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This repository is to enable fast and robust computation of activity based funding (ABF) and associated adjustments as described in the NEP20-21 references

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GreenlakeMedical/fastABF

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fastABF is a fast and robust computation module for activity based funding (ABF). It helps to streamline the computation of ABF activities as per the National Efficient Price (NEP) 20-21 framework guidelines. It covers the following major ABF activity types

  • admitted acute
  • admitted sub/non-acute
  • non-admitted
  • emergency department or emergency service

Documentation: fastABF doc


Features

  • Fast to setup - go from start to computing an example ABF episode within 5 minutes. Save close to a month of development and testing time!
  • Robust - with python type hints, strong version control (via Poetry) and strong test coverage the code base is ready for use in backend systems.
  • Easy to understand and extend - numerous comments and well structured organisation, ensure that health IT developers can easily use and extend these modules.
  • Pain free - The code aims to distill the numerous computations detailed in the IHPA NEP 20-21 computation documentation and guidelines. These span over 60 pages. This is in addition to the HAC computation guidelines which span over 40 pages. The effort we have put into this is time that you can spend on making other innovative contributions (or taking several long walks :) ).
  • Lower bug count - By leveraging a well tested and open source code base - developers can reduce the chance of introducing bugs into their ABF calculations by over 25-30%*
  • Incorporates METeOR conventions - The METeOR identifiers have been mapped to user friendly Python Enum names. Now instead of remembering the METeOR numerical identifiers you can use these human readable class names - reducing the possibility of bugs and errors creeping in.
  • HAC adjustment computations - The detailed steps of the HAC adjustments are included as well.
  • Remoteness calculations - This code also contains the steps to obtain the remoteness values (from postcode and SA2 address). Hence it enables automatic extraction of the RA16 remoteness class)

* based on the experience of the internal dev-team and bugs caught and resolved via type checking and testing during development.

Glossary

  • [HAC]: hosptial acquired complications
  • [IHPA]: Independent hospital pricing authority
  • [METeOR]: Metadata online registry
  • [ABF]: Activity based funding
  • [NEP]: National efficient price

It is assumed that you are familiar with

  • python
  • the terminology and concepts of ABF.

Attribution

Independent Hospital Pricing Authority material used 'as supplied', under a Creative Commons BY Attribution 3.0 Australia licence.

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About

This repository is to enable fast and robust computation of activity based funding (ABF) and associated adjustments as described in the NEP20-21 references

https://www.greenlakemedical.ai

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