A Bayesian framework for describing and predicting the stochastic demand of home care patients
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Summary
A Bayesian framework to represent the patients’ demand evolution along with the time and to predict it in future periods is proposed and results show the applicability of the proposed model in the practice and validate the approach, since parameter densities in accordance to clinical evidences and low prediction errors are found.
- Type
- article
- Published
- 2014-09-06
- Cited by
- 17
- References
- 59
- Access
- Open access
- OpenAlex
- https://openalex.org/W1988713442
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:62691052
Keywords
Randomness, Computer science, Bayesian probability, Markov chain Monte Carlo, Markov chain
References
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- Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
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- CODA: convergence diagnosis and output analysis for MCMC
- What is important to continuity in home care?. Perspectives of key stakeholders.
- Markov Chain Modelling for Geriatric Patient Care
- Fractals and Statistics: An R Package Called IFS
- Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals
- Modelling home care organisations from an operations management perspective
- Identifying needs and improving palliative care of chronically ill patients: a community-oriented, population-based, public-health approach
- Using a Markov reward model to estimate spend-down costs for a geriatric department
- A cost assignment policy for home care patients
- Estimating the Prognosis of Hepatitis C Patients Infected by Transfusion in Canada between 1986 and 1990
- Multivariate Statistical Modelling Based on Generalized Linear Models
- Generalized linear models with random e ects: a Gibbs sampling approach
- Effectiveness of potent antiretroviral therapy on progression of human immunodeficiency virus: Bayesian modelling and model checking via counterfactual replicates
- Length of Stay-Based Patient Flow Models: Recent Developments and Future Directions
- Models and estimation methods for clinical HIV-1 data
Cited by
- Staff dimensioning in homecare services with uncertain demands
- Bayesian joint modelling of the health profile and demand of home care patients
- A multi-user tool for enhancing the daily replanning and control of visits in home care services
- Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation
- An optimization tool to dimension innovative home health care services with devices and disposable materials
- Home healthcare integrated staffing and scheduling
- Operational research applied to decisions in home health care: A systematic literature review
- Literature review of managerial levers in primary care.
- Modified Needleman–Wunsch algorithm for clinical pathway clustering
- Bayesian spatio-temporal modelling and prediction of areal demands for ambulance services
- Merging short-term and long-term planning problems in home health care under continuity of care and patterns for visits
- An implementor-adversary approach for uncertain and time-correlated service times in the nurse-to-patient assignment problem
- A systematic review of the home health care planning literature: Emerging trends and future research directions
- Realization-based robust assignments for a nurse-to-patient assignment problem in home health care services
- Handling time-related demands in the home care nurse-to-patient assignment problem with the implementor-adversarial approach
- A Bayesian Model for Describing and Predicting the Stochastic Demand of Emergency Calls
- A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study
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