EMR Talk

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Electronic Medical Records:
An Introductory Tutorial
William Tierney, MD
Atif Zafar, MD
AHRQ PBRN Resource Center
Outline of Presentation
• Introduction to EMRs (very basic information)
• Barriers to Adoption: Some Problems with Data
Accessibility and Care Processes
• EMRs for Clinical Research
• EMRs and HIPAA Security
• No Nonsense Guide to Selecting an EMR
• Examples of EMRs
– OpenSource
– Commercial
• Lessons Learned


Introduction to EMRs
Introduction to EMRs
• Why do we need Electronic Medical Records
(EMRs)?
• Many problems with the current healthcare system
(underuse and overuse)
– 30% of children receive excessive antibiotics for otitis
– 20-50% of surgical procedures are not necessary
– 50% of back pain x-rays not necessary
– 50% of elderly patients don’t get a pneumovax
Introduction to EMRs
• Why do we need EMRs?
– Clinical practice is a data intensive operation a
– Inadequate data communication causes
medical errors
– Human cognition is good at pattern recognition
but not at remembering lists or evaluating
multiple business rules.
Why do we need EMRs?
• Available 24 x 7
• Can be viewed by more than one user at a
time
• Is available from remote locations
– To covering MDs
– Others with appropriate needs
• Data can nearly always be found
• Is legible

Why do we need EMRs?
• Enhances Communication:
– Between providers--clinical messaging
– Can tag EMR location with message
– Referrals
• Half of specialists didn’t know what main question
was
• A third of the time no information came back to
PCP

Why do we need EMRs?
• Cost Savings:
– Dictation cost savings
• $170/FTE/month
– Chart pull savings
• $217/FTE/month
– Savings accrue to practice, apply to all payers

Why do we need EMRs?
• Assist with Decision Support:
– Many domains—cost and selection of:
– Drugs
• 18% reduction found by Overhage
– Lab tests
• 10-15% reduction in cost for charges, last result,
probability of abnormal
– Radiological studies


Why do we need EMRs?
• Decision Support:
• In inpatients, computerizing ordering decreased
– Serious medication errors by 55%
– All medication errors by 81%
• EMR can help by
– Structuring medication orders
• 34% error rate with paper vs. 6% with electronic
– Alerting about
• Allergies
• Duplicate medications
• Many other issues

Introduction to EMRs
• Do EMRs make a difference?
– UNEQUIVOCALLY YES, BUT AT A COST!
– In multiple studies, EMRs have been shown to:
• Shorten Length of Stay in a Hospital setting
• Decrease Adverse Drug Events (ADEs)
• Improve Readability, Consistency and Content of
the medical record
• Improve Continuity of Care
• Reduce practice variation
• Most benefits come from Decision Support.
EMR Use in the United States
• Even though the US Health Care system is
the costliest in the world, its performance
ranks 37
th
in the world according to the
WHO!
• Only 5% of US primary care providers use
EMRs (Bates et. Al., JAMIA 2003), 7% of
all physicians (Wang, Bates, et. Al.,
American Journal of Medicine, April 2003)
EMR Use Around the World
Use PCs Use EMR
• Australia 90% 53%
• Denmark 95% 62%
• Netherlands 95% 88%
• Sweden 95% 90%
• United Kingdom 95% 58%
(c) 2001 Harris Interactive
Breakdown by Function - 2002
Australia UK
• Use EMR 90% 99%
• Of Those:
– Prescrip 100% 80%
– Notes Unknown 45%
– Reminders Unknown 70%
– Clin Vocab 15% (ICPC) 100% (Read)
– Paperless Unknown 45%

• $2B initiative by UK to get all physicians online
What is an EMR?
• At their heart, EMRs are just a database
• This database hold many kinds of information (coded
and not coded)
• This database is organized by date, time, pat ID and
contains:
– Patient registration data (name, contact info, DOB, SSN, etc.)
– Test results (laboratory, radiology, nuc med etc.)
– Medications (active, inactive) and Allergies
– Current list of diagnoses and problems
– Appointment Data
– Clinical Notes
– Billing Information

