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Mental Health Optimal Staffing Tool (MHOST)

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Helps measure patient acuity and dependency to inform evidence-based decision making on staffing and workforce



Ensuring that NHS organisations have the right staff, with the right skills in the right place has been a key trust board requirement since the National Quality Board (NQB) guidance was published in 2016. This emphasises the need for developing evidence-based, patient need-driven staffing levels in all mental health care settings. This approach was further support by the NQB in 2018 in their mental health staffing improvement resource.

The Mental Health Optimal Staffing Tool (MHOST) is an easy-to-use multi-disciplinary, evidence based system that enables ward based clinicians to: (i) assess patient acuity and dependency; and (ii) convert  acuity and dependency data into a workload index and required FTEs using built-in staffing multipliers to ensure that ward establishments reflect patient needs.


Benefits of the Mental Health Optimal Staffing Tool (MHOST)

The MHOST embraces all the principles that should be considered when evaluating/implementing decision support tools described in ‘Safe, sustainable and productive staffing: An improvement resource for mental health (NHSI , 2018)'

  • How acuity and dependency are measured in mental health settings

  • How to ensure that accurate data can be collected

  • What quality metrics should be allied to acuity and dependency measurement to enhance staffing decision making

  • How to use staffing multipliers to support professional judgement in reviewing and setting clinical workforce establishments.

The development process

The development of the MHOST was commissioned and funded by Health Education England (HEE). The tool is based on five acuity and dependency levels for each mental health inpatient specialty. Each acuity and dependency level has an associated descriptor to enable clinical staff to score patients receiving care in their ward. These descriptors were developed by expert reference groups during the MHOST project.

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