Public health information systems and data standards are essential for public health informatics. The birth of modern vital records systems in the 19th century in England and the U.S. established standards for collecting data on births, deaths, and diseases. This data has been critical for analyzing health trends, identifying disease outbreaks, and informing public health policy. Today, electronic systems have largely replaced paper-based reporting and allow more robust analysis and sharing of surveillance data. Standards ensure consistency and interoperability in collecting and aggregating this important public health information.
Healthcare analytics uses vast amounts of medical data to provide insights that can improve patient care. It has applications such as optimizing staffing, electronic health records, enhancing patient engagement through wearables, preventing opioid abuse by identifying risk factors, and predictive analytics to anticipate conditions and streamline care. Researchers are working to address barriers to healthcare analytics like ensuring high quality training data, eliminating bias, protecting patient privacy, and gaining provider trust.
Clinical Information Systems, Hospital Information Systems & Electronic Healt...Nawanan Theera-Ampornpunt
This document discusses clinical information systems (CIS), hospital information systems (HIS), and electronic health records (EHRs). It defines these terms and explains how they are used in hospitals to support various clinical and administrative functions. Key points include: CIS/HIS are used to manage patient data across departments; they integrate applications like electronic health records, laboratory information systems, pharmacy systems and more. EHRs allow longitudinal documentation of a patient's medical history and care. The use of these systems provides benefits like ubiquitous access to records, clinical decision support, and improved quality of care through functions like computerized physician order entry.
Introduction to Health Informatics and Health Information Technology (Part 1)...Nawanan Theera-Ampornpunt
Presented at the Health Informatics and Health Information Technology Course, Doctor of Philosophy and Master of Science Programs in Data Science for Health Care (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University on October 3, 2017
This document outlines the Province Health Management Information System (SPHIMS) policy for South Province. The objectives of SPHIMS are to establish an integrated web-based health information system to improve healthcare planning, management, and decision making. The key components include health data collection, management, analysis and dissemination. Data will be collected from various public and private health facilities to monitor resources, administration and disease surveillance. Training and regular reviews will ensure effective use of the health management information system.
The document provides an overview of biomedical informatics. It defines biomedical informatics as the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health. It notes that biomedical informatics develops theories, methods and processes for generating, storing, retrieving, using, and sharing biomedical data, information, and knowledge, building on computing, communication and information sciences. Biomedical informatics investigates reasoning, modeling, simulation and translation across scales from molecules to populations.
This document provides an overview of health information systems. It defines key terms like health information system and routine health information system. It describes the six components of an effective health information system according to the HMN framework: governance and leadership; data sources; data management; information products and dissemination; data quality; and data use. It also discusses data collection instruments, indicators, data quality dimensions, and characteristics of a strong health information system. The document is intended to teach participants about health information systems and their essential role in supporting decision-making across health system levels.
This document discusses electronic health records (EHRs) and their components and benefits. It describes how EHRs contain comprehensive patient health information that can be shared electronically. Key parts of an EHR include clinical decision support systems, computerized physician order entry systems, and health information exchange capabilities. The implementation of EHRs can improve patient safety, enhance clinical outcomes, and reduce healthcare costs through increased efficiency and avoidance of errors. However, barriers to adoption include financial costs, workflow changes, and privacy/security concerns.
This document outlines the essential components of a Health Management Information System (HMIS). It discusses the inputs, processes, and outputs of an HMIS and how it provides decision support. Key aspects covered include data collection, standardization, indicators, uses for planning, management, and assessment, and sources of health information such as vital events, infectious diseases reporting, and health facilities records. The document also defines health institutions and care providers and discusses data collection instruments and transmission of reports from facilities to higher levels.
- Lawrence Weed first described the concept of electronic medical records in the 1960s as a way to automate and organize patient records to improve care. Early systems like POMR were developed in the 1970s and refined in later decades.
- Today, most medical practices use electronic systems to record patient information like medical history, medications, test results, and billing data. Adoption has increased but fewer than half of physicians fully utilize digital records.
- Benefits include increased efficiency, reduced errors, better access to information, and potential financial incentives. Challenges include costs of implementation and use, user resistance, and privacy concerns over confidential patient data.
This document provides an introduction to health informatics, including definitions of key terms, subdomains, and applications. It defines health informatics as the intersection of information science, computer science, and healthcare. The document outlines several subdomains including clinical informatics, medical informatics, nursing informatics, and bioinformatics. It also discusses some benefits and barriers to health information technology adoption, highlighting how tools like electronic health records and data warehouses can help improve decision making by generating and sharing health information.
This document discusses clinical decision support systems (CDSS). It begins by defining CDSS as systems that apply medical knowledge to patient data to generate recommendations. It then provides an example of how CDSS could help prevent drug interactions. The document outlines different types of CDSS, including knowledge-based and non-knowledge-based systems using machine learning. It also discusses the history and examples of CDSS, highlighting their role in improving healthcare quality and reducing errors.
The document provides an overview of nursing informatics, including its history from the 1950s to present day, core competencies, education and certification requirements, roles and skills, average salaries, and future outlook. Nursing informatics integrates nursing, computer science, and information science to support data-driven decision making in healthcare. Key areas it can benefit include use of clinical data, patient record management, implementation of standards, and security/privacy of patient information.
A health information system (HIS) refers to a system designed to manage healthcare data, including a patient's electronic medical record, a hospital's operations, and supporting healthcare policy decisions. [HIS] has five core components: hardware, software, telecommunications, databases, and human resources/procedures. Good information management is crucial at all levels of healthcare from local to national as it provides data to policymakers, managers, and healthcare providers. A HIS aims to adequately enable information processing for patient care, administration, research, and education while considering economic and legal factors. It should provide the right information, knowledge, and data to the right people at the right time and place in the right format to support decision making and
Health Information Technology & Nursing InformaticsJil Wright
This document discusses health information technology and nursing informatics. It begins with an introduction by Jil Wright who identifies herself as a nursing informatics "geek". The document then provides resources for more information on health IT and nursing informatics. It discusses how nursing informatics integrates nursing science, computer science, and information science to support patients, nurses, and healthcare providers. Examples of clinical information systems and technologies that can help transform nursing practice are also provided, such as electronic medical records, wireless systems, and RFID technologies. Meaningful use requirements and examples of how health IT can improve documentation and the nursing process are summarized as well.
Introduction to Routine Health Information System SlidesSaide OER Africa
Introduction to Routine Health Information System was created for undergraduate and postgraduate health science students to introduce them to the concepts and methods of routine health information systems.
The learning objectives are to help users explain the roles of routine health information systems (RHIS) in health service management; examine strategies used to improve routine health information systems; acquaint with skills to carry out the process of improving RHIS performance; discuss three categories of determinants that influence RHIS.
