Machine learning in Medicine

Machine Learning and Evidence-Based Medicine

While waiting for the new book by Eric Topol: Deep Medicine, let's have a look at this article, and at this summary table:

 Xavier Miserachs

Health spending in late life

Predictive modeling of U.S. health care spending in late life

In US, it is said that a quarter of public expenditure for the elderly (Medicare) is spent in the last 12 months of life. Really what happens is that the last year is only close to 10% of the whole lifetime health spending. Anyway, a new article in Science highlights commmon misunderstandings on such figure and disentangles the fundamentals.

These common interpretations of end-of-life spending flirt with a statistical fallacy: Those who endup dying are not the same as those who were sure to die. Ex post, spending could appear concentrated on the dead, simply because we spend more on sicker individuals who have higher mortality—even if we never spent money on those certain to die within the year. Empirically, this suggests using predicted mortality, rather than ex post mortality, to assess end of-life spending.

Less than 5% of spending is accounted for by individuals with predicted mortality above 50%. The simple fact that we spend more on the sick—both on those who recover and those who die—accounts for 30 to 50% of the concentration of spending on the dead. 

Crucial conclusion:

In sum, although spending on the ex post dead is very high, we find there are only a few individuals for whom, ex ante, death is near certain. Moreover, a substantial component of the concentration of spending at the end of life is mechanically driven by the fact that those who end up dying are sicker, and spending, naturally, is higher for sicker individuals. Of course, we do not— and cannot—rule out individual cases where treatment is performed on an individal for whom death is near certain. But our findings indicate that such individuals are not a meaningful share of decedents. These findings suggest that a focus on end-of life spending is not, by itself, a useful way to identify wasteful spending. Instead, researchers must focus on quality of care for very sick patients.

Good article.

PS Eight years ago I made this presentation on estimates of costs of late life. The summary in this post (in catalan)

Club des Belugas - Never think twice

Regulating alcohol marketing

Policy Approaches for Regulating Alcohol Marketing in a Global Context: A Public Health Perspective

The article says:

The range of policy options for alcohol marketing restrictions includes four main categories: no restrictions, voluntary regulation or self-regulation, partial restrictions (e.g., on content, time and place, or particular audiences), and complete bans.

Unfortunately you'll not find a clear assessment of the impact of these policies. Only anecdotical facts. Therefore, no prescriptions can be made with sounding evidence. My impression is that somebody should care about the current advertising strategies that are very far from what WHO considered as comercials some years ago.

Conceptual framework on the growth of alcohol corporations, exposure to alcohol marketing, and alcohol-related public health problems.

Enabling Patients to Stick to their Medication

Investing in medication adherence improves health outcomes and health system efficiency

OECD provides some key figures on medication adherence:

Poor adherence is estimated to contribute to nearly 200 000 premature deaths in Europe per year. Patients with chronic diseases are particularly vulnerable to poor health outcomes if they do not adhere to their medications. Mortality rates for patients with diabetes and heart disease who don’t adhere are nearly twice as high as for those who do adhere.

It is estimated to cost EUR 125 billion in Europe and USD 105 billion in the United States per year in avoidable hospitalisations, emergency care, and outpatient visits.

The three most prevalent chronic conditions – diabetes, hypertension, and hyperlipidaemia – stand out as the diseases with the highest avoidable costs, for
which every extra USD spent on medications for patients who do adhere can generate between USD 3 to 13 in savings on avoidable emergency department visits and inpatient hospitalisations alone.

I'm dubious about the exact figures, anyway if you imagine that it is half ow what the say it would be a lot. Systematic reviews say that non-adherence is 15%. This is a hot topic and the ways to tackle are known.

Acknowledge: Medication non-adherence harms health and increases healthcare costs. The first step for the relevant stakeholders is to acknowledge that this problem exists and to adequately recognise its main drivers. Medication adherence needs to move up the policy agenda in order to raise awareness of the problem and mobilise adequate responses.

Inform: Few countries systematically monitor adherence. Routine adherence measures as well as adherence-related quality and performance indicators should be encouraged in order to improve health system effectiveness and efficiency.

Incentivise: Changes in financial incentives for providers and patients are essential. Shifting to payment systems that reward providers for the quality of patient outcomes would provide strong motivation to improve adherence. Medication adherence could also be considered as a measure for performance based contracts with pharmaceutical companies. Where patients’ co-payments for chronic medications exist, their reduction or removal should be considered to reduce financial barriers.

Steer and Support: The adherence process begins with a patient and a prescribing clinician and a dispensing pharmacist who should all be supported by other health system stakeholders. Payers/system designers can develop IT systems that facilitate optimal prescribing and patient-clinician communication or renewing prescriptions by patients. Educators have a role in equipping health professionals with skills in managing adherence such as person centred communication, shared decision-making, and socio-cultural competencies.

Clinical utility of genomic sequencing

The Path to Routine Genomic Screening in Health Care

Now that whole genome sequencing is knocking at the door of the clinician, it is the time to ask for clinical utility. The understanding of how such information will change diagnostic and therapy is paramount. There is still no need for cost-effectiveness, clinical utility comes first.
And the editorial at Annals explains exactly this issue, highly recommended:

There should be little doubt that individually tailored health care management plans based on DNA analysis are coming, but the timing of their introduction into routine clinical care is contingent on further demonstrations of clinical utility and proven implementation models.

My impression: let's wait for epigenetic biomarkers, beyond whole genome sequencing that provides less than 100 actionable genes out of 20.000. Though,

 The fact that only a small percentage of people would benefit from GS today is counterbalanced by growing evidence that the benefit could be significant, and perhaps even life saving

 

Pepe Castellanos at Barnadas Gallery