The Implications of Activity Based Funding for Emergency Departments : A Comprehensive Literature Review

Wylie, Kate, Bell, Anthony, FitzGerald, Gerard J., Crilly, Julia, Toloo, Ghasem (Sam), Burke, John, & Williams, Ged (2014) The Implications of Activity Based Funding for Emergency Departments : A Comprehensive Literature Review. Queensland University of Technology, Brisbane, QLD.


Executive Summary

Emergency Departments (EDs) locally, nationally and internationally are becoming increasingly busy. Within this context, it can be challenging to deliver a health service that is safe, of high quality and cost-effective. Whilst various models are described within the literature that aim to measure ED ‘work’ or ‘activity’, they are often not linked to a measure of costs to provide such activity. It is important for hospital and ED managers to understand and apply this link so that optimal staffing and financial resourcing can be justifiably sought. This research is timely given that Australia has moved towards a national Activity Based Funding (ABF) model for ED activity. ABF is believed to increase transparency of care and fairness (i.e. equal work receives equal pay). ABF involves a person-, performance- or activity-based payment system, and thus a move away from historical “block payment” models that do not incentivise efficiency and quality.

The aim of the Statewide Workforce and Activity-Based Funding Modelling Project in Queensland Emergency Departments (SWAMPED) is to identify and describe best practice Emergency Department (ED) workforce models within the current context of ED funding that operates under an ABF model.

The study is comprised of five distinct phases. This monograph (Phase 1) comprises a systematic review of the literature that was completed in June 2013. The remaining phases include a detailed survey of Queensland hospital EDs’ resource levels, activity and operational models of care, development of new resource models, development of a user-friendly modelling interface for ED mangers, and production of a final report that identifies policy implications.

The anticipated deliverable outcome of this research is the development of an ABF based Emergency Workforce Modelling Tool that will enable ED managers to profile both their workforce and operational models of care. Additionally, the tool will assist with the ability to more accurately inform adequate staffing numbers required in the future, inform planning of expected expenditures and be used for standardisation and benchmarking across similar EDs.

Summary of the Findings

Within the remit of this review of the literature, the main findings include:

  1. EDs are becoming busier and more congested

Rising demand, barriers to ED throughput and transitions of care all contribute to ED congestion. In addition requests by organisational managers and the community require continued broadening of the scope of services required of the ED and further increases in demand. As the population live longer with more lifestyle diseases their propensity to require ED care continues to grow.

  1. Various models of care within EDs exist

Models often vary to account for site specific characteritics to suit staffing profile, ED geographical location (e.g. metropolitan or rural site), and patient demographic profile (e.g. paediatrics, older persons, ethnicity). Existing and new models implemented within EDs often depend on the target outcome requiring change. Generally this is focussed on addressing issues at the input, throughput or output areas of the ED. Even with models targeting similar demographic or illness, the structure and process elements underpinning the model can vary, which can impact on outcomes and variance to the patient and carer experience between and within EDs. Major models of care to manage throughput inefficiencies include:

A. Workforce Models of Care focus on the appropriate level of staffing for a given workload to provide prompt, timely and clinically effective patient care within an emergency care setting. The studies reviewed suggest that the early involvement of senior medical decision maker and/or specialised nursing roles such as Emergency Nurse Practitioners and Clinical Initiatives Nurse, primary contact or extended scope Allied Health Practitioners can facilitate patient flow and improve key indicators such as length of stay and reducing the number of those who did not wait to be seen amongst others.

B. Operational Models of Care within EDs focus on mechanisms for streaming (e.g. fast-tracking) or otherwise grouping patient care based on acuity and complexity to assist with minimising any throughput inefficiencies. While studies support the positive impact of these models in general, it appears that they are most effective when they are adequately resourced.

  1. Various methods of measuring ED activity exist

Measuring ED activity requires careful consideration of models of care and staffing profile. Measuring activity requires the ability to account for factors including: patient census, acuity, LOS, intensity of intervention, department skill-mix plus an adjustment for non-patient care time.

  1. Gaps in the literature

Continued ED growth calls for new and innovative care delivery models that are safe, clinically effective and cost effective. New roles and stand-alone service delivery models are often evaluated in isolation without considering the global and economic impact on staffing profiles. Whilst various models of accounting for and measuring health care activity exist, costing studies and cost effectiveness studies are lacking for EDs making accurate and reliable assessments of care models difficult. There is a necessity to further understand, refine and account for measures of ED complexity that define a workload upon which resources and appropriate staffing determinations can be made into the future. There is also a need for continued monitoring and comprehensive evaluation of newly implemented workforce modelling tools.

This research acknowledges those gaps and aims to:

• Undertake a comprehensive and integrated whole of department workforce profiling exercise relative to resources in the context of ABF.

• Inform workforce requirements based on traditional quantitative markers (e.g. volume and acuity) combined with qualitative elements of ED models of care;

• Develop a comprehensive and validated workforce calculation tool that can be used to better inform or at least guide workforce requirements in a more transparent manner.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

296 since deposited on 16 Mar 2014
73 in the past twelve months

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ID Code: 68605
Item Type: Report
Refereed: No
Keywords: Health workforce, Funding models, Activity-based funding, Emergency department
ISBN: 9781921897986
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > PUBLIC HEALTH AND HEALTH SERVICES (111700) > Public Health and Health Services not elsewhere classified (111799)
Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > APPLIED ECONOMICS (140200) > Health Economics (140208)
Australian and New Zealand Standard Research Classification > STUDIES IN HUMAN SOCIETY (160000) > POLICY AND ADMINISTRATION (160500) > Health Policy (160508)
Divisions: Current > Research Centres > Centre for Emergency & Disaster Management
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Public Health & Social Work
Deposited On: 16 Mar 2014 23:33
Last Modified: 11 Jan 2017 12:29

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