Digitalising Clinical Guidelines: The Challenge of Patient's Preferences.

Will digitalised clinical guidelines be compatible with individualised and personalised patient care if the disease definitions and classifications used within them contain embedded preferences? Taking bone health as a case study, we found the dominant definition of osteoporosis installs the consensus preference judgement of a 1992 International Expert Committee in the form of a threshold cut-off on the bone mineral density continuum. We found that subsequent UK clinical guidelines follow suit on this diagnostic threshold, but also endorse preference-sensitive thresholds for interventions to prevent fractures, including ones underpinned by cost-effectiveness analysis. The resulting pre-emption of patient's preferences needs to be removed if 'computable' guidelines are to be reconcilable with personalised care.

Taking the Patient's Preferences into Account in the Anticoagulation Decision: Largely Lip-Service?

Clinical guidelines for the assessment and management of atrial fibrillation emphasize the importance of taking the patient's preferences into account. A detailed examination of those from the National Institute for Excellence in Health and Social Care (NICE) raise serious questions about whether the recommendations embed preferences about crucial trade-offs that pre-empt those of the patient; do not stress the need to provide them with the information on option consequences necessary for them to become an informed patient; and characterise them as 'concordant' or 'discordant' rather than independently valid. American and European guidelines do not differ significantly in these respects.

Do Shared Decision-Making and Patient Decision Aids Take Patient's Preferences Seriously?

Most clinical guidelines for the assessment and management of atrial fibrillation emphasize the importance of decision support provided by Patients Decision Aids, but they are to be used and evaluated only in the context of Shared Decision-Making. Detailed examination of 10 clinical decision support tools reveals that many do not engage with patient's preferences at all. Only two take them seriously in terms of their formation, elicitation and processing, aimed at identifying the optimal personalised decision for the patient.

Will 'Computable' Clinical Guidelines Be Compatible with Personalised Care?

Introduction: The potential benefits from digitalisation processes will only be fully realised if the conceptual challenges they uncover are accepted and addressed, alongside the technical ones such as interoperability. Will 'computable' clinical guidelines be compatible with personalised care if the definition of the relevant disease embeds preferences that pre-empt those of the individual patient?

Method: As a case study we investigated the definition of diabetes in glycaemic management guidelines.

Result: The dominant component of its definition - HbA1c ≥6.

Inferring Causality Is Preference-Sensitive: We Need a Book of Who as Well as Why.

In multiple publications over 3 decades, most recently in The Book of Why, Judea Pearl has led what he regards as the 'causal revolution'. His central contention is that, prior to it, no discipline had produced a rigorous 'scientific' way of making the causal inferences from observational data necessary for policy and decision making. The concentration on the statistical processing of data, outputting frequencies or probabilities, had proceeded without adequately acknowledging that this statistical processing is operating, not only on a particular set of data, but on a set of causal assumptions about that data, often unarticulated and unanalysed.

Individualising Life Expectancy Is Necessary for Optimal Prescribing.

One possible cause of overprescribing (or insufficient deprescribing) is the failure to explicitly address the individual's life expectancy (LE). For example, if a LE estimate shows the person has six months to live, this should influence the prescribing of a medication that offers benefits only over a much longer LE. Predicting exactly the number of years a person will live is impossible, but probabilistic forecasting is possible and arguably essential, both for the selection of the optimal intervention and for meeting the 'reasonable patient' standard of information about the harms and benefits of alternative options.

Multicriteria Decision Support Would Avoid Overdiagnosis and Overtreatment.

Population-level studies confirm the existence of significant rates of overdiagnosis and overtreatment in a number of conditions, particularly those for which the screening of asymptomatic individuals is routine. The implication is that the possibility of being overdiagnosed and/or overtreated must be mentioned as a possible harm in generating informed consent and participation from the individual invited to be screened. But how should the rates of such preference-insensitive population-level phenomena be introduced into preference-sensitive individual decision making? Three possible strategies are rejected, including the currently dominant one that involves presenting the rates relevant to overdiagnosis and overtreatment as discrete pieces of information about a single criterion (typically condition-specific mortality).

