Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

Environmental contamination and hospital-acquired infection: factors that are easily overlooked

There is an ongoing debate about the reasons for and factors contributing to healthcare-associated infection (HAI). Different solutions have been proposed over time to control the spread of HAI, with more focus on hand hygiene than on other aspects such as preventing the aerial dissemination of bacteria. Yet, it emerges that there is a need for a more pluralistic approach to infection control; one that reflects the complexity of the systems associated with HAI and involves multidisciplinary teams including hospital doctors, infection control nurses, microbiologists, architects, and engineers with expertise in building design and facilities management. This study reviews the knowledge base on the role that environmental contamination plays in the transmission of HAI, with the aim of raising awareness regarding infection control issues that are frequently overlooked. From the discussion presented in the study, it is clear that many unknowns persist regarding aerial dissemination of bacteria, and its control via cleaning and disinfection of the clinical environment. There is a paucity of good-quality epidemiological data, making it difficult for healthcare authorities to develop evidence-based policies. Consequently, there is a strong need for carefully designed studies to determine the impact of environmental contamination on the spread of HAI.

Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients.

RATIONALE: Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. OBJECTIVES: We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. METHODS: The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. MEASUREMENTS AND MAIN RESULTS: In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9% and increased mean costs by $1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1% and costs increased by $1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8%, respectively, to maintain incremental cost-effectiveness ratios less than $50,000 per life-year saved. CONCLUSIONS: Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development.

Economics and preventing healthcare acquired infection

The evolution of organisms that cause healthcare acquired infections (HAI) puts extra stress on hospitals already struggling with rising costs and demands for greater productivity and cost containment. Infection control can save scarce resources, lives, and possibly a facility’s reputation, but statistics and epidemiology are not always sufficient to make the case for the added expense. Economics and Preventing Healthcare Acquired Infection presents a rigorous analytic framework for dealing with this increasingly serious problem. ----- Engagingly written for the economics non-specialist, and brimming with tables, charts, and case examples, the book lays out the concepts of economic analysis in clear, real-world terms so that infection control professionals or infection preventionists will gain competence in developing analyses of their own, and be confident in the arguments they present to decision-makers. The authors: ----- Ground the reader in the basic principles and language of economics. ----- Explain the role of health economists in general and in terms of infection prevention and control. ----- Introduce the concept of economic appraisal, showing how to frame the problem, evaluate and use data, and account for uncertainty. ----- Review methods of estimating and interpreting the costs and health benefits of HAI control programs and prevention methods. ----- Walk the reader through a published economic appraisal of an infection reduction program. ----- Identify current and emerging applications of economics in infection control. ---- Economics and Preventing Healthcare Acquired Infection is a unique resource for practitioners and researchers in infection prevention, control and healthcare economics. It offers valuable alternate perspective for professionals in health services research, healthcare epidemiology, healthcare management, and hospital administration. ----- Written for: Professionals and researchers in infection control, health services research, hospital epidemiology, healthcare economics, healthcare management, hospital administration; Association of Professionals in Infection Control (APIC), Society for Healthcare Epidemiologists of America (SHEA)

Hand hygiene noncompliance and the cost of hospital-acquired methicillin-resistant Staphylococcus aureus infection.

BACKGROUND: Hand hygiene noncompliance is a major cause of nosocomial infection. Nosocomial infection cost data exist, but the effect of hand hygiene noncompliance is unknown. OBJECTIVE: To estimate methicillin-resistant Staphylococcus aureus (MRSA)-related cost of an incident of hand hygiene noncompliance by a healthcare worker during patient care. DESIGN: Two models were created to simulate sequential patient contacts by a hand hygiene-noncompliant healthcare worker. Model 1 involved encounters with patients of unknown MRSA status. Model 2 involved an encounter with an MRSA-colonized patient followed by an encounter with a patient of unknown MRSA status. The probability of new MRSA infection for the second patient was calculated using published data. A simulation of 1 million noncompliant events was performed. Total costs of resulting infections were aggregated and amortized over all events. SETTING: Duke University Medical Center, a 750-bed tertiary medical center in Durham, North Carolina. RESULTS: Model 1 was associated with 42 MRSA infections (infection rate, 0.0042%). Mean infection cost was $47,092 (95% confidence interval [CI], $26,040-$68,146); mean cost per noncompliant event was $1.98 (95% CI, $0.91-$3.04). Model 2 was associated with 980 MRSA infections (0.098%). Mean infection cost was $53,598 (95% CI, $50,098-$57,097); mean cost per noncompliant event was $52.53 (95% CI, $47.73-$57.32). A 200-bed hospital incurs $1,779,283 in annual MRSA infection-related expenses attributable to hand hygiene noncompliance. A 1.0% increase in hand hygiene compliance resulted in annual savings of $39,650 to a 200-bed hospital. CONCLUSIONS: Hand hygiene noncompliance is associated with significant attributable hospital costs. Minimal improvements in compliance lead to substantial savings.

