Nanomedicine concepts in the general medical curriculum: initiating a discussion

Various applications of nanoscale science to the field of medicine have resulted in the ongoing development of the subfield of nanomedicine. Within the past several years, there has been a concurrent proliferation of academic journals, textbooks, and other professional literature addressing fundamental basic science research and seminal clinical developments in nanomedicine. Additionally, there is now broad consensus among medical researchers and practitioners that along with personalized medicine and regenerative medicine, nanomedicine is likely to revolutionize our definitions of what constitutes human disease and its treatment. In light of these developments, incorporation of key nanomedicine concepts into the general medical curriculum ought to be considered. Here, I offer for consideration five key nanomedicine concepts, along with suggestions regarding the manner in which they might be incorporated effectively into the general medical curriculum. Related curricular issues and implications for medical education also are presented.

Evidence of the preferential use of disease prototypes over case exemplars among early year one medical students prior to and following diagnostic training

Two core dual processing theory (DPT) System I constructs (Exemplars and Prototypes) were used to: 1) formulate a training exercise designed to improve diagnostic performance in year one medical students, and 2) explore whether any observed performance improvements were associated with preferential use of exemplars or prototypes.

With IRB approval, 117 year one medical students participated in an acute chest pain diagnostic training exercise. A pre- and post-training test containing the same 27 case vignettes was used to determine if the subjects’ diagnostic performance improved via training in both exemplars and prototypes. Exemplar and Prototype theory was also used to generate a unique typicality estimate for each case vignette. Because these estimates produce different performance predictions, differences in the subjects’ observed performance would make it possible to infer whether subjects were preferentially using Exemplars or Prototypes.

Pre- vs. post-training comparison revealed a significant performance improvement; t=14.04, p<0.001, Cohen’s d=1.32. Pre-training, paired t-testing demonstrated that performance against the most typical vignettes>mid typical vignettes: t=4.94, p<0.001; and mid typical>least typical: t=5.16, p<0.001. Post-training, paired t-testing again demonstrated that performance against the most typical vignettes>mid typical: t=2.94, p<0.01; and mid typical>least typical: t=6.64, p<0.001. These findings are more consistent with the performance predictions generated via Prototype theory than Exemplar theory.

DPT is useful in designing and evaluating the utility of new approaches to diagnostic training, and, investigating the cognitive factors driving diagnostic capabilities among early medical students.

Understanding diagnostic error: looking beyond diagnostic accuracy

Whether a diagnosis is correct or incorrect is often used to determine diagnostic performance despite there being no valid measure of diagnostic accuracy. In this paper we draw on our experience of conducting research on diagnostic error and discuss some of the challenges that a focus on accuracy brings to this field of research. In particular, we discuss whether diagnostic accuracy can be captured and what diagnostic accuracy does and does not tell us about diagnostic judgement. We draw on these points to argue that a focus on diagnostic accuracy may limit progress in this field and suggest that research which tries to understand more about the factors that influence decision making during the diagnostic process may be more useful in helping to improve diagnostic performance.

Prospective risk analysis adjusted to the reality of clinical and fertility laboratory processes

Prospective risk analysis (PRA) is a valuable instrument in quality assurance. The practical application of PRA in clinical laboratories according to the method we have described elsewhere leaves room for a number of adaptations to make it more applicable to and consistent with actual laboratory processes.

We distinguished between more and less critical tests and products in the laboratory processes and scored the consequences of failures at different steps in line with the previously described failure type and effect analysis (FMEA) method. PRA was carried out for two typical laboratory processes: standard clinical laboratory testing and the cryopreservation of semen.

Tests in standard clinical laboratory in processes were labeled critical, semi-critical or non-critical. Consequence scoring (C) and assessed risk (R) were significantly higher for processes containing tests considered to be critical (C=6.6±1.5, R=19.3±13.5) as compared to processes containing tests considered semi- or non-critical (C=3.0±1.4, R=8.2±5.3 and C=3.2±1.8, R=8.6±5.9, respectively). There were no differences in the C and R scores for processes with tests considered semi- or non-critical. In the semen cryopreservation process, a distinction between the processes involving private semen and generally accessible semen was made. The C scores for these were significantly different (C=5.9±2.2 and 5.0±2.0, respectively), the R scores did not differ.

Introduction of a test criticality classification for the purpose of consequence scoring led to an improved PRA methodology, better reflecting the reality of clinical laboratory practice. We found that two levels of criticality, critical and less critical, were sufficient to achieve this improvement.