What is an EMR?
• So if an EMR is just a database, how is it different
from other databases, and why is it so useful?
• Value Added:
– A Clinical Knowledge Heirarchy (term dictionary)
• How do clinical concepts work together
• Ex: Digoxin toxicity can occur with hypokalemia
– A List of Current Clinical Recommendations
– A List of Appropriate Medication Indications, Doses,
Adverse Effects and Interactions and Cost Estimates
– Costs, Indications and Utility of Tests
What is an EMR?
• What are some typical EMR Components:
– Lab System: Contains all lab tests ordered and their
results and stored as coded results (LOINC etc.) in
many systems
– Radiology System: Stores test reports
– Pharmacy System:List of current medications, inactive
meds and when they were last dispensed or ordered
– Billing System : A list of diagnostic codes used for
billing (ICD9, CPT, etc.)
– Registration System: Names, Contact Info, Personal
Info, etc. for patients

What is an EMR?
• Additionally, many EMRs have:
– An Order Entry System (where physicians enter
orders, prescriptions, notes etc. online)
– A Decision Support System
• Often linked to the order entry system to
provide guidance at the point of care
• Contains databases for clinical knowledge,
guidelines, list of medication indications,
doses etc.

What is an EMR?
• The spectrum of EMRs
– EMRs target specific user bases, from solo
office-based practices to large, multispecialty
tertiary care centers
– Many features are thus directed at managing
workflows specifically to these user bases
• For example, large commercial EMRs unbundle
services such as clinical documentation, results
display etc. while office systems typically integrate
all of these under the same interface.
How do Clinicians Interact with EMRs


LAB SYSTEM
PHARMACY SYSTEM
RADIOLOGY SYSTEM
REGISTRATION SYSTEM
BILLING SYSTEM
Physicians
Clerks
Nursing Staff
Coding Staff
Patients
Insurance Co.
Order Entry/Results Reporting
Different Types of EMRs
• EMRs don’t necessarily need to be expensive and
complicated or require that a computer be used to
enter data
• Can have hybrid computer/paper based
approaches
– Ex: In the CHICA™ System, paper is used to interact
with an electronic data repository
– Standardized paper forms are printed and then
―scanned‖
– Characters are recognized and the electronic data so
generated interacts with the data repository
Different Types of EMRs
• At Indiana University, pediatric clinics use this
system:
– A data repository was developed using Microsoft SQL Server
– A clinical guideline system was written in Arden Syntax
– An optical character recognition system called Cardiff Teleforms is
used to process handwritten numerical data on preprinted scanned
forms
– The data so generated is stored in the database and dynamic
reminders are generated for the physician
– These are printed on the clinic computer
– The entire operation takes < 2-3 minutes!

Different Types of EMRs
• The Mosoriot Medical Record System™
– Indiana University has an HIV Effort in Kenya
– A Simple MS Access based database holds all
patient records (3 years worth!)
– Provides forms for data entry, standard term
dictionary, medication listings, registration
system, clinical documentation system etc.
– Created by 1 programmer over 2-3 weeks!
– Highly effective, easy to maintain, inexpensive!
Data Sources
• So how can EMRs populate their databases?
• Data can come from many many sources:
– Admission/Discharge/Billing
– Anesthesia Systems
– Cytology Systems
– Diagnostic Imaging Management Systems
– EKG Carts
– Endoscopy Systems
– ER Systems
Data Sources
• More Data Sources:
– Home Care Systems
– ICU Monitoring Systems
– IV Fluid Infusion Control Systems
– Laboratory Systems
– Nurse Triage
– Order Entry Systems
– Pharmacy Systems (Inpatient/Outpatient)
– Pulmonary Function Systems

Data Sources
• More Data Sources
– Radiology systems
– Risk Management systems
– Registration Systems
– Scheduling and Clinic Charge Systems
– Transcription Systems
– Unit Dose Dispensing machines
– Ventilator Management systems
Data Sources
• So if there are so many data sources
available and so many people are interested
in using EMRs, why are they not more
prevalent?
The Challenges of EMR
Implementation

