Optimising elective care delivery: A data-driven framework for reducing NHS waiting times [Written evidence submitted by Dr Mohammad Heydari (NWT0021)]
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Authors
Heydari, Mohammad
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Date
2025-05
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Report
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Ngā Upoko Tukutuku (Māori subject headings)
Keyword
Great Britain
National Health Services (Great Britain)
emergency medical services
medical appointments and schedules
hospital services administration
health sector management
queueing theory
Markov processes
public health services
delivery of health care
Report
National Health Services (Great Britain)
emergency medical services
medical appointments and schedules
hospital services administration
health sector management
queueing theory
Markov processes
public health services
delivery of health care
Report
ANZSRC Field of Research Code (2020)
Citation
Heydari, Mohammad. (2025, May). Optimising elective care delivery: A data-driven framework for reducing NHS waiting times [Written evidence submitted by Dr Mohammad Heydari (NWT0021)]. United Kingdom Parliment. https://committees.parliament.uk/writtenevidence/142089/html/
Abstract
This research directly confronts persistent inefficiencies in emergency healthcare logistics, particularly those arising in high-demand, high-stakes environments such as national call centres. Delays in triaging patients, dispatching ambulances, and allocating consultation staff can significantly compromise care delivery, leading to patient dissatisfaction, treatment delays, and—in critical cases—escalated clinical risk. Our findings, based on over 100 months of national call centre data, reveal that demand surges often overwhelm fixed-capacity systems, exposing the inadequacy of static scheduling and resource planning approaches.
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United Kingdom Parliament
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