Consumer-generated data increasingly is being used to forecast health outcomes, risks and healthcare utilization. In the absence of ethical standards to guide consumer-generated data use in healthcare analytics, there may be harms to patient privacy and autonomy, disruption of trust in the patient-provider relationship, or marginalization of individuals or populations.
Healthcare organizations and their vendors increasingly are using consumer and lifestyle data. This consumer and lifestyle data, referred to as consumer-generated data, includes data such as an individual’s purchase transactions, social media presence, internet searches, wearables data, etc.
While consumers may be aware of organizations using their consumer-generated data for marketing purposes, they are largely unaware that organizations are now using consumer-generated data alone, or integrated with clinical data, to make inferences regarding their health.
Consumer data predicting health risks
What they buy, what they post on Twitter or how many hours their wearable said they slept now are being used to predict their health risks, outcomes, costs, utilization or to develop targeted care interventions, said Dr. Eldesia Granger, group leader, clinical quality and informatics, at The MITRE Corporation.
“We recognize that consumer-generated data may be used in productive ways that ultimately benefit consumers’ health; it may provide critical insight into how social determinant factors affect health, facilitate a more personalized experience, and allow for more efficient use of finite healthcare resources,” she explained.
"The values, principles and guidelines are intended to reduce the likelihood of ethically questionable decisions and actions that can be rationalized away based on an organization’s intention to improve the health of individuals and populations."
Dr. Eldesia Granger, The MITRE Corporation
However, there also are concerns regarding the use of this data. Consumers often are unaware that consumer-generated data is being used for healthcare purposes, which raises privacy and transparency concerns, and there are questions about the accuracy of this data, she said.
“Consumer-generated data use also has the potential to exacerbate health inequities if organizations do not consider the structural factors – for example, public institutions and policies – influencing the consumer-generated data,” Granger said. “There is real concern that use of consumer-generated data may result in limited access to or denial of services based on perceptions of personal responsibility.”
Who to spend resources on?
In fact, what piqued Granger’s interest in this topic was a comment in an article a few years ago that remarked that healthcare organizations could use consumer-generated data to determine which patients to spend resources on based on their health behaviors and which not to waste their time or resources on.
“It is critical that organizations seek to understand the ‘why’ behind the inferences or risk scores reflected by the data,” she said. “Otherwise you run the risk that certain individuals or groups may be marginalized, limiting access to the necessary resources they need to achieve their greatest health. Organizations may have benevolent intentions, but consumers can potentially be harmed if inferences about their health are inaccurate or if consumer-generated data is used in an inappropriate or unethical manner.”
To maintain and foster trust within the healthcare system, it is critical that consumers understand who is using their data, what type of data is being used, how it is being used, and most important have an opportunity to make decisions regarding the use of that data in the context of their health, she added.
For healthcare organizations, there is opportunity and risk with the use of consumer-generated data in healthcare. At present, healthcare organizations and their vendors operate under a limited regulatory framework that provides minimal guidance or guardrails with regard to the use of consumer-generated data.
The ethical use of consumer data
“MITRE’s ethical framework addresses this gap by providing guidance to organizations regarding policies and governance processes to promote the ethical use of consumer-generated data in healthcare, as well as discusses ethical considerations, questions and constraints to guide consumer-generated data use,” Granger explained.
“In light of the increasing use of machine learning in healthcare, we also make some recommendations to facilitate the ethical use of machine learning for analysis of consumer-generated data and other data.”
The MITRE framework essentially serves as a safety net for healthcare organizations using consumer-generated data for health purposes to help them use it in a more critical and objective manner to prevent reputational harm and actively preserve and foster consumer trust, she added.
The MITRE framework provides values, principles and user-specific, actionable guidelines to support decision-making surrounding the use of consumer-generated data in healthcare, she continued.
“These values, principles and guidelines are not only informed by literature from philosophy, health, data science and technology, but were developed with the assistance of an interdisciplinary team from a variety of disciplines including medicine, public health, law, data science, ethics, policy, actuarial science, privacy and health communication,” she said.
“The values, principles and guidelines are intended to reduce the likelihood of ethically questionable decisions and actions that can be rationalized away based on an organization’s intention to improve the health of individuals and populations.”
This is an issue that touches everyone because health is universal, and everyone is generating consumer-generated data, she concluded.
Dr. Eldesia Granger will speaking more on this subject during her HIMSS20 session, “Ethical Framework – Use of Consumer Generated Data.” It’s scheduled for Thursday, March 12, from 4-5 p.m. in room W230A.
Email the writer: [email protected]
Healthcare IT News is a HIMSS Media publication.
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