Semantic Indexing of Patient Cases in a Boundary Infostructure for ehealth
|
|
- Henry Brett Stone
- 6 years ago
- Views:
Transcription
1 Semantic Indexing of Patient Cases in a Boundary Infostructure for ehealth Grace I. Paterson 1, MSc, Paul Fabry 2, MD, Andrew M. Grant 2, MB, PhD, Tuyet T. Thieu 1, BCS, Steven D. Soroka 3, MD, MSc, Hassan Diab 2, Andriy M. Moshyk 2, MD, MClinSci 1 Medical Informatics, Faculty of Medicine, Dalhousie University 5849 University Avenue, Halifax, Nova Scotia, Canada, B3H 4H7 grace.paterson@dal.ca 2 Centre for Research and Evaluation in Diagnostics, Centre hospitalier universitaire de Sherbrooke, Sherbrooke, Québec, Canada 3 Department of Medicine (Nephrology), Dalhousie University, Halifax, Nova Scotia, Canada Keywords: electronic health record, semantic indexing, chronic disease, nosology, clinical pragmatics Abstract This research explores semantic indexing using a boundary infostructure. The cases are about patients diagnosed with kidney disease secondary to hypertension or diabetes mellitus stored in electronic health records (EHR) from different jurisdictions, Quebec and Nova Scotia. The semantic foundation for case indexing is a three-layer ontology composed of subjects, structure and context. The subjects are the organizing principle for concepts chosen for completeness analysis. The completeness method uses semantic connections between concepts to focus its search for clinical pragmatic patterns in EHR instances. The concepts are the controlled vocabulary that can be represented with a unique concept identifier in UMLS with automated and manual mappings to nosology systems, SNOMED CT and ICD (versions 9, 9- CM and 10-CA). The structure is the information architecture and its expression in semantic classes, nosology systems, lexicons and HL7. The context is document-based communication and record-keeping skills. The semantic indexing of cases is based on a constrained set of subject terms drawn from clinical pragmatic patterns. The semantic indexing is stored in the Document Class, an HL7 Infrastructure class for Structured Documents. It supports retrieval of cases according to clinical pragmatic patterns that are embedded in the Chronic Kidney Disease Discharge Summary template for HL7 Clinical Document Architecture (CDA). The semantic indexing of patient cases is useful for bridging the gap between jurisdictions and leads to improvements in an HL7 Template functioning as a boundary object in the infostructure. 1. Introduction Clinical documentation is confounded by the way organizations store patient information in medical records. For patients diagnosed with a chronic condition, the clinical documentation tracks markers of disease progression. An infostructure may bridge the semantic gap caused by different ways of capturing clinical data in records, especially one composed of boundary objects. Boundary objects are pragmatic constructions that do the job required of them. They are implementations of medical language and information architecture standards used in electronic health records (EHR). Clinical pragmatic patterns are sense-making because they organize information in ways which correspond to how healthcare professionals expect them and in ways that facilitate their daily work [1]. They are assertions stated in actual discourse, such as discharge summaries and case writeups. The challenge is to retrieve Quebec cases that exhibit the clinical pragmatic patterns embedded in an HL7 Template designed for the Chronic Kidney Disease Discharge Summary for Nova Scotian cases. Both groups collect data differently making it difficult to determine if they mean the same thing. A boundary infostructure is pragmatically focused on finding a solution to how clinicians communicate meaning in documents. The boundary objects chosen for the infostructure are clinical terminology systems
2 (SNOMED CT, ICD-9, ICD-10-CA, UMLS) and a health information standard, HL7 CDA. Clinical terminology is defined as standardized terms and their synonyms which record patient findings, circumstances, events, and interventions with sufficient detail to support clinical care, decision support, outcomes research, and quality improvement; and can be efficiently mapped to broader classifications for administrative, regulatory, oversight and fiscal requirements [2]. The clinical pragmatics problem is a specialization of the terminology problem. 2. Methods Our cases are from the Centre Informatisé de Recherche Évaluative en Santé et Systèmes de Soins (CIRESSS), Université de Sherbrooke, Quebec (N=1006 visits by 762 patients); and from the Capital District Health Authority (CDHA), Halifax, Nova Scotia (N=2 visits by 1 patient). All patients have a diagnosis of chronic kidney disease (CKD) secondary to hypertension and/or diabetes mellitus. Each patient s information is transformed into a longitudinal EHR based on the HL7 CDA Release 2.0 standard and the CCD (Continuity of Care Document) specification. We manually mapped French terms in CIRESSS data to UMLS concept identifiers using bilingual personnel and UMLS Knowledge Sources. The patient data was loaded into an SQL database and rendered in English using our PatientRx style sheet. A subset of cases (N=17 visits for 5 patients in CIRESSS, 1 visit for 1 patient in CDHA) are filtered through the HL7 Template for Chronic Kidney Disease Discharge Summary to reduce the information to pertinent data for clinical communication [3]. These cases are put into a Clinical Document Repository. The semantic index for a patient case is stored in an HL7 Reference Information Model (RIM) Infrastructure class for structured documents.. The attribute, Document.bibliographicDesignationText, is defined as the citation for a cataloged document that permits its identification, location and/or retrieval from common collections [4]. While it is extremely unlikely that any two narrative references about the same patient will be strictly similar, it should be possible to produce a finite set of pattern expressions using boundary objects as mediators. A clinical pragmatic pattern can be described in language data, which Pratt defines as the data that the medical professional reduces or aggregates by logical inference and deduction to provide for the care of a patient or to communicate a medical concept to a student or colleague [5]. There is a strong association between the Problem-Based Learning (PBL) paradigm of medical education and the computational reasoning paradigm of Case-Based Reasoning (CBR) [6]. CBR cases provide medical students with an opportunity to learn how experts conceptualize knowledge in terms of constructs and also to leverage on experiential knowledge accumulated in the EHR which is then translated into a CBR case [2]. The process of transforming from EHR to CBR can serve as feedback to the student on their record-keeping practices and their ability to communicate clinically relevant information. The same process provides feedback to health informaticians on the infostructure s ability to support reuse from EHRs. A semantic index for a patient case is a tool for bridging between EHR and CBR representations of clinical data. A semantic foundation is required for case indexing to help ensure there is a single semantic interpretation for a statement. We created the semantic foundation for indexing using a 3-layer ontology model. The three-layer ontology is composed of subjects, structure and context. The subjects are the organizing principle for the clinical pragmatic patterns and are synthesized from facetted sources of information in the structure layer and expressed in XML for Topic Maps (XTM). The concepts are the controlled vocabulary that can be represented with a unique concept identifier in UMLS Version 2006AA with mappings to SNOMED CT and ICD (versions 9 and 10-CA). The structure is the information architecture and its expression in semantic classes, nosology systems, lexicons and health information standards. The relationship between subjects and structure supports semantic indexing of the examples in the Clinical Document Repository. The context is the use of subjects and structures to express a clinical pragmatic pattern in the production of an EHR or the production of an index for a CBR case.
