<abstract xmlns="http://www.w3.org/1999/xhtml">Introduction: Most of the forecast methods for hospital beds estimate a total number of beds per region, based on demographic and utilization indicators, without allocation on specialty wards.Objectives: Develop a forecast methodology per specialty in a county, according to the population needs.Materials and methods: Literature review, demographic data and indicators of hospital morbidity analysis; hospitalization rates adjustment for medical migration; model the allocation of new cases according to the previous hospitalization models.Results: the excess of hospitalization between similar counties varies between -34.71 to 96.50%; adjustment of the hospital beds for patient migration leads to increase in the number of beds in 5 of 6 counties; the allocation of new cases, based on the previous model of hospitalization, triggers the reallocation between specialties.Conclusions: demographic indicators, hospital activity, family doctor records can be used successfully to design the number of beds at county level, according to the needs of the population.</abstract>

Introduction: Most of the forecast methods for hospital beds estimate a total number of beds per region, based on demographic and utilization indicators, without allocation on specialty wards.Objectives: Develop a forecast methodology per specialty in a county, according to the population needs.Materials and methods: Literature review, demographic data and indicators of hospital morbidity analysis; hospitalization rates adjustment for medical migration; model the allocation of new cases according to the previous hospitalization models.Results: the excess of hospitalization between similar counties varies between -34.71 to 96.50%; adjustment of the hospital beds for patient migration leads to increase in the number of beds in 5 of 6 counties; the allocation of new cases, based on the previous model of hospitalization, triggers the reallocation between specialties.Conclusions: demographic indicators, hospital activity, family doctor records can be used successfully to design the number of beds at county level, according to the needs of the population.

Development of a Methodology for Hospital Beds Planning according to Population and Morbidity

“Carol Davila” University of Medicine and Pharmacy

Acta Medica Transilvanica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Introduction: Most of the forecast methods for hospital beds estimate a total number of beds per region, based on demographic and utilization indicators,...

Development of a Methodology for Hospital Beds Planning according to Population and Morbidity

Online veröffentlicht: 03. Aug. 2020

Seitenbereich: 6 - 10

Eingereicht: 22. Apr. 2019

Akzeptiert: 02. Juni 2020

DOI: https://doi.org/10.2478/amtsb-2020-0018

Schlüsselwörter
morbidity, hospital planning, beds infrastructure

© 2020 Heinz Vajasdi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Development of a Methodology for Hospital Beds Planning according to Population and Morbidity

Online veröffentlicht: 03. Aug. 2020

Seitenbereich: 6 - 10

Eingereicht: 22. Apr. 2019

Akzeptiert: 02. Juni 2020

DOI: https://doi.org/10.2478/amtsb-2020-0018

Schlüsselwörtermorbidity, hospital planning, beds infrastructure

© 2020 Heinz Vajasdi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
morbidity, hospital planning, beds infrastructure