Patient Data Concerns Within Health Research

By Lizza Miller

Many believe big data will become the single greatest source of power in the 21st century, with health research and care being its greatest beneficiary. Recent shifts in focus towards initiatives such as precision medicine, advanced patient registries, and patient generated health information (PGHI) reinforce these beliefs. Even technology heavy hitters, such as Apple and Google are using their expertise in building engaging products and aggregating data, in attempts to be a part of the movement.

Researchers are salivating at the mouth with anticipation of what all of this could mean for advancing cures for chronic diseases and cancers. However, being a relatively new territory, there are a lot of questions and concerns that must be addressed before these efforts can be truly effective. After participating in the Twitter chat hosted by PCORI and Health Affairs, three major issues concerning the use of patient data within health research arose:

• How do we engage the right patients consistently?
• How do we assure them that their data will remain private and secure?
• How do we aggregate all of this data into one comprehensive database (i.e. EHR)?

Gathering Patient Data

To reap the potential benefits of big data, small data must first be acquired. Of course, this is easier said than done. With only a small percentage of adult patients using digital health tools and almost half of all hospitals not having a patient engagement solution, there still exists a need to figure out how to effectively engage outside of the doctor’s office. Furthermore, proper motivation needs to be given to get the right patients to consistently contribute their information. Educating patients on the tools available, as well as what their contribution means to the health of others, may be the first step. Next would be to provide easy to use applications that make inputting data and giving personalized feedback effortless. If patients are to be actual partners, data flow should be bi-directional – going to both the researcher and the patient.

Patient Privacy and Data Security

The biggest concern in regards to PGHI is privacy and security (the latest hacks of hospital databases do not suppress these worries). Although millions of people use apps to track and manage their personal health, a reluctance remains when it comes to sharing this data due to concerns as to where it may end up. People need to be assured that their rights to their own health data are protected. However, standards and regulations are still not in place to protect data shared with an app in the same way information shared with a doctor is, being that sharing PGHI is a relatively new concept. The experience of early adopters will provide policymakers with a starting point as to what those should be. For now, trust and transparency are key to continuing reception.


We can gather and protect data until our hearts’ content but if the data is unable to be easily accessed and analyzed, why bother? That is why interoperability between health information technologies, specifically EHRs, is essential to such efforts. Leaders in healthcare innovation, such as Intermountain Healthcare, are pushing for the development of a mobile application-based ecosystem as a solution to the lack of interoperability. These apps will simplify integrating with and interacting to store and retrieve data from EHRs. Accumulating PGHI from multiple sources into one database would, theoretically, become automatic and the analysis of such information easier.


The benefits of big data within healthcare and research are undisputed, from accelerating research to influencing individual treatment programs. A lot of details need to be fleshed out before these benefits can be fully experienced. Once patients are engaged, their data is secure, and it is easily accessible and transferable, only then can it be comprehensive enough to have a major impact.

Patient Data Concerns Within Health Research

Lizza provides the strategic direction and vision for Datstat, using her two decades of experience in Medical Informatics and Behavioral Health. She founded DatStat with the belief that technology could transform how health researchers could engage with patients, track outcomes over time, and deliver empirically validated interventions at a scale that would positively impact the health of our world’s population.  Lizza realized all of the innovations taking place in the research world could have significant implications in the clinical world and has successfully pivoted the company to support population health more broadly.

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