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Artificial Intelligence in Health Care: the Hope, the Hype, the Promise, the Peril
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril Michael Matheny, Sonoo Thadaney Israni, Mahnoor Ahmed, and Danielle Whicher, Editors WASHINGTON, DC NAM.EDU PREPUBLICATION COPY - Uncorrected Proofs NATIONAL ACADEMY OF MEDICINE • 500 Fifth Street, NW • WASHINGTON, DC 20001 NOTICE: This publication has undergone peer review according to procedures established by the National Academy of Medicine (NAM). Publication by the NAM worthy of public attention, but does not constitute endorsement of conclusions and recommendationssignifies that it is the by productthe NAM. of The a carefully views presented considered in processthis publication and is a contributionare those of individual contributors and do not represent formal consensus positions of the authors’ organizations; the NAM; or the National Academies of Sciences, Engineering, and Medicine. Library of Congress Cataloging-in-Publication Data to Come Copyright 2019 by the National Academy of Sciences. All rights reserved. Printed in the United States of America. Suggested citation: Matheny, M., S. Thadaney Israni, M. Ahmed, and D. Whicher, Editors. 2019. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. NAM Special Publication. Washington, DC: National Academy of Medicine. PREPUBLICATION COPY - Uncorrected Proofs “Knowing is not enough; we must apply. Willing is not enough; we must do.” --GOETHE PREPUBLICATION COPY - Uncorrected Proofs ABOUT THE NATIONAL ACADEMY OF MEDICINE The National Academy of Medicine is one of three Academies constituting the Nation- al Academies of Sciences, Engineering, and Medicine (the National Academies). The Na- tional Academies provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. -
Programové Vybavení Pro Provoz Nukleární Medicíny Software
ČESKÉ VYSOKÉ UČENÍ TECHNICKÉ V PRAZE FAKULTA BIOMEDICÍNSKÉHO INŽENÝRSTVÍ Katedra biomedicínské techniky Programové vybavení pro provoz nukleární medicíny Software Systems for Nuclear Medicine Diplomová práce Studijní program: Biomedicínská a klinická technika Studijní obor: Systémová integrace procesů ve zdravotnictví Autor diplomové práce: Bc. Jana Švagriková Vedoucí diplomové práce: MUDr. Jan Bruthans, Ph.D. Kladno 2018 PROHLÁŠENÍ Prohlašuji, že jsem diplomovou práci s názvem „Programové vybavení pro provoz nukleární medicíny“ vypracovala samostatně a použila k tomu úplný výčet citací použitých pramenů, které uvádím v seznamu přiloženém k diplomové práci. Nemám závažný důvod proti užití tohoto školního díla ve smyslu § 60 Zákona č. 121/2000 Sb., o právu autorském, o právech souvisejících s právem autorským a o změně některých zákonů (autorský zákon), ve znění pozdějších předpisů. V Kladně 18.05.2018 …...….………...………………... Bc. Jana Švagriková PODĚKOVÁNÍ Na tomto místě bych ráda poděkovala svému vedoucímu diplomové práce panu MUDr. Janu Bruthansovi, Ph.D. za vedení a připomínky k mé práci, jeho rady a konzultace. Dále bych chtěla poděkovat všem osloveným společnostem za jejich informace a poskytnuté materiály. Poděkování patří také všem zúčastněným odborníkům. V neposlední řadě děkuji své rodině a přátelům. ABSTRAKT Diplomová práce s názvem „Programové vybavení pro provoz nukleární medicíny“ se zaměřuje na zhodnocení existujících softwarových produktů, zejména radiologických informačních systémů pro využití v provozu nukleární medicíny. Hlavním cílem bylo zmapování současného aktuálního stavu problematiky s důrazem na Českou republiku. Vybrané systémy byly nejprve popsány pomocí deskriptivní metody. Pomocí analýzy SWOT byly zhodnoceny možnosti jednotlivých systémů. Pro výběr ideální varianty systémů byla zvolena metoda multikriteriálního rozhodování, metoda TOPSIS. Závěrem byl vytvořen návrh na doporučení pro uživatele systémů a celkové zhodnocení formou diskuse. -
High-Confidence Medical Devices: Cyber-Physical Systems for 21St Century Health Care
