Adopting Integrated Health Information Systems in Intensive Care

Units

Christina-Athanasia Alexandropoulou

, Ilias Panagiotopoulos

and George Dimitrakopoulos

Department of Informatics and Telematics, Harokopio University, Athens, Greece

Keywords: Criticalities, Integrated Health Monitoring, Health Information Technology, Intensive Care Units.

Abstract: Although today’s advanced biomedical technology provides unsurpassed power in diagnosis, monitoring, and

treatment, interpretation of vast streams of information generated by this technology often poses excessive

demands on the cognitive skills of health-care personnel (nurses, doctors, etc). In addition, storage, reduction,

retrieval, processing, and presentation of information are significant challenges. These problems are most

severe in critical care environments such as Intensive Care Units (ICUs) where many events are life-

threatening and thus require immediate attention and the implementation of definitive corrective actions. As

such, the modern ICU environment provides fertile soil for the development of more accurate predictive

models, better decision support tools, and greater personalization of care. In this respect, the use of Health

Information Technology (HIT) and clinical informatics can rapidly analyse many variables to predict

outcomes of interest and face heavy uncertainties whose solution may require computing intensive tasks.

Therefore, the development of HIT-enabled specific applications or services to alleviate common information

management problems encountered in ICU environments is of fundamental importance. This paper discusses

the mixed-criticality characteristics of HIT-based systems in ICU environments, as a first requirement to

effectively manage them. To do so, the present study describes one principal use case, namely the Integrated

Intensive Care Clinical Information System (I-ICCIS), which stems from the combination of health

information technologies with classic health care practices in ICU environments. The main criticalities

anticipated in such a system are described, whereas open areas for future research activities are also identified.

1 INTRODUCTION

There is a broad consensus that health care in the 21st

century will require the intensive use of Health

Information Technology (HIT) and clinical

informatics to acquire and manage data, transform the

data to actionable information, and then disseminate

this information so that it can be effectively used by

the health-care personnel to improve patients’ care

(Gulavani and Kulkarni, 2010; Qi et al., 2017). Such

technology trends aim to help doctors and nurses to

keep up with the rapidly changing state of medical

knowledge, as well as to understand what these

changes mean for the treatment of specific patients.

In this respect, data from patient monitors and

medical devices, although available visually at the

bedside, is challenging to acquire and store in digital

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format. There is limited medical device

interoperability and integration with the electronic

medical record (EMR) remains incomplete at best and

cumbersome. Moreover, standard analytical

approaches provide little insight into a patient’s actual

pathophysiologic state (Islam et al., 2015).

Understanding the dynamics of critical illness

requires precisely time-stamped physiologic data

integrated with clinical context and processed with a

wide array of linear and nonlinear analytical tools.

This is well beyond the capability of typical

commercial monitoring systems. Such an

understanding derived from advanced data analytics

can aid health-care personnel in making timely and

informed decisions and improving patient outcomes

(Mieronkoski et al., 2017).

Alexandropoulou, C., Panagiotopoulos, I. and Dimitrakopoulos, G.

Adopting Integrated Health Information Systems in Intensive Care Units.

DOI: 10.5220/0009325302190225

In Proceedings of the 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2020), pages 219-225

ISBN: 978-989-758-420-6

219

The above problems are most severe in Intensive

Care Units (ICUs), which are hectic, chaotic, and

stressful work environments. Clinicians need to be up

to date on patient status at all times, coordinate and

follow plans for each patient, and closely

communicate critical information (Jacobs et al.,

2015). They need to continually observe, obtain, and

evaluate a vast array of information and collaborate

within a multidisciplinary team. They are required to

make diffιcult decisions about critically ill patients

under the pressure of time. Since team members

change with every shift, information can be lost in

multiple handovers. In addition, quick patient

turnover adds to the list of new issues that need to be

resolved on a daily or hourly basis. The combined

high cognitive workload and limited number of staff

available at any given time leads to an overall

decrease in situational awareness (Kurahashi et al.,

2016).

Furthermore, critical care involves highly

complex decision making. It is by nature data-intense.