Modelling the impact of antibiotic use and infection control practices on the incidence of hospital-acquired methicillin-resistant Staphylococcus aureus: a time-series analysis

Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a major nosocomial pathogen worldwide. A wide range of factors have been suggested to influence the spread of MRSA. The objective of this study was to evaluate the effect of antimicrobial drug use and infection control practices on nosocomial MRSA incidence in a 426-bed general teaching hospital in Northern Ireland.

Methods: The present research involved the retrospective collection of monthly data on the usage of antibiotics and on infection control practices within the hospital over a 5 year period (January 2000–December 2004). A multivariate ARIMA (time-series analysis) model was built to relate MRSA incidence with antibiotic use and infection control practices.

Results: Analysis of the 5 year data set showed that temporal variations in MRSA incidence followed temporal variations in the use of fluoroquinolones, third-generation cephalosporins, macrolides and amoxicillin/clavulanic acid (coefficients = 0.005, 0.03, 0.002 and 0.003, respectively, with various time lags). Temporal relationships were also observed between MRSA incidence and infection control practices, i.e. the number of patients actively screened for MRSA (coefficient = -0.007), the use of alcohol-impregnated wipes (coefficient = -0.0003) and the bulk orders of alcohol-based handrub (coefficients = -0.04 and -0.08), with increased infection control activity being associated with decreased MRSA incidence, and between MRSA incidence and the number of new patients admitted with MRSA (coefficient = 0.22). The model explained 78.4% of the variance in the monthly incidence of MRSA.

Conclusions: The results of this study confirm the value of infection control policies as well as suggest the usefulness of restricting the use of certain antimicrobial classes to control MRSA.

Using economic data to reduce healthcare-acquired infection

In this issue Burns et al. report an estimate of the economic loss to Auckland City Hospital from cases of healthcare-associated bloodstream infection. They show that patients with infection stay longer in hospital and this must impose an opportunity cost because beds are blocked. Harder to measure costs fall on patients, their families and non-acute health services. Patients face some risk of dying from the infection.

The increased risks of death and extra lengths of hospital and ICU stay from hospital-acquired bloodstream infections : a case-control study

Objectives Hospital-acquired bloodstream infections are known to increase the risk of death and prolong hospital stay, but precise estimates of these two important outcomes from well-designed studies are rare, particularly for non-intensive care unit (ICU) patients. We aimed to calculate accurate estimates, which are vital for estimating the economic costs of hospital-acquired bloodstream infections.

Markers of systemic inflammation in diagnostics and in prediction of outcome of community-acquired infection

Sepsis is associated with a systemic inflammatory response. It is characterised by an early proinflammatory response and followed by a state of immunosuppression. In order to improve the outcome of patients with infection and sepsis, novel therapies that influence the systemic inflammatory response are being developed and utilised. Thus, an accurate and early diagnosis of infection and evaluation of immune state are crucial. In this thesis, various markers of systemic inflammation were studied with respect to enhancing the diagnostics of infection and of predicting outcome in patients with suspected community-acquired infection. A total of 1092 acutely ill patients admitted to a university hospital medical emergency department were evaluated, and 531 patients with a suspicion of community-acquired infection were included for the analysis. Markers of systemic inflammation were determined from a blood sample obtained simultaneously with a blood culture sample on admission to hospital. Levels of phagocyte CD11b/CD18 and CD14 expression were measured by whole blood flow cytometry. Concentrations of soluble CD14, interleukin (IL)-8, and soluble IL-2 receptor α (sIL-2Rα) were determined by ELISA, those of sIL-2R, IL-6, and IL-8 by a chemiluminescent immunoassay, that of procalcitonin by immunoluminometric assay, and that of C-reactive protein by immunoturbidimetric assay. Clinical data were collected retrospectively from the medical records. No marker of systemic inflammation, neither CRP, PCT, IL-6, IL-8, nor sIL-2R predicted bacteraemia better than did the clinical signs of infection, i.e., the presence of infectious focus or fever or both. IL-6 and PCT had the highest positive likelihood ratios to identify patients with hidden community-acquired infection. However, the use of a single marker failed to detect all patients with infection. A combination of markers including a fast-responding reactant (CD11b expression), a later-peaking reactant (CRP), and a reactant originating from inflamed tissues (IL-8) detected all patients with infection. The majority of patients (86.5%) with possible but not verified infection showed levels exceeding at least one cut-off limit of combination, supporting the view that infection was the cause of their acute illness. The 28-day mortality of patients with community-acquired infection was low (3.4%). On admission to hospital, the low expression of cell-associated lipopolysaccharide receptor CD14 (mCD14) was predictive for 28-day mortality. In the patients with severe forms of community-acquired infection, namely pneumonia and sepsis, high levels of soluble CD14 alone did not predict mortality, but a high sCD14 level measured simultaneously with a low mCD14 raised the possibility of poor prognosis. In conclusion, to further enhance the diagnostics of hidden community-acquired infection, a combination of inflammatory markers is useful; 28-day mortality is associated with low levels of mCD14 expression at an early phase of the disease.

