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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


On 2nd March 2021, the NEP 2021-22 was released. As described in the main git repository, we are currently planning to implement, test and incorporate these updates into the next release of fastABF. If you would like to be kept updated on its progress please add yourself to the fastABF repository watchlist on Github or get added to the fastABF mailing list .


  • 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 has been prepared with production readiness for backend systems in mind.
  • Easy to understand and extend - numerous comments and well structured code 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 into ready to use packages. As those technical documents spans over 60 pages (in addition to the HAC computation guidelines which themselves span over 40 pages), the creation of fastABF has required a considerable amount of effort. This effort is time that you can now save for 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% 1
  • 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 (derived from the detailed HAC guidelines) are included as well. In addition the HAC are modeled using an easily reusable Enum class.
  • 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)
  • Helper functions - We have constructed helper functions to simplify workflow (e.g. a Charlson score calculator, remoteness calculators etc) aimed at simplifying future development.


It is assumed that you are familiar with

  • python at atleast a basic level.
  • the terminology and concepts of ABF.

You can follow along in the quick start example via a code editor, python commandline or a jupyter notebook


fastABF requires python 3.7 or higher.


Lets see how you can get started using fastABF in under 5 minutes!

> pip install fastabf 
That installs fastabf. Now we get on with using it.

Open up a python shell or notebook and type in the following (or copy-paste it from the box below)

from fastabf.datatypes import (ABF_Service_Category, Care_Type,
from fastabf.pipelines.nwau_admitted_acute import Admitted_Acute_Record

aar = Admitted_Acute_Record(
    sex=2, bool_is_emergency_admission=False, bool_foetal_distress_flag=False,
    bool_instrument_use_flag=False, bool_ppop_flag=False, bool_prima_flag=False,
    HAC1=False, HAC2=True, HAC3=False, HAC4=False, HAC6=False, HAC7=False, HAC8=False,
    HAC9=False, HAC10=False, HAC11=False, HAC12=False, HAC13=False, HAC14=False,
    HAC15p2=False, Charlson_Score=0,

abf_price = aar.get_abf_price()
print(f"The abf price is {abf_price}")

Nicely done!

In just 5 minutes you have computed the ABF price for an admitted acute episode that included various hospital acquired complication flags, location adjustments etc. This required over 20 steps behind the scenes. The power of using this toolbox is that all of them were orchestrated for you.


Please note that there are a few values that are unique to each hospital and must be set accordingly. They affect the price computations but would not need to be changed very often. Refer to the global variables section to learn more.


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



This project is licensed under the open source terms of the AGPLv3.0 license.


For healthcare providers and IT departments who need a proprietary license please contact the Greenlake Medical team for more information.

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