Background

Evidence-based priority setting is increasingly important for rationally distributing scarce health resources and for guiding future health research. We sought to quantify the contribution of a wide range of infectious diseases to the overall infectious disease burden in a high-income setting.

Methodology/Principal Findings

We used health-adjusted life years (HALYs), a composite measure comprising premature mortality and reduced functioning due to disease, to estimate the burden of 51 infectious diseases and associated syndromes in Ontario using 2005–2007 data. Deaths were estimated from vital statistics data and disease incidence was estimated from reportable disease, healthcare utilization, and cancer registry data, supplemented by local modeling studies and national and international epidemiologic studies. The 51 infectious agents and associated syndromes accounted for 729 lost HALYs, 44.2 deaths, and 58,987 incident cases per 100,000 population annually. The most burdensome infectious agents were: hepatitis C virus, Streptococcus pneumoniae, Escherichia coli, human papillomavirus, hepatitis B virus, human immunodeficiency virus, Staphylococcus aureus, influenza virus, Clostridium difficile, and rhinovirus. The top five, ten, and 20 pathogens accounted for 46%, 67%, and 75% of the total infectious disease burden, respectively. Marked sex-specific differences in disease burden were observed for some pathogens. The main limitations of this study were the exclusion of certain infectious diseases due to data availability issues, not considering the impact of co-infections and co-morbidity, and the inability to assess the burden of milder infections that do not result in healthcare utilization.

Conclusions/Significance

Infectious diseases continue to cause a substantial health burden in high-income settings such as Ontario. Most of this burden is attributable to a relatively small number of infectious agents, for which many effective interventions have been previously identified. Therefore, these findings should be used to guide public health policy, planning, and research.

Background

Acquired Brain Injury (ABI) from traumatic and non traumatic causes is a leading cause of disability worldwide yet there is limited research summarizing the health system economic burden associated with ABI. The objective of this study was to determine the direct cost of publicly funded health care services from the initial hospitalization to three years post-injury for individuals with traumatic (TBI) and non-traumatic brain injury (nTBI) in Ontario Canada.

Methods

A population-based cohort of patients discharged from acute hospital with an ABI code in any diagnosis position in 2004 through 2007 in Ontario was identified from administrative data. Publicly funded health care utilization was obtained from several Ontario administrative healthcare databases. Patients were stratified according to traumatic and non-traumatic causes of brain injury and whether or not they were discharged to an inpatient rehabilitation center. Health system costs were calculated across a continuum of institutional and community settings for up to three years after initial discharge. The continuum of settings included acute care emergency departments inpatient rehabilitation (IR) complex continuing care home care services and physician visits. All costs were calculated retrospectively assuming the government payer’s perspective.

Results

Direct medical costs in an ABI population are substantial with mean cost in the first year post-injury per TBI and nTBI patient being $32132 and $38018 respectively. Among both TBI and nTBI patients those discharged to IR had significantly higher treatment costs than those not discharged to IR across all institutional and community settings. This tendency remained during the entire three-year follow-up period. Annual medical costs of patients hospitalized with a brain injury in Ontario in the first follow-up year were approximately $120.7 million for TBI and $368.7 million for nTBI. Acute care cost accounted for 46-65% of the total treatment cost in the first year overwhelming all other cost components.

Conclusions

The main finding of this study is that direct medical costs in ABI population are substantial and vary considerably by the injury cause. Although most expenses occur in the first follow-up year ABI patients continue to use variety of medical services in the second and third year with emphasis shifting over time from acute care and inpatient rehabilitation towards homecare physician services and long-term institutional care. More research is needed to capture economic costs for ABI patients not admitted to acute care.

Background

The aim of this paper is to examine factors associated with discharge destination after acquired brain injury in a publicly insured population using the Anderson Behavioral Model as a framework.

Methods

We utilized a retrospective cohort design. Inpatient data from provincial acute care records from fiscal years 2003/4 to 2006/7 with a diagnostic code of traumatic brain injury (TBI) and non-traumatic brain injury (nTBI) in Ontario, Canada were obtained for the study. Using multinomial logistic regression models, we examined predisposing, need and enabling factors from inpatient records in relation to major discharge outcomes such as discharge to home, inpatient rehabilitation and other institutionalized care.

Results

Multinomial logistic regression revealed that need factors were strongly correlated with discharge destinations overall. Higher scores on the Charlson Comorbidity Index were associated with discharge to other institutionalized care in the nTBI population. Length of stay and special care days were identified as markers for severity and were both strongly positively correlated with discharge to other institutionalized care and inpatient rehabilitation, compared to discharge home, in both nTBI and TBI populations. Injury by motor vehicle collisions was found to be positively correlated with discharge to inpatient rehabilitation and other institutionalized care for patients with TBI. Controlling for need factors, rural location was associated with discharge to home versus inpatient rehabilitation.

