Hospital Efficiency Research Articles

Improving Hospital Efficiency and Cost Management: A Systematic Review and Meta-Analysis

Improving Hospital Efficiency and Cost Management: A Systematic Review and Meta-Analysis

Evaluating the Impact of the Level of Robustness in Operating Room Scheduling Problems.

Managing uncertainty in surgery times presents a critical challenge in operating room (OR) scheduling, as it can have a significant impact on patient care and hospital efficiency. Objectives: By incorporating robustness into the decision-making process, we can provide a more reliable and adaptive solution compared to traditional deterministic approaches. Materials and methods: In this paper, we consider a cardinality-constrained robust optimization model for OR scheduling, addressing uncertain surgery durations. By accounting for patient waiting times, urgency levels and delay penalties in the objective function, our model aims to optimise patient-centred outcomes while ensuring operational resilience. However, to achieve an appropriate balance between resilience and robustness cost, the robustness level must be carefully tuned. In this paper, we conduct a comprehensive analysis of the model's performance, assessing its sensitivity to robustness levels and its ability to handle different uncertainty scenarios. Results: Our results show significant improvements in patient outcomes, including reduced waiting times, fewer missed surgeries and improved prioritisation of urgent cases. Key contributions of this research include an evaluation of the representativeness and performance of the patient-centred objective function, a comprehensive analysis of the impact of robustness parameters on OR scheduling performance, and insights into the impact of different robustness levels. Conclusions: This research offers healthcare providers a pathway to increase operational efficiency, improve patient satisfaction, and mitigate the negative effects of uncertainty in OR scheduling.

Organizational culture and leadership style in Spanish Hospitals: Effects on knowledge management and efficiency

Hospital culture and leadership style have attracted considerable attention in research, with compelling evidence indicating their potential competitive advantages, including their crucial role in ensuring the successful implementation of knowledge management and its impact on hospital efficiency. The aim of this paper is to identify the effects of organizational culture and leadership style on knowledge management and hospital efficiency. Fuzzy cognitive maps (FCMs) are relational models that can be used to represent the opinions and knowledge of expert to infer cause-effect relationships among different concepts. The use of FCMs as a simulation tool enables the evaluation of potential scenarios based on different organizational cultures and leadership styles in hospitals. Developing an FCM for this study involved several steps. Firstly, data were collected through interviews with 21 experts in hospital management. The interviews were conducted between May and September 2023 either face-to-face or via videoconference. Once individual cognitive maps had been created, consensus among them was achieved through a multicriteria decision-making process, wherein the expert opinions were averaged. The separate cognitive maps of each expert were then integrated to produce a single FCM using the augmented FCM approach. Reflecting expert insights from the FCM, hospitals with a hierarchy culture exhibit diminished levels of knowledge creation, management, and overall hospital efficiency, whereas those with an adhocracy culture show improvements in knowledge creation, knowledge exploitation, and overall hospital efficiency in comparison to alternative ones. From the experts' FCM perspective regarding leadership style, transformational leadership achieves the highest level of knowledge management and hospital efficiency in hospitals with an adhocracy culture. Finally, this paper offers a reference for practising knowledge management and improving hospital efficiency through adhocracy culture and transformational leadership.

Impact of hospital pharmacy interventions on length of stay in hospitals: a protocol for a systematic review and meta-analysis

Background Length of stay (LOS) is an essential metric for hospital efficiency, patient outcomes and satisfaction. Studies indicate hospital pharmacy interventions positively affect LOS and other outcomes, yet results vary due to study differences. No systematic review or meta-analysis has been conducted on this topic; thus, the aim of this study is to systematically assess the effect of interventions on LOS. Methods This review will conduct a systematic search across MEDLINE, EMBASE, Cochrane Trials, Cochrane Reviews and the Cumulative Index to Nursing and Allied Health Literature to identify pertinent studies. An expert librarian will craft the search strategy, ensuring our review adheres to standard guidelines. We will use Covidence, a specialized systematic review management software, to optimize data management, the selection process and data extraction. A dedicated team of reviewers will independently evaluate titles and abstracts in duplicate, progressing to full-text examination of articles, to determine inclusion in our review and analysis. Data will be extracted by one reviewer, with independent data extraction by a second reviewer in a proportion of papers, and checking for consistency by a third. A template in Covidence will guide extraction of study, setting, participant, intervention and outcome characteristics and findings. The findings will be described narratively, and if possible given the methodological and statistical heterogeneity, meta-analysis will be undertaken. Discussion Considering the inconsistency of previous studies, this systematic review aims to clarify the potential impact of hospital pharmacy interventions on LOS. It will expand and reinforce existing knowledge, and provide detail about which intervention types have the most impact on LOS.

