Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas

Jean Paul Sebastian Piest; Masahiro Jinzaki; Yoshimasa Masuda; Masako Toriya; Osamu Nakamura; Tetsuya Toma

doi:10.1007/978-3-031-54712-6_1

Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas

Jean Paul Sebastian Piest
, Masahiro Jinzaki
, Yoshimasa Masuda
, Masako Toriya
, Osamu Nakamura
, Tetsuya Toma

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

Abstract

In March 2023, the five-year AI Hospital Program in Japan was completed. Various AI-applications have been implemented in four model AI Hospitals. This paper contains the results of a multiple use case analysis of an AI Hospital using the AIDAF and the intelligence amplification design canvas. The aim of this research paper is two-fold to: 1) evaluate the utility of the AIDAF and intelligence amplification design canvas to analyse implemented AI-applications, and 2) conduct a multiple use case analysis in an AI Hospital. A focus group was created and developed a three-step process to analyse nine use cases and related AI-applications that have been implemented at Keio University Hospital using the AIDAF and intelligence amplification design canvas. First, each use case was analysed using the four guiding principles of the intelligence amplification design canvas. Second, conceptual representations were created for each use case. Third, an aggregated view of the AI Hospital was created. The results and findings were discussed in five focus group meetings. This study provides empirical support that the AIDAF and the intelligence amplification design canvas can effectively support the individual analysis of implemented AI-applications as well as conducting a multiple use case analysis. As such, this study provided insight in the current state of the AI Hospital and identified opportunities for extensions and future development in the second term of the AI Hospital Program and Open Healthcare Platform 2030 consortium. The current study was mainly based on qualitative analysis and comparison implemented AI-applications within a single organization and did not include in-depth user research. Future research may contribute to the analysis of similar use cases in other (AI-)hospitals to conduct a cross use case analysis.

Original language	English
Title of host publication	Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers
Editors	Tiago Prince Sales, Sybren de Kinderen, Henderik A. Proper, Luise Pufahl, Dimka Karastoyanova, Marten van Sinderen
Publisher	Springer
Pages	5-22
Number of pages	18
ISBN (Electronic)	978-3-031-54712-6
ISBN (Print)	978-3-031-54711-9
DOIs	https://doi.org/10.1007/978-3-031-54712-6_1
Publication status	Published - 2 Mar 2024
Event	27th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2023 - the Bernoulli Institute at the University of Groningen, Groningen, Netherlands Duration: 30 Oct 2023 → 3 Nov 2023 Conference number: 27 https://www.rug.nl/research/bernoulli/conf/

Publication series

Name	Lecture Notes in Business Information Processing
Volume	498 LNBIP
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Conference

Conference	27th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2023
Abbreviated title	EDOC 2023
Country/Territory	Netherlands
City	Groningen
Period	30/10/23 → 3/11/23
Internet address	https://www.rug.nl/research/bernoulli/conf/

Keywords

AI
Hospital
Intelligence Amplification
Design Canvas
Enterprise Architecture
Focus Group
Multiple Use Case Analysis
Digital Healthcare
NLA

Access to Document

10.1007/978-3-031-54712-6_1

Cite this

Piest, J. P. S., Jinzaki, M., Masuda, Y., Toriya, M., Nakamura, O., & Toma, T. (2024). Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas. In T. P. Sales, S. de Kinderen, H. A. Proper, L. Pufahl, D. Karastoyanova, & M. van Sinderen (Eds.), Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers (pp. 5-22). (Lecture Notes in Business Information Processing; Vol. 498 LNBIP). Springer. https://doi.org/10.1007/978-3-031-54712-6_1

Piest, Jean Paul Sebastian ; Jinzaki, Masahiro ; Masuda, Yoshimasa et al. / Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas. Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers. editor / Tiago Prince Sales ; Sybren de Kinderen ; Henderik A. Proper ; Luise Pufahl ; Dimka Karastoyanova ; Marten van Sinderen. Springer, 2024. pp. 5-22 (Lecture Notes in Business Information Processing).

@inproceedings{3d3ae909fb7f4095a2ad4bb395c5c654,

title = "Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas",

abstract = "In March 2023, the five-year AI Hospital Program in Japan was completed. Various AI-applications have been implemented in four model AI Hospitals. This paper contains the results of a multiple use case analysis of an AI Hospital using the AIDAF and the intelligence amplification design canvas. The aim of this research paper is two-fold to: 1) evaluate the utility of the AIDAF and intelligence amplification design canvas to analyse implemented AI-applications, and 2) conduct a multiple use case analysis in an AI Hospital. A focus group was created and developed a three-step process to analyse nine use cases and related AI-applications that have been implemented at Keio University Hospital using the AIDAF and intelligence amplification design canvas. First, each use case was analysed using the four guiding principles of the intelligence amplification design canvas. Second, conceptual representations were created for each use case. Third, an aggregated view of the AI Hospital was created. The results and findings were discussed in five focus group meetings. This study provides empirical support that the AIDAF and the intelligence amplification design canvas can effectively support the individual analysis of implemented AI-applications as well as conducting a multiple use case analysis. As such, this study provided insight in the current state of the AI Hospital and identified opportunities for extensions and future development in the second term of the AI Hospital Program and Open Healthcare Platform 2030 consortium. The current study was mainly based on qualitative analysis and comparison implemented AI-applications within a single organization and did not include in-depth user research. Future research may contribute to the analysis of similar use cases in other (AI-)hospitals to conduct a cross use case analysis.",