Large volumes of data are collected from disparate

sources and reviewed usually retrospectively; and

even that is difficulty. Health care providers must

navigate through a jungle of monitors, screens,

software applications, and often paper charts that

provide supplemental patient data inherent in today’s

cacophony of information management systems (De

Georgia M. et al, 2015). In addition the amount of

information in critical care environments can be

overwhelming and difficult to process (Lighthall et

al., 2015). Accessing and integrating the required data

for decision-making can be time-consuming and

made difιcult by multiple logins, the need to use

different computers for certain tasks, or the

information sources being occupied or otherwise

unavailable. Furthermore, depending on local

resources and structure of an ICU, a large amount of

crucial information is still documented on paper by

multiple team members, often redundantly. This can

lead to missing or misplaced charts and a delay inflow

of information (James et al., 2018).

With the vision to build on the aforementioned

statements, modern ICU environments provide fertile

soil for the development of HIT-based systems, in

introducing data management supported tools and

greater personalization of care. In this manner, HIT-

based systems are expected to introduce many

benefits to the operation of ICUs; decrease of hospital

death, decrease of length of stay, decrease of cost and

increase of care quality (Heidari et al., 2013). In

addition, the complex information and

communication technology involved in HIT-based

systems may also include mission-critical

components (Ciccozzi et al., 2017). Identifying the

criticalities of the specific components, applications

or services in complex HIT-based systems is of

significant importance for their effective

implementation in ICU environments.

In the light of the above, digital management

systems and remote monitoring are on the corner,

aiming to prevent dangerous events and improve

patients’ outcome, considering high incidence of

adverse events, medical errors and shortage of

specialist nurse numbers in ICU. In that framework,

the present study aims to identify and model

criticalities of HIT-based systems in ICU, as a first

step to effectively manage them in system

implementation and deployment. Furthermore, one

principal use case that stems from the combination of

health information technologies with classic health

care practices in ICU is explored, by identifying and

explaining the mixed-criticality characteristics of the

associated system. In this respect, the present paper

proposes a hybrid data clinic management

framework, namely ‘I-ICCIS’ (Integrated Intensive

Care Clinical Information System) to pave the way

towards incorporating critical care informatics in

dynamically monitoring the patient’s status in ICU.

Such a framework aims to include acquisition,

synchronization, integration, and storage of all

relevant patient data generated from stand-alone

devices and disparate sources, that do not easily

integrate with one another, into a central information

platform, to extract clinically relevant features and

translate them into actionable information, parallel

with the assistance of health-care personnel.

The structure of this paper is as follows. Section 2

presents the background for this work, whereas health

information systems and technical challenges are

briefly discussed in section 3. ‘I-ICCIS’ framework

and its main criticalities are identified in section 4,

whereas concluding remarks and perspectives for

future work are drawn in section 5.

2 RELATED WORK AND

BACKGROUND

Healthcare is becoming one of the most attractive

applications fields, where the Information and

Communication Technologies (ICTs) can offer

improved access to care, increased quality and

efficiency and reduced costs. Such systems comprise

medical sensors, wireless networks and software

applications for patient and remote healthcare

monitoring.

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

220

In that framework, Milenkovic et al. (2006)

described the Terva monitoring system, which had

been introduced to collect data related to health

condition like blood pressure, temperature, sleep

conditions, weight, etc., over quite a long time. The

whole system has been housed in a suitcase that

includes a laptop, blood pressure monitor and several

other monitoring devices. Moreover, Shahriyar et al.

(2009) presented the Intelligent Mobile Health

Monitoring System (IMHMS), which provides

medical feedback to the patients through mobile

devices, based on the biomedical and environmental

data collected by deployed sensors. In addition, Lin et

al. (2018) developed a smart clothing–based

intelligent health monitoring system, which was used

for electrocardiography (ECG) signal collection and

heart rate monitoring, including eight kinds of

services, such as surveillance of signs of life, tracking

of physiological functions, monitoring of the activity

field, anti-lost, fall detection, emergency call for help,

device wearing detection, and device low battery

warning. Moreover, Watson for Oncology (IBM,

2016) assesses information from a patient’s medical

record and displays potential cancer treatment options

by combining the latest data of the international

bibliography with the analytical speed of IBM

Watson, in order to improve patient outcome.

Additionally, in the recent study of Lee et al.

(2019), an efficient, robust, and customizable

information extraction and pre-processing pipeline

for electronic health records has been addressed by

organizing data into a structured, machine-readable

format which can be effectively applied in clinical

research studies to optimize processes, personalize

care, and improve quality, and outcomes. Moreover,

Hammed and Owis (2015) have designed and

developed a real-time Integrated Health Monitoring

(IHM) system including biological sensors,

integrated networking, electronic patient records, and

web technology to allow remote monitoring of patient

status. This system aims to process, monitor and store

the vital signs of the patients starting from home until

reaching the hospital.