Problems with Electronic Data
• For the last 30 years the medical informatics
community has struggled with how to architect the
―vessel‖ that will hold patient data
• Problem is that they have focused on the wrong
problem!
• We don’t just want to create a system that permits
entry of data electronically, we want to create a
system that can acquire this data automatically
from other electronic data repositories and make
it available at the time of service.
Problems with the Data Sources
• Too many repositories or ―islands‖ of systems
• Difficult to ―bridge‖ and combine in useful ways
• Contain different data at different levels of granularity
• Each uses a different code to identify the same
information.
• Many institutions do not capture all of the data of interest
to clinicians.
– Labs are sent to external reference laboratories
– Patients fill their scripts at community pharmacies
• As a result many implementations do not lead to
satisfactory achievement of the intended quality assurance
goals
Problems with Data Sources
• Another problem is that there are many many care
providing sites in the United States:
– Hospitals 5000+
– Nursing Homes 19000+
– Pharmacies 59722+
– Physician offices 200000+
– Laboratories 63000
– Emergency Rooms 4856
– Hospice Care 2800
– Home Care agencies 4258
• All of these sites generate data that are not necessarily
compatible.

Problems with Electronic Data
• Thus, the problem is not one of creating database
fields de novo, it is one of merging existing fields
from many different sources in meaningful ways

• When commercial and other EMR vendors create
proprietary, closed, systems, with custom database
architectures, they often worsen the problem and
make it harder to populate the database with useful
information, inexpensively
(1) The Role of Standards
• Fortunately, most of the informatics community
has realized that the solution to the problem of
merging data lies in the implementation of
Standards for Data Communication.

• These standards permit data to be easily translated
from one database system to another
(1) Standards
• There are many many standards, each for a
different purpose
– Lab Data Communication
– General Clinical Messaging
– Radiology Image Transmittals
– Diagnostic Coding
– Procedure Coding
• Need to distinguish between coding standards and
messaging standards.
(1) Standards
• HL7 (Health Level 7)
– Most widely used standard
– General clinical messaging standard
– Communicates structured data
– Fields for:
• Diagnostic Results
• Notes
• Referrals
• Scheduling Information
• Nursing Notes
• Problems
• Clinical Trials data
(1) Standards
• Health Level 7
– 2000 hospitals, the CDC and most referral labs.
– Also used in Canada, Australia, New Zealand, Japan
and extensively in Europe
– Bridges many systems, including laboratory, dictation,
pharmacy, electronic patient records, performance
databases, data repositories (cancer registries) etc.
– Web Site:
• http://www.mcis.duke.edu/standards/HL7/h17.htm
(1) Standards
• LOINC
– Logical Observations and Indicators Names and
Codes
– A coding standard that is used for LAB data
– Used for representing laboratory observations
and common clinical measurements
– At least 5 large commercial labs (Corning,
MetPath, LabCorp, ARUP Labs and Life
Chem) have adopted LOINC
(1) Standards
• DICOM
– Another messaging standard
– Standard of choice for transmitting diagnostic
images
– Closely supported by all of the imaging vendors
and is working with the HL7 group
– Web site:
• http://www.xray.hmc.psu.edu/dicom/dicom_
home.html

(1) Some other coding standards
• ICD9/10 – Used to code diagnoses
• CPT – Used to code procedure data
• ISO+ - Used to code units of measure
• UMDNS – Device classification standard
• NDC – Drug entities classification
• SNOMED – organism names, topologies,
symptoms and pathology
• HOI – Outcomes variables
• UMLS – Metathesaurus for clinical nomenclature
• Arden Syntax – Clinical knowledge
(2) Patient Identification
• How do we ensure that the information
belongs to the correct person?
– Patients move and change addresses/tel#s
– Patients change names or use aliases
– Patients sometimes have multiple SSNs
– There are differences in patient, provider and
place of service identifiers among data sources
(2) Patient Identification
• Solutions to this problem do exist but at a local
institutional level at the moment
• Our institution uses a combination of mothers
maiden name, SSN and DOB to uniquely identify
the patient

• The Kassebaum-Kennedy Bill (PL 104-191) will
make this into a national effort and standardize
patient and provider identifiers
(3) Physician Data Capture
• The ―ultimate EMR‖ promises to capture whatever
data is needed to perform any EMR task –
outcomes analysis, utilization review, profiling
and cost estimation.