3 Table 1 gives the clinical pragmatics citation from the literature and the associated EHR observations from the HL7 Template for Chronic Kidney Disease Discharge Summary [2] and CIRESSS Data Dictionary. The Topic Map for the controlled vocabulary serves as the semantic glue for integrating the subjects with their context of use. Table 1 Subjects Associated with a Clinical Pragmatic Pattern Object (HL7 Template) Object (CIRESSS) Pattern Subject Patient: BirthTime ECLE_ZZ_AGE DU_PT Abnormal GFR glomerular Patient: SEXE filtration rates are Stage of AdministrativeGenderCode used to classify the Chronic stages of chronic NOM_DE_LA_REQUETE= Kidney Créatinine sérique and kidney disease [7, Disease TITRE_CHAMP=Créatinine umol/l page 1553] Observation: serum creatinine umol/l with Method=Clinical Chemistry Observation: Ferritin ug/l with Method=Ferritin Measurement Observation: % Saturation with Method=Transferrin Saturation Observation: HGB g/l with Method=Complete Blood Count Observation: iron deficiency anaemia code D50* with Method=ICD- 10-CA Observation: Total Protein mg/l with Method=urine specimen collection, 24 hours Observation: Creatinine mmol/l with Method=urine specimen collection, 24 hours Observation: Proteinuria with Interpretation=stage Observation: Blood Pressure with Method=Vital Signs SubstanceAdministration: drug from Cardiovascular drug hierarchy NOM_DE_LA_REQUETE= Ferritine and TITRE_CHAMP= Ferritine NOM_DE_LA_REQUETE= Capacité de fixation du fer and TITRE_CHAMP= Saturation en fer NOM_DE_LA_REQUETE=FSC and TITRE_CHAMP=Hb g/l ECLE_ME_CIM9 DIAGNOSTIC3= NOM_DE_LA_REQUETE= Analyse d'urine macro/microscopie and TITRE_CHAMP=Pro NOM_DE_LA_REQUETE= Electrophorèse des protéines urinaires and TITRE_CHAMP= Albumine Drug data not in dataset Laboratory investigations for comorbidities and some reversible causes of chronic kidney disease: Ferritin, iron saturation (if patient is anemic) iron supplementation results in the return of iron stores and the elevation of hemoglobin concentration [7, pages ] a five or six point scale for proteinuria (from no proteinuria to full nephrotic syndrome) would be useful [8, page 914]. Treat Blood Pressure to Target (130/80 for low levels of protein excretion and less than 125/75 in those with high levels of protein excretion); ACEi or ARB; need 3-4 medications [9] Anemic Iron store category Iron supply category Stage of Proteinuria Hypertension Treatment Target Blood Pressure
4 3. Results The Document.BibliographicDesignationText entry for each case is constructed from a constrained set of subject terms. There are 18 entries in the Clinical Document Repository. Table 2 displays the semantic indexing using the subject terms from Table 1. In seven cases, the CIRESSS element, TITRE_CHAMP =Créatinine, was unavailable for calculating the GFR and CKD stage. Proteinuria is determined by three methods: 24-hour urine collection for protein and creatinine clearance, random urine test for albumin:creatinine ratio (mg/mmol) and albumin level by a dipstick [7]. The stages of proteinuria are negative, trace, 1+, 2+, 3+ and nephrotic syndrome [8]. When the method is 24-hour urine collection for protein, the stage 1+ corresponds to about mg/24 hours, a 2+ to gm/24 hours, a 3+ to 2-5 gm/24 hours and a 4+ represents 7 gm/24 hours or greater [10]. There were no cases where we could calculate the albumin:creatinine ratio and the albumin level by a dipstick was not recorded in lab results. Table 2 Semantic Case Indexing by Subject Case GFR CKD Stage Anemic (ICD_Dx, Ferritin, % Sat, Hgb) Proteinuria Q <ICD-9=285.9> <Hgb normal low> Q <Hgb low> Q <ICD-9=285.8,285.9> <Hgb low> 3+ Q <Hgb normal> Q <Ferritin normal> <Hgb low normal> Q <% saturation low> <Hbg normal> Q <Hgb low normal> Q <Ferritin high> <Hgb low> Q <Ferritin high> <% saturation low> <Hgb low> 3+ Q <Ferritin normal> <% saturation low> <Hgb low> Q <Ferritin high> <Hgb low> negative Q <% saturation low> <Hgb normal> 3+ Q <ICD-9=285.9> <ferritin normal high> <%saturation normal> <Hgb low> Q <Hgb normal low> Q <Hgb low> Q <ICD-9=285.9> <% saturation high> <Hgb low> Q < abnormal> <Hgb low> NS <ICD-10-CA=D50.9> <Ferritin normal> <% saturation low> <Hgb low> 3+ Different subjects were recruited to prepare a discharge summary for Case NS Their communication of the subject, Hypertension Treatment, showed variation in the Course in Hospital narration. An example narration is: Hypertension: the blood pressure was elevated during the admission in the range of systolic, diastolic so hytrin 2 mg and cardiazem SR 180 mg BID was added. The norvasc was discontinued. He continues with acebutolol 200 mg BID. One of the drug names was incorrectly spelled in the narration. The Medications portion of the HL7 Template for Chronic Kidney Disease Discharge Summary addresses the lexical variants issue through linkage to the Nova Scotia Drug Formulary. The semantic indexing enhances the narration by associating the different medications with their drug class. The source of the association between the brand name and generic name is the online Nova Scotia Drug Formulary. SNOMED CT is the source of the association between generic name and drug class. In the clinical pragmatics in Table 1, ARB refers to alpha-adrenergic blocking agent and ACEi to angiotensinconverting enzyme inhibitor agent. Hytrin has-generic-name terazosin, which is-a alpha 1 adrenergic blocking agent