Technical Efficiency Of Private Hospitals In Kamrup (Metro) District, Assam: An Application Of Two Stage Data Envelopment Analysis model

Healthcare resources should not be misused as such resources can save people's life. Further, avoiding excessive resource employment can help minimize production costs. In this regard, measuring technical efficiency is essential as it helps identify the resource utilization level against the output level. The present study has estimated the relative technical efficiency scores of private hospitals in the Kamrup (Metro) district of Assam. The data for the study is collected from primary and secondary sources for the year 2019. Bootstrapping Data Envelopment Analysisis applied considering two outputs and six input variables. All the hospitals are technically inefficient; however, small size hospitals have shown better performance in terms of technical efficiency than big size hospitals. The study has not distinguished the number of inpatients based on the resources consumption. In this context, there is a further scope to improve the study. However, this is the first attempt to analyse the performance of private hospitals in terms of technical efficiency in Assam. It will help the management of concerned hospitals to improve their resource utilisation strategy.

Enhancing Hospital Efficiency and Patient Outcomes Through Flexible Resident Scheduling: A Meta-Analysis

Enhancing Hospital Efficiency and Patient Outcomes Through Flexible Resident Scheduling: A Meta-Analysis

The efficiency of residency training and health outcomes in China: Based on two-stage DEA and cluster analysis

To address the residency training performance and further explore its determinants, with the help of a unique dataset, our study calculated the efficiency of residency training and health outcomes in 18 Chinese tertiary hospitals from 2020 to 2021 using a two-stage data envelopment analysis (DEA) model given the two-stage characteristics of vocational training and clinical practice of residents. The results showed that the efficiency of the sample hospitals in both residency training and medical service provision was high, there are approximately 1/3 hospitals of sub-efficient in each stage, but the number of efficient units for assessing the residency training performance was slightly less than that for assessing the health outcome performance. All the decision-making units (DMUs) were clustered into four groups through K-means cluster analysis according to efficiency results. The results showed that there was an obvious inconsistency between the teaching goals and the health outcome goals of Chinese public hospitals. In some hospitals, the low residency pass rate resulted in the low efficiency in stage 1, while the redundant inputs in beds resulted in the low efficiency in stage 2. Residency training hospitals should strengthen their synergistic management in programs of residency training and health outcomes.

Optimization of Patient and Nurse Management in Health Care: A Case Study

Effective patient selection and nurse allocation are crucial for optimizing hospital care, especially in resource-constrained environments. This study introduces a two-stage mixed integer linear programming (MILP) model designed to prioritize patients based on care urgency and match them with appropriately skilled nurses. Following consultations with healthcare professionals, patients were categorized into three priority levels: high (critical care), normal (basic care), and low (expert consultations). Applying the model to the surgery department of Pabna Medical College Hospital, Bangladesh, 196 out of 950 patients were selected for care: 117 requiring critical care, 59 needing basic care, and 20 for consultative care, necessitating the allocation of 41 nurses. The model demonstrated significant improvements in patient selection and nurse workload management, ensuring maximum patient service within capacity constraints and achieving a balanced distribution of nurse workloads. This approach enhances hospital efficiency and patient care quality, allowing non-chosen patients to seek alternative care options. The model’s adaptability across different departments underscores its potential for widespread application in healthcare management. Journal of Engineering Science 15(1), 2024, 83-94

The efficiency evaluation of traditional Chinese medicine hospitals by data envelopment analysis in Zhengzhou, China.

