RT Journal Article
SR Electronic
T1 Operations management on the front line of COVID-19 vaccination: building capability at scale via technology-enhanced learning
JF BMJ Open Quality
JO BMJ Open Qual
FD British Medical Journal Publishing Group
SP e001372
DO 10.1136/bmjoq-2021-001372
VO 10
IS 3
A1 Smith, Iain M
A1 Bayliss, Elaine
A1 Salisbury, Hollie
A1 Wheeler, Ali
YR 2021
UL http://bmjopenquality.bmj.com/content/10/3/e001372.abstract
AB The globe is gripped by the COVID-19 pandemic. Mass population vaccination is seen as the solution. As vaccines become available, governments aim to deploy them as rapidly as possible. It is important, therefore, that the efficiency of vaccination processes is optimal.Operations management is concerned with improving processes and comprises systematic approaches such as Lean. Lean focuses explicitly on process efficiency through the elimination of non-value adding steps to optimise processes for those who use and depend on them.Technology-enhanced learning can be a strategy to build improvement capability at scale. A massive online programme to build capability in Lean has been developed by the regulator of England's National Health Service. Beta testing of this programme has been used by some test sites to refine their COVID-19 vaccination processes. The paper presents a case example of massive online learning supporting the use of Lean in the day-to-day operations management of COVID-19 vaccine processes.The case example illustrates the challenges that vaccination processes may present and the need for responsive and effective operations management. Building capability to respond rapidly and systematically in dynamic situations to optimise flow, safety and patient experience may be beneficial.Given the national imperative to achieve mass vaccination as rapidly as possible, systematic improvement methods such as Lean may have a contribution to make. Massive online programmes, such as that described here, may help with this effort by achieving timely knowledge transfer at large scale.All data relevant to the study are included in the article.