This document provides an overview of telemedicine, including its origins, definitions, types, equipment, staffing, benefits, and future directions. Telemedicine allows for the delivery of healthcare services via technology where distance is a factor, including video conferencing between patients and doctors, monitoring patient vitals remotely, and transferring medical data between hospitals. It has various applications like tele-radiology, cardiology, and psychiatry. Establishing telemedicine departments requires equipment like telescopes, ECG machines, digital cameras, and IT infrastructure. Staff typically include doctors, technicians, and administrators. Telemedicine provides benefits like increased access to expertise, cost savings, and opportunities for education and research. Its future expansion may include more robotics and remote
Modern society is highly dependent on the provisioning of clean water, healthy and plentiful food, breathable air, and prompt intervention to curtail disease outbreaks. The public health system is critical in supporting these activities. Today’s information technology provides public health practitioners key capabilities in maintaining the health of the population. This lecture will provide a basic foundation of knowledge about public health practice for clinical informaticians, and highlight specialized information systems and data standards used in public health today. We will explore the existing public health informatics infrastructure including surveillance systems, the process of electronic laboratory reporting (ELR) of notifiable diseases, vital statistics systems, and the critical importance of GIS systems in the public health
Unit-V Health information system MHA II Semester.pptxanjalatchi
This document discusses health informatics systems. It defines health informatics as the intersection of information science, computer science, and healthcare. The document outlines the objectives, requirements, components, sources, uses, and applications of health informatics. It discusses collecting and processing health-related data and information to organize healthcare services and conduct research. Some key benefits of health informatics systems include centralized data, increased efficiency, and improved security and access to patient information.
This document discusses Utah's strategies for improving population health through statewide clinical and public health data interoperability. It outlines Utah's shared vision for using data exchanges across EHRs, HIEs and public health to support population health goals. Key strategies discussed include developing a shared statewide health IT plan and governance model for a master person index to facilitate identity management and data sharing. The document also highlights challenges in making public health systems more interoperable and developing analytics to support diverse population health needs.
The Role of Laboratory Reports in the Adoption of Electronic Medical Recordssmartlinkemr
1) Laboratory information systems emerged in the late 1980s and early 1990s to manage clinical data generated in medical labs and reduce errors, increase reimbursements, and provide access to results.
2) Preventable medical errors are the fifth leading cause of death in the US, with up to 98,000 deaths annually due to issues like transcription errors that electronic records could help address.
3) The adoption of electronic medical records and electronic exchange of lab results can help streamline workflows in medical offices and facilitate care by providing instant access to results.
EHR guidelines from CDC SS-08_WILLIAMSON_GUGERTY.pptxanjalatchi
The document summarizes a presentation on the Centers for Disease Control and Prevention's involvement in health information technology and electronic health record standards development. It discusses how CCDC is participating in initiatives to define public health reporting requirements and support the adoption of EHR systems. It also provides an overview of CCDC's core health care surveys and plans to increasingly utilize electronic health data from sources like EHRs, claims, and administrative systems to conduct research more efficiently as adoption of digital health records increases.
IEx for Clinical Communication and Coordination: Health Department to Clinica...Catherine Schenck-Yglesias
AMIA 2012 Chicago Presymposium - WG-03: Current Issues for Population Health Informatics in Healthcare and Public Health - presentation by Joseph Gibson, MPH, PhD and Catherine Schenck-Yglesias, MHS
This document provides an overview of health informatics and the role of librarians. It defines key terms like electronic health records, health information technology, and meaningful use. It discusses stages of meaningful use and how health informatics tools can improve care delivery and outcomes. The document also explores potential roles for librarians in areas like patient education, training, and research support within the health informatics field.
This document discusses how electronic health records (EHRs) can empower patients. It defines an EHR as a digital record containing a patient's health information from encounters in health care settings. EHRs allow patients direct access to their health records, help coordinate care between providers, and place the patient at the center of their care by enabling more active participation. When patients are more engaged with their health data through EHRs and personal health records, they can make better health decisions and get higher quality care.
The Association of Record Librarians of North America was founded in 1928 as the first association for health information professionals. Over time it evolved into the American Health Information Management Association (AHIMA), which today defines health information management as ensuring the availability of health information to facilitate healthcare delivery and decision making across diverse organizations. AHIMA plays an active role in developing standards for electronic health records and health information confidentiality.
1) The document discusses NCHS's participation in health information technology and electronic health record standards development to support the adoption of EHRs.
2) NCHS has developed and maintained many critical classification standards used in healthcare and is engaged in several initiatives to develop standards for exchanging birth/death data with vital records systems and public health reporting from EHRs.
3) The presentation outlines NCHS's future directions, which include gaining experience receiving standardized administrative and EHR-derived data for its surveys as electronic health records become more widely adopted and able to exchange data.
Barry's 2015 CRC presentation with new CRC ppt templateBarry Dixon
This document discusses the history and future possibilities of wearable technology in healthcare. It notes that wearable devices could help monitor chronic conditions, track vital signs, and reduce healthcare costs. However, wearable devices also raise privacy and security issues. The document outlines several existing wearable devices and their healthcare applications. It predicts that wearables will play a larger role in personalized medicine by collecting more health data over larger populations.
CONTENTS:
Introduction to E Medicine.
History of E Medicine.
E Medicine: What It Means For Patients.
E Medicine: What It Means For Doctors.
National Overview Of E Medicine.
e-Health
m-Health
This presentation describes the historical basis for error reduction initiatives, published errors and rates of occurrence, prototype paper-based model vs software-based model, software-based model deployment, and results.
This document provides an introduction to routine health information systems (RHIS). It defines RHIS as ongoing data collection of health status, interventions, and resources for decision-making. RHIS includes facility-based service statistics, epidemiological and surveillance data, community-based health information, and health administration data. The document outlines the components and standards of a national health information system according to the Health Metrics Network framework. It also describes the three levels of management that RHIS supports - beneficiary, health facility, and system management - and the importance of crafting useful indicators to monitor health services and systems.
This document discusses health information systems (HISs). It defines health as the well-being of a person's physical, mental, and social condition. HISs gather, store, and transmit individuals' and organizations' health-related data, including hospitals, laboratories, and disease surveillance systems. This is done to increase the efficiency of health services and improve personal health. When establishing a HIS, many rules and regulations must be followed to protect individuals' privacy and ensure the accuracy of protected health information. Resources, indicators, data sources, data management, and dissemination and use are all important aspects of developing and maintaining an effective HIS.
Big data and better health outcomes, the journey to the Ministry of Health virtual information centre. Viewed from the National Health IT Board perspective.
Graeme Osborne, Director National Health IT Board
Presented at HINZ 2014, 12 November 2014, 8.30am, Plenary Room
EHRs, PHRs, EMRs: Making Sense of the Alphabet SoupCHI*Atlanta
CHI*Atlanta's October program tackles health records and the potential of user experience to improve their adoption. Panelists include CDC, Kaiser Permanente, and Greenway Technologies. Hosted at Philips Design to cover public, private, and vendor perspectives.
An overview of big data in clinical research. Discussion of big data related to real world evidence (RWE), wearable sensor data (IoT), and clinical genomics. Introduces the use of map-reduce infrastructure for big data in biomedicine.
This document discusses how machine learning and artificial intelligence are increasingly being applied to disease management and healthcare. It outlines several key trends driving this, such as widespread EHR adoption and the availability of large healthcare datasets. The document then provides examples of how supervised, unsupervised, and reinforcement learning are being used in applications like cancer diagnosis, echocardiography analysis, and sepsis treatment optimization. It also discusses regulatory considerations around FDA approval of AI clinical decision support systems. In summary, machine learning is becoming an important tool in healthcare, but ensuring its safe, effective, and appropriate use remains an ongoing challenge.
