PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 8632362

Developing a quality indicator logbook for the postanesthesia care unit setting.

J Zeller
View original source ↗Export metadata ↓

Abstract

In the interest of quality care, it is important for health care practitioners to examine practice and identify methods for improvement. Gathering data is one way to impact changes in practice. Recognizing that a simple, efficient method for gathering data was needed, a logbook was developed to replace the more time-consuming quality assurance form currently used at our northwest institution. Four incidents particular to the PACU were identified and included in the logbook. The goal of gathering risk indicator data about frequently occuring incidents was to make information available to nurses and adjunct health teams interested in quality assurance and improvement.

Explore related subjects

Data CollectionHumansNursing RecordsPostanesthesia NursingQuality Assurance, Health CareRisk ManagementJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J Zeller. 1995. Developing a quality indicator logbook for the postanesthesia care unit setting.. https://pubmed.ncbi.nlm.nih.gov/8632362/

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

KEEP EXPLORING

Related citations

PubMed1999

Identifying problems with data collection at a local level: survey of NHS maternity units in England.

OBJECTIVES: To document the extent to which maternity data are collected and how they are recorded, and to identify problems that may affect their availability throughout the NHS. METHODS: Postal survey in September 1997 with structured questionnaires. SETTING: 207 NHS trusts with maternity units in England. PARTICIPANTS: Heads of midwifery in maternity units. MAIN OUTCOME MEASURES: Extent to which maternity data were routinely recorded, how they were recorded and evaluated, and to whom they were made available. RESULTS: 167 (81%) of questionnaires were returned, representing 166 trusts. Of these trusts, 165 collected >/=17 of the 19 data items in HES maternity tail, and 158 collected >/=40 of the 45 items selected from Körner dataset. Only 18 collected all five items selected from the "indicators of success," and 17 did not collect any. In 58 of trusts data were primarily recorded on paper. A computerised maternity information system was used by 106 (63%) of trusts, but many recorded data on paper first. Thirty four did not audit data for accuracy. Most trusts analysed data not routinely collected at national level, but 18 did not analyse HES maternity tail and 17 did not analyse Körner data. CONCLUSIONS: Improvement is needed in quality, completeness, and availability of maternity data at a national level, particularly if the NHS information strategy is to be successfully implemented. Although most of the data items in national datasets are recorded locally, variations in the way data are defined, recorded, and analysed and lack of linkage between computer systems restrict their access, availability, and use at local, district, and national levels.

Data Collection↗
PubMed1999

Applied pharmacoeconomics: evaluation and use of pharmacoeconomic data from the literature.

The evaluation and use of published pharmacoeconomic data are discussed. The pharmacoeconomic literature is a vast and powerful source of information for pharmacists and others who must make decisions about services and products. Published studies can provide data quickly and inexpensively, but they may not necessarily meet criteria for quality and may not be generalizable to a specific situation. Guidelines are available that are intended to standardize study methods, minimize potential bias, and increase the comparability and credibility of data. Before relying on a published study, decision-makers should ensure that it meets criteria related to objective, perspective, pharmacoeconomic method, design, interventions, costs, outcomes, discounting, results, sensitivity analysis, extrapolation of conclusions, and sponsorship. A sound study can be used to support decisions in such diverse areas as individual patient treatment, formulary management, drug-use guideline development, disease management initiatives, and pharmaceutical service evaluation. A decision-maker may be able to use the results by applying them at face value, employing a sensitivity analysis, performing a meta-analysis, incorporating the data into a pharmacoeconomic model, or reproducing the study on a smaller scale. The selection of an application strategy should be based on the potential impact of the decision on the quality and cost of care, with more rigorous and complex strategies reserved for more extreme impacts. Published pharmacoeconomic data can help pharmacists make better and more informed decisions about pharmaceutical services and products.

Data Collection↗