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Efficient operating room management is essential and requires precise surgery scheduling. We hypothesized that an estimation formula for the preparation time for anesthesia induction and surgery could be developed by incorporating anesthesia and surgical factors, as well as the 'clinical department,' into the formula. This retrospective observational study analyzed 12,528 scheduled surgical cases. A regression analysis that included the clinical department, six anesthesia factors, and five surgical factors was conducted. This analysis aimed to develop both an analytical framework and an equation for estimating the time required for both anesthesia induction and surgical preparation. Our estimation formula wielded high accuracy (R2 = 0.801). Particularly, there was only a difference of less than 3 min for surgeries under general anesthesia. In addition, modeling preparation time using "medical interventions performed in the operating room" as a factor instead of patient characteristics was found to be beneficial. It was possible to develop a highly accurate formula for estimating preparation time of anesthesia induction and surgery by analyzing the anesthesia factors and the surgical factors and incorporating the clinical department as an estimation factor. However, this study represents the development phase of the estimation formula. A multicenter study is essential to validate its generalizability and robustness across different settings before broader application. [ABSTRACT FROM AUTHOR]

Abstract Efficient operating room management is essential and requires precise surgery scheduling. We hypothesized that an estimation formula for the preparation time for anesthesia induction and surgery could be developed by incorporating anesthesia and surgical factors, as well as the ‘clinical department,’ into the formula. This retrospective observational study analyzed 12,528 scheduled surgical cases. A regression analysis that included the clinical department, six anesthesia factors, and five surgical factors was conducted. This analysis aimed to develop both an analytical framework and an equation for estimating the time required for both anesthesia induction and surgical preparation. Our estimation formula wielded high accuracy (R2 = 0.801). Particularly, there was only a difference of less than 3 min for surgeries under general anesthesia. In addition, modeling preparation time using “medical interventions performed in the operating room” as a factor instead of patient characteristics was found to be beneficial. It was possible to develop a highly accurate formula for estimating preparation time of anesthesia induction and surgery by analyzing the anesthesia factors and the surgical factors and incorporating the clinical department as an estimation factor. However, this study represents the development phase of the estimation formula. A multicenter study is essential to validate its generalizability and robustness across different settings before broader application.

Abstract Background We investigated whether the treatment needs of patients with dementia with Lewy bodies (DLB) and their caregivers, along with their attending physicians’ perception of those treatment needs, differ according to the clinical department visited by the patients. Methods This was a subanalysis of a multicenter, cross-sectional, observational survey study. Data from the main study were classified according to the clinical department visited by the patient: psychiatric group (P-group), geriatric internal medicine group (G-group), and neurology group (N-group). The treatment needs of patients and caregivers were defined as “the symptom that causes them the most distress”, and the frequency of each answer was tabulated. Results This subanalysis included 134, 65, and 49 patient–caregiver pairs in the P-, G-, and N-groups, respectively. Statistically significant differences in patient background characteristics such as patient age; initial symptom domains; use of cholinesterase inhibitors, levodopa, antipsychotics, and Yokukansan; and total scores of the Mini-Mental State Examination, Neuropsychiatric Inventory-12, and Movement Disorder Society-Unified Parkinson’s Disease Rating Scale Parts II and III were shown among the three subgroups. While there were no differences in patients’ treatment needs among the subgroups, residual analysis showed that in the N-group, parkinsonism was more of a problem than other symptom domains (p = 0.001). There were significant differences in caregivers’ treatment needs among the three subgroups (p

This interpretative case study demonstrates how the work system properties and roles of clinical departments are perceived to shape their adoption of an organisation-wide electronic health record. In hospitals, with their heterogeneous and powerful clinical departments, partial or non-adoption by some departments may jeopardise effective overall use. Viewing a hospital's EHR adoption from a sociotechnical fit perspective, we unravel how clinical departments' adoption of this organisation-wide system was primarily shaped by their critical work system dependencies rather than their role during its implementation. From the interviewees' accounts, three orientations emerge: (1) organisation-oriented resulting in unconditional adoption; (2) department-oriented resulting in problematic or delayed adoption with high compromise costs; (3) environment-oriented resulting in at least partial non-adoption or extra design costs. Our subsequent analysis leads to the identification of four types of subunit-level characteristics influencing adoption. Their interplay informs departments in balancing between accepting compromise costs and negotiating design costs. We develop a diagnostic system model of subunit-level adoption that takes the embeddedness of the subunit into account and thereby complements individual- and organisation-level adoption theories. An accompanying heuristic may enable hospital managers to better anticipate the heterogeneity in departments' adoption. [ABSTRACT FROM AUTHOR]