Hospital-acquired human bocavirus in infants

Human bocavirus (HBoV) is a respiratory pathogen that affects young children. We screened 511 nasopharyngeal aspirates for hospital-acquired HBoV from infants hospitalised with respiratory infection from January to December 2008. Among 55 children with HBoV infection, 10 cases were hospital-acquired. Compared with the community-acquired cases, coinfection with other respiratory viruses in these patients was uncommon. HBoV should be considered for inclusion in screening protocols for nosocomial childhood respiratory infections, especially in intensive care units. (C) 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

Using a longitudinal model to estimate the effect of methicillin-resistant staphylococcus aureus infection on length of stay in an intensive care unit

Healthcare-associated methicillin-resistant Staphylococcus aureus(MRSA) infection may cause increased hospital stay or, sometimes, death. Quantifying this effect is complicated because it is a time-dependent exposure: infection may prolong hospital stay, while longer stays increase the risk of infection. We overcome these problems by using a multinomial longitudinal model for estimating the daily probability of death and discharge. We then extend the basic model to estimate how the effect of MRSA infection varies over time, and to quantify the number of excess ICU days due to infection. We find that infection decreases the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82), but is only indirectly associated with increased mortality. An infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% CI: 0.1, 0.5) for a patient with an APACHE II score of 10, and 1.2 days (95% CI: 0.5, 2.0) for a patient with an APACHE II score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection, but was slightly stronger closer to the start of infection. These results confirm the importance of MRSA infection in increasing ICU stay, but suggest that previous work may have systematically overestimated the effect size.

Key priorities for Australian infection control : summary of findings from the launch of the Centre for Research Excellence in Reducing Healthcare Associated Infections

The launch of the Centre of Research Excellence in Reducing Healthcare Associated Infection (CRE-RHAI) took place in Sydney on Friday 12 October 2012. The mission of the CRE-RHAI is to generate new knowledge about strategies to reduce healthcare associated infections and to provide data on the cost-effectiveness of infection control programs. As well as launching the CRE-RHAI, an important part of this event was a stakeholder Consultation Workshop, which brought together several experts in the Australian infection control community. The aims of this workshop were to establish the research and clinical priorities in Australian infection control, assess the importance of various multi-resistant organisms, and to gather information about decision making in infection control. We present here a summary and discussion of the responses we received.

Multilevel competing risk models to evaluate the risk of nosocomial infection

Introduction Risk factor analyses for nosocomial infections (NIs) are complex. First, due to competing events for NI, the association between risk factors of NI as measured using hazard rates may not coincide with the association using cumulative probability (risk). Second, patients from the same intensive care unit (ICU) who share the same environmental exposure are likely to be more similar with regard to risk factors predisposing to a NI than patients from different ICUs. We aimed to develop an analytical approach to account for both features and to use it to evaluate associations between patient- and ICU-level characteristics with both rates of NI and competing risks and with the cumulative probability of infection. Methods We considered a multicenter database of 159 intensive care units containing 109,216 admissions (813,739 admission-days) from the Spanish HELICS-ENVIN ICU network. We analyzed the data using two models: an etiologic model (rate based) and a predictive model (risk based). In both models, random effects (shared frailties) were introduced to assess heterogeneity. Death and discharge without NI are treated as competing events for NI. Results There was a large heterogeneity across ICUs in NI hazard rates, which remained after accounting for multilevel risk factors, meaning that there are remaining unobserved ICU-specific factors that influence NI occurrence. Heterogeneity across ICUs in terms of cumulative probability of NI was even more pronounced. Several risk factors had markedly different associations in the rate-based and risk-based models. For some, the associations differed in magnitude. For example, high Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were associated with modest increases in the rate of nosocomial bacteremia, but large increases in the risk. Others differed in sign, for example respiratory vs cardiovascular diagnostic categories were associated with a reduced rate of nosocomial bacteremia, but an increased risk. Conclusions A combination of competing risks and multilevel models is required to understand direct and indirect risk factors for NI and distinguish patient-level from ICU-level factors.