Footnote 5 Publication

A Cost-Benefit Analysis of Electronic Medical
Records in Primary Care
Samuel J. Wang, MD, PhD, Blackford Middleton, MD, MPH, MSc, Lisa A. Prosser, PhD,
Christiana G. Bardon, MD, Cynthia D. Spurr, RN, MBA, Patricia J. Carchidi, RN, MSN,
Anne F. Kittler, Robert C. Goldszer, MD, MBA, David G. Fairchild, MD, MPH,
Andrew J. Sussman, MD, MBA, Gilad J. Kuperman, MD, PhD, David W. Bates, MD, MSc
PURPOSE: Electronic medical record systems improve the
quality of patient care and decrease medical errors, but their
financial effects have not been as well documented. The purpose
of this study was to estimate the net financial benefit or cost of
implementing electronic medical record systems in primary
care.
METHODS: We performed a cost-benefit study to analyze the
financial effects of electronic medical record systems in ambulatory primary care settings from the perspective of the health
care organization. Data were obtained from studies at our institution and from the published literature. The reference strategy
for comparisons was the traditional paper-based medical
record. The primary outcome measure was the net financial
benefit or cost per primary care physician for a 5-year period.
RESULTS: The estimated net benefit from using an electronic

medical record for a 5-year period was $86,400 per provider.
Benefits accrue primarily from savings in drug expenditures,
improved utilization of radiology tests, better capture of
charges, and decreased billing errors. In one-way sensitivity
analyses, the model was most sensitive to the proportion of
patients whose care was capitated; the net benefit varied from a
low of $8400 to a high of $140,100. A five-way sensitivity analysis with the most pessimistic and optimistic assumptions
showed results ranging from a $2300 net cost to a $330,900 net
benefit.
CONCLUSION: Implementation of an electronic medical
record system in primary care can result in a positive financial
return on investment to the health care organization. The magnitude of the return is sensitive to several key factors. Am J
Med. 2003;114:397– 403. ©2003 by Excerpta Medica Inc.

E

gesting that electronic medical records provide financial
benefits by helping to reduce costs and improve revenues
(11–26), few formal cost-benefit analyses have been
done. Because their widespread adoption will depend in
part on the ability to make a business case for financial
benefits to the health care organization, we performed a
formal cost-benefit analysis of implementing an electronic medical record system.

lectronic medical record systems have the potential
to provide substantial benefits to physicians, clinic
practices, and health care organizations. These systems can facilitate workflow and improve the quality of
patient care and patient safety (1– 4). Application of information technology has been identified by the Institute
of Medicine as one of the principal ways to improve the
quality of health care (5). Because of these benefits, the
Leapfrog Group (6), a coalition of the nation’s largest
employers, is considering making use of outpatient electronic medical records its next standard for health care
purchasing contracts.
In several other countries, use of electronic medical
records ranges from 50% to 90% (7–9). In the United
States, however, adoption of electronic medical records
has been slow, and only about 7% of physicians use them
(10). The cost of implementation is often cited as a barrier
to their use. Although there are anecdotal reports sugFrom the Department of Information Systems (SJW, BM, CDS, PJC,
AFK, GJK, DWB), Partners HealthCare System, Boston, Massachusetts;
Division of General Medicine and Primary Care (BM, CGB, RCG, DGF,
AJS, GJK, DWB), Brigham and Women’s Hospital, Boston, Massachusetts; and Department of Ambulatory Care and Prevention (LAP), Harvard Medical School and Harvard Pilgrim Health Care, Boston, Massachusetts.
Requests for reprints should be addressed to Samuel J. Wang, MD,
PhD, Partners HealthCare System, 93 Worcester Street, Wellesley, Massachusetts 02481, or [email protected].
Manuscript submitted May 13, 2002, and accepted in revised form
December 3, 2002.
©2003 by Excerpta Medica Inc.
All rights reserved.

METHODS
Study Design
We performed a cost-benefit analysis of electronic medical record usage by primary care physicians in an ambulatory-care setting. The primary outcome measure was
net financial costs or benefits per provider during a 5-year
period. The model was framed from the perspective of the
health care organization, and the reference strategy was
the traditional paper-based medical record. All costs and
benefits were converted to 2002 U.S. dollars (27).
Data on costs and benefits came from primary data
collected from our electronic medical record system,
from other published studies, and from expert opinion.
When data were not available, expert opinion was obtained using a modified Delphi (28) technique to arrive at
group consensus with a 7-member expert panel. Primary
data were obtained from several internal medicine clinics
using our internally developed electronic medical record
0002-9343/03/$–see front matter 397
doi:10.1016/S0002-9343(03)00057-3