A brief presentation outlining the concepts of data quality in the context of clinical data, and highlighting the importance of data quality for population health, health analytics, and other secondary uses of clinical data.
Independent forces on the biomedical ecosystem is causing a convergence of care, quality measurement, and clinical research at the point of care. The presentation outlines some of the informatics implications of this convergence.
Quantum computing is an emerging new theory of computation based on the principles of quantum mechanics. It is the basis for a fundamentally new information processing model that is garnering increasing attention in the media and from commercial information technology companies. In certain computing tasks, it can theoretically arrive at a solution more efficiently than classical computers. In this session, we explore the basic principles behind quantum computing, including qubit superposition and entanglement -- the basis for quantum parallelism. We explore quantum logic gates as an abstracted representation of underlying hardware and discuss a simple quantum gate circuit that demonstrates parallelism. We also review the current state of the technology and what has been demonstrated compared to what is theoretically predicted. Current trends in the quantum computing industry will be presented along with proposed possible uses in biomedical informatics.
A brief overview of a 2017 project to integrate EHRs and EDRS systems to improve vital event data collection, as well as transmission of the vital event data using HL7.
This document discusses classic papers in medical informatics and how to identify them. It considers what makes a paper "classic" and different metrics that could be used like citations, influence on the field, or innovation. It reviews prior methods used to measure impact like journal impact factors. The document then discusses the author's own approach of identifying classic papers based on their timeless principles and influence on the emerging discipline of medical informatics. It provides a list of 20 papers the author considers classics in the field, with short descriptions of each paper's significance and influence.
Pathology informatics has evolved from early pioneers applying data analytics and computers to medicine. It involves applying information science principles to pathology practice and laboratory data. At UCDHS, pathology informatics manages laboratory information systems, implements digital pathology, performs data mining and analytics, and oversees clinical registries. Future trends include personalized medicine using "big data", wearable devices, learning healthcare systems, and tethered meta-registries that integrate multiple data sources to improve quality and lower costs.
This document discusses challenges and opportunities in electronically engaging patients for clinical care, research, and education. It uses the Athena Breast Health Network as an example of electronic engagement. Key opportunities include interacting with patients through their preferred channels like mobile, web, and email. Challenges include a lack of policies around email use for research/education and not tracking what mobile devices patients have. As mobile technology becomes more ubiquitous, health systems need policies for electronic engagement across roles and should leverage technologies like smartphones and apps to better communicate and provide services to patients.
This document discusses best practices for clinical systems integration. It emphasizes that interoperability between systems is key to automating complex workflows across different venues. It notes some of the requirements for interfacing with clinical systems, including understanding workflows and EHRs used, knowledge of HL-7 standards, use of standardized coding systems, and an interface engine. The document also lists some common mistakes in integration projects and provides an example of integrating an iPad application, Athena health questionnaires, and an EHR system.
This document discusses data quality in electronic health records and its importance for Medicare programs and healthcare quality. It makes three key points:
1) Medicare spending is unsustainable at current rates and data quality is important for value-based programs like MACRA that tie reimbursement to quality and cost measures.
2) MACRA was introduced to replace the flawed Sustainable Growth Rate formula and moves Medicare reimbursement towards value-based payments through programs like MIPS and APMs that require accurate clinical data.
3) High quality clinical data is essential for measuring healthcare quality, costs, and outcomes required by programs like MACRA and value-based payment models. Data profiling of EHRs reveals many quality issues that can
Quantum computing offers potential advantages over classical computing by utilizing principles of quantum mechanics like superposition and entanglement. A quantum bit or "qubit" can represent more than the binary states of 0 and 1, allowing quantum computers to potentially solve certain problems like searching large databases and optimizing complex systems much faster than classical computers. Several algorithms like Grover's algorithm and Shor's algorithm demonstrate quantum computing's potential. Experimental quantum computers with a handful of qubits have been built by companies like IBM, D-Wave, and others. While still in early stages, quantum computing shows promise for applications in optimization problems in areas like healthcare, machine learning, materials science, and more.
A presentation given at the Duke Margollis Health Policy meeting in 2015 and providing insights into the current challenges related to EHR data quality. Proposes a new approach - OneSource.
General Endocrinology and mechanism of action of hormonesMedicoseAcademics
This presentation, given by Dr. Faiza, Assistant Professor of Physiology, delves into the foundational concepts of general endocrinology. It covers the various types of chemical messengers in the body, including neuroendocrine hormones, neurotransmitters, cytokines, and traditional hormones. Dr. Faiza explains how these messengers are secreted and their modes of action, distinguishing between autocrine, paracrine, and endocrine effects.
The presentation provides detailed examples of glands and specialized cells involved in hormone secretion, such as the pituitary gland, pancreas, parathyroid gland, adrenal medulla, thyroid gland, adrenal cortex, ovaries, and testis. It outlines the special features of hormones, differentiating between peptides and proteins based on their amino acid composition.
Key principles of endocrinology are discussed, including hormone secretion in response to stimuli, the duration of hormone action, hormone concentrations in the blood, and secretion rates. Dr. Faiza highlights the importance of feedback control in hormone secretion, the occurrence of hormonal surges due to positive feedback, and the role of the suprachiasmatic nucleus (SCN) of the hypothalamus as the master clock regulating rhythmic patterns in biological clocks of neuroendocrine cells and endocrine glands.
The presentation also addresses the metabolic clearance of hormones from the blood, explaining the mechanisms involved, such as metabolic destruction by tissues, binding with tissues, and excretion by the liver and kidneys. The differences in half-life between hydrophilic and hydrophobic hormones are explored.
The mechanism of hormone action is thoroughly covered, detailing hormone receptors located on the cell membrane, in the cell cytoplasm, and in the cell nucleus. The processes of upregulation and downregulation of receptors are explained, along with various types of hormone receptors, including ligand-gated ion channels, G protein–linked hormone receptors, and enzyme-linked hormone receptors. The presentation elaborates on second messenger systems such as adenylyl cyclase, cell membrane phospholipid systems, and calcium-calmodulin linked systems.
Finally, the methods for measuring hormone concentrations in the blood, such as radioimmunoassay and enzyme-linked immunosorbent assays (ELISA), are discussed, providing a comprehensive understanding of the tools used in endocrinology research and clinical practice.
Are you ready to reap the benefits of this best magnesium supplement now? Visit us today to learn more about its health and vitality benefits.
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Introduction of mental health nursing, Perspective of mental health and mental health nursing, Evolution of mental health services, treatment and nursing practices Mental health team, Nature and scope of mental health nursing, Role & function of mental health nurse inn various settings and factors affecting the level of nursing practice, concept of normal and abnormal behavior
This Presentation provides information on hyperlipidemic drugs. It begins with an introduction to hyperlipidemia and its causes. It then discusses various drug classes for treating hyperlipidemia, including their mechanisms of action, effects on lipid levels, pharmacokinetics, therapeutic uses, adverse effects and interactions. The major drug classes discussed are HMG-CoA reductase inhibitors (statins), bile acid sequestrants, fibrates, and niacin. For each class, specific drugs are highlighted and their properties compared.
These lecture slides, by Dr Sidra Arshad, offer a simplified description of the physiology of insulin and glucagon.
