PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 10528577

Chartbook. Quality checkup.

T Hudson
View original source ↗Export metadata ↓

Abstract

With hospital quality programs, the reach is broad, not deep. So says the National Hospital Quality Improvement Survey, conducted by health care researcher Stephen Shortell for Arthur Andersen and the American Hospital Association. Though 93 percent of responding hospitals and health systems use CQI and TQM methods is some fashion, they've taught them to only 35 percent of employees and a scant 22 percent of doctors on their medical staffs. Those poor showings leave health care lagging behind most other industries.

Explore related subjects

Data CollectionHospital AdministrationTotal Quality ManagementUnited StatesNews

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

T Hudson. 1999. Chartbook. Quality checkup.. https://pubmed.ncbi.nlm.nih.gov/10528577/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