• This prospect excites many CEOs and CIOs

• However, much of the data needed for such
functionalities comes from physicians (disease
severity and clinical findings) and most of this
data is recorded as un-coded free text.
(3) Physician Data Capture
• In order for physician generated data to be useful
it needs to be in coded form so that algorithmic
assertions can be made

• The problem of coding free text data is of
paramount importance and information systems
designers have struggled with this as long as the
field of medical informatics has been in existence
(3) Physician Data Capture
• One approach we could take would be to translate
existing free text dictations into coded, computer
readable information, but:
– Human coding is error prone and expensive and is at
too high a level of granularity to be useful
– Decades of research into computer based coding has
still not yielded satisfactory results
• Or the physician could code the data themselves
by entering structured notes but:
– This is costly in terms of time as it requires the user to
map the terms into computer understandable words at a
level of granularity which is useful
(3) Physician Data Capture
• Commercial EMR vendors bypass the problem
and provide every mode of data entry possible:
– Direct keyboard entry
– Dictation with human transcription
– Voice Recognition
– Structured Data Entry
– Paper based data collection
– Web/PDA/Mobile devices
• Problem is that we don’t know which one is the
most efficient so users have to think with their feet
(3) Physician Data Capture
• We did a study at Indiana University comparing voice
recognition with typing and dictation/transcription and
found that (at least for 1 user):
– Voice recognition almost doubled the note size as
compared with typing
– It took longer to use voice recognition by 1.3 min as
compared with typed notes
– Voice recognition was 30 fold less accurate than
dictation/transcription
– During proofreading, the user missed 30% of errors
– 1.2% of errors changed the intended meaning
– Dictated note turnaround time was from 2-5 days!
(3) Physician Data Capture
• Managers and quality analysts want data that is
often never captured
– Formal functional status
– Detailed Guideline criteria
• And we don’t even know how much of this kind
of information is needed?
– For some disorders (angiography and knee surgery)
data sets have been developed but we do not know the
operating characteristics or predictive value of the data
elements?
– How do we define and collect the ―soft‖ data elements?
(3) Physician Data Capture
• We do have some instruments for some disorders
(CAGE, Hamilton Scale, SF12/36 etc.)

• But we lack them for many other clinical entities
and for much of specialty clinical care

• And checklist based symptom questionnaires as
opposed to validated instruments elicit many more
symptoms than open ended questions, so which of
these are really important?
(3) Physician Data Capture
• Coding of all medical information is unnecessary

• So where do we draw the line?
– (how much should be coded and how much can be
stored as free text) in order to maximize the utility of
the information.

• The other issue is with longevity of clinical notes.
– How often do you use a note from 2 years ago?
– How long do we need to keep the EMR data?
(4) Cost
• Cost is perhaps the biggest barrier to
implementation
• Unfortunately there are few studies that have
looked at the long term ROI with EMRs
• Most existing studies have been done by the
system vendors and so the data should be
examined with a cautious note
• However, the data that is available suggests that
the ROI is excellent!
(4) EMR Cost Analysis Studies
• Several studies are worth mentioning

• (1) Renner et. Al. looked at implementing an EMR
in 1996 in 40 primary care practices
– Its net present value (1996 dollars) was about $280,000
based on a 5-year model
– They found that reducing the cost of medications and
preventing ADEs was of the greatest benefit in primary
care
(4) EMR Cost Analysis Studies
• (2) Wang, Bates et. Al. looked at the cost of
implementing a full EMR in primary care as
compared with paper based chart systems
• Primary outcome was the cost benefit per provider
over a 5-year period
• Used average statistics from their institution
(Partners Healthcare, Boston), expert opinion and
national data to estimate costs
– System Costs ($13,100 initial, $3100 each year + HW)
– Induced Costs ($11,200 in year 1)

(4) EMR Cost Analysis Studies
• (2) Wang, Bates et al.
– Benefits resulted from costs averted ($/year)
• Transcription savings ($2700)
• Reduction in need for chart pulls ($5/chart pulled)
• Drug cost savings and prevention of ADEs ($2200)
• Laboratory and Radiology cost savings ($10,700)
• Charge capture improvement ($7700)
• Decrease in Billing Errors ($7600)
– All benefits finally being realized in year 4

(4) EMR Cost Analysis Studies
• (2) Wang, Bates et. Al.
– Resulted in present value of net benefit (2002
dollars) to be $86,400/provider in year 5
– Breaking down by EMR feature they got:
• Light EMR (net loss of $18,200/doc in year 5)
– Online patient charts only
• Medium EMR (net benefit of $44,600/doc in year 5)
– Adds an Electronic Prescribing Module
• Full EMR (net benefit of $86,400/doc in year 5)
– Adds Lab, Radiology and Charge Capture systems

