©
2006 HIMSS Analytics
TM
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TM
)
Electronic Medical Records
vs
. Electronic Health Record
s:
Yes, There
I
s a Difference
A HIMSS Analytics
TM
White Paper
By
Dave Garets
and
Mike Davis
Updated January 2
6, 2006
HIMSS Analytics, LLC
230 E. Ohio St., Suite 600
Chicago, IL 60611
-
3270
www.himssanalytics.org
©
2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
Executive Summary
Many people in the US healthcare industry
,
our government
, and the press
use the terms
electronic medical record
(EMR) and
electronic health record
(EHR) interchangeably
. However,
these te
rms
describe completely different concepts
, both of which are crucial to the success of
local, regional, and national goals
to improve patient
safety
, improve the quality and efficiency of
patient care,
and reduce healthcare delivery costs. EHRs are relian
t on EMRs being in place, and
EMRs
will never reach their full potential without interoperable EHRs in place. It s important to
understand the differences, and to
reduce
confusion in the
market.
T
he EMR is the legal record created in hospitals and ambula
tory environments that is the
source
of data for the EHR. The EHR represents the
ability
to easily share medical information among
stake
holders and
to have
a patient s
information follow
him or her
through the various modalities
of care engage
d by that individual
.
Stakeholders are composed of patients/consumers, healthcare
providers, employers, and/or payers/insurers, including the government.
But before we can move to effective EHR environments, provider organizations
must
implement
complete EMR solutions
. At this point
,
few hospitals have EMR solutions that can effectively
reduce medical errors or improve the quality and efficiency of patient care. The Clinical
Transformation
Staging Model has been developed by HIMSS Analytics to assess the status of
clin
ical system
/EMR
implementations in care
delivery
organizations. This model demonstrates
that US hospitals have a long journey ahead of them to achieve the EHR visions being espoused
in Washington
,
D.C.
and in the 200+ neo
-
CHIN
Regional Health Information O
rgan
i
zation
(
RHIO
)
initiatives in various states of development across the country.
EMR v
s. EHR
:
Definitions
The market has confused the electronic medical record (EMR) and the electronic health
record (EHR).
G
overnment
officials
, vendors, and consultant
s
have propagated this
confusion, in some cases unintentionally. The
definitions that HIMSS Analytics proposes
for these terms are
as follows:
Electronic Medical Record:
An application environment composed of the clinical data
repository, clinical decisio
n support, controlled medical vocabulary, order entry, computerized
pr
ovid
er order entry,
pharmacy,
and clinical documentation applications. This environment
supports the patient s electronic medical record across inpatient and outpatient environments, and
is used by healthcare
practitioners
to document, monitor, and manage health care delivery
within
a care delivery organization (CDO)
.
The data in the EMR is the legal record of what happened to
the patient
during their encounter at the CDO and is owned by
the CDO.
Electronic Health Record:
A
subset of each
care delivery organization s
EMR
,
presently
assumed to be
summaries like
ASTM s
Continuity of Care Record (CCR)
or
HL7 s
Continuity of
Care Document (CCD
),
is
owned by the patient
and has
patient input a
nd access that spans
episodes of care across multiple CDOs within a community
, region, or state (or in some countries,
©
2006 HIMSS Analytics
TM
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system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
the entire country)
.
The
EHR in the US
will ride on the proposed National Health Information
Network (NHIN
).
The EHR
can be established
only
if
the electronic medical records of
the
various CDOs
ha
ve
evolved to a level that can
create
and support a robust exchange of information between
stakeholders within a community or region. While some forms of early EHRs exist today in
limited environ
ments, it will be difficult to establish effective EHRs across the majority of the US
market until we have established clinical information transaction standards that can be easily
adopted by
the different
EMR
application architectures
now available.
Fu
rther differentiation between the EMR and EHR is defined in
Figure
1.
© 2005 HIMSS Analytics
The difference between EMR & EHR
Electronic Health Records
Subset (i.e. CCR or CCD) of
information from various CDOs
where patient has had
encounters
Owned by patient or
stakeholder
Community, state, or regional
emergence today (RHIOs)
-
or
nationwide in the future
Provides interactive patient
access as well as the ability for
the patient to append
information.
Connected by NHIN
Electronic Medical Records
The legal record of the CDO
A record of clinical services for
patient encounters in a CDO
Owned by the CDO
These systems are being sold
by enterprise vendors and
installed by hospitals, health
systems, clinics, etc.
