Band 2, Heft 2

The recognition over 25 years ago that the host response plays an exquisite role in sepsis, led to the today still-standard sepsis definition. Unfortunately, the inflammatory response syndrome (SIRS) criteria turned out to be less useful than anticipated, lacking sensitivity, specificity and ease of clinical application. Had novel host-response biomarkers been available by that time, it arguably would have been preferable to white blood cell count as an unspecific and not-sensitive laboratory-based SIRS criterion. Several novel markers have been put forward as sepsis markers with better diagnostic and/or prognostic potential in sepsis including inflammatory markers such as procalcitonin (PCT), presepsin, proadrenomedullin (ProADM), endothelial dysfunction markers such as P-selectin, E-selectin, intercellular cell adhesion molecule [ICAM]-1 and vascular cell adhesion molecule [VCAM]-1 and genetic markers among others. The limitations to using clinical parameters and conventional diagnostic markers for patients with clinical suspicion of sepsis may directly lead to both, under treatment of patients with severe disease needing urgent antibiotic and fluid therapy, and unnecessary and prolonged exposure to antimicrobial agents adversely affecting patient outcomes and increasing antibiotic resistance. The aim of this review is to summarize the current evidence for emerging diagnostic, prognostic, and therapeutic-response sepsis biomarkers in different infections and clinical settings, and discuss the reliability, potential benefit and limitations of these marker when used in clinical routine for sepsis management.

An increasing number of smartphone and software applications (“apps”) have been developed and marketed to assist in the process of diagnosis, yet little attention has been paid to their content, claims, potential risks, limitations or benefits of their use. This study sought to describe and catalogue available diagnosis apps and explore their impact on the diagnostic process. We undertook a content analysis of the app descriptions and developers’ websites using the descriptions provided for 131 medical diagnosis smartphone apps that were available in the Google Play and Apple App stores. Each app was reviewed for its content and approach, and its claims to medical authority. Four major categories of apps were identified: 1. apps for diagnosing; 2. diagnosis coding apps; 3. books, journals, or other publications in app format; 4. apps for medical education. Our analysis found that while these apps provide access to medical information previously widely not available to lay users and offered a convenient diagnostic tool for practitioners, many failed to describe the evidence base underpinning, or any other credential supporting, their design and use. These apps potentially shift how diagnosis operates, reconfiguring disease concepts and lay-professional relations. However they also raise the risk of conflict of interest and presenting inaccurate information. Further research is required into how these apps are used, the implications for medical practice and the impact on doctor-patient relationship.

Diagnostic errors have emerged as a serious patient safety problem but they are hard to detect and complex to define. At the research summit of the 2013 Diagnostic Error in Medicine 6th International Conference, we convened a multidisciplinary expert panel to discuss challenges in defining and measuring diagnostic errors in real-world settings. In this paper, we synthesize these discussions and outline key research challenges in operationalizing the definition and measurement of diagnostic error. Some of these challenges include 1) difficulties in determining error when the disease or diagnosis is evolving over time and in different care settings, 2) accounting for a balance between underdiagnosis and overaggressive diagnostic pursuits, and 3) determining disease diagnosis likelihood and severity in hindsight. We also build on these discussions to describe how some of these challenges can be addressed while conducting research on measuring diagnostic error.

Overdiagnosis and overtreatment are often thought of as relatively recent phenomena, influenced by a contemporary combination of technology, specialization, payment models, marketing, and supply-related demand. Yet a quick glance at the historical record reveals that physicians and medical manufacturers have been accused of iatrogenic excess for centuries, if not millennia. Medicine has long had therapeutic solutions that search for ever-increasing diagnostic problems. Whether the intervention at hand has been leeches and lancets, calomel and cathartics, aspirins and amphetamines, or statins and SSRIs, medical history is replete with skeptical critiques of diagnostic and therapeutic enthusiasm. The opportunity cost of this profusion shapes the other side of the coin: chronic persistence of underdiagnosis and undertreatment. Drawing from key controversies of the 19th and 20th centuries, we chart the enduring challenges of inter-related diagnostic and therapeutic excess. As the present critique of overdiagnosis and overtreatment seeks to mobilize resources from inside and outside of medicine to rein in these impulses, we provide an instructive historical context from which to act.

Electronic health record (EHR) usage is accelerating while preventable diagnostic error persists. EHRs may even contribute to diagnostic error through several pathways including poor usability and an over reliance on electronic chart based communication. The changing context of healthcare delivery offers potential financial incentives for organizations to leverage EHRs to reduce diagnostic error. The lack of standard quality metrics for reporting rates of diagnostic error, a lack of diagnostic feedback systems for physicians and organizations, and a lack of compelling evidence for specific interventions underscore the need for further research in preventing diagnostic error. Many potential strategies exist for EHRs to reduce the likelihood of diagnostic error. Practical next steps for leveraging EHR systems to assist in the diagnostic process are suggested. These include patient engagement strategies, closed loop result tracking, targeted next step reminder systems, and expansion of a list of actionable patient states based on diagnosis triggers.

