BackgroundIt is challenging to assess the quality of care and detect elder abuse in
nursing homes, since patients may be incapable of reporting quality issues
or abuse themselves, and resources for sending inspectors are limited.ObjectiveThis study correlates Google reviews of nursing homes with Centers for
Medicare and Medicaid Services (CMS) inspection results in the Nursing Home
Compare (NHC) data set, to quantify the extent to which the reviews reflect
the quality of care and the presence of elder abuse.MethodsA total of 16,160 reviews were collected, spanning 7,170 nursing homes. Two
approaches were tested: using the average rating as an overall estimate of
the quality of care at a nursing home, and using the average scores from a
maximum entropy classifier trained to recognize indications of elder
abuse.ResultsThe classifier achieved an F-measure of 0.81, with precision 0.74 and recall
0.89. The correlation for the classifier is weak but statistically
significant: = 0.13, P < .001, and 95% confidence
interval (0.10, 0.16). The correlation for the ratings exhibits a slightly
higher correlation: = 0.15, P < .001. Both the
classifier and rating correlations approach approximately 0.65 when the
effective average number of reviews per provider is increased by aggregating
similar providers.ConclusionsThese results indicate that an analysis of Google reviews of nursing homes
can be used to detect indications of elder abuse with high precision and to
assess the quality of care, but only when a sufficient number of reviews are
available.