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Ha NT, Harris M, Bulsara M, Doust J, Kamarova S, McRobbie D, O'Leary P, Parizel PM, Slavotinek J, Wright C, Youens D, Moorin R. Patterns of computed tomography utilisation in injury management: latent classes approach using linked administrative data in Western Australia. Eur J Trauma Emerg Surg 2023; 49:2413-2427. [PMID: 37318517 PMCID: PMC10728237 DOI: 10.1007/s00068-023-02303-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 06/03/2023] [Indexed: 06/16/2023]
Abstract
PURPOSE Whilst computed tomography (CT) imaging has been a vital component of injury management, its increasing use has raised concern regarding ionising radiation exposure. This study aims to identify latent classes (underlying patterns) of CT use over a 3-year period following the incidence of injury and factors predicting the observed patterns. METHOD A retrospective observational cohort study was conducted in 21,544 individuals aged 18 + years presenting to emergency departments (ED) of four tertiary public hospitals with new injury in Western Australia. Mixture modelling approach was used to identify latent classes of CT use over a 3-year period post injury. RESULTS Amongst injured people with at least one CT scan, three latent classes of CT use were identified including a: temporarily high CT use (46.4%); consistently high CT use (2.6%); and low CT use class (51.1%). Being 65 + years or older, having 3 + comorbidities, history with 3 + hospitalisations and history of CT use before injury were associated with consistently high use of CT. Injury to the head, neck, thorax or abdomen, being admitted to hospital after the injury and arriving to ED by ambulance were predictors for the temporarily high use class. Living in areas of higher socio-economic disadvantage was a unique factor associated with the low CT use class. CONCLUSIONS Instead of assuming a single pattern of CT use for all patients with injury, the advanced latent class modelling approach has provided more nuanced understanding of the underlying patterns of CT use that may be useful for developing targeted interventions.
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Affiliation(s)
- Ninh T Ha
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
| | - Mark Harris
- School of Accounting, Economics and Finance, Faculty of Business and Law, Curtin University, Perth, Western Australia, Australia
| | - Max Bulsara
- Institute for Health Research, University of Notre Dame, Fremantle, WA, Australia
- Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Crawley, Australia
| | - Jenny Doust
- Australian Women and Girls' Health Research Centre, School of Public Health, University of Queensland, Brisbane, Australia
| | - Sviatlana Kamarova
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia
- School of Health Sciences, University of Sydney, Camperdown, New South Wales, Australia
- Nepean Blue Mountains Local Health District, Kingswood, New South Wales, Australia
| | - Donald McRobbie
- School of Physical Sciences, University of Adelaide, Adelaide, Australia
| | - Peter O'Leary
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia
- Obstetrics and Gynaecology Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia
- PathWest Laboratory Medicine, QE2 Medical Centre, Nedlands, WA, Australia
| | - Paul M Parizel
- Medical School, University of Western Australia, Perth, WA, Australia
- Department of Radiology, Royal Perth Hospital, Victoria Square, Perth, WA, 6000, Australia
| | - John Slavotinek
- SA Medical Imaging, SA Health and College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Cameron Wright
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia
- Fiona Stanley Hospital, 11 Robin Warren Dr, Murdoch, WA, Australia
- Division of Internal Medicine, Medical School, Faculty of Health and Medical Sciences, University of Western, Perth, Australia
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia
| | - David Youens
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia
- Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Crawley, Australia
| | - Rachael Moorin
- Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia
- Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Crawley, Australia
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Stolz D, Mkorombindo T, Schumann DM, Agusti A, Ash SY, Bafadhel M, Bai C, Chalmers JD, Criner GJ, Dharmage SC, Franssen FME, Frey U, Han M, Hansel NN, Hawkins NM, Kalhan R, Konigshoff M, Ko FW, Parekh TM, Powell P, Rutten-van Mölken M, Simpson J, Sin DD, Song Y, Suki B, Troosters T, Washko GR, Welte T, Dransfield MT. Towards the elimination of chronic obstructive pulmonary disease: a Lancet Commission. Lancet 2022; 400:921-972. [PMID: 36075255 PMCID: PMC11260396 DOI: 10.1016/s0140-6736(22)01273-9] [Citation(s) in RCA: 202] [Impact Index Per Article: 101.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 05/23/2022] [Accepted: 06/28/2022] [Indexed: 10/14/2022]
Abstract
Despite substantial progress in reducing the global impact of many non-communicable diseases, including heart disease and cancer, morbidity and mortality due to chronic respiratory disease continues to increase. This increase is driven primarily by the growing burden of chronic obstructive pulmonary disease (COPD), and has occurred despite the identification of cigarette smoking as the major risk factor for the disease more than 50 years ago. Many factors have contributed to what must now be considered a public health emergency: failure to limit the sale and consumption of tobacco products, unchecked exposure to environmental pollutants across the life course, and the ageing of the global population (partly as a result of improved outcomes for other conditions). Additionally, despite the heterogeneity of COPD, diagnostic approaches have not changed in decades and rely almost exclusively on post-bronchodilator spirometry, which is insensitive for early pathological changes, underused, often misinterpreted, and not predictive of symptoms. Furthermore, guidelines recommend only simplistic disease classification strategies, resulting in the same therapeutic approach for patients with widely differing conditions that are almost certainly driven by variable pathophysiological mechanisms. And, compared with other diseases with similar or less morbidity and mortality, the investment of financial and intellectual resources from both the public and private sector to advance understanding of COPD, reduce exposure to known risks, and develop new therapeutics has been woefully inadequate.
