Chapter 1
Introduction to problem-based inductive clinical reasoning

Jill E. Maddison & Holger A. Volk

The Royal Veterinary College, Department of Clinical Science and Services, London, UK

The aim of this book is to assist you to develop a structured and pathophysiologically sound approach to the diagnosis of common clinical problems in small animal practice. The development of a sound basis for clinical problem solving provides the veterinarian with the foundation and scaffold to allow them to potentially reach a diagnosis regardless of whether they have seen the disorder before. Furthermore, the method presented in this book will help you avoid being stuck trying to remember long differential lists and hence free your thinking skills to solve complex medical cases. The aim of the book is not to bombard you with details of different diseases - there are many excellent textbooks and other resources that can fulfil this need. What we want to provide you with is a framework by which you can solve clinical problems and place your veterinary knowledge into an appropriate problem-solving context.

We all remember our first driving lessons, which may have been quite challenging - for us and/or our instructors! We had to think actively about many factors to ensure we drove safely. The more experienced we became at driving, the more non-driving-associated tasks, such as talking to our passengers, listening to the radio and changing the radio channels, we were able to do while driving. If we had attempted any of these tasks at the beginning of our driver training, we might have had an accident. As we become more experienced at a task, we need to think less about it, as we move to what is known as unconscious competence.

We see a similar process in clinical education. During the progression from veterinary student to experienced clinician, knowledge and skills are initially learnt in a conscious and structured way. Veterinary undergraduate education in most universities is therefore based on systems teaching, species teaching or a mixture of both. These are excellent approaches to help develop a thorough knowledge base and understanding of disease processes and treatments. However, when an animal or group of animals becomes unwell, the clinical signs they exhibit can be caused by a number of disorders of a range of different body systems - the list may seem endless. They do not present to the veterinarian with labels on their heads stating the disease they have (more's the pity!). Therefore, for the veterinarian to fully access their knowledge bank, they need to have a robust method of clinical reasoning they can rely on. This method allows them to consolidate and relate their knowledge to the clinical case and progress to a rational assessment of the likely differential diagnoses. This makes it easier to determine appropriate diagnostic and/or management options for the patient. Because you have a clear path, communication with the client becomes easier.

The next part of the journey of becoming an experienced clinician is that clinical judgement and decision-making processes become unconscious or intuitive. The rapid, unconscious process of clinical decision-making by experienced clinicians is referred to in medical literature as intuition or the 'art' of medicine. The conscious thinking process is often referred to as 'science' (evidence-based) or analytic. Intuition is context-sensitive, influenced by the level of the clinician's experience, context-dependent and has no obvious cause-and-effect logic. Why is this important? We have all thought - 'I just know that the animal has .' The unconscious mind will pretend to the conscious mind that the clinical decision was based on logical assumptions or causal relationships. This is not a problem as long the intuition or 'pattern recognition' has resulted in a correct diagnosis. However, when it does not, we need to understand why it failed and have a system in place to rationally progress our clinical decision-making. This book will provide you with the tools and thinking framework needed to unravel any clinical riddle, unleashing the potential of your unconscious mind rather than blocking your working memory as you try to recall all the facts you may have once known.

Why are some cases frustrating instead of fun?

Reflect on a medical case that you have recently dealt with that frustrated you or seemed difficult to diagnose and manage. Can you identify why the case was difficult?

There can be a multitude of reasons why complex medical cases are frustrating instead of fun.

• Was it due to the client (e.g. having unreal expectations that you could fix the problem at no cost to themselves? Unwilling or unable to pay for the diagnostic tests needed to reach a diagnosis? Unable to give a coherent history?)
• Was the case complex and didn't seem to fit any recognisable pattern?
• Were you unable to recall all the facts about a disease and this biased your thinking?
• Did the signalment, especially breed and age, cloud your clinical decision-making resulting in an incorrect differential list?
• Did the case seem to fit a pattern but subsequent testing proved your initial diagnosis wrong?
• Did you seem to spend a lot of the client's money on tests that weren't particularly illuminating?

Can you add any other factors that have contributed to frustrations and difficulties you may have experienced with medical cases?

Apart from the client issues (and as discussed later, we may be able to help a little bit here as well), we hope that by the end of this book, we will have gone some way towards removing the common barriers to correct, quick and efficient diagnosis of medical cases and have made unravelling medical riddles fun.

Solving clinical cases

When a patient presents with one or more clinical problems, there are various methods we can use to solve the case and formulate a list of differential diagnoses. One method involves pattern recognition - looking at the pattern of clinical signs and trying to match that pattern to known diagnoses. This is also referred to as developing an illness script. Another method can involve relying on blood tests to tell us what is wrong with the patient - also referred to as the minimum database. Or we can use problem-based clinical reasoning. Often, we may use all three methods.

Pattern recognition

Pattern recognition involves trying to remember all diseases that fit the 'pattern' of clinical signs/pathological abnormalities that the animal presents with. This may be relatively simple (but can also lead to errors of omission) and works best:

• For common disorders with typical presentations
• If a disorder has a unique pattern of clinical signs
• When all clinical signs have been recognised and considered, and the differential list is not just based on one cardinal clinical sign and the signalment of the patient presented
• If there are only a few diagnostic possibilities that are
  • easily remembered or
  • can easily be ruled in or out by routine tests
• If the vet has extensive experience, is well read and up-to-date, reflects on all of the diagnoses they make regularly and critically and has an excellent memory.

Pattern recognition works well for many common disorders and has the advantage of being quick and cost effective, provided the diagnosis is correct. The vet looks good to the client because they have acted decisively and confidently . provided the diagnosis is correct.

However, pattern recognition can be flawed and unsatisfactory when the clinician is inexperienced (and therefore has seen very few patterns) or only considers or recognises a small number of factors (and is not aware that this process is mainly driven by unconscious processes that might need to be reflected upon if they fail). Or even if the clinician is experienced, it can be flawed for uncommon diseases or common diseases presenting atypically, when the patient is exhibiting multiple clinical signs that are not immediately recognisable as a specific disease, or if the pattern of clinical signs is suggestive of certain disorders but not specific for them. In addition, for the experienced clinician, the success of pattern recognition relies on a correct diagnosis for the pattern observed previously being reached and not assuming that similar patterns must equal the same diagnosis. Pattern recognition can lead to dangerous tunnel vision where the clinician pursues his/her initial diagnostic hunch based on pattern spotting to the exclusion of other diagnostic possibilities. They may then interpret all subsequent data as favourable to their initial diagnosis, including ignoring data that doesn't 'fit' their preferred diagnosis. This phenomenon is described in psychological literature as confirmation bias - defined as a tendency for people to favour information that confirms their beliefs or hypotheses. And finally, the disadvantage of relying entirely on pattern recognition to solve clinical problems means that should the clinician realise subsequently that their pattern recognition was incorrect, they have no logical intellectual framework to help them reassess the patient. Thus, pattern-based assessment of clinical cases can result at best in a speedy, correct, 'good value' diagnosis but at worst in wasted time, money and, sometimes,...