Papers Containing Keywords(s): 'department'
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Alice Zawacki - 3
Viewing papers 1 through 10 of 23
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Working PaperMethodology on Creating the U.S. Linked Retail Health Clinic (LiRHC) Database
March 2023
Working Paper Number:
CES-23-10
Retail health clinics (RHCs) are a relatively new type of health care setting and understanding the role they play as a source of ambulatory care in the United States is important. To better understand these settings, a joint project by the Census Bureau and National Center for Health Statistics used data science techniques to link together data on RHCs from Convenient Care Association, County Business Patterns Business Register, and National Plan and Provider Enumeration System to create the Linked RHC (LiRHC, pronounced 'lyric') database of locations throughout the United States during the years 2018 to 2020. The matching methodology used to perform this linkage is described, as well as the benchmarking, match statistics, and manual review and quality checks used to assess the resulting matched data. The large majority (81%) of matches received quality scores at or above 75/100, and most matches were linked in the first two (of eight) matching passes, indicating high confidence in the final linked dataset. The LiRHC database contained 2,000 RHCs and found that 97% of these clinics were in metropolitan statistical areas and 950 were in the South region of the United States. Through this collaborative effort, the Census Bureau and National Center for Health Statistics strive to understand how RHCs can potentially impact population health as well as the access and provision of health care services across the nation.View Full Paper PDF
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Working PaperFull Report of the Comparisons of Administrative Record Rosters to Census Self-Responses and NRFU Household Member Responses
March 2023
Working Paper Number:
CES-23-08
One of the U.S. Census Bureau's innovations in the 2020 U.S. Census was the use of administrative records (AR) to create household rosters for enumerating some addresses when a self response was not available but high-quality ARs were. The goal was to reduce the cost of fieldwork during the Nonresponse Followup operation (NRFU). The original plan had NRFU beginning in mid-May and continuing through late July 2020. However, the COVID-19 pandemic forced the delay of NRFU and caused the Internal Revenue Service to postpone the income tax filing deadline, resulting in an interruption in the delivery of ARs to the U.S. Census Bureau. The delays were not anticipated when U.S. Census Bureau staff conducted the research on AR enumeration with the 2010 Census data in preparation for the 2020 Census or during the fine tuning of plans for using ARs during the 2018 End-to-End Census Test. These circumstances raised questions about whether the quality of the AR household rosters was high enough for use in enumeration. To aid in investigating the concern about the quality of the AR rosters, our analyses compared AR rosters to self-response rosters and NRFU household member responses at addresses where both ARs and a self-response were available.View Full Paper PDF
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Working PaperDeveloping Content for the Management and Organizational Practices Survey-Hospitals (MOPS-HP)
September 2021
Working Paper Number:
CES-21-25
Nationally representative U.S. hospital data does not exist on management practices, which have been shown to be related to both clinical and financial performance using past data collected in the World Management Survey (WMS). This paper describes the U.S. Census Bureau's development of content for the Management and Organizational Practices Survey Hospitals (MOPS-HP) that is similar to data collected in the MOPS conducted for the manufacturing sector in 2010 and 2015 and the 2009 WMS. Findings from cognitive testing interviews with 18 chief nursing officers and 13 chief financial officers at 30 different hospitals across 7 states and the District of Columbia led to using industry-tested terminology, to confirming chief nursing officers as MOPS-HP respondents and their ability to provide recall data, and to eliminating questions that tested poorly. Hospital data collected in the MOPS-HP would be the first nationally representative data on management practices with queries on clinical key performance indicators, financial and hospital-wide patient care goals, addressing patient care problems, clinical team interactions and staffing, standardized clinical protocols, and incentives for medical record documentation. The MOPS-HP's purpose is not to collect COVID-19 pandemic information; however, data measuring hospital management practices prior to and during the COVID-19 pandemic are a byproduct of the survey's one-year recall period (2019 and 2020).View Full Paper PDF
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Working PaperReleasing Earnings Distributions using Differential Privacy: Disclosure Avoidance System For Post Secondary Employment Outcomes (PSEO)
April 2019
Working Paper Number:
CES-19-13
The U.S. Census Bureau recently released data on earnings percentiles of graduates from post secondary institutions. This paper describes and evaluates the disclosure avoidance system developed for these statistics. We propose a differentially private algorithm for releasing these data based on standard differentially private building blocks, by constructing a histogram of earnings and the application of the Laplace mechanism to recover a differentially-private CDF of earnings. We demonstrate that our algorithm can release earnings distributions with low error, and our algorithm out-performs prior work based on the concept of smooth sensitivity from Nissim, Raskhodnikova and Smith (2007).View Full Paper PDF
