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CMS HCC Risk Scores and Home Health Patient Experience Measures
Hsueh-Fen Chen, PhD; J. Mick Tilford, PhD; Fei Wan, PhD; and Robert Schuldt, MA
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CMS HCC Risk Scores and Home Health Patient Experience Measures

Hsueh-Fen Chen, PhD; J. Mick Tilford, PhD; Fei Wan, PhD; and Robert Schuldt, MA
Risk adjustment for patient experience measures needs to be modified by including the CMS Hierarchical Condition Categories (HCC) risk scores of home health beneficiaries.
We also observed that increases in the percentage of African Americans and other racial/ethnic minority populations were negatively associated with patient experience measures, with 1 exception (discussion). Our findings are consistent with evidence from a recent patient-level study, which indicated that minority home health beneficiaries had lower patient experience rates in professional way and communication than home health beneficiaries who were non-Hispanic whites.25 Evidence from the same study also showed that Hispanic, African American, Asian, and Native Hawaiian or Pacific Islander home health beneficiaries had better experience measures in discussion than the non-Hispanic white population.25 The coefficients for discussion in our study are positive but not statistically significant. It is unclear why minorities gave a high rating for their home health providers discussing medicines, pain, and home safety but gave a low rating for the other measures. This may be explained by cultural differences among racial/ethnic groups regarding pain tolerance and differing attitudes among patients or informal caregivers about medication or patient safety. However, future studies that focus on the cultural differences affecting the rating of patient experience are needed.

Evidence from other studies showed that compared with not-for-profit agencies, for-profit agencies provided higher-cost and lower-quality home health care, including worsened process of care, poor functional improvement, and high rates of avoidable hospitalizations and bedsores.33 Our study found that compared with public and not-for-profit agencies, for-profit agencies had poorer patient experience performance in all 5 measures. We also found that increases in the number of tenured years with the Medicare program increased patient experience measures by about 0.01% to 0.04%. Over the past decade, the number of home health agencies increased dramatically, from about 7500 in 2000 to about 12,400 in 2014. This increase was partly due to the high profit margin from therapy visits in the Medicare home health payment system.7 Among all new home health agencies, 95% were for-profit entities, which are more likely to target therapy visits with high profit margins.34 The Medicare program is the primary payer for home health care and paid about $18 billion in 2015.7 The Medicare program strives to improve the quality and efficiency of care for Medicare home health beneficiaries. However, with the high cost and lower quality of care associated with for-profit agencies and with the rapidly growing number of for-profit agencies, CMS’ efforts to improve quality while controlling rising home health costs are limited because the license approval system and regulations for home health agencies occur at the state level. To overcome this problem, both payment reforms at the federal level and modifications at the state level for licensure and regulation are necessary to improve the quality and control the cost of home health care.

Limitations

Our study has limitations. First, we used data at the agency level. The patient experience measures are based on the HHCAHPS survey from nonhospice, nonmaternity home health patients who are 18 years or older.39 However, CMS HCC risk scores are based on Medicare beneficiaries who are 65 years or older.31,32 Although the sources of patient data provided by the HHCAHPS survey and the CMS HCC risk score were not completely the same, the majority of home health beneficiaries in our sample were Medicare beneficiaries who were 65 years or older11 and were more likely to be in the random sampling of the HHCAHPS survey. Therefore, the inconsistent patient sources among the HHCAHPS survey and CMS HCC risk scores are less likely to affect the estimates in our study. However, we recommend that future studies use patient-level data to examine CMS HCC risk scores and patient experience measures.

Secondly, due to missing data, we excluded 119 home health agencies that qualified for the HHCAHPS survey. These agencies were more likely to be for-profit home health agencies with lower patient volume than those included in our study. Additionally, the HHCAHPS survey exempted home health agencies that had fewer than 60 patients per year, and thus these agencies were excluded from our study.

CONCLUSIONS

Our findings have research and policy implications that apply to the 5-star patient survey rating system and the HHVBP pilot program. In terms of research, access to care for minorities and beneficiaries with complicated clinical conditions needs to be carefully monitored under the 5-star patient survey rating system and the HHVBP pilot program. Additionally, it is necessary to investigate the practice patterns of home health agencies and the home health market and to determine how home health agencies with a high proportion of beneficiaries who have advanced clinical and functional conditions fare. In terms of policy implications, the current risk factors used to adjust patient experience measures need to be modified. The CMS HCC risk score is based on Medicare home health beneficiaries’ enrollment data and inpatient and outpatient claims data.30 The enrollment data are collected by CMS, and inpatient and outpatient claims data are provided by hospitals and physicians, so there is little chance for home health agencies to practice upcoding that may affect the CMS HCC risk score. Thus, it is feasible to include the CMS HCC risk score of a home health beneficiary as a risk factor in the current risk adjustment for patient experience measures in an effort to avoid potential unintended consequences.

Acknowledgments

The authors thank Madison Hedrick, MA, of the Science Communication Group at the University of Arkansas for Medical Sciences, who provided editing for the original version of the manuscript.

Author Affiliations: Department of Health Policy and Management (H-FC, JMT, RS), and Department of Biostatistics (FW), College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR.

Source of Funding: None.

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (H-FC, FW); acquisition of data (H-FC, RS); analysis and interpretation of data (JMT, FW); drafting of the manuscript (H-FC, JMT); critical revision of the manuscript for important intellectual content (H-FC, JMT, FW, RS); statistical analysis (H-FC); and provision of patients or study materials (RS).

Address Correspondence to: Hsueh-Fen Chen, PhD, Department of Health Policy and Management, College of Public Health, University of Arkansas for Medical Sciences, 4301 W Markham St, Mail Slot 820-12, Little Rock, AR 72205. Email: hchen@uams.edu.
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