5 Cardizem SR has-generic-name diltiazem, which is-a calcium channel blocking agent Norvasc has-generic-name amlodipine, which is-a calcium channel blocking agent Acebutolol is-a beta 1 blocking agent The HL7 Template gives the user a practical way to classify and communicate the kidney health status. The MDRD calculation for GFR does not need the patient s weight, just the age, sex and serum creatinine. The K/DOQI staging for Chronic Kidney Disease is a gold standard that has been adopted for use by Canadian clinicians [7]. Different versions of the International Classification of Disease (ICD) are used for coded attributes, and different languages, French and English, are used for field descriptions and free text. There are two version of ICD-9: the original ICD-9 which was published in 1975, and ICD-9-CM (Clinical Modification) which was published in 1986 by the National Center for Health Statistics (NCHS) and includes new categories compared to the original version. Both versions are available for download from the Center for Disease Control website [11]. A discrepancy between the two versions is due to the new category "diabetes with hyperosmolarity" added in ICD-9-CM. Table 3 Differences in ICD9 and ICD-9-CM Versions for Diabetes Mellitus Coding Code ICD-9 ICD-9-CM Number Diabetes mellitus without mention of complication Diabetes mellitus without mention of complication Diabetes with ketoacidosis Diabetes with ketoacidosis Diabetes with other coma Diabetes with hyperosmolarity Diabetes with renal manifestations Diabetes with other coma Diabetes with ophthalmic manifestations Diabetes with renal manifestations Diabetes with neurological manifestations Diabetes with ophthalmic manifestations Diabetes with peripheral circulatory disorders Diabetes with neurological manifestations Diabetes with other specified manifestations Diabetes with peripheral circulatory disorders Diabetes with other specified manifestations Diabetes with unspecified complication Diabetes with unspecified complication 4. Discussion The boundary infostructure recognizes the ontological knowledge that currently exists in widely accepted boundary objects drawn from clinical terminology systems (SNOMED, ICD, UMLS) and the HL7 health information standard. It creates a bridge between the different versions of ICD and makes visible maintenance issues arising from version changes. There is such a proliferation of information captured in hospital records in CIRESSS that it is pragmatic to filter the information for case indexing. The first filter, from CIRESSS to CCD, achieved a transformation from French to English and structured the information into HL7 classes. The second filter, from CCD to the HL7 Template for Chronic Kidney Disease Discharge Summary, reduced the information to clinically relevant data captured at different time intervals admission, course in hospital, discharge. There was a need to attend to unit differences, for example, the expression of Total Protein was mg/l in Nova Scotia and g/l in Quebec. The semantic indexing of cases was achieved based on clinical pragmatic patterns found in literature. The process of seeking clinical pragmatic patterns in another dataset helps us improve the HL7 Template design. The template captures data that is meaningful for chronic disease management. Medical educators teach about the markers of disease progression, such as the urinary albumin:creatinine ratio for staging proteinuria, and health informaticians need to ensure the data can be captured in an EHR. The boundary infostructure shows promise as a tool for learning at the boundary between different jurisdictions and
6 different communities of practice (clinicians, health informaticians, administrators, medical educators and patients). Acknowledgements We acknowledge scholarship funding from the Canadian Institutes of Health Research (CIHR) PhD/Postdoctoral Strategic Training Program in Health Informatics. References 1. A.L. Rector. Clinical Terminology: Why is it So Hard? Methods Inf.Med Dec; 38(4-5): C.G. Chute, et al. Clinical Classification and Terminology: Some History and Current Observations Journal of the American Medical Informatics Association 2000; 7: G.I. Paterson, S.S.R. Abidi, S.D. Soroka. HealthInfoCDA: Case Composition Using Electronic Health Record Data Sources Stud Health Technol Inform. 2005;116: G. Beeler, et al.. HL7 Reference Information Model. Version: V Available at: 5. A.W. Pratt. Medicine, Computers, and Linguistics. Advances in Biomedical Engineering. 1973;3: H. Eshach, H. Bitterman. From case-based reasoning to problem-based learning. Acad Med. 1994;69(12): C. Stigant, L. Stevens, A. Levin. Nephrology: 4. Strategies for the Care of Adults with Chronic Kidney Disease. Can. Med. Assoc. J. 2003; 168: Available at 8. C.M. Clase, A.X. Gary, B.A. Kiberd. Classifying kidney problems: can we avoid framing risks as diseases? BMJ 2004;329; S.D. Soroka. Diabetes and Kidney Disease. DCPNS Round Table. June 25, The Internet Pathology Laboratory for Medical Education, Florida State University College of Medicine. Available at Center for Disease Control website: ftp://ftp.cdc.gov/pub/health_statistics/nchs/publications/
Development of a Case Index for a Clinical Document Repository for Chronic Kidney Disease Management
Development of a Case Index for a Clinical Document Repository for Chronic Kidney Disease Management By Performed at Medical Informatics, Dalhousie University 5849 University Avenue Halifax, NS B3H 4H7
More informationElevation of Serum Creatinine: When to Screen, When to Refer. Bruce F. Culleton, MD, FRCPC; and Jolanta Karpinski, MD, FRCPC
