Friday, March 14, 2014

There’s No Telling What Patients Want

“Shared decision-making” has become a frequent watchword of sorts, encompassing participatory concepts in which patients are better involved in their own care.  I, and many others, have espoused this sort of paradigm in medicine.

Unfortunately, there’s a bit of a problem.  On the physician side, we probably don’t have good mechanisms through which to translate evidence to individual patients.  Most information derived from clinical studies describes outcomes from aggregated cohorts – so, usually, the best we can do is inform our patients how the “average” person performed with a specific treatment.

Then, on the patient side – as this study demonstrates – their risk-taking behavior is heterogenous, irrational, and extreme.  These authors report on 234 surveys of patients presenting with low-acuity chest pain in a Veterans Affairs cohort, trying to get a handle on hospitalization preferences given a certain pretest likelihood of disease.  Their basic model:  hospitalization reduces the risk of bad outcome by 10%.  Then, they asked if the patient would like to be hospitalized for base likelihood of poor outcomes ranging from 1 in 2 to 1 in 10,000.

Half the patients wanted to be hospitalized, even when the benefit to hospitalization reduced the event rate from 1 in 10,000 to 1 in 11,000 (an NNT of 110,000).  Then, another 10% of patients wanted to be discharged in all circumstances, even when the risk of poor outcome was improved from 1 in 2 to 5 in 11 (an NNT of 22).  And, depending on how the risks were communicated, and whether visual or numeric scales were used, also affected how the patients chose.

So, ultimately – yes, we’d like to involve patients in their decisions.  But, unfortunately, it looks as though it’s going to be quite the challenging proposition – and we might not like (or have the capacity to abide by) their preferences.

“Measuring Patient Tolerance for Future Adverse Events in Low-Risk Emergency Department Chest Pain Patients”
http://www.ncbi.nlm.nih.gov/pubmed/24530111

2 comments:

  1. Check your NNT calculation on example 2 - tricky indeed!

    ReplyDelete

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