An important objective of the Successful Employment for Persons with Disabilities in Iowa project was its focus on reviewing as many accessible data sources as potentially possible within the time-frame of the DSPG program. The result of this was a survey of data sets that focused on Iowans with disabilities and exploring whether the information contained could be used to provide insight to persons with disabilities and employment in Iowa.
Of all the data sources pertaining to persons with a disability (PWD) in Iowa, the ACS includes the most fundamental and complete data set for providing a contextual overview to PWDs. For this reason, this section will document how the ACS data is structured for this particular project.
In the sections which pertain to disability, the ACS primary collects data on six different kinds of difficulty.
On questions of Employment & Income, B18120, B18121, B18140, contain information on:
On questions of Poverty, B18130, B18131, B21007, B23024 contain information on:
On questions of Insurance & Service, B18135, B21100, B22010 contain information on:
On questions regarding General Age and Sex can be found from B18101 – B18107. Additionally on the question of Age, B18108, B26108, B26208 contain information on:
One Miscellaneous Category is B10052, which contains information on:
Tables that are outside of the difficulties categories are created using a combination of different questions of the ACS Questionnaires. Employment information for Persons with Disabilities comes from a combination of the Employment, Poverty, Commute, and Disability answers that surveyors respond to when filling the questionnaire.
Because of a physical, mental, or emotional condition, does this person have difficulty doing errands alone such as visiting a doctor’s office or shopping? Questions on Poverty (Fill Value Questions).
This data set was used as a comparative supplement to the ACS data set. It contains information matching ACS questionnaires on Disability Status, Age and Type. The geographic scope of this survey is by the county level and the survey is conducted through telephone.
For the purposes of this project, we focused exclusively on the survey questions that related to the Mental Health sections. This information was taken from the National Survey on Drug Use and Health and the geographic scope of this data was by sub-state regions rather than county.
For the assessment of public services, the IVRS data set on Closed Iowa Vocational Rehabilitation Cases was an invaluable resource. This data set had two potential geographic information provided about the clients of the IVRS. The first of these are the office locations that the clients were receiving services from. The second was the location of the client at the end of their services. By calculating the number of employment and the changes in wages for each client, we tried to assess how functional the offices were at helping clients with their employment.
More information on the IVRS data set can be found in the Services section of the documentation.
For the assessment of public expenditures, we relied on the MDHS regional data sets to learn more about Expenditures, Persons Served, and Unduplicated Persons Served by Service. Due to the way that the data is organized, it took a lot of time to be able to collect all of the MHDS regions into one data table, preventing us from looking at all possible years. The geography of this data set is available for MHDS regions which are not as granular as county data but more so than SAMSHA or IVRS regions.
Another assessment of public services utilized the Successful Employment for Blind Iowans by Federal Fiscal Year data set from the Iowa Data portal. Unfortunately, the data was last updated for the years of 2016 since 2012, but much like the IVRS data, it contains information regarding hourly wage changes and earnings. The data set does not contain any geographical information.
For county level expenditures, we focused on data that was provided by the Iowa Department of Management which listed both budgeted and actual expenditures for counties in Iowa. Since they were separate data tables, the process was to first clean and merge them together to later map. We focused on two variables for expenditures; Physical Health and Social Services.
As a public service, this data set provided us with numbers of people and amounts in dollars for all of the people that received OASDI benefits by county. This information is also disaggregated by workers, spouses and children with disabilities or to these respective demographics as a result of someone with a disability in the household.
The following are data sets were reviewed but not utilized due to a number of reasons. Most prominently, data complexity, time-frame of the project, or thematic differences to employment affected our interest and ability to utilize the following data.
Tier One data sets are ones that overall matched the
thematic interest of the project and would have been investigated
further given more available time for the project.
This data set is based off of the information provided by the Bureau of Labor Statistics and has the ASEC (Annual Social and Economic Supplement) Public Use Data Dictionary containing questions on income and employment for people with disabilities. This data set was not explored due to a lack of time and potential complexities in having to calculate weighted values.
The PUMS data uses the information collected by the ACS data in order to allow for users to cross-check information that pre-tabulated data products by the ACS don’t depict. Due to sample size causing potential reliability errors and a learning curve with the PUMS API, we decided to focus more on the ACS with our limited time.
These data sets were ones that matched the thematic scope of the project in terms of disability, but did not necessarily contain information on employment, or data accessibility and complexity were a concern.
This data set contains information on households with disabilities by disability type which contains potential for comparison with other sets of information in the ACS. The difficulties with this data set were that the survey information was only gathered for particular areas of states.
The SIPP is a nationally representative longitudinal survey that provides information on income, employment, households and government participation programs. The code book for the questionnaires indicates that there are a number of disability related questions. The data set doesn’t calculate weights and since this has to be done manually we decided to not utilize the data set for its complexity.
This data set contains a column of reasons for why employees were separated in the Iowa Executive Branch. One of the possible reasons indicated is Disability and Mental Health. The data set has no particular geographic scope and for lack of priority on other datasets, was not utilized.
This data set contains information on discrimination complaint cases processed by a local agency. Data includes type of closure, dates when case was opened and closed, and basis of complaints received. The clients indicate whether their cases are related to a disability or not. Data doesn’t have a geography and no granular information besides the complaints are provided.
This Medicaid employment data table covers information from July and October of 2020 as well as April and October of 2021. There is no specific geographic scope for this data set and we were unable to look further into these tables for lack of time.
This data set contains detailed questionnaires on health characteristics by demographic and socioeconomic characteristics, including information on people with disabilities. The difficulty in this data set was accessibility and the lack of geographic scope.
This data set contains numbers of federal prisoners in Iowa which are reported to have disabilities disaggregated by similar difficulty types to the ACS data. The data is from 2016 and with limited time for the program, this data set was not utilized for its lack of employment focus for this project.
Contains a data set on Crime Against Persons with Disabilities from the years 2009 to 2019. Since it doesn’t contain any information on employment and the geography is at a national level, this data set was not utilized.
The BLS collects only labor force data at the county level for states. Unfortunately, the information collected by the BLS doesn’t include whether a person has disabilities or not. This was why the data was not utilized.
This data set has specific information about children from ages 3 - 21 in need of special education at the state level. Because of its geographic scope at the state level and its data not connecting to employment, we chose to prioritize other data sets.
Data set was inaccessible until later, this data set was not utilized due to a lack of time.