The NITRD Program The Networking and Information Technology Research and Development (NITRD) Program, one of the few formal interagency R&D activities within the Federal government, comprises the Government’s main unclassified R&D investments in advanced networking, computing, software, and related information technology (IT). The NITRD Program also supports research in the socioeconomic implications of IT and in development of a highly skilled IT workforce. Now in its 18th year, NITRD provides a framework and mechanisms for active coordination among 13 Federal research agencies; many other agencies with IT interests also participate in NITRD activities. NITRD is authorized by Congress through the High-Performance Computing Act of 1991 (Public Law 102-194), the Next Generation Internet Research Act of 1998 (Public Law 105-305), and the America COMPETES Act of 2007 (Public Law 110-69). The NITRD agencies work together in eight major research areas – called Program Component Areas (PCAs). In each PCA, agency program managers participate in an Interagency Working Group (IWG) or Coordinating Group (CG) that coordinates R&D activities and preparation of the annual Supplement to the President’s Budget for the NITRD Program. The PCAs are: High End Computing Infrastructure and Applications (HEC I&A), High End Computing Research and Development (HEC R&D), Cyber Security and Information Assurance (CSIA), Human Computer Interaction and Information Management (HCI&IM), Large Scale Networking (LSN), High Confidence Software and Systems (HCSS), Social, Economic, and Workforce Implications of IT and IT Workforce Development (SEW), and Software Design and Productivity (SDP). High Confidence Software and Systems R&D NITRD’s HCSS PCA supports R&D in scientific foundations and innovative and enabling software and hardware technologies for the design, control, assurance, verification and validation, and certification of complex, networked, distributed computing systems and cyber-physical (IT-enabled) systems such as aircraft and power grids. -
Achieving Safe DICOM Software in Medical Devices
Master Thesis in Software Engineering & Management REPORT NO. 2009:003 ISSN: 1651-4769 Achieving Safe DICOM Software in Medical Devices Kevin Debruyn IT University of Göteborg Chalmers University of Technology and University of Gothenburg Göteborg, Sweden 2009 Student Kevin Debruyn (820717-2795) Contact Information Phone: +46 73 7418420 / Email: [email protected] Course Supervisor Karin Wagner Course Coordinator Kari Wahll Start and End Date 21 st of February 2008 to 30 th of March 2009 Size 30 Credits Subject Achieving Safe DICOM Software in Medical Devices Overview The present document constitutes the project report that introduces, develops and presents the results of the thesis carried out by a master student of the IT University in Göteborg, Software Engineering & Management during Spring 2008 through Spring 2009 at Micropos Medical AB . Summary This paper reports on an investigation on how to produce a reliable software component to extract critical information from DICOM files. The component shall manipulate safety-critical medical information, i.e. patient demographics and data specific to radiotherapy treatments including radiation target volumes and doses intensity. Handling such sensitive data can potentially lead to medical errors, and threaten the health of patients. Hence, guaranteeing reliability and safety is an essential part of the development process. Solutions for developing the component from scratch or reusing all or parts of existing systems and libraries will be evaluated and compared. The resulting component will be tested to verify that it satisfies its reliability requirements. Subsequently, the component is to be integrated within an innovating radiotherapy positioning system developed by a Swedish start-up, Micropos . -
MDCG 2019-11 Guidance on Qualification and Classification of Software in Regulation (EU) 2017/745 – MDR and Regulation (EU) 2017/746 – IVDR
Medical Device Medical Device Coordination Group Document MDCG 2019-11 MDCG 2019-11 Guidance on Qualification and Classification of Software in Regulation (EU) 2017/745 – MDR and Regulation (EU) 2017/746 – IVDR October 2019 This document has been endorsed by the Medical Device Coordination Group (MDCG) established by Article 103 of Regulation (EU) 2017/745. The MDCG is composed of representatives of all Member States and it is chaired by a representative of the European Commission. The document is not a European Commission document and it cannot be regarded as reflecting the official position of the European Commission. Any views expressed in this document are not legally binding and only the Court of Justice of the European Union can give binding interpretations