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  Table of Contents  
Year : 2014  |  Volume : 32  |  Issue : 1  |  Page : 3-5

Automated surveillance systems for health care associated infections: need of the hour

Department of Laboratory Medicine, Jai Prakash Narain Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi, India

Date of Submission27-Aug-2013
Date of Acceptance03-Jan-2013
Date of Web Publication4-Jan-2014

Correspondence Address:
P Mathur
Department of Laboratory Medicine, Jai Prakash Narain Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi
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Source of Support: NICMR, New Delhi, India.,, Conflict of Interest: None

DOI: 10.4103/0255-0857.124285

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How to cite this article:
Mathur P. Automated surveillance systems for health care associated infections: need of the hour. Indian J Med Microbiol 2014;32:3-5

How to cite this URL:
Mathur P. Automated surveillance systems for health care associated infections: need of the hour. Indian J Med Microbiol [serial online] 2014 [cited 2020 Oct 27];32:3-5. Available from:

Health-care associated infections (HCAIs/HAIs) are indicators of potential shortcomings in the overall quality of patient care. Infections acquired in health-care set-ups have serious adverse consequences, affecting the patients, their families, third party payers and society as a whole. Prevention of HAIs therefore needs to be prioritized. The growing concern about HAIs, together with other patient safety issues prompted the World Health Organization (WHO) to launch the World Alliance for Patient Safety. Prevention of HAIs was the target of the Alliance's First Global Patient Safety Challenge, 'Clean Care is Safer Care'. [1] Apart from reduced mortality and improved patient outcomes, the economic benefits of prevention of HAIs are enormous. A worrying aspect of prevention however, is that although a lot is talked about HCAIs, there is a general lack of information on the quantum of its disease burden. Unlike in the west, where well-established surveillance systems give dependable information, which can be used to monitor rates over time and place, such systems are practically non-existent in the developing world. Control and preventive activities can only begin with a sound and systematic base-line data. Thus, HAI surveillance has become mandatory in many countries.

The seminal Study of the Efficacy of Nosocomial Infection Control demonstrated that up to 10-70% of HAIs could be prevented by systematic surveillance and implementation of standard preventive guidelines. [2] Surveillance systems are key for designing evidence-based programs for prevention and control. An effective surveillance and an infection control programme are essential not only for the well-being of patients, but also for the safety of hospital personnel.

Surveillance systems help to identify local problems and priorities and to evaluate the effectiveness of infection control activities. The most important issue with the establishment of a surveillance system is the adoption/use of standard definitions, which have to be used across a country. Inter-hospital and national comparisons can only be done if such uniform definitions are used. In my opinion, this is also one of the major hurdles for the establishment of surveillance systems in developing countries. This is partly due to lack of meta-analytic studies from developing nations on validation of diagnostic criteria for an infection syndrome. In such a scenario, an option is to begin with definitions proposed by bodies such as the Centre for Disease Control and Prevention (CDC), National Healthcare Safety Network (NHSN), WHO, Nosocomial Infection National Surveillance Scheme (NINSS) etc.

The traditional manual methods of surveillance are cumbersome, time consuming, labour intensive and often insensitive. They may also be limited in scope and are often applied inconsistently. [3] In most of the hospitals, surveillance activities are passive, involving data analysis of microbiological culture reports of routinely sent diagnostic samples. These methods are thus, sample rather than patient-centric and miss out patients, whose samples were not sent for diagnostic testing. Surveillance systems need to evolve with changes in health-care systems. Thus, to effectively reduce HAIs, an active, real-time surveillance system is needed, which is reliable, time-efficient, based on standard definitions and which uses information obtained from existing hospital databases. An effective automated surveillance system may meet these needs. [4]

Automated surveillance is a generic term for the process of obtaining useful information from large interrelated databases by identifying abnormal distributions of variables with a defined setting. It is often a product of multiple databases such as laboratory information system, clinical information system, admission-discharge-transfer databases and even online medical records. [5] The use of medical informatics in infection control surveillance has fostered efforts to increase efficiency by computerising surveillance activities, such as collection, analysis and dissemination of data.

The new automated electronic surveillance systems are being increasingly used in most western hospitals. They can easily track unusual microbiologic events. This has revolutionised the concept of surveillance, facilitating automatic tracking, feeding back information to central agencies and analysing data from multiple hospitals using standard definitions. They are being increasingly used to monitor the rates of HAIs with great accuracy; detection of multi-drug resistant (MDR) infections and outbreaks; and to evaluate the effectiveness of preventive activities. [4],[6] Thus, automated surveillance systems are now recognised as potential drivers of health-care quality improvement. Computerised infection control surveillance can also perform control-charting activities. It can alert the physicians about a patient colonised with antibiotic resistant pathogen. An important advantage of the computerised system is that it can have decision support or notification feature aids in other infection control activities, ultimately helping in reducing HAIs.