The Association Between Sensemaking During Physician Team Rounds and Hospitalized Patients' Outcomes

BACKGROUND

Sensemaking is the social act of assigning meaning to ambiguous events. It is recognized as a means to achieve high reliability. We sought to assess sensemaking in daily patient care through examining how inpatient teams round and discuss patients.

OBJECTIVE

Our purpose was to assess the association between inpatient physician team sensemaking and hospitalized patients' outcomes, including length of stay (LOS), unnecessary length of stay (ULOS), and complication rates.

DESIGN

Eleven inpatient medicine teams' daily rounds were observed for 2 to 4 weeks. Rounds were audiotaped, and field notes taken. Four patient discussions per team were assessed using a standardized Situation, Task, Intent, Concern, Calibrate (STICC) framework.

PARTICIPANTS

Inpatient physician teams at the teaching hospitals affiliated with the University of Texas Health Science Center at San Antonio participated in the study. Outcomes of patients admitted to the teams were included.

MAIN MEASURES

Sensemaking was assessed based on the order in which patients were seen, purposeful rounding, patient-driven rounding, and individual patient discussions. We assigned teams a score based on the number of STICC elements used in the four patient discussions sampled. The association between sensemaking and outcomes was assessed using Kruskal-Wallis sum rank and Dunn's tests.

KEY RESULTS

Teams rounded in several different ways. Five teams rounded purposefully, and four based rounds on patient-driven needs. Purposeful and patient-driven rounds were significantly associated with lower complication rates. Varying the order in which patients were seen and purposefully rounding were significantly associated with lower LOS, and purposeful and patient-driven rounds associated with lower ULOS. Use of a greater number of STICC elements was associated with significantly lower LOS (4.6 vs. 5.7, p = 0.01), ULOS (0.3 vs. 0.6, p = 0.02), and complications (0.2 vs. 0.5, p = 0.0001).

CONCLUSIONS

Improving sensemaking may be a strategy for improving patient outcomes, fostering a shared understanding of a patient's clinical trajectory, and enabling high reliability.

Lesson From a Case of Cervical Meningioma Misdiagnosed as Parkinsonism

INTRODUCTION

Lesion localization based on patient's manifestation is a fundamental step in making a neurological diagnosis. However, it has been reported that diagnosticians are vulnerable to the effects of various cognitive biases during diagnostic processes.

CASE REPORT

A 69-year-old man with right-hand stiffness visited the Movement Disorder Clinic with the history of periodic limb movement syndrome and restless leg syndrome. His sensory and deep tendon reflex examination results were normal. Brain magnetic resonance imaging was normal. Corticobasal degeneration was considered as a possibility, but functional imaging studies including FP-CIT positron emission tomography were all normal. Later, cervical spine magnetic resonance imaging revealed a cervical meningioma at the C2-C3 levels and he showed tingling senses in his right ulnar 3 fingers and a hyperactive knee jerk on his right side, which were absent on the first examinations.

CONCLUSIONS

Insufficient clinical information (declarative shortcoming) and inherent heuristic pitfalls (procedural shortcoming) were 2 major causes of the diagnostic error. Especially, in the present case, cognitive biases from framing effects and anchoring heuristics misled the clinical reasoning during the process of localization.

Use of an Expedited Review Tool to Screen for Prior Diagnostic Error in Emergency Department Patients

OBJECTIVE

Missed diagnoses are an important area of care quality resulting in significant morbidity and mortality. Determination of rates and causes has been limited by difficulties in screening, including the effort of manual chart review. We developed and tested a semi- automated review tool to expedite screening for diagnostic errors in an electronic health record (EHR).

METHODS

We retrospectively reviewed patients seen in the emergency department (ED) of a teaching hospital over 31 days, using an automated screen to identify those with a prior in-system visit during the 14 days preceding their ED visit. We collected prior and subsequent notes from the institution's EHR for these cases, then populated a specially designed relational database enabling rapid comparison of prior visit records to the sentinel ED visit. Each case was assessed for potential missed or delayed diagnosis, and rated by likelihood as "definite, probable, possible, unlikely or none."

RESULTS

A total of 5 066 patient encounters were screened by a clinician using the tool, of which 1 498 (30%) had a clinical encounter within the preceding 14 days. Of these, 37 encounters (2.6% of those reviewed) were "definite" or "probable" missed diagnoses. The rapid review tool took a mean of 1.9 minutes per case for primary review, compared with 11.2 minutes per case for reviews without the automated tool.