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Affiliation(s)
- Daiana Stolz
- Clinic of Respiratory Medicine and Pulmonary Cell Research, University Hospital Basel, Basel, Switzerland; Department of Clinical Research, University Hospital Basel, Basel, Switzerland; Clinic of Respiratory Medicine and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Takudzwa Mkorombindo
- Lung Health Center, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Desiree M Schumann
- Clinic of Respiratory Medicine and Pulmonary Cell Research, University Hospital Basel, Basel, Switzerland
| | - Alvar Agusti
- Respiratory Institute-Hospital Clinic, University of Barcelona IDIBAPS, CIBERES, Barcelona, Spain
| | - Samuel Y Ash
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mona Bafadhel
- School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK; Department of Respiratory Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chunxue Bai
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - James D Chalmers
- Scottish Centre for Respiratory Research, University of Dundee, Dundee, UK
| | - Gerard J Criner
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
| | - Shyamali C Dharmage
- Centre for Epidemiology and Biostatistics, School of Population and Global health, University of Melbourne, Melbourne, VIC, Australia
| | - Frits M E Franssen
- Department of Research and Education, CIRO, Horn, Netherlands; Department of Respiratory Medicine, Maastricht University Medical Centre, Maastricht, Netherlands
| | - Urs Frey
- University Children's Hospital Basel, Basel, Switzerland
| | - MeiLan Han
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Nadia N Hansel
- Pulmonary and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathaniel M Hawkins
- Centre for Cardiovascular Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Ravi Kalhan
- Department of Preventive Medicine and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Melanie Konigshoff
- Division of Pulmonary, Allergy and Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fanny W Ko
- The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Trisha M Parekh
- Lung Health Center, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Maureen Rutten-van Mölken
- Erasmus School of Health Policy & Management and Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Jodie Simpson
- Priority Research Centre for Healthy Lungs, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia
| | - Don D Sin
- Centre for Heart Lung Innovation and Division of Respiratory Medicine, Department of Medicine, University of British Columbia, St Paul's Hospital, Vancouver, BC, Canada
| | - Yuanlin Song
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; Shanghai Respiratory Research Institute, Shanghai, China; Jinshan Hospital of Fudan University, Shanghai, China
| | - Bela Suki
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Thierry Troosters
- Department of Rehabilitation Sciences, Research Group for Rehabilitation in Internal Disorders, KU Leuven, Leuven, Belgium
| | - George R Washko
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tobias Welte
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany; Biomedical Research in Endstage and Obstructive Lung Disease, German Center for Lung Research, Hannover, Germany
| | - Mark T Dransfield
- Lung Health Center, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA; Birmingham VA Medical Center, Birmingham, AL, USA.
