JMIR MEDICAL INFORMATICS

Slight et al

Original Paper

Meaningful Use of Electronic Health Records: Experiences From
the Field and Future Opportunities
Sarah Patricia Slight1,2, MPharm, PhD, PGDip; Eta S Berner3, EdD; William Galanter4, MS, MD, PhD; Stanley Huff5,6,
MD; Bruce L Lambert7, PhD; Carole Lannon8,9, MD, MPH; Christoph U Lehmann10, MD, FAAP, FACMI; Brian J
McCourt11, BA; Michael McNamara12, MD; Nir Menachemi13, MPH, PhD; Thomas H Payne14, MD; S Andrew
Spooner15, MD, MS, FAAP; Gordon D Schiff2,16, MD; Tracy Y Wang11, MD, MHS, MSc; Ayse Akincigil17, PhD;
Stephen Crystal17, PhD; Stephen P Fortmann18, MD; Meredith L Vandermeer18, MPH; David W Bates2,16, MD, MSc
1

Division of Pharmacy, School of Medicine Pharmacy and Health, Durham University, Durham, United Kingdom

2

The Centre for Patient Safety Research and Practice, Division of General Internal Medicine, Brigham and Womens Hospital, Boston, MA, UnitedStates3

Center for Health Informatics for Patient Safety/Quality, Department of Health Services Administration, University of Alabama at Birmingham,
Birmingham, AL, United States
4

University of Illinois at Chicago, Chicago, IL, United States

5

Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States

6

Intermountain Healthcare, Salt Lake City, UT, United States

7

Center for Communication and Health, Department of Communication Studies, Northwestern University, Chicago, IL, United States

8

James M Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States

9

Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States

10

Pediatrics and Biomedical Informatics, Vanderbilt University, Nashville, TN, United States

11

Duke Clinical Research Institute, Duke University, Durham, NC, United States

12

Departments of Pediatrics and Medical Informatics (DMI), Northwest Permanente, Portland, OR, United States

13

Richard M Fairbanks School of Public Health, Indiana University, Indianapolis, IN, United States

14

Department of Medicine, University of Washington, Seattle, WA, United States

15

Division of Biomedical Informatics, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States

16

Harvard Medical School, Boston, MA, United States

17

Institute for Health, Health Care Policy, and Aging Research, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States

18

Center for Health Research, Kaiser Permanente Northwest, Portland, OR, United States

Corresponding Author:
David W Bates, MD, MSc
The Centre for Patient Safety Research and Practice
Division of General Internal Medicine
Brigham and Womens Hospital
1620 Tremont Street
Boston, MA, MA 02120-1613
United States
Phone: 1 617 732 5650
Fax: 1 617 732 7072
Email: dbates@partners.org
Related Article:
This is a corrected version. See correction statement in: http://medinform.jmir.org/2015/3/e32/

Abstract
Background: With the aim of improving health care processes through health information technology (HIT), the US government
has promulgated requirements for “meaningful use” (MU) of electronic health records (EHRs) as a condition for providers
receiving financial incentives for the adoption and use of these systems. Considerable uncertainty remains about the impact ofthese requirements on the effective application of EHR systems.
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Slight et al

Objective: The Agency for Healthcare Research and Quality (AHRQ)-sponsored Centers for Education and Research in
Therapeutics (CERTs) critically examined the impact of the MU policy relating to the use of medications and jointly developed
recommendations to help inform future HIT policy.
Methods: We gathered perspectives from a wide range of stakeholders (N=35) who had experience with MU requirements,
including academicians, practitioners, and policy makers from different health care organizations including and beyond the
CERTs. Specific issues and recommendations were discussed and agreed on as a group.
Results: Stakeholders’ knowledge and experiences from implementing MU requirements fell into 6 domains: (1) accuracy of
medication lists and medication reconciliation, (2) problem list accuracy and the shift in HIT priorities, (3) accuracy of allergy
lists and allergy-related standards development, (4) support of safer and effective prescribing for children, (5) considerations forrural communities, and (6) general issues with achieving MU. Standards are needed to better facilitate the exchange of data
elements between health care settings. Several organizations felt that their preoccupation with fulfilling MU requirements stifled
innovation. Greater emphasis should be placed on local HIT configurations that better address population health care needs.
Conclusions: Although MU has stimulated adoption of EHRs, its effects on quality and safety remain uncertain. Stakeholders
felt that MU requirements should be more flexible and recognize that integrated models may achieve information-sharing goals
in alternate ways. Future certification rules and requirements should enhance EHR functionalities critical for safer prescribingof medications in children.
(JMIR Med Inform 2015;3(3):e30) doi: 10.2196/medinform.4457
KEYWORDS
medical informatics; health policy; electronic health records; meaningful use

Introduction
The Health Information Technology for Economic and Clinical
Health (HITECH) Act was signed into law on February 17,
2009 with the commitment of substantial financial resources toexpand the use of electronic health records (EHRs) and greathopes of promoting improvements in the efficiency of healthcare for all Americans. This effort is being led by the Centers
for Medicare & Medicaid Services (CMS) and the Office of the
National Coordinator for Health Information Technology (ONC)at the US Department of Health and Human Services (HHS)[1,2]. As a condition for clinicians and hospitals to receive
incentive payments, they needed to use certified EHRs in ameaningful manner (ie, “meaningful use” [MU]). Morespecifically, this involved using EHRs to improve quality, safety,
and efficiency; reduce health disparities; engage patients andfamily in their health; improve care coordination and populationand public health; and maintain privacy and security of patient
health information [3].
The CMS EHR incentive programs have included 3 stages todate, each with its own specific objectives, measures, andstandards. The final rules for MU Stage 1, which specify thecriteria that eligible professionals and hospitals need to meet toqualify for incentives, went into effect on September 26, 2010.
The rules defined 15 core and 10 menu-set objectives that
focused on providers capturing and sharing patient data. The
onset of MU Stage 2 criteria was delayed until 2014 andconcentrated on advanced clinical processes and more rigorous
health information exchange (HIE). Specific to the Stage 2
objectives was the expectation that patients would be provided
with secure online access to their health information. The Health
Information Technology Policy Committee (HITPC), which
advises the government on its EHR incentive program, submitted
its preliminary recommendations for MU Stage 3 to the ONC
in early 2013. As part of the federal rule-making process, thesepreliminary Stage 3 recommendations were released for public
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comment and generated a high volume of responses [4]. These
responses play a key role in informing the future direction of
MU and related health information technology (HIT) policies,
with Stage 2 now extended through to 2016 and Stage 3scheduled to begin in 2017. At this time, relatively little has
been published about professionals’ experiences with
implementing the Stage 2 requirements. A large number of thesecore measures are associated with the entering, recording, orordering of medicines. Our goals were to examine critically the
impact of MU to date, both experiences with Stage 2 andreactions to Stage 3 recommendations, with a particular focus
on medication requirements along with related broader policy
and implementation issues. We used this information to develop
a set of recommendations to help inform future policies.