A Cost-Benefit Analysis of Electronic Medical Records/Wang et al

Table 1. Costs of Electronic Medical Record System Used in the Model (Per Provider in 2002 U.S.
Dollars)
Base Case
System costs
Software (annual license)
Implementation
Support and maintenance
Hardware (3 computers ⫹ network)
Induced costs
Temporary productivity loss

$1600
$3400
$1500
$6600
$11,200

Sensitivity Analysis
(Range)
$ 800–$3200

Reference
*
†

$ 750–$3000
$3300–$9900

*
*

$5500–$16,500

*

* Data from Partners HealthCare System, Boston, Massachusetts.
†
B. Middleton, MD, MPH, MSc, MedicaLogic, written communication, 1998.

system (29) at Partners HealthCare System, an integrated
delivery network formed in 1994 by the Brigham and
Women’s Hospital and the Massachusetts General Hospital.
We constructed a hypothetical primary care provider
patient panel using average statistics from our institution.
This panel included 2500 patients, 75% of whom were
under 65 years of age; 17% of patients under 65 years old
belonged to capitated plans. In sensitivity analyses, panel
size was varied from 2000 to 3000 patients, and the proportion of patients under the age of 65 years whose cases
were capitated was varied from 0% to 28.7%. According
to industry estimates, health maintenance organization
enrollment was 28.7% of the U.S. population in 2000
(30,31).

Costs
There are two categories of costs associated with electronic medical record implementation: system costs and
induced costs (Table 1). System costs include the cost of
the software and hardware, training, implementation,
and ongoing maintenance and support. Induced costs are
those involved in the transition from a paper to electronic
system, such as the temporary decrease in provider productivity after implementation.
The software costs of $1600 per provider per year were
based on the costs for our electronic medical record system at Partners HealthCare on an annual per-provider
basis (as an “application service provider” model); this
figure includes the costs of the design and development of
the system, interfaces to other systems (e.g., registration,
scheduling, laboratory), periodic upgrades, and costs of
user accounts for support staff. Although these software
costs were based on our internally developed system, they
are consistent with license fees for commercially available
systems, which have been estimated at between $2500
and $3500 per provider for the initial software purchase,
plus annual maintenance and support fees of 12% to 18%
(K. MacDonald, First Consulting Group, Lexington,
Massachusetts, written communication, 1999). In sensi398

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tivity analyses, software costs were varied from 50% to
200% of the base value.
Implementation costs, estimated at $3400 per provider
in the first year, included workflow process redesign,
training, and historical paper chart abstracting. Ongoing
annual maintenance and support costs were estimated to
be $1500 per provider per year and included the costs of
additional technical support staff and system/network
administration.
Hardware costs were calculated to be $6600 per provider for three desktop computers, a printer, and network
installation. We assumed that hardware would be replaced every 3 years.
Based on our experience, we modeled the induced
costs of temporary loss of productivity using a decreasing
stepwise approach, assuming an initial productivity loss
of 20% in the first month, 10% in the second month,
and 5% in the third month, with a subsequent return
to baseline productivity levels. Using the average annual
provider revenues for our model patient panel, this
amounted to a revenue loss of $11,200 in the first year.

Benefits
Financial benefits included averted costs and increased
revenues. We obtained figures for average annual expenditures for a primary care provider at our institution before the implementation of an electronic medical record,
and applied to this the estimated percentage cost savings
after implementation (Table 2). For each item, the estimated savings was varied across the indicated range of
values in the sensitivity analysis. Benefits were divided
into three categories: payer-independent benefits, benefits under capitated reimbursement, and benefits under
fee-for-service reimbursement (32– 40).
Payer-independent benefits, which apply to both capitated and fee-for-service patients, come from reductions
in paper chart pulls and transcription. The average cost of
a chart pull at our institution is approximately $5, accounting for the time and cost of medical records personnel to retrieve and then re-file a paper chart. After con-

A Cost-Benefit Analysis of Electronic Medical Records/Wang et al

Table 2. Annual Expenditures Per Provider (in 2002 U.S. Dollars) before Electronic Medical Record System Implementation and
Expected Savings after Implementation
Annual Expenditures before
Implementation

Payer independent
Chart pulls
Transcription
Capitated patients
Adverse drug events
Drug utilization
Laboratory utilization
Radiology utilization
Fee-for-service patients
Charge capture
Billing errors

Expected Savings after Implementation

Amount

Reference

Base Case
Estimated Savings

Sensitivity Analysis
(Range)

