on 3 types of high-risk medications, including benzodiazepines, antipsychotics, and sedative hypnotics (Z-drugs), in older adults, and is specifically designed to help the physicians identify their reactions and prescribing decisions in stressful situations that are common in the inpatient setting. The simulation scenario is followed by a semistructured debriefing with an expert facilitator. The trial's primary outcome is the number of medication doses for any of the high-risk medications prescribed by the interns to patients aged 65 years or older who were not taking one of the medications upon admission. Secondary outcomes include prescribing by all providers on the care team, being discharged on 1 of the medications, and prescribing of related medications (eg, melatonin, trazodone), or the medications of interest for the control intervention. These outcomes will be measured using electronic health record data.

RESULTS

Recruitment of interns began on March 29, 2021. Recruitment for the trial ended in Q42021, with follow-up completed by Q12022.

CONCLUSIONS

This trial will evaluate the impact of a simulation-based training program designed using behavioral science principles on prescribing of high-risk medications by junior physicians. If the intervention is shown to be effective, this approach could potentially be reproducible by others and for a broader set of behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04668248; https://clinicaltrials.gov/ct2/show/NCT04668248.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/31464.

Key observations in terms of management of electronic health records from a mHealth perspective

The article is a narrative review that briefly describes some of the recent advances in healthcare data management that will have positive effect on mHealth. The advances described in this article are in fact innovation introduced by the author to the field of data management with respect to electronic health records. The research delineated is transdisciplinary in nature and will potentially have positive impact on healthcare outcomes. Also, the article illustrates the necessity for an out of the box thinking approach to improve mHealth while discussing the current impending issues related to data incompleteness of electronic health records and the much-needed decision support systems for mHealth. It is to be noted that most of the electronic health records are now accessed by patients through mobile devices. These mobile devices will run as clients while much of the heavy computing is performed using servers. Here it is important to discuss some of the important technologies and methods used for decision making. The article attempts to present a discussion on how this myriad of intertwining technologies support this decision making with respect to electronic health records. More importantly it is these processes that assist in decision making and efficiency for both mHealth users and providers. In this respect, the article first provides insights on the complexities of decision making involved with electronic health records. This is followed by a discussion on the problem of data incompleteness of electronic health records. Finally, the author provides some insights into the gravity of the problem of data incompleteness in terms of revenue loss/gain for healthcare providers.

Recognising the deterioration of patients in acute care wards: a qualitative study

Background: Infrastructure, equipment and staff constraints are often cited as barriers to the recognition and rescue of deteriorating patients in resource-limited settings. The impact of health-system organisation, decision-making and organisational culture on recognition of deterioration is however poorly understood. This study explores how health care providers recognise deterioration of patients in acute care in Sri Lanka. Methods: In-depth interviews exploring decision making and care processes related to recognition of deterioration, were conducted with a purposive sample of 23 health care workers recruited from ten wards at a district hospital in Sri Lanka. Interviews were audio-recorded, transcribed and coded thematically, line-by-line, using a general inductive approach. Results: A legacy of initial assessment on admission and inimical organisational culture undermined recognition of deteriorating patients in hospital. Informal triaging at the time of ward admission resulted in patients presenting with red-flag diagnoses and vital sign derangement requiring resuscitation being categorised as "bad". The legacy of this categorisation was a series of decision-making biases anchored in the initial assessment, which remained with the patient throughout their stay. Management for patients categorised as “bad” was prioritised by healthcare workers coupled with a sense of fatalism regarding adverse outcomes. Health care workers were reluctant to deviate from the original plan of care despite changes in patient condition (continuation bias). Organisational culture - vertical hierarchy, siloed working and a reluctance to accept responsibility- resulted in omissions which undermined recognition of deterioration. Fear of blame was a barrier to learning from adverse events. Conclusions: The legacy of admission assessment and hospital organisational culture undermined recognition of deterioration. Opportunities for improving recognition of deterioration in this setting may include establishing formal triage and medical emergency teams to facilitate timely recognition and escalation.

