Health Care Management Science

, Volume 15, Issue 4, pp 385–412

Modeling the demand for long-term care services under uncertain information

  • Teresa Cardoso
  • Mónica Duarte Oliveira
  • Ana Barbosa-Póvoa
  • Stefan Nickel
Article

DOI: 10.1007/s10729-012-9204-0

Cite this article as:
Cardoso, T., Oliveira, M.D., Barbosa-Póvoa, A. et al. Health Care Manag Sci (2012) 15: 385. doi:10.1007/s10729-012-9204-0

Abstract

Developing a network of long-term care (LTC) services is currently a health policy priority in many countries, in particular in countries with a health system based on a National Health Service (NHS) structure. Developing such a network requires proper planning and basic information on future demand and utilization of LTC services. Unfortunately, this information is often not available and the development of methods to properly predict demand is therefore essential. The current study proposes a simulation model based on a Markov cycle tree structure to predict annual demand for LTC services so as to inform the planning of these services at the small-area level in the coming years. The simulation model is multiservice, as it allows for predicting the annual number of individuals in need of each type of LTC service (formal and informal home-based, ambulatory and institutional services), the resources/services that are required to satisfy those needs (informal caregivers, domiciliary visits, consultations and beds) and the associated costs. The model developed was validated using past data and key international figures and applied to Portugal at the Lisbon borough level for the 2010–2015 period. Given data imperfections and uncertainties related to predicting future LTC demand, uncertainty was modeled through an integrated approach that combines scenario analysis with probabilistic sensitivity analysis using Monte Carlo simulation. Results show that the model provides information critical for informing the planning and financing of LTC networks.

Keywords

Long-term care Demand Markov model Simulation Uncertainty Portugal 

Abbreviations

AAGR

Average annual growth rate

AC

Ambulatory care

ADL

Activity of daily living

CD

Chronic diseases

CI

Confidence intervals

CS

Chronic patients with symptoms

CWS

Chronic patients without symptoms

D

Dependent individuals

FHC

Formal home-based care

GDP

Gross domestic product

IADL

Instrumental activity of daily living

IC

Institutional care

IHC

Informal home-based care

LOS

Length of stay

LTC

Long-term care

NC

Non-chronic individuals

ND

Non-dependent individuals

NHS

National health service

NHSur

National health survey

NS

Non-single individuals

NVLI

Not very low income

OC

Other causes

PE

Point estimates

PSSRU

Personal social services research unit

RNCCI

Rede nacional de cuidados continuados integrados

S

Single individuals

TC

Total cost

VLI

Very low income

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Teresa Cardoso
    • 1
  • Mónica Duarte Oliveira
    • 1
  • Ana Barbosa-Póvoa
    • 1
  • Stefan Nickel
    • 2
  1. 1.Centre for Management Studies of Instituto Superior TécnicoUniversidade Técnica de LisboaLisbonPortugal
  2. 2.Discrete Optimization and LogisticsKarlsruhe Institute of Technology, Institute of Operations ResearchKarlsruheGermany

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