Have you ever clicked ‘I agree’ to share information about yourself on a health app on your smartphone? Wondered if the results of new therapy reported on a patient community website were accurate? Considered altering a medical device to better meet your own needs, but had doubts about how the changes might affect its function?
While these kinds of decisions are increasingly routine, there is no clear path for getting information on health-related devices, advice on what data to collect, how to evaluate medical information found online, or concerns one might have around data sharing on patient platforms.
It’s not only patients who are facing these questions in the age of big data in medicine. Clinicians are also increasingly confronted with diverse forms of molecular, genetic, lifestyle, and digital data, and often the quality, meaning, and actionability of this data is unclear.
The difficulties of interpreting unstructured data, such as symptom logs recorded on personal devices, add another layer of complexity for clinicians trying to decide which course of action would best meet their duty of beneficence and enable the best possible care for patients.
Whether generated in clinical settings, or through direct-to-consumer companies, online platforms, apps, and wearables, more and more domains of our everyday lives are being datafied. This means that heart beats, steps taken, calories eaten, blood values, and even our moods, movements, and social activities are rendered usable for healthcare purposes, as well as commercial interests. These developments hold the promise of better, more personalized healthcare. Yet, they also bring about new challenges: besides the ethical challenges that such increasingly detailed and comprehensive monitoring raises, at a very practical level, there is the question of how the newly available data should (or should not!) be used in healthcare.
Some see artificial intelligence (AI) as a response to this challenge, promising a future in which greater computational power and machine learning will aid, or even automate, key aspects of decision making in healthcare. Yet, human intelligence will continue to be needed. Moreover, diagnostic and screening technologies can increasingly be found in people´s homes and on their personal devices, raising questions over the quality and meaning of the data generated. Some people feel that doctors should do this job. There have been numerous calls for more training of doctors in genomics, data science, as well as on the ethical concerns surrounding the communication of genetic information, and the risks of online or commercial sources of health information. In our view, it is unfair and unfeasible to ask this from doctors and other healthcare professionals. Many healthcare professionals are already overworked and under considerable stress. At present, few in the health care team are well-positioned, or have enough time, to offer discerning interpretations of diverse, unstructured data to inform decision-making in a standard clinical encounter.
In light of these practical, clinical, and ethical challenges, the time has come to consider new means to support both physicians and patients in navigating life in the age of big data.
In a recent article in Academic Medicine, we propose that we need a new medical specialty of Health Information Counseling (HIC). Trained in dedicated postgraduate programs, and working as a specialist on physician referral, a HIC would have a broad knowledge of various kinds of health data and data quality evaluation techniques, as well as analytic skills in statistics and data interpretation. She or he would have been trained in interpersonal communication, health management, insurance systems, and medico-legal aspects of data privacy, and would know enough about clinical medicine to advise on the relevance of any kind of data for prevention, diagnosis, and treatment. With time and applied experience, practicing HICs would become specialists in a particular domain, and know when to refer to a specialist on a matter beyond his or her expertise.
One of the strengths of the HICs would be their ability to translate the complex language of data into intelligible and actionable information for both patients and physicians. Acting akin to an expert consultation in a clinical specialty, they would offer their professional assessment regarding all issues of patient data interpretation to treating physicians, and oversee many patients as part of their caseload. The addition of the HIC to the panel of health professionals could also contribute to the prevention of overuse in medicine, as well as the reduction of mistakes. They can do this by assisting doctors in staying fully informed about novel tests, research studies, and data programs – or deciding that in some cases the best thing is not to get another test, or not collect more data. The creation of a cadre of skilled HICs would advance the clinical applicability of big data in an ethical, and equitable, fashion.
The meaningful integration of data science into the clinic is quickly turning into one of the defining challenges of 21st-century medicine. Leaving the problem of how to making health data actionable in the clinic unaddressed is not an option. Neither is simply adding the meta-skills of managing and evaluating health information to the existing tasks of physicians.
We welcome your thoughts on the profession of HIC, and other ways to take on these tasks moving forward!