Abstract
As health systems worldwide confront increasing demand variability, resource constraints, and unpredictable disruptions, such as pandemics, healthcare forecasting becomes crucial for aligning capacity with need. This paper examines the crucial role of forecasting in healthcare, its conceptual foundations, practical applications, challenges, and strategic implications. It examines forecasting techniques, explores supply–demand mismatches, and reviews the role of variation and variability in healthcare systems. Using theoretical insights, it identifies the operational challenges and approaches, including the advancement of artificial intelligence and machine learning, and their potential to improve the effectiveness of healthcare forecasting. The importance of the application of forecasting in tackling the expected and unexpected health systems complexities and disruptions globally is highlighted. This paper contributes to the growing discourse on forecasting and data-driven healthcare transformation and invites continued exploration into healthcare forecasting as a lever for quality improvement and resilience. It stimulates new thinking and insights into the application of healthcare forecasting as both a science and a strategic lever for improvement.
| Original language | English |
|---|---|
| Pages (from-to) | (In-Press) |
| Number of pages | 10 |
| Journal | Medinformatics |
| Volume | (In-Press) |
| Early online date | 16 Dec 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 16 Dec 2025 |
Bibliographical note
Copyright (c) 2025 AuthorThis is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited..
Keywords
- healthcare forecasting
- service delivery
- supply-demand mismatch
- variability
- quality improvement
- healthcare management