Conclusions

These findings show that need factors (Charlson Comorbidity Index, length of stay, and number of special care days) are most significant in terms of discharge destination. However, there is evidence that other factors such as rural location and access to supplemental insurance (e.g., through motor vehicle insurance) may influence discharge destination outcomes as well. These findings should be considered in creating more equitable access to healthcare services across the continuum of care.

Helicobacter pylori (H. pylori) is a bacterial pathogen that resides at the gastric mucosa and has a world-wide prevalence of over 50%. Infection usually lasts for the life of the host, and although all infected individuals will develop histologic gastritis only a subset will develop symptomatic gastritis, peptic ulcer disease, gastric MALT lymphoma, or gastric adenocarcinoma. The bacterial and host factors that determine clinical outcome and influence the development of widely varying diseases have not been elucidated. We compared disease in Helicobacter-infected severe combined immunodeficient (SCID) mice on different genetic backgrounds with their corresponding immunocompetent partners to determine if the genetics of the host significantly impacts the innate inflammatory outcome, independent of variations in bacterial virulence factors. BALB/c SCID and C57BL/6 SCID mice developed equivalent histologic gastritis by 8 weeks of infection. Immunocompetent BALB/c mice and C57BL/6 mice developed significantly lower or higher degrees of inflammation respectively. Innate inflammation in immunodeficient mice on the C57BL/6 background remained low even in the absence of the regulatory cytokine IL-10. These results demonstrate that adaptive immunity is not required for the generation of low level inflammation in response to Helicobacter infection and that the degree of inflammation is consistent among different genetic backgrounds. Additionally, this inflammation is limited even in the absence of regulatory T cells.

BACKGROUND

Disease-specific estimates of medical costs are important for health policy decision making.

OBJECTIVE

To identify predictors of health care costs associated with hepatitis C virus (HCV) seropositivity across disease phases.

METHODS

HCV laboratory tests from the BC Centre for Disease Control were linked to administrative data pertaining to health services and drugs dispensed to estimate costs among case subjects and controls. The case group comprised HCV seropositive individuals (n=20,001), and the control group comprised single-tested, HCV seronegative persons (n=70,752) identified between January 1997 and December 2004. Subject observation time was assigned to the three following disease phases: initial phase (after diagnosis), late phase (late-stage liver disease) and predeath phase (12 months before death). Case subjects and controls were matched for age, sex and a propensity score within each phase to determine the net cost attributable to HCV seropositivity, and were adjusted for demographic and clinical factors.

RESULTS

Costs increased with disease progression, with hospitalization being the highest cost component in all phases. Initial and late phase net costs (2005 Canadian dollars) were $1,850 and $6,000 per patient per year, respectively. Costs among case subjects were driven by age, comorbidities, mental illness, illicit drug use and HIV coinfection. While predeath case subject and control costs were virtually the same, costs were high and case subjects died at a younger age.

CONCLUSION

HCV seropositivity is associated with increased medical costs driven by viral sequelae and medicosocial vulnerabilities (ie, mental illness, illicit drug use and HIV coinfection). Cost mitigation and health outcome improvements will require broad-based prevention programming to reduce vulnerabilities and HCV treatment to prevent disease progression, respectively.

Background

Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research.

Methods

Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic.

Results

The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases.

Conclusion

Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.

Objective

We sought to validate a case-finding algorithm for human immunodeficiency virus (HIV) infection using administrative health databases in Ontario, Canada.

Methods

We constructed 48 case-finding algorithms using combinations of physician billing claims, hospital and emergency room separations and prescription drug claims. We determined the test characteristics of each algorithm over various time frames for identifying HIV infection, using data abstracted from the charts of 2,040 randomly selected patients receiving care at two medical practices in Toronto, Ontario as the reference standard.

Results

With the exception of algorithms using only a single physician claim, the specificity of all algorithms exceeded 99%. An algorithm consisting of three physician claims over a three year period had a sensitivity and specificity of 96.2% (95% CI 95.2%–97.9%) and 99.6% (95% CI 99.1%–99.8%), respectively. Application of the algorithm to the province of Ontario identified 12,179 HIV-infected patients in care for the period spanning April 1, 2007 to March 31, 2009.

Conclusions

Case-finding algorithms generated from administrative data can accurately identify adults living with HIV. A relatively simple “3 claims in 3 years” definition can be used for assembling a population-based cohort and facilitating future research examining trends in health service use and outcomes among HIV-infected adults in Ontario.

Objective To evaluate the effectiveness of the community based Cardiovascular Health Awareness Program (CHAP) on morbidity from cardiovascular disease.

Design Community cluster randomised trial.

Setting 39 mid-sized communities in Ontario, Canada, stratified by location and population size.

Participants Community dwelling residents aged 65 years or over, family physicians, pharmacists, volunteers, community nurses, and local lead organisations.

