Claudius Walter Lazarus — dHealth Innovation Hub, India.
“For it is in giving that we receive” St Francis of Assisi
When was the last time someone connected the word liquidity to patient medical data?
The concept of monetizing data is not new. We are often inundated with offers in our inbox with emails from companies offering consolidated business data for a price. Back in the 90s, it was commonplace to purchase trade data consolidated on a CD. Before that, we had data available in printed format, some of them running several hundred pages enclosed in thick, voluminous editions. The data was anything from directories of business establishments in a city with the contact numbers and names of key executives or quite simply lists of Orthopedic surgeons in a country. All kinds of data and lists were available for sale. With the rise of the internet, the method and form of supplying such data changed, offers of email lists for sale for every conceivable requirement bombarded our inboxes. There are several instances where company executives have paid off gullible insiders from their competitors to get a hold of confidential business data. Thus, paying for data legitimately or otherwise, is not new.
However, in ordinary parlance, we do not associate monetary value to such mundane and redundant things like patient medical data. Patient medical data, as we know, is a boring set of lines of text with incomprehensible medical terms and observations. Add to that the fact that a person needs to have some medical knowledge to be able to comprehend test reports, images, and inferences. Unless conditions require interventions and treatments, the patient data is confined to a file folder or a computer drive only to remain there until the next round of visits.
Medical data monetization
Patient medical data monetization is a new phenomenon that advocates providing a monetary value to each patient’s medical data. The healthcare industry does have the concept of paying for anonymized patient data; however, the patient is never the benefactor. The parties who benefit from monetizing this data would rather include data providers, hospitals, doctors, or data aggregators.
Value in patient medical data
During the visit of a senior European doctor to India, the head of the cardiology department at his hospital, the doctor was surprised to witness the efficacy of the clinical diagnosis of a young Indian doctor on a patient they both happened to examine at a Government hospital.
The young doctor was doing his residency in the hospital’s OPD section. Events got more interesting when they came to the next patient in the ward. The Senior doctor from Europe, after examining the patient, threw up a challenge to the young Indian doctor. He nudged the young Indian doctor to do his own examination of the patient and note down the findings.
The two doctors detailed their analysis of the patient examination. Both agreed that an X-ray and few blood tests were required. They then decided to meet the next day to verify and confirm the findings.
The following day, as agreed, they met at the patient’s bedside. The images and reports had arrived. The young Indian doctor, being courteous, requested the senior doctor to go first. The senior doctor agreed and looked at the reports and the images. As he detailed his glare at the report, he veered off glancing at the Indian doctor with a smile. He was in admiration. The Indian doctor, with little or no aides, only on the basis of a physical examination could pinpoint the patient’s exact medical condition. The European doctor also got it right, but only to a small extent. Given the difference in age and experience this was an eye opener to the doctor from Europe. What does this incident have to do with patient data?
Well, the Indian doctor was working day and night with all kinds of patients in an Indian government hospital wherein, the challenges of working are immense, the conditions overwhelming with an ill equipped facility. Add to these hundreds of patients make a beeline during the OPD days to get the free treatment. The scene is not for the weak-hearted.
It would be detrimental to think that there is a possibility of something positive in such a scenario. In fact, this seemingly hopeless situation exposes the Indian doctor to a myriad of cases; due to the sheer numbers, the data generated is enormous. The doctors examine, make notes, write prescriptions and repeat. Many patients make multiple visits with reports, treatment feedback, etc. The comings and goings, the massive patient data generated are entrenched in the doctor’s memory. In time, they are able to develop patterns and make inferences only by physical examination.
Now imagine if all this data is recorded systematically and made available to any doctor seeking them. All learnings from thousands of patients can now be compressed and made accessible to the universe.
Doctors who want to study cases before making a diagnosis will have at their disposal a rich pool of data that they can peruse to gain valuable insights. However, all this is possible only if data is made available.
The starting point of all this is some unknown patient in a town in India who made it through many difficulties and struggled to reach the hospital to seek treatment. Once the data is shared, unknowingly, the patient has made his medical data useful to someone else in the universe.
The patient data can now be made available on demand. The doctors who get access to this data benefit from their learning. Patients will benefit from enhanced knowledge of the doctors and more precise treatments. Pharma companies can focus their research on developing accurate medicines. In fact in time there are societal benefits that accrue.
What reward does the patient, based on whose medical data all these benefits accrued, get in return?
The answer is nothing.
The patient in fact in most cases is unaware that he has contributed to the medical universe.
An unknown patient from a town in India goes through pain, suffering, and many struggles to get his condition treated. His data benefits several people to varying degrees. It is only fair then that this unknown patient from a town in India gets some recognition, respect, acknowledgment, some token reward?
Is it not fair?
India is just a metaphor for any country, the country could be anywhere on this planet.
The idea of the patient being unknown, and the data coming from a populous country like India is not to be misconstrued as being condescending or biased. Rich countries with a much smaller population can also generate patient data. The idea that patient data monetization will benefit the unknown patient from a developing country is also not to be generalized. A patient from a developed country will also have the same expectation of getting respect, recognition, and some token for the data they share. Only in this case the awareness about data and privacy laws are much higher; as such, the expectations can be put into a proper perspective. In the case of patients from developing countries, the awareness regarding data protection and privacy issues is non-existent or very low. Thus, it becomes our duty to educate innocent and unsuspecting patients and give them their due.
Patient data monetization touches the source, the origin of the data. If by providing liquidity to the patient’s medical data, the universe, in a way, sends a Thank You note to the patient, and if the patient gives his nod, then the whole ecosystem seems to get legitimized. The patient smiles at the gesture, and the medical universe feels the positive ripple effect. This is beautiful and thus should be a priority. This frees the researchers, the doctors, and the other patients from feeling any perceived injustice done to anyone in this chain, and in this case, it’s only the patient.
The dHealth foundation has this act of giving back to the patients for their data at its core. Right from its inception, the foundation has championed the cause of patient data monetization. With the motto of “in giving that we truly receive, “ the dHealth foundation created the blockchain network optimized for Health and Wellness applications. dHealth has its native token with which to reward patients. You can read more about dHealth at www.dhealth.com.
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dHealth is a layer-1 protocol built for the healthcare industry. We’re tokenising the access and exchange of valuable health data by bridging the gap between corporations in the Web 2 world with a decentralised Medverse in the Web 3 world.
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