Reference

$5 (per chart)
$9600

*
*

600 charts
28%

300–1200
20%–100%

*
*,32

$6500
$109,000
$27,600
$59,100

33–36

34%
15%
8.8%
14%

10%–70%
5%–25%
0–13%
5%–20%

$383,100
$9700

†

2% (increase)
78%

1.5%–5%
35%–95%

†
†
†

†

‡
‡

37–39
‡

25,40
‡

* Primary data from the Partners HealthCare Electronic Medical Record System, Boston, Massachusetts.
†
From the Department of Finance, Brigham and Women’s Hospital, Partners HealthCare System.
‡
Expert panel consensus.

version to the electronic medical record system, chart
pulls can be reduced by 600 charts (range, 300 to 1200)
per year, based on the experience at one Partners HealthCare clinic. Transcription costs were reduced by 28%
from partial elimination of dictation. In the sensitivity
analysis, we varied the savings from 20% to 100% based
on the experiences from other implementations (32).
Benefits under capitated reimbursement accrue to the
practice and health care organization primarily from
averted costs as a result of decreased utilization. Clinical
decision support alerts and reminders can decrease utilization by reducing adverse drug events, offering alternatives to expensive medications, and reducing the use of
laboratory and radiology tests (37–39,41– 44). The expert
panel consensus was that adverse drug events would be
reduced by approximately 34% (range, 10% to 70%) as a
result of basic medication decision support. We used
standard financial benchmarks (33–35) to assign baseline
costs for adverse drug events, which took into account
additional outpatient visits, prescriptions, and admissions due to adverse drug events (36).
The expert panel estimated that alternative drug suggestion reminders would save 15% (range, 5% to 25%) of
total drug costs per year, and this was applied to the baseline annual drug expenditures for the capitated patients
in the panel. We estimated that laboratory charges could
be reduced by 8.8% (range, 0 to 13%) using decision support (37–39). Based on information from other studies,
the expert panel estimated that decision support for radiology ordering would achieve average savings of 14%
(range, 5% to 20%).
Benefits under fee-for-service reimbursement included increased revenue and reduced losses. Computer-

izing the encounter form process can improve the capture of in-office procedures that were performed but not
documented. Based on other studies (25,40), we projected a 2% improvement in billing capture (range, 1.5%
to 5%). By using an electronic medical record system that
either supplies or prompts for certain required fields, billing error losses can be reduced. The expert panel estimated that computerizing the encounter form could decrease these errors by 78% (range, 35% to 95%).

Statistical Analysis
We assumed that initial costs would be paid at the beginning of year 1 and that benefits would accrue at the end of
each year (Table 3). We assumed a phased implementation, in which only basic electronic medical record features were available in the first years (e.g., medicationrelated decision support), and more advanced features
were added in subsequent years (e.g., laboratory, radiology, and billing benefits). The primary outcome measure
was net benefit or cost per primary care provider. A discount rate of 5% was used in the base case and varied
from 0% to 10% in the sensitivity analysis.
One-way and two-way sensitivity analyses were performed using the ranges shown in Tables 1 and 2. Twoway sensitivity analyses were performed using all combinations of the five most important variables identified in
the one-way sensitivity analysis, and with pairwise combinations of one benefit variable with each of the three
primary cost variables (software, hardware, and support).
A five-way sensitivity analysis was performed using the
most and least favorable conditions for the five variables.
The time horizon was also varied from 2 to 10 years.
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A Cost-Benefit Analysis of Electronic Medical Records/Wang et al

Table 3. 5-Year Return on Investment Per Provider for Electronic Medical Record Implementation
Initial Cost
Costs
Software license (annual)
Implementation
Support
Hardware (refresh every 3 years)
Productivity loss
Annual costs
Present value of annual costs*
Benefits
Chart pull savings
Transcription savings
Prevention of adverse drug events
Drug savings
Laboratory savings
Radiology savings
Charge capture improvement
Billing error decrease
Annual benefits
Present value of annual benefits*
Net benefit (cost)
Present value of net benefit (cost)*

$1600
$3400
$1500
$6600

Year 1

Year 2

Year 3

Year 4

Year 5

$1600

$1600

$1600

$1600

$1600

$1500

$1500

$1500
$6600

$1500

$1500

$14,300
$13,619

$3100
$2812

$9700
$8379

$3100
$2550

$3100
$2429

$3000
$2700

$3000
$2700
$2200
$16,400

$3000
$2700
$2200
$16,400

$3000
$2700
$2200
$16,400
$2400
$8300
$7700
$7600

$3000
$2700
$2200
$16,400
$2400
$8300
$7700
$7600

$5700
$5429
$(8600)
$(8190)

$24,300
$22,041
$21,200
$19,229

$24,300
$20,991
$14,600
$12,612

$50,300
$41,382
$47,200
$38,832

$50,300
$39,411
$47,200
$36,982

Total

$11,200
$13,100
$13,100

$(13,100)
$(13,100)

$46,400
$42,900

$154,900
$129,300
$108,500
$86,400

* Assumes a 5% discount rate.

