Table Of ContentIntensive Care Information System Impacts 185
ACTA INFORM MED. 2013 Sep; 21(3): 185-191 doi: 10.5455/aim.2013.21.185-191
Received: 15 May 2013 • Accepted: 22 June 2013
conflict of interest: none declared
© AVICENA 2013
Intensive Care Information System Impacts
Asghar Ehteshami1, Farahnaz Sadoughi2, Maryam Ahmadi2; Parviz Kashefi3
Department of Health Information Management, School of Health Management and Information Sciences, Tehran
University of Medical Sciences, Tehran, Iran1
Department of Health Information Management, School of Health Management and Information Sciences, Tehran
University of Medical Sciences, Tehran, Iran2
Department of Intensive Care Medicine and Anesthesia, Faculty of medicine, Isfahan University of Medical
Sciences, Isfahan, Iran3
Corresponding Author: Associate prof. Farahnaz Sadoughi, PhD. Department of Health Information Management, School of Health
Management and Information Sciences, TUMS, No. 6, Rashid Yasemi St., Vali-e-asr Ave., Tehran, Iran. Email: [email protected]
Original Paper of intensive care information system on the by the intensive care environments empha-
ABSTRACT practices, patient outcomes and ICU per- sizes the opportunity of better intensive care
Introduction: Today, intensive care needs to formance. A total of 22 articles discussing services through patient oriented intensive
be increased with a prospect of an aging ICIS outcomes was included in this study care clinical information systems. There is an
population and socioeconomic factors influ- from 609 articles initially obtained from the immense need for developing guidelines for
encing health intervention, but there are some searches. Results: Pooling data across studies, standardizing ICIS to to maximize the power
problems in the intensive care environments, we found that the median impact of ICIS on of ICISs and to integrate with HISs. This will
it is essential to resolve. The intensive Care information management was 48.7%. The enable intensivists to use the systems in a
information system has the potential to solve median impact of ICIS on user’ outcomes was more meaningful way for better patient care.
many of ICU problems. The objective of the 36.4%, impact on saving tips by 24%, clinical This study provides a better understanding
review was to establish the impact of intensive decision support by a mean of 22.7%, clini- and greater insight into the effectiveness of
care information systems on the practitioners cal outcomes improved by a mean of 18.6%, ICIS in improving patient care and reducing
practice, patient outcomes and ICU perfor- and researches improved by 18%. Conclusion: health care expenses.
mance. Methods: Scientific databases and The functionalities of ICIS are growing day by Key words: ICU, ICIS, Information System,
electronic journal citations was searched to day and new functionalities are available with Outcome, Impact.
identify articles that discussed the impacts every major release. Better adoption of ICIS
1. INTRODUCTION
ical workflow interruptions, and Re- tiple tasks: Storing and processing
Today, intensive care needs to be source constraints (7, 8, 9). Clinical data and transform it to the
increased with a prospect of an aging In developing countries, not to suitable formats for clinical decision
population and socioeconomic fac- provide the information required making, Bringing distant data to the
tors influencing health intervention, by health plans often lead to unbal- bedside through an integrated HIS,
and there are some problems in the anced allocation of resources (10-12). Monitoring vital parameters and
ICUs, it is essential to resolve (1, 2, 3); Some factors affecting the quality detecting the specific problems, re-
Such as: Beds and skilled manpower of intensive care are as the follow- minding guidelines to intensive care
shortcoming, Exorbitant cost of treat- ings: Lack of accurate information team, improving decisions and clin-
ment, High rates of mortality, Severe upon infections and its inflicted ical guidelines fulfillment, reporting
Nosocomial infections, High LOS, heavy losses in lives and property in resources utilization and epidemi-
Low compliace with standards, Low intensive care, Irrational prescribing ology, and allow comparing of hos-
quality of care and improvements, antibiotics in the ICU, ICU Nurses pital costs (18-19). In addition, This
Epidemic of medical and medica- great errors in the calculation of the system is responsible for other duties
tion errors, Poor coordination of in- drugs dosage, inaccessibility of stan- including interface with bedside de-
tensive care team, and the lack of in- dard clinical guidelines and knowl- vices, physiological data capturing
formation required for clinical and edge at the point of care, and lack of automatically, computerized physi-
managerial decisions (4, 5, 6). Also, identifiable factors can increase ICU cian order entry, simplifying and ef-
Some problems must be considered mortality (13-14). ICIS has the poten- fecting processes, clinical alerting,
such as automatic scoring systems tial to improve Intensive care (15, 16) Reducing diagnosis and treatment
failure to predict disease severity and and is considered as the necessary time and optimizing them, and pre-
mortality, real time documentation solution for the Intensive care clin- venting of common medication er-
of clinical data, Inefficiency of inte- ical practice (16, 17). At the point of rors and adverse effects in ICU (4, 17).
