Use of discrete event simulation to improve a mental health clinic

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Introduction

Depression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature.

Methods

This paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK.

Results and discussion

The framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings.

Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department

Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department.

Integrating Science and Engineering to Implement Evidence-Based Practices in Health Care Settings

Integrating two distinct and complementary paradigms, science and engineering, may produce more effective outcomes for the implementation of evidence-based practices in health care settings. Science formalizes and tests innovations, whereas engineering customizes and optimizes how the innovation is applied tailoring to accommodate local conditions. Together they may accelerate the creation of an evidence-based healthcare system that works effectively in specific health care settings. We give examples of applying engineering methods for better quality, more efficient, and safer implementation of clinical practices, medical devices, and health services systems. A specific example was applying systems engineering design that orchestrated people, process, data, decision-making, and communication through a technology application to implement evidence-based depression care among low-income patients with diabetes. We recommend that leading journals recognize the fundamental role of engineering in implementation research, to improve understanding of design elements that create a better fit between program elements and local context.

Optimization of healthcare supply chain in context of macro-ergonomics factors by a unique mathematical programming approach

This study presents an integrated approach for analyzing the impact of macro-ergonomics factors in healthcare supply chain (HCSC) by data envelopment analysis (DEA). The case of this study is the supply chain (SC) of a real hospital. Thus, healthcare standards and macro-ergonomics factors are considered to be modeled by the mathematical programming approach. Over 28 subsidiary SC divisions with parallel missions and objectives are evaluated by analyzing inputs and outputs through DEA. Each division in this HCSC is considered as decision making unit (DMU). This approach can analyze the impact of macro-ergonomics factors on supply chain management (SCM) in healthcare sector. Also, this method ranks the relevant performance efficiencies of each HCSC. In this study by using proposed method, the most effective macro-ergonomics factor on HCSC is identified as "teamwork" issue. Also, this study would help managers to identify the areas of weaknesses in their SCM system and set improvement target plan for the related SCM system in healthcare industry. To the best of our knowledge, this is the first study for macro-ergonomics optimization of HCSC.

Health systems engineering fellowship: curriculum and program development

Industrial engineering and related disciplines have been used widely in improvement efforts in many industries. These approaches have been less commonly attempted in health care. One factor limiting application is the limited workforce resulting from a lack of specific education and professional development in health systems engineering (HSE). The authors describe the development of an HSE fellowship within the United States Department of Veterans Affairs, Veterans Health Administration (VA). This fellowship includes a novel curriculum based on specifically established competencies for HSE. A 1-year HSE curriculum was developed and delivered to fellows at several VA engineering resource centers over several years. On graduation, a majority of the fellows accepted positions in the health care field. Challenges faced in developing the fellowship are discussed. Advanced educational opportunities in applied HSE have the potential to develop the workforce capacity needed to improve the quality of health care.