University of Michigan (MI, USA) researchers and a Veterans Affairs team have designed a tool to help clinicians discuss lung cancer screening options with their patients and decide whether the potential benefit is worth the potential harms for each patient. The tool is termed Lung Decision Precision.
The findings were recently published in the Annals of Internal Medicine.
The tool advices clinician’s on how to:
- Prepare to talk with their patients by: 1) determining whether they’re eligible and 2) designing a patient-centered recommendation based on the patient’s individual risk profile.
- Talk to patients using the checklist provided. Use the evidence-based, personalized method of discussing benefits and harms, so patients can understand the trade-offs of screening.
- Document shared decision making in the medical record system with a simple copy and paste.
- Share a printable report with their patients.
“Our model is built on a comprehensive view of net benefits for individual patients, which incorporates the best evidence for personalizing the pros and cons of screening and assumes that not all patients will feel the same about screening and its consequences,” explained first author Tanner Caverly from the University of Michigan Medical School.
“This allows us to identify which patients are in the preference-sensitive zone for the decision about screening, and which ones have a very clear potential benefit to them,” Caverly added.
“If a physician is not clear about the potential benefit for a patient who’s in the high-benefit zone, they could miss an opportunity to do something really good for them, to say, ‘I don’t recommend this for everyone but I recommend it for you. But coming across strong for screening with a patient who has a fine balance of pros and cons could miss an opportunity to give them a choice, to tell them that their decision depends on the kind of person they are,” Caverly concluded.
Sources: Caverly TJ, Cao P, Hayward RA et al. Identifying patients for whom lung cancer screening is preference-sensitive: a microsimulation study Ann. Intern. Med. doi:10.7326/M17-2561 (2018) (Epub ahead of print); https://share.lungdecisionprecision.com/about/; www.eurekalert.org/pub_releases/2018-05/mm-u-tso052318.php