grated clinical alerts, Significant clin- care, this system can perform mul- Also, the following functions are per-
ACTA INFORM MED. 2013 SEp; 21(3): 185-191 / ORIgINAl pApER
186 Intensive Care Information System Impacts
formed by ICISs: Improving medica- Journals, Thieme, American Institute erized Medical Records, Computer
tion safety by BCMA, reducing inter- of Physics (AIP), Biological abstracts, generated reminders, Computer-
ruptions, appropriate tracking and CINAHL, Google scholar, and IEEE ized provider order entry, Electronic
improving quality of care, reducing Xplor were the starting point for the Medical Records, Electronic Patient
costs, reducing mortality and mor- search which searched in May 2012 Records System, Medical knowledge
bidity rates, reducing the nutritional for articles that discuss the impacts based system, Real time data acqui-
calculation time, reducing ICU-LOS, of Intensive Care Information System sition system, Patient Medical Re-
controlling processes and clinical in- in all areas. The MeSH vocabulary, cords, Uniform diagnostic coding
stabilities, controlling personal ther- which is used to index MEDLINE system, Rapid response system, Pic-
apeutic styles, automatic charting articles, does not contain “Intensive ture Archiving and Communication
of patient data and eliminating re- care Information System” or “Critical System, Medical Information System,
dundancies, increasing direct care Care Information System”. However, Clinical management database Cal-
time, and better coordinating be- since the MeSH terms “critical culation systems such as Web based
tween caregivers (15, 16, 17, 18, 19). care” and “Intensive Care” are syn- insulin dose calculator, Critical Care
ICIS can improve quality of care by onymous, the terms “Intensive Care Computing Scoring and prediction
using sensor technology in real-time Information System”, “Critical Care systems such as Logistic organ dys-
monitoring and analyzing activities Information System” and their ab- function score, Prediction Models
and clinical staff training, real-time breviations (“CCIS” and “ICIS” [All Alerting systems such as Elec-
access to the laboratory results at the Fields]) were used to search the ar- tronic alerting, Wireless alert system
point of care and performing many ticles with a focus on the impacts of Conventional documentation sys-
of the tests on the patient’s bedside, this system. The search criteria did tems such as Electronic documenta-
stoke control and reducing the risk not include any limitation on publi- tion system, Other Intensive Care sys-
of ICU requirements lacks. Using cation date. The reference lists of in- tems like Critical Care network, Dig-
handheld computers for fast access cluded articles were also searched ital ICU system, ICU safety reporting
to patient information, reference in- systematically. The particular diffi- system, Intensive care monitoring
formation, guidelines, formularies, culties of searching the Intensive care (system), National ICU dataset
and tracking the educational expe- information system literature are the Emergency information system
rience of learners and linking with lack of full text for much of the work. Types of outcome: We included
a CIS, Graphical display of physio- Inclusion/Exclusion Criteria studies if they gave outcomes such as
logical data and transmit the data to This study mainly focused on the clinical outcomes, saving tips, infor-
the central knowledge base systems impact of intensive care software mation management, clinical deci-
for medical reasoning and hence, re- within the scope of health care, es- sion support, improving researches,
ducing the need for mechanical ven- pecially hospital. As such, the inclu- and user outcomes (Figure 1).
tilation and reducing mortality rates sion criteria for the articles were the Literature screening: During the
(18, 19, 20, 21, 22). This literature re- followings: search, we found 609 manuscripts
view concentrated on scientific arti- Type of Settings: The type of set- (Table 1). We reviewed the criteria
cles and conducted a critical analysis tings included was Intensive Care for inclusion and exclusion of arti-
of the methods and results of each ar- units. cles in two steps. In the first step, we
ticle that met the inclusion criteria in Type of Intervention: Intensive screened titles for duplicate articles
order to better understand the impact Care Information System includes and the study criteria that 452 articles
of an ICIS on these variables. Current all qualified Information systems and excluded. In the second step, we re-
gaps in the literature are highlighted software which were implemented in viewed the inclusion and exclusion
and directions for future research are intensive care units, especially Crit- criteria (setting, intervention, out-
suggested. ical Care Information System and Pa- comes) in 157 potentially relevant full
tient Data Management System. texts and the abstracts that 135 articles
2. METHODS We excluded the following sys- excluded: (a) No access to 37 full texts
In this study, we present a liter- tems: a) Systems designed for rois- after contact the author three times.
ature review of Intensive Care In- tering or workload measurement; (b) Not focus on the Intensive Care
formation System impacts. The Such as Nursing Management System, Information system in from 98 po-
original review considered only Eng- Nursing record system, Workload tentially article And, at the end step,
lish language publications. Scientific management system; b) Some gener- we reviewed articles’ bodies. Finally,
databases and electronic journals ci- ally used technologies such as Artifi- 22 articles included in our study.
tations including PubMed, Science cial intelligence, Barcode Medication Data collection and analysis:
Direct, Cochrane Library, Wiley, administration, Clinical information Two reviewing authors (in two pairs)
Wiley InterScience, Wiley Cochrane technology, Telemedicine, Medical reviewed all relevant articles and in-
Library, Ebsco, MD Consult, Web informatics, Handheld Computers dependently assessed the quality of
of Science, Web of knowledge, Up Systems generally used in hospitals each study and extracted relevant
To Date, Mosby Nursing Consult, and not specifically in ICU; like Clin- data on the impacts of ICIS in them,
Proquest, Scopus, Elsevier, Springer, ical decision Support systems, Clin- resolving any differences by discus-
Springer and Kluwer, Ovid, Oxford ical Information System, Comput- sion among all reviewing authors.
