Comparison of multistate model, survival regression, and matched case-control methods for estimating excess length of stay due to healthcare-associated infections.

BACKGROUND: A recent systematic review recommended time-varying methods for minimizing bias when estimating the excess length of stay (LOS) for healthcare-associated infections (HAIs); however, little evidence exists concerning which time-varying method is best used for HAI incidence studies. AIM: To undertake a retrospective analysis of data from a one-year prospective incidence study of HAIs, in one teaching hospital and one general hospital in NHS Scotland. METHODS: Three time-varying methods - multistate model, multivariable adjusted survival regression, and matched case-control approach - were applied to the data to estimate excess LOS and compared. FINDINGS: The unadjusted excess LOS estimated from the multistate model was 7.8 (95% confidence interval: 5.7-9.9) days, being shorter than the excess LOS estimated from survival regression adjusting for the admission characteristics (9.9; 8.4-11.7) days, and the adjusted estimates from matched case-control approach (10; 8.5-11.5) days. All estimates from the time-varying methods were much lower than the crude time-fixed estimates of 27 days. CONCLUSION: Studies examining LOS associated with HAI should consider a design which addresses time-dependent bias as a minimum. If there is an imbalance in patient characteristics between the HAI and non-HAI groups, then adjustment for patient characteristics is also important, where survival regression with time-dependent covariates is likely to provide the most flexible approach. Matched design is more likely to result in data loss, whereas a multistate model is limited by the challenge in adjusting for covariates. These findings have important implications for future cost-effectiveness studies of infection prevention and control programmes.

Epidemiology of healthcare-associated infection reported from a hospital-wide incidence study: considerations for infection prevention and control planning.

BACKGROUND: The measure of disease frequency most widely used to report healthcare-associated infection (HAI) is the point-prevalence survey. Incidence studies are rarely performed due to time and cost constraints; they show which patients are affected by HAI, when and where, and inform planning and design of infection prevention and control (IPC) measures. AIM: To determine the epidemiology of HAI within a general and a teaching hospital in Scotland. METHODS: A prospective observational incidence study was undertaken for one year from April 2018 using data collected as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. A novel, robust approach was undertaken, using record linkage to national administrative data to provide full admission and discharge information. Cases were recorded if they met international HAI definitions. FINDINGS: Incidence of HAI for the combined hospitals was 250 HAI cases per 100,000 acute occupied bed-days (AOBD). Highest frequency was in urinary tract (51.2 per 100,000 AOBD), bloodstream (44.7), and lower respiratory tract infection (42.2). The most frequently reported organisms were Escherichia coli, Staphylococcus aureus, and norovirus. Incidence of HAI was higher in older people and emergency cases. There was an increase in the rate of HAI in summer months (pneumonia, respiratory, surgical, and gastrointestinal infection) and in winter months norovirus gastrointestinal infection (P < 0.0001). The highest incidence specialties were intensive care, renal medicine, and cardiothoracic surgery. HAI occurred at a median of 9 days (interquartile range: 4-19) after admission. Incidence data were extrapolated to provide an annual national estimate of HAI in NHS Scotland of 7437 (95% confidence interval: 7021-7849) cases. CONCLUSION: This study provides a unique overview of incidence of HAI and identifies the burden of HAI at the national level for the first time. Understanding the incidence in different clinical settings, at different times, will allow targeting of IPC measures to those patients who would benefit the most.

Impact of healthcare-associated infection on length of stay.

BACKGROUND: Increased length of stay (LOS) for patients is an important measure of the burden of healthcare-associated infection (HAI). AIM: To estimate the excess LOS attributable to HAI. METHODS: This was a one-year prospective incidence study of HAI observed in one teaching hospital and one general hospital in NHS Scotland as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. All adult inpatients with an overnight stay were included. HAI was diagnosed using European Centres for Disease Prevention and Control definitions. A multi-state model was used to account for the time-varying nature of HAI and the competing risks of death and discharge. FINDINGS: The excess LOS attributable to HAI was 7.8 days (95% confidence interval (CI): 5.7-9.9). Median LOS for HAI patients was 30 days and for non-HAI patients was 3 days. Using a simple comparison of duration of hospital stay for HAI cases and non-cases would overestimate the excess LOS by 3.5 times (27 days compared with 7.8 days). The greatest impact on LOS was due to pneumonia (16.3 days; 95% CI: 7.5-25.2), bloodstream infections (11.4 days; 5.8-17.0) and surgical site infection (SSI) (9.8 days; 4.5-15.0). It is estimated that 58,000 bed-days are occupied due to HAI annually. CONCLUSION: A reduction of 10% in HAI incidence could make 5800 bed-days available. These could be used to treat 1706 elective patients in Scotland annually and help reduce the number of patients awaiting planned treatment. This study has important implications for investment decisions in infection prevention and control interventions locally, nationally, and internationally.

Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection.

BACKGROUND: Few healthcare-associated infection (HAI) studies focus on risk of HAI at the point of admission. Understanding this will enable planning and management of care with infection prevention at the heart of the patient journey from the point of admission. AIM: To determine intrinsic characteristics of patients at hospital admission and extrinsic events, during the two years preceding admission, that increase risk of developing HAI. METHODS: An incidence survey of adults within two hospitals in NHS Scotland was undertaken for one year in 2018/19 as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. The primary outcome measure was developing any HAI using recognized case definitions. The cohort was derived from routine hospital episode data and linkage to community dispensed prescribing data. FINDINGS: The risk factors present on admission observed as being the most significant for the acquisition of HAI were: being treated in a teaching hospital, increasing age, comorbidities of cancer, cardiovascular disease, chronic renal failure and diabetes; and emergency admission. Relative risk of developing HAI increased with intensive care unit, high-dependency unit, and surgical specialties, and surgery <30 days before admission and a total length of stay of >30 days in the two years to admission. CONCLUSION: Targeting patients at risk of HAI from the point of admission maximizes the potential for prevention, especially when extrinsic risk factors are known and managed. This study proposes a new approach to infection prevention and control (IPC), identifying those patients at greatest risk of developing a particular type of HAI who might be potential candidates for personalized IPC interventions.

Bed-days and costs associated with the inpatient burden of healthcare-associated infection in the UK.

BACKGROUND: Healthcare-associated infection (HAI) is associated with increased morbidity and mortality resulting in excess costs. AIM: To investigate the impact of all types of HAI on the inpatient cost of HAI using different approaches. METHODS: The incidence, types of HAI, and excess length of stay were estimated using data collected as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. Scottish NHS reference costs were used to estimate unit costs for bed-days. Variable (cash) costs associated with infection prevention and control (IPC) measures and treatment were calculated for each HAI type and overall. The inpatient cost of HAI is presented in terms of bed-days lost, bed-day costs, and cash costs. FINDINGS: In Scotland 58,010 (95% confidence interval: 41,730-74,840) bed-days were estimated to be lost to HAI during 2018/19, costing £46.4 million (19m-129m). The total annual cost in the UK is estimated to be £774 million (328m-2,192m). Bloodstream infection and pneumonia were the most costly HAI types per case. Cash costs are a small proportion of the total cost of HAI, contributing 2.4% of total costs. CONCLUSION: Reliable estimates of the cost burden of HAI management are important for assessing the cost-effectiveness of IPC programmes. This unique study presents robust economic data, demonstrating that HAI remains a burden to the UK NHS and bed-days capture the majority of inpatient costs. These findings can be used to inform the economic evaluation and decision analytic modelling of competing IPC programmes at local and national level.

Evaluating the post-discharge cost of healthcare-associated infection in NHS Scotland.

BACKGROUND: Whereas the cost burden of healthcare-associated infection (HAI) extends beyond the inpatient stay into the post-discharge period, few studies have focused on post-discharge costs. AIM: To investigate the impact of all types of HAI on the magnitude and distribution of post-discharge costs observed in acute and community services for patients who developed HAI during their inpatient stay. METHODS: Using data from the Evaluation of Cost of Nosocomial Infection (ECONI) study and regression methods, this study identifies the marginal effect of HAI on the 90-daypost-discharge resource use and costs. To calculate monetary values, unit costs were applied to estimates of excess resource use per case of HAI. FINDINGS: Post-discharge costs increase inpatient HAI costs by 36%, with an annual national cost of £10,832,437. The total extra cost per patient with HAI was £1,457 (95% confidence interval: 1,004-4,244) in the 90 days post discharge. Patients with HAI had longer LOS if they were readmitted and were prescribed more antibiotics in the community. The results suggest that HAI did not have an impact on the number of readmissions or repeat surgeries within 90 days of discharge. The majority (95%) of the excess costs was on acute care services after readmission. Bloodstream infection, gastrointestinal infection, and pneumonia had the biggest impact on post-discharge cost. CONCLUSION: HAI increases costs and antibiotic consumption in the post-discharge period. Economic evaluations of IPC studies should incorporate post-discharge costs. These findings can be used nationally and internationally to support decision-making on the impact of IPC interventions.