Methods
We gathered the perspectives of a wide range of professionals(N=35) representing academicians, practitioners, policy makers,
and senior management officials identified through the CERTs,
henceforth referred to as “stakeholders.” Stakeholders initially
met in June 2014 as part of the national CERT steeringcommittee meeting to discuss the purpose and content of thisdocument and included representatives from different healthcare and academic organizations including: Agency for
Healthcare Research and Quality (AHRQ) (n=5), Kaiser
Permanente (n=4), Brigham and Women’s Hospital (n=3),
Cincinnati Children’s Hospital Medical Center (n=2), Food andDrug Administration (FDA) (n=2), Duke University (n=3),
Rutgers University (n=2), University of Alabama at Birmingham(n=2), Intermountain Healthcare (n=1), University of Illinois
at Chicago (n=1), Northwestern University (n=1), Universityof Washington (n=1), University of Maryland (n=1), Baylor
Scott and White Health (n=1), Baylor College of Medicine(n=1), Blue Cross Blue Shield Association (n=1), and a variety
of others (n=4). A number of stakeholders occupied roles suchas Chief Medical Information Officer or Chief Medical
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Informatics Officer in their respective health care organizations.
A number of open-ended questions were posed to the group
including:
•
•
•
•
•

What were your experiences of implementing Stage 2 MU
requirements?
What key challenges did you face?
How were these challenges overcome (or could they beovercome in the future)?
What are your thoughts on the proposed Stage 3
recommendations?
Do you think there were any important areas omitted in the
proposed Stage 3 recommendations?

Specific issues and recommendations were presented, discussed,
and agreed on as a group. Some of these issues that were agreed
on by the stakeholders have been documented and supported
by relevant literature. We used the principles of consensus
decision making; all stakeholders were (1) involved in the group
discussions (inclusive), (2) encouraged to contribute opinions
and suggestions (participatory), (3) given the opportunity tobuild on one another’s suggestions (collaborative), (4) afforded
equal input into the process (egalitarian), and (5) allowed tovoice any particular concerns that they may have so that thegroup could incorporate them into the emerging domains(cooperative). These include, for example, how organizational
differences in the delivery of health care could impact
stakeholders’ ability to achieve MU requirements, challenges
and opportunities for rural communities, and how EHRs could
be improved to support safer and more effective prescribing forchildren. The public commentary available on the government
website was reviewed to help inform these discussions [4]. A
summary of the key findings were presented to the group as anoral presentation (via a webinar) in January 2015 and aconcerted attempt was made to reach full agreement on the key
domains (principle of agreement seeking). All stakeholders had
the opportunity to provide feedback both verbally andelectronically, and all feedback was incorporated. The
stakeholders were convened for a second face-to-face meetingat the start of March 2015 and gave their final approval to themanuscript’s content and recommendations. All authors listedon this manuscript participated in these meetings. In the sections
that follow, we discuss these 6 domains, which include someof the key objective(s) on which the HITPC requested commentand the HITPC identification number to facilitatecross-referencing.