This study aimed to evaluate the operational efficiency of traditional Chinese medicine (TCM) hospitals in China. Pearson's analysis was used to test the correlation between the input and output variables. Data envelopment analysis (DEA) was utilized to analyze the input and output variables of 16 TCM hospitals, and each hospital efficiency score was computed by Deap 2.1, assuming variable return to scale (VRS), which is an input-oriented model. t tests were conducted to confirm the significant difference of efficiency scores at the hospital level and by hospital type, and ANOVA was used to test for significant differences in efficiency scores according to hospitals' size. The correlation coefficient of the input and output indicators was between 0.613 and 0.956 (p < 0.05). The difference in number of doctors (ND) and numbers of pharmacists (NP) were statistically significant (p < 0.05) at the hospital level. The mean efficiency scores for technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) in secondary TCM hospitals were 0.766, 0.919, and 0.838, respectively. Additionally, the lowest TE, PTE, and SE were 0.380, 0.426, and 0.380, respectively. Eight TCM hospitals in this study were DEA efficient, with an efficiency score of 1. There were no statistically significant differences in TE, PTE, and SE among hospital levels, hospital types or hospital sizes groups (p > 0.05). This study revealed that tertiary TCM hospitals had a greater level of efficiency than secondary TCM hospitals. In our study, 50% of TCM hospitals had inefficient management. Therefore, to activate the new development power of TCM hospitals, it is necessary to reform and improve the management system and mechanism of TCM hospitals, optimize the development environment of TCM hospitals and formulate development plans and measures based on local conditions.

Public Health Program Planning And Evaluation: A Management Approach

Since the health care sector is essentially a human services organisation, any hospital setup must have administration with a high degree of personal touch. Maximum efficiency in hospitals can only be attained when all hospital employees collaborate diligently and participate in management. All health professionals must be appropriately motivated in order to harness their intellectual and practical resources for the organization's advantage and to ensure that everyone benefits from the organization's work. Although money is the greatest motivator, it is not the only one. Serious elements like job satisfaction, accomplishment orientation, recognition, acceptance, etc. are needed to motivate people who have already reached their basic psychological needs. These are only possible if management fosters a friendly environment of respect for one another and acknowledges each employee for the high calibre of their work.

Comparison of effectiveness indicators before and during the COVID-19 pandemic in a university hospital

Objective: Our aim in this study is to reveal to what extent hospital efficiency indicators changed in a University Hospital between the period before the Covid 19 pandemic (2018-2019) and the period when the pandemic started and continued (2020-2021). Method: The study planned as a retrospective and descriptive type, data belongs to a 4-year period (2018-2021). The number of personnel for the years examined in the study, the number of applications to the outpatient clinic and emergency department calculated monthly and the number of deceased patients. Bed occupancy rate, inpatient rate, average patient stay days, bed turnover rate and bed turnover interval were used as hospital bed utilization efficiency indicators. Result: Among all years, April 2020 had the lowest number of emergency applications (n=1287) and total number of outpatient clinic applications (n=7530). The year with the highest bed occupancy rate was 2020 with 77.2±6.7. The highest inpatient rate was in 2020 with 6.7±2.1, the highest average day of stay was in 2021 with 10.8±2.2, the highest bed turnover rate was in 2018 and 2019 with 4.7±0.3 and the highest bed turnover interval was observed in 2021 with 5.2±2.2. April 2020 was the month with the highest inpatient rate at 11.8% and the highest bed turnover interval at 16.8. Conclusion: The number of patients applying to emergency departments and outpatient clinics decreased, the inpatient rate increased, the bed turnover rate decreased, the bed turnover interval extended and the average day of stay increased during the pandemic period.

