Data Limitations in the UDS Mapper.

Transcription

1 Data Limitations in the UDS Mapper

2 Data Limitations in the UDS Mapper 2 Acronyms Used in This Lesson Acronym ACS HCP UDS ZCTA What It Stands For American Community Survey Health Center Program Uniform Data System ZIP Code Tabulation Area

3 Data Limitations in the UDS Mapper 3 Patient Data Limitations Patient data are only from HCP grantees and look-alikes that report into the UDS Areas that appear underserved may actually be served by another provider type Data suppression Health centers are not to report ZIP Codes where fewer than 11 of their patients reside, so those patients are excluded from the ZCTA patient count

4 Data Limitations in the UDS Mapper 4 Income Level Data Limitations (1) The UDS does not contain income information on patients by ZIP Code Therefore, all calculations comparing patients and low-income population data are only estimates they should only be used as a starting point In the UDS Mapper it is assumed that 100% of HCP patients are lowincome (nationally, 92.0% of grantee and 91.9% of look-alike patients are low-income) For each ZCTA, the HCP: Penetration of Low-Income (%) percentage is estimated by dividing the number of reported UDS patients by the lowincome population from the Census Bureau s 5-year ACS

5 Data Limitations in the UDS Mapper 5 Income Level Data Limitations (2) In some scenarios, the low-income penetration is overestimated, and may even exceed 100%: If patients are not low-income (most often in rural areas) If patients are migrant or homeless, because these populations are not well-counted in the ACS Areas where there are multiple HCP organizations seeing the same patients (one health center offers a service the other one does not)

6 Data Limitations in the UDS Mapper 6 Geography Limitations Patients are reported by ZIP Code, not by address Therefore the data can only be shown at the ZCTA level, not at a finer level such as census tract Additionally, ZCTAs often cross county and state lines, therefore the data cannot be precisely aggregated to county or state reports See this diagram of Census Bureau-created geographies:

7 Data Limitations in the UDS Mapper 7 UDS and Population Data Limitations Comparing patient data to population data from different years The UDS patient data and ACS population data are updated on different schedules Between the summer when patient data are updated and late winter when population data are updated comparisons of patient data to population (i.e., penetration rates) will be using data from different years

8 Data Limitations in the UDS Mapper 8 Insurance Type Limitations These population data are estimated for ZCTAs The data are limited by the population data used to break down the categories The data can only break down into Uninsured; Medicaid or Other Public Insurance; and Medicare or Private Insurance categories Patient by insurance type is assumed to be current status

9 Data Limitations in the UDS Mapper 9 ZIP Code/ZCTA Limitations Changing/evolving ZIP Code boundaries: ZIP Codes change at the US Postal Service s discretion, but ZCTAs are updated less frequently Solution: ZIP Code layer is updated annually so that every reported ZIP Code matches the ZCTA that best fits that location Data are never left out of counts or analyses due to a new or changed ZIP Code

10 Data Limitations in the UDS Mapper 10 Estimated Data Limitations Not all data providers publish data at the ZCTA level so these data are estimated to that level: Includes Population Indicators data and population by insurance type data For these estimates, data at the state, county, or lower level are combined with census block population data and imputed to the ZCTA level Remember, these are estimates and should only be used as a starting point

11 Data Limitations in the UDS Mapper 11 End of Lesson Proceed to the next lesson to continue learning how to use the UDS Mapper