Lean Healthcare Improvement Model Using Simulation-Based Lean Six-Sigma and TRIZ

Abstract

As a part of primary care clinic, the Indonesian-community health center is responsible for efforts to encourage independence and create a community for healthy living. The service facility commonly used is the general polyclinic. A number of problems occur are non-value added activities that lead to a longer waiting time. Therefore, the aim of this study is to improve the service performance at Indonesian-community health center. This research used six sigma DMAIC model in evaluating the current service system using value stream mapping (VSM), determining critical waste using the Borda count method, identifying the root causes of critical waste, designing the alternative service system improvements using theory of inventive problem solving (TRIZ), building alternative simulation models using Flexsim software, and evaluate the improvement plan. The result shows that the average time of general polyclinic services in current system is 107 minutes with waiting as critical waste (23%). There are two health-service improvement scenarios developed using theory of inventive problem-solving method (TRIZ), i.e. scenario 1 and scenario 2. Both scenarios are evaluated by considering some criterias, i.e. idle time, waiting time, number of patients served, lead-time and process cycle efficiency. The best scenario is scenario 2 with 48.2% reduction in lead time and process cycle efficiency increased by 48%.

Lean, Six Sigma, and Simulation: Evidence from Healthcare Interventions

“…Then, simulations of future scenarios are developed in the analysis and improvement stages [65,66,135,150]. In this way, VSM provides insightful data from the process, e.g., cycle time, which is then used as an input for simulating possible changes and scenarios [134]. Afterwards, simulation is also used for both objectives, evaluation [154] and validation [139].…”

“…Therefore, VSM is a good starting point since it depicts the stream of processes from the customer's point of view [70]; however, it must be taken into account that conventional VSM does not specifically represent variability [163]. In fact, simulations are needed to model complex healthcare value streams such as patient queues [134]. Therefore, the optimization of VSM is a typical multiple-attribute decisionmaking (MADM) problem that involves the evaluation of multiple performance metrics such as inventory levels, lead times, and service levels [164].…”