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Keywords:

  • Bed occupancy rates;
  • hospital-acquired infections;
  • infectious disease epidemiology;
  • methicillin-resistant Staphylococcus aureus;
  • threshold

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

Clin Microbiol Infect 2012; 18: 941–945

Abstract

There is growing evidence that bed occupancy (BO) rates, overcrowding and understaffing influence the spread of hospital-acquired infections (HAIs). In this article, a systematic review of the literature is presented, summarizing the evidence on the adverse effects of high BO rates and overcrowding in hospitals on the incidence of HAIs. A Pubmed database search identified 179 references, of which 44 were considered to be potentially relevant for full-text review. The majority (62.9%) focused on methicillin-resistant Staphylococcus aureus-associated infection or colonization. Only 12 studies were found that provided a statistical analysis of the impact of BO on HAI rates. The median BO rate of the analysed studies was 81.2%. The majority of studies (75%) indicated that BO rates and understaffing directly influence the incidence of HAIs. Only three studies showed no significant association between BO rates and the incidence of HAIs. Interestingly, only one of the included studies detected a seasonal trend in the BO rate. The present review shows an association between BO rates and the spread of HAIs in various settings. Because the evidence on this topic is limited, we conclude that further research is needed in order to analyse the rationale of a threshold BO rate, because keeping beds empty is comparatively costly.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

Hospital-acquired infections (HAIs) are the most frequent adverse events in healthcare delivery [1]. Because of growing awareness in recent years, the burden caused by these infections, which is often complicated by antimicrobial resistance, has become a top priority within the European public health agenda [2,3]. It has been estimated that, in the EU alone, approximately 37 000 lives are lost because of HAIs each year, with an associated monetary cost of roughly €7 billion, which is mainly attributable to increased length of hospital stay [1].

HAIs are of great concern in European society, and may be considered from different viewpoints—those of the clinician, the healthcare official, a pharmaceutical company, the patient, and the public authority [4]. From a public health perspective, the major focus is on hospital-wide correlations between incidence rates of hospital-specific pathogens and a basket of hospital-specific parameters [5]. Transmission of HAIs is influenced by many different factors: several individual risk factors, such as exposure to invasive devices [6], antimicrobial use, intensity and frequency of patient contact with others or with the environment, and implementation of hygiene measures; and organizational and institutional factors. There is growing evidence that bed occupancy (BO) rates, overcrowding and understaffing do influence many of these transmission-associated factors. Unfortunately, relatively little is known about the effects of these organizational and institutional factors on the risk of HAIs [6]. Studies have shown that overcrowding and understaffing lead to failure of patient safety programmes via decreased healthcare worker hand hygiene compliance, increased movement of patients and staff between hospital wards, decreased levels of cohorting, and overburdening of screening and isolation facilities [7]. Even a BO threshold for patient safety has been discussed [8]; however, there are still insufficient data to support this. The present article summarizes the evidence on the influence of BO rates and overcrowding on HAIs.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

Studies were retrieved from PubMed (http://www.ncbi.nlm.nih.gov/pubmed/; accessed on 6 February 2012). Search terms included: (‘Clostridium difficile’ OR ‘VRE’ OR ‘vancomycin resistant enterococci’ OR ‘ESBL’ OR ‘extended spectrum beta lactamase’ OR ‘MRSA’ OR ‘methicillin-resistant Staphylococcus aureus’ OR ‘BSI’ OR ‘blood stream infections’ OR ‘central line-associated blood stream infections’ OR ‘CLA-BSI’ OR ‘VAP’ OR ‘ventilator acquired pneumonia’ OR ‘UTI’ OR ‘urinary tract infections’ OR ‘catheter-associated urinary tract infections’ OR ‘CA-UTI’ OR ‘SSI’ OR ‘surgical site infections’ OR ((‘nosocomial’ OR ‘hospital-associated’ OR ‘hospital-acquired’) OR ‘hospital associated’ OR ‘hospital acquired’) AND (‘infection’ OR ‘infections’))) AND (‘bed occupancy’ OR ‘overcrowding’ OR ‘bed utilization’ OR ‘workload’). References were also identified from the bibliographies of studies. The search was performed to identify studies that analysed the impact of BO on the spread of HAIs. The search was restricted to studies published between 1998 and February 2012. Language of publication was not restricted. The abstracts of all studies were reviewed. Two authors (K.K. and N.T.M.) independently assessed the inclusion (presence of a statistical analysis of association) and exclusion (reviews, comments, etc.) criteria. K.K. and N.T.M. abstracted data systematically and independently according to design, methods, sample size, type of infectious agent, and setting.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

Our literature search identified 179 references, of which 43 were considered to be potentially relevant for full-text review. An additional article was retrieved from the reference list in the literature [9]. Of the 44 full copies screened, 35 investigated the infectious agents associated with HAIs. The majority (62.9%) focused on methicillin-resistant S. aureus (MRSA)-associated infection or colonization. Only two focused on viral diseases (i.e. rotavirus and norovirus), and one on a parasitic disease (scabies).

Finally, 12 studies were identified as being valid for analysis. The flow of studies through the review process and the number of studies excluded are shown in Fig. 1.

image

Figure 1.  Flow chart of the review process.