of Union law. Guidance on Qualification and Classification of Software October 2019 Guidance on Qualification and Classification of Software in Regulation (EU) 2017/745 – MDR and Regulation (EU) 2017/746 – IVDR Page 1 of 28 Table of Contents 1. Scope and purpose of this document 3 2. Definitions and abbreviations 3 3. Qualification 6 3.1. Introduction to qualification criteria 6 3.2. Medical Device Software (MDSW) 7 3.3. ‘Software driving or influencing the use of a medical device’ 8 3.4. Qualification criteria of MDSW as an in vitro diagnostic medical device 10 4. Classification of MDSW per MDR 2017/745 12 4.1. Implementing Rules 12 4.2. Classification Rules 12 5. Classification and implementing rules per IVDR 2017/746 15 5.1. Implementing Rules: 15 5.2. Classification Rules: 15 6. Considerations on placing on the market and conformity assessment of MDSW 16 6.1. -
Software & Services
SOFTWARE & SERVICES Recognizing the software and service organizations that excelled in helping providers deliver better patient care PHYSICIAN PRACTICE SOLUTIONS BEST IN KLAS AMBULATORY EMR (1–10 PHYSICIANS) HOW DO VENDOR SOLUTIONS COMPARE? WHO IS KONFIDENCE SCORE TREND LEVEL 1. Cerner PowerChart Ambulatory BEST IN KLAS? 84.3 +13% üü 2. Amazing Charts 83.3 +4% üüü 3. SRSsoft EHR 81.0 -11% üü 4. athenahealth athenaClinicals 80.9 -7% üüü 5. Greenway PrimeSUITE Chart 79.1 -2% üüü HOW DO THEY SCORE? 6. Aprima EHR IN FIVE KEY PERFORMANCE CATEGORIES 78.2 -1% üüü 100 92.4 7. ADP AdvancedMD EHR +3% üüü 90 84.9 78.0 80.6 81.7 81.2 80 8. e-MDs Chart -13% üüü 70 74.0 60 AVG. SEGMENT MKT. 9. GE Healthcare Centricity Practice Solution EMR +1% üü PHYSICIAN PRACTICE PHYSICIAN 50 73.8 40 T10. eClinicalWorks EHR 73.4 -7% üüü 30 20 T10. Henry Schein MicroMD EMR 73.4 +4% üü 10 12. NextGen Healthcare EHR 0 65.1 -3% üüü SALES & FUNCTIONALITY GENERAL CONTRACTING & UPGRADES 13. Allscripts Professional EHR 64.7 -6% üüü SERVICE & IMPLEMENTATION SUPPORT 14. McKesson Practice Partner -14% & TRAINING 48.0 üü 0 10 20 30 40 50 60 70 80 90 100 SEE HOW OTHER VENDOR SOLUTIONS SCORE AT KLASRESEARCH.COM HOW DO THE TOP THREE SOLUTIONS TREND? SOLUTIONS NOT RANKED PRELIMINARY DATA PRODUCTS CompuGroup Medical Enterprise EHR (HEHR)*..................71.0 MIE WebChart EMR* ............................................................75.7 MTBC EMR* .........................................................................82.1 Optum Physician EMR* ........................................................79.6 -
Electronic Medical Records (Certificate) : Electronic Health Records and Security
Electronic Medical Records (certificate) : Electronic Health Records and Security Lesson 1 Overview The first lesson in your textbook begins with an introduction to Electronic Health Record (EHR). This chapter begins with the explanation of an EHR, who is able to document in the EHR, and the owner of the EHR. Further, the chapter discusses the transition from paper records and functions of the electronic software. Lastly, the chapter ends with both the advantages and disadvantages of EHR. 1.1 Describe the current use and contents of the EHR and describe advantages and disadvantages of EHR Assignment 1: Introduction To Electronic Health Records READING ASSIGNMENT Read this assignment. Then read Chapter 1 in your textbook. History of Medical Records A patient’s medical record is a complete physical collection of an individual’s healthcare information. Medical records started as early as 200 BCE in China and have been used throughout history to document communicable diseases. Originally keeping medical Copyright Penn Foster, Inc. 2018 Page 1 Course Version: 1 records weren’t required, but federal laws have been put into place that require all patient care to be documented in a medical record. Paper records are few and far between and most medical records are found within an EHR. Contents of EHR A health record is a combination of all the health information and documents of a single individual. Each time a patient is seen in the clinic or contacts the clinic, it should be documented within the medical record. Keeping accurate and up to date records is essential for quality patient care. -
What Is Medical Coding? What Is Medical Coding? Medical Coding Professionals Provide a Key Step in the Medical Billing Process