CONCLUSIONS

Diagnostic errors were present in a significant number of cases presenting to the ED after recent healthcare visits. An innovative review tool enabled a substantially increased efficiency in screening for diagnostic errors.

Cardiac Troponin I carryover by very high patient samples still causes false-positive results on the Beckman Coulter AccuTnI + 3

Background

False-positive cardiac troponin I results as a result of carryover have previously been reported on the Beckman Coulter AccuTnI assay. We sought to determine if the carryover problem had been resolved with the new AccuTnI + 3 assay.

Methods

Carryover experiments were performed in parallel on the Beckman Coulter Access2 analyser using the legacy AccuTnI and new AccuTnI + 3 assays. The same negative patient pool sample was analysed before and after a single analysis of an extremely elevated patient sample.

Results

Analysis of a single extremely high sample caused elevations above the 99th percentile cut-off, and thus false-positive cardiac troponin I results on both assays. Both assays demonstrated carryover and subsequent further elevations in negative pool results the following day.

Conclusions

Our study replicates our previously published findings of carryover and reagent pack contamination on the AccuTnI assay. Despite improvements on the new AccuTnI + 3 assay, carryover and reagent pack contamination are still present.

When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation

BACKGROUND

The threshold model represents an important advance in the field of medical decision-making. It is a linchpin between evidence (which exists on the continuum of credibility) and decision-making (which is a categorical exercise - we decide to act or not act). The threshold concept is closely related to the question of rational decision-making. When should the physician act, that is order a diagnostic test, or prescribe treatment? The threshold model embodies the decision theoretic rationality that says the most rational decision is to prescribe treatment when the expected treatment benefit outweighs its expected harms. However, the well-documented large variation in the way physicians order diagnostic tests or decide to administer treatments is consistent with a notion that physicians' individual action thresholds vary.

METHODS

We present a narrative review summarizing the existing literature on physicians' use of a threshold strategy for decision-making.

RESULTS

We found that the observed variation in decision action thresholds is partially due to the way people integrate benefits and harms. That is, explanation of variation in clinical practice can be reduced to a consideration of thresholds. Limited evidence suggests that non-expected utility threshold (non-EUT) models, such as regret-based and dual-processing models, may explain current medical practice better. However, inclusion of costs and recognition of risk attitudes towards uncertain treatment effects and comorbidities may improve the explanatory and predictive value of the EUT-based threshold models.

CONCLUSIONS

The decision when to act is closely related to the question of rational choice. We conclude that the medical community has not yet fully defined criteria for rational clinical decision-making. The traditional notion of rationality rooted in EUT may need to be supplemented by reflective rationality, which strives to integrate all aspects of medical practice - medical, humanistic and socio-economic - within a coherent reasoning system.

'It's like having a physician in your pocket!' A critical analysis of self-diagnosis smartphone apps

More than 100,000 mobile phone software applications ('apps') have been designed for the dissemination of health and medical information and healthcare and public health initiatives. This article presents a critical analysis of self-diagnosis smartphone apps directed at lay people that were available on the Apple App Store and Google Play in mid-April 2014. The objective of the analysis is to contribute to the sociology of diagnosis and to critical digital health studies by investigating the phenomenon of digitised diagnosis via apps. We adopted a perspective that views apps as sociocultural artefacts. Our analysis of self-diagnosis apps suggests that they inhabit a contested and ambiguous site of meaning and practice. We found that app developers combined claims to medical expertise in conjunction with appeals to algorithmic authority to promote their apps to potential users. While the developers also used appeals to patient engagement as part of their promotional efforts, these were undermined by routine disclaimers that users should seek medical advice to effect a diagnosis. More research is required to investigate how lay people are negotiating the use of these apps, the implications for privacy of their personal data and the possible effects on the doctor-patient relationship and medical authority in relation to diagnosis.

Current Evidence and Future Perspectives on the Effective Practice of Patient-Centered Laboratory Medicine

BACKGROUND

Systematic evidence of the contribution made by laboratory medicine to patient outcomes and the overall process of healthcare is difficult to find. An understanding of the value of laboratory medicine, how it can be determined, and the various factors that influence it is vital to ensuring that the service is provided and used optimally.

