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EMR & EMR Modules Lecture 9 Monday, February 4, 2013 Victoria Aceti Chlebus, MA

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EMR & EMR Modules . Lecture 9 Monday, February 4, 2013 Victoria Aceti Chlebus, MA. Agenda. EMR Lecture Leftovers Benefits of an EMR & Organization of an EMR EMR Modules Patient Care System (Data Entry) Computerized Physician Order Entry Electronic Medication Management & ePrescribing - PowerPoint PPT Presentation

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Page 1: EMR & EMR Modules

EMR & EMR Modules Lecture 9

Monday, February 4, 2013Victoria Aceti Chlebus, MA

Page 2: EMR & EMR Modules

AgendaEMR Lecture Leftovers• Benefits of an EMR & Organization of an EMR

EMR Modules• Patient Care System (Data Entry)• Computerized Physician Order Entry• Electronic Medication Management &

ePrescribing• PACS• CADx• Clinical Decision Support Systems

Page 3: EMR & EMR Modules

Patient Care System (Data Entry)

• EMR is a view-only system where entered information is accessed by a patient’s care circle.

• Can be specialized to specialties (Critical Care, Ophthalmology, OB/GYN, Chronic Disease Management)

• A Patient Care System (called sometimes by different names) is where information is entered through:– Progress Notes (free text or linked)– Standard templates– Assessments (Tests)– Interventions (Treatment Plans)– Scanned reports

Page 4: EMR & EMR Modules

Clinical Decision Support System

• An interactive computer software system which assists clinicians in making decisions about a patient’s current condition and treatment.

• There are many different modules which use CDSS:– Triage– Computerized Physician Order Entry– Electronic Medication Management & ePrescribing– CADx

Page 5: EMR & EMR Modules

Clinical Decision Support System

• Clinical Decision Support Systems (CDSS) work in the background and can create alerts for:– Patient Acuity – Drug interactions– Allergies– Routine Tests– Diagnosis assistance

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Triage Support: ePod

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• Orders are directives from physicians as to how to care for a patient and what medications they are prescribing.

• Order Entry is currently functional within many health organizations

• Computerized Physician Order Entry has been shown to decrease the number of medication errors, prescribing errors, order-to-patient time, and increase patient safety. – Some studies suggest a reduction in 18-32%

Computerized Physician Order Entry

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Computerized Physician Order Entry

Page 9: EMR & EMR Modules

Cancer Care Ontario

• Canada’s 1st cancer-specific CPOE System

• Currently used in 11 cancer centres (ADCP not included)

• Largest ambulatory oncology CPOE implementation in Canada with 100% success rate & 90% physician adoption

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Electronic Medication Management & ePrescribing

Tuesday, April 3Lecture 19

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What’s the Difference?

Electronic Medication Management

• Electronic prescribing, administration and dispensing of medication

• No connection to pharmacy or pharmacist

• Printed copy of prescription for patient to bring to pharmacy

ePrescribing

Electronic prescribing within an electronic medical record

Pharmacist has access to patient prescription history

Pharmacist has electronic copy of pending prescriptions

Printed copy of prescription for patient, or sent directly to pharmacist

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Electronic Medication Management

Prescribing• Ordering the drug, the dose, the frequency and

route of administration• Detailed list of available medications (including

generic products)• Compiles all the medications that have been

prescribed to that patient• Does not show which prescriptions have been

filed or indicate current medications

Page 13: EMR & EMR Modules

Electronic Medication Management

Medication Decision Support• Drug interactions– Drug-to-drug warnings– Drug-to-disease warnings

• Allergy reactions• Dosing information– Complex dosing regimens (chemotherapy)– Particularly important when treating neonates or

children

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Electronic Medication Management

Dispensing • Legibility of prescriptions• Legibility of doctor’s orders• Provides an effective check

and balance to capture errors

• Secondary identification management (Bar coding)

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Electronic Medication Management

Administration• In hospital: RN

– Highly structured– Usually regulated by a

form of technology• At home: patient or RN

– Often not regulated by a medical professional

– Can lead to complications

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ePrescribing

• Requires:– Common data language– Access to secure VPN system– Consent from patients to share data with pharmacist– Understanding between the provider and pharmacist as to

responsibilities

“The ability to send error-free, accurate, and understandable prescriptions electronically from

the provider to the pharmacy”(ePrescribing Canada, 2012).