Elevation of Serum Creatinine: When to Screen, When to Refer Bruce F. Culleton, MD, FRCPC; and Jolanta Karpinski, MD, FRCPC Presented at the University of Calgary s CME and Professional Development 2006-2007
More informationSemantic Alignment between ICD-11 and SNOMED-CT. By Marcie Wright RHIA, CHDA, CCS
Semantic Alignment between ICD-11 and SNOMED-CT By Marcie Wright RHIA, CHDA, CCS World Health Organization (WHO) owns and publishes the International Classification of Diseases (ICD) WHO was entrusted
More informationQUICK REFERENCE FOR HEALTHCARE PROVIDERS
KEY MESSAGES 1 SCREENING CRITERIA Screen: Patients with DM and/or hypertension at least yearly. Consider screening patients with: Age >65 years old Family history of stage 5 CKD or hereditary kidney disease
More informationThe openehr approach. Background. Approach. Heather Leslie, July 17, 2014
Heather Leslie, July 17, 2014 The openehr approach Background The open source openehr 1 architecture specifications 2 have evolved as the result of over 20 years of research and international implementations,
More informationChronic Kidney Disease: Optimal and Coordinated Management
Chronic Kidney Disease: Optimal and Coordinated Management Michael Copland, MD, FRCPC Presented at University of British Columbia s 42nd Annual Post Graduate Review in Family Medicine Conference, Vancouver,
More informationDifficult to Treat Hypertension
Difficult to Treat Hypertension According to Goldilocks JNC 8 Blood Pressure Goals (2014) BP Goal 60 years old and greater*- systolic < 150 and diastolic < 90. (Grade A)** BP Goal 18-59 years old* diastolic
More informationSitagliptin (Januvia)
Texas Prior Authorization Program Clinical Edit Criteria Drug/Drug Class Clinical Edit Information Included in this Document 25mg Drugs requiring prior authorization: the list of drugs requiring prior
More informationSNOMED CT and Orphanet working together
SNOMED CT and Orphanet working together Ian Green Business Services Executive, IHTSDO Dr. Romina Armando INSERM Session outline What is Orphanet? Rare disorders Orphanet nomenclature Mappings to other
More informationThe CARI Guidelines Caring for Australians with Renal Impairment. Specific effects of calcium channel blockers in diabetic nephropathy GUIDELINES
Specific effects of calcium channel blockers in diabetic nephropathy Date written: September 2004 Final submission: September 2005 Author: Kathy Nicholls GUIDELINES a. Non-dihydropyridine calcium channel
More informationAn Ontology-Based Electronic Medical Record for Chronic Disease Management
An Ontology-Based Electronic Medical Record for Chronic Disease Management Ashraf Mohammed Iqbal, Michael Shepherd and Syed Sibte Raza Abidi Faculty of Computer Science Dalhousie University Halifax, NS,
More informationReducing proteinuria
Date written: May 2005 Final submission: October 2005 Author: Adrian Gillin Reducing proteinuria GUIDELINES a. The beneficial effect of treatment regimens that include angiotensinconverting enzyme inhibitors
More informationAn Ontology for Healthcare Quality Indicators: Challenges for Semantic Interoperability
414 Digital Healthcare Empowering Europeans R. Cornet et al. (Eds.) 2015 European Federation for Medical Informatics (EFMI). This article is published online with Open Access by IOS Press and distributed
More informationIrish Practice Nurses Association Annual Conference Tullamore Court Hotel OCTOBER 6 th 2012
Irish Practice Nurses Association Annual Conference Tullamore Court Hotel OCTOBER 6 th 2012 Susan McKenna Renal Clinical Nurse Specialist Cavan General Hospital Renal patient population ACUTE RENAL FAILURE
More informationClinical Study Synopsis
Clinical Study Synopsis This file is posted on the Bayer HealthCare Clinical Trials Registry and Results website or on the website www.clinicalstudyresults.org hosted by the Pharmaceutical Research and
More informationAnalytical Methods: the Kidney Early Evaluation Program (KEEP) The Kidney Early Evaluation program (KEEP) is a free, community based health
Analytical Methods: the Kidney Early Evaluation Program (KEEP) 2000 2006 Database Design and Study Participants The Kidney Early Evaluation program (KEEP) is a free, community based health screening program
More informationCKDinform: A PCP s Guide to CKD Detection and Delaying Progression
CKDinform: A PCP s Guide to CKD Detection and Delaying Progression Learning Objectives Describe suitable screening tools, such as GFR and ACR, for proper utilization in clinical practice related to the
More informationChapter 1: CKD in the General Population
Chapter 1: CKD in the General Population Overall prevalence of CKD (Stages 1-5) in the U.S. adult general population was 14.8% in 2011-2014. CKD Stage 3 is the most prevalent (NHANES: Figure 1.2 and Table
More informationA Study on a Comparison of Diagnostic Domain between SNOMED CT and Korea Standard Terminology of Medicine. Mijung Kim 1* Abstract
, pp.49-60 http://dx.doi.org/10.14257/ijdta.2016.9.11.05 A Study on a Comparison of Diagnostic Domain between SNOMED CT and Korea Standard Terminology of Medicine Mijung Kim 1* 1 Dept. Of Health Administration,
More informationRebooting Cancer Data Through Structured Data Capture GEMMA LEE NAACCR CONFERENCE JUNE, 2017
Rebooting Cancer Data Through Structured Data Capture GEMMA LEE NAACCR CONFERENCE JUNE, 2017 Acknowledgement Richard Moldwin, MD, PhD, CAP Sandy Jones, CDC Wendy Blumenthal, CDC David Kwan, Cancer Care