ORIgINAl pApER / ACTA INFORM MED. 2013 SEp; 21(3): 185-191
Intensive Care Information System Impacts 187
We entered extracted data in data Number of two articles on the careful analysis of
Database or e-Journal
extraction form, designed in Spss v. articles the care process (5, 13), two articles
20 software, and analyzed it with de- Web of science 18 on the standardizing of care (13, 14),
scriptive statistics. Pub Med 10 one article on the clinical consulta-
Science Direct 75 tion (2), one article on the improving
3. RESULTS Scopus 14 evidence based medicine (8), one ar-
Proquest 11
The literature searches resulted in ticle on the stratifying mortality risk
Springer 33
a total of 609 articles, which were (8), and one article on the reducing
American Institute of Physics (AIP) 17
then initially screened based on the mortality (17)”. Content analysis of
Biological Abstracts 1
titles and duplication, resulting in the study showed that the quality of
CINAHL 7
the exclusion of 452 articles. The re- intensive care improved by 64%, ICU
Cochrane Library 1
maining 157 articles were then re- Performance improved by 45%, med-
Ebsco 20
viewed in full text and abstract, and ical errors reduced by 36%, in 32% of
Elsevier 5
135 articles were excluded because in cases the clinical alert presented, the
Google scholar 181
37 articles we did not access to full quality of care evaluation facilitated
IEEE Xplor 4
text after even contact the authors in the 27% of cases, the clinical cal-
MD consult 6
after 3 times, and, they did not have Mosby nursing consult 3 culation was performed and medi-
focus on Intensive Care Information OVID 74 cation administration improved in
System but used this system for other Oxford journals 1 23% of cases. Also, ICIS interfaced
purposes. A total of 22 articles, dis- Springer and Kluwer 5 with clinical devices, tracked the pa-
cussing Intensive care Information Thieme 37 tients, specified their needs, and pre-
System, Critical Care Information UP to Date 22 dicted patient outcome as well as pro-
System, and Patient Data Manage- Wiley 27 viding tele-care in 18% of cases. Fur-
ment System, met the eligibility cri- Wiley Cochrane library 1 thermore, ICIS reduced clinical risk,
teria. The impacts were grouped Wiley InterScience 36 improved patient safety, managed an-
into six groups by system outcomes: Table 1. results of primary search in the databases and tibiotics, facilitated patient old and
(1) Clinical outcomes, (2) Informa- e-journals new conditions overviews, improved
tion management, (3) Saving tips, ical calculating (5, 7, 16, 18, 20), five multidisciplinary communications
(4) Clinical decision support, (5) articles on the improving medication and planed patient care in 14% of
User outcomes, and (6) Improving administration (7, 8, 11, 15, 21), four cases. In 9% of cases, moreover, ICIS
researches. Some outcomes fall articles on the interfacing with clin- standardized intensive care as well as
into more than one group; such as ical devices (3, 8, 9, 21), four articles careful analyzing of the care process.
“clinical calculating”. Pooling data on the patient tracking (2, 5, 11, 15), It stratified mortality risk, reduced it,
across studies, we found that the me- four articles on the
dian impact of ICIS on information predicting patient
management was 48.7%. The median outcome (2, 8, 16,
impact of ICIS on user’ outcomes 20), four articles on ICIS Outcomes
was 36.4%, impact on saving tips by the providing tele- OCulticnoicmael s SaTvipinsg MInafnoarmgeamtioennt CliniScuapl Dpoerctision rIemsperaorcvhinegs User Outcomes
24%, clinical decision support by a care (8, 13, 15, 19),
mean of 22.7%, clinical outcomes im- four articles on the Reducirnisgk clinical paimtiepnrto svainfegt y sTaivmineg dIantcar eqausainligty Comstpalniadnacred wsith Impatrtoitvued ueser
pseraorvcehde sb iym ap rmoveeadn boyf 1188%.6.%, and re- snpeeecdisf y(i8n, g1 3, p16at, i1e7n)t, mAannatigbeiomtiecn t Rmeodrutacliintgy RICeUdu-LcOinSg pMtaraetinaessnumtr'siet dathanteda meAdidcjauls dtienvgic es Inscaretiassfaincgti ounser
three articles on the Standacradreizing of acnaarley spisr oocfe tshse Ourpteitsliiozmauitrzicoineng kBnuoilwdl endegwe aIcmcepsrsoivbiinligty
4. CLINICAL OUTCOMES
reducing clinical Specifying Care Improving cost- Integration with Clinical decision
patient needs planning effectiveness other systems supporting
The Clinical outcomes of intensive risk and improving
care information system were dis- patient safety (2, 8, cOopvnaedtriivetiinoetnw s Pterolev-icdainreg Impeprrfoovrminagn ICceU Elienctterrocnhiacn dgaeta
cussed in 21 out of the 22 articles re- 9), three articles on Clinical Reflects Clinical Managing
consultation reality calculating patient data
viewed (Table 2). Of these, according the antibiotic man-
to the outcomes order of priority, agement (5, 15, 16), Patients tracking admImmeipdnriicsoatvrtiainotgino n meRdeicdaulc einrrgo rs doEcleucmtreonntiicn g
14 articles reported the improving three articles on