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Working PaperLEHD Infrastructure S2014 files in the FSRDC
September 2018
Working Paper Number:
CES-18-27R
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2014 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifications made to the files to facilitate researcher access.View Full Paper PDF
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Working PaperOccupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.View Full Paper PDF
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Working PaperDeveloping a Residence Candidate File for Use With Employer-Employee Matched Data
January 2017
Working Paper Number:
CES-17-40
This paper describes the Longitudinal Employer-Household Dynamics (LEHD) program's ongoing efforts to use administrative records in a predictive model that describes residence locations for workers. This project was motivated by the discontinuation of a residence file produced elsewhere at the U.S. Census Bureau. The goal of the Residence Candidate File (RCF) process is to provide the LEHD Infrastructure Files with residence information that maintains currency with the changing state of administrative sources and represents uncertainty in location as a probability distribution. The discontinued file provided only a single residence per person/year, even when contributing administrative data may have contained multiple residences. This paper describes the motivation for the project, our methodology, the administrative data sources, the model estimation and validation results, and the file specifications. We find that the best prediction of the person-place model provides similar, but superior, accuracy compared with previous methods and performs well for workers in the LEHD jobs frame. We outline possibilities for further improvement in sources and modeling as well as recommendations on how to use the preference weights in downstream processing.View Full Paper PDF
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Working PaperCoverage and Agreement of Administrative Records and 2010 American Community Survey Demographic Data
November 2014
Working Paper Number:
carra-2014-14
The U.S. Census Bureau is researching possible uses of administrative records in decennial census and survey operations. The 2010 Census Match Study and American Community Survey (ACS) Match Study represent recent efforts by the Census Bureau to evaluate the extent to which administrative records provide data on persons and addresses in the 2010 Census and 2010 ACS. The 2010 Census Match Study also examines demographic response data collected in administrative records. Building on this analysis, we match data from the 2010 ACS to federal administrative records and third party data as well as to previous census data and examine administrative records coverage and agreement of ACS age, sex, race, and Hispanic origin responses. We find high levels of coverage and agreement for sex and age responses and variable coverage and agreement across race and Hispanic origin groups. These results are similar to findings from the 2010 Census Match Study.View Full Paper PDF
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Working PaperComparison of Survey, Federal, and Commercial Address Data Quality
June 2014
Working Paper Number:
carra-2014-06
This report summarizes matching of survey, commercial, and administrative records housing units to the Census Bureau Master Address File (MAF). We document overall MAF match rates in each data set and evaluate differences in match rates across a variety of housing characteristics. Results show that over 90 percent of records in survey data from the American Housing Survey (AHS) match to the MAF. Commercial data from CoreLogic matches at much lower rates, in part due to missing address information and poor match rates for multi-unit buildings. MAF match rates for administrative records from the Department of Housing and Urban Development are also high, and open the possibility of using this information in surveys such as the AHS.View Full Paper PDF
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Working PaperA COMPARISON OF PERSON-REPORTED INDUSTRY TO EMPLOYER-REPORTED INDUSTRY IN SURVEY AND ADMINISTRATIVE DATA
September 2013
Working Paper Number:
CES-13-47
The Census Bureau collects industry information through surveys and administrative data and creates associated public-use statistics. In this paper, we compare person-reported industry in the American Community Survey (ACS) to employer-reported industry from the Quarterly Census of Employment and Wages (QCEW) that is part of the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) program. This research provides necessary information on the use of administrative data as a supplement to survey data industry information, and the findings will be useful for anyone using industry information from either source. Our project is part of a larger effort to compare information on jobs from household survey data to employer-reported information. This research is the first to compare ACS job data to firm-based administrative data. We find an overall industry sector match rate of 75 percent, and a 61 percent match rate at the 4-digit Census Industry Code (CIC) level. Industry match rates vary by sector and by whether industry sector is classified using ACS or LEHD industry information. The educational services and health care and social assistance sectors have among the highest match rates. The management of companies and enterprises sector has the lowest match rate, using either ACS-reported or LEHD-reported sector. For individuals with imputed industry data, the industry sector match rate is only 14 percent. Our findings suggest that the industry distribution and the sample in a particular industry sector will differ depending on whether ACS or LEHD data are used.View Full Paper PDF