More informationFaculty/Presenter Disclosure
CSI for CKD Unravelling the myths surrounding chronic kidney disease Practical Evidence for Informed Practice Oct 21 2016 Dr. Scott Klarenbach University of Alberta Slide 1: Option B (Presenter with NO
More informationRenal Protection Staying on Target
Update Staying on Target James Barton, MD, FRCPC As presented at the University of Saskatchewan's Management of Diabetes & Its Complications (May 2004) Gwen s case Gwen, 49, asks you to take on her primary
More informationInformation Technology-Driven Analytics: The Link Between Data Aggregation, Analytics and EHRs. Ronald A. Paulus, MD President and CEO June 27, 2011
Information Technology-Driven Analytics: The Link Between Data Aggregation, Analytics and EHRs Ronald A. Paulus, MD President and CEO June 27, 2011 1 Summary Analytics and EHRs are co-dependent and complementary
More informationProfessor Suetonia Palmer
Professor Suetonia Palmer Department of Medicine Nephrologist Christchurch Hospital Christchurch 14:00-14:55 WS #108: The Kidney Test - When To Test and When to Refer ( and When Not To) 15:05-16:00 WS
More informationEffect of (OHDSI) Vocabulary Mapping on Phenotype Cohorts
Effect of (OHDSI) Vocabulary Mapping on Phenotype Cohorts Matthew Levine, Research Associate George Hripcsak, Professor Department of Biomedical Informatics, Columbia University Intro Reasons to map: International
More informationWELSH INFORMATION STANDARDS BOARD
WELSH INFORMATION STANDARDS BOARD DSC Notice: DSCN 2018 / 06 Date of Issue: 8 th August 2018 Welsh Health Circular / Official Letter: (2015) 053 Subject: CT Maturity Matrix Sponsor: Chris Newbrook, Head
More informationDiabetes in Renal Patients. Contents. Understanding Diabetic Nephropathy
Diabetes in Renal Patients Contents Understanding Diabetic Nephropathy What effect does CKD have on a patient s diabetic control? Diabetic Drugs in CKD and Dialysis Patients Hyper and Hypoglycaemia in
More informationChronic Kidney Disease (CKD) and egfr: Decision and Dilemma. Dr Bhavna K Pandya Consultant Nephrologist University Hospital Aintree
Chronic Kidney Disease (CKD) and egfr: Decision and Dilemma Dr Bhavna K Pandya Consultant Nephrologist University Hospital Aintree Topics CKD background egfr background Patient with egfr Referral Guidelines
More informationLab Values Explained. working at full strength. Other possible causes of an elevated BUN include dehydration and heart failure.
Patient Education Lab Values Explained Common Tests to Help Diagnose Kidney Disease Lab work, urine samples and other tests may be given as you undergo diagnosis and treatment for renal failure. The test
More informationThe Diabetes Kidney Disease Connection Missouri Foundation for Health February 26, 2009
The Diabetes Kidney Disease Connection Missouri Foundation for Health February 26, 2009 Teresa Northcutt, RN BSN Primaris Program Manager, Prevention - CKD MO-09-01-CKD This material was prepared by Primaris,
More informationInformation Technology-Driven Analytics: The Link Between Data Aggregation, Analytics and EHRs. Ronald A. Paulus, MD President and CEO June 27, 2011
Information Technology-Driven Analytics: The Link Between Data Aggregation, Analytics and EHRs Ronald A. Paulus, MD President and CEO June 27, 2011 1 Summary Analytics and EHRs are co-dependent and complementary
More informationThe new ERA-EDTA PRDs UK Renal SNOMED CT subset TheProject
The new ERA-EDTA PRDs UK Renal SNOMED CT subset TheProject Keith Simpson UKRR Advisor keith.simpson@nhs.net Thanks to ERA-EDTA Registry: Kitty Jager Managing Dir and members of the Coding and Terminology
More informationIndividual Study Table Referring to Part of Dossier: Volume: Page:
Synopsis Abbott Laboratories Name of Study Drug: Paricalcitol Capsules (ABT-358) (Zemplar ) Name of Active Ingredient: Paricalcitol Individual Study Table Referring to Part of Dossier: Volume: Page: (For
More informationLaboratory Engagement Plan
Laboratory Engagement Plan Transforming Kidney Disease Detection February 2018 National Kidney Foundation Laboratory Engagement Advisory Group GAP ANALYSIS Thirty million American adults are estimated
More information2017 Intelligent Medical Objects, Inc. All rights reserved. IMO and INTELLIGENT MEDICAL OBJECTS are registered trademarks of Intelligent Medical
1 SNOMED CT Expo 2017 Data Normalization, Groupers and Other Transformations as Actionable Solutions for the Healthcare Ecosystem Regis Charlot and Eric Rose, M.D. Intelligent Medical Objects, Inc. October
More informationBuilding a Diseases Symptoms Ontology for Medical Diagnosis: An Integrative Approach
Building a Diseases Symptoms Ontology for Medical Diagnosis: An Integrative Approach Osama Mohammed, Rachid Benlamri and Simon Fong* Department of Software Engineering, Lakehead University, Ontario, Canada
More informationThe CARI Guidelines Caring for Australasians with Renal Impairment. Blood Pressure Control role of specific antihypertensives
Blood Pressure Control role of specific antihypertensives Date written: May 2005 Final submission: October 2005 Author: Adrian Gillian GUIDELINES a. Regimens that include angiotensin-converting enzyme
More informationQuality of Care in Early Stage Chronic Kidney Disease
Quality of Care in Early Stage Chronic Kidney Disease 2012 2013 Supplementary Report to the 2015 Alberta Annual Kidney Care Report Kidney Health Strategic Clinical Network December 22, 2015 For more information
More informationHow to code rare diseases with international terminologies?