Results
Accurate Medication Lists and Medication
Reconciliation
When a patient is transferred from one health care setting orprovider to another, it is essential that accurate and up-to-date
information about the patient’s medications be provided. This
enables health care professionals responsible for the patient’s
care to identify any medication changes or discrepancies
between the prior and current medication lists. This process of
medication reconciliation helps health care providers makeinformed decisions and safely monitor their patients’ care [5].
A Stage 2 core measure recommended that medication
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Slight et alreconciliation be performed for more than 50% of patientstransitioning into the care of the eligible provider or admitted
to the eligible hospital’s or Critical Access Hospital’s (CAHs)
inpatient or emergency department (SGRP 302). However, theconsensus of the stakeholder group was that this process of
medicine reconciliation is very important and requires attention.
The quality and accuracy of these medication lists are often
poor and providing patients with medication lists that are of
dubious quality (due to missing, duplicated, or inaccurateprescription information) can pose a risk to patient safety.
Medication lists can also fall short, for example, by excluding
important information critical to pediatric dosing, such as theintended weight-based dose, adjustments made based ongestational age, and dose rounding. As part of the medication
reconciliation process, prescribers and nonprescribers (eg,medical assistants) are now entering medical information about
patient medications such as a report that the patient is not taking
a drug. This “not taking” data element fails to capture whether
the drug has or has not been prescribed or discontinued, orwhether the patient is choosing not to take the medication. The
ambiguity in the meaning of the data element “not taking”
introduces considerable variation in how individuals handle thisinformation in the EHR system and raises questions on how thequality of this process would be measured or monitored.
Better electronic tools are needed to assist with this medication
reconciliation process [6]. For example, 3 stakeholders
highlighted how Partners Healthcare developed an electronic
postdischarge tool that presents the ambulatory EHR medication
list (preadmission) alongside the discharge medication list on
the same screen with all differences in dose or frequency
highlighted [7]. Medications can then be efficiently added to,
updated, or deleted from the EHR medication list. The primarycare provider could also “verify” that a medication was
up-to-date, thus helping other clinicians judge the accuracy of
medication information. This electronic tool is one example ofautomated approaches that could more actively involve theprimary care provider and improve patient safety at the transition
from hospital to primary care.
A Stage 3 recommendation was that EHR systems should
provide functionality to help maintain an up-to-date accurate
medication list (SGRP 106); therefore, the incorporation of
external data, such as pharmacy dispense status notifications,
into vendor EHR systems was proposed for a future stage ofMU (SGRP 125). These data could better inform users as towhether a patient had their prescription(s) filled, was taking 2
kinds of the same drug (including detection of abuse), or wasusing multiple drugs whose indications overlap. All stakeholders
agreed that such needed interoperability poses additional
challenges related to data validity, reliability, and integrity, andconcerns about the willingness, timing, and ability of pharmacies
to make these data available electronically.
One specific recommendation from the stakeholder group wasthat medication cancelations should be transmitted topharmacies. This is often done in the inpatient setting, but it is
not done in the outpatient setting, although a standard does exist.
If this were done, it could help resolve many discrepancies inmedication reconciliation.
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Accurate Problem Lists and the Shift in Health
Information Technology Priorities
An accurate list of a patient’s problems and allergies represents
a key component of the patient’s EHR. Problem lists contain alist of patients’ problems or diagnoses and may be used byclinicians to familiarize themselves with the needs of a patientand orient caregivers to the reasons why a patient may be on aparticular medication or regimen. If a problem is properly
documented in a patient’s EHR, their clinician can receive
appropriate alerts and reminders to guide care. The problem list
also helps primary care practices to correctly identify
disease-specific populations and create patient registries
ensuring that all patients benefit from the most up-to-dateevidence-based care.
The MU Stage 3 recommendations expanded the scope ofreconciliations to include those of medication allergies andproblems (SGRP 302). Many stakeholders recognized theimportance of obtaining patients’ input on the accuracy ofproblem lists (SGRP 105) in the process of reconciliation.
However, concerns were raised by the stakeholder group about
whether and how patients should contribute to the same
up-to-date problem list as clinicians and, if so, whether this may
confuse and possibly interfere with the credibility of the list [4].
Some patients do not actually have any active problems andstakeholders grappled with the need to distinguish the explicit
absence of a problem from the situation in which a problem
may exist but was not entered (or does not fit the criteria that
CMS has determined for what constitutes a problem). For
example, one stakeholder highlighted how Intermountain
Healthcare had asked their physicians to enter problems or “noproblems” in the chart to comply with MU, but in actual use,
many items on the problem list were not “problems” according
to CMS rules and so “no CMS problems” was entered instead.
This proved confusing for clinicians to interpret.
One Stage 2 core measure recommended maintaining an
up-to-date problem list of current and active diagnoses (SGRP
105) and a medication allergy list (SGRP 107). Stage 3
recommendations expand on these basic requirements proposingthat EHR systems should also provide functionality to help keep
both problem and allergy lists accurate and up-to-date. One
stakeholder explained how the University of Washington has
developed new functionality using natural language processing
to help achieve this objective for EHR problem lists. However,
because of the burden of complying with MU requirements,
other work that was not directly tied to MU incentives was
postponed or halted. For example, before the launch of the MU
incentive program, there were active clinical decision support(CDS) initiatives on-going at the University of Washington for
the early detection of sepsis, identifying non-ICU patients at
risk of clinical deterioration, complying with guidelines toreduceventilator-associatedpneumonia,
venousthromboembolism, and other complications of ICU care—all
leading causes of patient harm. However, to meet MU
requirements, work on these projects was deferred and theclinical analysts, engineers, and senior programming staff wereredirected to work on implementing MU requirements. One
stakeholder reported a similar stifling of innovation at
Intermountain Healthcare, where the implementation of MU
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Slight et alcapabilities delayed other EHR development projects, such as
the replacement of legacy system functionality in labor anddelivery, electronic consent handling, clinical HIE workflow
integration, and replacement/enhancement of inpatientcomputerized provider order entry (CPOE) functionality. The
consensus of the stakeholder group was that this might represent
an opportunity cost for innovation. Institutions understandably
may place priority on innovations that will bring known rewards,
even if the innovations would not be as high a priority if there
were no incentives. These unintended consequences of the MU
incentives can be instructive to consider as other “pay for
performance” programs are initiated.
The definition of CPOE by CMS is “a provider’s use ofcomputer assistance to directly enter medical orders (eg,medications) from a computer or mobile device” [8]. The Stage
3 MU measure recommended 60% of medication orders and
60% of laboratory and radiology orders (as opposed to 30% inStage 2 MU) be recorded by the eligible or authorized provider
using CPOE. Stakeholders supported the inclusion of drug-druginteraction (DDI) checking in CPOE systems for “never”
combinations (SGRP 101)—combinations that have the potential
for severe adverse effects if prescribed together. Questions
frequently arose about who would create and maintain such an
externally vetted list of DDI alerts for “never” combinations.
Two stakeholders suggested that the creation of a national
knowledge base, which is managed centrally, might be one
possible option to consider so that each organization does nothave to individually reinvent the wheel. However, moststakeholders felt the overall utility of DDI alerts was mixed
because of a plethora of what clinicians perceived were“nuisance alerts” that they mostly ignored. All alerts need to be
implemented thoughtfully with careful attention paid to thebalance between sensitivity and specificity, how the alerts aredelivered to providers, how intrusive they are to provider
workflow, and the provider’s clinical specialty and patient
population. Stakeholders felt that organizations should beallowed flexibility in managing DDI alert implementation toensure that it does not result in too many false-positive warnings
and inaccurate or trivial information, resulting in alert fatigue[4].

Accurate Allergy Lists and Allergy-Related Standards
Development
Overview
Stage 2 and 3 recommendations require EHRs to maintain active
medication allergy lists (SGRP 107). This includes functionalitythat codes medication allergies and links them to related drug
family and code-related reactions. It known that an allergy thatis entered as free text in the EHR is neither interoperable acrossclinical information systems nor easily usable for CDS
applications, such as drug-allergy interaction checking.
However, the US government has not yet specified which
standard terminologies should be used to structure and encode
allergy information. The consensus of the stakeholder group
was that defining allergy standards will be essential to facilitate
both documentation and the exchange of information between
health care settings [4]. One stakeholder highlighted how Gosset al [9] defined a set of desirable characteristics to assess allergy
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standards and terminologies, and conducted an analysis to
examine the content coverage of each existing standard
terminology within specific domains. Systemized Nomenclatureof Medical Clinical Terms (SNOMED CT) was found to fulfill
the greatest number of desirable characteristics, whereas
RxNorm provided the most comprehensive coverage forrepresenting drug allergens, followed by Unique Ingredient
Identifier (UNII) and SNOMED CT. Unfortunately, no single
terminology was found to be, by itself, a complete solution.
SNOMED CT was the only terminology to contain concepts torepresent “no known allergies.” Failure to document positive
findings may result in compliance issues and can potentiallyjeopardize patient safety [9]. There is a lack of validated
outcome measures or service accreditation standards, which
would allow improved measurement of the quality of allergy
services provided [10]. The stakeholder group agreed that further
work is needed to develop a common terminology model, which
will reconcile overlapping concepts and terms.