Interfacing with Stratifying Automated
clinical devices mortality risk reporting
quality of care (2, 3, 4, 5-15), 10 articles the overview pa-
discussed the improving ICU Perfor- tient old and new Impeprrfoovrminagn ICceU CPlinreicsaeln atlienrgt s
mance (2, 5-7, 11-13, 15-18), and other conditions (13, 16,
Evaluating Improving
quality of care quality of care
clinical outcomes were as follows: 21), three articles
eight articles on the reducing medical on the improving comImmpuronvicinatgi on caClcliunliactainl g
eclrerso rosn (2th, e5 ,p 7r-e9s, e1n1,t i1n5g, 1c7l)i,n siecvael na laerrttis- (cmomulmtiudnisicciaptlioinna r(y9), eviIdmmeepndrcoiecv ibinnaegs ed meRdeicdaulc einrrgo rs
(3, 5, 6, 8, 11, 15, 18), six articles on 13, 22)”, three ar- PatiPernetd oicuttincog me
the evaluating quality of care (2, 8, ticles on the care
13, 15, 17, 19), five articles on the clin- planning (9, 13, 19), Figure 1: Intensive Care Information System Impacts
Figure 1: Intensive Care Information System Impacts
ACTA INFORM MED. 2013 SEp; 21(3): 185-191 / ORIgINAl pApER
188 Intensive Care Information System Impacts
Table2: Description of the 22 studies’ clinical outcomes
Articles mation management outcomes and
Clinical Outcomes Ballermann Skouroliakou Steurbaut Hristoskova Junger Colpaert Meyfroidt Ballermann saving tips outcomes (r = 0.453, Sig.
et al., 75 et al., 35 et al., 58 et al., 68 et al., et al., 60 et al., 61 et al., 62
2011 2008 2012 2010 59 2010 2009 2009 = 0.034).
2001
Saving tips
Antibiotic management - - * * - - - -
Saving tips outcomes in ICIS were
Reducing mortality - - - - - - - -
discussed in 17 articles (Table 4). Of
Standardizing of care - - - - - - - -
these, 11 articles discussed the im-
Careful analysis of the care - - * - - - - -
process proving cost-effectiveness (2, 3, 5, 7,
8, 10, 13-16, 21) 10 articles on the time
Specifying patient needs - - - * - - * -
saving (3, 4, 5, 6, 8, 9, 14, 15, 18, 20),
Care planning - - - - - - - *
eight articles on the optimizing re-
Overview patient old and - - - * - - - -
new conditions source utilization (2, 7, 8, 11, 13, 15,
Providing tele-care - - - - - - * - 16, 18), two articles on the reducing
Clinical consultation - * - - - - - - medical errors (2, 8), two articles on
Reflects reality - - - - - - - - the clinical Calculating (5, 20), two
Patients tracking - * * - - - - - articles on the reducing ICU length
Improving medication - - - - - * * - of stay (LOS) (2, 15), and, two articles
administration
on the improving ICU performance
Interfacing with clinical - - - - - * *
devices (8, 15). Content analysis of the study
Stratifying mortality risk - - - - - - * - showed that ICIS improved cost-ef-
fectiveness of intensive care and time
Improving ICU performance - * * * * * - -
saving, respectively in 50% and 45%
Presenting Clinical alerts - - * - * - * -
of cases. Also, it optimized resource
Evaluating quality of care - * - - - - * -
utilization, reduced medical errors as
Improving quality of care - * * - * * * *
well as ICU LOS, and improved ICU
Improving communication * - - - - - - *
performances by 36%, 9% and 9%,
Improving evidence based - - - - - - * -
medicine respectively. We found a significant
Reducing clinical risk - * - - - - * * correlation between saving tips out-
Clinical calculating - - * * - * - - comes and the followings: user’ out-
Reducing medical errors - * * - - * * * comes (r = 0.458, Sig. = 0.032) and re-
searches improvement outcomes (r =
Predicting Patient outcome - * - * - - * -
0.426, Sig. = 0.048), but no significant
Table 2. Description of the 22 studies’ clinical outcomes
correlation with clinical decision sup-
and improved clinical consultation as ticles on the patient’s data measure port outcomes (r = 0.418, Sig. = 0.053).
well as evidence based medicine and, and transmit (2, 5, 6, 10, 11, 13, 20), six Clinical decision support
too. We found a significant correla- articles on the ICIS integration with Clinical Decision Support in inten-
tion between clinical outcomes and other information systems (1, 6-9, 11), sive care information systems was dis-
the followings: saving tips outcomes and, six articles on the building new cussed in the 13 articles (Table 5). Of
(r = 0.755, Sig. = 0.000), information knowledge from the gathered data these, 10 articles discussed clinical de-
management outcomes (r = 0.622, (2, 5-8, 21). Analysis of the content cision support (1, 5, 6, 8, 11, 13, 15, 16,
Sig. = 0.002) and clinical decision showed that ICIS documented clin- 19, 21), six articles on the improving
support outcomes (r = 0.509, Sig. = ical data electronically, automated re- accessibility (1, 6, 8, 13, 18, 22), three
0.016), but, no significant correlation porting and managed patient data in articles on the Compliance with stan-
with user’ outcomes (r = 0.414, Sig. = 82% of cases. It, also increased data dards set (8, 14, 15) and one article on
0.055) and researches improvement (r quality and interchanged data elec- the adjusting medical devices (8).
