Factors Affecting Response Rates to the Consumer Assessment of Health Plans Study Survey

Objectives. Assess the determinants of nonresponse to a consumer health care survey. Methods. The first (1997; CAHPS 1.0) and third (1999; CAHPS 2.0) Medicare managed care (MMC) CAHPS surveys collected data on 215 and 365 health plan reporting units, respectively. Data indicated which beneficiaries...

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Veröffentlicht in:Medical care 2002-06, Vol.40 (6), p.485-499
Hauptverfasser: Zaslavsky, Alan M., Zaborski, Lawrence B., Cleary, Paul D.
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Zaborski, Lawrence B.
Cleary, Paul D.
description Objectives. Assess the determinants of nonresponse to a consumer health care survey. Methods. The first (1997; CAHPS 1.0) and third (1999; CAHPS 2.0) Medicare managed care (MMC) CAHPS surveys collected data on 215 and 365 health plan reporting units, respectively. Data indicated which beneficiaries responded by mail, responded by phone, could not be located, and did not respond. Inter-Study data described plan characteristics. χ 2 tests and logistic regression models, adjusted for clustering by plan, were used to test associations of individual and plan characteristics with availability of good contact information and response given good contact information. Results. Response rates in the 1997 and 1999 surveys were 75% and 80%, respectively. Older and disabled beneficiaries, women, nonwhite beneficiaries, and persons living in areas with more residents who were nonwhite, on public assistance, and less educated had lower response rates. These associations were partly explained by the distribution of bad contact information, but even among beneficiaries who could be located plan response rates varied greatly. For-profit plans are significantly more likely to have high rates of bad contact information and lower response rates. Telephone follow-up improved the sociodemographic representativeness of the sample, for both high and low response rate plans. Conclusion. CAHPS-MMC survey procedures, in particular telephone follow-up, have resulted in high response rates, and current case-mix strategies compensate for some of the remaining effects of differing response rates on comparisons among plans. Further efforts to explore the determinants of response rates are warranted.
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Assess the determinants of nonresponse to a consumer health care survey. Methods. The first (1997; CAHPS 1.0) and third (1999; CAHPS 2.0) Medicare managed care (MMC) CAHPS surveys collected data on 215 and 365 health plan reporting units, respectively. Data indicated which beneficiaries responded by mail, responded by phone, could not be located, and did not respond. Inter-Study data described plan characteristics. χ 2 tests and logistic regression models, adjusted for clustering by plan, were used to test associations of individual and plan characteristics with availability of good contact information and response given good contact information. Results. Response rates in the 1997 and 1999 surveys were 75% and 80%, respectively. Older and disabled beneficiaries, women, nonwhite beneficiaries, and persons living in areas with more residents who were nonwhite, on public assistance, and less educated had lower response rates. These associations were partly explained by the distribution of bad contact information, but even among beneficiaries who could be located plan response rates varied greatly. For-profit plans are significantly more likely to have high rates of bad contact information and lower response rates. Telephone follow-up improved the sociodemographic representativeness of the sample, for both high and low response rate plans. Conclusion. CAHPS-MMC survey procedures, in particular telephone follow-up, have resulted in high response rates, and current case-mix strategies compensate for some of the remaining effects of differing response rates on comparisons among plans. Further efforts to explore the determinants of response rates are warranted.</description><identifier>ISSN: 0025-7079</identifier><identifier>EISSN: 1537-1948</identifier><identifier>DOI: 10.1097/00005650-200206000-00006</identifier><identifier>PMID: 12021675</identifier><language>eng</language><publisher>United States: J. B. 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Assess the determinants of nonresponse to a consumer health care survey. Methods. The first (1997; CAHPS 1.0) and third (1999; CAHPS 2.0) Medicare managed care (MMC) CAHPS surveys collected data on 215 and 365 health plan reporting units, respectively. Data indicated which beneficiaries responded by mail, responded by phone, could not be located, and did not respond. Inter-Study data described plan characteristics. χ 2 tests and logistic regression models, adjusted for clustering by plan, were used to test associations of individual and plan characteristics with availability of good contact information and response given good contact information. Results. Response rates in the 1997 and 1999 surveys were 75% and 80%, respectively. Older and disabled beneficiaries, women, nonwhite beneficiaries, and persons living in areas with