Supporting Safer and More Effective Prescribing forChildrenStakeholders, especially those from the Cincinnati CERT thatspecializes in pediatric medication use, expressed concern about
the lack of attention paid to pediatric prescribing in the MU
criteria. Although Stage 2 and Stage 3 MU objectives required
CPOE systems to be used for 60% of medication orders (SGRP
101), EHR functionalities to assist with the prescribing of
medications for children have not been specifically mentionedor recommended. This is despite the fact that prescribing

Slight et al
medicines for children is reported in the literature to carrydisproportionately higher safety risks and be more error prone
compared to prescribing for adults [11]. A child’s continuously
changing physiology [12] and limited ability to tolerate errors[13,14] require consideration of gestational age, actual age,weight, length, body surface area, and body mass index whenprescribing drugs [15]. With almost one-quarter of the US
population being children [16], it stands to reason that EHR
functionalities should be developed and widely implemented
to promote safer pediatric prescribing.
The American Academy of Pediatrics (AAP), AHRQ, andHealth Level 7 (HL7) International, have described desirable
functionalities for EHRs in pediatric populations. Major areas
include immunization management, growth tracking, medication
dosing, data norms, and privacy in special pediatric populations[17]. For safe prescribing, pediatric drug dosages are usually
best calculated on the basis of body weight [18,19]. Stakeholders
pointed out how it is possible for an EHR system to use thisvalue to suggest doses or indeed request that the weight be
updated or entered in the system if absent. EHR systems could
also help minimize errors in computing of a volume of liquid
for a particular dose and round it to a convenient volume to beadministered by a caregiver. Because data norms and values(eg, body measurements and vital signs) change continuouslywith age, EHRs can also assist with the calculation and flagging
of abnormal values. Furthermore, they can generate instructions
to the pharmacy to dispense the drug in a particular way [17].
Textbox 1 lists EHR functionalities that stakeholders considered
important in prescribing for children.

Textbox 1. Electronic health record functionalities that stakeholders considered important in prescribing for children.
•

Weight-based/body surface-based dose calculations and range checks [14]•Ability to detect erroneously entered weights [14,20,21]•

Display of patient specific units of measure (eg, grams) along with the data values [22]•Rounding of medication doses to appropriate decimal precision with special consideration of the low-weight patients [23,24]•

Display of data that influenced the final dose and amount in the prescription, particularly to dispensing pharmacists [25]•Display of normal pediatric dose ranges and advice when no pediatric references exist [26]•Use pediatric dose ranges for alerts using patient weight/age with soft-stops for adult dose [27]•Appropriate alerts for age correction for preterm infants, neonates, and low-weight patients [28]•Recommendation of optimized dispensing format (liquid, tablet, etc) or concentration for the patient [22,29]•

Adolescent patients require a level of confidential care, especially when prescribing medications for reproductive or mental health issues [30,31]

Stage 3 recommendations propose a new measure that would
require health care providers to generate and transmit dischargeprescriptions electronically (SGRP 103). Although this objective
may improve workflow for pediatric providers and reduce therisk of illegible handwriting and transcription errors, thestakeholder group felt that it does not focus on the decision
support required to generate correct prescriptions and may
simply enable faster generation and transmission of potentiallyerroneous orders. Current formats for electronic prescription
messages do not include body weight or any details about thecalculations that yielded the dose [32]. Thus, the consensus of
the stakeholder group was that few of the Stage 2 requirements
were aligned sufficiently with the functionalities considered
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critical for the accurate prescribing of medications in children
and it was key that this issue be addressed in the developmentof future recommendations.

Challenges and Opportunities for Rural Communities
Awards totaling US $10 million were collectively granted to 5
domestic institutions to support HIT curriculum developmentin April 2010 to the University of Alabama at Birmingham,
Johns Hopkins University, Columbia University, Duke
University, and Oregon Health and Science University. Eachof these Curriculum Development Centers was given
responsibility to develop, revise, and share curriculum
components covering a specific set of HIT content areas. The
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ultimate aim was to prepare future professionals to meet
emerging workforce needs. Despite the initial HITECH funding
for training, stakeholders felt that the needs of the HIT
workforce in rural areas across the country have not been met
yet. Rural communities are more likely to have smaller practices,which have been among the last to embrace electronic medical
records [33]. They have fewer resources to both purchase EHRs
and to hire and retain HIT support staff. The overall IT
infrastructure in many of these areas (as in some low-resource
urban areas) is poor, which makes it even more challenging toparticipate in the electronic information exchange. Thus, patientswith complex conditions in rural communities may not benefit
from the quality improvements that the MU incentives aredesigned to deliver.
According to the stakeholders, especially those from the
University of Alabama at Birmingham CERT that specializes
in workforce training, several steps have been taken to addressthese issues. In addition to the workforce training programs, 62
Regional Extension Centers (RECs) have been established with
US $677 million in funding from the ONC to provide
on-the-ground assistance to smaller rural practices. In 2011, theONC announced an additional US $12 million in new technicalsupport assistance to help CAHs and rural hospitals adopt andbecome meaningful users of certified HIT. This funding was inaddition to the $20 million provided to RECs in September 2010
to provide technical assistance to the CAHs and rural hospitals[34]. In addition, University of Alabama at Birmingham andColumbia University collaborated with representatives fromseveral of the other RECs to adapt the original training
curriculum so that it would be better suited to the needs of ruraland low-resource urban practices. In 2013, the Health Services
and Resource Administration (HRSA) funded rural networks
in 15 states to develop rural HIT workforce development
programs to provide education, apprenticeships, and job
placements in rural practices [35]. HRSA, AHRQ, and ONC
have also developed resources, checklists, and toolkits to help
sites unable to afford expensive outside consultation [36].
One stakeholder pointed out that as more hospitals and practices
begin to meet the MU criteria, some of the traditional boundaries
that have separated rural primary care practices from tertiarycare centers in large urban areas may begin to disappear. Primarycare practices may have more access to information about theirpatients’ hospitals stays. Tertiary care hospitals are likely tohave a substantial number of patients from surrounding rural
areas who can benefit from patient portals or similar mechanisms
to promote patient engagement (SGRP 204A). However, patientengagement is likely to be another challenge going forwardwith rural residents, considering unreliable Internet connections,
low health literacy, and lack of resources. Although MU
requirements currently set a low percentage of patients who are
expected to use the portals, the consensus of the stakeholder
group was that systems must be scalable if more patients are tobenefit, which will likely entail use of novel technologies suchas mobile devices.

