Prospective observational study on the construction of a next-generation medical operations support system and hospital operations efficiency and reduction of medical staff burden through AI and digital technology

Prospective observational study on the construction of a next-generation medical operations support system and hospital operations efficiency and reduction of medical staff burden through AI and digital technology - Project R (AI & DX): Next-generation hospital management and workload reduction using AI

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000061004

Enrollment

Registered

2026-03-21

Start date

2026-03-19

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hospital Administration and Management, AI and Digital Technology, Reduction of Medical Staff Burden, Acute Care

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1. Management projects deliberated or decided upon in the strategy meetings of the Business Planning and Strategy Office. 2. Budget and financial closing data of all departments and management statistical records. 3. Minutes of strategy meetings and records of associated decision-making processes.

Exclusion criteria

Exclusion criteria: Routine maintenance and management tasks not directly related to the implementation of this system. Other records deemed inappropriate for this study by the principal investigator.

Design outcomes

Primary

Measure	Time frame
Integrated index of hospital operation efficiency and burden reduction: trends in time required for major decision-making (e.g., bed adjustment, emergency acceptance) and changes in physician overtime hours.	—

Secondary

Measure	Time frame
Labor environment indicators (overtime hours) Management indicators (operating income, labor distribution rate) Work efficiency indicators (time reduced by AI automation) Operational indicators (patient volume, wait times, surgery room usage) Psychological indicators (burnout scale, AI acceptance)	—

Countries

Japan

Contacts

Public ContactTAKEHIRO IZUMO

Japanese Red Cross Medical Center Business Planning and Strategy Office and Department of Respiratory Medicine

izumo_takehiro@med.jrc.or.jp09074122408

Outcome results