May have patient access to
some results info through a
portal
but is not interactive
Does not contain other CDO
encounter information
Figure
1
A Closer Look at the EMR and EHR Environments
The EMR environment is a complex and sophist
icated environment (see Figure 2
). It
s
foundation
is
the
clinical data repository (CDR), a
real
-
time transaction processing
database
of
patient
clinical information for
practitioners
.
The controlled medical vocabulary (CMV)
is critical
because it
ensur
es
that the
practitioners
who
use the EMR are accessing
accurate
and comparable
data. The CMV normalizes data from a
relational and definitional hierarchy that enable
s
other components of the EMR to optimally
operate. Without a functional CMV, the clinical decision support system (CDSS) and workflow
components
of the EMR will not perform as expected by the clinicians in the environment.
The
applications
of the EMR environment
are clinical documentation
for all
clinicians/
practitioners
, computerized provid
er order entry
(CPOE)
for all clinicians/
practitioners
,
©
2006 HIMSS Analytics
TM
4
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
and pharmacy management.
We believe that the pharmacy management application has
transitioned from a departmental system to a
n application of
the EMR due to the influence of
patient safety/medical error reduction
concern
s.
A foundation of EMR application
s
,
required to improve patient safety and reduce or eliminate
medical errors
,
is composed of the
CDR,
CPOE, pharmacy management system, and the
electronic medication administration record (eMAR)
, functionality normally found in the
electronic clinical docu
mentation systems of most vendors
. Therefore, we believe that the
pharmacy management system
should
now be counted as an application of the EMR
environment.
©
2006 HIMSS Analytics
Documentation
CPOE
Pharmacy
Workflow
CDSS
CMV
EMR and EHR Environments
EMPI
Interface Engine
Interface Engine
Web Portal
NHIN/
EHR
NHIN/
EHR
Laboratory
Radiology
PACS
Transcription
Departmental
Systems
Doc. Imaging
Pat. Access
Billing/Coding
HR
Scheduling
ERP
Resource
Management
CDR
= EMR
Environment
Figure
2
These applications are tightly coupled with the CDR
data
schema and the
CMV, CDSS, and
workflow components. These EMR applications are designed and built on the same architecture
as the EMR components.
We believe
that CDOs need to establish a solid EMR foundation with
nursing adoption of CPOE and clinical docum
entation applications before physician CPOE use
can be effectively established.
The EHR environment
relies
on
functional
EMR
s
that allow
care delivery organizations
to
exchange data/information with other CDOs or stakeholders within the community, region
a
lly
, or
nationally.
As noted in the executive summary, s
takeholders are composed of patients/consumers,
healthcare providers,
employers, and/or payers/insurers
, including the government
. The
evolving
NHIN
standards are
integral
to establishing effective da
ta/information flows between CDOs and
stakeholders. Currently
,
few EHRs exist, but early prototypes include the EHR environments in
Santa Barbara, C
alif.
, and
Marion County, I
nd
iana
.
In the future, CDOs may utilize portlets
,
©
2006 HIMSS Analytics
TM
5
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
which can display relevant
cont
ent
to
provide information exchange
with their various
stakeholders.
1
EMR Adoption Model
:
A New EMR
Penetration Assessment
Tool
Understanding the level of EMR capabilities in hospitals
is a
challenge
in
the US healthcare IT
market today
.
HIMSS Analytics
has created a
n
EMR Adoption M
odel
that identifies the levels of
EMR capabilities ranging from the initial CDR
en
vironment through a paperless E
MR
environment.
HIMSS Analytics
ha
s
developed
a methodology
and algorithms
to automatically
score
the
approximat
ely 4,000
hospitals in our database
relative to their
IT
-
enabled
clinical
transformation status, to provide peer comparisons for CDOs as they strategize their path to a
complete EMR and participation in an EHR.
The stages of the model are as follows:
Stag
e 0:
Some clinical automation
may be
present, but
all three of
the major ancillary
department systems for laboratory, pharmacy, and radiology are not implemented.
Stage 1:
All three of t
he major ancillary clinical systems are installed (i.e., pharmacy,
la
boratory, radiology).
Stage 2:
Major ancillary clinical systems feed data to a clinical data repository (CDR)
that provides physician access for retrieving and reviewing results. The CDR contains a
controlled medical vocabulary, and the clinical decision
support/rules engine for
rudimentary conflict checking. Information from document imaging systems may be
linked to the CDR at this stage.