Apart from sensitivity, they have also been reported to have a high specificity, positive predictive value, accuracy and time-efficiency. [6] This has helped in stepping up the surveillance activities from sample to patient-oriented ones. Since detection of HAIs is entirely dependent on its definition, incorporation of standard definitions in automated systems has been found to be its most important advantage. Daily recording of results also helps in temporal charting of HAIs for an individual patient. Automation ultimately also facilitates better utilisation of infection control nurses, as they can then devote more time to education, implementation of interventions and other infection control activities. [4]

Specific Software's like AD Bakt, Germwatcher , Electronic Microbiology Surveillance and COMPISS [7],[8] have been developed and implemented in individual hospitals to facilitate HAI surveillance. The CDC has recently initiated e-surveillance. National surveillance systems like the NHSN in the US, NINSS in England, KISS in Germany PREZIES in the Netherlands; NSHI in Belgium; NNSR in Hungary and RAISIN in France have been pivotal in implementing evidence-based protocols for infection control. The Hospitals in Europe Link for Infection Control through Surveillance aims to provide standard methods for surveillance of HAIs in Europe and a reference database for comparative purposes. Similarly, national surveillance systems are also in place in Japan (JANIS) and Australia (VICNISS).

This picture is in stark contrast to developing nations, where, due to lack of systematic surveillance, there is a paucity of information on the true prevalence of infections, which may actually be more than 40%. [1],[9] This in turn limits the formulation and implementation of preventive activities, which need to be targeted to priority areas. Today, Indian hospitals are facing severe problems of escalating MDR infections. Thus, preventive activities need to go beyond the current on-going practices, which rely mostly on passive surveillance. Many infections may be grossly over-diagnosed due to lack of uniform diagnostic criteria, prompting injudicious use of antimicrobials, in turn promoting drug resistance. The International Nosocomial Infection Control Consortium, a consortium based in Brazil is the only network operating in the developing countries, [10] which collects and analyses data from intensive care units across many developing nations and has been providing important data from these nations.

Thus, it is extremely important that we plan and implement preventive activities now. For this, the surveillance systems need to be augmented by switching to electronic formats, which can monitor each patient as soon as they are admitted. Use of standard definitions would also facilitate inter-hospital or inter-national comparison. The system will also help in generation of monthly rates of infections and help in monitoring these rates after implementation of any preventive activity. Development of automated surveillance systems can be a stepping-stone for the ultimate development of the much-needed National Nosocomial Infection Surveillance System for India.

 ~ Acknowledgment Top

The development of the indigenous software was funded through a grant support from Indian Council of Medical Research, whose aid is duly acknowledged.

 ~ References Top

1.World Health Organization is the publisher and no specific author name is mentioned that is the Organization WHO is the author of these guidelines. These guidelines were published in 2009. ISBN 978 92 4 159790 6 and is freely available on internet at the following web address  Back to cited text no. 1
2.Haley RW, Quade D, Freeman HE, Bennett JV. The SENIC Project. Study on the efficacy of nosocomial infection control (SENIC Project). Summary of study design. Am J Epidemiol 1980;111:472-85.  Back to cited text no. 2
3.Peterson LR, Brossette SE. Hunting health care-associated infections from the clinical microbiology laboratory: Passive, active, and virtual surveillance. J Clin Microbiol 2002;40:1-4.  Back to cited text no. 3
4.Wright MO, Perencevich EN, Novak C, Hebden JN, Standiford HC, Harris AD. Preliminary assessment of an automated surveillance system for infection control. Infect Control Hosp Epidemiol 2004;25:325-32.  Back to cited text no. 4
5.Write MO. Using computer technology to collect and manage data. In: Arias K, editor. APIC Infection Control Tool Kit Series: S urveillance Programs in Health Care Facilities. Washington DC: Association for Professionals in Infection Control and Epidemiology; 2003.  Back to cited text no. 5
6.Furuno JP, Schweizer ML, McGregor JC, Perencevich EN. Economics of infection control surveillance technology: Cost-effective or just cost? Am J Infect Control 2008;36 Suppl 3:S12-7.  Back to cited text no. 6
7.Rocha BH, Christenson JC, Evans RS, Gardner RM. Clinicians› response to computerized detection of infections. J Am Med Inform Assoc 2001;8:117-25.  Back to cited text no. 7
8.Dessau RB, Steenberg P. Computerized surveillance in clinical microbiology with time series analysis. J Clin Microbiol 1993;31:857-60.  Back to cited text no. 8
9.Raka L. Lowbury Lecture 2008: Infection control and limited resources - Searching for the best solutions. J Hosp Infect 2009;72:292-8.  Back to cited text no. 9
10.Rosenthal VD, Maki DG, Mehta A, Alvarez-Moreno C, Leblebicioglu H, Higuera F, et al. International Nosocomial Infection Control Consortium report, data summary for 2002-2007, issued January 2008. Am J Infect Control 2008;36:627-37.  Back to cited text no. 10


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