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Correction to: Prioritizing interdependent drivers of financial, economic, and political risks using a data‑driven probabilistic approach

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Risk Management 2022年第2期24卷 186-186页

作者： Qazi, Abroon simsekler, mecit can emre School of Business Administration American University of Sharjah Sharjah United Arab Emirates Department of Industrial and Systems Engineering Khalifa University of Science and Technology Abu Dhabi United Arab Emirates

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Evaluating the Impact of Patient No-Shows on Service Quality

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RISK MANAGEMENT AND HEALTHCARE POLICY 2020年 13卷 509-517页

作者： Marbouh, Dounia Khaleel, Iman Al Shanqiti, Khawla Al Tamimi, Maryam simsekler, mecit can emre Ellahham, Samer Alibazoglu, Deniz Alibazoglu, Haluk Khalifa Univ Dept Ind & Syst Engn Res Ctr Digital Supply Chain & Operat Abu Dhabi U Arab Emirates UCL Sch Management London England Cleveland Clin Abu Dhabi Heart & Vasc Inst Abu Dhabi U Arab Emirates Cleveland Clin Abu Dhabi Imaging Inst Abu Dhabi U Arab Emirates

Purpose: Patient no-shows are long-standing issues affecting resource utilization and posing risks to the quality of healthcare services. They also lead to loss of anticipated revenue, particularly in services where resources are expensive and in great demand. Methods: In order to address common reasons why patients miss appointments, this study reviews the current literature and investigates various tools and methods that have been implemented to mitigate such issues. Further, a case study is conducted to identify the rate of no-shows and underlying causes at a radiology department in one of the leading hospitals in the MENA region. Results: Our results show that the no-shows are high due to multiple factors, such as patient behavior, patients' financial situation, environmental factors and scheduling policy. Conclusion: In conclusion, we generate a list of recommendations that can help in reducing the rate of patient no-shows, such as patient education, application of dynamic scheduling policies and effective appointment reminder systems to patients.

关键词： quality no-shows overbooking resource utilization scheduling policy patient appointment predictive analytics

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Evaluation of System Modelling Techniques for Waste Identification in Lean Healthcare Applications

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RISK MANAGEMENT AND HEALTHCARE POLICY 2020年 13卷 3235-3243页

作者： Alkaabi, Maitha simsekler, mecit can emre Jayaraman, Raja Al Kaf, Abdulqader Ghalib, Hussam Quraini, Dima Ellahham, Samer Tuzcu, E. Murat Demirli, Kudret Khalifa Univ Sci & Technol Dept Ind & Syst Engn POB 127788 Abu Dhabi U Arab Emirates Cleveland Clin Abu Dhabi Heart & Vasc Inst Abu Dhabi U Arab Emirates Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ Canada

Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes. Methods: This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi. Results: VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste. Conclusion: As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.

关键词： lean healthcare value stream map system modelling techniques waste identification kaizen system approaches healthcare operations

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Exploring drivers of patient satisfaction using a random forest algorithm

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BMC MEDICAL INFORMATICS AND DECISION MAKING 2021年第1期21卷 157-157页

作者： simsekler, mecit can emre Alhashmi, Noura Hamed Azar, Elie King, Nelson Luqman, Rana Adel Mahmoud Ali Al Mulla, Abdalla Khalifa Univ Sci & Technol Dept Ind & Syst Engn POB 127788 Abu Dhabi U Arab Emirates Mubadala Healthcare Ipic Sq Abu Dhabi 45005 U Arab Emirates

Background Patient satisfaction is a multi-dimensional concept that provides insights into various quality aspects in healthcare. Although earlier studies identified a range of patient and provider-related determinants, their relative importance to patient satisfaction remains unclear. Methods We used a tree-based machine-learning algorithm, random forests, to estimate relationships between patient and provider-related determinants and satisfaction level in two of the main patient journey stages, registration and consultation, through survey data from 411 patients at a hospital in Abu Dhabi, UAE. Radar charts were also generated to determine which type of questions-demographics, time, behaviour, and procedure-influence patient satisfaction. Results Our results showed that the 'age' attribute, a patient-related determinant, is the leading driver of patient satisfaction in both stages. 'Total time taken for registration' and 'attentiveness and knowledge of the doctor/physician while listening to your queries' are the leading provider-related determinants in each model developed for registration and consultation stages, respectively. The radar charts revealed that 'demographics' are the most influential type in the registration stage, whereas 'behaviour' is the most influential in the consultation stage. Conclusions Generating valuable results, the random forest model provides significant insights on the relative importance of different determinants to overall patient satisfaction. Healthcare practitioners, managers and researchers can benefit from applying the model for prediction and feature importance analysis in their particular healthcare settings and areas of their concern.

