scholarly journals Root-Cause Analysis of Maternal Mortality in Fars Province, Southern Iran 2014: Negligence Is the Prime Suspect

2020 ◽  
Author(s):  
Alireza Mirahmadizadeh ◽  
Ali Semati ◽  
Babak Eshrati ◽  
Fariba Moradi ◽  
Nasrin Asadi
Keyword(s):  
Health Care ◽  
Sensitivity Analysis ◽  
Maternal Mortality ◽  
Surveillance System ◽  
Root Cause Analysis ◽  
Careful Examination ◽  
Fars Province ◽  
Maternal Deaths ◽  
Cause Analysis ◽  
Root Cause

Objective: we aimed to carry out an applied methodological tool, using Root-Cause Analysis (RCA), to determine the main causes of maternal mortality in Fars province, south of Iran, in 2014. Materials and methods: This is a case-series study and was conducted based on a careful examination of records and verbal autopsy with the family of the deceased person and their medical care team. Using RCA, quantitative dynamic modeling was done to display the overall impacts of different causes on maternal mortality. Finally, sensitivity analysis was done to determine the magnitude of contribution of each root-cause of maternal mortality. Results: Totally, all 10 maternal deaths with Maternal Mortality Rate (MMR) of 13.4 per 100.000 births, were recorded in the maternal surveillance system during 2014. The RCA results revealed that the root-causes of maternal mortality were ignorance and negligence (50%), delay in diagnosis (30%), delay in service provision in the first 24 hours after delivery (10%), and undesirable health care (10%). The results of sensitivity analysis in different scenarios revealed that medical negligence had the highest contribution to maternal mortality. Conclusion: Although maternal surveillance system stated some causes such as hemorrhage to be responsible for maternal deaths, the RCA showed that root-causes such as medical neglects had a fundamental role. Therefore, maternal mortality can be prevented by reforming the health care system and training all service providers, especially for high-risk mothers.  

A root-cause analysis of Maternal Mortality in a tertiary care hospital

2012 ◽  
Vol 2 (7) ◽  
pp. 383-384
Author(s):  
Dr. Samipa J. Shah ◽  
◽  
Dr. Akshay Shah ◽  
Dr. Punit B . Vasa ◽  
Dr. Yamini Trivedi
Keyword(s):  
Maternal Mortality ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Root Cause Analysis ◽  
Care Hospital ◽  
Cause Analysis ◽  
Root Cause

scholarly journals Root-Cause Analysis of Persistently High Maternal Mortality in a Rural District of Indonesia: Role of Clinical Care Quality and Health Services Organizational Factors

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Afzal Mahmood ◽  
Ismi Mufidah ◽  
Steven Scroggs ◽  
Amna Rehana Siddiqui ◽  
Hafsa Raheel ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Maternal Mortality ◽  
Clinical Care ◽  
Organizational Factors ◽  
Root Cause Analysis ◽  
Care Quality ◽  
Cause Analysis ◽  
Root Cause ◽  
Essential Services

Background. Despite significant reduction in maternal mortality, there are still many regions in the world that suffer from high mortality. District Kutai Kartanegara, Indonesia, is one such region where consistently high maternal mortality was observed despite high rate of delivery by skilled birth attendants. Method. Thirty maternal deaths were reviewed using verbal autopsy interviews, terminal event reporting, medical records’ review, and Death Audit Committee reports, using a comprehensive root-cause analysis framework including Risk Identification, Signal Services, Emergency Obstetrics Care Evaluation, Quality, and 3 Delays. Findings. The root causes were found in poor quality of care, which caused hospital to be unprepared to manage deteriorating patients. In hospital, poor implementation of standard operating procedures was rooted in inadequate skills, lack of forward planning, ineffective communication, and unavailability of essential services. In primary care, root causes included inadequate risk management, referrals to facilities where needed services are not available, and lack of coordination between primary healthcare and hospitals. Conclusion. There is an urgent need for a shift in focus to quality of care through knowledge, skills, and support for consistent application of protocols, making essential services available, effective risk assessment and management, and facilitating timely referrals to facilities that are adequately equipped.

Model Based Root Cause Analysis of Manufacturing Quality Problems Using Uncertainty Quantification and Sensitivity Analysis

2019 ◽  
Author(s):  
Kevin Otto ◽  
Josefina Sanchez Mosqueda
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Fault Tree Analysis ◽  
High Volume ◽  
Root Cause Analysis ◽  
Large Set ◽  
Cause Analysis ◽  
Quasi Monte Carlo ◽  
Root Cause ◽  
Product And Process

Abstract Diagnosing faulty performance deviations of electro-mechanical systems can be difficult, given the multitude of components and features which could contribute as root causes. Yet this is often a problem in manufacturing, where only some of the units built do not meet performance requirements only some of the time. In this context, product and process simulation studies can aid in diagnosis. This paper aims to develop a practical workflow and toolchain to guide use of uncertainty quantification and sensitivity analysis methods for root cause analysis of manufacturing processes. This approach offers more rapid diagnosis than the typical approach using some form of iterative experimentation such as Red-X, fault tree analysis and when in high volume production, statistical analysis and potentially machine learning. Here, part processes, features and assembly deviations are used as inputs to product performance simulation to understand their detrimental impact. The large set of possible process inputs can be systematically varied and contributions to system performance deviation computed. To do this simply using uncertainty quantification and sensitivity analysis is impractical, as the problem is too large. Rather, a sequential refinement workflow is developed to define the problem and possible causes, understand ability model causes, screen causal variables, and then apply quasi-Monte-Carlo uncertainty quantification sampling and global sensitivity analysis. This provides computational guidance to ascertain which manufacturing process inputs are more likely causes of performance deviations on manufactured units.

