PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 10311324

Case study: analyzing the market using DRGs and MDCs.

R A Reif·P A Bickett·D E Halberstadt
View original source ↗Export metadata ↓

Abstract

Union Memorial Hospital, in response to the growing need and pressure to plan, developed a strategic planning model whereby it could assess its competitive position in the marketplace, examine the strength of hospitals in geographic areas targeted for future growth, and analyze options available to improve its competitive standing. The model consists of a database that lists by DRG and MDC the number of cases at Union Memorial and area hospitals. This database can be used to analyze opportunity cases, physician specialties, and strategic alternatives to be considered for improved competitive standing.

Explore related subjects

Diagnosis-Related GroupsHospital Bed Capacity, 300 to 499Information SystemsMarketing of Health ServicesMarylandModels, TheoreticalPlanning TechniquesJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

R A Reif, P A Bickett, D E Halberstadt. 1985. Case study: analyzing the market using DRGs and MDCs.. https://pubmed.ncbi.nlm.nih.gov/10311324/

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

KEEP EXPLORING

Related citations

PubMed2006

Reliability of diagnoses coding with ICD-10.

OBJECTIVE: Reliability of diagnoses coding is essential for the use of routine data in a national health care system. The present investigation compares reliability of diagnoses coding with ICD-10 between three groups of coding subjects. METHOD: One hundred and eighteen students coded 15 diagnoses lists, 27 medical managers from hospitals 34 discharge letters, and 13 coding specialists 12 discharge letters. Agreement in principal diagnosis was assessed using Cohen's Kappa and the fraction of coincidences over the number of pairs, agreement for the full set of diagnoses with a previously developed measure p(om). RESULTS: Kappa values were fair (managers) or moderate (coders) for terminal codes with 0.27 and 0.42 (agreement 29.2% versus 46.8%), substantial for the chapter level with 0.71 and 0.72 (agreement 78.3% versus 80.8%). p(om) was lower for the full set of diagnoses than for principal diagnoses, for example in case of managers with 0.21 versus 0.29 for terminal codes. Best results were achieved by students coding diagnoses lists. In summary, the results are remarkably lower than in earlier publications. CONCLUSION: The refinement of the ICD-10 accompanied by innumerous coding rules has established a complex environment that leads to significant uncertainties even for experts. Use of coded data for quality management, health care financing, and health care policy requires a remarkable simplification of ICD-10 to receive a valid image of health care reality.

Diagnosis-Related Groups↗