关键词： Patient satisfaction Quality Healthcare operations Patient experience Random forests Data analytics Machine learning

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Variation in hospital performance measures from the Turkey Ministry of Health

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INTERNATIONAL JOURNAL FOR QUALITY IN HEALTH CARE 2021年第3期33卷 mzab109-mzab109页

作者： Saluvan, Mehmet Milliren, Carly E. Graham, Dionne A. simsekler, mecit can emre Akin, Merve Babacan Kocatakan, Pinar Goren, Mustafa Ozonoff, Al Boston Childrens Hosp Precis Vaccines Program 300 Longwood Ave Boston MA 02115 USA Boston Childrens Hosp Inst Ctr Clin & Translat Res 300 Longwood Ave Boston MA 02115 USA Boston Childrens Hosp Program Patient Safety & Qual 300 Longwood Ave Boston MA 02115 USA Harvard Med Sch Boston Childrens Hosp Dept Pediat 300 Longwood Ave Boston MA 02115 USA Khalifa Univ Sci & Technol Dept Ind & Syst Engn Abu Dhabi 127788 U Arab Emirates UCL Sch Management Gower St London WC1E 6BT England New York Turkish Consulate Gen 605 3rd Ave 30th Floor New York NY 10158 USA Gen Directorate Turkish Publ Hosp 6001 Cd 9 TR-06490 Ankara Turkey

Background: The Turkish healthcare system has seen broad population-based improvements in expanded health insurance coverage and access to healthcare services. Hospital performance in this national system is understudied. We aimed to identify trends in hospital performance over time following implementation of the Health Transformation Program and describe how regional outcomes correlate with regional vital statistics. Objective: We examine hospital performance data collected by the PHA from 2013 to 2015. We aim to identify the temporal variation in hospital performance for nearly 30 individual measures and to describe the relationship between hospital-level performance measures and regional vital statistics. Methods: We conducted a retrospective cohort study of 674 public hospitals in Turkey using baseline data from 2013 and follow-up data from 2014-15 collected by the Turkish Statistical Institution and the Public Hospital Agency. We report demographic and socioeconomic data across 12 geographic regions and analyze 29 hospital-level performance measures across four domains: (i) health services;(ii) administrative services;(iii) financial services and (iv) quality measures. We examine temporal variation, and study correlation between performance measures and regional vital statistics. We fit mixed-effects linear regression models to estimate linear trend over time accounting for within-hospital residual correlation. We prepared our manuscript in accordance with guidelines set by the STROBE statement for cohort studies. Results: During the 3 years of study period, 21 of 29 measures improved and 8 measures worsened. All but three measures demonstrated significant differences across regions of the country. Several measures, including inpatient efficiency, patient satisfaction and audit score, are associated with regional infant mortality and life expectancy. Conclusions: Evidence of temporal improvement in hospital-level performance may suggest some positive changes w

关键词： performance measurement quality measurement health policy audit patient outcomes patient satisfaction

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Ensuring protocol compliance and data transparency in clinical trials using Blockchain smart contracts

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BMC MEDICAL RESEARCH METHODOLOGY 2020年第1期20卷 224-224页

作者： Omar, Ilhaam A. Jayaraman, Raja Salah, Khaled simsekler, mecit can emre Yaqoob, Ibrar Ellahham, Samer Khalifa Univ Dept Ind Syst Engn Abu Dhabi 127788 U Arab Emirates Khalifa Univ Dept Elect Engn & Comp Sci Abu Dhabi 127788 U Arab Emirates Cleveland Clin Abu Dhabi Heart Vasc Inst Abu Dhabi U Arab Emirates

