Element 4 involves determining the need for amended and new AHA roles and service delivery models. It also identifies priority areas to prepare for strategic planning.
Aims
Complete a needs analysis, including:
- analysis of qualitative data collected from focus groups and consultations with key stakeholders
- ratification of discipline and/or program/service tasks
- quantification of need
- identification of strategic goals and priority areas for integrating the allied health assistant (AHA) workforce.
Timeframe
Element 4 takes place in months four to seven of the recommended nine-month timeline.
Principles
Element 4 uses all three principles of consultation, organisational priorities and change management.
Element 4 activities guide the data analysis to identify:
- statistical evidence of services/programs/departments’ need for an increased or amended allied health assistant (AHA) workforce
- priority areas within the organisation – that is areas where the majority of time (percentage) is spent on tasks that could be delegated to an AHA
- competency requirements and job specifications for AHAs within a discipline/service/program or team
- current knowledge held by allied health practitioner (AHPs) in relation to AHA scope of practice
- current supervision and delegation skills of the AHPs.
Quantifying time that can delegated to an AHA
Using the quantification survey and baseline workforce staffing profile data, the Victorian Assistant Workforce Model (VAWM) quantifies time spent by AHPs on tasks that could be delegated to an AHA.
In addition, by applying a staffing factor that translates direct allied health clinical care time into full-time equivalent, the VAWM enables a true estimate of costs associated with introducing new AHA roles.
The VAWM database provides an analysis of the baseline workforce staffing profile and quantification data.
Victorian Assistant Workforce Model data collection tool(opens in a new window)Excel 6.24 MBInstructions for using the data collection and analysis tool for the Victorian Assistant Workforce Model(opens in a new window)Word 4.41 MBBy analysing workforce survey data, we can identify organisational attitudes and culture relating to the allied health assistant (AHA) workforce.
Workforce survey data will identify:
- the survey response rate (providing an indication of staff engagement in the Victorian Assistant Workforce Model)
- job satisfaction of AHAs and AHPs relative to skill level, length of employment within the organisation, discipline, program or team
- the confidence of AHPs in delegating to the current AHA workforce
- the confidence of AHPs in the skills of the current AHA workforce
- trends in current use of AHAs by AHPs
- attitudes of staff in relation to the current and future AHA workforce
- perceived gaps in AHA availability, competency, and training and development needs
- identification of potential new and/or re-designed AHA roles
- qualitative data that can contribute to the development of the quantification survey.
Conducting data analysis
Data can be grouped and analysed in an Excel spreadsheet in a way that is relevant to the organisation and project scope.
Filtering data
Filtering data helps to narrow the focus of the worksheet, allowing you to view only the information you need [1].
To analyse the workforce survey data:
- filter data from the survey in discrete teams, services or disciplines to identify themes specific to this population. For example, filter the data by team to analyse the data from inpatient orthopaedic team
- compare data between populations and examine data patterns across the organisation
- identify findings relevant to organisational priorities and key stakeholders. For example, analyse data by discipline to report findings to discipline managers, or analyse data by service to report findings to service managers.
Hints
- To ensure respondents to the workforce survey cannot be identified, group responses together when analysing results. For example if there are three staff in the speech therapy department, include the results from those respondents in the results of a larger department to ensure all results have a group of no less than 10.
Reporting workforce survey data
Report data by discipline, program team/service, or individual organisational sites depending on the organisation’s project scope.
Provide reports to key stakeholders according to their needs. For example, aggregate data may be relevant for the steering committee, while data by discipline may be most meaningful to the AHP and AHA workforce.
Consideration should be given to how workforce survey results are best represented in visual and written formats. See the downloads section for further guidance in reporting workforce survey data.
Activity outputs
- Workforce survey data report (for inclusion in final report).
References
1. GCFLearnFree.org 2013, ‘Excel 2013 filtering data’, viewed 19 March 2015
Analyse focus group data to verify or adapt tasks from the allied health assistant (AHA) task list that are suitable for AHAs for your organisation.
You can also use the data to identify themes about culture, attitudes and barriers to the AHA workforce (including new roles and current skills in delegation). These themes can be addressed in the AHA workforce strategic plan (Element 5).
To analyse focus group data:
- Group data into common themes.
- Seek feedback, but be mindful that the level of consultation will depend on the timeframes of the project.
- Consult with the steering committee and with staff (informally or in further focus groups) to home in on a particular theme. Seek clarification until the data grouping can inform the quantification survey in the context of the organisation.
- Consult with managers to ratify tasks on the AHA task list.
Hints
- Analyse qualitative data objectively. Declare any bias. Include all qualitative data in the analysis, including stand-alone data, or data that doesn’t seem to ‘fit’.
- Identify, address and discuss barriers to increasing the AHA workforce or AHA use. This will facilitate discussion about opportunities for change. The success of the project relies on an increase in AHP confidence, in their ability to provide delegation and supervision and in AHA capacity to perform particular tasks.
- Pages 32–38 of Health Workforce Australia’s The assistants and support workers: workforce flexibility to boost productivity – full report outline barriers and potential solutions to AHA use.
