Are online reviews of assisted living communities associated with patient-centered outcomes?

Home time and state regulations among Medicare beneficiaries in assisted living communities

BACKGROUND

Home time is an important patient-centric quality metric, which has been largely unexamined among assisted living (AL) residents. Our objectives were to assess variation in home time among AL residents in the year following admission and to examine the associations with state regulations for direct care workers (DCW) training and staffing and for licensed nurse staffing.

METHODS

Medicare beneficiaries who entered AL communities in 2018 were identified, and their home time in the year following admission was measured. Home time was calculated as the percentage of time spent at home per day being alive. Resident characteristics and state regulations in DCW staffing, DCW training, and licensed staffing were measured. We used a multivariate linear regression model with AL-level fixed effects to estimate the relationship between person-level characteristics and home time. Linear regression models adjusting for resident characteristics were used to estimate the association between state regulations and residents' home time.

RESULTS

The study sample included 59,831 new Medicare beneficiary residents in 12,143 ALs. In the year following AL admission, residents spent 94% (standard deviation = 14.6) of their time at home. Several resident characteristics were associated with lower home time: Medicare-Medicaid dual eligibility, having more chronic conditions, and specific chronic conditions, for example, dementia. In states with greater regulatory specificity for DCW training and staffing, and lower specificity for licensed staffing, residents had longer adjusted home time.

CONCLUSION/IMPLICATIONS

Home time varied substantially among AL residents depending on resident characteristics and state-level regulatory specificity. AL residents eligible for Medicare and Medicaid had substantially shorter home time than the Medicare-only residents, largely due to longer time spent in nursing homes. State AL regulatory specificity for DCWs and licensed staff also impacted AL residents' home time. These findings may guide AL operators and state legislators in efforts to improve this important quality of life metric.

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.