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OBJECTIVE: To analyze primary medication nonadherence across several prescription indications and test the predictors of drug nonadherence in an adult primary care population. DESIGN: Retrospective observational study using primary care provider prescriptions linked to pharmacy-based dispensing data from 2012 to 2014. SETTING: Manitoba. PARTICIPANTS: Patients in the Manitoba Primary Care Research Network. MAIN OUTCOME MEASURES: Prevalence of primary medication nonadherence by drug class. Multivariable logistic regression models were used to test the associations of patient demographic and clinical or provider characteristics with primary medication nonadherence. The C statistic was used to assess the models’ discriminative performance. RESULTS: A total of 91,660 unique prescriptions were assessed from a cohort of more than 200,000 patients. Primary medication nonadherence ranged from 13.7% (antidepressants) to 30.3% (antihypertensives). In conditions that typically present symptomatically (eg, infections, anxiety) nonadherence ranged from 13.7% to 17.5%. The range was 21.2% to 30.0% for medications related to asymptomatic conditions or those typically detected by screening. The discriminative performance of the models based on patient demographic, clinical, or provider characteristics was weak. CONCLUSION: Primary medication nonadherence is common, occurring more often in asymptomatic conditions. The poor predictability of the models suggests that caution is required when considering characteristic-based interventions or prediction tools to improve primary medication nonadherence.

BackgroundPrediction of future critical illness could render it practical to test interventions seeking to avoid or delay the coming event.ObjectiveIdentify adults having >33% probability of near-future critical illness.Research DesignRetrospective cohort study, 2013–2015.SubjectsCommunity-dwelling residents of Manitoba, Canada, aged 40–89 years.MeasuresThe outcome was a near-future critical illness, defined as intensive care unit admission with invasive mechanical ventilation, or non-palliative death occurring 30–180 days after 1 April each year. By dividing the data into training and test cohorts, a Classification and Regression Tree analysis was used to identify subgroups with ≥33% probability of the outcome. We considered 72 predictors including sociodemographics, chronic conditions, frailty, and health care utilization. Sensitivity analysis used logistic regression methods.ResultsApproximately 0.38% of each yearly cohort experienced near-future critical illness. The optimal Tree identified 2,644 mutually exclusive subgroups. Socioeconomic status was the most influential variable, followed by nursing home residency and frailty; age was sixth. In the training data, the model performed well; 41 subgroups containing 493 subjects had ≥33% members who developed the outcome. However, in the test data, those subgroups contained 429 individuals, with 20 (4.7%) experiencing the outcome, which comprised 0.98% of all subjects with the outcome. While logistic regression showed less model overfitting, it likewise failed to achieve the stated objective.ConclusionsHigh-fidelity prediction of near-future critical illness among community-dwelling adults was not successful using population-based administrative data. Additional research is needed to ascertain whether the inclusion of additional types of data can achieve this goal.

Rationale: Accurately identifying use of life support in hospital administrative data enhances the data’s value for quality improvement and research in critical illness.Objectives: To assess the ac...

Background: Although multiple sclerosis (MS) confers an elevated risk of acute myocardial infarction (AMI), little is known about how it influences management of AMI. Methods: Using population-based administrative (health) data from two Canadian provinces, we conducted a retrospective matched cohort study. We identified people with MS who had an incident AMI, and up to five AMI controls without MS matched on age, sex, and region. We compared the likelihood of undergoing cardiac catheterization within 30 days of AMI, time to revascularization, use of recommended pharmacotherapy post-AMI, and mortality at 30 and 365 days post-AMI using multivariable regression models adjusting for potential confounders. We pooled findings across provinces using meta-analysis. Results: We identified 559 MS cases and 2523 matched controls. In the matched cohort, the MS cohort was less likely to undergo cardiac catheterization within 30 days of admission (odds ratio (OR) = 0.61; 95% confidence interval (CI) = 0.49–0.77), revascularization (hazard ratio (HR) = 0.78; 95% CI = 0.69–0.88), or to fill a prescription for recommended therapy. Mortality risk was higher in the MS cohort than in the matched cohort at 30 and 365 days post-AMI. Conclusion: Rates of diagnostic and therapeutic care, and survival after AMI were lower in the MS population than in a matched population.

Background The objective of this study was to determine primary prescription adherence for obstructive lung diseases (e.g., asthma, COPD) in an adult primary care patient population over a 3-year period. Methods A retrospective analysis of electronic medical record and administrative data was performed to determine primary adherence, defined as dispensation of a new prescription within 90 days of the date the prescription was written. Multivariable logistic regression models were used to test predictors of prescription primary adherence. Results Of 13,220 prescriptions for obstructive airway disease, 75.9% (N = 10,038) were filled. In multivariate analysis, depression, certain age groups (18–44 years), higher income quartile were associated with reduced prescription adherence. However, 1–2 ER visits in the previous year (compared to no ER visits), number of ambulatory visits in the previous year, and number of hospitalizations in the previous year, did not increase the likelihood of prescription adherence. Interpretation This study provides important insights about factors associated with prescription nonadherence and is the first study examining primary medication adherence with medications for obstructive lung disease in adults, providing indications of prescription nonadherence patterns among a broad population.