Background: Debiasing education has been recommended for physicians in training. We report on the efficacy of a workshop designed to aid family medicine residents recognize and respond to their risk of misdiagnosis due to cognitive biases during patient care. Methods: Residents participated in a debiasing workshop in which they were taught to recognize and respond to cognitive biases likely to contribute to misdiagnosis. Metacognition was introduced and cognitive forcing strategies were demonstrated and practiced. While precepting clinic visits, attendings evaluated residents in the following areas: 1) diagnostic concordance between resident and attending, 2) ability of the resident to perceive their risk of cognitive bias, 3) the quality of the resident’s plan to mitigate this risk, and 4) the presence of an unrecognized cognitive bias. Pre and post workshop data were compared. Results: Preceptor concurrence with the residents’ diagnoses was unchanged – 74% (63 of 85) vs. 78% (45 of 58, p=0.64). Residents’ ability to recognize their risk of cognitive bias was unchanged – 51% (43 of 85) vs. 57% (33 of 58, p=0.46). Residents’ formulation of an acceptable plan to mitigate the effect of cognitive bias increased from 84% (36 of 43) to 100% (33 of 33, p=0.02). Preceptors’ perception of an unrecognized cognitive bias in the residents’ presentation was unchanged – 12% (10 of 85) vs. 9% (5 of 58, p=0.55). Conclusions: A debiasing workshop for family medicine residents demonstrated improvement in one of four studied outcomes.

Background: Use of differential diagnosis (DDX) generators may reduce the incidence of misdiagnosis-related harm, but there is a paucity of research examining the use and impact of such systems in real-world settings. Methods: In September 2012, the DDX generator VisualDx was made available across our entire academic healthcare system. We examined the use of VisualDx by month for the 18 months following its introduction. In addition, we compared the number of inpatient dermatology consults requested per month at the flagship hospital of our healthcare system for the 12 months before versus 18 months after VisualDx introduction. Results: Across our entire academic healthcare system, there were a median of 474 (interquartile range 390–544) unique VisualDx sessions per month. VisualDx was accessed most frequently through mobile devices (35%) and the inpatient electronic health record (34%). Prior to VisualDx introduction, there was a non-significant increase in the number of inpatient dermatology consultations requested per month at the flagship hospital of our healthcare system (1.0 per month, 95% CI –2.5–4.6, p=0.54), which remained 1.0 consults per month (95% CI –0.9–2.9, p=0.27) following its introduction (p=0.99 comparing post- versus pre-introduction rates). Conclusions: The DDX generator VisualDx was regularly used, primarily on mobile devices and inpatient workstations, and was not associated with a change in inpatient dermatology consultation requests. Given the interest in DDX generators, it will be important to evaluate further the impact of such tools on the quality and value of care delivered.

Background: In an effective and efficient health system, laboratory medicine should play a critical role. This is not the case in Africa, where there is a lack of demand for diagnostic exams due to mistrust of health laboratory performance. Doctors with Africa CUAMM (Collegio Universitario Aspiranti Medici Missionari) is a non-profit organization, working mainly in sub-Saharan Africa (Angola, Ethiopia, Mozambique, Sierra Leone, South Sudan, Tanzania and Uganda) to help and sustain local health systems. Doctors with Africa CUAMM has advocated the need for a harmonized model for health laboratories to assess and evaluate the performance of the facilities in which they operate. Methods: In order to develop a harmonized model for African health laboratories, previous attempts at strengthening them through standardization were taken into consideration and reviewed. A survey with four Italian clinicians experienced in the field was then performed to try and understand the actual needs of health facilities. Finally a market survey was conducted to find new technologies able to update the resulting model. Results: Comparison of actual laboratories with the developed standard – which represents the best setting any African health laboratory could aim for – allowed shortcomings in expected services to be identified and interventions subsequently prioritized. The most appropriate equipment was proposed to perform the envisaged techniques. The suitability of appliances was evaluated in consideration of recognized international recommendations, reported experiences in the field, and the availability of innovative solutions that can be performed on site in rural areas, but require minimal sample preparation and little technical expertise. Conclusions : The present work has developed a new, up-to-date, harmonized model for African health laboratories. The authors suggest lists of procedures to challenge the major African health problems – HIV/AIDS, malaria, tubercolosis (TB) – at each level of pyramidal health system. This model will hopefully support the non-governmental organization (NGO) Doctors with Africa CUAMM in its activities in sub-Saharan hospitals, providing them with a guideline to programme future interventions.

Macrocomplexes between immunoglobins and aspartate aminotransferase (macro-AST) may result in persistently increased AST concentration. The presence of macro-AST in patients has been implicated in unnecessary investigations of abnormal liver function tests. We report the case of a 44-year-old female who presented to the rheumatology clinic with a 12-months’ history of constant widespread pain affecting her limbs and was found to have an elevated AST concentration. Further information from her GP revealed a 14-years’ history of elevated AST with otherwise normal liver function. Previous abdominal ultrasound and two liver biopsies carried out 2 years apart were normal. This prompted further analytical investigation by the biochemistry department which identified macro-AST as the cause. This case illustrates that persistently raised isolated AST concentration with no other abnormal indices may warrant macroenzyme analysis potentially avoiding unnecessary invasive investigations.