How to code rare diseases with international terminologies? Ana Rath Inserm US14, Paris, France ana.rath@inserm.fr Special thanks to Prof Paul Landais for his kind presentation. Needs for terminologies
More informationA Simple Pipeline Application for Identifying and Negating SNOMED CT in Free Text
A Simple Pipeline Application for Identifying and Negating SNOMED CT in Free Text Anthony Nguyen 1, Michael Lawley 1, David Hansen 1, Shoni Colquist 2 1 The Australian e-health Research Centre, CSIRO ICT
More informationAutomatic generation of MedDRA terms groupings using an ontology
Automatic generation of MedDRA terms groupings using an ontology Gunnar DECLERCK a,1, Cédric BOUSQUET a,b and Marie-Christine JAULENT a a INSERM, UMRS 872 EQ20, Université Paris Descartes, France. b Department
More informationSummary of Recommendation Statements Kidney International Supplements (2013) 3, 5 14; doi: /kisup
http://www.kidney-international.org & 2013 DIGO Summary of Recommendation Statements idney International Supplements (2013) 3, 5 14; doi:10.1038/kisup.2012.77 Chapter 1: Definition and classification of
More informationChronic kidney disease (CKD) has received
Participant Follow-up in the Kidney Early Evaluation Program (KEEP) After Initial Detection Allan J. Collins, MD, FACP, 1,2 Suying Li, PhD, 1 Shu-Cheng Chen, MS, 1 and Joseph A. Vassalotti, MD 3,4 Background:
More informationDiabetes and Hypertension
Diabetes and Hypertension M.Nakhjvani,M.D Tehran University of Medical Sciences 20-8-96 Hypertension Common DM comorbidity Prevalence depends on diabetes type, age, BMI, ethnicity Major risk factor for
More informationChapter 2: Identification and Care of Patients With CKD
Chapter 2: Identification and Care of Patients With CKD Over half of patients in the Medicare 5% sample (aged 65 and older) had at least one of three diagnosed chronic conditions chronic kidney disease
More informationORC: an Ontology Reasoning Component for Diabetes
ORC: an Ontology Reasoning Component for Diabetes Özgür Kafalı 1, Michal Sindlar 2, Tom van der Weide 2 and Kostas Stathis 1 1 Department of Computer Science Royal Holloway, University of London, UK {ozgur.kafali,kostas.stathis}@rhul.ac.uk
More informationThe hypertensive kidney and its Management
The hypertensive kidney and its Management Dr H0 Chung Ping Hypertension Management Seminar 20061124 Hypertensive kidney Kidney damage asymptomatic till late stage Viscous cycle to augment renal damage
More informationChapter 2: Identification and Care of Patients with CKD
Chapter 2: Identification and Care of Patients with CKD Over half of patients in the Medicare 5% sample (aged 65 and older) had at least one of three diagnosed chronic conditions chronic kidney disease
More informationFDA Workshop NLP to Extract Information from Clinical Text
FDA Workshop NLP to Extract Information from Clinical Text Murthy Devarakonda, Ph.D. Distinguished Research Staff Member PI for Watson Patient Records Analytics Project IBM Research mdev@us.ibm.com *This
More information5.2 Key priorities for implementation
5.2 Key priorities for implementation From the full set of recommendations, the GDG selected ten key priorities for implementation. The criteria used for selecting these recommendations are listed in detail
More informationSAGE. Nick Beard Vice President, IDX Systems Corp.
SAGE Nick Beard Vice President, IDX Systems Corp. Sharable Active Guideline Environment An R&D consortium to develop the technology infrastructure to enable computable clinical guidelines, that will be
More informationStages of Chronic Kidney Disease (CKD)
Early Treatment is the Key Stages of Chronic Kidney Disease (CKD) Stage Description GFR (ml/min/1.73 m 2 ) >90 1 Kidney damage with normal or GFR 2 Mild decrease in GFR 60-89 3 Moderate decrease in GFR
More informationToward a Diagnosis Driven (Dental) Profession through Controlled Terminology
Toward a Diagnosis Driven (Dental) Profession through Controlled Terminology James J. Cimino, MD Director, Informatics Institute University of Alabama at Birmingham Birmingham, Alabama, USA Los Angeles,
More informationMetabolic Syndrome and Chronic Kidney Disease
Metabolic Syndrome and Chronic Kidney Disease Definition of Metabolic Syndrome National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III Abdominal obesity, defined as a waist circumference
More informationText mining for lung cancer cases over large patient admission data. David Martinez, Lawrence Cavedon, Zaf Alam, Christopher Bain, Karin Verspoor
Text mining for lung cancer cases over large patient admission data David Martinez, Lawrence Cavedon, Zaf Alam, Christopher Bain, Karin Verspoor Opportunities for Biomedical Informatics Increasing roll-out
More informationKOS Design for Healthcare Decision-making Based on Consumer Criteria and User Stories
Taxonomy Strategies October 13, 2016 Copyright 2015 Taxonomy Strategies LLC. All rights reserved. KOS Design for Healthcare Decision-making Based on Consumer Criteria and User Stories Joseph A. Busch,
More informationInvestigating implementing CEN with HL7 V3 and SNOMED CT Final Report
Investigating implementing CEN 13606 with HL7 V3 and SNOMED CT Programme NPFIT Document Record ID Key Sub-Prog / Project Technology Office Prog. Director P. Jones Status
More informationPhysiotherapists in Canada, 2011 National and Jurisdictional Highlights
pic pic pic Physiotherapists in Canada, 2011 National and Jurisdictional Highlights Spending and Health Workforce Our Vision Better data. Better decisions. Healthier Canadians. Our Mandate To lead the
More information2019 COLLECTION TYPE: MIPS CLINICAL QUALITY MEASURES (CQMS) MEASURE TYPE: Process
Quality ID #119 (NQF 0062): Diabetes: Medical Attention for Nephropathy National Quality Strategy Domain: Effective Clinical Care Meaningful Measure Area: Management of Chronic Conditions 2019 COLLECTION
More informationA Lexical-Ontological Resource forconsumerheathcare
A Lexical-Ontological Resource forconsumerheathcare Elena Cardillo FBK-IRST, Via Sommarive 18, 38123 Trento, Italy cardillo@fbk.eu Abstract. In Consumer Healthcare Informatics it is still difficult for
More informationPrimary Care Approach to Management of CKD
Primary Care Approach to Management of CKD This PowerPoint was developed through a collaboration between the National Kidney Foundation and ASCP. Copyright 2018 National Kidney Foundation and ASCP Low
More informationOutpatient Management of Chronic Kidney Disease for the Internist
Outpatient Management of Chronic Kidney Disease for the Internist Annual Meeting of Maryland Chapter of the American College of Physicians February 3, 2018 MARY (TESSIE) BEHRENS, MD, FACP, FASN, FNKF MID-ATLANTIC
More informationCreatinine & egfr A Clinical Perspective. Suheir Assady MD, PhD Dept. of Nephrology & Hypertension RHCC
Creatinine & egfr A Clinical Perspective Suheir Assady MD, PhD Dept. of Nephrology & Hypertension RHCC CLINICAL CONDITIONS WHERE ASSESSMENT OF GFR IS IMPORTANT Stevens et al. J Am Soc Nephrol 20: 2305
More informationCHRONIC KIDNEY DISEASE WHY WOMEN MAY BE AT RISK?
