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Posts made in November 2013

Questionable Medical Guidelines lead to Confusion, Frustration and Danger to the Patient

Risk-calculatorWill recent discussions about the risk calculator, used to measure risk for heart disease and stroke, lead to widespread prescribing of statins which carry their own risks and concerns? Apart from the question of the accuracy of the risk calculator, the crucial issue is the use of a risk calculator as a measuring tool for prescribing statins. The problem is that there are differing opinions about exactly which measurement is the target.

The recently published guidelines indicate that people without a history of heart disease can start taking statins if they have a 7.5% higher risk of developing heart problems or stroke in the next 10 years, based upon family history, and other conditions such as inflammatory disease. That’s a significant change from the 20% higher risk that previous guidelines advised.

Because this represents such a dramatic shift, some heart experts are concerned that the standard treatment of heart disease such as proper diet and exercise, so successful for many patients, will be ignored. More concerning is the fact that individuals who do not need statins will be taking them.

For patients, long frustrated with health recommendations which seemingly change like the weather, this presents yet another occasion where controversy among health care professionals makes it very difficult to select a sound treatment choice.

This is especially true since the media, has widely publicized the argument that prescribing statins across a much larger population is a positive conclusion.  This creates the impression that this reasonable cure for many is a cure-all for everyone.  Couple this hype with the fact that one of the largest causes of medical errors in this country is misdiagnosis by doctors, and it is no wonder that doctors and patients are bewildered.

A recent Wall Street Journal article (November 18, 2013) cited misdiagnosis are among the most common, costly, and harmful medical errors,that could be prevented with more diligence.  “The Biggest Mistakes Doctors Make” outlines how some doctors who fail to follow best practices or follow through with patients have increased the chances that the wrong treatment, under-treatment or over-treatment can lead to serious , sometimes fatal medical errors.

The Centers for Disease Control and Prevention (CDC) reports that heart disease is the leading cause of death in both men and women and nearly 800,000 Americans experience heart attacks every year.

The American Heart Association contends that it is essential that all individuals measure their own risk of heart disease and make a plan for how to prevent it. To make matters worse they have a different patient risk calculator and indicate in bold on their website that this “risk calculator is NOT connected to the 2013 treatment guidelines for professionals”

How confusing is all of this to patients?  How disturbing to think that medical errors could occur when the individuals who do not meet the right targets are prescribed the wrong medication for them, because it is a popular perception that the medication is a cure-all.

The bottom line is that statins are a wonderful discovery and for the right patients potentially prolong their life and well-being.  However, like so many other complicated issues in health care today, this is another example of where mixed messages from researchers cause clinician uncertainty, along with a media frenzy, which makes it very difficult for physicians and patients to partner and make good health decisions.

What should an e-Patient do when confronted with these medical dilemmas?
1. Talk to your doctors. Question the rationale for medications that are prescribed. Weigh and measure the benefits and the risks.
2. Go online and review all of the pros and cons, side effects, long-term impact and short-term gains of a medication.
3. Do not make hasty decisions about treatments based on media hype, crowd sourced ideas or popular perceptions.
4. Always remember, you  have choices and they are yours to make.

Big Data Impacts Your Healthcare, Big Time!

Big data is the practice of taking masses of information, and mining it to cull out specific trends and characteristics, using sophisticated software and powerful hardware. In healthcare as well as in many other areas, data sets are growing in size because from information sensing mobile devices to remote sensing technologies to wireless networks, data is constantly collected and stored.

The healthcare industry has finally recognized that the days of keeping health data sequestered in proprietary silos is unacceptable. The adoption and near ubiquitous acceptance by clinicians of electronic health record systems requires that there are  innovative analytics solutions to peel back the new layers of information and insights contained in these records. A similar growth in electronically available hospital data, ambulatory data, pharmacy and payer claims information and data from personal health devices such as home monitors and smartphones continues to grow.

Consumers are eager to gain access to their health histories and to share them with their care providers. Payers, employers, providers and government agencies have come to realize that reforming healthcare is, in large measure, dependent on sharing important clinical data. Furthermore, the shift towards paying for health services based on outcomes rather than on procedures has focused attention on analytic techniques that can accurately distinguish between good and poor results.

The technology behind these  gargantuan data sets now enables researchers to begin to  understand underlying cause-and-effect relationships that previously remained hidden in too much information. For example, one important outcome of big data analytics is the ability to predict cases of hospital readmission.  Armed with this information, providers are able to implement better interventions among those patients whose conditions and behaviors are associated with a high degree of probability that they will return to the hospital within 30 days of an in-patient stay.

Patients on average spend an hour a year with a clinician, and in that time the clinician and the patient are expected to make effective treatment decisions. With big data they will have the information to understand outcomes of large patient populations which provides the clinical context required for effective decision-making, including ways to reduce medical errors, and more effectively deal with chronic disease management.

The big data analytics approach, includes identifying hidden drug interactions as well as the care processes, conditions and patient characteristics that affect safety and efficacy. This deep analysis enables organizations to determine which approaches are most effective, where gaps exist, and how to chart the structure of complex treatments. As we work with big data, the models will become increasingly predictive and, hopefully, will lead to cures for diseases that today seem intractable

The advent of personalized medicine which includes whole genome sequencing further changes what can be understood and applied in healthcare treatment and outcomes.   With deep data analytics, drug developers can match patient types to therapies most likely to work for them, as well as identify new therapeutic approaches, while providers can tailor those remedies to the specific needs of each individual patient. Additionally, health plans can use the information to develop comparative effectiveness models for specific scenarios and develop more efficient and cost-effective approaches to healthcare delivery.

The goal of medicine is to provide the right care, at the right time, every time, for every patient. From a quality of care perspective, it has always been important for healthcare organizations to have a full picture of what is happening in their patients’ health.  Predictive analytics with big data is truly the pathway to achieving this type of value based healthcare. It represents a sea-change for the future of medicine for everyone.