SYSTEMS-LEVEL QUALITY IMPROVEMENT
Using OPC and HL7 Standards to Incorporate an Industrial Big Data
Historian in a Health IT Environment
Márcio Freire Cruz
Carlos Arthur Mattos Teixeira Cavalcante
Sérgio Torres Sá Barretto
Received: 19 March 2018 /Accepted: 18 May 2018
Springer Science+Business Media, LLC, part of Springer Nature 2018
Health Level Seven (HL7) is one of the standards most used to centralize data from different vital sign monitoring systems. This
solution significantly limits the data available for historical analysis, because it typically uses databases that are not effective in
storing large volumes of data. In industry, a specific Big Data Historian, known as a Process Information Management System
(PIMS), solves this problem. This work proposes the same solution to overcome the restriction on storing vital sign data. The
PIMS needs a compatible communication standard to allow storing, and the one most commonly used is the OLE for Process
Control (OPC). This paper presents a HL7-OPC Server that permits communication between vital sign monitoring systems with
PIMS, thus allowing the storage of long historical series of vital signs. In addition, it carries out a review about local and cloud-
based Big Medical Data researches, followed by an analysis of the PIMS in a Health IT Environment. Then it shows the
architecture of HL7 and OPC Standards. Finally, it shows the HL7-OPC Server and a sequence of tests that proved its full
operation and performance.
OLE for process control
Big data historian
Medical Information Systems are crucial for the effective care
of patients under clinical monitoring. Although several solu-
tions are available, this work highlights the software embed-
ded in equipment designed to monitor the patients’ vital signs,
such as heart rate, temperature, and blood pressure, among
others [1, 2].
Vital sign monitoring systems generally use proprietary
technologies. This usually restricts their integration with
third-party systems or other devices within the Health IT en-
vironment [1, 3].
Systems Interoperability requires communication standards
that allow intercommunication. In Health IT Environments,
the Health Level Seven (HL7) standard is one of the most
important. HL7 employs a specific communication model
and vocabulary consistent with medical concepts, allowing
for data sharing among clinical systems, hospital administra-
tive systems, and laboratory and medical equipment [4, 5].
In general, centralized systems that monitor and store pa-
tients’ vital signs through heterogeneous equipment use the
HL7 standard in conjunction with local relational databases or,
recently, cloud-based Big Data systems. However, both solu-
tions store all the captured data without filtering. This is not
proficient for storing extremely large volumes of data (years
of minute-by-minute vital sign data, for example), which
limits the capacity to conduct historical analysis.
Industrial applications typically use a specific type of Big
Data Historian Database, called Process Information
Management Systems (PIMS). These systems can capture,
store and execute real-time queries regarding hundreds of var-
iables registered per second over years or decades, using filters
to store only the data that are important for future analysis.
PIMS require a communication standard, such as OLE for
Process Control (OPC), to store industrial device data, e.g.
flow rate, pressure and temperature data. A software program
known as an OPC Server captures data from industrial de-
vices, using their proprietary drivers to convert the data format
into the OPC standard [6–8].
This article is part of the Topical Collection on Systems-Level Quality
* Márcio Freire Cruz
Graduate Program in Mechatronics, Federal University of Bahia
(UFBA), Salvador, Bahia 40170-110, Brazil
Journal of Medical Systems (2018) 42:122