Following the above works, it should be stated

that storage, reduction, retrieval, processing, and

presentation of patient information are significant

challenges. These problems are most severe in critical

care environments such as Intensive Care Units

(ICUs) where many events are life-threatening and

thus require immediate attention and the

implementation of definitive corrective actions. A

review of the relevant literature reveals the ongoing

and increased interest in the HIT-based systems and

solutions for ICUs. In this manner, Hayes-Roth B. et

al (1992) presented the function of Guardian, an

intelligent system for intensive care monitoring.

Guardian’s system interprets perceived information

from the environment, performs all knowledge-based

reasoning and problem solving (e.g. problem

detection, diagnosis, prediction, planning, and

explanation) and decides what actions to perform. It

also constructs and modifies dynamic global control

plans to coordinate its perception, reasoning, and

action. Furthermore, Kaur and Shimi (2016) proposed

an intelligent patient monitoring system for ICUs

being able to acquire, store and present data to

medical staff. This system is able to independently

operate and it can replace, in some cases, the medical

staff in nursing centers. Besides, it provides a good

environment for the patients by offering an efficient

monitoring and the adequate treatment.

Prajapati et. al. (2017) are proposing an intelligent

real time IoT-based system for monitoring ICU

patients (IRTBS), which can help to fast

communication and identifying emergency and

initiate communication with healthcare staff and also

helps to initiate proactive and quick treatment.

Moreover, Flohr et. al. (2018) designed an intelligent

monitoring and communication system, namely

VitalPad, to improve patient safety in an pediatric

ICU. This system supports the clinical decision-

making via smart alerts, cumulative risks scores and

context-sensitive icons based on the assessment of

vital signs and other monitoring data, drug infusion

information, clinical checklists, and/or response to

application messages. In a more recent study,

Davoudi et. al. (2019) examined the feasibility of

using pervasive sensing technology and artificial

intelligence for autonomous and granular monitoring

in ICU. They used wearable sensors, light and sound

sensors, and a camera to collect data on patients and

their environment.

3 HEALTH INFORMATION

SYSTEMS AND TECHNICAL

CHALLENGES

The medical field is closely related to human life, and

a wrong decision is intolerable. With the intensive use

of health information technology and clinical

informatics, HIT-based systems tend to act more

intelligent and autonomously with their operation

based mainly on the computer’s and technological

equipment’s integrity. The key features that HIT-

based systems should have in general are the follow

(Osmon et al., 2004; Kotronis et al., 2017):

Adopting Integrated Health Information Systems in Intensive Care Units

221

▪ Accurate, comprehensive and complete data

collection, which include accurate and timely

recording of patients’ status and clinical events.

▪ Interfaces with other systems that will enhance

the reception and exchange of information.

▪ Ability to perform fast and complex queries in

order to retrieve the information that is

required.

▪ Availability of information for a wide range of

clinical and administrative purposes.

▪ The medical history, which will be stored in the

clinical information system, should be clearly

identifiable, interpretable and provide only the

necessary information without unnecessary

details.

▪ At every episode of care and every patient's

file, HIT-based systems should allow the

performing of retrospective checks on access

and processing and should be easily adapted to

user requirements wherever is possible.

In this manner, a clinical information system

relies on the accuracy of the data entered into it.

Therefore, it is important the quality control

measurements to be able to ensure the accuracy of the

data retrieved. In addition, it is not uncommon for the

health-care personnel to enter or extract data from the

chart that are referring to an incorrect patient, which

can lead to severe processing errors. In addition, the

successful integration with other information (digital

examinations from other laboratories), as well as the

medical equipment around the patient's bed, and

generally, within the unit, is highly desirable. For this

reason, it is necessary the existence of strict technical

standards, which will allow the necessary

communication infrastructure, facilitating the access

to vital information produced by all systems (Gambo

et al., 2011).

The malfunctions or computer viruses, the

system’s incompatibility, as well as the technical

damage to the equipment that make up the clinical

information system can lead to the destruction of

some databases included in the system. Therefore, the

backup of these systems, the use of secondary power

sources in emergencies and computer antivirus

programs are key ways that can prevent the

catastrophic loss of information included in the

clinical information systems (Sellars and Easay,

2008). Some examples of technical challenges can be

categorized to the following aspects:

▪ The ability to handle the enormous amount of

data produced by recording even a minimal

amount of data per patient.

▪ The need to ensure that all personal information

is kept in a secure environment. They should be

covered by legislation stipulating how

electronic information will be retrieved,

transmitted, and stored.

