Optimizing cost and quality through enhanced clinical grouping, a multi-expert collaborative approach

Jeff Hatcher ^a, Jean Noël Nikiema ^b, Kristin Dahlen ^c, Eva Wensaas ^c, Jim Pearse ^d, Amanda Ling ^e

Although Diagnosis-Related Groups (DRGs) have long served as a cornerstone for cost control and reimbursement in healthcare, the methodologies supporting their development, updating, and geographic relocation lack flexibility. Traditional DRG systems are often developed based on region-specific clinical practices and historical datasets, which makes it challenging to adapt them to new environments or to integrate ongoing advances in real-world data coding and clinical management procedures. As a result, these systems may not fully capture the evolving complexities of patient care, potentially limiting their effectiveness in optimizing hospital stays, resource allocation, and overall care trajectories.

The rapid expansion of clinical data (driven by advancements in electronic health records, improved coding standards), and more granular data collection (along with the increasing complexity of patient care), calls for significant improvements in cost-clinical grouping systems development and usage. Modern healthcare demands grouping methodologies that are not only accurate in reflecting current clinical practices but are also flexible enough to adapt to continuous changes in medical protocols and patient demographics.

In response to these challenges, this panel discussion brings together experts from clinical informatics, health economics, healthcare analytics, and medical practice. The session aims to foster an in-depth dialogue on innovative methodologies that can refine and enhance existing cost-clinical grouping systems. The panel will explore a wide array of analytical approaches (including traditional statistical models, case-mix methods, rule-based algorithms, and advanced machine learning algorithms) to critically assess their potential in creating more adaptive and effective grouping strategies.

^a Canadian Institute for Health Information, Canada
^b Department of Management, Evaluation and Health Policy School of Public Health, Université de Montréal, Canada
^c Norwegian directorate of Health, Norway
^d Nous Group, Australia
^e Business Insights and Clinical Analytics, North Meropolitan Health Service, Government of Western Australia, Australia, Australia

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