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Can technology help individualized medical decision making?

Leslie Kernisan, MD, MPH
Physician
September 1, 2013
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Shouldn’t everyone get an individualized assessment of likely benefits, burdens, and risks before making a big medical decision?

I was asked this question recently, during an interview for an Internet radio show on aging.

Per my host’s request, I’d been explaining the practice of geriatrics, and talking about the geriatric approach to addressing the medical needs of older adults. Since I’d mentioned that aging often brings on greater risk of side-effects or complications from anesthesia, the host, Harriet Tramer, asked me whether older adults should be trying to avoid surgeries. I responded by trying to explain the idea of balancing likely benefits versus burdens and risks, before making a decision about surgery. Some surgeries seem more likely to lead to substantial benefits than others. Some situations seem riskier, or more burdensome, than others. Hence, an individualized approach is best.

Which led Ms. Tramer to ask me the question above: shouldn’t everyone — not just the elderly, or those seeing geriatricians — get this type of individualized counseling before deciding to pursue an operation, or making another type of big medical decision?

Well, yes! Patients of any age can benefit from this type of individualized counseling, which is sometimes referred to as shared decision making. It enables patients to make more informed decisions. It can also help patients obtain care that is a better fit for their values and preferences. And in some case, it might improve outcomes, if patient and clinician decide to forgo a risky procedure. Last but not least, individualized assessments of likely benefits and risks could improve the value of healthcare (value = benefit/cost), if such assessments result in patients forgoing expensive procedures that are unlikely to be helpful.

This type of individualized care is good for everyone, but is especially beneficial as people get older. Since older adults tend to have more chronic conditions and disabilities, there is more to consider when trying to identify benefits, risks, and burdens of a given course of action.

But there is a downside to engaging in this kind of collaborative and individualized medical decision making: it requires time, energy, and effort. And for clinicians, not only does it take time and energy to have the conversation with patients and families, but it also usually takes time and energy to figure out just what are the risks, benefits, and burdens when a specific patient faces a specific medical decision.

Could technology make this process of estimating risks, benefits, and burdens easier for clinicians and patients?

The challenges of individualized medical decision making

Several years ago, one of my elderly primary care patients developed memory problems. He had been pretty hale and sharp, in relatively good health. But then he started to complain of difficulty remembering things and organizing himself, and after a thorough evaluation, we diagnosed him with Alzheimer’s disease.

Before he became too impaired, we talked about his preferences for healthcare in the future. He voiced a preference for not spending too much time in the hospital, and he wanted to avoid surgeries and procedures unless they were likely to really improve his quality of life. And of course, he didn’t want to be kept on life support if he were terminally ill.

About a year later, he’d progressed to moderate dementia, and his medical decision making had been taken over by a professional conservator. He developed a bad cold, and the urgent care doctor did an x-ray to evaluate for pneumonia. On x-ray, he didn’t have pneumonia. He did, however, seem to have a lump in his lung, and a follow-up CT scan confirmed a small-medium lung mass, suspicious for cancer.

And now what to do? The usual next step would be to have the lung doctors biopsy the mass. Small localized lung cancers in particular can often be treated with surgical removal (unless the biopsy shows that it’s one of those cancers that is unlikely to be successfully treated with surgery.) But this patient was elderly, and had dementia. Which meant that surgery would be more burdensome to experience, and came with higher risks of complications during and immediately after the surgery.

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The conservator and I weren’t sure what to do. When patients are making decisions for themselves they often just make a gut decision (undoubtedly influenced by the doctors around them) and don’t always want statistics and details. But I wanted to make sure we’d considered the decision properly, and the conservator certainly wanted to be sure of doing right by the patient.

We needed data:

  • How likely was it that the mass was likely to make him feel symptomatically sick and/or shorten his life, if left untreated?
    • The oncologists refused to answer this question, saying they absolutely needed a biopsy sample before they’d hazard a guess.
  • How likely was the patient to find the biopsy procedure uncomfortable? What was the risk of complications? (And how do we factor in the risk of things like getting delirium or distressed by the procedure, and subsequently falling at home?)
  • If he had the biopsy and it turned out to be the type of cancer that was likely to be cured by surgery, what would be the risks/benefits/burdens of the surgery, and would the conservator consider them acceptable?
  • What was the patients overall prognosis and life expectancy, even before taking into account the new lung mass?

As you can see, a tailored assessment of risks, benefits, and burdens became very complicated, very quickly.

We never did get the exact statistics, although I did spend a fair amount of time looking things up in my medical references, and talking to my specialty colleagues.

In the end, we decided to not get a biopsy, and instead repeat the scan in several months to see if the mass was growing. Not because we’d biopsy him at that point, but because we decided it would be useful for us to know if the patient was suffering from an advancing lung cancer. We also, of course, made plans to follow the patient’s weight, appetite, and function.

What would’ve been the alternative to this process? Here are some other ways the situation can play out:

  • Physician decides the patient should next have a biopsy. Patient and conservator go along with what the physicians recommend.
  • Physician decides the patient is elderly and has dementia and so should not have further complicated medical care. Patient and conservator go along with physician’s recommendation.
  • Physician tells conservator: the decision is up to you, and tries to avoid influencing the conservator’s decision. The conservator may or may not try to look things up on the Internet, or otherwise get more information. Most proxies, in my experience, do not ask the physician “which choice do you think is likely to give this person the best quality of life over the next five years,” but I wish they would.

Facilitating individualized medical decision making for everyone

Individualized decision making is important. If we want more patients to be able to access it, we’ll need to develop better tools and resources.

To date, the main resources available are decision aids, many of which have been carefully developed by non-profit experts and are of high quality. When a good decision aid can be located and used, patients and clinicians generally benefit.

The trouble is that decision aids are often not available for the decision at hand. To begin with, a good decision aid can be hard to find online; many are only made available as an institutional subscription, so individual patients and small clinical practices may not be able to access them.

Another problem is that decision aids are usually created for a certain common condition or decision, and are tailored to help an “average” patient. Unfortunately, I know of no pre-made decision aid meant to help elderly patients with dementia consider their options for diagnosis and management of a suspicious lung nodule. Dementia and advanced age are complex factors because they both introduce a lot of variability into the factors of risk, benefit, burdens, and preferences.

Still, although I don’t expect there will ever be a pre-fabricated decision aid available to help with the situation I described, I do think that the right tools could go a long way in helping clinicians and patients and families make decisions for frail elders. For example, we might eventually have easier access to calculators (perhaps relying on information gleaned from big data) that can capture the patient’s physiologic data and present us with better information on prognosis and risk during procedures.

Technology, data, and a new culture of shared decision making hold such promise. Within the next, say, ten years, will we see it turn into real improvements for the real sticky situations affecting elders and their families? Will it soon be easier for all clinicians to provide better help, to all patients?

Leslie Kernisan is an internal medicine physician and geriatrician who blogs at GeriTech.

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