Decision-modeling Methods Used to Design Decision Support Systems for Staffing
Bibliographic Data
| ID | 9104631 |
|---|---|
| Authors | Paul C Nutt (Ohio State University Hospital, corresponding author) |
| Year | 1984 |
| Volume | 22 |
| Issue | 11 |
| Pages | 1002-1013 |
| Publication date | 1984-11-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/00005650-198411000-00003 |
| PMID | 6503395 |
| OpenAlex | W2051015042 |
| Language | EN |
| References cited | 3 |
This paper explores the merits of two methods that extract the decision models of experts to serve as a decision support mechanism for staffing. One method has experts make judgments about hypothetical cases and the other has experts decompose the decision into criteria weighting and scaling. Staffing models were developed for each method using nurses who work in neonatology wards in two large hospitals. The four decision models were used to predict the demands for nursing time in both hospitals, which were compared with an ex post facto assessment of needs to validate the models. To measure transportability, the author used the model developed in one site to predict nursing hours for the other site. Both methods were found to be acceptable when applied at the site where they were developed. However, the ability to transport either model was negligible, suggesting that universal protocols for staffing do not exist
Data mining · Decision analysis · Decision model · Decision support system · Machine learning · Management science · Operations research · Staffing · Statistics · Weighting · Work (physics) · Computer Science · Engineering · Medicine · Multi-Criteria Decision Making · Nursing
| Citation velocity | historical |
|---|---|
| Highly cited | No |