= 0.360, Sig. = 0.098). tronically in 55% and 41% of cases, According to analysis of content,
Information Management respectively. ICIS, moreover, mea- ICIS supported clinical decisions in
A total of 7 Information manage- sured and transmitted patient data in 45% of cases. It also improved prac-
ment outcomes of intensive care in- 32% of cases, integrated with other titioners’ accessibility to the infor-
formation system was discussed in 20 information systems and built new mation, compliance with standards
articles (Table 3). Of these, according knowledge from the gathered data and adjusted medical devices, re-
to the outcomes order of priority, 18 in 27% of cases. We found no signifi- spectively, by 27%, 14%, and 5%. We
articles focused on the electronic doc- cant correlation between informa- found a significant correlation be-
umenting and automated reporting tion management outcomes and the tween clinical decision support out-
(2, 3, 5-11, 13, 15-22), 18 articles on the followings: user’ outcomes (r = 0.303, comes and user’ outcomes (r = 0.496,
Managing patient data (1, 2, 3, 5-11, 13- Sig. = 0.171), clinical decision support Sig. = 0.019), but no significant cor-
16, 19-22), 12 articles on the increasing outcomes (r = 0.316, Sig. = 0.152), re- relation with research improvement
data quality (2, 3, 7, 8, 11, 13-17, 19, 21), searches improvement outcomes (r = outcomes (r = 0.280, Sig. = 0.207).
nine articles on the electronic data 0.214, Sig. = 0.338). But, we found a User Outcomes
interchange (2, 5-11, 16), seven ar- significant correlation between infor- 13 articles discussed user outcomes
ORIgINAl pApER / ACTA INFORM MED. 2013 SEp; 21(3): 185-191
Intensive Care Information System Impacts 189
Table2: Description of the 22 studies’ clinical outcomes (continued)
helped to perform researches.
Clinical Outcomes Articles
We found a significant correlation
Bete ragl.e, r Ralö.,h 7r2i g et Beto asml.,a 4n2 Met eayl.f,r o74i dt Dete acrl.u, y64e n2a0e0r3e Hetr aavl.n, a33k Ralö.,h 6r3i g2 0e1t 1 Aalr.t, s6 9e t between research improvement out-
71 2006 2009 2003 2009 1992 2002
come and saving tips (r = 0.426, Sig.
Antibiotic management * - - - - - - - = 0.048), but we found no significant
Reducing mortality - - - - - - - * correlation with the followings: clin-
Standardizing of care - - - - - - - ical decision support outcomes (r =
Careful analysis of the care - - - - - - - - 0.280, Sig. = 0.207), user’ outcomes
process
(r = 0.359, Sig. = 0.101), information
Specifying patient needs - - - - - - - -
management outcomes (r = 0.214, Sig.
Care planning - * - - - - - -
= 0.338) and clinical outcomes (r =
Overview patient old and new - - - * - - - -
conditions 0.362, Sig. = 0.098).
Providing tele-care * * - - - - - -
5. DISCUSSION
Clinical consultation - - - - - - - -
For several years, the number of
Reflects reality - - - - - - - -
intensive care clinical information
Patients tracking * - - - * - - -
systems has been spreading rapidly.
Improving medication * - - * * - - -
administration Some of the most putative appealing
Interfacing with clinical devices - - - * - - - - advantages of such systems are: elec-
Stratifying mortality risk - - - - - - - - tronic documentation and auto-
Improving ICU performance - - - - * - - * mated reporting, patient data man-
Presenting Clinical alerts - - * - - - - - agement, improving practitioners’
satisfaction, quality of care as well
Evaluating quality of care * * - - - - - *
as data, increasing cost effectiveness,
Improving quality of care * - * - * - * -
time saving, decision supporting
Improving (multidisciplinary) - - - - - - - -
communication and improving researches. ICIS has
Improving evidence based - - - - - - - - many clinical outcomes. According
medicine
to the study, this system improves the
Reducing clinical risk & - - - - - - - -
improving patient safety quality of care and the performance
Clinical calculating - - - - - - - - of the ICU. Also, it is able to provide
Reducing medical errors * - - - * - - * clinical alerts and thus considerably
Predicting Patient outcome - - - - - - - - reduce medical errors. In addition,
the system not only provides an eval-
Table 2. Description of the 22 studies’ clinical outcomes (continued)
Table3: Description of the 22 studies’ information management outcomes
of ICIS (Table 5). All of these, dis- Increasing Measure Build new Integration Electronic Managing Electronic
and patient documentation
cussed the increasing user satisfaction Studies data transmit knowledge with other data data and
quality the from the information interchange automated
(1, 2, 6, 8-11, 13-16, 18, 22). Also, three padtiaetnat 's gathered system reports
data
of these focused on the improving
user attitude (2, 8, 14). Content anal-
Berger et al., 71 2006 - - - - - - *
ysis of the study showed that ICIS in-
Röhrig et al., 72 2009 * - - - - * *
creased the users’ satisfaction by 59%. Bosman et al., 42 2003 * - - - - * *
It also improved their attitude in 14% Meyfroidt et al., 74 2009 * - * - - * *
of cases. We found a significant cor- Decruyenaere et al., 64 * * - * * * *
2003
relation between user’ outcomes and
Hravnak et al., 33 1992 - - - * - * -
the followings: clinical decision sup-
Röhrig et al., 63 2011 - * - - * * *
port outcomes (r = 0.496, Sig. = 0.019)
