Monitoring the air microbiologic quality in health care units.

Sirbu, Dana ; Curseu, Daniela ; Popa, Monica 等

1. INTRODUCTION

Healthcare-associated infections are an important cause of morbidity and mortality in hospitals. Each year more than 2 million patients acquire healthcare-associated infections, resulting in a lot of deaths and healthcare costs that are very difficult to estimate (Burke, 2003). Infectious agents may be transmitted to patients and medical staff via several vectors, including instruments and air. Numerous studies concerning the importance of airborne transmission of pathogens in hospitals have been described previously (Burge, 1990; Gangneux et al., 2006). The aim of this study was to establish data on the microbial level in selected areas of health care units in order to improve the quality of air, to prevent air contamination and decrease the incidence of aerogenic infections.

2. MATERIALS AND METHODS

The study was conducted over a 12-month period in a county hospital from Cluj-Napoca, with different services. 16 hospital areas expected to have different densities of airborne microflora were selected from the following departments with a total of 667 beds: internal diseases (102 beds), surgical department (170 beds), neurosurgery (85 beds), gynecology (90 beds), otorinolaringology (70 beds), ophthalmology (75 beds), and psychiatry (75 beds). Air contamination was monitored by using a Slit-to-Agar (STA) biological air sampler (model Cassella) and different agar plates placed in two points of each of the tested rooms (Buddemeyer, 2005). Sampling was done during the morning hours (7-8 AM), before the beginning of the activity and in the afternoon hours (14-16 PM), at the end of the program, on 1day/month over a 12-month period, making a total of 48 samples for each location. This sampler drew air at a high speed through a narrow slit and blew it over a solid nutrient agar plate. The plate rotated at a uniform speed under the slit, and a complete rotation of the plate took 30 minutes. After each sampling period, the culture plate was immediately processed to determine bacterial growth. The total numbers of colony forming units (CFU) were counted and identified (Barrow & Feltham, 1993), and the data was expressed as the number of CFU per cubic meter of air sampled. Mean values ([+ or -]SD) were calculated for each hospital department.

3. RESULTS AND DISCUSIONS

Microbial air contamination data for different departments obtained before and after activity program are shown in Table 1. As expected, the mean bacterial counts before the activity were low (55- 314 CFU/[m.sup.3]).

Immediately after the program activity ended the levels of air contamination increased substantially (between 204 in operating rooms and 1564 CFU/[m.sup.3] in patient rooms), emphasizing the importance of air contamination monitoring in two moments of the day at least. The highest mean level (mean value: 822 CFU/[m.sup.3]) was in the patient rooms (314-1564 CFU/[m.sup.3]) which was associated with the level of traffic and human activity, lack of ventilation, surface contamination as previously demonstrated in other environments (Burge, 1990).

The second highest levels (mean value: 469 CFU/[m.sup.3]) were recorded in the intensive care rooms (276 - 685 CFU/[m.sup.3]). Results of air sampling in intensive care rooms were in the same range as those reported by several other investigators (Gangneux et al., 2006). However, some of the levels (i.e., 1149 CFU/[m.sup.3]) detected during the peak activity periods in neurosurgery services, were much higher than expected and recommended by national standards (<100[degrees]CFU/[m.sup.3]). The intensive care unit of a hospital is a true example of a "risk area" where the quality of the air is important to prevent possible hospital infections in the patient, and consequently to protect the patient's health.

Microbiological contamination of air in the operating room is generally considered to be a risk factor for surgical site infections in clean surgery. In line with expectations for clinical areas, the operating rooms recorded the lowest levels (mean value: 125 CFU/[m.sup.3]). The highest values were obtained in neurosurgery departments (mean 235 CFU/[m.sup.3] and the biggest more than 393 CFU/[m.sup.3] correlated with the peak activity). Operating room air is contaminated with microorganisms attached to lint, skin cells, or respiratory droplets, and their number is largely proportional to the amount of human activity in the room (Bergeron et al., 2007).