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Vest JR, Unruh MA, Casalino LP, Shapiro JS. The complementary nature of query-based and directed health information exchange in primary care practice. J Am Med Inform Assoc 2021; 27:73-80. [PMID: 31592529 DOI: 10.1093/jamia/ocz134] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 05/27/2019] [Accepted: 07/07/2019] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE Many policymakers and advocates assume that directed and query-based health information exchange (HIE) work together to meet organizations' interoperability needs, but this is not grounded in a substantial evidence base. This study sought to clarify the relationship between the usage of these 2 approaches to HIE. MATERIALS AND METHODS System user log files from a regional HIE organization and electronic health record system were combined to model the usage of HIE associated with a patient visit at 3 federally qualified health centers in New York. Regression models tested the hypothesis that directed HIE usage was associated with query-based usage and adjusted for factors reflective of the FITT (Fit between Individuals, Task & Technology) framework. Follow-up interviews with 8 key informants helped interpret findings. RESULTS Usage of query-based HIE occurred in 3.1% of encounters and directed HIE in 23.5%. Query-based usage was 0.6 percentage points higher when directed HIE provided imaging information, and 4.8 percentage points higher when directed HIE provided clinical documents. The probability of query-based HIE was lower for specialist visits, higher for postdischarge visits, and higher for encounters with nurse practitioners. Informants used query-based HIE after directed HIE to obtain additional information, support transitions of care, or in cases of abnormal results. DISCUSSION The complementary nature of directed and query-based HIE indicates that both HIE functionalities should be incorporated into EHR Certification Criteria. CONCLUSIONS Quantitative and qualitative findings suggest that directed and query-based HIE exist in a complementary manner in ambulatory care settings.
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Affiliation(s)
- Joshua R Vest
- Indiana University Richard M Fairbanks School of Public Health at IUPUI, Department of Health Policy & Management; Center for Biomedical Informatics, the Regenstrief Institute, Inc, Indianapolis, IN
| | - Mark A Unruh
- Department of Healthcare Policy and Research, Weill Medical College, New York, NY, USA
| | - Lawrence P Casalino
- Department of Healthcare Policy and Research, Weill Medical College, New York, NY, USA
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Wakefield BJ, Turvey C, Hogan T, Shimada S, Nazi K, Cao L, Stroupe K, Martinez R, Smith B. Impact of Patient Portal Use on Duplicate Laboratory Tests in Diabetes Management. Telemed J E Health 2020; 26:1211-1220. [PMID: 32045320 DOI: 10.1089/tmj.2019.0237] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Background: Patients seek care across multiple health care settings. One coordination issue is the unnecessary duplication of laboratory across different health care settings. This analysis examined the association between patient portal use and duplication of laboratory testing among Veterans who are dual users of Veterans Affairs (VA) and non-VA providers. Materials and Methods: A national sample of Veterans who were newly authenticated users of the portal during fiscal year (FY) 2013 who used Blue Button at least once were compared with a random sample of Veterans who were not registered to use the portal. From these two groups, Veterans who were also Medicare-eligible users in FY2014 were identified. Duplicate testing was defined as receipt of more than five HbA1c (hemoglobin A1c) in 1 year. Results: Use of the Blue Button decreased the odds of duplicate HbA1c testing in VA and Medicare-covered facilities across three comparisons: (1) overall between users and nonusers: portal users were less likely to have duplicate testing; (2) pre-post comparison: there was a trend toward lower duplicate testing in both groups across time; and (3) pre-post comparisons accounting for use of the portal: the trend toward lower duplicate testing was greater in Blue Button users. Conclusion: Duplicate HbA1c testing was significantly lower in dual users of VA and Medicare services who used the Blue Button feature of their VA patient portal. Non-VA providers encounter barriers to access of complete information about Veterans who also use VA health care. Provider endorsement of consumer-mediated health information exchange could help further this model of sharing information.
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Affiliation(s)
- Bonnie J Wakefield
- Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Healthcare System, Iowa City, Iowa, USA.,Sinclair School of Nursing, University of Missouri, Columbia, Missouri, USA
| | - Carolyn Turvey
- Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Healthcare System, Iowa City, Iowa, USA.,Rural Health Resource Center, Iowa City Veterans Affairs Healthcare System, Iowa City, Iowa, USA.,Department of Psychiatry College of Medicine, University of Iowa, Iowa City, Iowa, USA
| | - Timothy Hogan
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts, USA.,Division of Health Informatics and Implementation Science, Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Stephanie Shimada
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts, USA.,Division of Health Informatics and Implementation Science, Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Kim Nazi
- Independent Consultant, Albany, New York, USA
| | - Lishan Cao
- Center of Innovation for Complex Chronic Healthcare, Hines VA Hospital, Hines, Illinois, USA
| | - Kevin Stroupe
- Center of Innovation for Complex Chronic Healthcare, Hines VA Hospital, Hines, Illinois, USA.,Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA
| | - Rachael Martinez
- Center of Innovation for Complex Chronic Healthcare, Hines VA Hospital, Hines, Illinois, USA
| | - Bridget Smith
- Center of Innovation for Complex Chronic Healthcare, Hines VA Hospital, Hines, Illinois, USA.,Center for Healthcare Studies, Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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5
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Peng P, Beitia AO, Vreeman DJ, Loo GT, Delman BN, Thum F, Lowry T, Shapiro JS. Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation. J Am Med Inform Assoc 2019; 26:19-27. [PMID: 30445562 DOI: 10.1093/jamia/ocy135] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 09/22/2018] [Indexed: 11/12/2022] Open
Abstract
Objective We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology. Methods Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions. Results LOINC's content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001). Conclusion LOINC's content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.