Innovative IoT Solutions for Enhanced Patient Health Monitoring and Healthcare Efficiency in Hospitals

Abstract: Hospitals worldwide have been grappling with overcrowding, a challenge that became particularly acute during the COVID-19 pandemic. Implementing IoT devices can enhance hospital efficiency and reduce the risk of infection for healthcare providers. With IoT, remote health monitoring becomes possible, leading to more timely and improved patient care. The research employs a stratified sampling method, with survey questionnaires distributed to gather data. Based on this data, a proposed system will be developed to evaluate its feasibility and effectiveness. As IoT technology advances, the system is expected to evolve, providing users with greater confidence and ease of use. The goal of this research and proposal is to implement a solution that enhances health monitoring in hospitals, ultimately offering patients better and more timely healthcare.

Optimizing thermal comfort and energy efficiency in hospitals with PCM-Enhanced wall systems

Currently, outpatient areas in hospital buildings daily accommodate a significant number of patients with various diseases, presenting a dual challenge of augmenting architectural energy efficiency while concurrently elevating levels of indoor comfort. This research introduces a novel approach to enhancing hospital optimal design: by incorporating Phase Change Materials (PCM) within the architectural walls and using automated machine learning to integrate multi-objective optimization for developing PCM wall system strategies under a comprehensive criteria framework. The findings demonstrate that the incorporation of PCM into the walls of buildings markedly improves indoor comfort while simultaneously reducing the demand for energy. However, these benefits come at the cost of certain financial efficiencies. Specifically, after achieving the targeted optimal thermal comfort, the extent of thermal comfort enhancement across various patient groups ranged from 37.0% to 43.5%. Concurrently, energy efficiency improvements were observed to range between 7.64% and 7.98%. The Life Cycle Cost (LCC) of these optimization strategies falls within a range of 44,950 to 83,894 CNY. In summary, these findings underscore the potential of using PCM within the building wall system to advance thermal comfort management and energy conservation design.

Financial management, efficiency, and care quality: A systematic review in the context of Health 4.0.

This article investigates the intersection between innovation, Health 4.0, and financial management in the healthcare industry, emphasizing the importance of operational efficiency and quality of care. The study aims to analyze how financial management processes in healthcare relate to Health 4.0 and enhance care quality. It begins with a thorough theoretical grounding, proposing a framework that connects Health 4.0 with financial management practices. A systematic review of the literature was conducted, identifying trends, challenges, and opportunities in the financial management of Health 4.0. The results highlight selected articles on responsible innovation, Health 4.0 technologies, investments in health, hospital efficiency, performance forecasting, and high-cost patient management. These articles were clustered into "Data Analysis and Machine Learning in Healthcare" and "Health Management and Sustainability," providing a categorized understanding of the topics. The study reveals that Health 4.0 offers significant opportunities for process efficiency and cost reduction without compromising service quality. It highlights strategic advantages in addressing contemporary healthcare challenges by optimizing processes, improving financial projections, and incorporating advanced technologies efficiently. The successful implementation of Health 4.0 can lead to substantial improvements in service quality, adding value to patients and driving local economic development. This article offers valuable insights for healthcare professionals and managers, emphasizing the transformative potential of Health 4.0 and outlining strategies for its effective implementation. The clustering of articles provides a clearer understanding of current research in Health 4.0, contributing significantly to the field and guiding future research directions.

Accountable hospital governance structure rules in Iran: a qualitative document analysis

PurposeHospital governance accountability structures in Iran, similar to other countries, have undergone various reforms with different goals. The current study aimed to identify the rules and regulations of the hospital governance structure in Iran and how they pay attention to accountability.Design/methodology/approachThis qualitative document content analysis study was conducted using hospital governance structure documents in Iran using the Ready materials, Extract data, Analyze data and Distil (READ) document analysis framework. 2,921 documents were extracted from the official government websites of Iran. After screening, seven documents related to the hospital governance structure were selected. A directed content analysis approach was used. The findings were finally future purification matched with the original documents.FindingsThe findings showed that documents had not addressed the inclusive governance structure of the hospital comprehensively. The medical staff organization structure is not considered in the documents, and its duties are assigned to a technical or a clinical director. Most documents addressed financial accountability. The documents did not require the hospital’s governance to have an inclusive accountability structure. However, they paid more attention to the administrative and financial autonomy of hospitals.Practical implicationsAccountability is one of the most essential components in the hospital's governance structure. It can increase the success of hospital efficiency, effectiveness, vision and mission fulfillment. The study result can help health services policymakers and managers formulate better organization structure rules and regulations for hospital governance accountability.Originality/valueThis study is the first qualitative analysis of accountable governance structure documents in Iranian hospitals. We used the READ method as a comprehensive approach for document analysis.

