Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 3897485

Work sampling. Analyzing nursing staff productivity.

B K Hagerty·R S Chang·C D Spengler
View original source ↗Export metadata ↓

Abstract

Most managers have only a vague idea of how their employees spend their time. Work sampling is a technique that can identify the types of activities that staff perform and the amount of time that they spend on each activity. With this information, managers can make decisions regarding allocation of staff and activities, thereby increasing efficiency and effectiveness of personnel. This paper describes the use of work sampling as a technique to study employee time allocation and productivity. It offers suggestions for planning, implementation, and utilization of the results of a work sampling study. A work sampling study conducted at the University of Michigan Medical Center's Psychiatric Nursing Department is used as an example.

Explore related subjects

Data CollectionEfficiencyHospital Bed Capacity, 500 and overHumansMichiganNurse AdministratorsNursing Service, HospitalPlanning TechniquesPsychiatric Department, HospitalTime and Motion StudiesWorkJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

B K Hagerty, R S Chang, C D Spengler. 1985. Work sampling. Analyzing nursing staff productivity.. https://pubmed.ncbi.nlm.nih.gov/3897485/

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↗