Measures of Decision Aid Quality Are Preference-Sensitive and Interest-Conflicted - 2: Empirical Measures.

Empirical measures of 'decision aid quality', like normative ones, are of a formative construct and therefore embody interest-conflicted preferences in their criteria selection and weighting. The preferences of the International Patient Decision Aid Standards consortium distinguish the quality of the decision-making process and the quality of the choice that is made '(i.e.

Measures of Decision Aid Quality Are Preference-Sensitive and Interest-Conflicted - 1: Normative Measures.

The belief that following rigorous inclusive methods will eliminate bias from 'quality' measures ignores the preferences necessarily embedded in any formative instrument. These preferences almost always reflect the interests of its developers when one uses the wide definition of 'interest' appropriate in healthcare research and provision. We focus on the International Patient Decision Aid Standards instrument, a popular normative measure of decision aid quality.

People Living with Multiple Long-Term Conditions: Meeting the Challenges of Personalized Decision Making.

As with any diagnosis, the underlying purpose of a 'multimorbidity' one is to identify and establish the impact of a person's health conditions on their lives and to facilitate personalized decisions regarding proposed interventions. Clinicians routinely make decisions about the use of interventions for people with multiple long-term conditions. This is challenging because evidence to support this process currently relies on guidance on single health conditions for people without multimorbidity, typically taking fewer medications.

Evaluations of Decision Support Tools Are Preference-Sensitive and Interest-Conflicted: The Case of Deliberation Aids.

The questions 'What constitutes a good health care decision?', and, by extension, 'What constitutes good healthcare decision support?' continue to be asked. The most developed answers focus largely, often exclusively, on the quality of the 'deliberation' component as the determinant of the quality of the decision or decision aid. We argue that these answers and resulting aids reflect the preferences of healthcare professionals and aid developers and that these preferences are closely aligned with their interests.

Are Clinical Decision Support Systems Compatible with Patient-Centred Care?

Few, if any, of the Clinical Decision Support Systems developed and reported within the informatics literature incorporate patient preferences in the formal and quantitatively analytic way adopted for evidence. Preferences are assumed to be 'taken into account' by the clinician in the associated clinical encounter. Many CDSS produce management recommendations on the basis of embedded algorithms or expert rules.

Ethics in Telehealth: Comparison between Guidelines and Practice-based Experience -the Case for Learning Health Systems.

Objectives: To understand ethical issues within the tele-health domain, specifically how well established macro level telehealth guidelines map with micro level practitioner perspectives.

Methods: We developed four overarching issues to use as a starting point for developing an ethical framework for telehealth. We then reviewed telemedicine ethics guidelines elaborated by the American Medical Association (AMA), the World Medical Association (WMA), and the telehealth component of the Health Professions council of South Africa (HPCSA).

A Generic Rapid Evaluation Support Tool (GREST) for Clinical and Commissioning Decisions.

A fast and frugal generic tool can provide decision support to those making decisions about individual cases, particularly clinicians and clinical commissioners operating within the budget and time constraints of their practices. The multi-national Generic Rapid Evaluation Support Tool (GREST) is a standard preference-sensitive Multi-Criteria Decision Analysis-based tool, but innovatory insofar as an equity criterion is introduced as one of six. Equity impact reflects the number of population QALYs lost or gained in moving from Old (current intervention) to New (contemplated intervention).

A Multi-Criterial Support Tool for the Multimorbidity Decision in General Practice.

The magnitude and seriousness of the challenge posed by heterogeneous multimorbidity in most health services is now unquestioned. Equally well-acknowledged is the fact that existing guidelines essentially set out the principles of best practice in an idealised setting, concentrating on information gathering and not providing any personalisable decision support for the general practitioner aiming to share decision making with a person with multiple morbidities in the reality of routine practice. Existing decision aids have been developed largely within the single condition context and can draw on a body of robust research largely absent in the multimorbidity context.