more residents who were nonwhite, on public assistance, and less educated had lower response rates. These associations were partly explained by the distribution of bad contact information, but even among beneficiaries who could be located plan response rates varied greatly. For-profit plans are significantly more likely to have high rates of bad contact information and lower response rates. Telephone follow-up improved the sociodemographic representativeness of the sample, for both high and low response rate plans. Conclusion. CAHPS-MMC survey procedures, in particular telephone follow-up, have resulted in high response rates, and current case-mix strategies compensate for some of the remaining effects of differing response rates on comparisons among plans. Further efforts to explore the determinants of response rates are warranted.</description><subject>Age Distribution</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Consumer Behavior - statistics &amp; numerical data</subject><subject>Correspondence as Topic</subject><subject>Data Collection - methods</subject><subject>Ethnic Groups - statistics &amp; numerical data</subject><subject>Female</subject><subject>Health care surveys</subject><subject>Health Care Surveys - methods</subject><subject>Health surveys</subject><subject>Hispanics</subject><subject>Humans</subject><subject>Interviews as Topic - methods</subject><subject>Male</subject><subject>Managed care</subject><subject>Medicare</subject><subject>Medicare - statistics &amp; numerical data</subject><subject>Modeling</subject><subject>Regression analysis</subject><subject>Reproducibility of Results</subject><subject>Response rates</subject><subject>School surveys</subject><subject>Sex Distribution</subject><subject>Telephone</subject><subject>Telephones</subject><subject>United States - epidemiology</subject><issn>0025-7079</issn><issn>1537-1948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kUFvEzEQhS1UREPhH1SVT70tjO21vT5GEW2RKoFakLhZG--YpN3NBo-3Vf49bpOWE76M_Oa9sfUNY1zAJwHOfoZytNFQSQAJptyqJ8m8YTOhla2Eq5sjNitNXVmw7pi9J7oDEFZp-Y4dCwlSGKtn7NdFG_KYiM9jxJDXm9_8Bmk7bgj5TZuReB55XiFfFGkaMPE5ERINuMl8jPwK2z6v-Pe-3RC_zVO347dTesDdB_Y2tj3hx0M9YT8vvvxYXFXX3y6_LubXVVDWmqp2MnZQq7AMdgmNltBFGZpaCY1Wal0LK7SLXeNqE2IEVFiDUI1aYmtsiOqEne_nbtP4Z0LKflhTwL58CMeJvBXGOSdUMTZ7Y0gjUcLot2k9tGnnBfgnqv6Fqn-l-iyZEj07vDEtB-z-BQ8Yi6HeGx7HPmOi-356xORXz3D8_7ZVYqf72B2VHbyOVdY0Qjr1F8Zgipk</recordid><startdate>20020601</startdate><enddate>20020601</enddate><creator>Zaslavsky, Alan M.</creator><creator>Zaborski, Lawrence B.</creator><creator>Cleary, Paul D.</creator><general>J. 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Assess the determinants of nonresponse to a consumer health care survey. Methods. The first (1997; CAHPS 1.0) and third (1999; CAHPS 2.0) Medicare managed care (MMC) CAHPS surveys collected data on 215 and 365 health plan reporting units, respectively. Data indicated which beneficiaries responded by mail, responded by phone, could not be located, and did not respond. Inter-Study data described plan characteristics. χ 2 tests and logistic regression models, adjusted for clustering by plan, were used to test associations of individual and plan characteristics with availability of good contact information and response given good contact information. Results. Response rates in the 1997 and 1999 surveys were 75% and 80%, respectively. Older and disabled beneficiaries, women, nonwhite beneficiaries, and persons living in areas with more residents who were nonwhite, on public assistance, and less educated had lower response rates. These associations were partly explained by the distribution of bad contact information, but even among beneficiaries who could be located plan response rates varied greatly. For-profit plans are significantly more likely to have high rates of bad contact information and lower response rates. Telephone follow-up improved the sociodemographic representativeness of the sample, for both high and low response rate plans. Conclusion. CAHPS-MMC survey procedures, in particular telephone follow-up, have resulted in high response rates, and current case-mix strategies compensate for some of the remaining effects of differing response rates on comparisons among plans. Further efforts to explore the determinants of response rates are warranted.</abstract><cop>United States</cop><pub>J. B. Lippincott Williams and Wilkins Inc</pub><pmid>12021675</pmid><doi>10.1097/00005650-200206000-00006</doi><tpages>15</tpages></addata></record>
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subjects Age Distribution
Aged
Aged, 80 and over
Consumer Behavior - statistics & numerical data
Correspondence as Topic
Data Collection - methods
Ethnic Groups - statistics & numerical data
Female
Health care surveys
Health Care Surveys - methods
Health surveys
Hispanics
Humans
Interviews as Topic - methods
Male
Managed care
Medicare
Medicare - statistics & numerical data
Modeling
Regression analysis
Reproducibility of Results
Response rates
School surveys
Sex Distribution
Telephone
Telephones
United States - epidemiology
title Factors Affecting Response Rates to the Consumer Assessment of Health Plans Study Survey
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