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Notice

Proposed Information Collection; Comment Request; Comparing Health Insurance Measurement Error (CHIME)

Document Details

Information about this document as published in the Federal Register.

Published Document

This document has been published in the Federal Register. Use the PDF linked in the document sidebar for the official electronic format.

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AGENCY:

U.S. Census Bureau, Commerce.

ACTION:

Notice.

SUMMARY:

The Department of Commerce, as part of its continuing effort to reduce paperwork and respondent burden, invites the general public and other Federal agencies to take this opportunity to comment on proposed and/or continuing information collections, as required by the Paperwork Reduction Act of 1995.

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DATES:

To ensure consideration, written comments must be submitted on or before January 16, 2015.

ADDRESSES:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

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FOR FURTHER INFORMATION CONTACT:

Requests for additional information or copies of the information collection instrument(s) and instructions should be directed to Joanne Pascale, 301-763-4920, joanne.pascale@census.gov.

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SUPPLEMENTARY INFORMATION

I. Abstract

This study is designed to assess reporting accuracy in surveys that measure health insurance. Several federal, state and private surveys measure health insurance coverage, but have different origins and methodological approaches, and serve different purposes. They also produce different estimates of coverage, and few studies have assessed reporting accuracy across surveys. Previous research indicates that much of the variation in the estimates is rooted in subtle differences in the questionnaires. A common strategy for assessing the validity of a self-reported measure from a survey is a reverse “record check” study in which administrative records are assumed to contain the correct status on a given measure (e.g., health insurance coverage). Contact information from the records is used as sample to conduct a survey in which the same information, in this case health insurance, is asked about. Data from the records is then compared to the answers from the survey to assess reporting accuracy.

The proposed study will survey a sample of people enrolled in Medica Health Plans (a Minnesota based health insurance plan) whose coverage type is known from the records to be Medicaid, MinnesotaCare, employer-sponsored insurance, non-group coverage within the marketplace (called MNSure) or non-group coverage outside the marketplace. The sample will be randomly assigned to one of two questionnaire modules on health insurance—the newly-redesigned Current Population Survey Annual Social and Economic Supplement (CPS) or the American Community Survey (ACS)—in order to contrast reporting error across different questionnaire versions. For analysis, the level of agreement between the data from the records and the survey report is referred to as “absolute accuracy,” and the comparison of absolute accuracy for any given survey to the absolute accuracy for a different survey is referred to as “relative accuracy.”

In order to minimize respondent burden but still mimic actual survey conditions of the CPS and ACS to an extent, the survey includes a short subset of questions from those surveys in order to set the context for the health insurance modules. Thus typical questions on demographics (e.g.: age, race, education), employment status, government program participation will precede the health insurance questions.

II. Method of Collection

The study will consist of a computer-assisted telephone interview (CATI) conducted by Census Bureau interviewers from the Hagerstown, Md., call center. Sample is being provided by Medica Research Institute (MRI), an affiliate of Medica Health Plans, based in Minnesota. Medica will mail an advance letter to enrollees from among five different markets: Medicaid, MinnesotaCare (a state-specific program for low income), employer-sponsored insurance, direct purchase through the marketplace, and direct purchase outside the marketplace. The letter will explain that Medica has partnered with the Census Bureau on a study, and it will invite enrollees who do not wish to participate to opt-out by calling in to the Medica call center. Medica will then draw a sample from among enrollees who did not opt out for transfer to the Census Bureau. Data collection is to take place from late February through early April, 2015, in order to mimic the actual time frame of the CPS ASEC.

III. Data

OMB Control Number: 0607-XXXX.

Form Number(s): Not yet assigned.

Type of Review: Regular submission.

Affected Public: Medica enrollees and their household members.

Estimated Number of Respondents: 5,000 household respondents.

Estimated Time per Response: 13 minutes.

Estimated Total Annual Burden Hours: Interviewing: 5,000 household cases * 13 minutes/case = 1,083 hours; Contact attempts not resulting in completed interviews = 11,667 cases * 10 seconds/case = 1,945 hours; Total = 3,028 hours.

Estimated Total Annual Cost to Public: $0.

Respondent's Obligation: Voluntary.

Legal Authority: Title 13 U.S.C. Section 182.

IV. Request for Comments

Comments are invited on: (a) Whether the proposed collection of information is necessary for the proper performance of the functions of the agency, including whether the information shall have practical utility; (b) the accuracy of the agency's estimate of the burden (including hours and cost) of the proposed collection of information; (c) ways to enhance the quality, utility, and clarity of the information to be collected; and (d) ways to minimize the burden of the collection of information on respondents, including through the use of automated collection techniques or other forms of information technology.

Comments submitted in response to this notice will be summarized and/or included in the request for OMB approval of this information collection; they also will become a matter of public record.

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Dated: November 12, 2014.

Glenna Mickelson,

Management Analyst, Office of the Chief Information Officer.

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[FR Doc. 2014-27085 Filed 11-14-14; 8:45 am]

BILLING CODE 3510-07-P