An explosion in the collection of personal data is fostering concerns about the extent to which health information is accessed—and about the privacy and confidentiality of this information. Two recent National Public Radio stories highlight a few of the burgeoning uses of these abundant data.
In the first, an insurer uses personal data to predict who will get sick so it can identify patients at highest risk for hospital admission, or readmission, and then provide them with personal health coaches. The coordinated care given to patients by the coaches (for example, arranging a visiting nurse or streamlining appointments) has been shown to improve hospitalization rates. The insurer says it follows federal health privacy guidelines for anonymity and uses the information to better serve its members.
The second story explains that results of online health searches aren’t always confidential, and data brokers are tracking information and selling it to interested parties. The author notes that data gathered on the Web are, for the most part, unregulated. Both stories raise questions about privacy and confidentiality of health information and how to best protect it.
Pragmatic clinical trials also seek to use personal health data to answer important questions on the risks, benefits, and burdens of therapeutic interventions. In a blog post in Health Affairs, Joe Selby, executive director of the Patient-Centered Outcomes Research Institute (PCORI), underscores the need for trust, support, and active engagement of patients when involving them in health data research, even with privacy protections in place. PCORI has launched the National Patient-Centered Clinical Research Network (PCORnet) as a means of harnessing large clinical data sets to study the comparative effectiveness of treatments, and a central tenet of the network is that patients, clinicians, and healthcare systems should be actively involved in the governance of the use of health information.
Read the full articles
From NPR: Insurer Uses Personal Data To Predict Who Will Get Sick
From NPR: Online Health Searches Aren't Always Confidential
From Health Affairs: Advancing the Use of Health Data in Research With PCORnet
How concerned are people about the privacy of their medical information? Not very—according to the November 2014 Truven Health Analytics–NPR Health Poll (opens as PDF). The poll asked how respondents feel about sharing their electronic health information and other data with researchers, employers, health plans, and their doctors. The majority expressed a willingness to share their anonymized health information with researchers; less than a quarter expressed willingness to share non-healthcare data with their healthcare providers.
Each month, the Truven Health Analytics–NPR Health Poll surveys approximately 3,000 Americans to gauge attitudes and opinions on a wide range of healthcare issues. Poll results are reported by NPR on the health blog Shots. Among the results of this survey:
- 74% of respondents indicated that their physician uses an electronic medical record system.
- 68% of respondents would share their health information anonymously with researchers.
- 44% of respondents have looked through their health information kept by their physician.
The survey analyses were stratified by age, education, generation, and income. Poll questions were posed by cell phone, land line, and online during the first half of August 2014. The margin of error was plus or minus 1.8 percentage points. An executive summary of the survey, including questions and survey data, is here.
Michael Bass and Maria Varela Diaz of the Department of Social Sciences, Feinberg School of Medicine, Northwestern University, have kindly given the Living Textbook permission to post their presentation (link opens as a PDF) about how to use an application programming interface (API) to create a computer adaptive testing (CAT) program that integrates patient-reported outcome (PRO) measures with an institution’s electronic health record (EHR) system.
With a CAT approach, PRO assessment can cover a wide range of question/response items with increased precision. In their CAT application, the authors describe a clinical use case for a mobile health solution, using measures from the NIH-sponsored PRO Measurement Information System (PROMIS®) domain framework, in which a health assessment is issued by a physician, administered to a patient via phone, and then sent back to the EHR.
You can read more about CAT in the Patient-Reported Outcomes chapter of the Living Textbook.