Background Clinical Trials (CTs) help in testing and validating the safety and efficacy of newly discovered drugs on specific patient population cohorts. However, these trials usually experience many challenges, such as extensive time frames, high financial cost, regulatory and administrative barriers, and insufficient workforce. In addition, CTs face several data management challenges pertaining to protocol compliance, patient enrollment, transparency, traceability, data integrity, and selective reporting. Blockchain can potentially address such challenges because of its intrinsic features and properties. Although existing literature broadly discusses the applicability of blockchain-based solutions for CTs, only a few studies present their working proof-of-concept. Methods We propose a blockchain-based framework for CT data management, using Ethereum smart contracts, which employs IPFS as the file storage system to automate processes and information exchange among CT stakeholders. CT documents stored in the IPFS are difficult to tamper with as they are given unique cryptographic hashes. We present algorithms that capture various stages of CT data management. We develop the Ethereum smart contract using Remix IDE that is validated under different scenarios. Results The proposed framework results are advantageous to all stakeholders ensuring transparency, data integrity, and protocol compliance. Although the proposed solution is tested on the Ethereum blockchain platform, it can be deployed in private blockchain networks using their native smart contract technologies. We make our smart contract code publicly available on Github. Conclusions We conclude that the proposed framework can be highly effective in ensuring that the trial abides by the protocol and the functions are executed only by the stakeholders who are given permission. It also assures data integrity and promotes transparency and traceability of information among stakeholders.

关键词： Blockchain Clinical trials Healthcare Ethereum Smart contracts IPFS

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Evaluating inputs of failure modes and effects analysis in identifying patient safety risks

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INTERNATIONAL JOURNAL OF HEALTH CARE QUALITY ASSURANCE 2019年第1期32卷 191-207页

作者： simsekler, mecit can emre Kaya, Gulsum Kubra Ward, James R. Clarkson, P. John Khalifa Univ Sci Technol Dept Ind & Syst Engn Abu Dhabi U Arab Emirates UCL Sch Management London England Univ Cambridge Dept Engn Cambridge England

Purpose There is a growing awareness on the use of systems approaches to improve patient safety and quality. While earlier studies evaluated the validity of such approaches to identify and mitigate patient safety risks, so far only little attention has been given to their inputs, such as structured brainstorming and use of system mapping approaches (SMAs), to understand their impact in the risk identification process. To address this gap, the purpose of this paper is to evaluate the inputs of a well-known systems approach, failure modes and effects analysis (FMEA), in identifying patient safety risks in a real healthcare setting. Design/methodology/approach This study was conducted in a newly established adult attention deficit hyperactivity disorder service at Cambridge and Peterborough Foundation Trust in the UK. Three stakeholders of the chosen service together with the facilitators conducted an FMEA exercise along with a particular system diagram that was initially found as the most useful SMA by eight stakeholders of the service. Findings In this study, it was found that the formal structure of FMEA adds value to the risk identification process through comprehensive system coverage with the help of the system diagram. However, results also indicates that the structured brainstorming refrains FMEA participants from identifying and imagining new risks since they follow the process predefined in the given system diagram. Originality/value While this study shows the potential contribution of FMEA inputs, it also suggests that healthcare organisations should not depend solely on FMEA results when identifying patient safety risks;and therefore prioritising their safety concerns.

关键词： Patient safety System thinking Risk management

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Exploring Quality Differences in Telemedicine Between Hospital Outpatient Departments and Community Clinics: Cross-sectional Study

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JMIR MEDICAL INFORMATICS 2022年第2期10卷 e32373页

作者： Alhajri, Noora simsekler, mecit can emre Alfalasi, Buthaina Alhashmi, Mohamed Memon, Hamda Housser, Emma Abdi, Abdulhamid Mustafa Balalaa, Nahed Al Ali, Maryam Almaashari, Raghda Al Memari, Shammah Al Hosani, Farida Al Zaabi, Yousif Almazrouei, Shereena Alhashemi, Hamed Khalifa Univ Coll Med & Hlth Sci Al Saada RdZone 1POB 11001 Abu Dhabi U Arab Emirates Khalifa Univ Coll Engn Dept Ind & Syst Engn Abu Dhabi U Arab Emirates Zayed Mil Hosp Dept Family Med Abu Dhabi U Arab Emirates Sheikh Shakhbout Med City Dept Gen Surg Abu Dhabi U Arab Emirates Abu Dhabi Hlth Serv Co Ambulatory Healthcare Serv Abu Dhabi U Arab Emirates Sheikh Khalifa Med City Dept Dermatol Abu Dhabi U Arab Emirates Abu Dhabi Publ Hlth Ctr Abu Dhabi U Arab Emirates Dept Hlth Abu Dhabi U Arab Emirates

