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Supporting Material

Costing activities at the patient level can help organisations to understand the composition of their costs. The data produced can be a powerful tool in informing the efficient redesign of pathways, elimination of waste and the reduction of costs. The following documents provide supporting material for the revised clinical costing standards, published by the HFMA in March 2011, and for the successful implementation of a clinical costing system.

Clinical costing implementation guide

This guide, updating an earlier implementation guide published by the Department of Health provides practical, hands-on advice and guidance to support the implementation of clinical costing. It also contains information, previously published in the clinical costing standards themselves, for example: survey questions to identify the costs of teaching and examples of how to allocate direct costs. While likely to be of most use to acute organisations, the document provides generic guidance that should be of value across all healthcare settings.

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Excel

Materiality and quality score (MAQS) template (April 2012)

Standard 9 in the clinical costing standards sets out a methodology for organisations to measure the materiality and quality of their costing systems and processes. Overall MAQS are calculated from individual MAQS of cost pools/cost pool groups taking account of the actual level of resources involved, the quality score of the allocation methodology used and the percentage of patient records flowing into the costing system. This spread sheet (a full version of the extract included within appendix D of the standards) provides a template for organisations to calculate their own MAQS score. (Please note included financial figures are indicative only and should be deleted before use.) This template is based on an acute model of healthcare. However it will also help mental health organisations understand the approach to self-assessment of costing processes.


 

 

Excel

Allocation methodologies/MAQS scores - acute (April 2012)

A fuller version of the allocation methodologies table and suggested MAQS score ratings included as appendix C of the Acute health clinical costing standards 2012/13. This table supports Standard 3 (Allocation of costs) in providing examples of allocation methodologies and Standard 9 (Quality assessment and measurement) in providing the relevant MAQS score for each method (gold, silver, bronze or baseline).

 

 


Excel

Allocation methodologies/MAQS scores - mental health (April 2012)

A fuller version of the allocation methodologies table and suggested MAQS score ratings included as appendix C of the Mental health clinical costing standards 2012/13. This table supports Standard 3 (Allocation of costs) in providing examples of allocation methodologies and Standard 9 (Quality assessment and measurement) in providing the relevant MAQS score for each method (gold, silver, bronze or baseline).


 

 

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Allocating costs into variable, semi-fixed and fixed categories: acute health example (April 2012)

A fuller version of the allocation methodologies table and suggested MAQS score ratings included as appendix C of the Mental health clinical costing standards 2012/13. This table supports Standard 3 (Allocation of costs) in providing examples of allocation methodologies and Standard 9 (Quality assessment and measurement) in providing the relevant MAQS score for each method (gold, silver, bronze or baseline).


 


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SIFT, MADEL and NMET Costing Methodologies

A costing methodology was developed by the Department as part of 2009’s multi-professional education and training (MPET) review. The outcome of this exercise has informed the education and development tariff, which the Department is developing. Diagrams illustrating the costing methodologies for SIFT, MADEL and NMET are included in this pdf.



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Data quality issues and solutions checklist

This table is a supplement to the HFMA’s Clinical costing implementation guide and to Standard 8 within the clinical costing standards (data integrity). It sets out possible problem events and solutions as well as data quality issues and solutions.

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