Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 8783543

Data-driven interventions to improve patient satisfaction.

K M Luther
View original source ↗Export metadata ↓

Abstract

The way patients view their care, as measured by their reported satisfaction, has far-reaching implications for managed care and outcomes monitoring. By understanding what is most important to their patients, nurses can modify their care to improve satisfaction. Data from surveys, complaint management programs, and other sources can be used to define particular needs of patients, develop programs to address those needs, and monitor improvement.

Explore related subjects

Data CollectionHealth Services Needs and DemandHospital UnitsHospital-Patient RelationsHumansNursing CareOutcome Assessment, Health CarePatient SatisfactionSurveys and QuestionnairesJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

K M Luther. 1996. Data-driven interventions to improve patient satisfaction.. https://doi.org/10.1097/00001786-199607000-00006

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↗