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author = "Piest, \{Jean Paul Sebastian\} and Masahiro Jinzaki and Yoshimasa Masuda and Masako Toriya and Osamu Nakamura and Tetsuya Toma",

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Piest, JPS, Jinzaki, M, Masuda, Y, Toriya, M, Nakamura, O & Toma, T 2024, Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas. in TP Sales, S de Kinderen, HA Proper, L Pufahl, D Karastoyanova & M van Sinderen (eds), Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers. Lecture Notes in Business Information Processing, vol. 498 LNBIP, Springer, pp. 5-22, 27th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2023, Groningen, Netherlands, 30/10/23. https://doi.org/10.1007/978-3-031-54712-6_1

Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas. / Piest, Jean Paul Sebastian; Jinzaki, Masahiro; Masuda, Yoshimasa et al.
Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers. ed. / Tiago Prince Sales; Sybren de Kinderen; Henderik A. Proper; Luise Pufahl; Dimka Karastoyanova; Marten van Sinderen. Springer, 2024. p. 5-22 (Lecture Notes in Business Information Processing; Vol. 498 LNBIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas

AU - Piest, Jean Paul Sebastian

AU - Jinzaki, Masahiro

AU - Masuda, Yoshimasa

AU - Toriya, Masako

AU - Nakamura, Osamu

AU - Toma, Tetsuya

N1 - Conference code: 27

PY - 2024/3/2

Y1 - 2024/3/2

N2 - In March 2023, the five-year AI Hospital Program in Japan was completed. Various AI-applications have been implemented in four model AI Hospitals. This paper contains the results of a multiple use case analysis of an AI Hospital using the AIDAF and the intelligence amplification design canvas. The aim of this research paper is two-fold to: 1) evaluate the utility of the AIDAF and intelligence amplification design canvas to analyse implemented AI-applications, and 2) conduct a multiple use case analysis in an AI Hospital. A focus group was created and developed a three-step process to analyse nine use cases and related AI-applications that have been implemented at Keio University Hospital using the AIDAF and intelligence amplification design canvas. First, each use case was analysed using the four guiding principles of the intelligence amplification design canvas. Second, conceptual representations were created for each use case. Third, an aggregated view of the AI Hospital was created. The results and findings were discussed in five focus group meetings. This study provides empirical support that the AIDAF and the intelligence amplification design canvas can effectively support the individual analysis of implemented AI-applications as well as conducting a multiple use case analysis. As such, this study provided insight in the current state of the AI Hospital and identified opportunities for extensions and future development in the second term of the AI Hospital Program and Open Healthcare Platform 2030 consortium. The current study was mainly based on qualitative analysis and comparison implemented AI-applications within a single organization and did not include in-depth user research. Future research may contribute to the analysis of similar use cases in other (AI-)hospitals to conduct a cross use case analysis.

AB - In March 2023, the five-year AI Hospital Program in Japan was completed. Various AI-applications have been implemented in four model AI Hospitals. This paper contains the results of a multiple use case analysis of an AI Hospital using the AIDAF and the intelligence amplification design canvas. The aim of this research paper is two-fold to: 1) evaluate the utility of the AIDAF and intelligence amplification design canvas to analyse implemented AI-applications, and 2) conduct a multiple use case analysis in an AI Hospital. A focus group was created and developed a three-step process to analyse nine use cases and related AI-applications that have been implemented at Keio University Hospital using the AIDAF and intelligence amplification design canvas. First, each use case was analysed using the four guiding principles of the intelligence amplification design canvas. Second, conceptual representations were created for each use case. Third, an aggregated view of the AI Hospital was created. The results and findings were discussed in five focus group meetings. This study provides empirical support that the AIDAF and the intelligence amplification design canvas can effectively support the individual analysis of implemented AI-applications as well as conducting a multiple use case analysis. As such, this study provided insight in the current state of the AI Hospital and identified opportunities for extensions and future development in the second term of the AI Hospital Program and Open Healthcare Platform 2030 consortium. The current study was mainly based on qualitative analysis and comparison implemented AI-applications within a single organization and did not include in-depth user research. Future research may contribute to the analysis of similar use cases in other (AI-)hospitals to conduct a cross use case analysis.

KW - AI

KW - Hospital

KW - Intelligence Amplification

KW - Design Canvas

KW - Enterprise Architecture

KW - Focus Group

KW - Multiple Use Case Analysis

KW - Digital Healthcare

KW - NLA

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DO - 10.1007/978-3-031-54712-6_1

M3 - Conference contribution

SN - 978-3-031-54711-9

T3 - Lecture Notes in Business Information Processing

SP - 5

EP - 22

BT - Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers

A2 - Sales, Tiago Prince

A2 - de Kinderen, Sybren

A2 - Proper, Henderik A.

A2 - Pufahl, Luise

A2 - Karastoyanova, Dimka

A2 - van Sinderen, Marten

PB - Springer

T2 - 27th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2023

Y2 - 30 October 2023 through 3 November 2023

ER -

Piest JPS, Jinzaki M, Masuda Y, Toriya M, Nakamura O, Toma T. Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas. In Sales TP, de Kinderen S, Proper HA, Pufahl L, Karastoyanova D, van Sinderen M, editors, Enterprise Design, Operations, and Computing. EDOC 2023 Workshops - IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, 2023, Revised Selected Papers. Springer. 2024. p. 5-22. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-031-54712-6_1

Multiple Use Case Analysis of an AI Hospital Using the AIDAF and Intelligence Amplification Design Canvas

Abstract

Publication series

Conference

Keywords

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