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Abstract

There was a time that medical information flowed in only one direction – from doctor to patient. That time has passed. With the advent of several factors – in the U.S., the Meaningful Use standard that governs the use of Electronic Health Records (EHR) and the exchange of patient clinical data among healthcare providers as well as between healthcare providers and insurers or patients¹, the Affordable Care Act and incentive-based reimbursement, and global population health trends – a push has emerged that is shifting the patient’s role from passive recipient of care to active member of the care team². Consequently, regulators and providers are searching for solutions to increase patient engagement. This is causing patient-generated health data (PGHD) to emerge as a hot topic.

What is Patient-Generated Health Data?

PGHD, at its most basic level, is any information a patient shares with a provider. Traditionally, this would encompass symptoms as well as family history. However, patients today are increasingly collecting their own biometric data, using an ever-expanding array of personal monitors that can record everything from heart rates and rhythms to steps and glucose levels in real time³.

PGHD is also generating new challenges for healthcare providers due to the fact that participating providers must integrate PGHD into electronic health records as part of Meaningful Use Stage 3 rules by 2018. Even in countries where this requirement is not an issue, healthcare providers will still have to meet the challenge of integrating PGHD into their patient health records.

Indeed, Dr. Gregory Abowd, Distinguished Professor of the School of Interactive Computing at Georgia Tech, predicted in 2011 at an industry forum that “Within five years, the majority of clinically relevant data will be collected outside of clinical settings⁴.” In the five years since that statement, the volume of such data has increased substantially – perhaps not the majority at this point, but still, enough to warrant attention.

PGHD is distinct from data generated within clinical settings in two important ways⁵:

•  Patients, not providers, are primarily responsible for capturing and
  recording the data
• Patients decide how to share or distribute these data to healthcare
  providers and others

In Europe, collection of patient reported outcome measures, or PROMs (the continent’s PGHD equivalent) has been under way for some time. In the Netherlands, for example, collection of PROMs is mandated for certain types of patients and conditions – mandated, that is, for the providers, who in turn are required to ensure that their patients participate and respond to questionnaires. To meet this need, tools are used that electronically and automatically select validated survey instruments from an integrated library and administer them to patients at appropriate intervals (before, during, and after treatment as indicated), based on the diagnoses. These tools are generally integrated via standards-based methods with each provider’s electronic medical record (EMR).

According to the European Patients’ Academy, patient-reported outcomes are important because they provide a patient perspective on a disease or treatment that might not be captured by a clinical measurement, but may be as important to the patient (and their adherence to the treatment) as a clinical measurement⁶.

Insurers today are continually seeking surrogate data as an alternative to more traditional sources of underwriting data (e.g., paramedical exams and attending physician statements). For example, some insurers are incorporating data elements generated by wearable devices into their pricing and underwriting considerations.

Usability and Reliability of PGHD

Clinicians continue to be divided as to the utility of patient-generated health data. The latest studies have found that only 15% of physicians recommend patient use of wearables or other health apps to improve health. Some physicians have even stated they will only take a patient’s health data seriously if it has been generated from an FDA-approved device⁷. Primary clinical objections were⁸:

• Information overload: Clinicians may be overwhelmed with primarily normal readings
• Workload: The cost of and complexity for a practitioner of collecting the data
• Unintended consequences: Clinician liabilities stemming from lack of
  timely, appropriate review of and action on the data
• Other: Health care providers simply don’t know what to do with the
  results

Conversely, patients in a study conducted by the Society for Participatory Medicine were significantly more enthusiastic about PGHD⁷:

• 76% would use a clinically-accurate and easy-to-use personal monitoring device
• 57% would share the data generated with a health professional
• 81% would be more likely to use a device if it was recommended by their provider

According to a study by the Pew Research Center that looked at the tracking of health indicators, more than 40% of patients who use tracking devices claim this activity has changed their overall approach to maintaining their health or the health of someone for whom they care. It has also led them to ask their doctors new questions or to seek second opinions. Additionally, one-third states that data from these devices has affected a decision about how to treat an illness or condition⁹.

Challenges

Some notable challenges related to PGHD use include the following:

• Privacy and security: Devices and applications that collect PGHD can interface into other applications and interact with covered entities; the data then becomes protected health information (PHI).
• Information integrity: Multiple sources can generate the data. The majority of electronic health records systems are only beginning to incorporate patient collected data – and when they do, providers want them to distinguish which data came from a patient’s devices from data obtained by health professionals³.
• Data longevity: PGHD often lack the historical sweep of longitudinal data (e.g., the same input collected at points in time, over years or decades). Because self-tracking is still relatively new, PGHD are relatively short-term data sets and have no baseline for comparison. The data may not be useful for years¹⁰.

Insurance Implications of PGHD

New technologies are simply increasing the volume of raw patient data available, but the data itself does not necessarily convey the context. For example, a patient’s weight tracked month after month might not convey anything about his or her health without additional indicators such as diet, lifestyle, age, family history, etc.¹¹ This is one of the challenges the insurance industry is increasingly facing when trying to make good decisions based on PGHD. 

Insurers also have to consider the potential for anti-selection as the asymmetry of knowledge between applicant and underwriter increases (e.g., direct-to-consumer tests for genetic profiles and HIV). Patients currently can decide whether, and with whom, to share their self-generated data. Indeed, 90% of respondents to a recent global survey conducted by Accenture Consulting on patient engagement said they would share data from their apps or wearable devices with medical providers, while 63% said they would share the data with their health plans, and 31% would share it with their employers¹².

Conclusion

Medical directors, pricing actuaries, underwriters, and claims examiners are likely to find themselves breaking new ground when trying to correlate clinical data with PGHD in order to derive the complete story of an insured’s health or risk status. The American Health Information Management Association (AHIMA) recommends that with the anticipated growth in use and availability of mobile apps and data collection devices, strategic planning for incorporating this type of data should begin now¹³.