scholarly journals Primary care access barriers faced by immigrant populations in their host countries: a systematic review protocol aiming to construct a conceptual framework using root cause analysis to capture 'what leads to what'

2020 ◽  
Vol 12 (2) ◽  
pp. 139
Author(s):  
Tanvir C. Turin ◽  
Nashit Chowdhury ◽  
Mahzabin Ferdous ◽  
Ruksana Rashid ◽  
Marcus Vaska ◽  
...  
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Health Care ◽  
Conceptual Framework ◽  
Root Cause Analysis ◽  
Immigrant Communities ◽  
Cause Analysis ◽  
Primary Care Access ◽  
Root Cause ◽  
Care Access

ABSTRACT INTRODUCTIONUnderstanding primary care access or health service utilisation challenges among immigrant communities is important for tailoring services to community needs, which is the core of precision population health. AIMWe aim to inventory the primary care access barriers faced by immigrant communities through a comprehensive systematic review and develop a conceptual framework to explain the barriers, using a root cause analysis approach. METHODSAcademic databases of primary research articles and grey literature will be searched using appropriate keywords. Relevant information will be extracted into tabular format from finally selected literature. Our proposed approach of framing the barriers to identify the root causes is adapted from the root cause analysis method, which is the process of identifying and understanding the underlying causes to discover the root causes of problems. RESULTSThe study will produce a systematic, quantified and documented list of the barriers faced by immigrants in a solution-oriented approach. DISCUSSIONThe proposed research, as a first step towards determining possible mitigation strategies for health-care access by immigrants, will provide the background needed to devise and test tailored interventions to improve future access to health care for immigrants. We will follow the integrated knowledge translation or community engagement knowledge mobilization approach, where we are engaged with community-based citizen researchers from the inception of our programme. We plan to disseminate the results of our review through meetings with key stakeholders and social media outreach, followed by journal publications and presentations on relevant platforms.

Failure mode and effect analysis (FMEA) of radiotherapy

2020 ◽  
Vol 10 (4) ◽  
pp. 1-22
Author(s):  
Rajaram Govindarajan ◽  
Mohammed Laeequddin
Keyword(s):  
Health Care ◽  
Quality Management ◽  
Ethical Dilemma ◽  
Failure Modes ◽  
Root Cause Analysis ◽  
Effect Analysis ◽  
Cause Analysis ◽  
Content Type ◽  
Root Cause ◽  
Error Proofing

Learning outcomes Learning outcomes are as follows: students will discover the importance of process orientation in management; students will determine the root cause of the problem by applying root cause analysis technique; students will identify the failure modes, analyze their effect, score them on a scale and prioritize the corrective action to prevent the failures; students will analyze the processes and propose error-proof system/s; and students will analyze organizational culture and ethical issues. Case overview/synopsis Purpose: This case study is intended as a class-exercise, for students to discover the importance of process-orientation in management, analyze the ethical dilemma in health care and to apply quality management techniques, such as five-why, root cause analysis, failure mode and effect analysis (FMEA) and error-proofing, in the management of the health-care and service industry. Design/methodology/approach: A voluntary reporting of a case of “radiation overdose” in a hospital’s radio therapy treatment unit, which led to an ethical dilemma. Consequently, a study was conducted to establish the causes of the incident and to develop a fail-proof system, to avoid recurrence. Findings: After careful analysis of the process-flow and the root causes, 25 potential failure modes were detected and the team had assigned a risk priority number (RPN) for each potential incident, selected the top ten RPNs and developed an error-proofing system to prevent recurrence. Subsequently, the improvement process was carried out for all the 25 potential incidents and a new control mechanism was implemented. The question of ethical dilemma remained unresolved. Research limitations/implications: Ishikawa diagram, FMEA and Poka-Yoke techniques require a multi-disciplinary team with process knowledge in identifying the possible root causes for errors, potential risks and also the possible error-proofing method/s. Besides, these techniques need frank discussions and agreement among team members on the efforts for the development of action plan, implementation and control of the new processes. Practical implications: Students can take the case data to identify root cause analysis and the RPN (RPN = possibility of detection × probability of occurrence × severity), to redesign the protocols, through systematic identification of the deficiencies of the existing protocols. Further, they can recommend quality improvement projects. Faculty can navigate the case session orientation, emphasizing quality management or ethical practices, depending on the course for which the case is selected. Complexity academic level MBA or PG Diploma in Management – health-care management, hospital administration, operations management, services operations, total quality management (TQM) and ethics. Supplementary materials Teaching Notes are available for educators only. Subject code CSS 9: Operations and Logistics.

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