Background: Telemedicine is a care delivery modality that has the potential to broaden the reach and flexibility of health care services. In the United Arab Emirates, telemedicine services are mainly delivered through either integrated hospital outpatient department (OPDs) or community clinics. However, it is unknown if patients' perceptions of, and satisfaction with, telemedicine services differ between these two types of health care systems during the COVID-19 pandemic. Objective: We aimed to explore the differences in patients' perceptions of, and satisfaction with, telemedicine between hospital OPDs and community clinics during the COVID-19 pandemic. We also aimed to identify patient- or visit-related characteristics contributing to patient satisfaction with telemedicine. Methods: In this cross-sectional study that was conducted at Abu Dhabi health care centers, we invited outpatients aged 18 years or over, who completed a telemedicine visit during the COVID-19 pandemic, to participate in our study. Patients' perceptions of, and satisfaction with, telemedicine regarding the two system types (ie, hospital OPDs and community clinics) were assessed using an online survey that was sent as a link through the SMS system. Regression models were used to describe the association between patient- and visit-related characteristics, as well as the perception of, and satisfaction with, telemedicine services. Results: A total of 515 patients participated in this survey. Patients' satisfaction with telemedicine services was equally high among the settings, with no statistically significant difference between the two setting types (hospital OPDs: 253/343, 73.8%;community clinics: 114/172, 66.3%;P=.19). Video consultation was significantly associated with increased patient satisfaction (odds ratio [OR] 2.57, 95% CI 1.04-6.33;P=.04) and patients' support of the transition to telemedicine use during and after the pandemic (OR 2.88, 95% CI 1.18-7.07;P=.02). Patients who used video

关键词： COVID-19 patient satisfaction technology acceptance hospital community clinic video consultation audio consultation outpatient department OPD policy making UAE

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Risk Identification Practice in Patient Safety Context

Risk Identification Practice in Patient Safety Context

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： simsekler, mecit can emre Jayaraman, Raja Khalifa Univ Sci & Technol Dept Ind & Syst Engn Abu Dhabi U Arab Emirates UCL Sch Management London England

ISBN: (纸本)9781538667866

Risk identification has gained an increased interest in healthcare to improve patient safety and quality within the scope of risk management. While past studies evaluated the evolvement of the risk management practice in healthcare in general, they also suggested that healthcare can learn and adapt from other safety-critical industries, such as aviation, chemical, nuclear and others. In this study, we particularly reviewed the current risk identification practice in patient safety context. Moreover, we compared healthcare with other industries to shed light on what can particularly be learned on risk identification to accelerate improvements in patient safety and enhance quality of care in healthcare delivery.

关键词： Risk identification risk management healthcare safety-critical industries patient safety

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Managing Product Recalls in Healthcare Supply Chain

Managing Product Recalls in Healthcare Supply Chain

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Jayaraman, Raja AlHammadi, Fatima simsekler, mecit can emre Khalifa Univ Dept Ind & Syst Engn Abu Dhabi U Arab Emirates UCL Sch Management London England

ISBN: (纸本)9781538667866

Product recalls in the healthcare industry contribute to significant supply chain disruptions. In the absence of a reliable product tracking communicating recall information and to recover or safe disposal of the product is extremely challenging. Healthcare product recalls are more generally classified based on severity of risk to patient life and such a classification often does not help supply chain community to assess the impact of recalls and develop alternative sourcing strategies. Hence there is critical need to assess and review healthcare product recalls with an emphasis on supply chain and logistics. In this paper we review the extant literature to identify and categorize factors that often lead to product recalls, and propose a potential approach to enable effective product tracking and recall communication using blockchain technology. The resulting information can aid research and practice community to develop suitable frameworks, models and strategies to mitigate product recalls.

关键词： Product recall Supply Chain Globalization Blockchain Innovation Information technology

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