Hospital margins are down – is selling your health data a solution

Hospital margins are down – is selling your health data a solution

A framework allowing a more sensible approach to health data collection

In our previous blog we outlined the pressure on hospital margins and the entire hospital business model as a direct result of Covid-19. One solution is the sale by hospitals of your health data to research organisations, both commercial and not-for profit and insurers.

There is enough personal medical data on file to think of this as a ‘Big Data’ opportunity. The sale of personal healthcare information collected by hospitals, certainly in the US and UK, is entirely legal if the data is anonymised.

The buyers are R&D drugs and devices companies interested primarily in the medical discovery and innovation in exchange for margin in one form or another, non-profits looking for research mandates and insurers looking at utilisation management and managed care to cost control and improve service delivery.

However, it is increasingly clear that this medical data is not as anonymised as once believed. The data can reasonably easily be tied back to individual patients, which is eroding patient trust, which in turn has potentially pernicious implications.

The negative implications are initially for patients via drugs companies and insurers but finally for the entire healthcare system, which depends on broad patient confidence to be effective i.e. keep populations healthy and productive.

“The temptation has never been greater to take shortcuts around health data protections to vie for huge federal grants or to develop and monetise intellectual property. That is why we have adopted our approach, and we hope it will serve as an example for others.”

Marschall Runge M.D, Ph.D, Dean and Executive Vice President for Medical Affairs, Michigan Medicine – University of Michigan

Much like policing, a national health policy only works by consent in a democracy. The erosion of user trust in health systems has considerable economic implications related to productivity and business confidence and so in the end, everyone’s wealth, safety and standard of living.

In the US, The University of Michigan (U-M) has been looking at the reputational and practical risks associated with the re-sale of patient data collected by hospitals (as well as businesses involved in selling ancestry DNA tests, where the real value is in the database of DNA sets collected by ancestry companies).

The University set out a new data collection framework for the healthcare sector and published this framework recently in the New England Journal of Medicine.  The framework is designed to enable better data collection and better processing, whilst respecting both patient privacy and commercial regulations. The hoped for outcome is maintaining patient confidence in hospital and other medical services abilities to anonymise, collect and store data within the healthcare system.

The Michigan data collection framework should also have a role in rebuilding confidence amongst patients in the insurer driven ‘managed care’ arena in the US healthcare system (and further afield).

‘Managed care’ is a set of processes and techniques used to reduce the cost (whilst maintaining the quality) of commercial healthcare. In essence, it means less time spent in hospitals and more time spent at home during recovery with additional emphasis on preventative medicine, i.e. fewer people ending up in hospital in the first place.

‘Managed care’ was introduced in the US in the 1980s and is driven by health insurers’ need to curb the spiralling cost of claims against policies. Health insurers’ products only work if enough people can afford to pay the premiums that cover the percentage and cost of claims, whilst leaving a margin for the insurance companies and so investors.

If healthcare premiums rise aggressively, whilst the number of people that can afford to pay the insurance premiums falls, it creates a downward revenue spiral that destroys the insurers business model.

Insurance is a key mechanism underpinning planning and capital management in developed or developing economies, or put another way, insurance frees up the movement of vast amounts of investment capital, which is necessary for GDP growth and human problem solving.

The ‘Managed care’ principle now extends across many countries’ healthcare systems and is seen as a set of protocols, especially the preventative element, that will be essential in the struggle to maintain and afford national health systems in developed economies with unhelpful demographics i.e. more old people than young.

‘Managed care’ is also, in some part, the response to so-called ‘utilisation’ data, which is the record of patient use of various medical services, procedures and protocols.

Because health insurers are driven to constantly cut costs, there is legitimate concern that this leads to rejection by insurers of recommended patient care protocols that is not always in the interest of the patient.

Nevertheless, insurers need a mechanism to manage and contain their risks with respect to patient care and the ever ambitious recommendations by medical professionals, otherwise the entire edifice will collapse.

Big data from healthcare that can be tied to individual medical records is very attractive if cost cutting is your goal in insurance. If individuals know their data can be tied back to them individually they may conclude that it is inevitable that insurers will use non-transparent and attritional techniques to reduce the approvals of, and pay-outs for, claims. It is not a question of evidence but of perception.

Even without abundant publicly accessible evidence of unsatisfactory commercial behaviour by insurers, patients may be justified in their cynicism – it is not a coincidence that insurers are no longer allowed to regulate themselves in the UK and other countries.

Health insurers may well like nothing better than to have big data pools from hospitals and General Practitioner businesses that can be tied back to individual patients. For the sake of their own business models, they should be wary of getting what they wish for.

The profit motive means that insurers will be driven to exclude as many potentially unprofitable individuals as they possibly can or to refuse to pay for innovative services that are expensive and used by only a very few patients.

The sale of data held in patient records and DNA sets was already happening before the current health crisis. As long as patients’ names and identities remain anonymous and regulations permit this way of collecting and selling data, then it will be for the greater good. However, if the data is, in practice, easy to tie back to individual patients it will create acute market information asymmetry, which in the end causes markets to fail.

The current health crisis has not served healthcare centres and hospitals well, some may go bankrupt, others will be forced to consolidate. Their business models will have to change and they need capital to do this.

The hospital groups for now are not attractive to investors in the traditional sense.  A data agreement underpinned by the Michigan University framework or a similar framework could enhance their chances of independence and survival.

Michigan’s big data framework for healthcare should therefore be welcomed by all parties. Truly anonymous healthcare data has the potential to generate great value for hospitals, research companies, insurers and the general population.

Processing truly anonymised healthcare data could improve ‘managed care’, ‘utilisation management’, drug development, medical device innovation, the hospital business model and user trust. The value generation could easily run to a trillion dollars over the mid-term.