Arts et al., 69 2002 * - - - * * *
and saving tips (r = 0.458, Sig. = 0.032), Ballermann et al., 75 2011 - - - - - * *
but, we found no significant correla- Skouroliakou et al., 35 2008 * * * - * * *
tion between user’ outcomes and the Steurbaut et al., 58 2012 - * * - * * *
followings: research improvement Hristoskova et al., 68 2010 * - - - - * *
outcomes (r = 0.359, Sig. = 0.101), in- Junger et al., 59 2001 - * * * * * *
formation management outcomes (r Colpaert et al., 60 2010 * - * * * * *
= 0.303, Sig. = 0.118) and clinical out- Meyfroidt et al., 61 2009 * - * * * * *
comes (r = 0.414, Sig. = 0.055). Ballermann et al., 62 2009 - - - * * * *
Ilan et al., 65 1012 - - - - - - -
Improving research
Mador et al., 44 2009 - - - - - - -
Four articles reported impact of
Slosarik et al., 70 1980 * - - - - - *
intensive care information system on
De Keizer et al., 66 1998 * * - - - * *
the improving research (2, 8, 18, 21)
Junger et al., 73 2002 - * - - - * *
(Table 5). According to an analysis
LISING et al., 67 2005 * - - - - * -
of the content, ICIS, in 18% of cases,
Table 3. Descripti on of the 22 studies’ information management outcomes
3. Saving tips
ACTA INFORM MED. 2013 SEp; 21(3): 185-191 / ORIgINAl pApER
190 Intensive Care Information System Impacts
Table2: Description of the 22 studies’ clinical outcomes (continued)
Articles
In addition, ICIS is able to save
Clinical Outcomes Ilan et al., 65 Mador et Slosarik De Keizer Junger LISING
2012 al., 44 2009 et al., 70 et al., 66 et al., et al., 67 time and to increase the cost-effec-
1980 1998 73 2002 2005
tiveness of intensive care as well as op-
Antibiotic management - - - - - -
timizing resource utilization and re-
Reducing mortality - - - - - - ducing ICU LOS. This system enables
Standardizing of care - - - * - * clinicians to improve accessibility to
Careful analysis of the care process - - - * - - patient information. It is able to im-
Specifying patient needs - - - * - - prove the compliance with standards
Care planning - - - * - - as well as adjusting medical devices.
Overview patient old and new conditions - - - * - - Furthermore, ICIS increases the sat-
isfaction of nurses and intensivists,
Providing tele-care - - - * - -
and improves their attitude. Also, it
Clinical consultation - - - - - -
facilitates performing the clinical re-
Reflects reality - - - - - -
searches. There is the some signifi-
Patients tracking - - - - - -
cant correlation between various im-
Improving medication administration - - - - - -
pacts of ICIS. We think if clinical out-
Interfacing with clinical devices - - - - - -
comes improve in ICIS, saving tips,
Stratifying mortality risk - - - - - - information management and clin-
Improving ICU performance * - * * - - ical decision support outcomes will
Presenting Clinical alerts - - * - - - improve. Also, if we encourage saving
Evaluating quality of care - - - * - - tips outcomes in ICIS, it will be im-
Improving quality of care * * - * - * proved clinical, information manage-
Improving (multidisciplinary) - - - * - - ment and users’ satisfaction as well as
communication
improving researches. Moreover, if
Improving evidence based medicine - - - - - -
we strengthen the information man-
Reducing clinical risk & improving patient - - - - - - agement outcomes, clinical outcomes
safety
and Savings tips will improve, too. In
Clinical calculating - - * - * -
addition, If in the system upgrading,
Reducing medical errors - - - - - -
we have special attention to clinical
Predicting Patient outcome - - - - * -
decision support, thus, the nurses
Table 2. D escription of the 22 studies’ clinical outcomes (continued) Table 4: Description of the 22 studies’ saving tips outcomes
and intensivists satisfaction will be
uation of qu2a. liItnyfo romfa tcioanr Me,a nbaugetm aenlst o per- Time Reducing Optimizing Improving Improving Clinical Reducing
saving ICU-LOS resource cost- ICU calculating medical
forms the clinical calculations as well Studies utilization effectiveness performance errors
as improving medication administra-
tion, manages antibiotics and inter- Berger et al., 71 2006 * - * - - - -
face with medical devices. It is able Röhrig et al., 72 2009 - - - - - - -
to predict patient outcome(s), deter- Bosman et al., 42 2003 * - - * - - -
mine his/her needs and track him/
Meyfroidt et al., 74 2009 - - - * - - -
her and also it can provide tele-care
Decruyenaere et al., 64 - - * - - - -
in some cases. In addition, it is able 2003
to reduce clinical risk and thus bring Hravnak et al., 33 1992 - - - - - - -
patient safety. It also provides reviews
Röhrig et al., 63 2011 - - - * - - -
of previous and current status of the
Arts et al., 69 2002 - - * * - - -
patient to practitioners, plans patient
Ballermann et al., 75 2011 - - - - - - -
care, improves multidisciplinary
Skouroliakou et al., 35 2008 - * * * - - *
communication, standardizes the
intensive care and analyzes the care Steurbaut et al., 58 2012 * - - * - * -
process carefully. ICIS can stratify Hristoskova et al., 68 2010 * * * * * - -
mortality risk and thus reduce the Junger et al., 59 2001 * - - - - - -
ICU mortality rate. It moreover is Colpaert et al., 60 2010 - - * * - - -
able to improve Evidence-based med-
Meyfroidt et al., 61 2009 * - * * * - *
icine as well as medical consultations.