Learning objectives:
1. Describe the synthesis and release of insulin
2. Explain the mechanism of action of insulin
3. Discuss the metabolic functions of insulin
4. Elucidate the effects of insulin on adipose tissue, skeletal muscle, and liver
5. Enlist the factors which stimulate and inhibit the release of insulin
6. Explain the mechanism of action of glucagon
7. Discuss the metabolic functions of glucagon
8. Elucidate the role of insulin and glucagon in glucose homeostasis during the fasting and fed states
9. Discuss the role of other hormones in the glucose homeostasis
10. Differentiate between the types of diabetes mellitus
11. Explain the pathophysiology of the features of diabetes mellitus
12. Discuss the complications of diabetes mellitus
13. Explain the rationale of oral hypoglycemic drugs
14. Describe the features of hyperinsulinemia
Study Resources:
1. Chapter 79, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 24, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 39, Berne and Levy Physiology, 7th edition
4. Chapter 19, Human Physiology, From Cells to Systems by Lauralee Sherwood, 9th edition
5. Chapter 3, Endocrine and Reproductive Physiology, Bruce A. White and Susan P. Porterfield, 4th edition
6. Insulin and Insulin Resistance, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1204764/
7. Complications of diabetes mellitus,
https://pdb101.rcsb.org/global-health/diabetes-mellitus/monitoring/complications
Safety should always come first when it comes to medical operations involving the use of a Huber needle. Disposable safety Huber needles are useful in this situation. A secure and effective method of accessing and delivering medication to a patient's port is provided by these single-use devices. But it might be difficult to choose the best option when there are so many on the market. We've put up the best advice to selecting the ideal disposable safety Huber needle so you can make an educated choice.
The Revolutionary Nature of Needleless Double Transfer Spikes in HealthcareNanchang Kindly Meditech
It's likely that you have witnessed medical personnel using needles to transmit fluids or medicines if you have ever visited a hospital or other healthcare facility. But as technology advances, needleless double transfer spikes are becoming more and more common and revolutionizing the delivery of healthcare.
- Video recording of this lecture in English language: https://youtu.be/AWaobASkZM4
- Video recording of this lecture in Arabic language: https://youtu.be/1cQRmJ3SKWc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
This presentation gives a clear explanation of hemodynamics and cardiac electrophysiology which will be helpful for students of bpharmacy sem 5 as a part of the pharmacology. the presentation is explained diagramatically which makes ease for the students.
HIV weakens the immune system, increasing the risk of TB in people with HIV. Infection with both HIV and TB is called HIV/TB coinfection. This presentation is an overview on "HIV-Tuberculosis Coinfection"
Principles of Cleaning
Nonsurgical root canal treatment is a predictable method of retaining a tooth that otherwise would require extraction. Success of root canal treatment in a tooth with a vital pulp is higher than that of a tooth that is necrotic with periradicular pathosis. The difference is the persistent irritation of necrotic tissue remnants, and the inability to remove the microorganisms and their by-products. The most significant factors affecting this process are tooth anatomy and morphology, and the instruments and irrigants available for treatment. Instruments must contact and plane the canal walls to debride the canal.
Morphologic factors such as lateral and accessory canals, canal curvatures, canal wall irregularities, fins, cul-de-sacs, and isthmuses make total debridement virtually impossible. Therefore the goal of cleaning not total elimination of the irritants but it is to reduce the irritants.
Currently there are no reliable methods to assess cleaning. The presence of clean dentinal shavings, the color of the irrigant, and canal enlargement three file sizes beyond the first instrument to bind have been used to assess the adequacy; however, these do not correlate well with debridement. Obtaining glassy smooth walls is a preferred indicator. The properly prepared canals should feel smooth in all dimensions when the tip of a small file is pushed against the canal walls. This indicates that files have had contact and planed all accessible canal walls thereby maximizing debridement (recognizing that total debridement usually does not occur).
Principles of Shaping
The purpose of shaping is to
1) facilitate cleaning and
2) provide space for placing the obturating materials.
The main objective of shaping is to maintain or develop a continuously tapering funnel from the canal orifice to the apex. This decreases procedural errors when cleaning and enlarging apically. The degree of enlargement is often dictated by the method of obturation. For lateral compaction of gutta percha the canal should be enlarged sufficiently to permit placement of the spreader to within 1-2 millimeters of the corrected working length. There is a correlation between the depth of spreader penetration and the apical seal.5 For warm vertical compaction techniques the coronal enlargement must permit the placement of the pluggers to within 3 to 5 mm of the corrected working length.6
As dentin is removed from the canal walls the root is weakened.7 The degree of shaping is determined by the preoperative root dimension, the obturation technique, and the restorative treatment plan. Narrow thin roots such as the mandibular incisors cannot be enlarged to the same degree as more bulky roots such as the maxillary central incisors. Post placement is also a determining factor in the amount of coronal dentin removal.
Hemodialysis: Chapter 11, Venous Catheter - Basics, Insertion, Use and Care -...NephroTube - Dr.Gawad
- Video recording of this lecture in English language: https://youtu.be/QeWTw_fYPlA
- Video recording of this lecture in Arabic language: https://youtu.be/fUWI9boFc7w
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Interventional radiology is a medical specialty that uses imaging techniques, such as X-rays, CT scans, and ultrasound, to guide minimally invasive procedures to diagnose and treat a variety of conditions. These procedures can be an alternative to open surgery, often resulting in shorter recovery times for patients.
Regenerative Medicine in Chronic Pain ManagementReza Aminnejad
Regenerative technologies are the future of medicine. The current clinical strategy focuses primarily on treating the symptoms but regenerative medicine seeks to replace tissue or organs that have been damaged by age, disease, trauma, or congenital issues.
Health communication, AI and health misinformation.pptx
Public Health Information Systems and Data Standards in Public Health Informatics
1. PUBLIC HEALTH INFORMATION SYSTEMS
AND DATA STANDARDS IN PUBLIC HEALTH
INFORMATICS
MED264: Principles of Biomedical Informatics
Michael Hogarth, MD, FACP
Professor, Internal Medicine
Professor and Vice Chair, Dept. of Pathology and Laboratory Medicine
PI, California Electronic Death Registration System (CA-EDRS)
http://www.hogarth.org
mahogarth@ucdavis.edu
3. The birth of “public health”
• Dr. Chadwick
– Secretary for the British Poor-Law
commission
– Demonstrated the value and need for
information that could be obtained
from a vital records process.
• 1836 – the birth of modern “vital
records”
– following a cholera epidemic of 1831
– the UK enacted a registration law
creating a central register office with
responsibility for records and
statistics of births, marriages, and
deaths in England and Wales
4. The UK Public Health Act of 1848
• Sir Edwin Chadwick published a
widely read and important report
on sanitation and disease
– felt that disease was the main cause
of poverty, hence preventing
disease would reduce poverty.