Training Certification Continuing Education ICD-10 Jobs Networking Resources Store Log In / Join Certification Overview Medical Coding Certification Medical Billing Certification Medical Auditing Certification Medical Compliance Certification Practice Manager Certification Locate Exam Prepare for Exam Exam Tips Credential Verification FAQ Home > Medical Coding > What is Medical Coding? What is Medical Coding? Medical coding professionals provide a key step in the medical billing process. Every time a patient receives professional health care in a physician’s office, hospital outpatient facility or ambulatory surgical center (ASC), the provider must document the services provided. The medical coder will abstract the information from the documentation, assign the appropriate codes, and create a claim to be paid, whether by a commercial payer, the patient, or CMS. Prepare for certification and a career in medical coding Validate your knowledge, skills, and expertise with medical coding certification Is Medical Coding the same as Medical Billing? No. While the medical coder and medical biller may be the same person or may work closely together to make sure all invoices are paid properly, the medical coder is primarily responsible for abstracting and assigning the appropriate coding on the claims. In order to accomplish this, the coder checks a variety of sources within the patient’s medical record, (i.e. the transcription of the doctor’s notes, ordered laboratory tests, requested imaging studies and other sources) to verify the work that was done. Then the coder must assign CPT® codes, ICD-9 codes and HCPCS codes to both report the procedures that were performed and to provide the medical biller with the information necessary to process a claim for reimbursement by the appropriate insurance agency. -
Electronic Medical Records Software January 2019
ELECTRONIC MEDICAL RECORDS SOFTWARE JANUARY 2019 Powered by Methodology CONTENTS 3 Introduction 5 Defining Electronic Medical Records Software 6 FrontRunners (Small Vendors) 8 FrontRunners (Enterprise Vendors) 10 Runners Up 16 Methodology Basics 2 INTRODUCTION his FrontRunners analysis Enterprise Vendor graphic had a Tis a data-driven assessment minimum qualifying score of 3.51 identifying products in the for Usability and 3.50 for User Electronic Medical Records Recommended, while the Small software market that offer the Vendor graphic had a minimum best capability and value for small qualifying score of 3.21 for Usability businesses. For a given market, and 3.25 for User Recommended. products are evaluated and given a score for Usability (x-axis) and To be considered for the Electronic User Recommended (y-axis). Medical Records FrontRunners, a FrontRunners then plots 10-15 product needed a minimum of 20 products each on a Small Vendor user reviews published within 18 and an Enterprise Vendor graphic, months of the evaluation period. based on vendor business size, per Products needed a minimum user category. rating score of 3.0 for both Usability and User Recommended in both the In the Electronic Medical Records Small and Enterprise graphics. FrontRunners infographic, the 3 INTRODUCTION The minimum score cutoff to be included in the FrontRunners graphic varies by category, depending on the range of scores in each category. No product with a score less than 3.0 in either dimension is included in any FrontRunners graphic. For products included, the Usability and User Recommended scores determine their positions on the FrontRunners graphic. -
Towards a Radiology Patient Portal Corey W Arnold,1 Mary Mcnamara,1 Suzie El-Saden,2 Shawn Chen,1 Ricky K Taira,1 Alex a T Bui1
Research and applications Imaging informatics for consumer health: towards a radiology patient portal Corey W Arnold,1 Mary McNamara,1 Suzie El-Saden,2 Shawn Chen,1 Ricky K Taira,1 Alex A T Bui1 1Medical Imaging Informatics, ABSTRACT look up health information online verified it with Department of Radiological Objective With the increased routine use of advanced their physicians.7 Sciences, University of fi California–Los Angeles, imaging in clinical diagnosis and treatment, it has Several bene ts of tailored information within Los Angeles, California, USA become imperative to provide patients with a means to patient portal applications have been demon- – 2Department of Imaging view and understand their imaging studies. We illustrate strated,8 10 including equipping patients