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Challenges and Success in setting up 3D Printing Lab integrated with EMR and VNA in a Tertiary care hospital in Middle East
In recent years’ 3D printing has shown exponential growth in clinical medicine research and education (Carlos et al.). Imaging departments are at the center of 3D printing service delivery efforts of establishing a 3D printing lab and making it a unique contribution towards patient care (Kent Thielen et al.). Building a fully electronic medical record (EMR) integrated workflow to deliver 3D services offers unique advantages for clinicians. In Sidra Medicine we have successfully tested the electronic process by generating 3D orders and delivering the printed models such as hearts skulls and mandibles. To facilitate clinicians and 3D printing lab staff we developed an automatic workflow in our EMR and radiology information system (RIS). Clinicians use our Cerner EMR to order 3D printing services by selecting the available 3D printing orders for each modality i.e. MR CT and US. The order also allows them to add their requirements by filling out relevant Order entry fields (OEFs). 3D printing orders populate the RIS worklist for 3D lab staff to start complete and document the service process. Consultation with ordering clinicians and radiologists is also vital in 3D printing process so we developed a message template for the communication between lab staff and clinicians which also has the capability to attach 3D model PDFs. 3D Lab staff upload the models to our Vendor Neutral Archive (VNA) before completing storing the models in the patient»s record. Building a 3D workflow in an existing EMR has potential benefits to facilitate the 3D service delivery process. It allows 3D printing to rank amongst other modalities important for patient care by living where all other clinical care orders reside. It also allows 3D Lab staff to document the process through quick communication.
Beyond the hospital walls: The lived experiences of Sidra's radiologists with home-based picture archiving and communication system during a global crisis
Objective: This study explores the adaptation of radiologists at Sidra Medicine Qatar to the home-based picture archiving and communication system (HPACS) during the COVID-19 pandemic. Methods: This qualitative study used a phenomenological methodology to delve into the experiences of radiologists using HPACS which emerged as a crucial tool for remote radiology practice during the pandemic. It highlights the perceived benefits barriers and challenges of using HPACS and emphasizes its role in ensuring continuity of patient care and diagnostics while adhering to safety protocols. Results: The study reveals how HPACS facilitated work efficiency and safety and also presented challenges such as workspace limitations and technical issues. The findings suggest a transformative impact of HPACS on the field of radiology and indicate a future marked by increasingly digital and decentralized practices. Conclusion: This research contributes to understanding the adaptation of healthcare professionals to remote work technologies and provides insights for improving remote radiology systems and preparing for future crises.
Epidemiological analysis of event-based surveillance data of Crimean-Congo Hemorrhagic Fever (CCHF) outbreaks across Balochistan Province, Pakistan, from 2000 to August 2021
Background Crimean-Congo hemorrhagic fever (CCHF) is endemic in Balochistan caused by the Bunyaviridae family’s tick-borne virus (Nairovirus). The CCHF virus leads to severe viral hemorrhagic fever outbreaks with a fatality rate of 10–40%. This study aims to describe the epidemiological trend of CCHF in Balochistan and provide recommendations for controlling current and future outbreaks.
Methods A descriptive approach was adopted for data analysis utilizing the standard case definition of the Vector-Borne Diseases (VBD) program.
“Any person of any age and gender residing in Balochistan from 2000 until August 10 2021 presenting with the acute onset of illness featuring a high-grade fever (38.5°C) persisting for more than 3 days but less than 10 days. Individuals should also exhibit any two of the following symptoms: hemorrhagic or purpuric rash nosebleed blood in vomit/sputum/stool or other hemorrhagic symptoms. Moreover there should be no known predisposing factors for hemorrhagic manifestations and individuals must have had contact with a confirmed patient or engaged in handling animals and raw animal products.”
The study covered cases identified from 2000 to August 10 2021 and the descriptive study was conducted at the Provincial Disease Surveillance and Response Unit (PDSRU) in Quetta. Frequencies were calculated and Excel 2016 was used to generate tables and graphs.
Results Based on the case definition 1418 laboratory-confirmed cases of CCHF were identified out of 2542 reported cases from 2000 to August 10 2021. Most cases (89% n = 1262) were found to be males. The case fatality rate increased from 5% to 13% over the last decade. The highest number of CCHF cases occurred in 2017 (n = 172) followed by 2005 (n = 108) and 2004 (n = 107). Direct animal contact was reported in 61% of cases with 22% being butchers and farmers each. CCHF poses a significant public health issue in Balochistan.
Conclusion This study provides a detailed overview of CCHF in Balochistan over the last 21 years recommending the declaration of CCHF as a public health emergency. Establishing a comprehensive tick surveillance system ecological studies and health education sessions in collaboration with the livestock department is crucial to prevent future outbreaks.
Saffara: Intelligent queuing application for improving clinical workflow
This paper examines the impact on patient experience through the creation of a bespoke patient queuing and communication application using in-house developed technologies. Sidra Medicine hospital's outpatient pharmacy was experiencing mismanaged queue lines dissatisfied patients and the lack of data necessary to determine the length of time elapsing in obtaining medication. After analyzing patient surveys through the method of sentiment analysis and generation of word clouds we validated that there was scope for workflow improvement in the pharmacy department. The Center for Medical Innovation Software and Technology (CMIST) department was commissioned to develop the software application necessary to deliver efficiency and improvement in response to the lack of a queuing and communication system. The use of an in-house development team to create an application for queuing and communication as opposed to selecting a popular vendor software resulted in many advantages. Some of the main advantages were that the requirements of pharmacy were delivered through rapid customization and in multiple iterations which were delivered in response to the ever changing customer demand. By using scrum methodology the team was able to deliver the application called Saffara for managing queues in the pharmacy and improving patient experience while obtaining medication. The Saffara application has a unique feature of being integrated to the hospital EMR (Electronic Medical Record) system while ensuring confidentiality efficiency and time saving. The application integrates with the hospital's EMR to obtain patient information appointment times and prescribed medication. This integration allowed for the identification of patients' progress and calculation of patients ‘wait times. Patients are automatically notified when their medication is ready for collection through system generated SMS texts. The application also utilizes a notification display for communication with patients as part of our business continuity procedure. In addition to notifying the patient the Saffara application also generates detailed analytical reports for each hour and for each patient which allows us to analyze the bottlenecks in the clinical workflow. We present these technologies to any stakeholders through a web dashboard and detailed web-based reports in our application. The pharmacy stakeholders i.e. the pharmacy management team utilize the dashboards and quantitative data in the reports to predict staffing levels to deliver optimization in patient medication delivery. In this paper we present the methods we use to calculate the useful analytics like patient wait times across different stages in the workflow and hourly breakdown of patients being served. We will also discuss how we reduced patient wait times by adding unique features to a queuing application like automation of steps in the pharmacy workflow through generation of patient identifiers and automatic ticket tracking. This paper will also highlight how we are scaling our application from pharmacy to all clinics of the hospital. The goal of the application is to provide a consistent experience for patients in all clinics as well as a consistent way for staff to gather and analyze data for workflow improvement. Our future work is to explore how we can use machine learning to identify the parameters that play a vital role in wait times as well as patient experience. The objective of this paper is to highlight how our technology converges the patient experience and staff workflow enhancements to deliver improvement in a clinical workflow setting.