CONTENT

This review summarizes existing evidence supporting the impact of laboratory medicine in healthcare and indicates the gaps in our understanding. It also identifies deficiencies in current utilization, suggests potential solutions, and offers a vision of a future in which laboratory medicine is used optimally to support patient care.

SUMMARY

To maximize the value of laboratory medicine, work is required in 5 areas: (a) improved utilization of existing and new tests; (b) definition of new roles for laboratory professionals that are focused on optimizing patient outcomes by adding value at all points of the diagnostic brain-to-brain cycle; (c) development of standardized protocols for prospective patient-centered studies of biomarker clinical effectiveness or extraanalytical process effectiveness; (d) benchmarking of existing and new tests in specified situations with commonly accepted measures of effectiveness; (e) agreed definition and validation of effectiveness measures and use of checklists for articles submitted for publication. Progress in these areas is essential if we are to demonstrate and enhance the value of laboratory medicine and prevent valuable information being lost in meaningless data. This requires effective collaboration with clinicians, and a determination to accept patient outcome and patient experience as the primary measure of laboratory effectiveness.

An integrated breast cancer risk assessment and management model based on fuzzy cognitive maps

BACKGROUND

There is a growing demand for women to be classified into different risk groups of developing breast cancer (BC). The focus of the reported work is on the development of an integrated risk prediction model using a two-level fuzzy cognitive map (FCM) model. The proposed model combines the results of the initial screening mammogram of the given woman with her demographic risk factors to predict the post-screening risk of developing BC.

METHODS

The level-1 FCM models the demographic risk profile. A nonlinear Hebbian learning algorithm is used to train this model and thus to help on predicting the BC risk grade based on demographic risk factors identified by domain experts. The risk grades estimated by the proposed model are validated using two standard BC risk assessment models viz. Gail and Tyrer-Cuzick. The level-2 FCM models the features of the screening mammogram concerning normal, benign and malignant cases. The data driven Hebbian learning algorithm (DDNHL) is used to train this model in order to predict the BC risk grade based on these mammographic image features. An overall risk grade is calculated by combining the outcomes of these two FCMs.

RESULTS

The main limitation of the Gail model of underestimating the risk level of women with strong family history is overcome by the proposed model. IBIS is a hard computing tool based on the Tyrer-Cuzick model that is comprehensive enough in covering a wide range of demographic risk factors including family history, but it generates results in terms of numeric risk score based on predefined formulae. Thus the outcome is difficult to interpret by naive users. Besides these models are based only on the demographic details and do not take into account the findings of the screening mammogram. The proposed integrated model overcomes the above described limitations of the existing models and predicts the risk level in terms of qualitative grades. The predictions of the proposed NHL-FCM model comply with the Tyrer-Cuzick model for 36 out of 40 patient cases. With respect to tumor grading, the overall classification accuracy of DDNHL-FCM using 70 real mammogram screening images is 94.3%. The testing accuracy of the proposed model using 10-fold cross validation technique outperforms other standard machine learning based inference engines.

CONCLUSION

In the perspective of clinical oncologists, this is a comprehensive front-end medical decision support system that assists them in efficiently assessing the expected post-screening BC risk level of the given individual and hence prescribing individualized preventive interventions and more intensive surveillance for high risk women.

Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework

Diagnostic errors are major contributors to harmful patient outcomes, yet they remain a relatively understudied and unmeasured area of patient safety. Although they are estimated to affect about 12 million Americans each year in ambulatory care settings alone, both the conceptual and pragmatic scientific foundation for their measurement is under-developed. Health care organizations do not have the tools and strategies to measure diagnostic safety and most have not integrated diagnostic error into their existing patient safety programs. Further progress toward reducing diagnostic errors will hinge on our ability to overcome measurement-related challenges. In order to lay a robust groundwork for measurement and monitoring techniques to ensure diagnostic safety, we recently developed a multifaceted framework to advance the science of measuring diagnostic errors (The Safer Dx framework). In this paper, we describe how the framework serves as a conceptual foundation for system-wide safety measurement, monitoring and improvement of diagnostic error. The framework accounts for the complex adaptive sociotechnical system in which diagnosis takes place (the structure), the distributed process dimensions in which diagnoses evolve beyond the doctor's visit (the process) and the outcomes of a correct and timely "safe diagnosis" as well as patient and health care outcomes (the outcomes). We posit that the Safer Dx framework can be used by a variety of stakeholders including researchers, clinicians, health care organizations and policymakers, to stimulate both retrospective and more proactive measurement of diagnostic errors. The feedback and learning that would result will help develop subsequent interventions that lead to safer diagnosis, improved value of health care delivery and improved patient outcomes.

