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Lu R, Zhang Y, Luo L, Yuan Q, Chen S, Lv N, Zheng F, Deng G, Ma Y, Xu J, Chen Z, Zhang F. Increasing hospital administrative efficiency via optimized office automation systems: A PDCA cycle approach. PLoS One 2025; 20:e0321475. [PMID: 40299830 PMCID: PMC12040115 DOI: 10.1371/journal.pone.0321475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Accepted: 03/06/2025] [Indexed: 05/01/2025] Open
Abstract
BACKGROUND Increasing hospital administrative efficiency is crucial with regard to efforts to manage competitive pressures in healthcare. Despite extensive research on healthcare optimization, the role of Office Automation Systems (OASs) in administrative efficiency in the hospital context remains underexplored. This study addresses this gap by employing the plan-do-check-act (PDCA) cycle to improve administrative processes at the Second Affiliated Hospital, Zhejiang University School of Medicine. METHODS As part of this study, the root causes of inefficiencies in administrative processes were analyzed, and a PDCA cycle approach was implemented to address these inefficiencies. Monthly training sessions were conducted, and rankings were displayed to raise awareness of this topic among employees. A total of 41 high-frequency processes were monitored and divided into the categories of medical research, clinical use, and daily administrative work. Data were collected from 2021 to 2023, and statistical analyses were conducted via SPSS and R software. RESULTS Significant improvements in process implementation times were observed. With regard to clinical use processes, the median number of days required to process hospitalization and discharge procedures decreased from 4.33 in 2021 to 0.04 in 2023 (P < 0.001). Similarly, the number of days spent processing software requests decreased from 75.98 in 2021 to 31.33 in 2023 (P < 0.001). With respect to medical research processes, the median number of days required for animal laboratory access training applications decreased from 10.87 to 1.24 days (P < 0.01). Daily administrative processes also significantly improved, such that the median number of days spent on processing fixed asset disposal applications decreased from 5.96 to 4.21 (P < 0.01). CONCLUSION The application of the PDCA cycle significantly improved the efficiency of hospital administrative processes, thus highlighting the potential of this approach to serve as a valuable tool for continuous efforts to improve hospital administration. This study provides a framework for other hospitals seeking to increase their administrative efficiency via digital transformation and continuous quality improvement.
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Affiliation(s)
- Ruiwen Lu
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yiming Zhang
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Likang Luo
- Department of Artificial Intelligence and Information, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Quan Yuan
- The School of Management, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shuihong Chen
- Department of Quality Management Office, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Na Lv
- Department of Quality Management Office, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fenfang Zheng
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Guofang Deng
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yuefeng Ma
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jie Xu
- Department of Artificial Intelligence and Information, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zexin Chen
- Office of Scientific Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fengjiang Zhang
- Office of Party and Government Affairs, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Chen J, Chen Y, Liang X, Yu L, Sun J, Luo X, Zhang M, Wu Z. The mitigating effect of new digital technology on carbon emissions: evidence from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:9433-9444. [PMID: 38191736 DOI: 10.1007/s11356-023-31792-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/27/2023] [Indexed: 01/10/2024]
Abstract
This paper investigates the impacts of new digital technology on carbon emissions in China. To better capture the feature of new digital technology, we distinctively measure it using the invention patent stock of new generation information technology industry. The empirical results show that the development of new digital technology significantly reduces carbon dioxide (CO2) intensity. The results are still robust after addressing the endogeneity issues using instrumental variable regressions. The carbon reduction mechanisms of new digital technology include reducing energy intensity, optimizing energy structure, and advancing treatment technology. We further confirm the spatial spillover and nonlinear effects of new digital technology on CO2 intensity and the moderating effect of urban digitalization in carbon reduction. The study suggests that the potential of new digital technology in reducing carbon emissions should be highly attentioned by governments.
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Affiliation(s)
- Jun Chen
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China.
- The Key Lab of Coevolution Between Ecological Environment Resources and Economic Society System, Guangdong University of Finance & Economics, Guangzhou, 510320, China.
| | - Yina Chen
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Xiangcui Liang
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Lu Yu
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Jielun Sun
- School of Mathematics and Statistics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Xintong Luo
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Mansi Zhang
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
| | - Zhuoqi Wu
- School of Economics, Guangdong University of Finance & Economics, Guangzhou, 510320, China
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