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Affiliation(s)
- Paul Peng
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Anton Oscar Beitia
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Daniel J Vreeman
- Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - George T Loo
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bradley N Delman
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Frederick Thum
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Tina Lowry
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jason S Shapiro
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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6
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Vreeman DJ, Abhyankar S, Wang KC, Carr C, Collins B, Rubin DL, Langlotz CP. The LOINC RSNA radiology playbook - a unified terminology for radiology procedures. J Am Med Inform Assoc 2019; 25:885-893. [PMID: 29850823 PMCID: PMC6016707 DOI: 10.1093/jamia/ocy053] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 05/01/2018] [Indexed: 11/30/2022] Open
Abstract
Objective This paper describes the unified LOINC/RSNA Radiology Playbook and the process by which it was produced. Methods The Regenstrief Institute and the Radiological Society of North America (RSNA) developed a unification plan consisting of six objectives 1) develop a unified model for radiology procedure names that represents the attributes with an extensible set of values, 2) transform existing LOINC procedure codes into the unified model representation, 3) create a mapping between all the attribute values used in the unified model as coded in LOINC (ie, LOINC Parts) and their equivalent concepts in RadLex, 4) create a mapping between the existing procedure codes in the RadLex Core Playbook and the corresponding codes in LOINC, 5) develop a single integrated governance process for managing the unified terminology, and 6) publicly distribute the terminology artifacts. Results We developed a unified model and instantiated it in a new LOINC release artifact that contains the LOINC codes and display name (ie LONG_COMMON_NAME) for each procedure, mappings between LOINC and the RSNA Playbook at the procedure code level, and connections between procedure terms and their attribute values that are expressed as LOINC Parts and RadLex IDs. We transformed all the existing LOINC content into the new model and publicly distributed it in standard releases. The organizations have also developed a joint governance process for ongoing maintenance of the terminology. Conclusions The LOINC/RSNA Radiology Playbook provides a universal terminology standard for radiology orders and results.
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Affiliation(s)
- Daniel J Vreeman
- Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Swapna Abhyankar
- Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA
| | - Kenneth C Wang
- Imaging Service, VA Maryland Health Care System, Baltimore, Maryland, USA.,Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Christopher Carr
- Informatics Department, Radiological Society of North America, Oak Brook, Illinois, USA
| | - Beverly Collins
- Department of Radiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Daniel L Rubin
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA and.,Department of Radiology, Stanford University, Stanford, California, USA
| | - Curtis P Langlotz
- Department of Radiology, Stanford University, Stanford, California, USA
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7
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Wang KC. Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging. J Digit Imaging 2019; 31:353-360. [PMID: 29725962 PMCID: PMC5959830 DOI: 10.1007/s10278-018-0069-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
Abstract
Standard clinical terms, codes, and ontologies promote clarity and interoperability. Within radiology, there is a variety of relevant content resources, tools and technologies. These provide the basis for fundamental imaging workflows such as reporting and billing, and also facilitate a range of applications in quality improvement and research. This article reviews the key characteristics of lexicons, coding systems, and ontologies. A number of standards are described, including International Classification of Diseases-10-Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and RadLex. Tools for accessing this material are reviewed, such as the National Center for Biomedical Ontology BioPortal system. Web services are discussed as a mechanism for semantic application development. Several example systems, workflows, and research applications using semantic technology are also surveyed.
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Affiliation(s)
- Kenneth C Wang
- Baltimore VA Medical Center, 10 N. Greene St., Room C1-24, Baltimore, MD, 21201, USA. .,Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA.
