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Dealing with isolation and medical uncertainty
Published in Peter Davies, Lindsay Moran, Hussain Gandhi, Adrian Roebuck, Clare J Taylor, The New GP′s Handbook, 2022
Managing uncertainty is a major part of medicine. It is something we do every day, whatever specialty or niche we are practising in. We are all making decisions on partial information, on probabilities rather than certainties. We are all doing this quickly, and of course we are all making some mistakes as we do so.
The discipline of strategic thinking in healthcare
Published in Robert Jones, Fiona Jenkins, Managing and Leading in the Allied Health Professions, 2021
To understand the full set of consequences, strategic thinking must uncover the amount of uncertainty; the lower the amount of uncertainty, the better the understanding of the likely consequences. Uncertainty, as it is used here, is defined as a lack of sure knowledge about past, present or future events. Consequently, every strategic situation could be categorised by the amount of uncertainty in framing the problem and finding a solution.56,59,60 Table 12.1 displays strategic situations by five classes of uncertainty. For example, in class 1, which represents the lowest levels of uncertainty, decisions are mechanical and do not require a great deal of strategic thinking. The problem is well-defined and the trends are clear enough to be able to predict what might happen if a strategic opportunity is exploited. An example of low uncertainty would be determining the costs and benefits of shifting acute cases over to day surgery, such as simple inguinal hernias or eye surgery, or developing clinical guidelines for ACE (angiotensin converting enzyme) inhibitor therapy. There are other strategic situations that have much higher levels of uncertainty.
Complexity: Cloud 9, Caryl Churchill (1979)
Published in Ewan Jeffrey, David Jeffrey, Enhancing Compassion in End-of-Life Care Through Drama, 2021
Pattern recognition may of course lead to the doctor jumping to the wrong conclusions because this intuitive reasoning involves making assumptions. The problem is made more acute by frequent media coverage of doctors’ mistakes, leading to added pressure in diagnostic situations. Doctors are unhappy with uncertainty: yet uncertainty is one factor that is inevitable in a clinical context. Let us take a different example where an assumption has more serious consequences.
Adopting a portfolio of ultrasonic and advanced bipolar electrosurgery devices from a single manufacturer compared to currently used ultrasonic and advanced bipolar devices: a probabilistic budget impact analysis from a Spanish hospital perspective
Published in Journal of Medical Economics, 2023
Alessandra Piemontese, Lucas Cohen, George W. J. Wright, Natalia Robledinos-Antón, Nadine Jamous, Giovanni A. Tommaselli, Thibaut Galvain
This study has several notable strengths. The model was designed to incorporate clinical evidence from the literature for all surgical specialties with sufficient available data. This data was used to directly compare the relative efficacy of Ethicon devices versus other manufacturers17–21, or estimate comparative efficacy based on a NMA16 when direct comparative evidence was unavailable. In the absence of head-to-head comparisons for some specialties, the NMAs enabled indirect comparisons of Ethicon advanced energy portfolio devices to Non-Ethicon advanced energy devices through a common comparator, usually conventional surgical methods16. Clinical evidence was incorporated into the model, regardless of whether results favored products from Ethicon or other manufacturers. Next, the use of a stochastic model allowed for the incorporation of parameter uncertainty into the results, allowing for a robust probabilistic analysis across 10,000 model iterations. Incorporating variability in costs supports the generalizability of results, since other hospital settings across Spain and Europe may have different costs. The probabilistic analysis also enabled incorporation of the uncertainty in the healthcare resource use outcomes. The finding that the Ethicon portfolios were still cost saving in the scenario with higher Ethicon device prices further support the robustness and generalizability of the analysis results to other hospital settings in Europe.
Twelve tips for introducing very short answer questions (VSAQs) into your medical curriculum
Published in Medical Teacher, 2023
Laksha Bala, Rachel J. Westacott, Celia Brown, Amir H. Sam
First, there are many situations in which a single best answer does not exist in medicine. Clinical uncertainty is inherent in medicine. Decisions around diagnosis and management are often nuanced and indeed even experts do not always agree on a single diagnosis or best course of action. Furthermore, as summarised by Surry et al. (2017), ‘patients do not walk into the clinic saying, I have one of these five diagnoses, which do you think is most likely?’ (p. 1082). Assessing students using an artificial situation whereby a patient presents with a list of five possible diagnoses is inauthentic and does not reflect the environment in which clinicians practice. Rather, clinicians formulate a list of possible diagnoses following assessment of a patient including taking a history, examining and considering available investigation results. Given the role assessment has in driving learning behaviours (Epstein 2007), it is essential that assessment methods encourage learning that prepares students for the realities of clinical practice.
Twelve Tips for teaching shared decision making
Published in Medical Teacher, 2023
Matthew Zegarek, Rebecca Brienza, Noel Quinn
Uncertainty is intrinsic to clinical medicine. Stochastic uncertainty refers to unknown outcomes for a particular patient (e.g. whether or not they personally will develop cancer), probabilistic uncertainty refers to lack of or conflicting empirical data (e.g. the degree of benefit of cancer screening), while informational uncertainty refers to lack of usable information for a particular clinical situation (e.g. how much greater is my patient’s risk for lung cancer than the average person in this trial based on her asbestos exposure?). Some data suggests that use of patient decision aids can reduce patient uncertainty in their decision making, which is a goal of SDM. However, some degree of uncertainty is not modifiable (Politi et al. 2016). All of these forms of uncertainty may affect decision making, and many recommend that uncertainty is explicitly acknowledged with patients (Politi and Street 2011; Berger 2015). However, uncertainty is rarely discussed in clinical practice, perhaps because many residents are trained to display confidence and are worried that discussing uncertainty will lead to patient confusion and anxiety (Politi and Street 2011).