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Achieving Meaningful Use: Easier for Some Than for
Others?
Many different stakeholders supported the MU general goalthat providers should have appropriate information about
patients transitioning into their care (SGRP 303). Stage 3
recommendations expanded on this Stage 2 objective byspecifying the types of information that should be included in
the summary care record, such as a concise narrative section,
goals, instructions, and care team members. The consensus of
the stakeholder group was that some organizations, such as
Kaiser Permanente or Intermountain Healthcare, might find it
easier to achieve this objective than others. Suchwell-established integrated delivery systems have organized,
coordinated, and collaborative networks that bring together
various health care providers to deliver coordinated care to adefined patient population [37]. They include primary andspecialty outpatient care, as well as community and tertiary
hospital services. The effective use of HIT is a key attribute ofsuccessful integrated delivery systems [37,38]. For example, inthe case of Kaiser Permanente or the Veterans Affairs systems,
the same longitudinal EHR is accessible and shared by bothprimary care physicians and specialists, thus facilitating the
tracking of patients across the continuum [38]. Kaiser
Permanente also has an integrated pharmacy system that is used
for most patient prescriptions. One stakeholder highlighted how,for the past 20 years, Kaiser Permanente has had a bidirectional
electronic HL7-based interface in place in their pharmacy
systems, which has ensured that the information presented totheir patients was consistent, whether they were engaged withclinical operations, outpatient pharmacy locations, or mail orderpharmacy services. It also meant that the Stage 2
recommendation to generate and transmit permissible dischargeprescriptions electronically (SGRP 103) was easily achievable
for all eligible providers. However, this stakeholder also
explained how other measures, such as Summary of Caredocumentation at time of transitions with external organizations,have required substantial resources to fund technical andoperational change that has impacted less than 2% of Kaiser
Permanente’s patient population. Care should be taken to avoid
MU requirements that are unnecessarily burdensome to mature,
typically staff model systems that have historically been theleaders in integrated use of clinical information.
Another issue raised by a different stakeholder related to whetherorganizations are using existing functionality (eg, Surescripts)
or have chosen to develop their own. Kaiser Permanente andother integrated delivery systems lacked the functionality tobring medication information from external pharmacies into
their EHR system and were swayed by the MU incentives to
add this to their systems. However, the value of this functionality
within staff model systems such as Kaiser Permanente is likely
to be low in light of the fact that Kaiser Permanente patientsobtain nearly all their medications from Kaiser Permanente.
Stakeholders agreed in principle that external interoperability
functionality can help maintain accurate medication and problem
lists, although they felt that implementation should be flexibly
based on the organizational-specific contexts. They also feltthat many of the specific criteria should be postponed until thetechnological, operational, and legal issues are more fully
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evolved and the quality and accuracy of tools are sufficiently
tested.
Finally, Stage 3 recommendations propose a new measure thatwould require health care providers to use CPOE forreferrals/transition of care orders (SGRP 130). One stakeholder
highlighted how some organizations, including Intermountain
Healthcare, already use extensive CPOE/CDS capabilities andother advanced functionality and questioned the value of
spending considerable resources to develop functionality thatthey believed would add little to their existing systems simply
to meet MU requirements. For example, for the successful
attestation of Stage 1, Intermountain Healthcare estimated thatits 696 eligible professionals and 22 hospitals were eligible forapproximately US $46.3 million. The high degree of
coordination already inherent in their delivery model and IT

Slight et alsystems meant that total costs for the implementation of Stage
1 recommendations were considerably lower than for others at
an estimated US $17.3 million, resulting in a net revenue benefitof US $29 million. Although this financial benefit may seem
substantial, another stakeholder pointed out how these total
implementation costs may not reflect the “true” cost because
they did not include the development of the system’s computer
network (in their case, this was already in existence) or the
disruption caused by HIT implementations and upgrades.
Therefore, the consensus of the stakeholder group was that it isimportant to understand the current structural advantages ofexisting integrated delivery systems in the achievement of MU
objectives and to recognize the need for future MU requirements
to be applied and interpreted more flexibly. Textbox 2 lists asummary of the key issues for each domain.

Textbox 2. A summary of the key issues in each domain.
1. Accurate Medication Lists and Medication Reconciliation•

The quality and accuracy of these medication lists is often poor and providing patients with medication lists that are of dubious quality can posea risk to patient safety.

•

Better electronic tools are needed to assist with this medication reconciliation process.

•

The incorporation of external data, such as pharmacy dispense status notifications, into vendor EHR systems could better inform providers abouta patient’s medicines usage.

2. Accurate Problem Lists and the Shift in HIT Priorities•

EHR systems should also provide functionality to help keep both problem and allergy lists accurate and up-to-date.

•Institutions understandably may place priority on innovations that will bring known rewards, even if the innovations would not be as high apriority if there were no incentives.

•

All CDS alerts need to be implemented thoughtfully with careful attention paid to the balance between sensitivity and specificity, and how thealerts are delivered to providers.

3. Accurate Allergy Lists and Allergy-Related Standards Development•

Defining allergy standards will be essential to facilitate both documentation and the exchange of information between health care settings.

4. Supporting Safer and More Effective Prescribing for Children•

Data norms and values change continuously with age and EHRs can assist with the calculation and flagging of abnormal values.

•

Few Stage 2 requirements were aligned sufficiently with the functionalities considered critical for the accurate prescribing of medications inchildren and it was key that this issue be addressed in the development of future recommendations.

5. Challenges and Opportunities for Rural Communities•

Despite the initial HITECH funding for training, the needs of the HIT workforce in rural areas across the country have not been met.

•

Patient engagement is likely to be challenge going forward with rural residents, considering unreliable Internet connections, low health literacy,
and lack of resources.

•

Although MU requirements currently set a low percentage of patients who are expected to use the portals, systems must be scalable if morepatients are to benefit, which will likely entail use of novel technologies such as mobile devices.

6. Achieving MU: Easier for Some Than for Others?
•

Some MU measures have been easily achievable for integrated delivery systems, whereas other measures have required substantial resources tofund and have impacted only a small portion of their patient population.

•

Future MU requirements need to be applied and interpreted more flexibly.

