Application of Automation and Manufacture techniques oriented to a service-based business using the Internet of Things (IoT) and Industry 4.0 concepts. Case study: Smart Hospital

Flórez, Camilo Andrés Cáceres; Rosário, João Mauricio; Hurtado, Dario Amaya

doi:10.1590/0104-530X5416-20

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Thematic Section: Digital Transformation, Intelligent Manufacturing and Supply Chain Management 4.0 • Gest. Prod. 27 (3) • 2020 • https://doi.org/10.1590/0104-530X5416-20 copy

Application of Automation and Manufacture techniques oriented to a service-based business using the Internet of Things (IoT) and Industry 4.0 concepts. Case study: Smart Hospital

Aplicação de técnicas de Atomação e Manufatura orientadas para um Modelo de Negócios baseado em serviços, usando o conceito de Internet das Coisas (IoT) e Indústria 4.0. Estudo de caso: Hospital Inteligente

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract:

The implementation of Manufacture and Automation techniques is mandatory in the current world. Mainly, the enhancement and progress of healthcare are fundamental in wellbeing improvement. This paper points to the utilization of the Internet of Things (IoT) and Industry 4.0 concepts oriented to the optimization of a Smart Hospital using the Hospital Emergency Department (HED) as a case study. This proposal focuses on the development of a smart Hospital-based of the IoT, Industry 4.0, Health 4.0, and other current technology. On the other hand, the use of a computational simulation tool like the Discrete Event Simulation Model (DES) will allow the test, recognition, and reduction of bottlenecks in the HED workflow. The issue given by the bottlenecks is automatically controlled using an improved dynamic shift management proposal based on control theory, forecasting methods, and telemedicine. The results show an improvement in the use of the resources and a reduction of the length of stay that directly reduces the HED mortality rate, improving the service quality. The objective of this paper is to propose a simulation tool-based on DES for a selected HED, using forecasting methods of the patients’ arrival in a HED using the Autoregressive integrated moving average (ARIMA) model. Following the forecasted entries, a proposal for bottleneck avoidance using a HED DES was realized. The forecasting data provided useful predictive information for the improvement of the HED workflow. As well as the analyzed data of a traditional HED system is helpful to solve the overcrowding problem. Finally, the use of simulation tools allows the test and validation of novel proposals for two smart HED optimization proposals following e-Health and Hospital 4.0 principles.

Keywords:
Emergency Department; Smart Hospital; Discrete Event Simulation; Hospital 4.0; Health 4.0; Smart Decision Support Tool

Stage	Probability Distribution (Minutes)	Staff	Abbreviation	Current Staff
Reception	Uniform (5,10)	Receptionist	R (Receptionist)	2
Lab Tests	Triangular (10, 20, 30)	Laboratory Technician	T (Laboratory Technician)	3
Examination Room	Uniform (10, 20)	Physician	D (Physician Doctor)	2
Reexamination Room	Uniform (7,12)	Physician	D (Physician Doctor)	2
Treatment Room (TR)	Uniform (20,30)	TR Nurse	TN (Treatment Room Nurse)	1
Emergency Room (ER)	Uniform (60,120)	ER Nurse	EN (Emergency Room Nurse)	9

Key Performance Indicator (KPI)	Traditional HED		Smart HED 1		Smart HED 2
Key Performance Indicator (KPI)	Value	STD	Value	STD	Value	STD
Expected Time in System (h): Total	3.68	0.7	2.73	0.27	2.69	0.26
Expected Number Out (patients/ hour)	4.66	0.27	7.55	0.39	7.55	0.38
Average Waiting Time (min): Reception	0	0	0	0	0	0
Average Waiting Time (min): Laboratory	0.54	0.3	40.94	22.2	38.73	21.72
Average Waiting Time (min): Doctor	84.67	25.62	19.35	0.5	18.89	0.63
Average Waiting Time (min): Emergency Room	0.03	0.16	0.95	2.13	0.9	1.68
Average Waiting Time (min): Treatment Room	19.7	11.11	15.11	9.75	15.37	10.49
Average Queue Length: Reception	0	0	0	0	0	0
Average Queue Length: Laboratory	0.05	0.03	5.62	3.33	5.3	3.22
Average Queue Length: Doctor	17.83	5.55	5.2	0.18	5.07	0.2
Average Queue Length: Emergency Room	0	0.01	0.06	0.14	0.05	0.1
Average Queue Length: Treatment Room	0.61	0.41	0.85	0.61	0.87	0.67
Utilization (%): Reception	0.28	0.01	0.34	0.01	0.34	0.01
Utilization (%): Laboratory	0.5	0.05	0.63	0.06	0.63	0.06
Utilization (%): Doctor	0.96	0.01	0.83	0.04	0.83	0.04
Utilization (%): Emergency Room	0.34	0.04	0.41	0.05	0.41	0.05
Utilization (%): Treatment Room	0.64	0.09	0.48	0.05	0.48	0.05