Lack of timely follow-up of abnormal imaging results and radiologists' recommendations

PURPOSE

Abnormal imaging results may not always lead to timely follow-up. We tested whether certain aspects of communication in radiology reports influence the response of the referring providers, and hence follow-up on abnormal findings.

METHODS

We focused on 2 communication-related items that we hypothesized could affect follow-up: expressions of doubt in the radiology report, and recommendations for further imaging. After institutional review board approval, we conducted a retrospective review of 250 outpatient radiology reports from a multispecialty ambulatory clinic of a tertiary-care Veterans Affairs facility. The selected studies included 92 cases confirmed to lack timely follow-up (ie, further tests or consultations, treatment, and/or communication to the patient within 4 weeks), as determined in a previous study. An additional 158 cases with documented timely follow-up served as controls. Doubt in the narrative was measured by the presence of key phrases (eg, "unable to exclude," "cannot exclude," "cannot rule out," "possibly," and "unlikely"), in the absence of which we used reviewer interpretation. A physician blinded to follow-up outcomes collected the data.

RESULTS

Patients whose reports contained recommendations for further imaging were more likely to have been lost to follow-up at 4 weeks compared with patients without such recommendations (P = .01). Language in the report suggestive of doubt did not affect the timeliness of follow-up (P = .59).

CONCLUSIONS

Abnormal imaging results with recommendations for additional imaging may be more vulnerable to lack of timely follow-up. Additional safeguards, such as tracking systems, should be developed to prevent failure to follow up on such results.

Initial blood lactate correlates with carboxyhemoglobin and clinical severity in carbon monoxide poisoned patients

OBJECTIVE

The aim of this study was to assess the role of blood lactate levels at admission in carbon monoxide (CO)-poisoned patients for establishing severity of poisoning and short term prognosis.

METHOD

All cases of CO poisoning visited in the emergency department during the years 2012 and 2013 were retrieved from the hospital database. The concentration of COHb and lactate was assessed in arterial blood in all patients with suspected CO poisoning, along with the plasma concentration of troponin I (TnI). The control population for TnI results consisted in 125 blood donors.

RESULTS

Twenty three (61%) out of 38 CO-poisoned patients underwent hyperbaric oxygen (HBO) treatment, and 10 (26%) were admitted to a hospital ward. A significant correlation was found between lactate and COHb (r=0.54; p<0.001), and between lactate and TnI (r=0.44; p=0.001). A significant correlation was also found between COHb and TnI (r=0.38; p=0.020). Blood lactate levels were higher in patients treated with HBO and hospital admission. In multivariate analysis, none of the parameters was associated with HBO treatment, whereas increased value of blood lactate (p=0.036) was the only significant predictor of hospital admission. Twenty five (66%) patients had detectable TnI levels compared to 13% controls (p<0.001), whereas 16% CO-poisoned patients had TnI levels >99th percentile compared to 2% controls (p=0.003). The odds ratio for detectable TnI and TnI >99th percentile in CO-poisoned patients were 13.1 (p<0.001) and 7.6 (p=0.006), respectively.

CONCLUSION

Initial blood lactate level may be useful for risk stratification of CO-poisoned patients, especially for predicting hospitalization.

Expert and competent non-expert visual cues during simulated diagnosis in intensive care

The aim of this study was to examine the information acquisition strategies of expert and competent non-expert intensive care physicians during two simulated diagnostic scenarios involving respiratory distress in an infant. Specifically, the information acquisition performance of six experts and 12 competent non-experts was examined using an eye-tracker during the initial 90 s of the assessment of the patient. The results indicated that, in comparison to competent non-experts, experts recorded longer mean fixations, irrespective of the scenario. When the dwell times were examined against specific areas of interest, the results revealed that competent non-experts recorded greater overall dwell times on the nurse, where experts recorded relatively greater dwell times on the head and face of the manikin. In the context of the scenarios, experts recorded differential dwell times, spending relatively more time on the head and face during the seizure scenario than during the coughing scenario. The differences evident between experts and competent non-experts were interpreted as evidence of the relative availability of task-specific cues or heuristics in memory that might direct the process of information acquisition amongst expert physicians. The implications are discussed for the training and assessment of diagnostic skills.