Discussion
We assessed stakeholders’ learning and experiences from theimplementation of MU requirements over the past 4 years, with
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a particular focus on medication requirements and attempted to
identify problem areas where midcourse corrections might behelpful. Six specific issues were highlighted, all of which present
opportunities for improvement. The implementation of MU
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capabilities was reported to have stifled innovation at someorganizations. This appears to run counter to the ONC’s goalof encouraging innovation and creating “an environment of
testing, learning, and improving, thereby fostering breakthroughsthat quickly and radically transform health care” [39]. The
challenge in many organizations was that resources were largely
focused on implementing basic MU criteria and diverted awayfrom addressing other meaningful local problems and creating
innovative solutions.
Likewise, although the EHR incentive program was viewed asa valuable opportunity to encourage provider-level clinicalquality measure (CQM) innovation and perform provider-level
CQM testing, some stakeholders felt it distracted them at least
temporarily from their efforts to develop and implement suchquality measurement and improvement systems. The HITPC
also raised the possibility of allowing health care organizations
to submit a locally developed CQM as a menu item, in lieu of
one of the existing measures specified in the MU program [3].
Health care organizations may find this difficult to achieve,
especially if their clinical analysts, engineers, and seniorprogramming staff are focused on achieving MU requirements
rather than other EHR development projects. Furthermore, theFood and Drug Administration Safety and Innovation Act(FDASIA) working group was clear that any new HIT regulatory
framework should promote innovation rather than stifle it [40].
This FDASIA working group recommended more local HIT
configuration and integration, as well as more control andaccountability for outcomes of use. A greater emphasis shouldbe placed on local HIT configuration that addresses population
health needs. Thus, MU requirements will need to change andevolve over the next few years to achieve this broader and more
flexible orientation. The concerns we have identified havespurred the following recommendations:
1.

2.

3.

4.

5.

Definitions of transitions in care should enable and support
shared patient record systems. Better tools andinteroperability with external data are needed for effective
and efficient medication reconciliation. On the other hand,measures should not drive unnecessary or unreliable datatransmission.
Development of a common terminology model is needed
to facilitate documentation and encoding of key data
elements, notably patient allergies.
Future MU certification rules and requirements should
consider EHR functionalities that are critical, but often
lacking, for the accurate prescribing of medications inchildren.
Future MU requirements should put more emphasis on
flexibly understanding, incorporating, and supporting local
HIT configurations that address population health needs.
The MU objectives should acknowledge the diversity ofhealth care systems. For example, integrated delivery
systems are more likely to achieve the goal of information
sharing because of their integrated structure, greater
functionality, and improved interoperability. From thepolicy perspective, this could be handled by offering
exceptions or alternate routes for qualification.

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Slight et al
The sampling strategy used in this study ensured that theperspectives of highly knowledgeable informants from the 5
AHRQ-sponsored CERTs were captured. Our sample included
those directly involved in the implementation of MU criteria(eg, Chief Medical Information Officer or Chief Medical
Informatics Officer) and those who were knowledgeable about,
but not directly involved in, the day-to-day implementation
work (eg, academicians, practitioners, policy makers).
Participants were free to raise any issues that they felt wererelevant to the topic under discussion. Consequently, we believethat the information gathered was reflective of genuine concernsand views. All stakeholders were given an opportunity toprovide feedback on the key domains, ensuring that theconclusions accurately reflected the opinions and views
collected. A limitation of this study was that it was performedin the US context and, therefore, could be viewed as lessapplicable to other countries. However, we believe that theimplementation and adoption of EHRs is highly heterogeneous
across health care systems and countries, and will be of interest.
The future course that the federal government will take withrespect to HIT and policy measures is uncertain. It is not clear
whether there will be a fourth stage of MU, although thatcurrently seems unlikely. Taking stock of the important ways
MU has been successful in achieving many of its
objectives—such as dramatically increasing the number of
medications ordered electronically—as well as where it
encountered predicted and unanticipated problems, will be
critical to mapping the next steps. Overall, the incentives andspecific MU criteria will almost certainly be less important thanthey have been in the future as information systems more
broadly improve their functionality and many of the challenges
that we face today become embedded as the standard of care.
It does appear that certification will continue to be important,although providers have recently called for separating MU fromcertification [41]. The ONC will likely continue to(appropriately) maintain its “bully pulpit” role in helping toencourage and accelerate the development of standards andinteroperability among other needs. Finally, it appears likelythat a national Center for HIT Safety will be established, adevelopment many of the CERT stakeholders welcomed,
especially given the valuable role CERTs have historicallyplayed in the coordination of national medication improvement
efforts [39].
Regardless, we believe it will be important for the federal
government to address some of the issues we have identified inthis paper, including problems with how medication
reconciliation is being promoted, the issues around accurate
problem lists and the shift in HIT priorities, supporting safer
and effective prescribing for children and rural communities,
and making achieving MU more likely to result in the care
improvement desired by all stakeholders. Any new policy will
introduce new problems and it is essential for the federal
government and others to consider how best to address theseissues and others through the MU incentive program.

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Slight et al

Acknowledgments
We would like to thank the CERTs Scientific Forum for agreeing to host these meetings.

Authors' Contributions
DWB conceived this manuscript. SPS reviewed the public commentary available on the government website and led the writingof this manuscript with TYW, SAS, CUL, NM, ESB, BG, BLL, THP, SH, and MM contributing. All coauthors commented on
subsequent drafts and gave their approval for the final version to be published. SPS and DWB acts as guarantors.

Conflicts of Interest
Dr Bates and Dr Lehmann have served as members of the HIT Policy Committee. Dr Huff has served as a member of the HITStandards Committee.

References
1.
2.
3.

4.
5.

6.

7.

8.

9.

10.

11.

12.
13.
14.
15.

16.