CHRONIC KIDNEY DISEASE WHY WOMEN MAY BE AT RISK? Dr. Judy A Geissler, DNP, APNP, FNP-BC, CNN Vascular Access Advanced Practice Provider Employer- Medical College of Wisconsin No financial disclosures Barbara
More informationIdentifying and Managing Chronic Kidney Disease: A Practical Approach
Identifying and Managing Chronic Kidney Disease: A Practical Approach S. Neil Finkle, MD, FRCPC Associate Professor Division of Nephrology, Department of Medicine, Dalhousie University Program Director,
More informationThe National Quality Standards for Chronic Kidney Disease
The National Quality Standards for Chronic Kidney Disease Dr Robert Lewis Chief of Service, Wessex Kidney Centre, Portsmouth Specialist Committee Member Quality Standard for Chronic Kidney Disease, NICE
More informationUNIVERSITY OF CALGARY. diabetes mellitus. Vinay Deved A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
UNIVERSITY OF CALGARY Quality of care and outcomes for First Nations People and non-first Nations People with diabetes mellitus by Vinay Deved A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL
More informationCLINICIAN-LED E-HEALTH RECORDS. (AKA GETTING THE LITTLE DATA RIGHT) Dr Heather Leslie Ocean Informatics/openEHR Foundation
CLINICIAN-LED E-HEALTH RECORDS (AKA GETTING THE LITTLE DATA RIGHT) Dr Heather Leslie Ocean Informatics/openEHR Foundation An ongoing issue In attempting to arrive at the truth, I have applied everywhere
More informationANEMIA & HEMODIALYSIS
ANEMIA & HEMODIALYSIS The anemia of CKD is, in most patients, normocytic and normochromic, and is due primarily to reduced production of erythropoietin by the kidney and to shortened red cell survival.
More informationRare Diseases Nomenclature and classification
Rare Diseases Nomenclature and classification Annie Olry ORPHANET - Inserm US14, Paris, France annie.olry@inserm.fr Using standards and embedding good practices to promote interoperable data sharing in
More informationOutline. Outline CHRONIC KIDNEY DISEASE UPDATE: WHAT THE GENERALIST NEEDS TO KNOW 7/23/2013. Question 1: Which of these patients has CKD?
CHRONIC KIDNEY DISEASE UPDATE: WHAT THE GENERALIST NEEDS TO KNOW MICHAEL G. SHLIPAK, MD, MPH CHIEF-GENERAL INTERNAL MEDICINE, SAN FRANCISCO VA MEDICAL CENTER PROFESSOR OF MEDICINE, EPIDEMIOLOGY AND BIOSTATISTICS,
More informationChapter 2: Identification and Care of Patients With Chronic Kidney Disease
Chapter 2: Identification and Care of Patients With Chronic Kidney Disease Introduction The examination of care in patients with chronic kidney disease (CKD) is a significant challenge, as most large datasets
More informationMeasure Owner Designation. AMA-PCPI is the measure owner. NCQA is the measure owner. QIP/CMS is the measure owner. AMA-NCQA is the measure owner
2011 EHR Measure Specifications The specifications listed in this document have been updated to reflect clinical practice guidelines and applicable health informatics standards that are the most current
More informationBoise State University Foundational Studies Program Course Application Form
Boise State University Foundational Studies Program Course Application Form Due to the Foundational Studies Program by August 19, 2011 After the Foundational Studies Program has approved a course, departments
More informationRedwood Mednet Connecting California to Improve Patient Care 2012 Conference. Michael Stearns, MD, CPC, CFPC HIT Consultant
Redwood Mednet Connecting California to Improve Patient Care 2012 Conference Michael Stearns, MD, CPC, CFPC HIT Consultant Why is it Important to Codify Clinical Data? Common dilemma associated with trying
More informationFigure 1 LVH: Allowed Cost by Claim Volume (Data generated from a Populytics analysis).