with Services, Greater Los Angeles, the feasibility of a patient portal that automatically vetted, higher quality information regarding their VA Medical Center, Los structures and integrates radiology reports with disease or condition; and facilitating access to their Angeles, California, USA corresponding imaging studies according to several underlying medical records. However, little work Correspondence to information orientations tailored for the layperson. has been done to make the full range of radiology Dr Corey W Arnold, Medical Methods The imaging patient portal is composed of content—imaging and text—available to patients in Imaging Informatics, an image processing module for the creation of a an understandable format. This lack is in spite of Department of Radiological Sciences, University of timeline that illustrates the progression of disease, a the fact that radiology reports and images consti- California–Los Angeles, 924 natural language processing module to extract salient tute a significant amount of the evidence used in Westwood Blvd Ste 420, Los concepts from radiology reports (73% accuracy, F1 score diagnosis and treatment assessment. -
Kareo User Manual
Kareo User Manual Table Of Contents 1. GET STARTED ............................................................................................................................................................................................. 1 1.1 Installation ................................................................................................................................................................................... 1 1.1.1 System Requirements .........................................................................................................................................................................1 1.1.2 Download and Install Kareo ............................................................................................................................................................. 2 1.1.3 Software Updates ............................................................................................................................................................................... 2 1.2 User Login .................................................................................................................................................................................... 3 1.2.1 Kareo Login with User ID/Password ............................................................................................................................................... 3 1.2.2 Password Change ............................................................................................................................................................................... -
Top 20 Ehr Software
TOP 20 EHR SOFTWARE C M CONVERTED MEDIA TOP 20 EHR SOFTWARE 1 AdvancedMD AdvancedEHR 11 Allscripts Allscripts Professional EHR 2 Cerner Cerner Ambulatory EHR 12 CareCloud CareCloud Charts 3 athenahealth athenahealth EHR 13 CureMD All in One EHR 4 Epic Epic EHR 14 Practice Velocity VelociDoc EHR Azalea Health 5 Practice Fusion Practice Fusion EHR 15 Azalea EHR Innovations 6 Kareo Kareo Clinical 16 ReLi Med Solutions ReLiMed EMR 7 Henry Schein MicroMD EMR 17 MedEZ MedEZ 8 drchrono drchrono EHR 18 iSALUS Healthcare OfficeEMR 9 NextGen Healthcare NextGen Healthcare EHR 19 ChartLogic ChartLogic EMR Modernizing 10 EMA 20 ICANotes ICANotes EHR Medicine C M CONVERTED MEDIA EHR IN PRACTICE HOW THESE RANKINGS WERE GENERATED This ranking was determined using a number of factors including industry standing, public opinion of software, social media presence, and available software features relevant to the needs of a small business. This ranking should serve as a rough estimate of software suitability, and more in-depth analysis can be taken below or by using our EHR software comparison. C M CONVERTED MEDIA SHORTLISTING EHR VENDORS CHECKLIST Research EHR employed by similar sized practices in 1 6 Produce an RFI document and send to vendor shortlist the same specialty Identify market leading solutions which offer some 2 7 Narrow shortlist based on RFI responses support in your specialty Leverage professional network for recommendations Compile requirements and business processes in an 3 8 based on their experience RFP document Narrow shortlist based