Capacity planning in Specialized Healthcare

Doctoral thesis, 2018

The purpose of the thesis is to contribute to the knowledge of healthcare capacity planning for effective use of resources. Capacity planning concerns the balancing of the demand for capacity with the available capacity of the production system. Within the healthcare setting, various studies report on the difficulties of providing healthcare services according to patient demand. So, how can the balance between required and available capacity be achieved? How can we use our resources in accordance with what the patients need?

The research presented in this thesis is based on five research questions which are answered by the results of five case studies made at Swedish hospital departments. The research questions concern how discrepancies between practice and capacity planning theory may affect production performance; what a tactical capacity planning framework in healthcare would comprise; on what conditions rough-cut capacity methods (RCCP) are applicable in healthcare; the importance of including the knowledge of the surgeons when estimating required capacity; and if a team-based workflow can be employed without compromising production performance. The five research questions are answered through five individual studies, all with a case study approach.

The findings presented in this thesis provide knowledge regarding the structure of capacity planning processes; more specifically regarding the linkages between capacity planning processes and their effects on production performance. Furthermore, the research provides a step-by-step framework for tactical capacity planning to improve production performance by keeping a long-term perspective when planning. The tactical framework describes the structure of the capacity planning process and its included activities. Additionally, the framework gives an account of required information for the planning process and proposes possible adjustment to balance demand and supply. The output of the planning process is also described. To support the task of balancing required and available capacity two studies contribute to the interpretation of patient demand into required capacity. First, conditions under which rough-cut capacity planning methods are applicable in a healthcare setting are studied and discussed. Second, the research extends existing knowledge of the estimation of required surgery time, based on surgeons’ subjective knowledge of the patient condition and thereby decreasing the risk of exceeding the scheduled surgery time. As concerns assessing available capacity, the research studies the use of a team-based work method, which shows an increase of productivity compared with a functionally divided production system, while maintaining the same level of resources. In a capacity planning perspective, the use of teams simplifies the assessment of available capacity by reducing the number of planning points from individual workers to the number of teams.