Chronic Kidney Disease (CKD): The New Silent Killer Nelson Kopyt D.O. Chief of Nephrology, LVH Valley Kidney Specialists For the past several decades, the health care needs of Americans have shifted from
More informationEfficacy and tolerability of oral Sucrosomial Iron in CKD patients with anemia. Ioannis Griveas, MD, PhD
Efficacy and tolerability of oral Sucrosomial Iron in CKD patients with anemia Ioannis Griveas, MD, PhD Anaemia is a state in which the quality and/or quantity of circulating red blood cells are below
More informationSupplementary Appendix
Supplementary Appendix This appendix has been provided by the authors to give readers additional information about their work. Supplement to: Wanner C, Inzucchi SE, Lachin JM, et al. Empagliflozin and
More informationS150 KEEP Analytical Methods. American Journal of Kidney Diseases, Vol 55, No 3, Suppl 2, 2010:pp S150-S153
S150 KEEP 2009 Analytical Methods American Journal of Kidney Diseases, Vol 55, No 3, Suppl 2, 2010:pp S150-S153 S151 The Kidney Early Evaluation program (KEEP) is a free, communitybased health screening
More informationClinical Pearls in Renal Medicine
Clinical Pearls in Renal Medicine Joel A. Gordon MD Professor of Medicine Nephrology Division Staff Physician Kidney Disease and Blood Pressure Clinic Disclosures None of my financial holdings will have
More informationClinical decision support (CDS) and Arden Syntax
Clinical decision support (CDS) and Arden Syntax Educational material, part 1 Medexter Healthcare Borschkegasse 7/5 A-1090 Vienna www.medexter.com www.meduniwien.ac.at/kpa (academic) Better care, patient
More informationBiomedical resources for text mining
August 30, 2005 Workshop Terminologies and ontologies in biomedicine: Can text mining help? Biomedical resources for text mining Olivier Bodenreider Lister Hill National Center for Biomedical Communications
More informationHYPERTENSION GUIDELINES WHERE ARE WE IN 2014
HYPERTENSION GUIDELINES WHERE ARE WE IN 2014 Donald J. DiPette MD FACP Special Assistant to the Provost for Health Affairs Distinguished Health Sciences Professor University of South Carolina University
More informationA n aly tical m e t h o d s
a A n aly tical m e t h o d s If I didn t go to the screening at Farmers Market I would not have known about my kidney problems. I am grateful to the whole staff. They were very professional. Thank you.
More informationCase-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials
Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials Riccardo Miotto and Chunhua Weng Department of Biomedical Informatics Columbia University,
More informationDiabetic Nephropathy. Objectives:
There are, in truth, no specialties in medicine, since to know fully many of the most important diseases a man must be familiar with their manifestations in many organs. William Osler 1894. Objectives:
More informationClassification of CKD by Diagnosis
Classification of CKD by Diagnosis Diabetic Kidney Disease Glomerular diseases (autoimmune diseases, systemic infections, drugs, neoplasia) Vascular diseases (renal artery disease, hypertension, microangiopathy)
More informationNational Chronic Kidney Disease Audit
National Chronic Kidney Disease Audit // National Report: Part 2 December 2017 Commissioned by: Delivered by: // Foreword by Fiona Loud And if, as part of good, patient-centred care, a record of your condition(s),
More informationClinical terms and ICD 11
Clinical terms and ICD 11 Family of Classifications Robert Jakob, WHO Detail of health information -> Classification Reality (individual detail) Free Text (medical information) Terminologies / ICD-11 URI
More informationSupplementary Online Content
Supplementary Online Content Tangri N, Stevens LA, Griffith J, et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA. 2011;305(15):1553-1559. eequation. Applying the
More informationReview of C-CDA R1.1 Allergy and Intolerance templates
Review of C-CDA R1.1 Allergy and Intolerance templates Lisa R. Nelson March 26, 2014 This work is copyrighted by Janie Appleseed and made available under the terms of the Creative Commons Attribution-NonCommercial-No
More informationCharacteristics of factor x so that its clearance = GFR. Such factors that meet these criteria. Renal Tests. Renal Tests
Renal Tests Holly Kramer MD MPH Associate Professor of Public Health Sciences and Medicine Division of Nephrology and Hypertension Loyola University of Chicago Stritch School of Medicine Renal Tests 1.
More informationHeiner Oberkampf. DISSERTATION for the degree of Doctor of Natural Sciences (Dr. rer. nat.)
INTEGRATED REPRESENTATION OF CLINICAL DATA AND MEDICAL KNOWLEDGE AN ONTOLOGY-BASED APPROACH FOR THE RADIOLOGY DOMAIN Heiner Oberkampf DISSERTATION for the degree of Doctor of Natural Sciences (Dr. rer.
More informationManagement of Hypertension. M Misra MD MRCP (UK) Division of Nephrology University of Missouri School of Medicine
Management of Hypertension M Misra MD MRCP (UK) Division of Nephrology University of Missouri School of Medicine Disturbing Trends in Hypertension HTN awareness, treatment and control rates are decreasing
More informationCombining Archetypes with Fast Health Interoperability Resources in Future-proof Health Information Systems
180 Digital Healthcare Empowering Europeans R. Cornet et al. (Eds.) 2015 European Federation for Medical Informatics (EFMI). This article is published online with Open Access by IOS Press and distributed
More informationLong-term outcomes in nondiabetic chronic kidney disease
original article http://www.kidney-international.org & 28 International Society of Nephrology Long-term outcomes in nondiabetic chronic kidney disease V Menon 1, X Wang 2, MJ Sarnak 1, LH Hunsicker 3,
More informationKey Elements in Managing Diabetes
Key Elements in Managing Diabetes Presentor Disclosure No conflicts of interest to disclose Presented by Susan Cotey, RN, CDE Lennon Diabetes Center Stephanie Tubbs Jones Health Center Cleveland Clinic
More informationA Descriptive Delta for Identifying Changes in SNOMED CT
A Descriptive Delta for Identifying Changes in SNOMED CT Christopher Ochs, Yehoshua Perl, Gai Elhanan Department of Computer Science New Jersey Institute of Technology Newark, NJ, USA {cro3, perl, elhanan}@njit.edu
More informationOnline clinical pathway for chronic kidney disease (CKD) in primary care. February 27, 2015 Dr. Kerry McBrien University of Calgary
Online clinical pathway for chronic kidney disease (CKD) in primary care February 27, 2015 Dr. Kerry McBrien University of Calgary FACULTY/PRESENTER DISCLOSURE Faculty: Kerry McBrien Relationships with
More information