Stage 3:
Clinical documentation (e.g. vital signs, flow sheets)
is required;
nursing notes,
care plan charting, and/o
r the electronic medication administration record (eMAR)
system
are scored with extra points, and are
implemented and integrated with the CDR
for at least one service in the hospital. The first level of clinical decision support is
implemented to conduct e
rror checking with order entry (i.e., drug/drug, drug/food,
drug/lab conflict checking
normally found in the pharmacy
). Some level of medical
image access from picture archive and communication systems (PACS) is available for
access by physicians via the o
rganization s intranet or other secure networks
outside of
the radiology department confines
.
Stage 4:
Computerized
Practitioner
/Physician
Order Entry (CPOE) for use by any
clinician is added to the nursing and CDR environment along with the second level
of
clinical decision support capabilities related to evidence based medicine protocols. If one
patient service area has implemented CPOE and completed the previous stages, then this
stage has been achieved.
Stage 5:
The
closed loop medication administrat
ion environment
is fully implemented in
at least one patient care service area
.
The eMAR and bar coding or other auto
1
Introduction to JSR 168 The Java Portlet Specification
, White Paper, Sun Microsystems, 2003.
©
2006 HIMSS Analytics
TM
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system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
identification technology, such as radio frequency identification (RFID), are implemented
and
integrated with CPOE and pharmacy to maximiz
e point of care patient safety
processes for medication administration.
Stage 6:
Full physician documentation/charting
(structured templates)
is implemented for
at least one patient care service area. Level three of clinical decision support provides
gui
dance for all clinician activities related to protocols and outcomes in the form of
variance and compliance alerts. A full complement of
radiology
PACS systems provides
medical images to physicians via an intranet and displaces all film
-based images.
Sta
ge 7:
The hospital has a paperless EMR environment. Clinical information can be
readily shared via electronic transactions or exchange of electronic records with all
entities within a regional health network (i.e., other hospitals, ambulatory clinics, sub
-
acute environments, employers, payers and patients). This stage allows the
HCO to
support the true electronic health record as envisioned in the ideal model.
The majority of US hospitals are in the early stages of EM
R transformation. Currently 19
percent
of US hospitals have not achieve
d Stage 1 and are at Stage 0, 21 p
ercent have
achieved Stage 1, 5
0 p
ercent have achieved stage 2,
approximately eight
percent have
achieved stage 3,
approximately two
percent
percent have achieved Stage 4, and
less than
one
percent
of hospitals have achieved stage 5
and stage 6 (see Figure 3)
.
2006 HIMSS Analytics
TM
CDR, CMV, CDSS inference
engine, may have Document Imaging
Stage 2
Clinical documentation (flow sheets), CDSS
(error checking), PACS available outside Radiology
Stage 3
CPOE, CDSS (clinical protocols)
Stage 4
Closed loop medication administration
Stage 5
Physician documentation (structured templates), full
CDSS (variance & compliance), full PACS
Stage 6
Medical record fully electronic;
CDO able to contribute to EHR as byproduct of EMR
Stage 7
EMR Adoption Model
2005 Final
0.0%
0.1%
0.5%
1.9%
8.1%
49.7%
20.5%
Stage 1
Ancillaries
Lab, Rad, Pharmacy
Stage 0
All Three Ancillaries Not Installed
19.3%
% of US
Hospitals
Figure 3
The US EMR Market Today
: Challenges for EHRs
©
2006 HIMSS Analytics
TM
7
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
The majority of US hospitals are in the early stages of EMR
adoption
.
Currently
,
approximately
61
percent of the US hospital market has some level of
EMR
applications
installed to support care
delivery
(stage 2 or higher)
.
A further evaluation of the market shows the percentage of EMR
adoption
by stage (see Table
1
).
Stage
Hospitals In a Stage
% of 3917 Total Hospitals
Stage 0
754
19.25%
Stage 1
804
20.53%
Stage 2
1945
49.66%
Stage 3
318
8.12%
Stage 4
73
1.86%
Stage 5
18
0.46%
Stage 6
5
0.13%
Stage 7
0
0.00%
Total
3917
100.00%
Table
1
Table
1
shows that the vast majority of US hospitals have not transformed beyond stage 2 of the
EMR Adoption Model
.
It also shows that
19.25
% of American hospitals don t even have all three
ancillary systems
(
labo
ratory, radiology, and pharmacy)
instal
led, much less components of the
EMR.
It will be
impossible for those organizations to participate in an EHR initiative
in their
community or region
without manually entering
summary
care record information into the EHR
system.
