Dataset Information

Telephone health survey estimates: Effects of nonresponse and sample limitations.

ABSTRACT:

Objective

The objective of this study was to assess nonresponse error in telephone health survey data based on an address-based sample.

Data sources

Telephone and in-person interviews in Greater Boston.

Study design/data collection

Interviewers attempted telephone interviews at addresses that were matched to telephone numbers using questions drawn from federal health surveys. In-person household interviews were carried out with telephone nonrespondents and at addresses without matching telephone numbers.

Principal findings

After adjusting for demographic differences, only eight of 15 estimates based on the telephone interviews lay within two standard errors of the estimates when data from all three groups were included.

Conclusions

For health surveys of address-based samples, many estimates based on telephone respondents differ from the total population in ways that cannot be corrected with simple demographic adjustments.

SUBMITTER: Fowler FJ

PROVIDER: S-EPMC6505407 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Telephone health survey estimates: Effects of nonresponse and sample limitations.

Fowler Floyd J FJ Brenner Philip S PS Buskirk Trent D TD Roman Anthony A

Health services research 20190118 3

<h4>Objective</h4>The objective of this study was to assess nonresponse error in telephone health survey data based on an address-based sample.<h4>Data sources</h4>Telephone and in-person interviews in Greater Boston.<h4>Study design/data collection</h4>Interviewers attempted telephone interviews at addresses that were matched to telephone numbers using questions drawn from federal health surveys. In-person household interviews were carried out with telephone nonrespondents and at addresses with ...[more]

PMID: 30657170

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Project description:ObjectivesWe provide new estimates on size, composition and distribution of human resource for health in India and compare with the health workers population ratio as recommended by the WHO. We also estimate size of non-health workers engaged in health sector and the size of technically qualified health professionals who are not a part of the health workforce.DesignNationally representative cross-section household survey and review of published documents by the Central Bureau of Health Intelligence.SettingNational.ParticipantsHead of household/key informant in a sample of 101 724 households.InterventionsNot applicable.Primary and secondary outcome measuresThe primary outcome was the number and density of health workers,and the secondary outcome was the percentage of health workers who are technically qualified and the percentage of individuals technically qualified and not in workforce.ResultsThe total size of health workforce estimated from the National Sample Survey (NSS) data is 3.8 million as of January 2016, which is about 1.2 million less than the total number of health professionals registered with different councils and associations. The density of doctors and nurses and midwives per 10 000 population is 20.6 according to the NSS and 26.7 based on the registry data. Health workforce density in rural India and states in eastern India is lower than the WHO minimum threshold of 22.8 per 10 000 population. More than 80% of doctors and 70% of nurses and midwives are employed in the private sector. Approximately 25% of the currently working health professionals do not have the required qualifications as laid down by professional councils, while 20% of adequately qualified doctors are not in the current workforce.ConclusionsDistribution and qualification of health professionals are serious problems in India when compared with the overall size of the health workers. Policy should focus on enhancing the quality of health workers and mainstreaming professionally qualified persons into the health workforce.

Project description:BACKGROUND:With India preparing for the next decennial Census in 2021, we compared the disability estimates and data collection methodology between the Census 2011 and the most recent population-level survey for India and its states, to highlight the issues to be addressed to improve robustness of the disability estimates in the upcoming Census. METHODS:Data from the Census 2011 and from two complementary nationally representative household surveys that covered all Indian states with the same methodology and survey instruments-the District-Level Household Survey-4 (DLHS-4, 2012-2013) and the Annual Health Surveys (AHS three rounds, 2010-11, 2011-12 and 2012-13) were used. Data from DLHS-4 and AHS 2012-13 round were pooled to generate estimates for the year 2012-13. Data collection methodology between the sources was compared, including the review of definitions of each type of disability. The overall, mental, visual, hearing, speech, and movement disability rate (DR) per 100,000 population were compared between the sources for India and for each state, and the percent difference in the respective rates was calculated. We explored the reliability of these estimates comparing yearly data from the AHS for three successive rounds. RESULTS:Survey data were collected through proxy reporting, however, it is not entirely clear whether the data were proxy- or self-reported or a mix of both in the Census. The overall DR was 25.1% higher in the Census (2,242; 95% CI 2,241-2,243) than the survey (1,791; 95% CI 1,786-1,797) per 100,000 population, with the state-level difference ranging from -64% in Tamil Nadu to 107% in Sikkim state. Despite both sources using nearly similar definitions for overall disability and disability by type, the difference in DR was 125.5%, 54.2%, -25.7%, -19.7%, and 21.9% for hearing, speech, mental, movement, and visual DR, respectively. At the state-level, the difference in disability-specific estimates ranged from -84% to 450%. The extent of variations in the disability-specific estimates in AHS successive rounds ranged from -25% to 929% at the state-level. CONCLUSIONS:There is momentum globally towards building disability measurement that is consistent with the data required for monitoring of the Sustainable Development Goals to ensure robust estimation of disability. The current estimates from the Census and surveys seem much lower than would be expected at the population level. We make recommendations that India needs to take serious note of in order to improve the validity and reliability of India's disability estimates.

Dataset Information

Telephone health survey estimates: Effects of nonresponse and sample limitations.

Objective

Data sources

Study design/data collection

Principal findings

Conclusions

Publications

Telephone health survey estimates: Effects of nonresponse and sample limitations.

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