Background: We investigated whether the treatment needs of patients with dementia with Lewy bodies (DLB) and their caregivers, along with their attending physicians' perception of those treatment needs, differ according to the clinical department visited by the patients. Methods: This was a subanalysis of a multicenter, cross-sectional, observational survey study. Data from the main study were classified according to the clinical department visited by the patient: psychiatric group (P-group), geriatric internal medicine group (G-group), and neurology group (N-group). The treatment needs of patients and caregivers were defined as "the symptom that causes them the most distress", and the frequency of each answer was tabulated. Results: This subanalysis included 134, 65, and 49 patient–caregiver pairs in the P-, G-, and N-groups, respectively. Statistically significant differences in patient background characteristics such as patient age; initial symptom domains; use of cholinesterase inhibitors, levodopa, antipsychotics, and Yokukansan; and total scores of the Mini-Mental State Examination, Neuropsychiatric Inventory-12, and Movement Disorder Society-Unified Parkinson's Disease Rating Scale Parts II and III were shown among the three subgroups. While there were no differences in patients' treatment needs among the subgroups, residual analysis showed that in the N-group, parkinsonism was more of a problem than other symptom domains (p = 0.001). There were significant differences in caregivers' treatment needs among the three subgroups (p < 0.001). The patient–physician concordance rates for the symptom domains that caused patients the most distress were: P-group, 42.9% (kappa coefficient [κ] = 0.264); G-group, 33.3% (κ = 0.135), and N-group, 67.6% (κ = 0.484). The caregiver–physician concordance rates for the symptom domains that caused the caregivers the most distress were: P-group, 54.8% (κ = 0.351), G-group, 50.0% (κ = 0.244), and N-group, 47.4% (κ = 0.170). Conclusion: This subanalysis revealed differences in the treatment needs of patients with DLB and their caregivers according to the clinical department they attended. There might be a lack of awareness of those treatment needs by the attending physicians, regardless of their specialty. Trial registration: UMIN Clinical Trials Registry UMIN000041844. [ABSTRACT FROM AUTHOR]

The article shows the necessity of applying new teaching technologies in educational process at clinical departments. The innovative audio-visual technologies stimulate students’ cognitive activity, improve their practical skills, develop clinical thinking.

Objectives: This study explores the specialized nursing requirements of different clinical departments and their influence on the design of nursing units, which ultimately improves the nursing staff's efficiency and work experience. Background: Specialization of nursing work is important in the provision of quality of healthcare. Most of the research related to nursing units has focuses on general medical–surgical nursing units and has not differentiated between clinical departments. Method: This study was conducted in one inpatient building at a large general hospital in China. Survey data were collected from 11 clinical departments via questionnaire, and interviews were conducted in 10 of the clinical departments. Results: All 11 clinical departments had significant differences in their evaluations of and requirements for the arrangement of their physical space. Specialized requirements were found in three areas: nursing work processes, arrangement and needs of clinical spaces, and allocation of facilities and equipment. Conclusion: Evaluation of the specialized requirements of different clinical departments would contribute to the body of knowledge on nursing unit design and has a positive effect on the development and improvement of design theory. Suggestions for how the design of nursing units could be improved to support the specialized demands of different departments are provided. [ABSTRACT FROM AUTHOR]

Clinics are the backbone of the healthcare system in all nations, providing a vast array of services, including patient diagnosis and treatment. One critical step to warranting patient safety and health is to improve the performance of clinical departments. To this end, this paper integrated resilience engineering (RE) and lean management (LM) principles to propose a comprehensive framework for evaluating and enhancing the performance of clinical departments. Initially, the Best-Worst Method was utilized to determine the relative importance of each indicator. Afterward, a validated questionnaire was administered to clinical department specialists to collect the required data. The data envelopment analysis model was then employed to evaluate the clinical department in a real-world case study. In addition, the impact of each indicator on the clinical department was analyzed using robustness analysis and statistical tests. The outcomes indicated the ranking of clinics from best to worst performance. Furthermore, the best and worst indicators for each clinic and the entire clinical department were determined. Moreover, a strengths-weaknesses-opportunities-threats analysis was used to propose appropriate strategies to improve the performance of a clinical department. To the best of our knowledge, this paper is the first attempt to quantitatively evaluate the performance of clinical departments in terms of RE and LM indicators. The framework presented in this study can be implemented in various healthcare units to improve their RE- and LM-related performance. • Evaluating a clinical department using resilience engineering and lean management. • Using combination of qualitative and quantitative approaches in a real case study. • Suggesting appropriate improvement actions using the SWOT analysis. • Proposing a framework using data envelopment analysis and best-worst method. [ABSTRACT FROM AUTHOR]

Competing Interests: None declared.

Purpose – The purpose of this paper is to evaluate clinical departments' performance per clinical sector in the context of the Greek public hospital care system. Design/methodology/approach – The sample consisted of 96 internal pathology and surgical clinical departments in 15 hospitals in Greece and their technical efficiency was assessed by the use of data envelopment analysis. The proposed model used the number of nursing staff, medical specialists and department beds, pharmaceutical expenditure and clinical leadership job satisfaction as inputs while the number of hospitalized patients was selected as an output. Clinical leadership job satisfaction was captured by the use of a specialized questionnaire. The methodology applied investigated variations in technical efficiency in the presence or absence of job satisfaction. The model proposed an efficiency improvement through the possible reduction of inputs (input oriented) variable returns to scale. Findings – Processing the results revealed variations in the way clinical leadership job satisfaction affects efficiency assessments per clinical sector. The impact of job satisfaction is verified for the surgical sector and rejected marginally for the pathology sector. Applied methodology results proposed reductions in pharmaceutical expenditure, human resources and available beds. These are indications towards implementing rational economic and human resources management and productive factors development. Originality/value – This research effort uses job satisfaction as a quantitative variable to assess efficiency, focusing on clinical efficiency per clinical sector. In all efforts to restrain health expenditure, measuring clinical department efficiency is critical for health policy makers. [ABSTRACT FROM AUTHOR]