To account for variations in functionality among different systems, we constructed two additional models in
which only subsets of the full functionality were included
(Table 4). The “light” electronic medical record system
included savings from chart pulls and transcriptions
only, whereas the “medium” system also included benefits from electronic prescribing (adverse drug event prevention and drug expenditure savings).

RESULTS
In the 5-year cost-benefit model (Table 3), the net benefit
of implementing a full electronic medical record system
was $86,400 per provider. Of this amount, savings in drug

expenditures made up the largest proportion of the benefits (33% of the total). Of the remaining categories, almost half of the total savings came from decreased radiology utilization (17%), decreased billing errors (15%),
and improvements in charge capture (15%).

Sensitivity Analyses
The model was most sensitive to variations in the proportion of patients in capitated health plans; the net benefit
varied from $8400 to $140,100 (Figure). The model was
least sensitive to variations in laboratory savings, in which
the net benefit ranged from $82,500 to $88,300.
In two-way sensitivity analyses, the pair of input variables that yielded the least favorable outcome was a low
proportion of capitated patients and a high discount rate;

Table 4. Effect of Electronic Medical Record Feature Set Variations on Net Benefits
Feature
Online patient charts
Electronic prescribing
Laboratory order entry
Radiology order entry
Electronic charge capture

Benefit

Light EMR

Medium EMR

Full EMR

Chart pull savings
Transcription savings
Adverse drug event prevention
Alternative drug suggestions
Appropriate testing guidance
Appropriate testing guidance
Increased billing capture
Decreased billing errors

⫹
⫹

⫹
⫹
⫹
⫹

($18,200)

$44,600

⫹
⫹
⫹
⫹
⫹
⫹
⫹
⫹
$86,400

Net benefits (costs):
EMR ⫽ Electronic Medical Record.
400

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A Cost-Benefit Analysis of Electronic Medical Records/Wang et al

Figure. Tornado diagram showing the one-way sensitivity analysis of net 5-year benefits per provider. Each bar depicts the overall
effect on net benefits as that input is varied across the indicated range of values, while other input variables are held constant. The
vertical line indicates the base case.

the net benefit range was as low as $3000 per provider.
The pair that had the most favorable outcome was a high
proportion of capitated patients and greater savings from
drug suggestions; the net benefit was as high as $202,200
per provider. For the two-way sensitivity analyses performed with the three primary cost variables, the pair of
variables that yielded the least favorable outcome was a
low proportion of capitated patients and a high annual
software license (net cost of $200 per provider), and the
pair with the most favorable outcome was a high proportion of capitated patients and a low hardware cost (net
benefit of $146,200 per provider).
In the five-way sensitivity analyses, when the most pessimistic assumptions were made, the model showed a net
cost of $2300 per provider. When the most optimistic
assumptions were used, this analysis yielded a net benefit
of $330,900 per provider.
When the time horizon was reduced to 2 years instead
of 5 years, the net cost was $2100 per provider, and when
the time horizon was lengthened to 10 years, the net benefit was $237,300 per provider.
For the “light” electronic medical record, in which the
system is used only to reduce paper chart pulls and transcription costs, the net cost was $18,200 per provider (Table 4). For the “medium” electronic medical record, in
which benefits from electronic prescribing are added, the
net benefit was $44,600 per provider.

DISCUSSION
Our analysis indicates that the net financial return to a
health care organization from using an ambulatory electronic medical record system is positive across a wide

