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The American Journal of Managed Care October 2018
Putting the Pieces Together: EHR Communication and Diabetes Patient Outcomes
Marlon P. Mundt, PhD, and Larissa I. Zakletskaia, MA
Primary Care Physician Resource Use Changes Associated With Feedback Reports
Eva Chang, PhD, MPH; Diana S.M. Buist, PhD, MPH; Matt Handley, MD; Eric Johnson, MS; Sharon Fuller, BA; Roy Pardee, JD, MA; Gabrielle Gundersen, MPH; and Robert J. Reid, MD, PhD
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Stephen M. Shortell, PhD, MPH, MBA; Patricia P. Ramsay, MPH; Laurence C. Baker, PhD; Michael F. Pesko, PhD; and Lawrence P. Casalino, MD, PhD
Nudging Physicians and Patients With Autopend Clinical Decision Support to Improve Diabetes Management
Laura Panattoni, PhD; Albert Chan, MD, MS; Yan Yang, PhD; Cliff Olson, MBA; and Ming Tai-Seale, PhD, MPH
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Amanda S. Parsons, MD; Varna Raman, MBA; Bronwyn Starr, MPH; Mark Zezza, PhD; and Colin D. Rehm, PhD
Clinical Outcomes and Healthcare Use Associated With Optimal ESRD Starts
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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
Gatekeeping and Patterns of Outpatient Care Post Healthcare Reform
Michael L. Barnett, MD, MS; Zirui Song, MD, PhD; Asaf Bitton, MD, MPH; Sherri Rose, PhD; and Bruce E. Landon, MD, MBA, MSc

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.
Study Design and Study Sample

We used a cross-sectional study design in which the home health agency was the unit of analysis. The study sample consisted of Medicare-certified home health agencies in 50 states and the District of Columbia. Home health agencies with fewer than 60 patients were excluded because they were exempted from the HHCAHPS survey.1

Variables Measured

Dependent variables. The dependent variables are the 5 risk-adjusted agency-level patient experience measures from the 2 global questions and 3 composite measures extracted from CMS Home Health Compare. The HHCAHPS survey has 2 global questions; they include the “overall rating of care” provided by the home health agency (hereafter termed rating) and “patient willingness to recommend the home health agency to family or friends” (hereafter termed recommendation).29 The scale for rating in the survey ranges from 0 to 10. CMS reports the percentage of rating for an agency based on the percentage of patients who gave their home health care a rating of 9 or 10. The choices in the survey for recommendation include (1) definitely no, (2) probably no, (3) probably yes, and (4) definitely yes. The percentage of recommendation at the agency level is the number of patients who answered “definitely yes” divided by the total number of patients.

For the composite measures, CMS uses the data from the other 17 patient experience questions from the HHCAHPS survey. Each of these 3 measures is calculated from 4 or more topically related survey questions.1 The resulting composite measures include the following: “how often the home health team gives care in a professional way” (hereafter termed professional way), “how well the home health team communicates with patients” (hereafter termed communication), and whether or not the “home health team discuss[ed] medicines, pain, and home safety with patients” (hereafter termed discussion). The HHCAHPS survey website provides detailed information for the composite measures.29

The risk-adjusted global and composite measures for patient experience at the agency level are measured as a percentage. A higher percentage of patient experience measures indicates that the patients perceive higher-quality care from home health agencies.

Key independent variables. The key independent variable is the agency-level HCC risk score, extracted from PUPDHHA.26 The agency-level HCC risk score is the sum of CMS HCC risk scores from individual Medicare home health beneficiaries divided by the total number of Medicare home health beneficiaries for an individual home health agency.28 CMS constructs a CMS HCC risk score for an individual Medicare home health beneficiary as a risk factor to calculate a beneficiary’s likelihood of unplanned hospitalization and emergency department visits within 60 days of home health care for public reporting.30 The CMS HCC risk score for an individual Medicare home health beneficiary is a function of the beneficiary’s age, gender, original reason for Medicare entitlement, prior care setting, clinical conditions from CMS HCC, and their interaction terms. The CMS website provides detailed information about the CMS HCC risk score for home health beneficiaries.31,32

Control variables. In addition to the average CMS HCC risk score at the agency level, previous studies show that beneficiaries of different races/ethnicities rate their respective patient experience surveys differently.19,20,25 Therefore, we included variables describing the percentage of beneficiaries who were African American, Hispanic, and of other racial group, which includes beneficiaries who were not white, African American, or Hispanic. Finally, because the characteristics of home health agencies are associated with the quality of care provided,33,34 we included 2 dummy variables for ownership of a home health agency (ie, not-for-profit and public home health agencies, with for-profit home health agencies as the reference group) and the number of years that home health agencies had been certified by the Medicare program in the analytical models.


Home health agencies practice within a given state, facing that state’s regulations, which may differ from those of other states. Additionally, there is high variation in home health utilization across states, with $176 per beneficiary per year for the states at the 10th percentile and $866 per beneficiary per year for those at the 90th percentile.35 We applied fixed-effects models at the state level, with robust standard errors for each patient experience measure to account for differences in regulations and other state characteristics that affect the practice of home health agencies. Stata 14.2 (StataCorp; College Station, Texas) was used for data management and analyses. We used xtreg for the fixed-effects model.

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