Intervention Communities were randomised to receive CHAP (n=20) or no intervention (n=19). In CHAP communities, residents aged 65 or over were invited to attend volunteer run cardiovascular risk assessment and education sessions held in community based pharmacies over a 10 week period; automated blood pressure readings and self reported risk factor data were collected and shared with participants and their family physicians and pharmacists.

Main outcome measure Composite of hospital admissions for acute myocardial infarction, stroke, and congestive heart failure among all community residents aged 65 and over in the year before compared with the year after implementation of CHAP.

Results All 20 intervention communities successfully implemented CHAP. A total of 1265 three hour long sessions were held in 129/145 (89%) pharmacies during the 10 week programme. 15 889 unique participants had a total of 27 358 cardiovascular assessments with the assistance of 577 peer volunteers. After adjustment for hospital admission rates in the year before the intervention, CHAP was associated with a 9% relative reduction in the composite end point (rate ratio 0.91, 95% confidence interval 0.86 to 0.97; P=0.002) or 3.02 fewer annual hospital admissions for cardiovascular disease per 1000 people aged 65 and over. Statistically significant reductions favouring the intervention communities were seen in hospital admissions for acute myocardial infarction (rate ratio 0.87, 0.79 to 0.97; P=0.008) and congestive heart failure (0.90, 0.81 to 0.99; P=0.029) but not for stroke (0.99, 0.88 to 1.12; P=0.89).

Conclusions A collaborative, multi-pronged, community based health promotion and prevention programme targeted at older adults can reduce cardiovascular morbidity at the population level.

Trial registration Current controlled trials ISRCTN50550004.

Objective

To estimate the rate of new chronic benzodiazepine use after hospitalization in older adults not previously prescribed with benzodiazepines.

Design

Retrospective cohort study using linked, population-based administrative data.

Setting

Ontario, Canada between April 1, 1992 and March 31, 2005.

Participants

Community-dwelling seniors who had not been prescribed benzodiazepine drugs in the year before hospitalization were selected from all 1.4 million Ontario residents aged 66 years and older.

Main Outcome Measures

New chronic benzodiazepine users, defined as initiation of benzodiazepines within 7 days after hospital discharge and an additional claim within 8 days to 6 months. We used multivariate logistic regression to examine for the effect of hospitalization on the primary outcome after adjusting for confounders.

Results

There were 405,128 patient hospitalizations included in the cohort. Benzodiazepines were prescribed to 12,484 (3.1%) patients within 7 days of being discharged from hospital. A total of 6,136 (1.5%) patients were identified as new chronic benzodiazepine users. The rate of new chronic benzodiazepine users decreased over the study period from 1.8% in the first year to 1.2% in the final year (P < .001). Multivariate logistic regression found that women, patients admitted to the intensive care unit or nonsurgical wards, those with longer hospital stays, higher overall comorbidity, a prior diagnosis of alcoholism, and those prescribed more medications had significantly elevated adjusted odds ratios for new chronic benzodiazepine users. Older individuals had a lower risk for the primary outcome.

Conclusion

New benzodiazepine prescription after hospitalization occurs frequently in older adults and may result in chronic use. A systemic effort to address this risky practice should be considered.

Existing data stored in a hospital's transactional servers have enormous potential to improve performance measurement and health care quality. Accessing, organizing, and using these data to support research and quality improvement projects are evolving challenges for hospital systems. The authors report development of a clinical data warehouse that they created by importing data from the information systems of three affiliated public hospitals. They describe their methodology; difficulties encountered; responses from administrators, computer specialists, and clinicians; and the steps taken to capture and store patient-level data. The authors provide examples of their use of the clinical data warehouse to monitor antimicrobial resistance, to measure antimicrobial use, to detect hospital-acquired bloodstream infections, to measure the cost of infections, and to detect antimicrobial prescribing errors. In addition, they estimate the amount of time and money saved and the increased precision achieved through the practical application of the data warehouse.

Automated bloodstream infection surveillance using electronic data is an accurate alternative to surveillance using manually collected data.

We compared manual and computer-assisted bloodstream infection surveillance for adult inpatients at two hospitals. We identified hospital-acquired, primary, central-venous catheter (CVC)-associated bloodstream infections by using five methods: retrospective, manual record review by investigators; prospective, manual review by infection control professionals; positive blood culture plus manual CVC determination; computer algorithms; and computer algorithms and manual CVC determination. We calculated sensitivity, specificity, predictive values, plus the kappa statistic (κ) between investigator review and other methods, and we correlated infection rates for seven units. The κ value was 0.37 for infection control review, 0.48 for positive blood culture plus manual CVC determination, 0.49 for computer algorithm, and 0.73 for computer algorithm plus manual CVC determination. Unit-specific infection rates, per 1,000 patient days, were 1.0–12.5 by investigator review and 1.4–10.2 by computer algorithm (correlation r = 0.91, p = 0.004). Automated bloodstream infection surveillance with electronic data is an accurate alternative to surveillance with manually collected data.