HealthIT.gov. 2015. Health IT regulations: meaningful use regulations URL: http://www.healthit.gov/
policy-researchers-implementers/meaningful-use-regulations [accessed 2015-05-24] [WebCite Cache ID 6Ylk9mfv2]
Blumenthal D, Tavenner M. The "meaningful use" regulation for electronic health records. N Engl J Med 2010 Aug
5;363(6):501-504. [doi: 10.1056/NEJMp1006114] [Medline: 20647183]
Department of Health and Human Services, Office of the National Coordinator for Health Information Technology. Request
for Comment Regarding the Stage 3 Definition of Meaningful Use of Electronic Health Records (EHRs). 2013 Jan 14.
URL: http://www.healthit.gov/sites/default/files/hitpc_stage3_rfc_final.pdf [accessed 2015-09-13] [WebCite Cache ID
6bWMjeeEY]
regulations.gov. Your voice in federal decision-making URL: http://www.regulations.gov/ [accessed 2015-04-08] [WebCite
Cache ID 6XdQbcd1z]
EHR Incentive Program. Eligible Professional Meaningful Use Menu Set Measures Measure 6 of 9. 2014 May. Medication
reconciliation URL: http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads/
7_Medication_Reconciliation.pdf [accessed 2015-04-08] [WebCite Cache ID 6XdRfFrnu]
Schnipper JL, Hamann C, Ndumele CD, Liang CL, Carty MG, Karson AS, et al. Effect of an electronic medication
reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial. Arch Intern
Med 2009 Apr 27;169(8):771-780. [doi: 10.1001/archinternmed.2009.51] [Medline: 19398689]
Schnipper JL, Liang CL, Hamann C, Karson AS, Palchuk MB, McCarthy PC, et al. Development of a tool within theelectronic medical record to facilitate medication reconciliation after hospital discharge. J Am Med Inform Assoc 2011
May 1;18(3):309-313 [FREE Full text] [doi: 10.1136/amiajnl-2010-000040] [Medline: 21486889]
The Centers for Medicare & Medicaid Services. Stage 2: Eligible Hospital and Critical Access Hospital Meaningful Use
Core Measures Measure 1 of 16. 2012 Oct. URL: http://www.cms.gov/site-search/search-results.
html?q=Eligible%20Hospital%20and%20Critical%20Access%20Hospital%20Meaningful%20Use%20Core%20Measures%20Measure%201%20of%2016.
%20Stage%202 [accessed 2015-04-08] [WebCite Cache ID 6XdSm5XDp]
Goss FR, Zhou L, Plasek JM, Broverman C, Robinson G, Middleton B, et al. Evaluating standard terminologies for encoding
allergy information. J Am Med Inform Assoc 2013;20(5):969-979 [FREE Full text] [doi: 10.1136/amiajnl-2012-000816][Medline: 23396542]
Royal College of Physicians. 2010. Allergy services: still not meeting the unmet need URL: https://www.rcplondon.ac.uk/
sites/default/files/documents/allergy-services-still-not-meeting-the-unmet-need.pdf [accessed 2015-05-24] [WebCite Cache
ID 6Yllb4yT1]
Gerstle RS, Lehmann CU, American Academy of Pediatrics Council on Clinical Information Technology. Electronicprescribing systems in pediatrics: the rationale and functionality requirements. Pediatrics 2007 Jun;119(6):e1413-e1422.
[doi: 10.1542/peds.2007-0889] [Medline: 17545368]
Hughes RG, Edgerton EA. Reducing pediatric medication errors: children are especially at risk for medication errors. Am
J Nurs 2005 May;105(5):79-80, 82, 85 passim. [Medline: 15867545]
Stavroudis TA, Miller MR, Lehmann CU. Medication errors in neonates. Clin Perinatol 2008 Mar;35(1):141-61, ix. [doi:10.1016/j.clp.2007.11.010] [Medline: 18280880]
Kim GR, Lehmann CU, Council on Clinical Information Technology. Pediatric aspects of inpatient health information
technology systems. Pediatrics 2008 Dec;122(6):e1287-e1296. [doi: 10.1542/peds.2008-2963] [Medline: 19047228]
Lowry S, Quinn M, Ramaiah M, Brick D, Patterson E, Zhang J, et al. A Human Factors Guide to Enhance EHR Usabilityof Critical User Interactions When Supporting Pediatric Patient Care. 2012 Jun. URL: http://www.nist.gov/healthcare/usability/upload/NIST-IR-7865.pdf [accessed 2015-09-13] [WebCite Cache ID 6bWNQboed]
KIDS COUNT data center. 2014. Total population by child and adult populations URL: http://datacenter.kidscount.org/
data/tables/99-total-population-by-child-and-adult [accessed 2015-04-08] [WebCite Cache ID 6XdSuHso0]

http://medinform.jmir.org/2015/3/e30/

XSL• FO
RenderX

JMIR Med Inform 2015 | vol. 3 | iss. 3 | e30 | p. 9
(page number not for citation purposes)

JMIR MEDICAL INFORMATICS
17.

18.

19.

20.
21.
22.
23.

24.

25.

26.
27.
28.
29.
30.

31.
32.
33.
34.

35.

36.

37.
38.
39.

40.