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The findings from the 12 articles met the inclusion criteria and were considered to be relevant (Table 1). Of these, 66.7% (8/12) investigated MRSA-associated infection or colonization [9–16], one studied MRSA and extended-spectrum β-lactamase-producing Gram-negatives [5], one studied C. difficile [11], one studied Enterobacter cloacae [12], and one studied different infection types caused by varying agents (pneumonia and bloodstream infections) [17]. The median BO rate was 81.2%.

Table 1.   Characteristics of included studies
ReferenceSettingInvestigation period/type of studyType of infection/infectious agentBO rate (%)Potential threats to validityMain findingsAuxiliary findings
  1. ARIMA, autoregressive integrated moving average; BO, bed occupancy; BSI, bloodstream infection; ESBL, extended-spectrum β-lactamase; ICU, intensive-care unit; MLRM, multivariate linear regression model; MRSA, methicillin-resistant Staphylococcus aureus; NICU, neonatal intensive-care unit; PSM, patient safety measures; RR, risk ratio.

[10]900-bed hospital, all units included (general wards only, no ICUs)24 months of time-series data (surveillance data); retrospectiveMRSA infections76.3 (73–86)Not controlled for the number of patient bed-daysBO and MRSA incidence positively correlated
[11]900-bed hospital, 8 general medicine wards and 8 surgical wards, each with 30 beds65 months of time-series data (surveillance data); MLRM (ARIMA); prospectiveMRSA infections110 (91–124) Episodes of overcrowding triggered increases in MRSA incidenceSeasonal fluctuations with increase in BO and antibiotic use and decrease in staff and PSM during winter months
[12]1500-bed university hospital (including 120 ICU beds)67 months of time-series data (surveillance data); MLRM (ARIMA); retrospectiveMRSA infections and colonizations78 (64–90; general wards) BO and MRSA incidence positively correlatedBO and PSM negatively correlated
[13]12 hospitalsTwo periods of annual cross-sectional data; simple correlation coefficients (surveillance data); retrospectiveMRSA bactaeremia81.3 (62–92; first period); 82.5 (68–95; second period) BO and MRSA incidence positively correlated in second period, but not in first periodTurnover interval and MRSA incidence negatively correlated in second period, but not in first period
[9]38–40 hospitalsOne period of annual cross-sectional data, simple correlation coefficients (surveillance data); retrospectiveMRSA bactaeremia84.9 (76–94) BO and MRSA incidence positively correlated
[19]15-bed NICU, 60 patients12 months; multivariate logistic regression; retrospective Enterobacter cloacae infections and colonizationsAlternative measures of overcrowding/understaffingSmall sample sizeRR for acquisition of E. cloacae markedly higher in times of overcrowdingHigh non-compliance rate (37%) of staff with hand-washing and hand disinfection
[5]1500-bed university hospital (including 120 ICU beds)67 months of time-series data (surveillance data); MLRM (ARIMA); retrospectiveMRSA infections and colonizations; ESBL-producing Gram-negative infections and colonizations78 (69–86; general wards) BO and MRSA incidence and BO and ESBL incidence positively correlatedIncidence of nosocomial MRSA and ESBL showed decreasing and increasing trends, respectively
[18]1500-bed university hospital (including 120 ICU beds)67 months of time-series data (surveillance data); MLRM (ARIMA); retrospective Clostridium difficile (toxin-positive stool samples and/or cultured isolates)78 (64–90; general wards) BO and C. difficile incidence positively correlatedLength of stay and C. difficile incidence negatively correlated
[14]1 ICU, 61 patients48 months; multivariate logistic regression (surveillance data); retrospectiveMRSA infections and colonizationsAlternative measures of overcrowding/understaffingSmall sample sizeNo evidence that staffing or workload predicts risk of MRSA acquisition 
[15]33-bed NICU (223 patients)73 months of time-series data (surveillance data), MLRM (ARIMA); prospectiveMRSA infections and colonizations85.8 BO and MRSA incidence not significantly correlatedUse of hand sanitizers negatively correlated with MRSA incidence
[17]182 ICUs; 1313 pneumonia cases and 513 BSI cases12 months, linear regression model (surveillance data); retrospectiveBSI; pneumonia83 Fewer infections associated with high BO and higher nurse/ventilated patient ratioNurse/patient ratio not significantly associated with infection rates
[16]1 ICU, 50 patients19 months of time-series data, simple correlation coefficients; retrospectiveMRSA (not further specified)Alternative measures of overcrowding/understaffingSmall sample sizeSignificant correlation between MRSA incidence and: staff/patient ratio; nurse/patient ratio; and staff/workload ratio

The majority of the studies (75%) indicated that overcrowding of hospitals directly influences the incidence of HAIs. Six used monthly time-series data, and found a positive correlation for the incidence of HAIs and BO rates [5,10–12,16,18]. Of these, three used a multivariate adjusted autoregressive integrated moving average model [5,12,18], and three determined simple univariate correlation coefficients [10,11,13]. However, one study showed limited validity, as it was not controlled for the number of patient bed-days [10]. Two studies investigated annual cross-sectional data while applying a statistical comparison of BO and MRSA rates of different hospitals [9,13]. The first of these studies analysed two time periods, but found a positive correlation for the second period only [13]. The second study, however, applied the very same methodology to another set of hospitals, and found a positive correlation for the entire sample of data [9]. One study, a retrospective cohort study, found that the risk ratio for E. cloacae infection was markedly higher in times of overcrowding and understaffing [19].