(4) EMR Cost Analysis Studies
• (2) Wang, Bates et. Al.
– Conclusions: An Ambulatory EMR
• Resulted in net benefits across a range of assumptions, which
increase as more features are added and as the time horizon
lengthens
• Most benefit was derived from reductions in drug
expenditures, improved test utilization, improved charge
capture and reduced billing errors
• The greater the portion of capitated patients the greater the
return, although benefits also accrue for fee-for-service patients
(but mostly to payers and not health care institutions)
• Limitation: Did not consider malpractice reduction, increased
provider productivity or decreased staffing requirements.
• Intangible benefits: Improved Quality and Decreased Errors
(5) Other Barriers
• (1) Physician reluctance and fear that their
productivity may decline (which it does)
• (2) Unreliability of EMR Vendors in a
volatile IT economy. Lack of adequate IT
support from the vendors
• (3) Concerns over data security
Summary: Barriers to EMR Use
• Too many data sources, no simple way to
coordinate and connect them except to use
standards which are still evolving
• Unique patient identification still a problem – esp
in large tertiary care centers
• Physician data capture inefficient and expensive
Summary: Barriers to EMR Use
• Startup costs can be prohibitive but long term
benefits are clearly evident form pilot studies
• Physician reluctance a major barrier to use
• Concerns over security still an issue, eg: HIPAA
• System vendors are transient and fail to provide
adequate support
EMRs for Clinical Research
EMRs for Research
• So what EMR functions do we need in order to
effectively do clinical research?
• Answer: Depends on what you want to do
• However, to be able to ask questions of your
practice, you need:
– Registration data (Registration system)
– Diagnoses (Billing data)
– Medications (Pharmacy data)
– Labs and other Test Results (Lab/Radiology data)
AND
– A system to query these databases intelligently
EMRs for Research
• You don’t necessarily need a decision
support or order entry system but if you
want to intervene, you may want to include
these systems as well

EMRs for Research
• Note that the registration, billing, pharmacy and
lab/radiology data usually (but not always) exists,
outside of the context of any specific EMR system

• These are just data repositories which need to be
tapped into and queried

• So you need a system to access and query these
databases, independent of any electronic medical
record system.
EMRs for Research
• Alternatively, you could build a master repository
which acquires and stores this information and
permits intelligent queries to be performed

• This is exactly what we did in Kenya in the
Mosoriot Medical Record System, although data is
still hand-entered. Eventually it will be
downloaded using HL7 messages.
Mosoriot Medical Record System
• An example of an EMR that is inexpensive and functional
and supports both clinical care and research in rural Kenya
• Built in 2-3 weeks by 1 programmer using Microsoft
Access
• Consists of:
– Data dictionary tables which define test names,
medications, diagnoses etc.
– Forms which are used for data entry
– Has tables for registration data, billing data, medication
lists, lab and test results
– Currently running on Tablet PC devices in Kenya

Research Workflow Model
LAB SYSTEM
PHARMACY SYSTEM
RADIOLOGY SYSTEM
REGISTRATION SYSTEM
BILLING SYSTEM
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INTERVENTION
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EMR Features Conducive to
Research
• Reliance on Standards (HL7, LOINC, ICD9, CPT)
• Easy access to data repository, i.e. database
structure is well documented
• Built-in Practice Profile Management systems
• Built-in decision support and order entry
functionality
• Able to export data in a standard format (CSV,
MDB etc.)

