Prediction of acute care bed requirements for scattered area populations
In supporting the projection of bed requirements for Newfoundland to 1986, an extensive literature review was conducted to identify small area population projection methods and bed prediction models. A bed prediction model was developed for this study. For each health region, projected morbidity for...
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ftunivbritcolcir:oai:circle.library.ubc.ca:2429/22221 2023-05-15T17:16:51+02:00 Prediction of acute care bed requirements for scattered area populations O’Brien, Eoin 1980 http://hdl.handle.net/2429/22221 eng eng For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. Hospitalization - Newfoundland - Statistics Hospitals - Planning - Newfoundland and Labrador Rural health services - Newfoundland and Labrador Hospital Planning - Newfoundland Rural Health - Newfoundland Text Thesis/Dissertation 1980 ftunivbritcolcir 2019-10-15T17:55:45Z In supporting the projection of bed requirements for Newfoundland to 1986, an extensive literature review was conducted to identify small area population projection methods and bed prediction models. A bed prediction model was developed for this study. For each health region, projected morbidity for diagnostic (bed) clusters was calculated by: projecting the age-sex population; holding 1976 age-sex cluster morbidity patterns and length of stay constant; projecting the base and flow referral morbidity patterns of four health regions and finally the projected morbidity patterns were combined and translated into beds and adjusted for occupancy. The population projection method was the Short Ratio. The diagnostic clusters were medical-surgical, obstetrical, pediatrics and psychiatry. The prediction of beds utilizing this model was compared with a bed to population rate method. It was demonstrated that bed requirements do change in respect of age-sex population changes. The requirements are stated for each region. This study suggests that the model used for bed and population projections are useful planning tools in Newfoundland because of ease in use. The elemental problem of supplying a population data base for each hospital district by age and sex was solved and is expected to be extremely useful in years to come. The usefulness will come from an evaluation of these methods and their acceptance as first steps in the planning process. Medicine, Faculty of Population and Public Health (SPPH), School of Graduate Thesis Newfoundland University of British Columbia: cIRcle - UBC's Information Repository Newfoundland |
institution |
Open Polar |
collection |
University of British Columbia: cIRcle - UBC's Information Repository |
op_collection_id |
ftunivbritcolcir |
language |
English |
topic |
Hospitalization - Newfoundland - Statistics Hospitals - Planning - Newfoundland and Labrador Rural health services - Newfoundland and Labrador Hospital Planning - Newfoundland Rural Health - Newfoundland |
spellingShingle |
Hospitalization - Newfoundland - Statistics Hospitals - Planning - Newfoundland and Labrador Rural health services - Newfoundland and Labrador Hospital Planning - Newfoundland Rural Health - Newfoundland O’Brien, Eoin Prediction of acute care bed requirements for scattered area populations |
topic_facet |
Hospitalization - Newfoundland - Statistics Hospitals - Planning - Newfoundland and Labrador Rural health services - Newfoundland and Labrador Hospital Planning - Newfoundland Rural Health - Newfoundland |
description |
In supporting the projection of bed requirements for Newfoundland to 1986, an extensive literature review was conducted to identify small area population projection methods and bed prediction models. A bed prediction model was developed for this study. For each health region, projected morbidity for diagnostic (bed) clusters was calculated by: projecting the age-sex population; holding 1976 age-sex cluster morbidity patterns and length of stay constant; projecting the base and flow referral morbidity patterns of four health regions and finally the projected morbidity patterns were combined and translated into beds and adjusted for occupancy. The population projection method was the Short Ratio. The diagnostic clusters were medical-surgical, obstetrical, pediatrics and psychiatry. The prediction of beds utilizing this model was compared with a bed to population rate method. It was demonstrated that bed requirements do change in respect of age-sex population changes. The requirements are stated for each region. This study suggests that the model used for bed and population projections are useful planning tools in Newfoundland because of ease in use. The elemental problem of supplying a population data base for each hospital district by age and sex was solved and is expected to be extremely useful in years to come. The usefulness will come from an evaluation of these methods and their acceptance as first steps in the planning process. Medicine, Faculty of Population and Public Health (SPPH), School of Graduate |
format |
Thesis |
author |
O’Brien, Eoin |
author_facet |
O’Brien, Eoin |
author_sort |
O’Brien, Eoin |
title |
Prediction of acute care bed requirements for scattered area populations |
title_short |
Prediction of acute care bed requirements for scattered area populations |
title_full |
Prediction of acute care bed requirements for scattered area populations |
title_fullStr |
Prediction of acute care bed requirements for scattered area populations |
title_full_unstemmed |
Prediction of acute care bed requirements for scattered area populations |
title_sort |
prediction of acute care bed requirements for scattered area populations |
publishDate |
1980 |
url |
http://hdl.handle.net/2429/22221 |
geographic |
Newfoundland |
geographic_facet |
Newfoundland |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
_version_ |
1766082200849088512 |