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Clinical Practice Paramedic decision-making and the influence of bias: a case study David (Spud) Tory, Paramedic, South Western Ambulance Service, Blandford Forum, UK; Iain Darby, Programme Lead, Paramedic Science, Bournemouth University, Bournemouth, UK. Email: idarby@bournemouth.ac.uk Abstract Background: Prehospital clinical decision-making is a complex, evolving skill. Typically, there are multiple possible diagnoses and several potential treatment pathways to be considered, and usually prehospital clinicians have to base their decisions on imperfect information. Biases will inevitably compete to influence clinicians as they attempt to weigh the probabilities of diagnoses, degrees of certainty and permissible risks in their decision-making process. With experience, as intuition and tacit knowledge develop, paramedics will depend less on explicit knowledge and algorithm-based decision-making tools. Paramedics must strive to strike the right balance between the intuitive and analytical aspects of clinical decision-making, while maintaining an awareness of the human factors that will influence them in this process if optimal clinical decisions and therefore patient outcomes are to be achieved. This case study illustrates complex decision-making in the prehospital setting, with a focus on the influence of bias. Key words l Clinical decision-making l Emotional bias l Irrational deductive process l Rapid deduction process l Probabilities of diagnosis l Permissible risks Accepted for publication:1 April 2022 This critical analysis will evaluate the clinical decision-making process during an incident that I attended but was led by another paramedic, where there were several possible patient diagnoses and three potential treatment pathways. The probabilities of diagnoses, degrees of certainty and permissible risks will be analysed during the assessment, consideration of diagnoses and treatment stages of this incident. Particular attention will be paid to the influence of emotional biases on our deductive process throughout. This analysis is anonymised in accordance with the 2018 Data Protection Act and the Health and Care Professions Council Standards of Conduct, Performance and Ethics (2016). The incident This incident was assigned to us at 22:25, 35 minutes before our shift was due to finish. We were tired, and our desire to finish on time made us acutely aware of how close this was to the end of our shift. The patient, who was in his 80s, was sent an ambulance because of an episode of confusion during the evening, which had now resolved. He had a 2-month history of a cough and had had his influenza vaccination 30 hours before this incident. The patient was tachypnoeic, but my impression was that he appeared otherwise well; he was self-mobilising, fully orientated and reported no pain or impairments at that time. The patient’s wife, also in her 80s, was in attendance and mobilising using a frame. However, it was apparent that the patient and his wife were dependent on each other for their personal care, with no relatives or friends able to assist them. On examination, the patient had a peripheral body temperature (PBT) of 38.6°C and a respiration rate (RR) of 26 breaths per minute (bpm). All his other baseline observations were unremarkable and his chest was clear of adventitious sounds on auscultation. We were attending the patient in his home, which was unkempt but warm. We considered that, alongside his overall presentation, the patient’s elevated PBT and RR were primarily indicative of infection, sepsis or an adverse reaction to his influenza vaccination. Without further tests, possible only in definitive care, we could not be certain of the his diagnosis. lthcare Ltd Hea MA 2022 © 226 Vol 14 No 6 • Journal of Paramedic Practice
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Clinical Practice At this time, there were three treatment pathways available to us: leave the patient at home with advice on what to do if his condition worsened and recommend that he contact his GP in the morning to discuss his symptoms; remain at the scene and contact an out-of-hours (OOH) doctor to discuss immediate assessment at home; or convey the patient to an emergency department (ED) for assessment and treatment if required, having first instigated care for the patient’s wife in the absence of her husband. We were aware that waiting on the scene for a call from the OOH doctor or to organise care for the patient’s wife’s at this time of night would result in significant time being spent at the scene. It soon became apparent that we were manipulating the available information and further assessment decisions to conform to our desired belief that the patient’s elevated PBT and RR were a self-limiting reaction to his influenza vaccination. If this were so, it would be safe to leave him at home, and we would make a timely finish. This was the incident outcome. The desire not to finish late caused a significant emotional bias in our decision-making (Lempert and Phelps, 2013). Analysis of this incident will show that this bias caused the adoption of irrationally rapid and therefore potentially erroneous diagnosis forecasting (BlumenthalBarby and Krieger, 2015). Our diagnosis forecasting was affirmed by biases of confirmation (manipulating information to conform to a desired outcome or belief) and anchoring (depending too heavily on an initial piece of information) (Shaffer et al, 2016; Featherstone et al, 2020; Stephens, 2020). These human factors (Collen, 2017) were apparent throughout the incident. lthcare Ltd Hea MA 2022 © Patient assessment The patient’s elevated PBT was indicative of an immune response to illness or infection (Lu and Dai, 2009; Rubia-Rubia et al, 2011; Podsiadło et al, 2019). The origin of his elevated RR could have been metabolic acidosis, indicative of systemic disorders such as infection or sepsis (Cretikos et al, 2008; Rolfe, 2019; Martin-Rodriguez et al, 2020), but that can also occur in response to an increase in blood temperature as a mechanism of physical thermoregulation (Onisor et al, 2019). These factors in the patient’s assessment, and his history of a cough and recent episode of confusion were the primary factors in the clinical decision-making in this incident. Multiple theories explain the process of clinical decision-making, but all these theories share two distinct aspects: the formation of a hypothesis; and the accumulation and deduction of data from the patient’s assessment and history, to confirm or reject this hypothesis (Lempert and Phelps, 2013; Monteiro et al, 2018). We identified the patient’s recent influenza vaccine as a plausible hypothesis to explain his elevated PBT and RR. Confirmation and anchoring biases were instrumental in our failure to continue to hypothesise differential diagnoses (Yousaf et al, 2020), thereby avoiding the necessity for the further assessments required to properly inform analysis of these diagnoses. Further assessments would have included systematic observation, auscultation and palpation of the patient’s thorax and abdomen, and rigorous history-taking to enable us to assess the diagnoses’ pre-test probabilities (Brown and Cadogan, 2016; Bickley and Szilagyi, 2017). Our failure to carry out these assessments was in contravention of rational reasoning and rigour in our deductive process (Simmons, 2010) as we had insufficient facts upon which to base an informed decision. Therefore, our deductive process was irrational (Blumenthal-Barby and Krieger, 2015). Benner et al (2016) describe how early formation of a hypothesis becomes an increasingly intuitive process with experience, and that the risk of bias is greatest at this stage of the clinical decision-making process. The deductive stage is analytical and needs to be systematic to mitigate errors in clinical judgement; at this stage, the risk of a disorganised deductive process becomes greater (Blumenthal-Barby and Krieger, 2015). Probability of diagnosis and differential diagnoses As we did not consider the pre-test probabilities that the patient’s presentation was caused by his influenza vaccine or differential diagnoses of infection or sepsis, we could not have assessed our degrees of certainty, nor considered whether the risks of leaving him at home were permissible. At the time of this incident (November 2020), older adults (aged 65 years or over) in England were offered the adjuvanted trivalent influenza vaccine (aTIV) (Public Health England, 2020). If the patient’s elevated RR and PBT were a result of his aTIV administration, these would have been systemic adverse reactions (Seqirus, 2020). Systemic adverse reactions to vaccinations are classified as serious (Kroger et al, 2022). Moro et al (2020) searched the Vaccine Adverse Event Reporting System (VAERS) for adverse reactions occurring following the administration of IIV3-HD, an aTIV licensed for use in the United Journal of Paramedic Practice • Vol 14 No 6 227