HIPAA Security
Introduction
• HIPAA = Heath Information Portability and
Accountability Act
• Final Security Rule Published in the Federal
Register on February 20, 2003 (effective 60 days)
– http://www.cms.hhs.gov/hipaa/hipaa2/regulations/secur
ity/default.asp
• Designation: 45 CFR 160, 162, 164
• Compliance Dates: April 20, 2005
– Covered Entities: 24 months after effective date
– Small Health Plans: 36 months after effective date
HIPAA Security
• Some excellent links:
• http://privacy.med.miami.edu/glossary/gt_security_rule.htm
• http://www.hipaadvisory.com/tech/wireless.htm
• http://www.hipaadvisory.com/regs/securityoverview.htm
HIPAA Security
• Security should not be confused with Privacy or
Confidentiality
– Privacy: The rights of an individual to control his/her
personal information without risk of divulging or
misuse by others against his or her wishes
– Confidentiality only becomes an issue when the
individuals personal information has been received by
another entity. Confidentiality is then a means of
protecting this information
– Security refers to the spectrum of physical, technical
and administrative safeguards used for this protection
HIPAA Security
• Addresses 3 tiers of protection:
– Administrative Safeguards
– Physical Safeguards
– Technical Safeguards
Administrative Safeguards
• Institutional level
– Develop security management process where
potential ―threats‖ to PHI are determined
– Provide training to all employees about HIPAA
– Provides appropriate level of authorization
based on a protocol for granting access
– Violations should be clearly documented and
investigated
– A disaster recovery plan should be in place
Physical Safeguards
• Applies to 3 elements of the PHI data
storage infrastruture:
– Facility where PHI data is stored
– Workstations on which it is stored
– Media on which it is stored
Physical Safeguards
• Require that the facility have access control
• Contingency plans need to be in place in case an
intruder gains access
• Workstation security measures be in place
– Automatic logoff
– Screen is placed away from potential viewers
– PDAs should be password protected
• Devices and media should be appropriately
disposed of in case they are no longer needed and
data should be erased properly
Technical Safeguards
• Applies to how information is stored, verified,
accessed and transmitted/received
• Access and audit controls
• Emergency access to information when needed
• Automatic logoff is enforced
• Data is encrypted and decrypted during
transmission
• Verify integrity of the storage and transmission
(digital signatures)
Am I HIPAA Compliant?
Questions to ask yourself and your
institution
Questions to ask your institution
• 1. Was a security audit done and if so what are the
results?
• 2. Did I get the appropriate HIPAA training and
do I have a certificate to prove this?
• 3. Are there procedures in place to grant access to
PHI to authorized users?
• 4. What are the procedures in place in case of
disaster, data loss or data theft? Are Backups
made frequently?

Facility, Workstation, Media
• 1. What are the procedures in place to safeguard
the facility from intruders? Are there contingency
plans for dealing with intruders, data theft or other
event?

• 2. How do protect the safety of workstations? Are
they password protected?

• 3. Can bystanders view the screens on which PHI
may potentially be displayed?

Facility, Workstation, Media
• 4. Is an automatic logoff mechanism enforced?
What time limits are provided before this occurs?
• 5. What types of data are stored on PDA devices
and if PHI is stored is it password protected or
encrypted?
• 6. What procedures are used when disposing of,
reusing or archiving data on hard disks, CDs,
floppys and Zip disks? Are PHI data erased
properly if the disks are to be disposed of or
reused?

Data Level
• 1. Are there audit mechanisms for checking who is
accessing the PHI data and is this done on a
regular basis by authorized personnel?
• 2. Are there procedures in place to grant
emergency access to information if needed?
• 3. Is data integrity checked when the data is
transmitted or received? (digital signatures, digital
certificates, checksums etc.)
• 4. Is the data encrypted and decrypted during the
transmission process?
HIPAA Wireless Security
Before you Begin
• Do I really need to be wireless of can I get
by with a wired connection?
– Is space limitation a problem?
– Is mobility absolutely necessary?
• Do I have the permission of my institution
to install wireless networks?
• Do I have adequate IT support to do this?
11 Steps to Wireless Security
• Wireless is inherently unsecure
• Many Many ways of hacking into wireless
networks
• Technology base is there to make it secure
• Some simple steps can be taken to
maximize the security of your wireless
network
11 Steps to Wireless Security
• 1. Change the default SSID (network
name) on the router so that your
name/location is kept secret
• 2. Disable the SSID broadcast, if your
router supports it. This will prevent
hackers from seeing you
• 3. Change the administrator’s password
on your router.