Key Performance Indicator (KPI)	Trad. HED vs S-HED 1		Trad. HED vs S-HED 2		S-HED 1 vs S-HED 2
Key Performance Indicator (KPI)	Difference	Improve (%)	Difference	Improve (%)	Difference	Improve (%)
Expected Time in System (h)	0.95	26	0.99	27	0.04	1
Expected Number Out (patients/h)	2.89	62	2.89	62	0.00	0.00
Avg Waiting Time (min): Reception	0.00	-	0.00	-	0.00	-
Avg Waiting Time (min): Laboratory	-40.40	-	-38.19	-	2.21	5
Avg Waiting Time (min): Doctor	65.32	77	65.78	78	0.46	2
Avg Waiting Time (min): Emergency Room	-0.92	-	-0.87	-	0.05	5
Avg Waiting Time (min): Treatment Room	4.59	23	4.33	0.22	-0.26	-2
Avg Queue Length: Reception	0.00	-	0.00	-	0.00	-
Avg Queue Length: Laboratory	-5.57	-	-5.25	-	0.32	6
Avg Queue Length: Doctor	12.63	71	12.76	72	0.13	3
Avg Queue Length: Emergency Room	-0.06	-	-0.05	-	0.01	17
Avg Queue Length: Treatment Room	-0.24	-39	-0.26	-43	-0.02	-2
Utilization (%): Reception	0.06	21	0.06	21	0.00	0.00
Utilization (%): Laboratory	0.13	26	0.13	26	0.00	0.00
Utilization (%): Doctor	-0.13	-14	-0.13	-14	0.00	0.00
Utilization (%): Emergency Room	0.07	21	0.07	21	0.00	0.00
Utilization (%): Treatment Room	-0.16	-25	-0.16	-25	0.00	0.00

Key Performance Indicator (KPI)	Traditional HED		S-HED 1		S-HED 2
Key Performance Indicator (KPI)	Value	STD	Value	STD	Value	STD
Expected Time in System (h): Total	3.68	0.7	2.73	0.27	2.69	0.26
Expected Number Out (patients/ hour)	4.66	0.27	7.55	0.39	7.55	0.38
Average Waiting Time (min): Reception	0	0	0	0	0	0
Average Waiting Time (min): Laboratory	0.54	0.3	40.94	22.2	38.73	21.72
Average Waiting Time (min): Physician Room	84.67	25.62	19.35	0.5	18.89	0.63
Average Waiting Time (min): Emergency Room	0.03	0.16	0.95	2.13	0.9	1.68
Average Waiting Time (min): Treatment Room	19.7	11.11	15.11	9.75	15.37	10.49
Average Queue Length: Reception	0	0	0	0	0	0
Average Queue Length: Laboratory	0.05	0.03	5.62	3.33	5.3	3.22
Average Queue Length: Physician Room	17.83	5.55	5.2	0.18	5.07	0.2
Average Queue Length: Emergency Room	0	0.01	0.06	0.14	0.05	0.1
Average Queue Length: Treatment Room	0.61	0.41	0.85	0.61	0.87	0.67
Utilization (%): Reception	0.28	0.01	0.34	0.01	0.34	0.01
Utilization (%): Laboratory	0.5	0.05	0.63	0.06	0.63	0.06
Utilization (%): Physician	0.96	0.01	0.83	0.04	0.83	0.04
Utilization (%): Emergency Room	0.34	0.04	0.41	0.05	0.41	0.05
Utilization (%): Treatment Room	0.64	0.09	0.48	0.05	0.48	0.05

Key Performance Indicator (KPI)	Trad. HED vs. S-HED1		Trad. HED vs. S-HED2		S-HED 1 vs. S-HED 2
Key Performance Indicator (KPI)	Difference	Improve (%)	Difference	Improve (%)	Difference	Improve (%)
Expected Time in System (h)	0.95	26	0.99	27	0.04	1
Expected Number Out (patients/h)	2.89	62	2.89	62	0.00	0.00
Avg Waiting Time (min): Reception	0.00	-	0.00	-	0.00	-
Avg Waiting Time (min): Laboratory	-40.40	-	-38.19	-	2.21	5
Avg Waiting Time (min): Physician	65.32	77	65.78	78	0.46	2
Avg Waiting Time (min): Emergency Room	-0.92	-	-0.87	-	0.05	5
Avg Waiting Time (min): Treatment Room	4.59	23	4.33	0.22	-0.26	-2
Avg Queue Length: Reception	0.00	-	0.00	-	0.00	-
Avg Queue Length: Laboratory	-5.57	-	-5.25	-	0.32	6
Avg Queue Length: Physician	12.63	71	12.76	72	0.13	3
Avg Queue Length: Emergency Room	-0.06	-	-0.05	-	0.01	17
Avg Queue Length: Treatment Room	-0.24	-39	-0.26	-43	-0.02	-2
Utilization (%): Reception	0.06	21	0.06	21	0.00	0.00
Utilization (%): Laboratory	0.13	26	0.13	26	0.00	0.00
Utilization (%): Physician	-0.13	-14	-0.13	-14	0.00	0.00
Utilization (%): Emergency Room	0.07	21	0.07	21	0.00	0.00
Utilization (%): Treatment Room	-0.16	-25	-0.16	-25	0.00	0.00

Universidade Federal de São Carlos Departamento de Engenharia de Produção , Caixa Postal 676 , 13.565-905 São Carlos SP Brazil, Tel.: +55 16 3351 8471 - São Carlos - SP - Brazil
E-mail: gp@dep.ufscar.br

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