• Chadwick led the creation of the
Public Health Act of 1848
– created a General Health Board to
oversee sanitation
• Included mechanism for local
boards of health to be created
with an appointed medical officer
– established several an important
precedent for government to
oversee sanitation as a way of
reducing the burden of disease
5. Snow and the Theory of Disease
London Cholera Outbreak 1854 Snow’s map of cases
Dr. John Snow (1813-1858) http://en.wikipedia.org/wiki/John_Snow_(physician)
6. Vital Records and Public Health
• William Farr, in 1838, became
the first medical statistician in
the General Register Office for
England and Wales
• instrumental in using statistics
to study the health of
populations
• Set up a system for routinely
recording causes of death
• Used this data (vital statistics)
to compare mortality rates
across different occupations
• Instrumental in the creation of
ICD – international
classification of disease
http://en.wikipedia.org/wiki/File:Farr_william1870.gif
7. Data, Statistics, and Improving the Public’s Health
• Florence Nightingale (1820-
1910)
• The first “public health
informaticist”
• Believed statistics could lead
to improvements in health
care practices
• Developed the “Model
Hospital Statistical Form” to
collect and generate data to
perform statistics and identify
areas for improvement
• Founded a the first formal
nursing training program
(Nightingale School for
Nurses, King’s College,
London)
8. U.S. Vital Statistics Reporting - 1890
http://www.cdc.gov/nchs/data/vsushistorical/vsush_1890_1.pdf
9. Public Health and Improving Population Health
• Improved Sanitation
– Sewage treatment
– Potable water
• Vaccination
– Small pox, polio, diphtheria,
whooping cough, tetanus,
influenza, measles, mumps,
rubella
– Pneumonia, haemophilus
influenza, herpes zoster,
hepatitis
• Surveillance
– Monitoring
– Serologic and Microbiologic
testing
• Providing safety net care
– County health programs
http://en.wikipedia.org/wiki/File:Salk_headlines.jpg
10. The Value of Public Health
http://en.wikipedia.org/wiki/File:Measles_US_1944-2007_inset.png
11. The Role of Data in Public Health
• Data acquisition and analysis are fundamental
to public health practice
• Public health data to public health practice is
akin to vital signs in individual patient practice
15. California Open Data – Sept 2014
https://health.data.ca.gov/
Este Geraghty, MD, MPH,MS,GISP
16. The Role of Informatics in Public Health
• Health data is critical to public health practice
• Information management, information science,
and information technology are key functions in
public health
– Data collection systems
– Information representation
• coding, data elements, metadata
– Data management
• storage, archiving
– Computer security for digital data
• policies, security procedures
18. Public Health one of the first use computers
• 1938 – Illinois Dept. of Public
Health acquires an IBM
tabulation system for vital
statistics (Lumpkin. Public Health
Informatics and Information Systems. 2002)
• 1951 – US Census Bureau used
the first computer (ENIAC) to
tabulate the census
http://en.wikipedia.org/wiki/File:Early_SSA_accounting_operations.jpg
IBM 285
Tabulator
(1936)
19. Common Informatics Activities
• Public health informatics planning and policy
– Strategic planning – to align with org
– Policy development – privacy, legal, ethics
• Information Management infrastructure
– Analytics platform (SPSS, SAS)
– Data Set acquisition, curating, distribution
• Information Technology Infrastructure
– Geographic Information Systems
• To support professional GIS analysts
• Provide infrastructure for information dissemination
– Information technology services coordination
• Public health application development, support – ELR, eVitalRecords, IIS
• Web site management
• Coordinating the installation/operation of other public health systems
(STEVE, EVVE, NEDSS)
• Managing/coordinating electronic medical record systems for clinical care
20. HI-TECH and Public Health
1. Meaningful Use public
health “menu options”
– Electronic laboratory
reporting
– Immunization information
systems
2. State Health Information
Exchange (HIE)
– Universal adoption of HIE
within the state prior to 2015
– Grant program administered
by HHS and funded by ARRA
22. Core Public Health Information Systems
• Vital Records Systems
• Immunization Registries
• Disease Surveillance Systems
• Electronic Laboratory Reporting Systems
• Disease Registries (cancer, etc..)
• Health Information Exchanges (HIE)
• Geospatial Information Systems (GIS)
24. Vital Records Systems
• Vital “Statistics”
– “statistics” = ‘data about the state’
– originated from:
•need to track populations and their status (health)
•need to officially record lineage and thus ownership and
entitlements
• “Vital Records” systems are managed in public
health and typically consist of:
– birth certificates
– death certificates
– marriage certificates
25. US Vital Statistics System
• 1632: Virginia - first state to legally require registration of
vital events (birth, death, marriage)
• 1902: US Bureau of the Census authorized to obtain
annual copies of records filed in the vital statistics offices
of states having adequate death registration systems
• 1915: National birth registration collection authorized
• 1933: All states reporting both birth and death events
27. NCHS National Death Index File
http://www.cdc.gov/nchs/data_access/ndi/about_ndi.htm
Available to investigators solely for
statistical purposes in medical and
health research.
Not accessible to organizations or the
general public for legal,
administrative, or genealogy
purposes.
28. Standard Birth and Death Certificates
• These are ‘model’ certificates offered to states
in order that there is uniformity in data
collection making it easier to aggregate at the
federal level
• Last revision - 2003
http://www.cdc.gov/nchs/nvss/vital_certificate_revisions.htm
29. Natality Data and Public Health
• Natality Files
– Teen childbearing
– Non-marital childbearing
– Pre-term birth
– Low birthweight
– Cesarean delivery
1940 1950 1960 1970 1980 1990 2000
0
20
40
60
80
100
Birthrateper1,000women
aged15-19
0
100
200
300
400
500
600
700
Numberofbirths(inthousands)
Number of births
Birth rate
Number of births and birth rates for teenagers
aged 15-19 years: United States, 1960-2000
http://www.cdc.gov/nchs/nvss/vital_certificat
e_revisions.htm
30. Death Files and Public Health
• Death Statistics Files
– Cause-of-death trends
– Leading causes of death
– Life expectancy
– socio-economic factors
– Demographic variation
http://www.cdc.gov/nchs/nvss/vital_certificat
e_revisions.htm
31. Problems with Vital Statistics Today
• Federal government issued reports on
national birth and mortality statistics lag 12-15
months
• A significant amount of the information
reported is also collected as part of medical
care (the medical record) – but the certificate
and medical record are often contradictory
and not equivalent!
• Registration is mostly a manual process even
today.
34. Death Registration in California Today
• In 2005, California
implemented an electronic
death registration system
• Today, 99.8% of all deaths
are registered electronically
in CA-EDRS
• The system contains death
certificate data for over 2.1
million deaths since 2005.
36. Immunization Information Systems
• What are they?
– Confidential, population-based, computerized
information systems that attempt to collect
vaccination data about all residents within a
geographic area
• Advantages of IIS:
– Significantly reduces paperwork and staff time for
schools, doctors, public health
– Assists in reminding parents of needed immunizations
– Allows public health to monitor immunizations
http://www.cdc.gov/vaccines/programs/iis/faq.htm
38. SEER -– Cancer Registry Data
• Surveillance Epidemiology and End
Results (SEER)
• Since 1973, an national cancer
registry run by the National Cancer
Institute
• Collects and publishes cancer
incidence and survival data
• Derives data from a set of local
cancer registries covering 26% of the
population
• NCI staff work with the North
American Association of Central
Cancer Registries (NAACCR) to
develop guidelines on the data to be
collected
39. National Health Information Network
• NHIN should “be a decentralized architecture built
using the Internet linked by uniform communications
and a software framework of open standards and
policies”
• 2005: ONC awards contracts to develop prototype
architectures
• 2006: Executive order requires federal agencies
dealing with health information to adhere to national
interoperability standards
• 2008: ONC announced NHIN CONNECT with 20
federal agencies being interconnected on “the NHIN”
42. What is GIS?
“Geographic Information
Systems (GIS) are
computer based systems
for the integration and
analysis of geographic
data”
Cromley and McLafferty. GIS and Public Health.