11 Steps to Wireless Security
• 4. Turn on the highest level of security
supported by your hardware (i.e. Wireless
Equivalent Privacy – WEP, which is older or
WPA which is the latest and most secure)
• 5. Make sure you have the latest firmware
updates. Implement MAC (media access
control), which specifies exactly which WLAN
PC cards can access the network and
excludes others

11 Steps to Wireless Security
• 6. Place the Wireless Access Point (WAP)
towards the middle of the building, keeping
the zone of potential access within the
building.
• 7. Do your own security audit. Use Network
Stumbler (www.netstumbler.com) on your
Tablet PC, laptop of PDA and walk around
the perimeter of your building to see where
and what a would-be hacker may see
11 Steps to Wireless Security
• 8. If you have a limited number of wireless
clients (Tablet PC’s), provide them with static
IP addresses, and disable DHCP on your
router. This ensures that only “authorized”
machines can “see” your network.

11 Steps to Wireless Securit
• 9. If we are in an enterprise setting, use
VPN’s (Virtual Private Networks). You can
isolate your WLAN from the wired network
using products such as the Netgear FVM318
or the SonicWall SOHO TZW. Then you can
use the VPN to tunnel directly into the wired
network securely
11 Steps to Wireless Security
• 10. Avoid using public hotspots, areas that
are insecure and open for general use.

• 11. Turn off file and print sharing on your
Tablet PCs. Most devices do not prevent
client-to-client traffic, so people sitting across
the street from you can be looking at your
shared directory remotely.

Guide to Selecting and
Deploying an EMR
Selecting an EMR
• Award winning EMRs
• CPRI Davies Award Winners (1995-2000)
– Emphasis on successful implementation, not on
technology that is behind the design
– Functional Requirements:
• Integrate data from multiple sources
• Provide decision support
• Used by caregivers as primary source of information
• Must enhance care, not just replace paper
• So who are there award winners and what are their
strategies for success?
Davies Award Winners
1995 Intermountain Healthcare System, Salt Lake City
Columbia Presbyterian Medical Center
Department of Veteran Affairs CPRS (now open-source)
1996 Brigham and Women’s Hospital
1997 Kaiser Permanente, Cleveland OH
Regenstrief Medical Record System
North Mississippi Health Services
1998 Kaiser Permanente, Portland OR
Northwest Memorial Hospital, Chicago
1999 Kaiser Permanente, Rocky Mtn. Region
2000 Harvard Vanguard System
Davies Award Winners
Common Strategies and Attitudes
towards implementing EMRs
Common Strategies
• Vision of healthcare as an information
business
• Sustained leadership (5 years +)
• Run by project leaders and not CIOs
– Most projects had physician champions
• EMRs subjected not to a cost benefit ROI
analysis but to an ―unremitting pressure to
show value‖
Common Strategies
• Customer Service, Customer Service!
– Frequent, sustained, end-user orientations and
feedback with demonstrated responsiveness to
feedback!
• Weekly Regenstrief Pizza Meetings
• Kaiser physician focus groups
• Northwestern weekly feedback with ―supplements‖
– System developers were also the salespeople,
troubleshooters, coaches and colleagues!
Common Strategies
• Plans in place for system evaluation and change
management
• All winners had to re-engineer some workflow
process – ―don’t automate a manual process that
occurs commonly but does not work‖!
• Incremental deployment – don’t rush things
• Each increment overcame a specific barrier to
care
• Systems were viewed as tools to enable care
process improvement and were not an end to
themselves
Common Strategies
• All resulted in a decreased reliance on paper-based
sources of information
• Decision Support, Decision Support, Decision
Support -> provides the largest value added
compared to a paper system
• Focus on standards based data architecture rather
than specific applications to do this or that
• FAST RESPONSE TIME!
• Flexible enough to adapt to organizational change
So what can I do to implement an
EMR in my practice?
Can I implement an EMR?
• Depends on your size and your budget
• Solo practice -> yes, definitely
• Multispecialty group (2-100) -> probably
(cost is around $4-20K per provider)
• Multispecialty, multisite groups – maybe
• Tertiary care centers with scattered
secondary care sites -> probably need to be
brave and wealthy!
What EMR should I choose?
• Do not start in ―product selection mode‖
• Begin by identifying the practice processes
that you wish to improve first
• Then search for the functions you need:
– Problem List Medications
– Clinical Encounters Lab/Xray/Pathology
– Telephone Calls Referrals
– Preventive Care Managed care
Which EMR should I choose?
• Anticipate primary and secondary users
– Primary
• Clinical decision making,
• Documentation
• Support for Billing
– Secondary
• Provider profiling and service utilization
• Quality report cards and outcomes analysis
• Regulatory reporting and justification for studies
What if I have a limited budget?
• Again, think of using selected modules to
enhance parts of your practice
– Clinical Note Systems
– Prescription Writer
• Use one or more of the OpenSource EMRs
– Need some level of IT expertise to deploy
– No real support available from the developers
Examples of OpenSource EMRs
• a. OpenEMR (http://www.synitech.com/openemr/
<http://www.idltechnology.com/products/openemr/index.php>)
• b. Care2002 (<http://sourceforge.net/projects/care2002/>)
• c. Open Infrastructure for Outcomes – UCLA
(<http://sourceforge.net/projects/open-outcomes/>)
• d. PatientRunner (<http://sourceforge.net/projects/patientrunner/>) –
mental health record system
• e. OpenSDE (<http://sourceforge.net/projects/opensde/>) – structured
note entry system
• f. MedSurvey (<http://sourceforge.net/projects/medsurvey/>) – clinical
information system for Windows PCs
• g. OpenEMed (<http://sourceforge.net/projects/openmed/>) – Java
based EMR
• h. Hardhats (VA’s VISTA software) – yes this IS open source now and
available to EVERYONE (<http://www.hardhats.org/>),
(<http://sourceforge.net/projects/hardhats/>)

