# Quantifying Staff Preferences for Workforce Retention Strategies in Remote Australian Primary Health Care Services

## TL;DR

This paper compares methods to measure preferences of remote Australian health workers to improve retention strategies and service delivery.

## Contribution

The study provides a rationale for using Best-Worst Scaling Object Case to assess staff preferences in remote Aboriginal health settings.

## Key findings

- Best-Worst Scaling Object Case is most suitable for measuring preferences in remote primary health care settings.
- The method allows quantified results to be translated into actionable retention strategies.
- Logistical and cultural considerations are critical when choosing a methodology for remote areas.

## Abstract

To outline key criteria when choosing how to measure remote area primary health care workers' retention preferences and compare six different methodological approaches against these criteria.

Australians living in remote communities experience poorer health outcomes. Many health services serving remote populations have persistent workforce shortages, high staff turnover and short retention which adversely affect access to timely, appropriate health care, care continuity and cultural appropriateness of care. Improved understanding of staff preferences for different retention initiatives could inform initiatives to improve workforce stability.

Measuring the preferences of remote primary health care staff is complex. Key criteria to guide methodology choice include: i) logistical considerations related to geographical remoteness, ii) diversity of primary care staff, iii) minimising participants' cognitive load and time required for data collection, iv) ability to quantify preferences, v) appropriateness of methodologies for staff from different socio‐cultural backgrounds, vi) minimising bias, and vii) making trade‐offs given limited resources for implementing retention incentives. Six different methodological approaches are compared: Rating, Ranking, Best Worst Scaling (BWS) Object Case, BWS Profile Case, BWS Multi‐profile Case and conventional Discrete Choice Experiments (DCE).

The comparison of different methodologies reveals the advantages of using a BWS Object Case methodological approach for measuring primary health care service workers' preferences in remote primary health care settings. Importantly, this paper demonstrates how the quantified results from BWS object case analysis can be translated into actionable retention initiatives designed to retain remote area health workers, given ongoing budget constraints and the need to ensure cultural appropriateness.

What is already known on this subject?
Remote Australian health services have been persistently impacted by high turnover of health care staff.Stated preference survey methods have only been occasionally applied in health research in high income countries to understand health care workers' preferences in remote settings.Different methodological approaches have a range of strengths and weaknesses which may make them more or less suitable for use in remote settings.

Remote Australian health services have been persistently impacted by high turnover of health care staff.

Stated preference survey methods have only been occasionally applied in health research in high income countries to understand health care workers' preferences in remote settings.

Different methodological approaches have a range of strengths and weaknesses which may make them more or less suitable for use in remote settings.

What does this study add?
This study compares a range of methodological approaches that could be used to measure remote primary health care service staff members' preferences.A rationale is provided for using a Best‐Worst Scaling Object Case methodological approach for measuring primary health care service staff members' preferences in remote Aboriginal health care settings.

This study compares a range of methodological approaches that could be used to measure remote primary health care service staff members' preferences.

A rationale is provided for using a Best‐Worst Scaling Object Case methodological approach for measuring primary health care service staff members' preferences in remote Aboriginal health care settings.