With the rapid and ubiquitous acceptance of new technologies, algorithms will be used to estimate new measures of mental state and behavior based on digital data. The algorithms will analyze data collected from sensors in smartphones and wearable technology, and data collected from Internet and smartphone usage and activities. In the future, new medical measures that assist with the screening, diagnosis, and monitoring of psychiatric disorders will be available despite unresolved reliability, usability, and privacy issues. At the same time, similar non-medical commercial measures of mental state are being developed primarily for targeted advertising. There are societal and ethical implications related to the use of these measures of mental state and behavior for both medical and non-medical purposes.

The digital revolution in medicine not only offers exciting new directions for the treatment of mental illness, but also presents challenges to patient privacy and security. Changes in medicine are part of the complex digital economy based on creating value from analysis of behavioral data acquired by the tracking of daily digital activities. Without an understanding of the digital economy, recommending the use of technology to patients with mental illness can inadvertently lead to harm. Behavioral data are sold in the secondary data market, combined with other data from many sources, and used in algorithms that automatically classify people. These classifications are used in commerce and government, may be discriminatory, and result in non-medical harm to patients with mental illness. There is also potential for medical harm related to poor quality online information, self-diagnosis and self-treatment, passive monitoring, and the use of unvalidated smartphone apps. The goal of this paper is to increase awareness and foster discussion of the new ethical issues. To maximize the potential of technology to help patients with mental illness, physicians need education about the digital economy, and patients need help understanding the appropriate use and limitations of online websites and smartphone apps.

Increasing quantities of medical and health data are being created outside of HIPAA protection, primarily by patients. Data sources are varied, including the use of credit cards for physician visit and medication co-pays, Internet searches, email content, social media, support groups, and mobile health apps. Most medical and health data not covered by HIPAA are controlled by third party data brokers and Internet companies. These companies combine this data with a wide range of personal information about consumer daily activities, transactions, movements, and demographics. The combined data are used for predictive profiling of individual health status, and often sold for advertising and other purposes. The rapid expansion of medical and health data outside of HIPAA protection is encroaching on privacy and the doctor-patient relationship, and is of particular concern for psychiatry. Detailed discussion of the appropriate handling of this medical and health data is needed by individuals with a wide variety of expertise.

There has been increasing interest in the use of smartphone applications (apps) and other consumer technology in mental health care for a number of years. However, the vision of data from apps seamlessly returned to, and integrated in, the electronic medical record (EMR) to assist both psychiatrists and patients has not been widely achieved, due in part to complex issues involved in the use of smartphone and other consumer technology in psychiatry. These issues include consumer technology usage, clinical utility, commercialization, and evolving consumer technology. Technological, legal and commercial issues, as well as medical issues, will determine the role of consumer technology in psychiatry. Recommendations for a more productive direction for the use of consumer technology in psychiatry are provided.

Big data are coming to the study of bipolar disorder and all of psychiatry. Data are coming from providers and payers (including EMR, imaging, insurance claims and pharmacy data), from omics (genomic, proteomic, and metabolomic data), and from patients and non-providers (data from smart phone and Internet activities, sensors and monitoring tools). Analysis of the big data will provide unprecedented opportunities for exploration, descriptive observation, hypothesis generation, and prediction, and the results of big data studies will be incorporated into clinical practice. Technical challenges remain in the quality, analysis and management of big data. This paper discusses some of the fundamental opportunities and challenges of big data for psychiatry.