Opportunities to use electronic health record audit logs to improve cancer care

The rapid adoption of electronic health records (EHRs) has created extensive repositories of digitized data that can be used to inform improvements in care delivery, processes, and patient outcomes. While the clinical data captured in EHRs are widely used for such efforts, EHRs also capture audit log data that reflect how users interact with the EHR to deliver care. Automatically collected audit log data provide a unique opportunity for new insights into EHR user behavior and decision‐making processes. Here, we provide an overview of audit log data and examples that could be used to improve oncology care and outcomes in four domains: diagnostic reasoning and consumption, care team collaboration and communication, patient outcomes and experience, and provider burnout/fatigue. This data source could identify gaps in performance and care, physician uptake of EHR features that enhance decision‐making, and integration of data trends for oncology. Ensuring researchers and oncologists are familiar with the data's potential and developing the data engineering capacity to utilize this rich data source, will expand the breadth of research to improve cancer care.

More Thumbs Than Rules: Is Rationality an Exaptation?

The literatures on bounded and ecological rationality are built on adaptationism-and its associated modular, cognitivist and computational paradigm-that does not address or explain the evolutionary origins of rationality. We argue that the adaptive mechanisms of evolution are not sufficient for explaining human rationality, and we posit that human rationality presents exaptive origins, where exaptations are traits evolved for other functions or no function at all, and later co-opted for new uses. We propose an embodied reconceptualization of rationality-embodied rationality-based on the reuse of the perception-action system, where many neural processes involved in the control of the sensory-motor system, salient in ancestral environments have been later co-opted to create-by tinkering-high-level reasoning processes, employed in civilized niches.

Frequency of medical students' language expressing implicit uncertainty in simulated handovers

OBJECTIVES

The aim of this study was to investigate the number and type of implicit expressions of uncertainty by medical students during simulated patient handovers.

METHODS

Eighty-seven volunteer medical students, a convenience sample collected on a first-come, first-served basis, participated in simulated handovers. They each worked with three simulated patients who presented with different chief complaints and personal conditions. The handovers were video recorded and transcribed. A framework of implicit expressions of uncertainty was used to identify and count modifiers that attenuate or strengthen medical information using MAXQDA lexical search. We analysed the findings with respect to the patients' contexts.

RESULTS

Implicit uncertainty expressions which attenuate or strengthen information occurred in almost equal frequency, 1879 (55%) versus 1505 (45%). Attenuators were found most frequently in the category 'Questionable', 1041 (55.4%), strengtheners in the category 'Focused', 1031 (68.5%). Most attenuators and strengtheners were found in the handover of two patients with challenging personal conditions ('angry man', 434 (23.1%) versus 323 (21.5%); 'unfocused woman', 354 (19.4%) versus 322 (21.4%)) and one patient with abnormal laboratory findings ('elevated creatinine', 379 (20.2%) versus 285 (18.9%)).

CONCLUSIONS

Medical students use a variety of implicit expressions of uncertainty in simulated handovers. These findings provide an opportunity for medical educators to design communication courses that raise students' awareness for content-dependent implicit expressions of uncertainty and provide strategies to communicate uncertainty explicitly.

Use of heuristics during the clinical decision process from family care physicians in real conditions

RATIONALE AIMS AND OBJECTIVES

The available evidence on the use of heuristics and their relationship with diagnostic error in primary care is very limited. The aim of the study is to identify the use of unknown thought and specifically the possible use of Representativeness, Availability and overconfidence heuristics in the clinical practice of primary care physicians in cases of dyspnoea and to analyse their possible relationship with diagnostic error.

METHODS

A total of 371 patients consulting with new episodes of dyspnoea in Primary Care centres in Spain were registered. Based on specific operational definitions, the use of unconscious thinking and the use of heuristics during the diagnostic process were assessed. Subsequently, the association between their use and diagnostic error was analysed.