Our results showed (table 2) that the majority of isolated organisms were those associated with humans' activity (Staphylococcus spp., Micrococcus spp., and Streptococcus spp.) between 52 - 96% from samples, rather than with dust and soil (fungi, actinomycetes) just between 4 - 48% from samples. The number of microorganisms associated with dust and soil (Gangneux et al., 2002) were due to poor environmental sanitation or too inadequate air-handling. The efficiency of the filtration systems cannot be determined because the supplied air was not sampled during this study. 32.2 % of samplers were gram-positive cocci, and from this average 15.5 % were hemolytic (from 0 in operating rooms to 52% from samples in patient rooms from neurosurgery department).

This study illustrates the parameters which must be considered in a monitoring program. The most significant feature to consider is the fluctuation in airborne contamination levels of a given area in relatively brief time periods and the magnitude of such fluctuations. Consequently, it is necessary to collect a series of samples in sequence, with the briefest practical intervals between samplings. It is also necessary to be aware of the factors which influence the count and their fluctuation. Essentially, four major factors interact to determine the level of microbial contamination in a given space at a given time: the quality of air entering the space; the number of occupants in the space and the extent of their physical activity; the degree of contamination associated with the activity; and the rate of ventilation. We can add to these factors the particle size of the contaminants (which determines the rate of sedimentation) and the biological and environmental factors which influence biological decay (type of organism, temperature, humidity, radiation, etc.).

4. CONCLUSIONS

Environment monitoring must be regarded as an important phase to assure and improve the quality of the services provided by a hospital. Controlling and monitoring air microbial levels will help to ensure that the preventive measures put into place remain effective and will furnish indispensable data needed to track, identify, and remedy nosocomial infections, should they occur.

In this study the hospitals were able to maintain low contamination levels in certain critical areas (intensive care and operating rooms) by employing properly designed ventilation systems, careful housekeeping, traffic control, and personnel hygiene. The environment in patient rooms can be improved significantly by applying modern ventilation techniques. The active sampling must become an essential environmental monitoring tool, in medical sectors. A plan of environment monitoring could allow to define the real risks and to check if preventive and safeguard measures are correctly applied.

5. REFERENCES

Barrow, G.I & Feltham, R.K.A. (1993). Cowan and Steel's Manual for the Identification of Medical Bacteria. 3rd edition. ISBN 0-521-3261 1-7, Cambridge University Press

Bergeron, V.; Reboux, G.; Poirot, J. L. & Laudinet N. (2007). Decreasing Airborne Contamination Levels in High-Risk Hospital Areas Using a Novel Mobile Air-Treatment Unit Infect Control Hosp Epidemiol; october 2007, vol. 28, no. 10:1181-1186, ISSN: 0899-823X

Buddemeyer, J. (2005). Selecting and Active Air sampling Methodology Controlled Environments. Available from: http://www.cemag.us/articles.asp?pid=537 Accesed on: 2009-03-31

Burge, H. A. (1990). Risks associated with indoor infectious aerosols. Toxicol. Ind. Health, 1990, vol 6:263-274, ISSN (printed): 0748-2337, ISSN: 1477-0393

Burke, J.P. (2003). Infection control--a problem for patient safety. N Engl J Med, febr. 2003, vol 348, no7: 651-656

Gangneux, J.P.; Bretagne, S.; Cordonnier, C. et al. (2002). Prevention of nosocomial fungal infection: the French approach. Clin InfectDis. 35:343-346, ISSN: 1058-4838

Gangneux, J.P.; Gangneux, F.R.; Gicquel, G.; Tanquerel, J.J; Chevrier, S. & Poisson, M. (2006). Bacterial and Fungal Counts in Hospital Air: Comparative Yields for 4 Sieve Impactor Air Samplers with 2 Culture Media. Infect Control Hosp Epidemiol nov. 2006, 27: 1405-1408, ISSN: 1559-6834

*** (1982) Ministry of Health, Romania, Order no. 190/1982--technical rules to prevent and fight hospital infections

Tab. 1. Bacterial air contamination before and after the end the
program, in different areas of investigated hospital

