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With electronic health record (=
EHR) adoption rising across the U.S., the volume and detail of information =
captured by healthcare organizations and providers will grow exponentially.=
Although health care providers and others use various sources and methods =
to capture and synthesize patient-level data, EHRs have been recognized as =
the data source with the highest potential to provide timely and relevant d=
ata in a form that is quickly usable for quality and safety improvement, po=
pulation health, and research (sometimes labeled =E2=80=9Csecondary=E2=80=
=9D use or "reuse"). EHR data obtained durin=
g episodes of care will become increasingly valuable to healthcare organiza=
tions striving to leverage electronic information to drive efficiency and q=
uality. Of particular interest are efforts to leverage clinical data captur=
ed during episodes of care and link the clinical data to supplemental data =
collected for other purposes including: 1) research, 2) patient-safety even=
t reporting, 3) public health reporting, and 4) Determination of Coverage. =
Once captured, aggregated and analyzed, these combined data can be used to =
identify trends, predict outcomes and influence patient care, drug developm=
ent and therapy choices.
For example, a clinician treat=
ing a patient who is participating in a clinical trial or comparative effec=
tiveness research (CER) would select, through the EHR, the applicable elect=
ronic case report form (eCRF) and would be able to complete the form with a=
combination of information extracted automatically from his or her most re=
cent entry into the patient=E2=80=99s EHR and new information added by the =
clinician in direct response to the eCRF. Data captured would be stored and=
ultimately aggregated and transferred to the end users.
The utility of EHR data for suppl=
emental purposes has been limited due to a lack of uniformity in the termin=
ology and definitions of data elements across EHRs. This limitation is comp=
ounded by the fact that clinician workflow often records patient informatio=
n in unstructured free-text data well after the episodes of care. Linking E=
HR data with other data in a uniform and structured way could accelerate qu=
ality and safety improvement, population health and research.
<=
span>A multi-pronged approach is warranted. Various clinical and health ser=
vices research groups and specialty societies are already engaged in indepe=
ndent initiatives to standardize data collection across projects in their d=
omains in order to maximize the utility of the resulting datasets for subse=
quent research. Many important efforts that focus on this level of standard=
ization, such as the Patient Reported Outcomes Measurement =
System (PROMIS), PhenX(consensus measu=
res for Phenotypes and eXposures), and the Federal Interagency=
Traumatic Brain Injury Research (FITBIR) Informatics System=
, are funded by the National Institutes of Health (NIH) and other Federal s=
ources. The National Library of Medicine (NLM) is working with the NIH rese=
arch community and others to identify and coordinate research initiatives t=
hat use standardized patient assessment instruments and structured data def=
initions, also known as Common Data Elements&nbs=
p;(CDEs). Work is also beginning, under the auspices of NLM and the Departm=
ent of Health and Human Services (HHS), to consider how to incorporate thes=
e CDEs more directly into the data infrastructure for patient-centered outc=
omes research (PCOR) using EHRs. The Agency for Healthcare Research and Qua=
lity (AHRQ) has developed a comparable library of terms and Common Formats to standardize data coll=
ected and reported for patient safety events. With such CDEs and standardiz=
ed assessment instruments, data captured within an EHR could be consistentl=
y defined and collected, thereby improving its validity and usability not j=
ust in retrospective analysis but also in prospective observational or inte=
rventional research, comparative effectiveness research and patient safety =
monitoring.
The Office of the National Coordinato= r for Health IT (ONC) has demonstrated its value as a forum for addressing = complex data architecture challenges, particularly as a means to publicly d= evelop and test alternatives in advance of their inclusion in the regulatio= ns implementing the 2009 Health Information Technology and Economic and Cli= nical Health (HITECH) Act. The Structured Data Capture Initiative will buil= d on both the results of and lessons learned in prior efforts to bring cons= ensus to this next critical aspect of our collective health data infrastruc= ture.
To define the necessary requirements (including metadata) that will =
drive the identification and harmonization of standards to facilitate the c=
ollection of supplemental EHR-derived data.
This initiative will develop and validate a standards-base=
d data architecture so that a structured set of data can be accessed from E=
HRs and be stored for merger with comparable data for other relevant purpos=
es to include:
The electronic Case Report Form (eCRF) used f= or clinical research including Patient Centered Outcomes Research (PCOR)
The Incident Report used for patient safety r= eporting leveraging AHRQ =E2=80=98Common Formats=E2=80=99 and FDA form 3500= /3500a
The Surveillance Case Report Form used for pu= blic health reporting of infectious diseases
The collection of patient information used for Determination of Coverage= , as resources permit.
