Do website reviews of internists inform patients with diabetes or hypertension about the quality of care they would receive from these physicians?

Objective

Assess the accuracy of patient ratings of physicians obtained by internet searches.

Data

Physician quality measures (QMs) were drawn primarily from patient charts for 1,042 internists who completed a diabetes or hypertension practice improvement module (PIM) (08/01/2011-11/12/2012). PIM completion is part of the American Board of Internal Medicine's (ABIM) maintenance of certification process and included abstracting 25 charts and collecting 25 patient survey responses for patients with the applicable chronic condition.

Chart PIM-QMs applicable to both patient cohorts included: share of patients with blood pressure/LDL controlled and providing smoking cessation advice. Patient survey PIM-QMs included patient assessment of care quality/physician self-care support as very-good or excellent. We applied an expert panel based PIM-QM composite, comprising mostly chart-based QMs. PIM-QMs mirror quality measures applied by NCQA/CMS.

We mimic consumer searches by entering each internist's name and location into a Google search, extracting ratings from the first two health-websites on the search list. Searches captured 1,013 ratings for 602 internists (58% of our sample) from eight websites. We normalized ratings by dividing each rating by that website's maximum score (e.g., 2 out of 5 stars yielded a normalized rating of 40%). We categorized the normalized website rating as top score if >=80% (59% of ratings) and bottom score if <=0% (12% of ratings).

Methodology

We estimated the relationship between internists' PIM-QMs and having any website rating using probit regression. PIM physician QMs were evaluated as dependent variables using binomial-regression (Logit-link) where a website rating was the explanatory variable controlling for sub-specialization, PIM, website. We accounted for physicians being rated on multiple websites.

Findings

Our analysis indicated that patients with diabetes/hypertension obtain limited information from internet searches regarding which physicians to avoid (bottom rating associated only with patient share with LDL controlled (p-stat<.05)) but not whom to choose (normalized rating or top rating was not associated with any PIM-QM, only 6 ratings per website). However, ratings from the most popular website (HealthGrades (n=465)) yielded information regarding the overall quality of physicians (normalized rating was a significant positive predictor of PIM-QM composites (p-stat<.05)). Yet, more information about quality would have been revealed had ABIM patient ratings been accessible (PIM-QM patient reviews significantly correlated with PM-QM clinical composite (p-stat<.001) and these associations were significantly larger than website ratings associations (p-interaction<.01).

Conclusion

Consumers obtain limited physician quality information from website searches and yet there exists a great potential for patient reviews to aid consumers.