Ballermann et al., 62 2009 * - - - - - -
ICIS impacts on information man-
Ilan et al., 65 1012 - - - - - - -
agement. It measures some of patient
data and increases their quality as Mador et al., 44 2009 * - - - - - -
well as capturing them. It integrated Slosarik et al., 70 1980 - - - - - - -
with other hospital existing infor- De Keizer et al., 66 1998 - - * * - - -
mation systems; thus, exchanges the Junger et al., 73 2002 * - - - - * -
data between them and builds new
LISING et al., 67 2005 * - - * - - -
knowledge from the pooled data.
Table 4. De scription of the 22 studies’ saving tips outcomes
ORIgINAl pApER / ACTA INFORM MED. 2013 SEp; 21(3): 185-191
5. User Outcomes
Intensive Care Information System Impacts 191
Clinical decision support Users Research 5. Steurbaut K, Colpaert K, Van Hoecke S, Steurbaut S, Danneels
Studies Compliance Adjusting Improving Clinical Improve Increasing Improving C, Decruyenaere J, et al. Design and evaluation of a service ori-
with medical accessibility decision user user researches ented architecture for paperless ICU tarification. Journal of
standards devices making attitude satisfaction
medical systems. 2012; 36(3): 1403-1416.
Berger et al., 71 2006 - - * - - * * 6. Junger A, Michel A, Benson M, Quinzio LA, Hafer J, Hartmann
Röhrig et al., 72 2009 - - - - - - - B, et al. Evaluation of the suitability of a patient data manage-
ment system for ICUs on a general ward. International journal
Bosman et al., 42 2003 - - - - - - -
of medical informatics. 2001; 64(1): 57-66.
Meyfroidt et al., 74 2009 - - - - - - * 7. Colpaert K, Vanbelleghem S, Danneels C, Benoit D, Steurbaut
K, Van Hoecke S, et al. Has information technology finally been
Decruyenaere et al., 64 2003 - - - * - * -
adopted in Flemish intensive care units? BMC medical informat-
Hravnak et al., 33 1992 - - * * - * - ics and decision making. 2010; 10(1): 62.
Röhrig et al., 63 2011 - - - - - * - 8. Meyfroidt G. How to implement information technology in the
operating room and the intensive care unit. Best Practice & Re-
Arts et al., 69 2002 - - - * - * -
search Clinical Anaesthesiology. 2009; 23(1): 1-14.
Ballermann et al., 75 2011 - - * - - * - 9. Ballermann M, Shaw NT, Mayes DC, Gibney RN. Impact of a
Skouroliakou et al., 35 2008 - - - - * * * clinical information system on multitasking in two intensive
care units. Journal of Health Informatics. 2011; 7(1): e2.
Steurbaut et al., 58 2012 - - - * - - -
10. Röhrig R, Wrede C. Patientendatenmanagementsysteme. Inten-
Hristoskova et al., 68 2010 * - - * - * - sivmedizin und Notfallmedizin. 2011; 48(5): 411-416.
11. Decruyenaere J, DeTurck F, Vanhastel S, Vandermeulen F, De-
Junger et al., 59 2001 - - - * - * -
meester P, De Moor G. On the design of a generic and scalable
Colpaert et al., 60 2010 - - - - - - - multilayer software architecture for data flow management in
Meyfroidt et al., 61 2009 * * * * * * * the intensive care unit. Methods of information in medicine.
2003; 42(1): 79-88.
Ballermann et al., 62 2009 - - - - - * -
12. Ilan R, Doan J. Removing nonessential central venous cathe-
Ilan et al., 65 1012 - - - - - - - ters: evaluation of a quality improvement intervention. Cana-
Mador et al., 44 2009 - - - - - - - dian Journal of Anesthesia/Journal canadien d’anesthésie. 2012;
59(12): 1102-1110.
Slosarik et al., 70 1980 - - - - - - -
13. De Keizer N, Stoutenbeek C, Hanneman L, De Jonge E. An eval-
De Keizer et al., 66 1998 - - * * - * - uation of patient data management systems in Dutch intensive
care. Intensive care medicine. 1998; 24(2): 167-171.
