Demand, capacity, and access of the outpatient clinic: A framework for analysis and improvement

Rationale While theoretical frameworks for optimization of the outpatient processes are abundant, practical step‐by‐step analyses to give leads for improvement, to forecast capacity, and to support decision making are sparse. Aims and objectives This article demonstrates how to evaluate and optimize the triad of demand, (future) capacity, and access time of the outpatient clinic using a structured six‐step method. Methods All individual logistical patient data of an orthopaedic outpatient clinic of one complete year were analysed using a 6‐step method to evaluate demand, supply, and access time. Trends in the data were retrospectively analysed and evaluated for potential improvements. A model for decision making was tested. Both the analysis of the method and actual results were considered as main outcomes. Results More than 25 000 appointments were analysed. The 6‐step method showed to be sufficient to result in valuable insights and leads for improvement. While the overall match between demand and capacity was considered adequate, the variability in capacity was much higher than in demand, thereby leading to delays in access time. Holidays and subsequent weeks showed to be of great influence for demand, capacity, and access time. Using the six‐step method, several unfavourable characteristics of the outpatient clinic were revealed and a better match between demand, supply, and access time could have been reached with only minor adjustments. Last, a clinic specific prediction and decision model for demand and capacity was made using the 6‐step method. Conclusions The 6‐step analysis can successfully be applied to redesign and improve the outpatient health care process. The results of the analysis showed that national holidays and variability in demand and capacity have a big influence on the outpatient clinic. Using the 6‐step method, practical improvements in outpatient logistics were easily found and leads for future decision making were contrived.