Table
2
provides an overvie
w of the stage
1
hospitals.
Hospitals
with
400 beds
or fewer
represent
the majority of stage
1
hospitals, with a close approximation of percentages between the
respective segments. This is not surprising as this segment of the market represents approximate
ly
90 percent of hospitals in the US market. Most hospitals represented in the stage
1
demographic
are
integrated delivery systems (
IDS
s)
,
urban, general medical, and non
-
academic
hospitals
.
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2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
20.53%
of US Hospitals
Bedsize Category
% of Stage 1
Total Hospitals
% of Total
0-100
252
31%
1355
19%
101-200
223
28%
1019
22%
201-400
229
28%
1044
22%
401-600
72
9%
334
22%
>600
28
3%
165
17%
Total
804
100%
3917
21%
IDS?
% of Stage 1
Total Hospitals
% of Total
No
275
34%
1149
24%
Yes
529
66%
2768
19%
Urban?
% of Stage 1
Total Hospitals
% of Total
No
112
14%
605
19%
Yes
692
86%
3312
21%
Academic?
% of Stage 1
Total Hospitals
% of Total
No
751
93%
3599
21%
Yes
53
7%
318
17%
General Medical?
% of Stage 1
Total Hospitals
% of Total
No
90
11%
735
12%
Yes
714
89%
3182
22%
Table
2
The majority of stage 2 hospitals also included
hospitals of
400 bed
s or fewer
(see Table
3
). As
with stage 1 hospitals,
the majority of stage 2 hospitals are IDS, urban, general medic
al
, and non
-
academic hospitals.
©
2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
49.66%
of US Hospitals
Bedsize Category
% of Stage 2
Total Hospitals
% of Total
0-100
525
27%
1355
39%
101-200
564
29%
1019
55%
201-400
600
31%
1044
57%
401-600
169
9%
334
51%
>600
87
4%
165
53%
Total
1945
100%
3917
50%
IDS?
% of Stage 2
Total Hospitals
% of Total
No
559
29%
1149
49%
Yes
1386
71%
2768
50%
Urban?
% of Stage 2
Total Hospitals
% of Total
No
205
11%
605
34%
Yes
1740
89%
3312
53%
Academic?
% of Stage 2
Total Hospitals
% of Total
No
1773
91%
3599
49%
Yes
172
9%
318
54%
General Medical?
% of Stage 2
Total Hospitals
% of Total
No
284
15%
735
39%
Yes
1661
85%
3182
52%
Table
3
The demographics of stage 3 hosp
itals are shown in Table
4.
Hospitals
with between
201
-
400
bed
s
represent the majority of stage 3 hospitals. As with stages 1 and 2, the majority of hospitals
in stage 3 are IDS, urban, general medical, and non
-
academic hospitals.
©
2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
8.12%
of US Hospitals
Bedsize Category
% of Stage 3
Total Hospitals
% of Total
0-100
56
18%
1355
4%
101-200
83
26%
1019
8%
201-400
107
34%
1044
10%
401-600
53
17%
334
16%
>600
19
6%
165
12%
Total
318
100%
3917
8%
IDS?
% of Stage 3
Total Hospitals
% of Total
No
102
32%
1149
9%
Yes
216
68%
2768
8%
Urban?
% of Stage 3
Total Hospitals
% of Total
No
25
8%
605
4%
Yes
293
92%
3312
9%
Academic?
% of Stage 3
Total Hospitals
% of Total
No
287
90%
3599
8%
Yes
31
10%
318
10%
General Medical?
% of Stage 3
Total Hospitals
% of Total
No
43
14%
735
6%
Yes
275
86%
3182
9%
Table
4
Stage 4 hospitals show some interesting diversions from the other stages. While the majority of
hospitals are in the
101
-
200
bed size segment, the second leading segment of hospitals is the
201
-
400
bed range (see Table
5
). The demographics of t
he majority of these hospitals follow those of
the previous stages
:
IDS, urban, general medical, and non
-
academic hospitals.
©
2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
1.86%
of US Hospitals
Bedsize Category
% of Stage 4
Total Hospitals
% of Total
0-100
14
19%
1355
1%
101-200
16
22%
1019
2%
201-400
15
21%
1044
1%
401-600
12
16%
334
4%
>600
16
22%
165
10%
Total
73
100%
3917
2%
IDS?
% of Stage 4
Total Hospitals
% of Total
No
19
26%
1149
2%
Yes
54
74%
2768
2%
Urban?