▪ The need to provide systems that support the

availability of data.

▪ User-friendly interfaces that can cover the

requirements for functionality and

performance.

▪ The need for communication methods between

the central clinical information system and

local peripheral systems through the ability to

exchange secure messages.

▪ The existence of a high quality clinical

information system, which will be flexible and

will ensure that the right data are available only

to the right people.

There are also issues regarding ownership and

management of data, who and how to handle the

information, such as anonymity in investigations,

who will have authorized access to the information

and for how long, and in what ways will have access.

In particular, only the treating clinicians would still

have to know to whom the data refers in order to act

on it.

Furthermore, the majority of HIT-based systems

have been designed to diagnose individually, but it is

difficult to exhaust human diseases by the rules. So,

the involvement of doctors and health care personnel

is required. Integrating doctors’ clinical diagnostic

process into a medical electronic health information

system (e-HIS) with powerful storage, searching, and

reasoning capabilities is expected to make a better

and faster diagnosis, as depicted in Figure 1. In this

direction, due to the fact that vast streams of data are

generated for patients which reflect dynamic and

complex physiology, data integration should be

managed in the appropriate clinical context. Most of

these parameters, however, are generated from stand-

alone devices that do not easily integrate with one

another. Some connect directly into the bedside

monitor but many others do not (or do so

incompletely meaning that not all the data is captured

electronically). A lack of functional medical device

interoperability is one of the most significant

limitations in health care today.

4 I-ICCIS FRAMEWORK AND

ITS MAIN CRITICALITIES

As mentioned previously, most care medical devices

are not designed to interoperate, and therefore there is

no universally adopted standard that facilitates

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

222

Figure 1: Integrating clinical diagnostic process into a

medical electronic health information system (e-HIS).

multimodal data acquisition and synchronization in a

clinical setting. In this direction, a central clinical

information system that provides comprehensive,

cross-manufacturer medical device integration for the

care of a single critically ill patient at the bedside of

an ICU is not available.

In the context of the present work, an Integrated

Intensive Care Clinical Information System, namely

‘I-ICCIS’, is proposed which enables the health-care

personnel (doctors, nurses, etc) to monitor the health

status of all the patients in an ICU for further

assessment and recommendations. Medical

information from the patients, e.g., stemming from

embedded sensors and digital vital signs, is

electronically transmitted via a secure channel to

clinical monitoring center of ‘I-ICCIS’. In addition,

critical information towards the examination results

from other laboratories should also be embedded in

digital form. As such, ‘I-ICCIS’ can be used for

monitoring physiological signs and health parameters

of the ICU patients in real-time. The health-care

personnel should be alerted if there is a cause for

concern, e.g., inferred symptoms of a health problem

which requires immediate medical attention.

Based o the above, ‘I-ICCIS’ architecture is

composed of three (3) subsystems:

▪ Patients’ clinical data monitoring center

(medical information from the patients is

introduced based on various sources to enhance

the interoperability),

▪ Data repository (medical data is stored and

processed),

▪ Patients’ health record (hand-made clinical

data, demographic information, clinical history

data).

Figure 2: I-ICCIS subsystems, components and criticalities.

Figure 2 illustrates ‘I-ICCIS’ as a mixed-

criticality system with its three subsystems in

conjunction with its criticalities. In the following, we

discuss the identified criticalities grouped related to

each discrete subsystem.

1st Subsystem – Patients’ Clinical Monitoring

Data Center. It is characterized as safety-critical

subsystem with a high significance in the ‘I-ICCIS’,

due to the fact that the operation and visualization of

the patients clinical data in real-time to the health-

care personnel is of fundamental importance. The

received bio-signals and examinations from medical

laboratories outside the ICU must be presented in

textual or graphical waveforms for visualization and

diagnosis purposes. In addition, it is critical for the

system to support multiple different platforms for the

data visualization. Accuracy, time and power

consumption regarding the real-time clinical status of

patients in the ICU are safety-critical parameters with

a very high significance.

2nd Subsystem – Patients’ Health Record. It is

characterized as safety-critical subsystem with a high

significance in the ‘I-ICCIS’. First, the accuracy and

time regarding the patient’s medical record are safety-

critical parameters with a very high significance as it

holds all patients sensitive medical data, demographic

information and clinical history data. Secondly, the

operation (power consumption) of the patients’ hand-

made clinical data to the patients’ medical record is

very important. In practice this subsystem involves

similar criticalities as in the clinical monitoring center

section.

