Information on prevalence, use and spending by count of select chronic conditions among Original Medicare (or fee-for-service) beneficiaries.
Usage
cc_multiple(
year,
level = NULL,
sublevel = NULL,
fips = NULL,
age_group = NULL,
demographic = NULL,
subdemo = NULL,
mcc = NULL,
tidy = TRUE
)Format
- prevalence
Prevalence estimates are calculated by taking the beneficiaries within the MCC category divided by the total number of beneficiaries in the fee-for-service population, expressed as a percentage.
- tot_std_pymt_percap
Medicare standardized spending includes total Medicare payments for all covered services in Parts A and B and is presented per beneficiary (i.e. per capita). Standardized payments are presented to allow for comparisons across geographic areas in health care use among beneficiaries.
- tot_pymt_percap
Medicare spending includes total Medicare payments for all covered services in Parts A and B and is presented per beneficiary (i.e. per capita).
- hosp_readmsn_rate
Hospital readmissions are expressed as a percentage of all admissions. A 30-day readmission is defined as an admission to an acute care hospital for any cause within 30 days of discharge from an acute care hospital. Except when the patient died during the stay, each inpatient stay is classified as an index admission, a readmission, or both.
- er_visits_per_1k
Emergency department visits are presented as the number of visits per 1,000 beneficiaries. ED visits include visits where the beneficiary was released from the outpatient setting and where the beneficiary was admitted to an inpatient setting.
Arguments
- year
integer, YYYY, calendar year of Medicare enrollment. Run the helper function
cc_years()to return a vector of currently available years.- level
Geographic level of data; options are
"National","State", and"County"- sublevel
The state and/or county where the Medicare beneficiary resides. The values include the 50 United States, District of Columbia, Puerto Rico or U.S. Virgin Islands. Data aggregated at the National level are identified by "National'.
- fips
FIPS state and/or county code where the Medicare beneficiary resides. This column will be blank for data aggregated at the National level or for Puerto Rico and Virgin Islands.
- age_group
Population age level at which the data has been aggregated.
"All"includes all Fee-for-Service Medicare beneficiaries."<65"or"65+"returns data by those age groups.- demographic
Population demographic level at which the data has been aggregated.
"All"includes all Fee-for-Service Medicare beneficiaries."Sex"aggregates by beneficiary gender,"Race"by beneficiary race."Dual Status"aggregates by the beneficiary's dual eligibility status.- subdemo
For
Sex, a beneficiary’s sex is classified as Male or Female and is identified using information from the CMS enrollment database. ForRace, the race/ethnicity classifications are: Non-Hispanic White, Black or African American, Asian/Pacific Islander, Hispanic, and American Indian/Alaska Native. ForDual Status, beneficiaries can be classified as 'Medicare and Medicaid' or 'Medicare Only'. Beneficiaries enrolled in both Medicare and Medicaid are known as “dual eligibles.” Medicare beneficiaries are classified as dual eligibles if in any month in the given calendar year they were receiving full or partial Medicaid benefits.- mcc
To classify MCC for each Medicare beneficiary, the 21 chronic conditions are counted and grouped into four categories: -
"0 to 1"-"2 to 3"-"4 to 5"-"6+"- tidy
Tidy output; default is
TRUE.
Value
A tibble containing the search results.
Details
The Multiple Chronic Conditions dataset provides information on the number of chronic conditions among Original Medicare beneficiaries. The dataset contains prevalence, use and spending organized by geography and the count of chronic conditions from the set of select 21 chronic conditions. The count of conditions is grouped into four categories (0-1, 2-3, 4-5 and 6 or more).