% of Stage 4
Total Hospitals
% of Total
No
5
7%
605
1%
Yes
68
93%
3312
2%
Academic?
% of Stage 4
Total Hospitals
% of Total
No
44
60%
3599
1%
Yes
29
40%
318
9%
General Medical?
% of Stage 4
Total Hospitals
% of Total
No
37
51%
735
5%
Yes
36
49%
3182
1%
Table
5
The majority of stage 5 hospitals are in the 201
400 bed range, and the 401
600 bed hospit
als
represent the second largest number in this stage (see Table 6). The majority of these hospitals are
urban, academic, general medical, and belong to an IDS.
©
2006 HIMSS Analytics
TM
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ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
0.46%
of US Hospitals
Bedsize Category
% of Stage 5
Total Hospitals
% of Total
0-100
3
17%
1355
0%
101-200
3
17%
1019
0%
201-400
7
39%
1044
1%
401-600
4
22%
334
1%
>600
1
6%
165
1%
Total
18
100%
3917
0%
IDS?
% of Stage 5
Total Hospitals
% of Total
No
3
17%
1149
0%
Yes
15
83%
2768
1%
Urban?
% of Stage 5
Total Hospitals
% of Total
No
0
0%
605
0%
Yes
18
100%
3312
1%
Academic?
% of Stage 5
Total Hospitals
% of Total
No
14
78%
3599
0%
Yes
4
22%
318
1%
General Medical?
% of Stage 5
Total Hospitals
% of Total
No
5
28%
735
1%
Yes
13
72%
3182
0%
Table 6
Stage 6 hospital are almost equally distributed by bed size
, but currently there are more of these
hospitals in the <600 bed range (see Table 7). The hospitals are urban, part of an IDS, and are
slightly more academic and non
-
general medical.
©
2006 HIMSS Analytics
TM
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system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
0.13%
of US Hospitals
Bedsize Category
% of Stage 6
Total Hospitals
% of Total
0-100
1
20%
1355
0%
101-200
1
20%
1019
0%
201-400
1
20%
1044
0%
401-600
0%
334
0%
>600
2
40%
165
1%
Total
5
100%
3917
0%
IDS?
% of Stage 6
Total Hospitals
% of Total
No
0
0%
1149
0%
Yes
5
100%
2768
0%
Urban?
% of Stage 6
Total Hospitals
% of Total
No
1
20%
605
0%
Yes
4
80%
3312
0%
Academic?
% of Stage 6
Total Hospitals
% of Total
No
2
40%
3599
0%
Yes
3
60%
318
1%
General Medical?
% of Stage 6
Total Hospitals
% of Total
No
3
60%
735
0%
Yes
2
40%
3182
0%
Table 7
Conclusion
There are
a total of
754
acute
care
hospitals that have not
fully
implemented a base of
major
clinical
ancillary department
applications
(e.g.
,
laboratory, pharmacy, radiology)
to
qualify for
stage 1 designation
. This represents approximately 19
percent of the hospitals in the
database.
Most hospitals occupy the stage 1 and stage 2 levels of the
EMR Adoption Model
. The combined
percentage of hospitals in these two stages is approximately 71 percent.
At this time
,
there are only
414
US hospitals that are stage 3
-6
of the
EMR Ad
option Model
. This
shows the tremendous amount of work and investment that must be done by US hospitals to
implement clinical systems
to enable
their
participation in
EHR initiatives. More importantly,
further implementation of
higher stage EMR application
s
will enable the reduction or elimination
of medical errors, while providing the digital environment
. The higher stages of the model
represent the
facilita
tion
of
not only improved patient care, but
also
improvements in efficiency
and effectiveness with
which
patient care services are
delivered by clinicians
.
Once we begin to deliver these capabilities within the healthcare organizations
,
we can begin to
focus on sharing patient care information among all of the healthcare stakeholders. Currently
, the
©
2006 HIMSS Analytics
TM
14
All rights reserved. No part of this paper may be reproduced, adapted, translated, stored in a retr
ieval
system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or
otherwise, without the prior written permission of HIMSS Analytics
.
Source: HIMSS Analytics Database (derived from the Dorenfest IHDS+ Database
TM
)
hype surrounding healthcare IT
has the
cart before the horse
.
How can we discuss the potential
of EHRs
, much less implement them,
until we have implemented effective EMR
s,
not only in
hospitals, but
in all care delivery organizations including physician
practices
?