Study Data And Methods
Here we summarize the methodologies we used to estimate the current adoption of
EMR systems and the potential savings, costs, and . health and safety benefits
Estimation of current HIT adoption and related factors.Our primary data source ★
was the Healthcare Information and Management Systems Society (HIMSS)–
Dorenfest survey, which represents a broad canvassing of acute care hospitals,
chronic care facilities, and ambulatory practices on their adoption and plans to adopt
various HIT components.Our lower-bound estimate of HIT adoption assumed an
integrated system that had an EMR, clinical decision support, and a central data
.repository—from the same vendor to ensure interoperability
Estimation of potential HIT efficiency savings. We conducted a broad literature ★
survey to capture evidence of HIT effects. The survey was primarily from peer-reviewed
literature, but it included some information from non-peer-reviewed literature. Expert
opinion was used to validate some of this evidence.we describe our results only as
“potential.” However, we do not believe that they represent the “best-case scenario,” for
:three reasons
We have not included many other effects (such as transaction savings, (1)
reductions in malpractice costs, and research and public health savings), and
there may be more sizable savings from HIT-motivated health care changes that
we are not able to predict: Modern EMR systems may be more effective than the
legacy systems reporting evidence; (2) we have not included certain domains
such as long-term care; and (3) we do not report possible values above the
mean. The results are not worst-case, either. We chose to interpret reported
evidence of negative or no effect of HIT as likely being attributable to ineffective
.or not-yet-effective implementation
Estimating the costs of adoption. For hospital adoption, we built a model of ★
EMR system costs based on the literature and on information supplied directly
to us from hospitals. Our data allowed us to relate hospital adoption costs to
size and operating expenses of hospitals and generally represented the
adoption of newer, more complete EMR systems, including clinical decision
support and computerized physician order entry (CPOE). Starting with current
adoption rates of EMR systems, we simu-lated ten-and fifteen-year adoption
periods, in which physicians’ choices were approximated by random selections
from the ambulatory EMR list, and hospitals adopted systems and paid costs
.consistent with our data related to size and operating expenses
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Estimating potential safety benefits.Using medication error and adversedrug event ★
rates from the literature, as well as limited evidence of COPE's reduction of medication
error rates, we extrapolated these potential safety benefits to a future with broad
national adoption of CPOE. Using the 2000 National Ambulatory Medical Care Survey
(NAMCS) database on office visits, we extrapolated the effects to full national adoption
and show the likely distribution of possible savings and adverse drug events avoided
.as a function of practice characteristics and size
Estimating other potential health benefits.We considered two kinds of ★
interventions—disease prevention and chronic disease management—that
would exploit key features of HIT. We applied recommended disease
management and prevention interventions to appropriate members of that
population. We report the health benefits and savings associated with various
degrees of patient participation in these programs, as might be obtained with
.HIT support