3rd Subsystem – Data Repository. The challenge in

this subsystem is the management of medical data. It

is critical to protect patients sensitive medical data,

from the clinical monitoring data center and patients’

Adopting Integrated Health Information Systems in Intensive Care Units

223

health record to the data repository and then to ‘I-

ICCIS’. Data/service reliability, data availability,

privacy and flexibility regarding the data repository

of the presented health-care information system in the

ICU are critical parameters with a very high

significance.

‘I-ICCIS’ as a Whole Clinical Information

Framework. In general, the ‘I-ICCIS’ inherits the

criticalities of its subsystems (clinical monitoring

data center, data repository, patients’ health record).

In this section, we expand on the criticalities of the ‘I-

ICCIS’ as an integrated system (Kotronis et. al.,

2017).

First, the real-time monitoring process is safety-

critical. The ‘I-ICCIS’ has functions that must react

in real-time and provide time predictable

communication among different devices. A failure to

perform an operation within a given time may result

in serious harm. The significance of the real-time

monitoring is very high.

Secondly, the fault isolation is also a safety-

critical parameter. Faults in an application / device

must not propagate to other. Any fault must be

handled by the failing application itself or by the

system, while cascading failure effects should be

highly improbable. In addition, the real-time behavior

of an application must be correct, independently of

the execution of other applications. Moreover, due to

high significance of the data, the traffic leaving the

devices must be encrypted, while ensuring their

integrity. It is critical to avoid errors or intentional

modification to the data being transmitted. In order to

meet this criticality, well-known network security

protocols and software suites can be employed.

The ‘I-ICCIS’ framework must provide fault

information to the devices, applications (lost data)

and system. As such, fault information occurring at

the lower levels is a safety-critical parameter for

taking corrective actions. Moreover, another highly

significant safety-critical parameter is the systems’

interconnection. All the devices (e.g., sensors, digital

vital signs, digital results from laboratory

examinations) must interact and cooperate. In

addition, ‘I-ICCIS’ management framework should

be developed while taking into account health care

certificability for higher applicability in the ICU

domain. Finally, data should have a robust and

extendable standard format to be readable more or

less indefinitely.

5 CONCLUSIONS

Recent trends in the world of HIT-based systems and

clinical informatics to acquire and manage data,

transform the data to actionable information, and then

disseminate this information so that it can be

effectively used to improve patient care, have paved

the way for innovative healthcare services and

applications. Those services and applications are

most severe in critical care environments such as

Intensive Care Units (ICUs) where many events are

life-threatening and thus require immediate attention

and the implementation of definitive corrective

actions. Therefore, managing the criticalities of

specific subsystems and components in such

environments is of fundamental importance.

In this respect, this paper aims to identify

technical challenges towards HIT-based systems, as a

first step to effectively manage them in system

implementation and deployment. In addition, the

present study proposes a hybrid data clinic

management framework, namely ‘I-ICCIS’

(Integrated Intensive Care Clinical Information

System) to pave the way towards incorporating

critical care informatics in dynamically monitoring

the patient’s state in ICU. Such a framework

integrates all relevant patient data generated from

stand-alone devices and disparate sources that do not

easily integrate with one another, into a central

information platform, to extract clinically relevant

features and translate them into actionable clinical

information. Fundamental aspects on the mixed-

criticality characteristics of ‘I-ICCIS’ are presented in

detail.

Last, this work opens the gates to a series of

exciting work areas. First, a generic HIT-based

architecture for supporting mixed-criticality

healthcare systems in ICUs shall be specified.

Second, a set of requirements regarding ICU

environment can be further extended. Third,

interoperation and communication issues among

different sources and devices shall be explored due to

their crucial importance within the context of ICUs.

Fourth, additional novel healthcare oriented

applications for ICUs can be investigated, through the

proposed approach. Moreover, AI-enabled solutions

should be implemented in the presented integrated

intensive care clinical data management system for

making life-critical decisions and predicting adverse

outcomes before they happen, better manage highly

complex situations, and ultimately allow clinicians to

spend less time analyzing data and more time

harnessing their experience and human touch in

delivering care. Finally, what could also be

ICT4AWE 2020 - 6th International Conference on Information and Communication Technologies for Ageing Well and e-Health

224

investigated is to understand aspects that are likely to

maximize health-care personnel (nurses, doctors, etc)

adoption of intelligent integrated HIT-based systems

in ICUs.

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