2002. Guilford Press
http://www.cdc.gov/gis/mg_age_adj_98_01.htm
43. Key Functions of a GIS System
• Ability to store or compute and display spatial
relationships between objects on a digital map
• Ability to store attributes of those objects
• Ability to analyze spatial and attribute data in
addition to managing and retrieving data
• Ability to integrate spatial data from different
resources
Goodchild, MF. GIS and geographic research. In J. Picles (Ed.), Ground truth: The Social
Implications of geographic information systems (pp31-50). New York. Guilford Press. 1995
44. GIS Layers
• GIS systems typically
store information about
the world in layers
• Each layer has additional
geospatial objects
• One can add/remove
layers in a GIS system
• As layers are added, a
picture of the real world
emerges
http://www.rockvillemd.gov/gis/
45. GIS Data and Image Basics
• Ways GIS systems represent geospatial objects
– Vector Data
• geometric approximations of objects on the earth
• Objects are described by their type, and their geometric
shape
• The GIS system uses this information to ‘draw’ the objects
with correct proportions and geographic orientation
– Raster Data
• Data is stored in as individual pixels, which individually carry
color and position information
• Provides more of a ‘real world’ view – looks like a satellite
photograph
46. Vector Data
• Vector data provides a way of representing
real world features in terms of their geometry
– “a sketch” of the real feature
• Vector data includes geospatial attributes that
describe the feature
• The geometry
– Made up of one or more vertices
– A vertex describes a position in space using an x,y
coordinate system
47. Types of Vector Geospatial Objects
• Vector point
– Consists of a single vertex
– A single point on the map
• Polyline
– Consists of two or more vertices with the first and last
vertices not being the same
• Polygon
– Four or more vertices are present
– Last vertex is the same as the first (closed the loop)
48. Vector Object Types
T. Sutton, O. Dassau, M. Sutton. A Gentle Introduction to GIS. Dept of Land Affairs. Eastern Cape, South Africa.
49. Vector Layers
Vector map with road Road layer only
T. Sutton, O. Dassau, M. Sutton. A Gentle Introduction to GIS. Dept of Land Affairs. Eastern Cape, South Africa.
50. Adding data attributes to vector objects
• Vector object data comes in two types:
– (1) geospatial data about the object
– (2) additional data related to the object
• This is the “secret sauce” of GIS – it is a
geospatial *database*
– Allows for a broad variety of analyses regarding
geospatial objects and attribute data such as disease
conditions, etc..
– Allows for map-based visualization of disease patterns
or other information
51. Combining geospatial and disease data
Geospatial
data
Other data related
to the object
T. Sutton, O. Dassau, M. Sutton. A Gentle Introduction to GIS. Dept of Land Affairs. Eastern Cape, South Africa.
53. Raster Data
• Raster data is used when
information is contiguous
across an area and is not
easily divided into vector
features
• Raster data set is
composed of rows and
columns of pixels, with
the value in the pixel
representing some
characteristic (snow level,
temperature, depth, etc..)
T. Sutton, O. Dassau, M. Sutton. A Gentle Introduction to GIS. Dept of Land Affairs. Eastern Cape, South Africa.
Sacramento Area Raster image:
created with Google Earth
54. Raster Data
• Provides for analysis
that cannot be done
easily with vector data
– Water flow over land to
calculate watersheds
– Identification of areas
where plants are
growing poorly
– Areas of deforestation
– Areas under risk of
flooding
56. What is surveillance?
“the ongoing systematic collection, analysis, and
interpretation of outcome-specific data for use
in planning, implementation, and evaluation of
public health practice”
Thacker SB, Berkelman RL. Public health surveillance system in the United States. Epidemiol Rev. 1988; 10:164-190
57. Disease Surveillance – the basics
• Disease surveillance is a critical function in public
health
• Several types of surveillance systems
– Sentinel surveillance systems
•Collect/analyze data from a select group of institutions
– Household surveys
•Population based, monitoring of a disease/condition
– Laboratory-based surveillance
•Reporting the genetic variability of an agent
– Integrated disease surveillance and response
•Use data from health facilities, labs, etc...
•Monitor communicable diseases
58. National Notifiable Disease Surveillance
System: A History
• 1878: Congress authorizes the US Marine Hospital
Service to collect morbidity reports on cholera,
smallpox, plague, and yellow fever from US consuls
overseas.
• 1893: Expanded to include data from states for this
list of “notifiable diseases”
• 1912: state and public health service begin reporting
– 5 diseases by telegraph
– 10 diseases by letter
60. CDC Surveillance Systems and Programs
• CDC has over 30 surveillance programs and systems
• Here are some examples
– 121 cities mortality reporting system
– Active Bacterial Core Surveillance
– Border Infectious Disease Surveillance Project
– Foodborne Diseases Active Surveillance Network (Foodnet)
– Waterborne-Disease Outbreak Surveillance System
– Public Health Laboratory Information System (PHLIS)
61. Categorizing Surveillance Systems
• Rapid (Early) Recognition Disease Surveillance
– Surveillance for a disease that demands early detection and fast
countermeasures to avoid high mortality“
– Premium placed on early detection – tapping data streams for a pattern that we
believe means disease *outbreak* (the signal)
– Typically need immediate input from multiple disparate data sources that are
associated with behavior or actions typically occurring because of the outbreak
– Informatics impact: Access to absenteeism data, over-the-counter medications
for “the cold”, clinical encounter types, patient ‘complaints’ (symptoms –
syndromic surveillance).
• Exposure/Disease Monitoring Surveillance System
– Surveillance for a disease that results from prolonged exposure to causal factors
– Premium placed on understanding the association of a causal factor with the
disease
– Typically need long term longitudinal data for causal factors
– Example: Cancer Registries
– Informatics impact: Access to longitudinal data (clinical encounters, cumulative
CT radiation dose, etc..)
62. Early Recognition Surveillance
• Goals: Reduce the number of cases of a
disease by
– Rapid administration of prophylaxis: administering
the most effective prophylaxis (if it exists) to the
right people in the quickest way possible
– Enable “social distancing” to reduce the spread of
the disease
• Systems typically built to tap multiple types of
information, including chief complaints in the
ED (“syndromic surveillance)
63. Why is Early Recognition surveillance
so important?
• We live in a time of rapid
travel between large
urban areas – perfect
conditions for a killer
communicable disease
• 2009 H1N1 Influenza A
pandemic had a mortality
rate of only 0.01% (1 in
10,000) yet it killed
14,000 worldwide in a
few months...
61 million infected
64. The big threat....a viral pandemic
• 1918 Influenza pandemic
– 20% fatality rate
– 50 million died (3% of the
world population of 1.86
billion)
• Avian flu (H5N1)
– H5N1 has a 60% fatality rate
(three times that of 1918 virus)
– So, 3x3%=9% of 7 billion
630 million deaths
worldwide....
