Online Customer Reviews of Assisted Living Communities: Association with Community, County, and State Factors.

OBJECTIVES

Online reviews provided by users of assisted living communities may offer a unique source of heretofore unexamined data. We explored online reviews as a possible source of information about these communities and examined the association between the reviews and aspects of state regulations, while controlling for assisted living, county, and state market-level factors.

DESIGN

Cross-sectional, observational study.

SETTING AND PARTICIPANTS

Sample included 149,265 reviews for 8828 communities.

METHODS

Primary (eg, state regulations) and secondary (eg, Medicare Beneficiary Summary Files) data were used. County-level factors were derived from the Area Health Resource Files, and state-level factors from the integrated Public Use Microdata series. Information on state regulations was obtained from a previously compiled regulatory dataset. Average assisted living rating score, calculated as the mean of posted online reviews, was the outcome of interest, with a higher score indicating a more positive review. We used word cloud to visualize how often words appeared in 1-star and 5-star reviews. Logistic regression models were used to determine the association between online rating and a set of community, county, and state variables. Models were weighted by the number of reviews per assisted living bed.

RESULTS

Overall, 76% of communities had online reviews. We found lower odds of positive reviews in communities with greater proportions of Medicare/Medicaid residents [odds ratio (OR) = 0.986; P < .001], whereas communities located in micropolitan areas (compared with urban), and those in states with more direct care worker hours (per week per bed) had greater odds of high rating (OR = 1.722; P < .001 and OR = 1.018, P < .05, respectively).

CONCLUSIONS AND IMPLICATIONS

Online reviews are increasingly common, including in long-term care. These reviews are a promising source of information about important aspects of satisfaction, particularly in care settings that lack a public reporting infrastructure. We found several significant associations between online ratings and community-level factors, suggesting these reviews may be a valuable source of information to consumers and policy makers.