Taking Control: Learn More About Accessing Your Health Information

Woman looking at electronic medical records on her smartphone

Credit: Lydia Polimeni, NIH

Usually, I share cool science advances and major medical breakthroughs on this blog. But, today, I’d like to share something a little different, something of great importance for both your health and the advancement of biomedical research: new guidelines on how you can access your own health information.

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule has long supported the right of individuals to request and obtain copies of their medical records and other health information maintained by health-care professionals, medical facilities, and health insurance plans. However, due to the increasing use of online health-information technology and growing interest among Americans in being active participants in health-related decisions, the U.S. Department of Health and Human Services (HHS) recently issued much-anticipated guidance that serves to answer common questions and clarify key issues regarding access to health information under HIPAA. Think of it as a valuable personal roadmap for navigating a part of health care that is all-too-often confusing and frustrating!

Among the many reasons that people need easy, affordable access to their health records is to empower them to take more control over decisions regarding their health. Such information can help individuals improve their ability to monitor chronic conditions, stick with treatment plans, track progress in wellness programs, and identify and correct erroneous information. In addition, some people may want such access so they can directly contribute their health information to biomedical research projects. One such endeavor is the new, NIH-led Precision Medicine Initiative Cohort, in which 1 million or more volunteers will agree to share data, including information from their health records. Maintaining the security and privacy of individual information will be of paramount importance. In return, participants will have the highest levels of access to their study results, along with summarized results from across the cohort.

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Big Data Study Reveals Possible Subtypes of Type 2 Diabetes

Computational model

Caption: Computational model showing study participants with type 2 diabetes grouped into three subtypes, based on similarities in data contained in their electronic health records. Such information included age, gender (red/orange/yellow indicates females; blue/green, males), health history, and a range of routine laboratory and medical tests.
Credit: Dudley Lab, Icahn School of Medicine at Mount Sinai, New York

In recent years, there’s been a lot of talk about how “Big Data” stands to revolutionize biomedical research. Indeed, we’ve already gained many new insights into health and disease thanks to the power of new technologies to generate astonishing amounts of molecular data—DNA sequences, epigenetic marks, and metabolic signatures, to name a few. But what’s often overlooked is the value of combining all that with a more mundane type of Big Data: the vast trove of clinical information contained in electronic health records (EHRs).

In a recent study in Science Translational Medicine  [1], NIH-funded researchers demonstrated the tremendous potential of using EHRs, combined with genome-wide analysis, to learn more about a common, chronic disease—type 2 diabetes. Sifting through the EHR and genomic data of more than 11,000 volunteers, the researchers uncovered what appear to be three distinct subtypes of type 2 diabetes. Not only does this work have implications for efforts to reduce this leading cause of death and disability, it provides a sneak peek at the kind of discoveries that will be made possible by the new Precision Medicine Initiative’s national research cohort, which will enroll 1 million or more volunteers who agree to share their EHRs and genomic information.

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Creative Minds: Lessons from Halfway Around the Globe

Transporting a patient in Nepal

Caption: Duncan Maru (right) and Community Health Director Ashma Baruwal (left) evaluating a patient in rural Nepal.
Credit: Allison Shelley

A decade ago, as a medical student doing volunteer work at a hospital in India’s capital of New Delhi, Duncan Maru saw a young patient who changed the course of his career: a 12-year-old boy in a coma caused by advanced tuberculosis (TB). Although the child had been experiencing TB symptoms for four months, he was simply given routine antibiotics and didn’t receive the right drugs until his parents traveled hundreds of miles at considerable expense to bring him to a major hospital. After five weeks of intensive treatment, the boy regained consciousness and he was able to walk and talk again.

That’s quite an inspiring story. But it’s also a story that haunted Maru because he knew that if this boy had access to good primary care at the local level, his condition probably never would have become so critical. Determined to help other children and families in similar situations, Maru has gone on to dedicate himself to developing innovative ways of providing high-quality, low-cost health care in developing areas of the world. His “lab” for testing these efforts? The South Asian nation of Nepal—specifically, the poverty-stricken, rural district of Achham, which is located several hundred miles west of the national capital of Kathmandu.

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Creative Minds: Building a Better Electronic Health Record

Doctor with tablet

Stock photo

Is 5 too few and 40 too many? That’s one of many questions that researcher David Chan is asking about the clinical reminders embedded into those electronic health record (EHR) systems increasingly used at your doctor’s office or local hospital. Electronic reminders, which are similar to the popups that appear when installing software on your computer, flag items for healthcare professionals to consider when they are seeing patients. Depending on the type of reminder used in the EHR—and there are many types—these timely messages may range from a simple prompt to write a prescription to complex recommendations for follow-up testing and specialist referrals.

Chan became interested in this topic when he was a resident at Brigham and Women’s Hospital in Boston, where he experienced the challenges of seeing many patients and keeping up with a deluge of health information in a primary-care setting. He had to write prescriptions, schedule lab tests, manage chronic conditions, and follow up on suggested lifestyle changes, such as weight loss and smoking cessation. In many instances, he says electronic reminders eased his burden and facilitated his efforts to provide high quality care to patients.

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