Developing, testing and applying instruments for measuring rising dependency-acuity's impact on ward staffing and quality

Int J Health Care Qual Assur. 2009;22(1):30-9. doi: 10.1108/09526860910927934.


Purpose: This paper aims to explains how relatively simple nurse staffing formulas from "best practice" ward dependency-acuity data can be used for nursing workforce planning and development.

Design/methodology/approach: The paper combines literature, detailed ward surveys, workshop and expert group/stakeholder information to generate and test care levels/nurse multipliers for setting ward establishments.

Findings: The paper finds that professional-judgement based ward staffing can be abandoned, while complex acuity-quality, timed-task and regression-based nurse staffing algorithms for setting ward establishments may be unnecessary since the new multipliers, underpinned by robust validity and reliability testing, seem to be remarkably accurate nurse-staffing determiners at a fraction of the cost.

Research limitations/implications: As care levels and multipliers stand they are suitable only for UK National Health Service acute wards. Primary care, mental health, learning disability and other specialist group care levels and multipliers need developing.

Practical implications: Users, at a minimum, can adopt care level data and multiplier staffing recommendations for benchmarking purposes. Ultimately, the algorithms can be used to: adjust ward establishments according to workload; or set staffing for new, inpatient services.

Originality/value: The paper offers a simple system for assessing patients' nursing needs and setting ward staffing accordingly.

MeSH terms

  • Algorithms
  • Health Services Needs and Demand / organization & administration
  • Health Status*
  • Humans
  • Nursing Administration Research / organization & administration*
  • Personnel Staffing and Scheduling / organization & administration*
  • Quality Indicators, Health Care / organization & administration
  • Quality of Health Care / organization & administration*
  • Research Design*
  • United Kingdom