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8
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Vest JR, Ben-Assuli O. Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information. Int J Med Inform 2019; 129:205-210. [PMID: 31445257 DOI: 10.1016/j.ijmedinf.2019.06.013] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/17/2019] [Accepted: 06/17/2019] [Indexed: 10/26/2022]
Abstract
INTRODUCTION Interoperable health information technologies, like electronic health records (EHR) and health information exchange (HIE), provide greater access to patient information from across multiple organizations. Also, an increasing number of public data sources exist to describe social determinant of health factors. These data may help better inform risk prediction models, but the relative importance or value of these data has not been established. This study assessed the performance of different classes of information individually, and in combination, in predicting emergency department (ED) revisits. METHODS In a sample of 279,611 adult ED encounters. We compared the performance of Two-Class Boosted Decision Trees machine learning algorithm using 5 classes of information: 1) social determinants of health measures only, 2) current visit EHR information only, 3) current and historical EHR information, 4) HIE information only, and 5) all available information combined. RESULTS The social determinants of health measure only model had the overall worst performance with an area under the curve AUC of 0.61. The model using all information classes together had the best performance (AUC = 0.732). The model using HIE information only performed better than all other single information class models. CONCLUSIONS Broad information sources, which are reflective of patients' reliance on multiple organizations for care, better support risk prediction modeling in the emergency department.
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Affiliation(s)
- Joshua R Vest
- Indiana University, Richard M. Fairbanks School of Public Health, Indianapolis, IN, United States; Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
| | - Ofir Ben-Assuli
- Ono Academic College, Faculty of Business Administration, Kiryat Ono, Israel.
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9
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Vest JR, Simon K. Hospitals' adoption of intra-system information exchange is negatively associated with inter-system information exchange. J Am Med Inform Assoc 2018; 25:1189-1196. [PMID: 29860502 DOI: 10.1093/jamia/ocy058] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 05/22/2018] [Indexed: 11/13/2022] Open
Abstract
Introduction U.S. policy on interoperable HIT has focused on increasing inter-system (ie, between different organizations) health information exchange. However, interoperable HIT also supports the movement of information within the same organization (ie, intra-system exchange). Methods We examined the relationship between hospitals' intra- and inter-system information exchange capabilities among health system hospitals included in the 2010-2014 American Hospital Association's Annual Health Information Technology Survey. We described the factors associated with hospitals that adopted more intra-system than inter-system exchange capability, and explored the extent of new capability adoption among hospitals that reported neither intra- or inter-system information capabilities at baseline. Results The prevalence of exchange increased over time, but the adoption of inter-system information exchange was slower; when hospitals adopt information exchange, adoption of intra-system exchange was more common. On average during our study period, hospitals could share 4.6 types of information by intra-system exchange, but only 2.7 types of information by inter-system exchange. Controlling for other factors, hospitals exchanged more types of information in an intra-system manner than inter-system when the number of different inpatient EHR vendors in use in health system is larger. Conclusion Consistent with the U.S. goals for more widely accessible patient information, hospitals' ability to share information has increased over time. However, hospitals are prioritizing within-organizational information exchange over exchange between different organizations. If increasing inter-system exchanges is a desired goal, current market incentives and government policies may be insufficient to overcome hospitals' motivations for pursuing an intra-system-information-exchange-first strategy.
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Affiliation(s)
- Joshua R Vest
- Indiana University Richard M. Fairbanks School of Public Health, Department of Health Policy & Management, Indianapolis, Indiana, USA.,Regenstrief Institute, Indianapolis, Indiana, USA
| | - Kosali Simon
- Indiana University School of Public & Environmental Affairs
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10
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Beitia AO, Lowry T, Vreeman DJ, Loo GT, Delman BN, Thum FL, Slovis BH, Shapiro JS. Standard Anatomic Terminologies: Comparison for Use in a Health Information Exchange-Based Prior Computed Tomography (CT) Alerting System. JMIR Med Inform 2017; 5:e49. [PMID: 29242174 PMCID: PMC5746622 DOI: 10.2196/medinform.8765] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 10/04/2017] [Accepted: 10/05/2017] [Indexed: 12/31/2022] Open
Abstract