Enhancing Hospital Efficiency through IoT and AI: A Smart Healthcare System

In the rapidly evolving healthcare landscape, the integration of Internet of Things (IoT) and Artificial Intelligence (AI) is transforming hospital efficiency. This study explores how these technologies can enhance hospital operations by optimizing resource management, improving patient care, and reducing operational costs. IoT devices enable real-time monitoring of patient health and hospital assets, facilitating timely interventions and maintenance. Concurrently, AI-driven analytics improve decision-making processes by predicting patient needs and optimizing resource allocation. The synergy between IoT and AI creates a smart healthcare system that offers advanced data processing and actionable insights, leading to improved patient outcomes. Despite challenges such as data privacy concerns and infrastructure investments, the potential benefits of IoT and AI in healthcare are substantial. This paper presents a comprehensive framework for integrating these technologies into hospital operations, highlighting their impact on efficiency and patient care. The findings suggest that IoT and AI can significantly enhance hospital performance, paving the way for a smarter healthcare system.

Activity‐based funding reform and the performance of public hospitals: The case of Queensland, Australia

AbstractThis study investigates the impact of activity‐based funding (ABF) on the performance of hospitals by exploiting a natural experiment that happened in the state of Queensland, Australia. To examine the outcome of the reform, the performance of hospitals is measured by the technical efficiency estimated from data envelopment analysis (DEA) models. We try to identify the causal effect of ABF on the technical efficiency of hospitals by incorporating difference‐in‐differences approach in the popular two‐stage DEA framework. We find empirical evidence that ABF improves the technical efficiency of hospitals.

"Modernizing Cervical Cytology Screening with Liquid-Based Methods at Community-Level Hospitals: A Much-Needed Breakthrough for India".

Cervical cancer still ranks highest causing cancer-related morbidity and mortality in women in India. It is prudent to emphasise and implement cervical cancer screening strategies in the population efficiently and with regular intervals. Conventionally, PAP smear cytology is obtained by wooden spatula-Ayre's spatula. To improve sensitivity and specificity of the procedure and detection rate, better techniques of cells retrieval are available mainly liquid-based cytology (LBC), with help of cyto-brush. Literature has consistently proven efficiency of the technique and also reduced the proportion of inadequate sampling. We conduct this study to compare both the techniques and efficiency in a community hospital from data over 6years,to asses its role and benefits among Indian women. To compare conventional PAP smear and liquid-based cytology techniques analysing detection rates of positive lesions (CIN and also includes ASCUS and malignant), incidence of inadequate sampling, efficiency and cost-effectiveness. This is retrospective study at tertiary care obstetric hospital affiliated to government-run medical college in a metropolitan city of Mumbai. Data are retrieved from the Pathology Department, Medical Records Department, laboratory books and OPD registers. Pap's smear sampling was done mainly from OPD with all indications including routine tests as a part of gynaecological evaluation and screening, as well as for suspicious lesions on inspection. Group A consists women who had conventional PAP smear test for 3years (Dec 2015-Nov 2018) and Group B had women who benefited by LBC method for 3years (Dec 2018-Nov 2021). COVID-19 pandemic majorly affected the routine gynaecological OPD practice during 2021 as hospital was COVID facility hospital. Demographic parameters and presentations were comparable and similar. LBC methods have higher detection rate for positive reports, including ASCUS. But results were comparable in both groups and not statistically different. Importantly, incidences of inadequate sampling are reduced significantly with the LBC method. Unsatisfactory smears war high in Group A (7.752%) compared to Group B (3.712%) p-value 0.005, stating the increased rate of requirement of sending repeat smears, which involves higher engagement of time, resources and active participation from healthcare personnel. Good detection rates and significantly low rates of unsatisfactory smears make LBC rational and cost-effective. These are the times to switch to liquid-based cytology techniques, especially at the community level hospitals; in order to detect more women with cervical premalignant as well as malignant neoplastic lesions and to save lives. This can be made possible by emphasising the policy makers to incorporate these services through quality resources.