The infrastructure will consist o=
f four new standards that will enable EHRs to capture and store structured =
data. These will consist of:
The standards will facilitate the=
collection of data in such a way that any researcher, clinical trial spons=
or and/or reporting entity can access and interpret the data in electronic =
format. They will also support development of concise, architectural guidan=
ce using easy-to-understand documentation, user-friendly tooling and formal=
models to assist vendors in applying technical requirements for the custom=
ized use of specified forms or templates. For the purposes of this initiati=
ve, the data collected will not be stored within the EHR system. In sharing=
this data, ONC recognizes that certain forms of data may be subject to par=
ticular state or federal laws regulating use and disclosure. Standard speci=
fications will incorporate the tools necessary for driving interoperability=
such as XML and the CDISC/ IHE integration profile Retrieve Form for Data Capture (RFD)=
; this does not, however, imply any=
constraints on data formats that can be used during data capture and proce=
ssing, as long as they do not prevent interoperability. The RFD integration=
profile is currently used within the research community to embed structure=
d electronic forms with common data elements within the EHR to facilitate c=
ollection of research data. The SDC Initiative will align with and leverage=
other initiatives of ONC . It will also build upon external initiatives th=
at are focused on improving the comparability and utility of data derived f=
rom independent collection efforts through standardizing definitions of dat=
a elements and tools, such as PROMIS, PhenX, caDSR, and other initiatives i=
dentified in the NLM-NIH Common Data Element repository, and the AHRQ =E2=
=80=98Common Formats=E2=80=99 and Electronic Data Methods (EDM) Forum for C=
omparative Effectiveness Research (CER).
Given the significant Federal investm= ents made in EHR adoption in the last 4 years, structured data capture with= in EHRs is poised to be a critical component of a variety of health service= s, quality measurement and clinical and health services research. Stage 3 M= eaningful Use (MU) will focus on creating a learning health system to suppo= rt quality, research, and improve public and population health. This initia= tive will lead the national vision to design the trusted mechanisms to enab= le patient information to flow securely from the system it was collected=E2= =80=94the EHR=E2=80=94to other systems, such as research consortia, registr= ies, bio repositories and public health systems, with an authorized use for= it. Information will be shared in compliance with policy, regulation, and = Patient Consent Directives (e.g., 42 C.F.R Part 2 Confidentiality of alcoho= l and drug abuse patient records; and 38 USC =C2=A7 7332-Confidentiality of= certain medical records). The identification and harmonization of standard= s for structured data capture within EHRs will not only help achieve this v= ision, but they will also help reduce the:
Data collection burden on health care providers by enabling secure, sing= le-point data entry that populates to multiple systems
Need to make site-specific modifications to EHR system capabilities in o= rder to enable participation in important reporting and research activities=
Barriers to volunteer adverse event reporting on medical products to pub= lic health agencies leading to improvements in population health
These efforts will identify a sta=
ndard for structured data, whether it is used for a clinical trial, Determi=
nation of Coverage, or to report on a patient safety event, which can be co=
llected in a timely manner, then readily compared and aggregated improving =
the overall quality, value and utility of these data. Furthermore, the deve=
lopment of a national infrastructure will improve access to standardized el=
ectronic versions of data collection instruments relevant for use in resear=
ch and patient care such as validated instruments for collecting data on pa=
in, fatigue, physical function, depression, anxiety and social function. It=
will be easier to integrate these instruments into EHRs in ways that will =
ultimately reduce duplicate data entry. Likewise, data collected will be mo=
re comparable and therefore more useful in ascertaining what works best for=
different patient populations.
The SDC Initiative will provide an in=
frastructure to standardize the capture and expanded use of patient-level d=
ata collected within an EHR. In the short term, specification of standards =
for data reuse will support and spur development and implementation of soft=
ware and pilots that will inform refinement of these standards, prior to th=
eir consideration for inclusion in Meaningful Use and EHR certification req=
uirements. In the longer term, the additional functionality will support en=
hancements and efficiencies in such diverse domains as patient-centered out=
comes research and clinical trials, adverse event reporting and public heal=
th monitoring and surveillance, Determination of Coverage and patient care.=
The value of this initia=
tive will be measured through the attainment of the following immediate and=
long-term outcomes:
Standardization efforts established b= y other projects will be leveraged. These include, but are not limited to:<= /span>
Voting on the SDC Project Charter is now closed.