Quality Improvement for Cardiovascular Care
Developing a Rural, Community-Based Registry
for Cardiovascular Quality Improvement
James R. Langabeer II, PhD; Tiffany Champagne-Langabeer, PhD; Derek Smith, PhD
Background: Cardiovascular disease is one of the leading causes of death, yet most evidence is collected from small
clinical trials or individual hospital providers. Achieving scalable data to enable quality improvements (QIs) remains a
challenge. We investigate whether a registry that is shared by multiple providers and integrates data longitudinally
could help drive QIs across a large rural geographic region. Methods: We describe a case study involving the
development of an informatics infrastructure across the entire state of Wyoming. This rural, regional, community-
based cardiovascular system of care involved all interventional hospitals in the state as well as all surrounding
states. Data exchange was initiated between 36 hospitals, and 56 ambulance agencies, to a centralized registry for
clinical analytics and QI for patients with acute myocardial infarction. Results: After 3 years, the registry maintained
all documented acute myocardial infarctions across Wyoming. Median total ischemic time (time from patient’s
symptom onset to definitive treatment) had a 36.7% improvement during the program. Changes in quality for the rural
community included reduction in overall treatment times, as well as enhanced training, standardized protocols, and
community awareness. We also share key lessons learned. Conclusions: Collaborative data registries for emergency
cardiovascular care can help providers and communities measure and improve the quality of the care across regions.
Key words: informatics, quality improvement, registry, system of care
C
ardiovascular disease is the leading cause of
death in the United States.
1
While mortality rates
after acute myocardial infarction (AMI) have decreased
somewhat over the last 20 years, there is still sig-
nificant room for improvement.
2
Given the high dis-
ease burden and mortality rates (1 in 4 deaths in the
United States), some communities have created for-
mal partnerships between hospitals and emergency
medical services (EMS) to improve patient care out-
comes, since the transitions between ambulance and
hospital necessitates seamless coordination and rapid
response.
3
These “systems of care” rely on principles
of data sharing, collaboration between providers, and
development of standardized protocols.
4,5
Cardiovascu-
lar systems of care have been posited as a key strategy
for a learning health care system.
6
The challenge for many community-based systems
of care, particularly those in rural and often medically
underserved regions, is that data are essentially un-
known prior to arrival at the receiving hospital.
7
EMS
data are usually paper-based, and records from a trans-
Author Affiliations: The University of Texas Health Science Center,
Houston (Drs Langabeer and Champagne-Langabeer); and The University
of Wyoming, Laramie (Dr Smith).
Correspondence: James R. Langabeer II, PhD, School of Biomedical
Informatics, The University of Texas Health Science Center, 7000 Fannin
St, Houston, TX 77030 (James.R.Langabeer@uth.tmc.edu).
Partial support for this research was received from The Leona M. and
Harry B. Helmsley Charitable Trust in coordination with the American
Heart Association.
The authors declare no conflicts of interest.
Q Manage Health Care
Vol. 27, No. 4, pp. 209–214
Copyright C
2018 Wolters Kluwer Health, Inc. All rights reserved.
DOI: 10.1097/QMH.0000000000000189
fer hospital are often not shared with the receiving
hospital.
8
As a result, the receiving facility might not
have structured data for the medications, treatments,
and interventions that were performed before their
arrival.
9
The impact of information transmission prehos-
pital arrival on quality of patient care is unknown and
makes continuous learning and quality improvement
(QI) difficult for the community.
6
Each individual hospital maintains only a portion of
data in their individual electronic health record (EHR)
system. Cardiac catheterization laboratories often have
their own unique cardiovascular information systems,
as do the prehospital EMS providers. While the use of
a health information exchange would help serve these
purposes, in most instances, there is not a function-
ing exchange in the community. Lack of integration
between these providers and systems remains a chal-
lenge to understanding interventions, treatments, and
outcomes associated with longitudinal care.
Community systems of care involve collaboration on
a routine basis to report on outcomes data, share pro-
cesses and best practices, and utilize data mining to
improve quality of care. Understanding the patient’s
onset of symptoms, arrival of EMS personnel, time
of first electrocardiography (ECG), dose and time of
medications provided are all examples of how mul-
tiple providers come together to agree on standard-
ized protocols and to establish performance measures
and benchmarks. Example of key measures include
“time from first medical contact to balloon,” “total is-
chemic time,” or “door to balloon” (D2B). These tem-
poral metrics reflect coordination of care and focus
on improving both an individual organization’s perfor-
mance and that of the entire community system. With-
out data integration spanning multiple providers and
agencies, it is impossible to calculate many of the key
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October–December 2018
Volume 27
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