In contrast to these studies, some (25%) found divergent results. One study, using a multivariate logistic regression including 61 MRSA patients (colonization and infections), found no evidence that intensive-care unit staffing or workload predicts the risk of MRSA acquisition [14]. Sakamoto et al. [15] used monthly time-series data to determine simple univariate correlation coefficients, and showed that BO rates (r = 0.033, p 0.199), patient/nurse ratio (r = −0.769, p 0.295) and colonization pressure (r = 0.006, p 0.571) were not significantly associated with MRSA incidence density rates. The only factor that was significantly associated was the amount of alcohol-based hand sanitizer used for one patient per day (= −0.769, p 0.011). The third descriptive epidemiological study analysed a total of 1312 cases of pneumonia and 513 cases of bloodstream infection . The major finding was that fewer nosocomial infections were associated with a high BO rate and a high nurse/ventilated patient ratio [17]. However, the turnover interval was not checked, which might have impaired the results. As, by definition, no case of nosocomial infection would appear if a patient stayed on a ward for <24 h, a short turnover interval could lead to an underestimation of incidence rates.

Interestingly, only one study detected a seasonal trend in the BO rates [11]. Although a seasonal trend can be excluded for some studies [5,12,18], for the majority of all studies (66%) no information on seasonality is available.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

BO rates have been proposed as a measure that reflects the ability of a hospital to properly care for patients [20]. However, whether this measure can be considered useful in guiding the planning and operational management of hospital beds in order to guarantee appropriate compliance with patient safety measures depends on the answers to three questions: (i) to what extent do BO rates influence patient outcomes; (ii) what would be a target BO rate to aspire to; and (iii) would any attempt to reduce the BO rate to the target level be cost-effective?

Patient safety measures such as hand hygiene may take considerable time. Overworked staff may feel that they do not have enough time to undertake these measures without compromising patient care. In addition, understaffing is most likely to happen when BO rates are high [6,9]. Accordingly, high BO rates directly impact on the incidence and spread of hospital-acquired infections, as shown in the present review of the literature. Only two studies showed no significant association between BO rates and the incidence of HAIs, and one found a negative correlation. In summary, the existing studies support the conclusion that BO rates have an important impact on patient outcomes. It is not clear to what extent BO rates have a direct impact on HAIs or can be considered as proxy indicators for deficiencies in hygiene measures resulting from overcrowding and understaffing. The implementation and the true extent of the use of patient safety measures such as hand disinfection and barrier precautions is interesting with regard to future studies. The main research in this field has been focused on mainly one pathogen only (MRSA). Little attention has been drawn to infections caused by Gram-negatives or viruses, or vancomycin-resistant enterococci. As transmission pathways differ between pathogens, it is interesting to investigate whether BO rates influence the incidence rates of differing pathogens to varying extents.

As mentioned before, one study showed that simple fluctuations in the BO rate did not have a direct impact on the incidence of MRSA infection as long as the BO rate was within designated levels. Instead, episodes of significant overcrowding, with occupancy levels in excess of designated numbers, triggered increases in infection incidence rates [10]. The BO rate analysed was, however, substantially higher (up to 120% during the winter months) than in any other study of this review (median of 81.2%).

A few studies suggested that high level of HAIs in the UK might have been attributable to the fact that BO rates exceeded the European average [8,21]. Consequently, it was proposed to define a threshold BO rate to deliver effective and safer healthcare. In detail, an absolute maximum BO rate in the range of 82–85% was proposed to keep the level of HAIs at the minimum possible level [8,21].

The question remains of whether the implementation of such a threshold BO rate would be rational in comparison with other patient safety measures. A recent study was aimed at answering this question by comparing the impacts of the BO rate and of hand disinfection, respectively, on the cost of MRSA-related infections [22]. Not surprisingly, the results indicated that hand disinfection is highly (cost-)effective. The economic interpretation of the correlation between the BO rate and the MRSA incidence rates, however, leads to another conclusion: One additionally occupied bed influences the BO rate and thus influences the number of HAIs, but the overall impact per single occupied bed is extremely low. In detail, keeping an additional bed unoccupied for 24 h saves only €0.39 in potential costs incurred by MRSA-related infections, an amount that is negligible [22].

These results are based on crude extrapolations, focus on the German reimbursement scheme, and may not be generalizable to the situation in other European countries. They may, however, underline the relevance of patient safety measures such as hand disinfection. Further research is needed to answer the question of whether there should be a threshold BO rate. The implementation of such a threshold BO rate, however, will always involve keeping beds empty, which is a costly measure, irrespective of the national healthcare organization and reimbursement scheme.

Transparency Declaration

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References

The authors declare that they have no competing interests.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Transparency Declaration
  8. References
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