Medical experts have worked for decades to improve the chances that patients will get the scans, routine tests and medicines that can do them the most good – and avoid the ones that won’t help them at all.
But in the push toward evidence-based medicine, a new study says, a key step has mostly gotten overlooked: helping doctors stop or scale back – or deintensify – treatment once it has started, and take the screening, testing and treatment down a notch as evidence changes or the patient’s health, age and lifestyle change.
To truly help patients, it’s time to include clear off-ramp instructions for providers and patients, especially in primary care, say the authors of a new study published in JAMA Internal Medicine.
They lay out a process for doing so, based on an intensive review of hundreds of recommendations built on reams of research and evidence. Backed by a panel of expert advisors from a wide range of fields, they identify an initial set of 37 specific instances where physicians could deintensify care safely for certain patients.
“For many years, we’ve been focused on making sure patients get all the care they need, because there were deficits,” says Eve Kerr, M.D., M.P.H., lead author of the study and a professor in the Department of Internal Medicine at the University of Michigan and Senior Investigator at the VA Center for Clinical Management Research. “But there are times when patients are getting care too frequently or more intensely than they might have once needed. Those are opportunities to improve their care without harming their health, or perhaps even reducing risk and increasing quality of life.”
A new framework to build on
Kerr and her colleagues from Michigan Medicine, U-M’s academic medical center, and the VA Ann Arbor Healthcare System emphasize that their new paper sets out a framework for future efforts by guideline developers to offer specific guidance on right-sizing care.
The initial set of recommendations is tailored for adult primary care. But the authors hope that the professional societies that create treatment guidelines will be able to adopt their approach to more precisely frame future recommendations to encompass not only when to start treatments or screening, but also when to stop or scale them back.
For instance, as people with diabetes get older, they don’t need to take multiple medications to lower their blood sugar or blood pressure to the same target number they aimed for when they were younger. That’s because the evidence that supports those low targets comes from studies that focused on preventing diabetes-related problems decades in the future. Plus, older patients are at higher risk from low blood sugar that these medications may cause.
Or, in another example, men who have been used to getting a periodic blood test for prostate specific antigen to look for possible signs of prostate cancer can stop getting tested after about age 69 – unless they’re African-American or have a family history of prostate cancer and thus at higher risk.
These types of guideline-based deintensifications were only included in the new paper’s appendix after undergoing a thorough review using a formal structure that clearly stated when and for whom a treatment or test should be scaled back, and confirmatory ratings by experts in the field.
“We hope this can be a reproducible process for identifying and specifying opportunities to deintensify care, with enough information to guide measurement,” says Kerr.
But she and her colleagues firmly note that no individual physicians should be penalized for failing to deintensify care, because of the important role of patient preference and clinical nuance. Instead, health care systems could use the highly specified recommendations from this study to track and improve deintensification for their population of patients.
Moving forward
Over time, if health systems incorporate deintensification recommendations into their electronic health record systems, they could help prompt physicians to discuss deintensification with appropriate patients. And they could track aggregate data about how well the system as a whole is doing.
“We need to move toward a place of balance in our clinical care delivery,” says senior author Timothy Hofer, M.D., M.Sc., professor of internal medicine at U-M and investigator at the VA CCMR. “If we make recommendations about starting a form of care, we should also say when to stop, and include specification about populations and times and actions for doing so.”
The authors point to data from the National Poll on Healthy Aging, based at U-M’s Institute for Healthcare Policy and Innovation, which found that only 14% of older adults believe that “more is usually better” when it comes to medical care, and that 25% agree with the statement that their health providers often order tests and treatments that the patients don’t feel are needed.
In an accompanying editorial also published today, evidence-based medicine researchers Raj Mehta, M.D., and Richard Lehman, BM, BCh, write that “clinical practice has always involved decisions to do less–it just lacks the momentum and formalization needed for broad support. Guidelines focused on deintensification may be the signal of change needed to empower health care practitioners to reverse the trend of unnecessary care and counter the existing bias to do more.”
The team that wrote the new paper is working to study how often patients are receiving care that might once have been right for them but is now too intense. Kerr heads the Michigan Program on Value Enhancement at IHPI, which brings together IHPI researchers and Michigan Medicine clinicians to develop and test new ways to right-size care in real-world settings.
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In addition to Kerr and Hofer, the new study’s authors are Mandi L. Klamerus, MPH; Adam A. Markovitz, BS; Jeremy B. Sussman, MD, MSc; Steven J. Bernstein, MD, MPH; Tanner J. Caverly, MD, MPH; Roger Chou, MD; Lillian Min, MD, MSHS; Sameer D. Saini, MD, MS; Shannon E. Lohman, BS; Sarah E. Skurla, MPH; David E. Goodrich, EdD; and Whit Froehlich, BA. The study was funded by the Department of Veterans Affairs (HSR&D grant IIR 15-131).
