Medical guidelines that embrace the humility of uncertainty could help doctors choose treatments with more research evidence behind them

We are physicians who share a common frustration with guidelines based on weak or no evidence. (Pexels photo)

Clinical guidelines greatly influence how doctors care for their patients. By providing recommendations on how to diagnose and treat particular situations, guidelines can help standardize the care patients receive. For instance, when a patient is suffering from an infection, a physician can consult the relevant guidelines to confirm that antibiotics are the appropriate treatment. Regulators, insurance payers and lawyers can also use guidelines to manage a doctor’s performance, or as evidence in malpractice cases. Often, guidelines compel doctors to provide care in specific ways.

We are physicians who share a common frustration with guidelines based on weak or no evidence. We wanted to create a new approach to medical guidelines built around the humility of uncertainty, in which care recommendations are only made when data is available to support the care. In the absence of such data, guidelines could instead present the pros and cons of various care options.

We got together an international team of physicians and pharmacists to create a guideline on creating guidelines. We call this new type of guideline a WikiGuideline, not affiliated with Wikipedia but similarly opening collaboration to all people. The idea was to enable any qualified practitioner to have a voice in guideline construction, rather than limiting authorship to academics who are politically active in specialty societies in wealthy countries.

Why a new guideline for medical guidelines?

The clinical guidelines movement first began to gain steam in the 1960s. Guideline committees, usually composed of subspecialty experts from academic medical centers, would base care criteria on randomized clinical trials, considered the gold standard of empirical evidence.

Unfortunately, many committees have since started providing answers to clinical questions even without data from high-quality clinical trials. Instead, they have based recommendations primarily on anecdotal experiences or low-quality data.

Medical guidelines made with insufficient data can lead to patient harm.

For example, guidelines once instructed doctors to prescribe hormone replacement therapy to all post-menopausal women to prevent breast cancer. However, a subsequent large randomized controlled trial showed that giving hormone replacement therapy actually increased the risk of breast cancer. While guidelines have since been updated to narrow down who would benefit from hormone replacement therapy, prior practices have likely resulted in breast cancer for many patients.

Other poorly made guidelines have also seen similar results.

A guideline that instructed doctors to use higher doses of an antibiotic called vancomycin for bacterial infections was later shown to not only be less effective but also increase the risk of kidney failure. Likewise, a guideline that promoted aggressive, rapid administration of antibiotics to patients who may have pneumonia was found to not improve outcomes and cause side effects for patients who did not actually end up diagnosed with pneumonia.

Another guideline promoted the use of medications called beta blockers for certain types of surgeries before researchers learned that they increased the risk of heart attacks during and after the procedures. Similarly, a guideline promoting the use of intensive insulin therapy in the ICU was later shown to cause blood sugar levels to drop to dangerously low levels.

A WikiGuideline for bone infection

To create a new form of medical guideline that takes the strength of available evidence for a particular practice into account, we gathered 60 other physicians and pharmacists from eight countries on Twitter to draft the first WikiGuideline. Bone infections were voted as the conditions most in need of new guidelines.

We all voted on seven questions about bone infection diagnosis and management to include in the guideline, then broke into teams to generate answers. Each volunteer searched the medical literature and drafted answers to a clinical question based on the data. These answers were repeatedly revised in open dialogue with the group.

These efforts ultimately generated a document with more than 500 references and provided clarity to how providers currently manage bone infections. Of the seven questions we posed, only two had sufficient high-quality data to make a “clear recommendation” on how providers should treat bone infection. The remaining five questions were answered with reviews that provided pros and cons of various care options.

The recommendations WikiGuidelines arrived at differ from current bone infection guidelines by professional group for medical specialists. For example, WikiGuidelines makes a clear recommendation to use oral antibiotics for bone infections based on numerous randomized controlled trials. Current standard guidelines, however, recommend giving intravenous antibiotics, despite the evidence that giving treatment orally is not only just as effective as giving it intravenously, but is also safer and results in fewer side effects.

Next steps

Providers benefit from careful review of a clinical case. When there isn’t enough data to make a clear recommendation, laying out what data is available can help inform their clinical judgment.

We believe that more inclusive guideline committees that open participation to qualified practitioners instead of just those within specialty societies could help make for better medical guidelines. The WikiGuidelines Group now has over 110 members from over 14 countries, many of which are lower- and lower-middle-income countries. We are currently working on a guideline for managing heart valve infections.

It is our hope that future guidelines can avoid the errors of the past by incorporating the humility of uncertainty into the process, acknowledging when the evidence is unclear and only issuing clear recommendations when high quality data can support them.

This article is republished from The Conversation under a Creative Commons license. Read the original article.