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Survey of Medical Informatics CS 493 – Fall 2004 August 30, 2004

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Survey of Medical Informatics. CS 493 – Fall 2004 August 30, 2004. Components of a National Health Information Infrastructure. Chapter 2: Patient Safety - Achieving a New Standard of Care. IOM Report. Improving Safety. - PowerPoint PPT Presentation

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Page 1: Survey of Medical Informatics

Survey of Medical Informatics

CS 493 – Fall 2004

August 30, 2004

Page 2: Survey of Medical Informatics

Components of a National Health Information InfrastructureChapter 2: Patient Safety - Achieving a

New Standard of Care.

IOM Report

Page 3: Survey of Medical Informatics

Improving Safety

Clinical Decision Support Systems (CDSSs) – ex. for medication order entry

Computer-based alerts and reminders – facilitate adherence to care protocols

Computer-assisted diagnosis can help with evidence-based practice of medicine

Access to clinical information at the point of care – for ex. Access to lab results, radiology results can eliminate need for redundant tests

Page 4: Survey of Medical Informatics

Trends in technology adoption “it takes an average of 17 years” before

research results make into practice.

Page 5: Survey of Medical Informatics

NHII Defined (NCVHS definition)The NHII is defined as a set of technologies,

standards, applications, systems, values, and laws that support all facets of individual health, health care, and public health (National Committee on Vital and Health Statistics, 2001).

Page 6: Survey of Medical Informatics
Page 7: Survey of Medical Informatics

Some examples of LHII

New England Healthcare Electronic Data Interchange Network (NEHEN) A network of providers, health plans and payers

Indiana Network for Patient Care (INPC) Started by Regenstrief Institute 10 years ago 13 acute care hospitals and 20% of the outpatient

physician practices in the metropolitan (Indianapolis) area. The Santa Barbara County Care Data Exchange

75% of healthcare providers in the Santa Barbara County participating in this experiment

Page 8: Survey of Medical Informatics

From IOM Report, pg 57

Page 9: Survey of Medical Informatics

EHR in clinical practice

17% in US; 58% in UK; 90% in Sweden Lack of incentives in US for change

Page 10: Survey of Medical Informatics

Data Acquisition Methods & Interfaces Data Capture

Speech Free text Document imaging Video Structured data Signal data Abstracted data Coded data

Guidelines on UI Usable Grouped Minimalist Standards-based Prioritized Use of graphics and

icons

Page 11: Survey of Medical Informatics

Health Care Data Standards

Standardized measures and data elements Datasets for clinical practice Terminologies standards Clinical Concepts and guidelines knowledge

representation standards Identifiers Reference information models Document standards

Page 12: Survey of Medical Informatics

Data Repositories

Collects and collates patient information from numerous sources

Patient centric Supports health care delivery, surveillance,

and clinical decision support Need to migrate to such repositories from

current departmental “silos” systems.

Page 13: Survey of Medical Informatics

Clinical Event Monitors Clinical event monitors can be used to support real-time

error prevention Used in conjunction with data repositories Bates et. Al., 2003

Prevent adverse drug events Nosocomial infections (infections that originate or

occur in a hospital – basically infections acquired at a hospital)

Injurious falls

Bates, D. W., S. Murff, H. Evans, P. D. Stetson, L. Pizziferri, and G. Hripcsak. 2003.Policy and the future of adverse event detection using information technology. J AmMed Inform Assoc 10 (2):226–228.

Page 14: Survey of Medical Informatics

Data Warehouse

Clinical data warehouse is similar to data repository but designed for long term archival of clinical data and aggregation across institution, regional, national or even international.

Page 15: Survey of Medical Informatics

Data Mining Techniques

Methods to obtain useful information from data warehouses

Data mining is useful for surveillance, case-based reasoning and even rule induction for expert systems

Natural Language Processing can also be applied to extract information from narrative texts

Data Mining Presentation

Page 16: Survey of Medical Informatics

NLP and Data Mining

MedLEE – rule-based NLP system http://lucid.cpmc.columbia.edu/medlee/ Dept of Medical Informatics of Columbia

University Medical Language Extraction and Encoding

System

Page 17: Survey of Medical Informatics

Clinical Document Architecture XML markup of clinical documents Standardizing structure of clinical documents Ability to handle structured and semi-

structured documents CDA + Standardized terminology can help to

apply clinical decision tools

Page 18: Survey of Medical Informatics

Digital Sources of Evidence or Knowledge Bibliographic

MEDLINE: http://medlineplus.gov/ Comprehensive source for medical journal articles maintained

by National Library of Medicine (and other information related OVID: http://www.ovid.com/site/index.jsp

