Forecasting the residual service life of NHS hospital buildings: a stochastic approach

Abstract

Service life appraisal is an important facet of the management of the NHS estate portfolio. Existing approaches to remaining service life estimation use simple deterministic methods, which could yield inaccurate results. An alternative approach to forecasting the remaining life of hospital buildings, based upon a combination of weighted average techniques and a Markov property; the minimum of exponentials, is presented. The results from this model were compared with those obtained by means of existing techniques, and revealed an average percentage difference of 56.26%. This confirms the notion that stochastic approaches in combination with elemental weightings could yield greater accuracy. Whilst the results obtained can be used primarily to determine the overall residual service life of a hospital building, the model also allows the condition state transition probabilities to be calculated at a given time. On the macro level, this information can be used for optimization of maintenance strategies.

Keywords:

• Service life
• forecasting
• minimum of exponentials
• hospital buildings
• probability
• Markov chain
• stochastic forecasting