Difference between revisions of "Healthcare Data Monetization"

Revision as of 09:00, 11 March 2021

Overview

The definition of monetize is “to change into money.” ^[1] Today, data is constantly being collected from us, and many companies and organizations are capitalizing on this data's value. This can make some people uncomfortable to know that the data being collected on them from social media or online shopping is being used to make a company money; as a result, people may choose to refrain from such activities. However, in the age of digitalization, it is harder and harder to avoid. Important things like banking and health records are being moved to electronic, and for most people, being part of the Big Data for these things is unavoidable. This data is more sensitive and private than friends on Facebook or favorite online store, and as such, companies pay large amounts to store and protect this data. Health data monetization is leveraging the huge amount of health data health system already have, store, and protect to increase their revenue. ^[2]

History

History of Electronic Health Data

Health records were poorly kept up until about the 19th century; however, by the end of the 19th century, health records included diagnosis, family history, notes, instructions, clinical tests, and everyone one would expect to see in health records today ^[3]. Because these records were taken by hand, any different doctor or hospital would only have the records that were accessible, and so records were often discontinuous from place to place. Paper records held through to the mid to late 20th century; in about the 1970s and 1980s software development made it possible for patient data to be inputted electronically, indexed and accessed across all departments of a health systems ^[4]. Since then, there has been a huge push for healthcare organizations to utilize Electronic Health Records (EHR), and as of 2017, about 86% of physicians have adopted EHR. ^[5]

The amount of new health data being generated every year with the amount of new data in 2020 globally being 2,314 exabytes, where 1 exabyte is equivalent to 1 billion gigabytes ^[6]. It is projected that for the United States, expenditures on EHR will total around $19.9 billion in 2024 ^[7].

History of Data Monetization

be something useful that could be done with it to make them money, lower costs, or overall just increase revenue. What really kicked off data monetization was digital advertising; data on consumes was constantly being collected to help pinpoint consumer behavior and personalize the marketing ^[8]. Companies are constantly using data collected to help improve the experience of the consumer with the hopes that its services/products will continue to be utilized. Look at Spotify, for example, who customizes playlists based on recent listening activity; this is an example of data monetization because it is using data collected from the listener to improve the experience, which may make the listener less likely to use competitor streaming services or more likely to pay for Spotify Premium. A different way we see data monetization is the direct selling of data to a third party, oftentimes without the knowledge or consent of the user.

Methods to Monetize

Indirect

Indirect implies that the data monetization comes from leveraging the data to increase revenues, never leaving the organization ^[9]. By analyzing the data that is being collected on patients, more strategic, calculated decisions can be made. For health systems, this means that clinical data can be used to help innovate care delivery processes; additionally, patterns in demographic, health behaviors, and health data can used to improve health outcomes of patients. ^[10]. Preventative care tends to be cheaper for health organization than a trip to the emergency room, and so if on the large scale, patient health outcomes are improved with the help of leveraging data, health systems can save money ^[11].

Direct

Direct implies the selling of data for a profit ^[9] . Buyers of this data could be suppliers of the clinical setting or pharmaceutical companies who are interested in improving marketing strategies or assessing clinical need ^[12]. This is what traditionally one may think of when monetizing data comes to mind. As previously mentioned, this EHR data holds sensitive, private information, and so before the data ever leaves the organization, it is made anonymous.

President and CEO of Trinity Health, Mike Slubowski, on Truveta's capabilities.

Current Examples of Health Data Monetization

Truveta, Inc.

Truveta is a startup made up of a pool of 14 of the largest health systems in the United States that can come together to pool their anonymous health data; the goal of Truveta is to “leverage patient data to improve patient care, address health inequity, accelerate the development of treatments and reduce the time to make a diagnosis” ^[13]. While this may seem indirect since no data is directly being sold, it is direct monetization in that the de-identified patient information is leaving the organization. This specific startup is cofounded by providers, with those health systems participating benefiting from the data analysis and information found. They claim that they will help advance healthcare by: improving patient care, accelerating treatment during pandemics, expediting the diagnostic odyssey, advance health equity, and empower patients on their journey ^[14]. This aligns with the mission of health systems to achieve better health, but also can save these health systems millions of dollars down the line.

VITAL Platform

VITAL is a platform created by Highmark Health with the goal of leveraging claims and clinical data to “generate evidence that can lead to reduced medical spend, improved quality outcomes and enhanced patient access to new technologies” ^[15]. Started in 2015, VITAL allowed Highmark to try out and analyze the effect of new technologies that saved money and improved health outcomes; at this point, this was indirect monetization, as it was within the organization. However, since this time, VITAL has considered commercializing, which would be direct, since the data would be being sold outside the organization.

Ethical Considerations

HIPAA

HIPAA stands for the Health Insurance Portability and Accountability Act of 1996. It is a “federal law that required the creation of national standards to protect sensitive patient health information from being disclosed without the patient’s consent or knowledge.” When talking about sharing patient data, it is imperative that HIPAA be considered to avoid legal repercussions. It is legal to share protected health information (PHI), as long as confidentiality is maintained; oftentimes this means any identifying information is omitted ^[16]. It is this de-identifying that allows for health systems to monetize their data directly. One concern that has been brought up regarding this privacy that American’s are afforded with regards to their health data is that when given to a third party or merged and compared to other data sets, identification of patients may be easy.

Whose Data is it?

The default for a provider to record health data is to do so electronically. Once your provider inputs your health data from your visit, you may not truly know what is being done with your data. While at some point during your intake in a clinical setting, medical release or consent forms are signed, there are some concerns about whether this truly counts as informed consent. Many people may lack the health literacy to understand what the forms are entailing; additionally, the specifics of where your data is going are most of the time not outlined, so is it really considered “informed”?. Some may be comfortable with indirect monetization, but not direct or nothing at all; the doctor or provider is not an IT expert, and so one may experience the roadblock of struggling to actually get in contact with someone who can help you better understand what is being done with your data.

Inclusion

Another think that must be considered is the representation of the data. Certainty health data has the power to make life saving changes, but will it only benefit those whose identities are most represented in the data? In the search of data justice, it must be considered that certain populations may not have as much access to a clinical setting, and therefore are not represented; this could lead to perpetuating inequities that already exist in health ^[17].

References

1. ↑ Cambridge Dictionary Defintion- Monetize
2. ↑ A New Era in Healthcare Data Monetization
3. ↑ From Papyrus to the Electronic Tablet: A Brief History of the Clinical Medical Record with Lessons for the Digital Age
4. ↑ Health Information Management History: Past, Present, and Future
5. ↑ Health IT Dashboard
6. ↑ Statista: Healthcare Data Generated
7. ↑ Hospital EHR Spending Projected to Reach $9.9B by 2024
8. ↑ The story of data: How did we get here?
9. ↑ ^{9.0 9.1} A New Era in Healthcare Data Monetization
10. ↑ Truveta, formed with big-name health systems, aims for AI-powered data advances
11. ↑ The Impact of Personalized Preventative Health Care Quality, Utilization, and Expenditured
12. ↑ How Third Parties Harvest Health Data from Providers, Payers and Pharmacies
13. ↑ Unlocking Value in Health Data
14. ↑ Why Truveta
15. ↑ Vital: Our Vision for Transformation
16. ↑ Health Insurance Portability and Accountability Act of 1996
17. ↑ Exploring Data Justice: Conceptions, Applications and Directions