Commercial database supporting medical research: including 1,200 journals, over 160 books and more than 300 databases

Structured evidence: Trial Bank Project: http://rctbank.ucsf.edu/ Captures clinical trial results that are published in journals in a

standardized way so that evidence-based medicine can become a reality

Page 19: Survey of Medical Informatics

Digital Sources of Evidence or Knowledge Practice parameters

American Association of Critical Care Nurseshttp://www.aacn.org/

National Guideline Clearinghousehttp://www.guideline.gov/

American Diabetes Associationhttp://www.diabetes.org/home.jsp

National Committee for Quality Assurance (NCQA) – a watchdog group for the managed care industry The Health Plan Employer Data and Information Set

(HEDIS) – tool used by health plans to measure performance of care and service provided. About 60 different measures are tracked across health plans.

Page 20: Survey of Medical Informatics

Digital Sources of Evidence or Knowledge DXplain

http://www.lcs.mgh.harvard.edu/ From Massachusetts General Hospital and Harvard

Medical School Decision support tool that helps physicians with clinical

diagnosis Illiad: http://www.openclinical.org/aisp_iliad.html National Drug File:

http://www.medsphere.com/products/clinical.wpl?m=55#module

Genbank: http://www.ncbi.nlm.nih.gov/Genbank/ Molecular Modeling Database

Page 21: Survey of Medical Informatics

Computer based guidelines

Greenes, R. A., M. Peleg, A. T. S. Boxwala, V. Patel, and E. H. Shortliffe. 2001. Sharable computer-based clinical practice guidelines: Rationale, obstacles, approaches, and prospects. Medinfo 10 (Pt 1):201–205.

Disease management Encounter workflow management Reminders/alerts Clinical trial support Care plan/critical path support Appropriateness of treatment determination Risk assessment Demand management Education and training Reference

Page 22: Survey of Medical Informatics

Digital Sources of Evidence or Knowledge Diabetes Quality Improvement Project (DQIP) Infobutton

Page 23: Survey of Medical Informatics

Communication Technologies

Factors Bandwidth Transmission latency Availability Security and

confidentiality Access

Type of communication Physician-physician Physician-patient Patient-patient Mass media

communication Medical Literature

dissemination

Page 24: Survey of Medical Informatics

Clinical Information Systems

NHII + EHR

Page 25: Survey of Medical Informatics

What is NHII ?

Interoperability Standards

NationalInfrastructure

Evidence-based

Decision

LongitudinalEHR

Population Health

Avoidance of Medical

Errors

Page 26: Survey of Medical Informatics

1980 1990 2000

CPRScanned DocsUnstructured TextLimited Discrete DataLimited to single facility

EMRStructured dataTranscribed TextOrders/ResultsEnterprise SystemsIDN

EHRComprehensiveDistributed andFederated.Emphasis on: Evidence-based Medicine Public HealthFunctional: Direct Care Clinical Support Infrastructure

Evolution of the EHR conceptTrends

Page 27: Survey of Medical Informatics

Distributed concept

Acute Care Facility

EHR

EHR

EHR

Notes

Images

Structured

Page 28: Survey of Medical Informatics

Federation concept

Integrated Delivery Network (IDN)

ACF ACF

Clinics

Long Term Care

Page 29: Survey of Medical Informatics

Federation concept

Local Health Information Infrastructure (LHII)Community Area Network

IDN IDN

OtherClinics

LongTermFacilities

Page 30: Survey of Medical Informatics

Federation concept

National Health Information Infrastructure

LHII

Goal: Access to longitudinal electronic health record from cradle to grave for every individual by those authorized to access it from anywhere across the nation and the world.

LHII

LHIILHIILHII

Page 31: Survey of Medical Informatics

Implementing the systems

IOM-HL7 Demonstration Project

Page 32: Survey of Medical Informatics

HIMSS 2003 – Interoperability Demonstration Project CDC FDA Markle Foundation/Connecting for Health

Initiative 19 participating organizations Results

Gaps in interoperability standards Lack of standards to represent ADE

Page 33: Survey of Medical Informatics

Davies Award Winners

CPRI-HOST started Now part of HIMSS Recognizes organization for implementing

CPR systems

Page 34: Survey of Medical Informatics

Other factors

Organizational leadership Financial incentives Technical assistance Privacy & Confidentiality