Background A health information exchange (HIE)–based prior computed tomography (CT) alerting system may reduce avoidable CT imaging by notifying ordering clinicians of prior relevant studies when a study is ordered. For maximal effectiveness, a system would alert not only for prior same CTs (exams mapped to the same code from an exam name terminology) but also for similar CTs (exams mapped to different exam name terminology codes but in the same anatomic region) and anatomically proximate CTs (exams in adjacent anatomic regions). Notification of previous same studies across an HIE requires mapping of local site CT codes to a standard terminology for exam names (such as Logical Observation Identifiers Names and Codes [LOINC]) to show that two studies with different local codes and descriptions are equivalent. Notifying of prior similar or proximate CTs requires an additional mapping of exam codes to anatomic regions, ideally coded by an anatomic terminology. Several anatomic terminologies exist, but no prior studies have evaluated how well they would support an alerting use case. Objective The aim of this study was to evaluate the fitness of five existing standard anatomic terminologies to support similar or proximate alerts of an HIE-based prior CT alerting system. Methods We compared five standard anatomic terminologies (Foundational Model of Anatomy, Systematized Nomenclature of Medicine Clinical Terms, RadLex, LOINC, and LOINC/Radiological Society of North America [RSNA] Radiology Playbook) to an anatomic framework created specifically for our use case (Simple ANatomic Ontology for Proximity or Similarity [SANOPS]), to determine whether the existing terminologies could support our use case without modification. On the basis of an assessment of optimal terminology features for our purpose, we developed an ordinal anatomic terminology utility classification. We mapped samples of 100 random and the 100 most frequent LOINC CT codes to anatomic regions in each terminology, assigned utility classes for each mapping, and statistically compared each terminology’s utility class rankings. We also constructed seven hypothetical alerting scenarios to illustrate the terminologies’ differences. Results Both RadLex and the LOINC/RSNA Radiology Playbook anatomic terminologies ranked significantly better (P<.001) than the other standard terminologies for the 100 most frequent CTs, but no terminology ranked significantly better than any other for 100 random CTs. Hypothetical scenarios illustrated instances where no standard terminology would support appropriate proximate or similar alerts, without modification. Conclusions LOINC/RSNA Radiology Playbook and RadLex’s anatomic terminologies appear well suited to support proximate or similar alerts for commonly ordered CTs, but for less commonly ordered tests, modification of the existing terminologies with concepts and relations from SANOPS would likely be required. Our findings suggest SANOPS may serve as a framework for enhancing anatomic terminologies in support of other similar use cases.
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Affiliation(s)
- Anton Oscar Beitia
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Tina Lowry
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel J Vreeman
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.,Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - George T Loo
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Bradley N Delman
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Frederick L Thum
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Benjamin H Slovis
- Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA, United States
| | - Jason S Shapiro
- Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Tung M, Sharma R, Hinson JS, Nothelle S, Pannikottu J, Segal JB. Factors associated with imaging overuse in the emergency department: A systematic review. Am J Emerg Med 2017; 36:301-309. [PMID: 29100783 DOI: 10.1016/j.ajem.2017.10.049] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Revised: 10/17/2017] [Accepted: 10/18/2017] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND Emergency departments (ED) are sites of prevalent imaging overuse; however, determinants that drive imaging in this setting are not well-characterized. We systematically reviewed the literature to summarize the determinants of imaging overuse in the ED. METHODS We searched MEDLINE® and Embase® from January 1998 to March 2017. Studies were included if they were written in English, contained original data, pertained to a U.S. population, and identified a determinant associated with overuse of imaging in the ED. RESULTS Twenty relevant studies were included. Fourteen evaluated computerized tomography (CT) scanning in patents presenting to a regional ED who were then transferred to a level 1 trauma center; incomplete transfer of data and poor image quality were the most frequently described reasons for repeat scanning. Unnecessary pre-transfer scanning or repeated scanning after transfer, in multiple studies, was highest among older patients, those with higher Injury Severity Scores (ISS) and those being transferred further. Six studies explored determinants of overused imaging in the ED in varied conditions, with overuse greater in older patients and those having more comorbid diseases. Defensive imaging reportedly influenced physician behavior. Less integration of services across the health system also predisposed to overuse of imaging. CONCLUSIONS The literature is heterogeneous with surprisingly few studies of determinants of imaging in minor head injury or of spine imaging. Older patient age and higher ISS were the most consistently associated with ED imaging overuse. This review highlights the need for precise definitions of overuse of imaging in the ED.
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Affiliation(s)
- Monica Tung
- Johns Hopkins University School of Medicine, Department of Medicine, United States
| | - Ritu Sharma
- Johns Hopkins University Bloomberg School of Public Health, United States
| | - Jeremiah S Hinson
- Johns Hopkins University School of Medicine, Department of Emergency Medicine, United States
| | - Stephanie Nothelle
- Johns Hopkins University School of Medicine, Department of Medicine, United States
| | - Jean Pannikottu
- Johns Hopkins University School of Medicine, Department of Medicine, United States; Northeastern Ohio Medical University, United States(1)
| | - Jodi B Segal
- Johns Hopkins University School of Medicine, Department of Medicine, United States; Johns Hopkins University Bloomberg School of Public Health, United States; Johns Hopkins University Center for Health Services and Outcomes Research, United States.
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