RESULTS

In 49.6% of cases, the confirmatory diagnosis coincided with the first diagnostic impression, suggesting the use of the representativeness heuristic in the diagnostic decision process. In 82.3% of the cases, the confirmatory diagnosis was among the three diagnostic hypotheses that were first identified by the general physicians, suggesting a possible use of the availability heuristic. In more than 50% of the cases, the physicians were overconfident in the certainty of their own diagnosis. Finally, a diagnostic error was identified in 9.9% of the recorded cases and no statistically significant correlation was found between the use of some unconscious thinking tools (such as the use of heuristics) and the diagnostic error.

CONCLUSION

Unconscious thinking manifested through the acceptance of the first diagnostic impression and the use of heuristics is commonly used by primary care physicians in the clinical decision process in the face of new episodes of dyspnoea; however, its influence on diagnostic error is not significant. The proposed explicit and reproducible methodology may inspire further studies to confirm these results.

Biasing Influence of 'Mental Shortcuts' on Diagnostic Decision-Making: Radiologists Can Overlook Breast Cancer in Mammograms When Prior Diagnostic Information Is Available

When making decisions under uncertainty, people in all walks of life, including highly trained medical professionals, tend to resort to using 'mental shortcuts', or heuristics. Anchoring-and-adjustment (AAA) is a well-known heuristic in which subjects reach a judgment by starting from an initial internal judgment ('anchored position') based on available external information ('anchoring information') and adjusting it until they are satisfied. We studied the effects of the AAA heuristic during diagnostic decision-making in mammography. We provided practicing radiologists (N = 27 across two studies) a random number that we told them was the estimate of a previous radiologist of the probability that a mammogram they were about to see was positive for breast cancer. We then showed them the actual mammogram. We found that the radiologists' own estimates of cancer in the mammogram reflected the random information they were provided and ignored the actual evidence in the mammogram. However, when the heuristic information was not provided, the same radiologists detected breast cancer in the same set of mammograms highly accurately, indicating that the effect was solely attributable to the availability of heuristic information. Thus, the effects of the AAA heuristic can sometimes be so strong as to override the actual clinical evidence in diagnostic tasks.

Improving Diagnostic Efficiency with Frequency Double-Trees and Frequency Nets in Bayesian Reasoning

Background. Medical students often have problems with Bayesian reasoning situations. Representing statistical information as natural frequencies (instead of probabilities) and visualizing them (e.g., with double-trees or net diagrams) leads to higher accuracy in solving these tasks. However, double-trees and net diagrams (which already contain the correct solution of the task, so that the solution could be read of the diagrams) have not yet been studied in medical education. This study examined the influence of information format (probabilities v. frequencies) and visualization (double-tree v. net diagram) on the accuracy and speed of Bayesian judgments. Methods. A total of 142 medical students at different university medical schools (Munich, Kiel, Goettingen, Erlangen, Nuremberg, Berlin, Regensburg) in Germany predicted posterior probabilities in 4 different medical Bayesian reasoning tasks, resulting in a 3-factorial 2 × 2 × 4 design. The diagnostic efficiency for the different versions was represented as the median time divided by the percentage of correct inferences. Results. Frequency visualizations led to a significantly higher accuracy and faster judgments than did probability visualizations. Participants solved 80% of the tasks correctly in the frequency double-tree and the frequency net diagram. Visualizations with probabilities also led to relatively high performance rates: 73% in the probability double-tree and 70% in the probability net diagram. The median time for a correct inference was fastest with the frequency double tree (2:08 min) followed by the frequency net diagram and the probability double-tree (both 2:26 min) and probability net diagram (2:33 min). The type of visualization did not result in a significant difference. Discussion. Frequency double-trees and frequency net diagrams help answer Bayesian tasks more accurately and also more quickly than the respective probability visualizations. Surprisingly, the effect of information format (probabilities v. frequencies) on performance was higher in previous studies: medical students seem also quite capable of identifying the correct solution to the Bayesian task, among other probabilities in the probability visualizations.