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Clinical Practice

Paramedic decision-making and the influence of bias: a case study

David (Spud) Tory, Paramedic, South Western Ambulance Service, Blandford Forum, UK; Iain Darby, Programme Lead, Paramedic Science, Bournemouth University, Bournemouth, UK. Email: idarby@bournemouth.ac.uk

Abstract

Background: Prehospital clinical decision-making is a complex, evolving skill. Typically, there are multiple possible diagnoses and several potential treatment pathways to be considered, and usually prehospital clinicians have to base their decisions on imperfect information. Biases will inevitably compete to influence clinicians as they attempt to weigh the probabilities of diagnoses, degrees of certainty and permissible risks in their decision-making process. With experience, as intuition and tacit knowledge develop, paramedics will depend less on explicit knowledge and algorithm-based decision-making tools. Paramedics must strive to strike the right balance between the intuitive and analytical aspects of clinical decision-making, while maintaining an awareness of the human factors that will influence them in this process if optimal clinical decisions and therefore patient outcomes are to be achieved. This case study illustrates complex decision-making in the prehospital setting, with a focus on the influence of bias. Key words l Clinical decision-making l Emotional bias l Irrational deductive process l Rapid deduction process l Probabilities of diagnosis l Permissible risks

Accepted for publication:1 April 2022

This critical analysis will evaluate the clinical decision-making process during an incident that I attended but was led by another paramedic, where there were several possible patient diagnoses and three potential treatment pathways. The probabilities of diagnoses, degrees of certainty and permissible risks will be analysed during the assessment, consideration of diagnoses and treatment stages of this incident. Particular attention will be paid to the influence of emotional biases on our deductive process throughout.

This analysis is anonymised in accordance with the 2018 Data Protection Act and the Health and

Care Professions Council Standards of Conduct, Performance and Ethics (2016).

The incident This incident was assigned to us at 22:25, 35 minutes before our shift was due to finish. We were tired, and our desire to finish on time made us acutely aware of how close this was to the end of our shift.

The patient, who was in his 80s, was sent an ambulance because of an episode of confusion during the evening, which had now resolved. He had a 2-month history of a cough and had had his influenza vaccination 30 hours before this incident. The patient was tachypnoeic, but my impression was that he appeared otherwise well; he was self-mobilising, fully orientated and reported no pain or impairments at that time. The patient’s wife, also in her 80s, was in attendance and mobilising using a frame. However, it was apparent that the patient and his wife were dependent on each other for their personal care, with no relatives or friends able to assist them.

On examination, the patient had a peripheral body temperature (PBT) of 38.6°C and a respiration rate (RR) of 26 breaths per minute (bpm). All his other baseline observations were unremarkable and his chest was clear of adventitious sounds on auscultation. We were attending the patient in his home, which was unkempt but warm. We considered that, alongside his overall presentation, the patient’s elevated PBT and RR were primarily indicative of infection, sepsis or an adverse reaction to his influenza vaccination. Without further tests, possible only in definitive care, we could not be certain of the his diagnosis.

lthcare Ltd

Hea

MA

2022

©

226

Vol 14 No 6 • Journal of Paramedic Practice

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