Data quality in different ICD10 systems: comparison of a block contract funded system and an activity based funded system

Rebecca Ziffer ^a, Alex Kafetz ^b, Sharon Roumanos ^a

Introduction
Different healthcare systems use different ICD coding systems including the Australian Modification (ICD-10-AM), ICD-10-CM in the USA and a Canadian Version (ICD-10-CA). These are implemented against the backdrop of different approaches in government to health policy, Canada uses block payments, whilst Australia uses an activity-based funding system (ABF). A study is taking place commissioned by the Pacific Health Services Authority (PHSA) in British Columbia to understand the differences in coding in their system compared to the Australian system especially different approaches to mandatory fields.

Methods
Over 900 indicators pertaining to the data quality of the ICD10 data have been developed for the specific use against the Australian modification. Approximately 200 of these have been adapted to be used on the ICD-10-CA modification to be tested across 14 hospitals in British Columbia. Specific attention is going to be paid to a subset of highly prevalent long-term conditions such as diabetes. The aim will be to identify different approaches to mandatory fields in these two systems - one which uses block contracting and one which uses activity-based funding. The approach to mandatory fields is likely to affect a number of secondary uses for the data including population health management, resource allocation and measurement of safety and quality.

Results
Results are not yet available but will be before the PCSI conference in 2024

Discussion
There are a number of similar challenges in the Canadian and Australian health systems not least the narrowing of inequalities with regards to First Nations, Metis, and Inuit peoples in Canada and Aboriginal and Torres Strait Islanders in Australia. On the face of it, the ICD coded data should be a perfect source to be able to do this and create best practice in quality and safety in healthcare. However, the differing approach to mandatory fields may be a severe impediment to be able to do this. This also means data submitted to global analytic bodies such as The Organisation for Economic Co-operation and Development (OECD) and the World Health Organization cannot be compared like-for-like due to these different approaches.

This study, which will be the first of its kind, will identify the differing policy guidelines and approaches to mandatory fields, using the lens of prevalent long term conditions and offer quantitative assessments of the differences and similarities of the two approaches and qualitative discussion points as to the advantages and disadvantages and each and suggest learning and recommendations where consistency and common approaches to mandatory fields will make data more robust and of higher quality.


^a Beamtree, Australia
^b Beamtree, United Kingdom

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