– Wild type Avian Flu, so far, has
not demonstrated the ability to
have airborne spread, but......
• Dec 2011 - Dr. Fouchier of
Erasmus Medical Center
modified H5N1 (avian flu) such
that it gained the ability to latch
onto cells in the respiratory
passage ways (making it
airborne).
http://en.wikipedia.org/wiki/1918_flu_pandemic
http://en.wikipedia.org/wiki/Human_mortality_from_H5N1
http://en.wikipedia.org/wiki/
File:Colorized_transmission_e
lectron_micrograph_of_Avian
_influenza_A_H5N1_viruses.j
pg
H5N1 - electron micrograph
1918 pandemic victim
67. Key Aspects of “Early Recognition”
• Defining “Signals”
– Are we talking about the same thing?
– Are we defining it the same way?
• Signal Detection
– “how do I set thresholds?”
• Signal Characterization
– “so what should we do?”
Mirhaji. Public health meets translational informatics: A desiderata. JALA 2009;14:157-70
68. Examples of Early Recognition Surveillance
• Pneumonia and Influenza Mortality Surveillance
– 122 cities, vital statistics offices report total number of death
certificates received and the number for which pneumonia or
influenza was listed as the underlying cause or a contributing cause to
the death
• ILINet
– 3,000 healthcare providers (The US Influenza Sentinel Provider
Surveillance Network) across all 50 states, DC, territories reporting
Influenza Like Illness cases from over 30 million patient visits annually
• Foodnet
– Surveillance on campylobacter, cryptosporidium, cyclospora, Listeria,
Salmonella, Toxin producing E-Coli, Shigella, Vibrio Cholera, Yersinia
diagnosed by laboratory testing of samples from patients
69. 121 Cities Mortality Reporting System
• Reports from vital records
offices for jurisdictions that
have one of the 121 cities
• In place for 40+ years
70. Sentinel Provider Network (ILINet)
• Interested providers (hospitals,
doctors, nurse practitioners) and
enroll them into the CDC sentinel
provider network
• Goal - one reporting sentinel provider
for every 250,000 residents
• Smaller states – minimum of 10
sentinel providers
• Sentinel Provider
– Any specialty (nursing homes, prisons do not
participate)
– ILI Case Definition: fever >100F and cough or
sore throat
– Data collection: summary data each week,
total patients, age groups
– Collection of respiratory specimens sent to
state lab
• 12 million patients visits per year
71. The CDC’s FluView
• A weekly influenza surveillance
report
• Consolidates 5 sources of
information
– rate of influenza positive
specimens (US virologic
surveillance system)
– proportion of deaths attributed to
influenza (P&I 122 cities rep)
– pediatric deaths from influenza
– Proportion of outpatient visits for
influenza-like illness (from ILINet’s
Sentinel Network providers)
– State map showing geographic
spread of Influenza
• Not very automated.... Requires
manual collection and
submission of data
http://www.cdc.gov/flu/weekly/index.htm#OISmap
73. Syndromic Surveillance
• “the ongoing, systematic collection, analysis,
interpretation, and application of real-time (or
near real time) indicators for diseases and
outbreaks that allow for their detection before
public health authorities would otherwise note
them.”
• Emphasizes
– Timeliness of inbound data (real-time)
– Automated analysis
– Visualization tools
Lee, LM editor. Principles and Practice of Public Health Surveillance, 3rd Ed. Oxford Press. 2010
74. Data Sources and “Syndromic
Surveillance” systems
Yan, Chen, Zeng. Syndromic surveillance systems: Public health and biodefense.
Ann Rev Inf Science and Technology. Vol 32. 2008
75. Challenges with ED Encounter Data
• If data is coded
– Code mismatch
• The use of different coding systems, or different versions of the same
coding system across the various source sites
• If data is not coded (common)
– Misspellings: 10-20% of common words are misspelled in
hospital records
– Abbreviations: 20% of all words in chief complaints were
nonstandard abbreviations or acronyms
– Negatives: “no fever present” can be a challenge to process
correctly (NegEx – an open source negation detection module
for clinical natural language processing)
– Extraneous characters: often cause challenges for natural
language processing systems in detecting word boundaries and
the “part of speech” for the word or phrase (verb, noun, etc..)
Hauentstein, et al. In Disease Surveillance: A Public Health Informatics Approach. Edited by Lombardo J, Buckeridge DL. Wiley
Publishers. 2007
76. BioSense 1.0
• National lab test orders
and results
• DoD and VA sentinel
clinical data
• Clinical lab orders
• Advice nurse call line
types
• Lab Response
Network (Biowatch)
• Over-the-counter drug
sales
82. Scope of PHIN
5 public health functional areas
1. Detection and monitoring
2. Data analysis
3. Knowledge management
4. Alerting
5. Response
9 IT functions
To support these 5 public health functions, the CDC
has developed specifications for nine IT functions:
1. Automated exchange of data between public
health partners
2. Use of electronic clinical data for event detection
3. Manual data entry for event detection and
management
4. Specimen and lab result information management
and exchange
5. Management of possible case, contacts, and
threat data
6. Analysis and visualization
7. Directories of public health and clinical personnel
8. Public health information dissemination and
alerting
9. IT security and critical infrastructure protection
85. Immunizations HL7 Messages
CDC Implementation Guide Message Types Involved
• VXU – unsolicited request
immunization record
• VXQ – unsolicited
immunization record update
• QBP – Query by parameter
• RSP – Respond to QBP
• ADT – Admit, Discharge,
Transfer message
• ACK – Acknowledgement
message
86. Standardizing Lists of Vaccines and Manufacturers
Standard vaccine codes (CVX) Standard manufacturer codes (MVX)
87. Example Immunization Information System HL-7
Message
MSH|^~&||GA0000||VAERS PROCESSOR|20010331605||ORU^RO1|20010422GA03|T|2.3.1|||AL|
PID|||1234^^^^SR~1234-12^^^^LR~00725^^^^MR||Doe^John^Fitzgerald^JR^^^L||20001007|M||2106-3^White^HL70005|123 Peachtree St^APT
3B^Atlanta^GA^30210^^M^^GA067||(678) 555-1212^^PRN|
NK1|1|Jones^Jane^Lee^^RN|VAB^Vaccine administered by (Name)^HL70063|
NK1|2|Jones^Jane^Lee^^RN|FVP^Form completed by (Name)-Vaccine provider^HL70063|101 Main Street^^Atlanta^GA^38765^^O^^GA121||(404) 554-9097^^WPN|
ORC|CN|||||||||||1234567^Welby^Marcus^J^Jr^Dr.^MD^L|||||||||Peachtree Clinic|101 Main Street^^Atlanta^GA^38765^^O^^GA121|(404) 554-
9097^^WPN|101 Main Street^^Atlanta^GA^38765^^O^^GA121|
OBR|1|||^CDC VAERS-1 (FDA) Report|||20010316|
OBX|1|NM|21612-7^Reported Patient Age^LN||05|mo^month^ANSI|
OBX|1|TS|30947-6^Date form completed^LN||20010316|
OBX|2|FT|30948-4^Vaccination adverse events and treatment, if any^LN|1|fever of 106F, with vomiting, seizures, persistent crying lasting over 3 hours, loss of
appetite|
OBX|3|CE|30949-2^Vaccination adverse event outcome^LN|1|E^required emergency room/doctor visit^NIP005|
OBX|4|CE|30949-2^Vaccination adverse event outcome^LN|1|H^required hospitalization^NIP005|
OBX|5|NM|30950-0^Number of days hospitalized due to vaccination adverse event^LN|1|02|d^day^ANSI|
OBX|6|CE|30951-8^Patient recovered^LN||Y^Yes^ HL70239|
OBX|7|TS|30952-6^Date of vaccination^LN||20010216|
OBX|8|TS|30953-4^Adverse event onset date and time^LN||200102180900|
OBX|9|FT|30954-2^Relevant diagnostic tests/lab data^LN||Electrolytes, CBC, Blood culture|