EMRs for Primary Care Practice
• Recent survey done by the journal Family
Practice Management (2001)
• Surveyed 28 vendors
• Price structure highly variable
• Found that the market is highly volatile and
some vendors went out of business or
merged with others during the time of the
survey

EMRs for Primary Care Practice
• Five star systems:
– ChartWare
– HealthProbe Patient Information Manager
– EpicCare

EMRs for Primary Care Practice
• Four Star Systems
– Logician
– NextGen
– Pearl
– Physician Practice Solutions
– PowerMed EMR
– Practice Partner Patient Records
– QD Clinical
EMRs for Primary Care Practice
• Four Star Systems
– SOAPWare
– Welford Chart Notes
– Clinical Works Module (ASP)
– NextGen (ASP)
– Physician Practice Solution (ASP)
– topsChart (ASP)

EMRs for Primary Care Practice
• 4+ physician practices:
– ENTITY, Logician, NextGen, ClinicalWorks
• 10+ physician practices:
– EpicCare, PEARL, Physician Practice Solution

• All others can serve practices of any size
EMRs for Primary Care Practice
• Most allow ICD9 and CPT codes
• Many allow access from the web
• Most allow multiple modes of data entry
(keyboard, mouse, touch-screen, light-pen,
voice recognition etc.)
• Most permit integration of hospital data
with a primary care database
Integration with Handhelds
• Some EMRs allow data access from PDAs
and other handheld or laptop devices:
– ChartWare - O-HEAP
– DOCU*MENTOR - Partner
– ENTITY - PowerMed
– EpicCare - SOAPWare
– MedicWare - Welford ChartNotes
– NextGen - ClinicalWorks
– topsCHART

Other EMR Surveys/Resources
• HealthCare Informatics 2004 Resource Guide
– Comprehensive listing of EMRs, features,
costs, contact information etc.
– $50 per copy
– Order from:
• http://www.healthcare-informatics.com
Some Lessons Learned
Lessons learned the hard way
• Well-designed renowned vendor products
meet about 80% of your needs -> where
will the other 20% come from?
• Poorly designed systems will be quickly
abandoned by time-pressured end-users
• Caveat Emptor: ―Total Solution‖, ―Turnkey
solution‖, esp if a proprietary black box
Lessons learned the hard way
• Clinical/Administrative information is
inherently structured. Capturing it in
unstructured ways (images) is a costly
mistake
• Data acquisition costs may be more
expensive than operational expense (I.e.
keyboard entry time more costly than
provider input)
Lessons learned the hard way
• Users will accept a tradeoff if there is a
clear payback in functionality
• Attitudes towards computer use are not age
dependent
• Be the 10
th
customer to a vendor, never the
first!
• Beware of vendors who say ―we can do that
…what is it?‖
Lessons learned the hard way
• The most important information a vendor
will give you is the address of 2-3 sites
where their system is currently in use

Acknowledgements
• David Bates, MD
• Daniel Masys, MD

DISCUSSION AND
QUESTIONS

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