Activity outputs
- AHA task list finalised.
- Findings in relation to opportunities, barriers and solutions to change documented for inclusion in final report.
Using the baseline workforce staffing profile data, you can calculate survey response rates and identify priority areas of the allied health assistant (AHA) workforce. It also provides a before-and-after measure of the workforce composition so you can judge the effectiveness of the project.
Analysis of this data also provides the following information for the AHA and allied health practitioner (AHP) workforce:
- current budgeted full-time equivalent (FTE)
- baseline workforce compositions (AHA and AHP FTE as a percentage of the workforce).
Apply the current budgeted FTE to the quantification data in the Victorian Assistant Workforce Model (VAWM) database to determine the current percentage of AHP time spent on AHA tasks (see Activity 4.4).
Analysis of the baseline workforce staffing profile data
Use the VAWM database template to generate the following reports for the baseline workforce staffing profile data:
- current budgeted FTE of AHP and AHA workforce
- AHA percentage of workforce by site, discipline or team
- AHP percentage of workforce by site, discipline or team
- clinical incidents by site
- wait list (number of weeks) by site.
Calculations
To determine the baseline workforce staffing profile data without using the VAWM database template, apply the following calculations:
AHP % = (AHP FTE / (AHA FTE + AHP FTE)) x100
AHA % = (AHA FTE/ (AHA FTE + AHP FTE)) x 100
Activity outputs
- Current budgeted FTE recorded.
- Workforce composition (%) for AHA and AHP workforce calculated and recorded.
- Wait lists recorded (optional).
- Clinical incidents recorded (optional).
Victorian Assistant Workforce Model data collection tool(opens in a new window)Excel 6.24 MBInstructions for using the data collection and analysis tool for the Victorian Assistant Workforce Model(opens in a new window)Word 4.41 MBThe quantification surveys provide a raw data set that identifies time spent by an AHP on tasks that could be delegated to an allied health assistant (AHA).
You can use the Victorian Assistant Workforce Model (VAWM) database template to collate the individual quantification surveys.
Victorian Assistant Workforce Model data collection tool(opens in a new window)Excel 6.24 MBInstructions for using the data collection and analysis tool for the Victorian Assistant Workforce Model(opens in a new window)Word 4.41 MBCollated data can be analysed to identify time in minutes, hours, converted hours, full-time equivalent (FTE) and percentage of allied health practitioner (AHP) time spent on tasks.
The database allows you to analyse the organisation as a whole, or targeted areas such as programs, services or disciplines so you can identify priority areas.
The analysis of the quantification data by the VAWM database template is further defined and described in the data analysis guide.
Data analysis guide: Activity 4.4(opens in a new window)Word 238 KBConverting data to real FTE for AHAs
The data collated from the quantification surveys accounts for the raw time AHPs spend on AHA tasks.
However it does not account for the time needed to complete all the requirements of a position such as paid breaks, public holidays and leave entitlements. These need to be included to provide an accurate FTE that can guide recruitment and scoping for AHA roles.
To convert the raw data to FTE, you can apply a staffing factor. This is a number used to transform the raw data to the FTE of a position, taking into account these role requirements.
Alfred Health developed the Allied Health Staffing Factor (AHSF) to calculate the true costs and FTE requirements of allied health clinical roles [1].
Reporting on the quantification data analysis
Determine how needs analysis results are best represented in visual and written formats. See the downloads section for further guidance in reporting quantification data.
Activity outputs
- AHP time spent on AHA tasks in minutes identified.
- Total hours AHP spent on AHA tasks identified.
- AHP time spent on AHA tasks represented in FTE (optional) identified.
- Percentage of current budgeted AHP FTE spent on AHA tasks identified.
- Priority areas for AHA workforce reform identified.
References
1. 10th National Allied Health Conference 2013, ‘Educate, motivate, innovate, celebrate’, 16–18 October 2013, Brisbane Convention and Exhibition Centre.
Cross-referencing the data analysis from each of the data collection methods will help you to identify common themes.
These themes will highlight your organisation’s priorities, or identify conflicting evidence that prompts further analysis.
Areas for further analysis can be included in the strategic plan (Element 5).
Identification of priority areas
Review all data to determine if there is evidence to support qualitative findings.
For example, did AHAs and AHPs identify barriers that prevented using the current AHA workforce to its full scope? Does the quantitative data support these findings?
Example
One service reported consistently that they had adequate access to AHAs but a low level of confidence in delegating to AHAs.
The quantification survey results identifies that the same team is currently spending the equivalent of 0.5 full-time equivalent (FTE) on tasks that could be delegated to an AHA.
This may indicate that the AHP workforce needs further training in supervision and delegation of AHAs, or the competencies of the AHA workforce need to be reviewed relative to the needs of this service.
Activity outputs
- Priority areas for the AHA workforce identified.
- Areas requiring further analysis identified.
- Barriers and solutions to maximising use or increasing capacity of an AHA workforce identified.
Data analysis guide: Activity 4.4(opens in a new window)Word 238 KB
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