Junger et al., 73 2002 - - - - - - -
14. Lising M, Kennedi C. A multimethod approach to evaluating
LISING et al., 67 2005 * - - - * * - critical care information systems. Computers Informatics Nurs-
ing. 2005; 23(1): 27-37.
Table 5. Description of the 22 studies’ outcomes related to clinical decision support, researches, and users
15. Berger MM, Revelly JP, Wasserfallen JB, Schmid A, Bouvry S,
provide d as well as clinical outcomes. to maximize the power of ICISs. This Cayeux MC, et al. Impact of a computerized information system
on quality of nutritional support in the ICU. Nutrition. 2006;
Discussion will enable intensivists to use the sys-
22(3): 221-229.
5. CONCLUSION tems in a more meaningful way for
For several years, the number of intensive care clinical information systems has been 16. Hristoskova A, Moeyersoon D, Van Hoecke S, Verstichel S, De-
The sfpurenadcintgi oranpiadllyi t(4ie6)s. Soofm et hofe t hsey mstoestm pust ativbee atptpeera lipnga atdiveanntta gceas roef .s uIcnh tseysntesmivs ear ec: are ap- cruyenaere J, De Turck F. Dynamic composition of medical sup-
are groweleicntrgo ndica dyo cbuym ednatayt ioann adn dn aeuwto mfuatnedc r-epoprtliincg,a ptaiotiennst dgaetat mmanoargeem aetntt,e inmtpiroovnin go n hos- port services in the ICU: Platform and algorithm design details.
tionalities are available with every pital day by day; the full potential of Computer methods and programs in biomedicine. 2010; 100(3):
248-264.
major release. The work of intensiv- ICIS has yet to be exploited.
17. Arts D, De Keizer N, Scheffer G, De Jonge E. Quality of data col-
ists and ICU nurses is very specific Acknowledgment
lected for severity of illness scores in the Dutch National Inten-
in nature. ICIS enable for electronic This study was part of a PhD disser- sive Care Evaluation (NICE) registry. Intensive Care Med. 2002;
documentation and automated re- tation supported by Tehran University 28: 656-659.
porting, patient data management, of Medical Sciences (grant No: TUMS/ 18. Slosarik W, Luger G, Kirkpatrick J, Koffler H, Burstein R, edi-
tors. The UNMH Intensive Care Information System. Proceed-
improving practitioners’ satisfac- SHMIS-1391/340).
ings of the Annual Symposium on Computer Application in
tion, quality of care as well as data,
Medical Care, AMIA. 1980:
increasing cost effectiveness, time REFERENCES 19. Röhrig R, Rüth R. Intelligent telemedicine in intensive care
saving, decision supporting and im- 1. Hravnak M, Stein K, Dale B, Hazy J, editors. Ongoing develop- units. Bed-side operation of medical technology devices and IT
proving researches. Better adoption ment of the Critical Care Information System: the collaborative in intensive care medicine]. Bundesgesundheitsblatt, Gesund-
of ICIS by the intensive care environ- approach to automating information management in an inten- heitsforschung, Gesundheitsschutz. 2009; 52(3): 279.
sive care unit. Proceedings of the Annual Symposium on Com- 20. Junger A, Böttger S, Engel J, Benson M, Michel A, Röhrig R, et
ments emphasizes the opportunity of
puter Application in Medical Care. AMIA, 1992. al. Automatic calculation of a modified APACHE II score using a
better intensive care services through 2. Skouroliakou M, Soloupis G, Gounaris A, Charitou A, Papasa- patient data management system (PDMS). International journal
patient oriented intensive care clin- rantopoulos P, Markantonis SL, et al. Data analysis of the ben- of medical informatics. 2002; 65(2): 145-157.
ical information systems, for example efits of an electronic registry of information in a neonatal in- 21. Meyfroidt G, Güiza F, Ramon J, Bruynooghe M. Machine learn-
clinical decision making, clinical cal- tensive care unit in Greece. Perspectives in Health Information ing techniques to examine large patient databases. Best Practice
Management/AHIMA, American Health Information Manage- & Research Clinical Anaesthesiology. 2009; 23(1): 127-143.
culating, and remote monitoring of
ment Association. 2008: 5. 22. Ballermann M, Shaw NT, Mayes DC, Gibney RN. Critical care
patients. There is an immense need 3. Bosman R, Rood E, Oudemans-van Straaten H, Van der Spoel J, providers refer to information tools less during communica-
for developing guidelines for stan- Wester J, Zandstra D. Intensive care information system reduces tion tasks after a critical care clinical information system in-
dardizing intensive care applications documentation time of the nurses after cardiothoracic surgery. troduction. International Perspectives in Health Informatics.
so that the application is used seam- Intensive care medicine. 2003; 29(1): 83-90. 2011; 164: 37.
4. Mador RL, Shaw NT. The impact of a Critical Care Information
lessly for ICU environment purposes
System (CCIS) on time spent charting and in direct patient care
and are integrated with HISs such as
by staff in the ICU: a review of the literature. International jour-
EMR and patient monitoring systems nal of medical informatics. 2009; 78(7): 435-445.
ACTA INFORM MED. 2013 SEp; 21(3): 185-191 / ORIgINAl pApER