range of assumptions. The primary areas of benefit are
from reductions in drug expenditures, improved utilization of radiology tests, improvements in charge capture,
and decreased billing errors. Benefits increase as more
features are used and as the time horizon is lengthened. In
sensitivity analyses, the net return was positive except
when the most pessimistic assumptions were used.
Savings to the health care organization are obtained
under both capitated and fee-for-service reimbursement,
but these savings depend on the reimbursement mix: the
greater the proportion of capitated patients, the greater
the total return. Among fee-for-service patients, a large
portion of the savings from improved utilization may accrue to the payer instead of the provider organization. As
a result, payers may be motivated to offer incentives to
providers to use an electronic medical record to help control costs. In addition, although full capitation appears to
be less prevalent now than several years ago, with the
continued rise in health care expenditures, other types of
risk-sharing arrangements are likely to become more
common in the future (45), such as partial capitation, risk
pools, and pharmacy withholds.
We used conservative estimates of cost savings from an
electronic medical record. For example, one clinic was
able to reduce chart pulls by 60% to 70% and its medical
records staff by 50%, for an annual savings of about $4000
per provider (15). Others have identified even larger savings from the use of drug suggestions for certain classes of
medications (46). In one outpatient clinic, display of formulary information at the time of ordering lowered drug
costs by up to 26% (M. Overhage, MD, Regenstrief Institute, Indianapolis, Indiana, written communication,
2001). Savings due to prevention of adverse drug events
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A Cost-Benefit Analysis of Electronic Medical Records/Wang et al

in the model did not include costs of malpractice settlements, injury to patients, or decreased quality of life for
patients, so the actual savings may be higher. We may
have also underestimated future cost savings because the
model did not account for the annual growth rate of expenditures, which may outpace inflation in some categories, such as in drug and radiology costs.
Other potential areas of savings were not included in
the model because adequate data were not available.
These include savings in malpractice premium costs (40),
storage and supply costs (47), generic drug substitutions
(48), increased provider productivity (19,23,24), decreased staffing requirements (23,24,49), increased reimbursement from more accurate evaluation and management coding, and decreased claims denials from inadequate medical necessity documentation.
Although we accounted for a temporary (3-month)
loss of productivity in our model, some providers may
have a longer period of reduced productivity. To measure
this effect, we performed a sensitivity analysis that included a prolonged 10% productivity loss for 12 months
and found that there was still a 5-year net benefit of
$57,500 per provider.
This study has several limitations. The cost-benefit
model was based on primary data from our institution,
estimates from published literature, and expert opinion.
The effectiveness of some of these interventions has been
demonstrated in the inpatient setting, but outpatient effectiveness is less certain. There may be other costs associated with implementation of an electronic medical
record. For example, system integration costs may be
greater at other institutions, depending on the number
and complexity of system interfaces that are required.
However, the majority of benefits in this model can be
obtained even with a minimal number of interfaces (i.e.,
registration, scheduling, and transcription). In addition,
there may be other unforeseen expenses associated with
clinic workflow process redesign, reassignment of clinic
staff, or productivity loss during unscheduled computer
system or network outages.
In most cases, clinical decision support features will
decrease utilization by suggesting more appropriate testing. This leads to cost savings among capitated patients,
but it could also have an adverse effect on revenues from
fee-for-service patients that may offset billing improvements. The overall net effect would depend on the mix of
capitated versus fee-for-service patients.
Our cost-benefit model was geared toward primary
care providers. Diagnostic test utilization may be higher
for specialists, so there may be more opportunities for
cost-saving interventions. On the other hand, specialists
may be less likely to comply with computer reminders
recommending alternative medications or tests.
This study was framed from the perspective of the
health care organization to aid in making decisions about
402

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implementation of an electronic medical record. It may
also be worthwhile to take the societal perspective, which
would include benefits to payers and patients. For example, despite the trend away from global risk capitation,
payers are moving toward patient cost-sharing approaches, such as differential co-payments, high deductible options, and health savings accounts. With these
types of arrangements, patients may prefer to seek care
with providers who use electronic medical records to
control costs and improve quality of care.
Not all benefits of an electronic medical record are
measurable in financial terms; other benefits include improved quality of care, reduced medical errors, and better
access to information (2,3,50 –54). A cost-benefit analysis
is only one part of a complete analysis of the effects of
implementing an electronic medical record system. At
our institution, the electronic medical record is a key
component of a strategic goal of clinical system integration to allow providers to move between sites in the network to deliver seamless care at the most appropriate primary, secondary, or tertiary care location.
Based on a combination of savings data from our institution and projections from other published studies,
we conclude that implementing an ambulatory electronic
medical record system can yield a positive return on investment to health care organizations. The magnitude
and timing of this financial return varies, but is positive in
the long run across a wide range of assumptions. Because
of their quality and cost benefits, electronic medical
records should be used in primary care, and incentives to
accelerate their adoption should be considered at the national level.

ACKNOWLEDGMENT
We would like to thank Marc Overhage, MD, Homer Chin,
MD, Barry Blumenfeld, MD, and Tejal Gandhi, MD, who
joined three of the coinvestigators to serve on our expert panel.

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