Delivering healthcare efficiency – can AI help identify performance issues

The packaging and delivery of treatment in developed economies across the world are often inefficient, ineffective and unfriendly to consumers/patients, resulting in soaring costs and much publicised medical errors (Herzlinger, 2006). The situation in developing economies differs little (Gok and Sezen, 2013; Yang and Zeng, 2014; Alonso et al., 2015). Such evidence suggests the shared goal of performance improvement is equally elusive to all healthcare systems, regardless of structure, funding arrangements and economic development. Building on our previous qualitative research which explored strategy development and implementation in the NHS, this paper presents the initial findings from our continuing longitudinal study into performance in the UK healthcare provider, the NHS. Our objective was to examine hospital performance to see if those hospitals who had heavily invested in managerial interventions such as lean or new public management performed any better than others. The NHS has been subjected to many cost-saving initiatives and strategic restructuring and has multiple targets which cover financial, clinical and operational aspects of service design and delivery. The most recent, the Carter Review (2016) suggested a number of approaches to limit unwarranted variation and thus improve overall performance. To date, no step change in improvement has been achieved, despite such concerted efforts. We propose that core principles of Operations Management theory (Deming, 1986; Schmenner and Swink, 1998) can provide means of addressing unwarranted performance variation and unlock targeted performance potential. This is particularly relevant in the current era where organisations commit to being Lean and Agile without necessarily fulfilling these aspirations. We develop the Swift Even Flow Capability Cycle as a key ingredient to managing service operations within healthcare.