Level of contamination (CFU/[m.sup.3])

 Mean Before
 [+ or -] SD activity
 (7-8 AM)

Patient rooms (N = 48 samples for each service)

National target (NT) 500

Mean values 822 314
Surgical services 594 [+ or -] 126 314 [+ or -] 202
Obstetrical services 425 [+ or -] 67 78 [+ or -] 103
Otorinola-ringology 590 [+ or -] 89 551 [+ or -] 69
Neuro- surgery 432 [+ or -] 104 78 [+ or -] 75
Ophthalmology 846 [+ or -] 102 236 [+ or -] 106
Medical services 1397 [+ or -] 245 393 [+ or -] 204
Psychiatry 1470 [+ or -] 548 551 [+ or -] 278

Intensive care rooms (N = 48 samples for each service)

National target (NT) 500
Mean values 469 276
Surgical services 196 [+ or -] 47 78 [+ or -] 105
Obstetrical services 550 [+ or -] 217 472 [+ or -] 178
Otorinola-ringology 550 [+ or -] 179 470 [+ or -] 107
Neurosurgery 580 [+ or -] 368 82 [+ or -] 105

Operating rooms (N= 48 samples for each service)

National target (NT) 300
Mean values 125 55
Surgical services 130 [+ or -] 65 78 [+ or -] 7
Obstetrical services 98 [+ or -] 32 55 [+ or -] 22
Otorinola-ringology 108 [+ or -] 28 49 [+ or -] 15
Neuro-surgery 235 [+ or -] 106 69 [+ or -] 41
Ophthalmology 51 [+ or -] 19 22 [+ or -] 12

 After % of
 activity samples
 (14-16 PM) > NT

Patient rooms (N = 48 samples for each service)

National target (NT) 1000

Mean values 1564 26.15
Surgical services 1181 [+ or -] 204 15.62
Obstetrical services 1186 [+ or -] 106 13.52
Otorinola-ringology 629 [+ or -] 138 5.2
Neuro- surgery 1023 [+ or -] 146 3.12
Ophthalmology 1417 [+ or -] 79 35.36
Medical services 2362 [+ or -] 365 49.92
Psychiatry 3149 [+ or -] 645 60.32

Intensive care rooms (N = 48 samples for each service)

National target (NT) 1000
Mean values 685 7.8
Surgical services 314 [+ or -] 204 0
Obstetrical services 629 [+ or -] 409 3.12
Otorinola-ringology 647 [+ or -] 408 3.12
Neurosurgery 1149 [+ or -] 158 24.96

Operating rooms (N= 48 samples for each service)

National target (NT) 600
Mean values 204 0
Surgical services 236 [+ or -] 123 0
Obstetrical services 157 [+ or -] 54 0
Otorinola-ringology 157 [+ or -] 49 0
Neuro-surgery 393 [+ or -] 128 0
Ophthalmology 78 [+ or -] 69 0

Tab. 2. Types of microorganism detected in the air of hospital
departments

Site Microorganism Microorganism
 associated with associated with
 humans activity soil and dust
 % samples % samples

 Total Hemolytic

Patient rooms from following services :

--surgical 89.5 20.8 10.5
--obstetrical 79.1 31.2 20.9
--otorinolaringology 52 20.8 48
--neuro--surgery 62.4 52.0 37.6
--ophthalmology 66.5 31.2 33.5
--medical services 52 18.7 48
--psychiatry 62.4 39.5 37.6

Intensive care rooms from following services :

--surgical 79.1 2.1 20.9
--obstetrical 96.0 4.2 4.0
--otorinolaringology 89.5 0 10.5
--neuro--surgery 87.4 20.8 12.6

Operating rooms from following services :

--surgical 62.4 0 37.6
--obstetrical 81.1 2.1 18.9
--otorinolaringology 76.9 0 23.1
--neuro--surgery 89.5 4.2 10.5
--ophthalmology 60.5 0 39.5