Spooner SA, Council on Clinical Information Technology‚ American Academy of Pediatrics. Special requirements ofelectronic health record systems in pediatrics. Pediatrics 2007 Mar;119(3):631-637. [doi: 10.1542/peds.2006-3527] [Medline:
17332220]
Maat B, Au YS, Bollen CW, van Vught AJ, Egberts TC, Rademaker CM. Clinical pharmacy interventions in paediatricelectronic prescriptions. Arch Dis Child 2013 Mar;98(3):222-227. [doi: 10.1136/archdischild-2012-302817] [Medline:
23184352]
Ginzburg R, Barr WB, Harris M, Munshi S. Effect of a weight-based prescribing method within an electronic health recordon prescribing errors. Am J Health Syst Pharm 2009 Nov 15;66(22):2037-2041. [doi: 10.2146/ajhp080331] [Medline:
19890088]
Selbst SM, Fein JA, Osterhoudt K, Ho W. Medication errors in a pediatric emergency department. Pediatr Emerg Care
1999 Feb;15(1):1-4. [Medline: 10069301]
Condren M, Studebaker IJ, John BM. Prescribing errors in a pediatric clinic. Clin Pediatr (Phila) 2010 Jan;49(1):49-53.
[doi: 10.1177/0009922809342459] [Medline: 19643978]
Croskerry P, Shapiro M, Campbell S, LeBlanc C, Sinclair D, Wren P, et al. Profiles in patient safety: medication errors in
the emergency department. Acad Emerg Med 2004 Mar;11(3):289-299 [FREE Full text] [Medline: 15001413]
Patterson ES, Zhang J, Abbott P, Gibbons MC, Lowry SZ, Quinn MT, et al. Enhancing electronic health record usability
in pediatric patient care: a scenario-based approach. Jt Comm J Qual Patient Saf 2013 Mar;39(3):129-135. [Medline:
23516763]
Johnson KB, Lee CK, Spooner SA, Davison CL, Helmke JS, Weinberg ST. Automated dose-rounding recommendations
for pediatric medications. Pediatrics 2011 Aug;128(2):e422-e428 [FREE Full text] [doi: 10.1542/peds.2011-0760] [Medline:
21788218]
Johnson KB, Ho Y, Cala CM, Davison C. Showing your work: impact of annotating electronic prescriptions with decision
support results. J Biomed Inform 2010 Apr;43(2):321-325 [FREE Full text] [doi: 10.1016/j.jbi.2009.11.008] [Medline:
19995617]
Kirkendall ES, Spooner SA, Logan JR. Evaluating the accuracy of electronic pediatric drug dosing rules. J Am Med Inform
Assoc 2014 Feb;21(e1):e43-e49 [FREE Full text] [doi: 10.1136/amiajnl-2013-001793] [Medline: 23813541]
Scharnweber C, Lau BD, Mollenkopf N, Thiemann DR, Veltri MA, Lehmann CU. Evaluation of medication dose alerts inpediatric inpatients. Int J Med Inform 2013 Aug;82(8):676-683. [doi: 10.1016/j.ijmedinf.2013.04.002] [Medline: 23643148]
D'Agostino J, Gerdes M, Hoffman C, Manning M, Phalen A, Bernbaum J. Provider use of corrected age during healthsupervision visits for premature infants. J Pediatr Health Care 2013;27(3):172-179.
Zimmer KP, Miller MR, Lee BH, Miller RE, Lehmann CU. Electronic narcotic prescription writer: use in medical error
reduction. J Patient Saf 2008;4(2):98-105.
Anoshiravani A, Gaskin GL, Groshek MR, Kuelbs C, Longhurst CA. Special requirements for electronic medical records
in adolescent medicine. J Adolesc Health 2012 Nov;51(5):409-414. [doi: 10.1016/j.jadohealth.2012.08.003] [Medline:
23084160]
Britto MT, Tivorsak TL, Slap GB. Adolescents' needs for health care privacy. Pediatrics 2010 Dec;126(6):e1469-e1476[FREE Full text] [doi: 10.1542/peds.2010-0389] [Medline: 21098148]
National Council for Prescription Drug Programs. 2014. Standards information URL: http://www.ncpdp.org/Standards[accessed 2015-05-24] [WebCite Cache ID 6YlnxjggO]
National Rural Health Association. The future of rural health URL: http://www.ruralhealthweb.org/index.
cfm?objectid=EAB2AE78-3048-651A-FE4CBFB6C083F34F.,[WebCite Cache ID 6XdS5vIBh]
HealthcareITNews. 2011 Feb 08. ONC awards additonal $12M to 48 RECs for EHR adoption URL: http://www.
ruralhealthweb.org/index.cfm?objectid=EAB2AE78-3048-651A-FE4CBFB6C083F34F., [accessed 2015-05-24] [WebCite
Cache ID 6YlmrBrbT]PR Newswire. 2013 Sep 12. HHS awards $5.3 million to boost health IT for rural areas URL: http://www.prnewswire.com/
news-releases/hhs-awards-53-million-to-boost-health-it-for-rural-areas-223471081.html [accessed 2015-04-08] [WebCite
Cache ID 6XdUzXxKY]Agency for Healthcare Research Quality. Appendix B: Getting Ready: A Planning Checklist for Rural and Community
Hospitals Considering Implementing Health IT. 2012 Oct. URL: https://healthit.ahrq.gov/sites/default/files/docs/page/
AppendixB.pdf [accessed 2015-09-13] [WebCite Cache ID 6bWOHGN6q]
Enthoven AC. Integrated delivery systems: the cure for fragmentation. Am J Manag Care 2009 Dec;15(10 Suppl):S284-S290[FREE Full text] [Medline: 20088632]
Maeda J, Lee K, Horberg M. Comparative health systems research among Kaiser Permanente and other integrated delivery
systems: a systematic literature review. Perm J 2014;2014(3):18.
Office of the National Coordinator for Health Information Technology. Federal Health Information Technology Strategic
Plan 2011-2015. 2015. URL: http://www.healthit.gov/sites/default/files/utility/final-federal-health-it-strategic-plan-0911.
pdf [accessed 2015-05-24] [WebCite Cache ID 6Ylnl5DgR]
Slight S, Bates D. A risk-based regulatory framework for health IT: recommendations of the FDASIA working group. J
Am Med Inform Assoc 2014:1-4.

http://medinform.jmir.org/2015/3/e30/

XSL• FO
RenderX

Slight et al

JMIR Med Inform 2015 | vol. 3 | iss. 3 | e30 | p. 10(page number not for citation purposes)

JMIR MEDICAL INFORMATICS
41.

Slight et al

California Medical Association. 2015 Jan 23. AMA asks feds to decouple EHR certification from meaningful use URL:
http://www.cmanet.org/news/detail/?article=ama-asks-feds-to-decouple-ehr-certification [accessed 2015-05-24] [WebCite
Cache ID 6YlnZzcTX]

Abbreviations
CAH: Critical Access Hospital
CDS: clinical decision support
CERT: Centers for Education and Research in Therapeutics
CPOE: computerized provider order entry
CQM: clinical quality measure
DDI: drug-drug interaction
EHR: electronic health records
FDASIA: Food and Drug Administration Safety and Innovation Act
HIE: health information exchange
HIT: health information technology
HITECH: Health Information Technology for Economic and Clinical Health
HITPC: Health Information Technology Policy Committee
HRSA: Health Services and Resource Administration
MU: meaningful use
REC: Regional Extension Centers
UNII: Unique Ingredient Identifier

Edited by G Eysenbach; submitted 19.04.15; peer-reviewed by C Kruse, T Otte-Trojel; comments to author 07.05.15; revised version
received 02.06.15; accepted 24.07.15; published 18.09.15
Please cite as:
Slight SP, Berner ES, Galanter W, Huff S, Lambert BL, Lannon C, Lehmann CU, McCourt BJ, McNamara M, Menachemi N, Payne
TH, Spooner SA, Schiff GD, Wang TY, Akincigil A, Crystal S, Fortmann SP, Vandermeer ML, Bates DW
Meaningful Use of Electronic Health Records: Experiences From the Field and Future Opportunities
JMIR Med Inform 2015;3(3):e30
URL: http://medinform.jmir.org/2015/3/e30/
doi: 10.2196/medinform.4457
PMID:©Sarah Patricia Slight, Eta S Berner, William Galanter, Stanley Huff, Bruce L Lambert, Carole Lannon, Christoph U Lehmann,
Brian J McCourt, Michael McNamara, Nir Menachemi, Thomas H Payne, S Andrew Spooner, Gordon D Schiff, Tracy Y Wang,
Ayse Akincigil, Stephen Crystal, Stephen P Fortmann, Meredith L Vandermeer, David W Bates. Originally published in JMIR
Medical Informatics (http://medinform.jmir.org), 18.09.2015. This is an open-access article distributed under the terms of theCreative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution,and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The
complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright andlicense information must be included.

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