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So what’s the hold up?

• Data sharing and secure VPNs• Patient privacy issues • Pharmacists not wanting responsibility or liability • Ammenwerth et al. (2008): The Effect of Electronic

Prescribing on Medication Errors and Adverse Drug Events: A Systematic Review– ePrescribing can reduce the risk for medication errors– Searched literature from 1976-2006, n=27 met inclusion criteria– 23 of the 27 studies found medication error risk reduction– Significant error reduction from 13% to 98%– Researchers found studies concluding 98% reduction grossly

overestimated

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Picture and Archiving Communication Systems (PACS)

Picture and archiving information system

Original PACS system integrated in 1982 in the US

Allows for sharing of diagnostic images through a centralized repository

Different types of health information available in PACS: Radiology Cardiovascular

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DI

19

SAHIMAGING

GHC MAMMOGRAPHY

ARCHIVE

RADIOLOGIST RIS

DI

REPORT

RIS

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• Replacement of hard copy medical images• Remote access• Electronic integration of information (EMR & RIS)• Improvement of workflow• Additional tools to improve patient diagnoses• Improved collaboration • Improved communication

Benefits of PACS

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• Technical issues impeding the delivery of images

• Potential loss of data or lack of data transmission

• Legal issues of responsibility between organizations

• High cost of integrating system and updating system

PACS Challenges

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• Originally the “Pan-Northern Ontario PACS Project”

• NEODIN is one of four Diagnostic Imaging Repositories being implemented in Ontario

• NW-LHIN, NE-LHIN & Champlain LHIN• A total of 59 hospitals (including

Group Health Centre) involved• Overall goal is to link up all 4 in

Ontario for one repository

Pan-Northern O

ntario PACS Project

22

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23

WS

SAHIMAGING

GHC MAMMOGRAPHY

ARCHIVE

RADIOLOGIST RIS

WS

REPORT

RIS

DI-r

SAH

TOH

HSN

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Computer Assisted Diagnosis Combines artificial intelligence and digital images to

help diagnose irregularities

Used in the detection of cancers and heart disease at the screening stage

Introduced in 1960s who proposed the idea that computers could detect irregularities

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• Reviewed evidence for the effectiveness of computer-assisted diagnosis in cancer imaging

• Looked at studies from 1990-2010• N=48 from 9199 identified studies• Looked at sensitivity and specificity

measures

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Eadie et al. Systematic Review

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• Binary classification used to measure the accuracy of a diagnosis:– Sensitivity: measure of true positive and false

negative diagnoses– Specificity: measure of true negative and false

positive diagnoses

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Sensitivity & Specificity

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Application Radiologist AUC (SD) CADx AUC (SD)Mammogram (n = 8) 0.86 (0.07) 0.95 (0.03)Breast US (n = 7) 0.88 (0.03) 0.95 (0.01)Breast US + mammogram (n = 3)

0.81 (0.08) 0.89 (0.04)

Lung CT (n = 3) 0.84 (0.01) 0.79 (0.01)

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Findings

Systematic review conducted in 2011 found that CADx assist in the diagnosis of breast cancers, but no evidence of overall benefit from using CADx. Further there is no evidence that CADx are a detriment to diagnosis.

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• High rate of false-positives, thus still requires a Radiologist to differentiate between significant and insignificant results

• Potential loss of diagnosing ability without CAD– When should your clinical judgment override

that of a computer?

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Issues with Computer-Assisted Diagnosis

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Final Thoughts

• EMRs have the potential to improve patient care and decrease medical risk.

• Clinicians need to be educated on the limitations of CDSSs as to understand when clinical judgment overrides system features.

• There is still much to be understood about how these systems are designed and flow into clinical practice.