Literature DB >> 12629920

Impact of differential response rates on the quality of data collected in the CTS physician survey.

Julie A Schoenman, Marc L Berk, Jacob J Feldman, Andrew Singer.   

Abstract

Survey administrators face trade-offs between expending additional survey resources to maximize response rates versus using fewer resources and accepting lower response rates. Using data from the Community Tracking Study's Physician Survey, we examined how survey estimates and data quality changed as additional respondents completed the survey. Results showed that improvements in response rates over the range examined (i.e., up to 65%) did not change estimates appreciably nor affect data quality. As long as these results are not overstated to imply that extremely low response rates are credible, this study may permit researchers to disseminate interesting results in peer-reviewed journals even when the response rate falls slightly short of current standards. It must also be emphasized, however, that we were unable to measure the nonresponse effect of those who were never interviewed. Achieving a response rate significantly above 65% might have changed the survey results appreciably.

Mesh:

Year:  2003        PMID: 12629920     DOI: 10.1177/0163278702250077

Source DB:  PubMed          Journal:  Eval Health Prof        ISSN: 0163-2787            Impact factor:   2.651


  12 in total

1.  Predictors of the growing influence of clinical practice guidelines.

Authors:  Ann S O'malley; Hoangmai H Pham; James D Reschovsky
Journal:  J Gen Intern Med       Date:  2007-03-27       Impact factor: 5.128

2.  Measuring Integration of Cancer Services to Support Performance Improvement: The CSI Survey.

Authors:  Mark J Dobrow; Lawrence Paszat; Brian Golden; Adalsteinn D Brown; Eric Holowaty; Margo C Orchard; Neerav Monga; Terrence Sullivan
Journal:  Healthc Policy       Date:  2009-08

3.  Access to electronic health records by care setting and provider type: perceptions of cancer care providers in Ontario, Canada.

Authors:  Margo C Orchard; Mark J Dobrow; Lawrence Paszat; Hedy Jiang; Patrick Brown
Journal:  BMC Med Inform Decis Mak       Date:  2009-08-10       Impact factor: 2.796

4.  The "medicine in Australia: balancing employment and life (MABEL)" longitudinal survey--protocol and baseline data for a prospective cohort study of Australian doctors' workforce participation.

Authors:  Catherine M Joyce; Anthony Scott; Sung-Hee Jeon; John Humphreys; Guyonne Kalb; Julia Witt; Anne Leahy
Journal:  BMC Health Serv Res       Date:  2010-02-25       Impact factor: 2.655

5.  Do additional recontacts to increase response rate improve physician survey data quality?

Authors:  Gordon B Willis; Tenbroeck Smith; Hyunshik J Lee
Journal:  Med Care       Date:  2013-10       Impact factor: 2.983

6.  Intraurban influences on physician colorectal cancer screening practices.

Authors:  Sherri Sheinfeld Gorin; Alfred R Ashford; Rafael Lantigua; Farida Hajiani; Rebeca Franco; Julia E Heck; Donald Gemson
Journal:  J Natl Med Assoc       Date:  2007-12       Impact factor: 1.798

7.  Effects of changes in incomes and practice circumstances on physicians' decisions to treat charity and Medicaid patients.

Authors:  Peter J Cunningham; Jack Hadley
Journal:  Milbank Q       Date:  2008-03       Impact factor: 4.911

8.  Implementing academic detailing for breast cancer screening in underserved communities.

Authors:  Sherri Sheinfeld Gorin; Alfred R Ashford; Rafael Lantigua; Manisha Desai; Andrea Troxel; Donald Gemson
Journal:  Implement Sci       Date:  2007-12-17       Impact factor: 7.327

9.  A randomised trial and economic evaluation of the effect of response mode on response rate, response bias, and item non-response in a survey of doctors.

Authors:  Anthony Scott; Sung-Hee Jeon; Catherine M Joyce; John S Humphreys; Guyonne Kalb; Julia Witt; Anne Leahy
Journal:  BMC Med Res Methodol       Date:  2011-09-05       Impact factor: 4.615

10.  Response audit of an Internet survey of health care providers and administrators: implications for determination of response rates.

Authors:  Mark J Dobrow; Margo C Orchard; Brian Golden; Eric Holowaty; Lawrence Paszat; Adalsteinn D Brown; Terrence Sullivan
Journal:  J Med Internet Res       Date:  2008-10-16       Impact factor: 5.428

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