- Context of unmanaged liabilities
- Enforceable obligations
- Obligation to not negate ME/CFS legal status
- Obligation to procure ME/CFS medical education
- Obligation to not mislead or evade diagnosis and to provide sufficient detail (FND, MUS, PPS, ‘dysregulation model’ and Long Covid examples)
- Obligation to not abuse power and authority
- Obligation to recognise ME/CFS patient housebound or carer status
- Tests of lawfulness
- Risks – compliance and operational
- Unlawful clinical judgement (examples)
- Expertise risk and reputational risk – medical and legal
- Illusion of legal authority vs medical law enforcement
- Knowledge-gap risk and audit trails (examples plus research-market inefficiencies)
- Freedom of Information Act risks – flawed clinical judgement, discrimination and education refusal
- Third party risk from preceding unlawful clinical judgement
- Liability, malpractice and indemnification
- Irrelevance of official edicts and officialised redistribution of liabilities to frontline balance sheets (vaccination and NICE guideline examples)
- Compromised indemnification, insurance cover nullification and liability for lost income
- Evaluating duties of care and unmanaged risk exposures
- Risk mitigation
- Version history
These compliance documents are live pre-released drafts that are specifically not structured for scientific audiences. Specific scientific referencing can be provided in consulting contexts, not limited to practice management, claims management, underwriting or litigation support for professionals or organisations.
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A journalistic summary of these documents for lay audiences will soon be published.
Identically, models cannot excuse discrimination that is substantiated in law. The simple clinical judgement lawfulness tests above apply to the lawfulness of model driven decision-making. Replacing the word “clinician” with “model” in the tests arrives at identical conclusions: a priori assumption of ineligibility/insufficient eligibility of ME/CFS patient cohorts or individuals is unlawful.
Identically, models cannot excuse discrimination that is substantiated in law. Model-driven scoring replicates, scales and accelerates decision-making. It does not replace the clinician, particularly where reasonable clinical limitations are highlighted
The purpose of model driven scoring in any medical context is to replicate, scale and accelerate decision-making. It does not replace the clinician – it is applied by medical practice.
Where a model is known not to account for either medical, policy or legal requirements, its application must be selective to be lawful. Where model limitations have been communicated, the tenability of delaying or obfuscating terminal obligation/liability is negated further.
Example: Q Model covid risk assessment tool and Group 6 vaccination scheme eligibility
As demonstrated regarding tests of clinical judgement unlawfulness, medical requirements dictated by Joint Committee on Vaccination and Immunisation (JCVI) policy cannot be applied in a way that substantiates incidents of discrimination in law or breaches duties of care.
As a specifically relevant example, the Q Model tool made available to UK primary care specifically predicts probability of death and hospitalisation. It does not account for exacerbation of existing illness and thus does not account for:
- the Green Book and JCVI requirement of clinical judgement
- the consensus ME/CFS literature specificities outlined above regarding the impact of viral infection, the unusual severity of ME/CFS or its prevalence
- the requirement that clinical judgement avoids discrimination in order to be lawful
- the requirement that clinical judgement accounts for duties of care in order to be lawful
These tests are related to the tests of clinical judgement lawfulness: