Developing a Mental Health Experience of Services (MHES) Survey for Scotland

Chapter Eight: Resource and budget considerations

This chapter presents an analysis of interviewees' views on the budget and resource implications of commissioning and conducting surveys and their specific considerations for the cost of a MHES survey.

Chapter summary

Key Findings and Further Considerations

• The cost of the MHES survey will depend on several factors, including:
• Target audience
• Sample size
• Methodology
• Level of analysis
• Online surveys were frequently highlighted as the most cost-effective approach.
• Consideration should be given to the staff time and resources required to:
• Manage and analyse the survey
• Support service improvements based on the survey findings

Interviewees repeatedly explained that the cost of the survey will depend on which of the many factors outlined throughout this report are chosen, such as the target audience, sample size, scale, ambition, methodology, level of analysis required, and dissemination of the survey.

Regarding data collection, online surveys were often highlighted as the most cost-effective approach, as they would not require physical paper surveys, postage or data entry. Interviewees also noted inflationary cost considerations for a paper survey, such as future increases in postage costs. Although an online survey could work for the majority of potential respondents, interviewees highlighted the need for accessibility to capture a range of voices and requested exploring other options to minimise barriers to completion and ensure some groups are not excluded.

Interviewees also noted the need to consider how much staff time and resources would be required to administer or analyse a MHES survey. It was suggested that as the complexity of the survey increases, the number of people required to administer, maintain, collect, analyse, and disseminate the survey will increase, as will overall costs. For example, resource requirements could depend on the selected data collection approach, how many people would access the data and results, the level of data reporting and reporting formats required, and the number of free text questions which require analysis. Ways to reduce analysis time and cost were suggested, such as using AI to analyse free text responses. Regarding the dissemination method, one interviewee noted that services may not want the results for their service to be publicly available. While this could be mitigated by a closed reporting system where different results can be accessed by different audiences, the need for different layers of data and account management would increase costs.

In addition, interviewees noted that consideration should be given to the resources required to support service improvements generated from the survey findings. One noted that, while this would be a bigger cost than the survey itself, there would be a return on investment in the survey in the form of improved quality of care.