Anesthetics drug wastage and preventive strategies: Systematic review.

Surgical Patients and hospitals are now facing financial strain due to direct anesthetic demand as a result of the development of new anesthetic drugs, equipment, and techniques. Up to 15% of a hospital's pharmacy budget is currently allocated to anesthetic drug expenses. Drug wastage during anesthesia practice is a widespread hidden source of healthcare waste that leads to anesthetic drug shortages as well as poor operating room efficiency. On the other hand, despite the fact that it is preventable in the vast majority of cases, it is well described that drug wastage is routinely observed, including in developing countries where the consequences significantly affect both hospitals and patients. This review aims to review the prevalence of anesthetic drug waste across the world and systematically formulate and describe preventive strategies. Relevant publications were identified using systematic searches on databases including Google Scholar, Medline (PubMed), the Cochrane Library, and Embase. In addition, papers were detected and then selected through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria guidelines and the inclusion and exclusion criteria. Using the predetermined terms and dates from the searching databases, a total of 504 articles were identified. Based on the screening criteria, 16 papers were considered eligible and included in the final review. In addition, the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis was used for evaluating the quality of selected articles. This study is registered on PROSPERO, number CRD42024497044. Of the sixteen publications from eleven different nations that were considered suitable for inclusion, only two of them addressed the waste of inhalational anesthetics. In more than half of eligible articles, propofol was the frequently wasted drug that contributed to increased financial loss through drug waste. The first most significant factor contributing to the waste of intravenous and inhalational anesthetics was the disposal of multidrug vials following their use for a single patient and high fresh gas flow, respectively. Anesthetic medication waste is a common occurrence worldwide, despite the fact that it is expensive and has a significant negative impact on operating room efficiency. Because the majority of drug waste is avoidable, preventive measures may lower drug waste and improve patient and hospital efficiency.

A Proof of Concept Using BLE to Optimize Patients Turnaround Time (PTAT) in Health Care

In 2022, Malaysia's Ministry of Health (MOH) acknowledged that government hospitals continue to face challenges in delivering high-quality patient care. A significant issue is the absence of a Real-Time Patient Location Monitoring and Tracking Solution, which prevents doctors from efficiently tracking patients within medical facilities. This lack of real-time tracking contributes to a decline in service quality, creating an urgent need for optimization in patient monitoring and tracking solutions. Implementing an effective tracking system can significantly enhance patient care quality, improve resource utilization management, and boost staff productivity, ultimately saving costs, time, and resources for hospitals. One critical area for improvement is the Patient Turnaround Time (PTAT), which refers to the duration a patient spends being processed at a hospital before being discharged. PTAT is currently prolonged in many hospitals due to the complex processes involved and patients becoming untraceable while waiting for their turn. To address these challenges, we have developed an Internet of Things (IoT) solution utilizing Bluetooth Low Energy (BLE) technology to optimize PTAT. This solution enables hospital staff to track patient movements and localize them in real-time. By using wearable devices, the system measures the distance from patients to various Access Points (AP) spread throughout the hospital based on the dBm value. This paper presents comprehensive experimentation for the Proof of Concept (POC) and pilot testing of this BLE-based solution. The results demonstrate the accuracy of using the Received Signal Strength Indicator (RSSI) to optimize patient turnaround times in hospitals. By implementing this BLE solution, hospitals can reduce the time patients spend waiting for treatment, thereby improving overall patient satisfaction and hospital efficiency. The ability to monitor patient locations in real-time will ensure that patients receive timely care, reducing the likelihood of them wandering off and becoming untraceable. This technology represents a significant step forward in modernizing patient care and streamlining hospital operations in Malaysia.