OBR|2|||30955-9^All vaccines given on date listed in #10^LN|
OBX|1|CE30955-9&30956-7^Vaccine type^LN|1|08^HepB-Adolescent/pediatric^CVX|
OBX|2|CE|30955-9&30957-5^Manufacturer^LN|1|MSD^Merck^MVX|
OBX|3|ST|30955-9&30959-1^Lot number^LN|1|MRK12345|
OBX|4|CE|30955-9&30958-3^ Route^LN|1|IM^Intramuscular ^HL70162|
OBX|5|CE|30955-9&31034-2^Site^LN|1|LA^Left arm^ HL70163|
OBX|6|NM|30955-9&30960-9^Number of previous doses^LN|1|01I
OBX|7|CE|CE|30955-9&30956-7^Vaccine type^LN|2|50^DTaP-Hib^CVX|
OBX|8|CE|30955-9&30957-5^ Manufacturer^LN|2|WAL^Wyeth_Ayerst^MVX|
OBX|9|ST|30955-9&30959-1^Lot number^LN|2|W46932777|
OBX|10|CE|30955-9&30958-3^ Route^LN|2|IM^Intramuscular^HL70162|
90. Death Certificates - ICD
• Causes of Death are coded using the International
Classification of Disease, 10th edition (ICD-10)
• ACME – Automated Classification of Medical Entities
– Developed to improve consistency
– Developed with experienced nosologists
– SuperMICAR: a software system that automates the
classification and allows the use of literal text from the
death certificate
• Used today to expedite the coding of causes of death on certificate
information submitted by states to the National Center for Health
Statistics (NCHS).
91. PHIN - VADS
• A one-stop shop for obtaining vocabularies
related to public health
• Main purpose is to distribute value sets
developed by the CDC for use in v2.x and CDA
messages in public health
• 592 value sets supporting 60 HL7 and CDA
message implementation guides
• Value sets are function specific and derived from
a number of vocabularies (LOINC, SNOMED, CPT,
ICD, etc..)
95. ICD 11
• Foundation = ICD Concepts
• Linearization=A specific list for a
particular Purpose (primary care,
cause of death, etc...)
Editor's Notes
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24
25
26
27
28
29
30
31
32
33
34
Another commonly encountered system in public health today is the immunization registry.
Immunization Information Systems, or IIS, are population-based, secure, confidential, computerized data about the immunization status of all residents within an area.
The advantage of an IIS is significant reduction in paperwork as well as staff time across a broad spectrum of information partners in public health, including schools, doctors, and the public health department.
An IIS can also assist in reminding parents of upcoming needed immunizations.
38
39
40
In this session, we will cover an overview of geographic information systems and their use in public health
57
58
59
60
69
70
76
77
78
Now we will focus on healthcare data exchange standards as used in public health.
In response to the need for a more robust and comprehensive public health informatics infrastructure, the Centers for Disease Control (CDC) devised the public health information network, or PHIN.
PHIN has three strategic goals:
1. Lead the development of policies, standards, and services for nationwide public health information exchange
2. Support public health needs in national information technology initiatives
3. Enable key public health information exchange
PHIN focuses on workflows and transactions that are key in enabling five functions in public health. These include: (1) detection and monitoring, (2) data analysis, (3) knowledge management, (4) alerting and communication, and (5) Response
To support these functions, PHIN outlines a number of information technology functions.
These include:
Automated exchange of data between public health entities
Leveraging clinical information system data for event detection
Specimen and laboratory result information management and exchange
Management of cases, contacts, and other threat data
Analysis and visualization of the data, particularly super-imposed on geographic information
Directories of public health and clinical personnel
Public health reporting and alerting systems
Protection of data through IT security and robust critical infrastructure
This is an example of a PHIN standard that supports the communication of reportable cases between states and the CDC.
The PHIN Condition Reporting specifications uses the HL7 v2.5 standard as a mechanism for packaging the required information for submission to the CDC.
It employs an ORU^R01 message, which is commonly used by filler systems such as laboratory information systems or radiology information systems to transfer information to a central electronic health record systems.
In this diagram, you can see an example PHIN reportable condition messaging that uses the HL7 standard.
In this case, it is reporting answers to a number of questions, each question represented as an orderable test, and each answer being put into an OBX segment, much like one might do with a laboratory test result.
IIS systems can employ a PHIN Immunization Message standard to support communication between IIS systems and EHR systems.
A number of H-7 message types are involved including VXU, VXQ, QBP, RSP and the standard ADT and ACK messages.
Much like other systems in healthcare, immunization registries benefit significantly from having well-structured and coded data.
To ensure this, HL-7 has standardized the content related to immunization.
in this case, it involves the vaccine codes (CVX), as well as the manufacturer codes (MVX)
The CDC publishes allowable codes sets for these.
Now we will look at the use of coding and classification systems specifically in public health today
As we have seen, The most common coding system encountered in public health is the International Classification of Disease (ICD), which has been used for over 150 years to report summary causes of death from death certificates.
The process of converting the multi-statement causes of death section into a single summary cause is called “nosology”.
For many years this was done manually, and in many cases a substantial number of death certificate causes of death are still classified manually.
However, since the early 1970’s, the NCHS has attempted to help with the classification by providing software systems that automated parts of this process.
The most recent component of the Automated Classification of Medical Entities (ACME) system is tthe SuperMICAR system.
SuperMICAR automates the classification of literal text from the death certificate into ICD-10 codes. It can handle over 75% of the cases automatically. The rest are done manually by a nosologist, who also reviews all of the assignments.
For this reason, the official national statistics on causes of death are typically delayed 1-3 years.
Vocabulary standards are a key component of the PHIN infrastructure.
For this reason, the CDC has developed and implemented a comprehensive infrastructure for managing code sets required in PHIN.
This systems is known as VADS – the Vocabulary Access and Distribution System
The CDC has developed a list of 592 value sets that support 60 HL7 and CDA message implementations used in PHIN.
The values sets derive their codes from a number of coding systems, including LOINC, SNOMED CT, CPT, ICD and others.
PHIN VADS provides a means for managing these value sets and for local and state entities to automatically keep updated on the latest versions.
This shows the VADS value set of codes and descriptions for Microorganisms used in electronic laboratory reporting messages. The CDC publishes these through the Vocabulary Server infrastructure they have developed.