To examine the trends in antiepileptic drug (AED) use among individuals living in Manitoba with and without a history of epilepsy.Using data obtained from administrative health databases in Manitoba, we assessed the quarterly prevalence of AED use between 1998 and 2013 among individuals with and without a history of epilepsy using cross-sectional time series analysis.Over the study period, the number of individuals prescribed AEDs increased more than 3-fold, from 8,883 to 27,246. The prevalence of AED use among patients with epilepsy increased by 3%, from 789.6 per 1,000 in 1998/1999 to 813.9 per 1,000 in 2012/2013 (p0.001 after 2006). In contrast, we observed a 210% increase in AED use among patients without epilepsy from 6.8 to 21.1 per 1,000 over the same period (p0.001). We observed a 55-fold rise in gabapentin use among patients without a seizure disorder (from 0.2 to 11.1 per 1,000; p0.001), while gabapentin use among those with epilepsy increased only 2-fold, from 21.6 to 41.3 per 1,000 (p0.001).There has been a marked increase in the prevalence of AED users over the last 15 years, with a large shift towards the use of newer antiepileptic agents (primarily gabapentin) among those without epilepsy. Further research on the effect of these trends on health and economic outcomes will be of interest for clinicians and policymakers.

IntroductionMechanical ventilation (MV) is an important intervention used in critically ill patients. Accurately identifying MV use in Hospital Discharge Abstracts will be extremely useful in population-based research. Although Canadian Institute for Health Information collects information on MV for all hospitalization, its validity in intensive care unit (ICU) patients is unknown. Objectives and ApproachWe validated MV use within ICU patients in Hospital Discharge Abstracts. Winnipeg Regional Health Authority (WRHA) ICU database prospectively collects use of MV by trained nurses. All patients admitted to a WRHA ICU (82 beds) between April 1, 2000 and March 31, 2012 were identified in Hospital Discharge Abstracts. MV was identified in Hospital Discharge Abstracts through International Classification of Diseases (ICD-9-CM), prior to 2004, while Canadian Classification of Health Interventions (CCI) were used 2004 onwards. Agreement between the WRHA database (gold standard) and Hospital Discharge Abstracts for invasive ventilation, non-invasive ventilation or neither was calculated at ICU encounter level. ResultsThere were 54,680 WRHA ICU admission during the study period. The linking of these two sources was highly successful with accurate identification exceeding 99%. There were 26,083 mechanical ventilations (25,387 invasive; 696 non-invasive) from the Hospital Discharge Abstracts and 30,455 (28,315 invasive; 4,554 non-invasive) from the CIC data. Hospital Discharge Abstracts had a sensitivity of 82.8%, specificity of 96.4%, Positive Predictive Value (PPV) of 96.7%, and Negative Predictive Value (NPV) of 81.7% for identifying mechanical ventilation. For invasive ventilation, Sensitivity was 85.5%, Specificity was 95.6%, PPV was 95.4% and NPV was 86.0%. Validation of non-invasive ventilation was poor in sensitivity (9.38%) and PPV (61.35%): with specificity 99.5% and NPV 92.36%. Conclusion/ImplicationsHospital Abstracts data are a good source to identity mechanically ventilated patients for ICU containing hospital stays especially invasive mechanical ventilations. Future research needs to explore the poor agreement with non-invasive mechanical ventilation.

ObjectiveTo compare the risk of incident acute myocardial infarction (AMI) in the multiple sclerosis (MS) population and a matched population without MS, controlling for traditional vascular risk factors.MethodsWe conducted a retrospective matched cohort study using population-based administrative (health claims) data in 2 Canadian provinces, British Columbia and Manitoba. We identified incident MS cases using a validated case definition. For each case, we identified up to 5 controls without MS matched on age, sex, and region. We compared the incidence of AMI between cohorts using incidence rate ratios (IRR). We used Cox proportional hazards regression to compare the hazard of AMI between cohorts adjusting for sociodemographic factors, diabetes, hypertension, and hyperlipidemia. We pooled the provincial findings using meta-analysis.ResultsWe identified 14,565 persons with MS and 72,825 matched controls. The crude incidence of AMI per 100,000 population was 146.2 (95% confidence interval [CI] 129.0–163.5) in the MS population and 128.8 (95% CI 121.8–135.8) in the matched population. After age standardization, the incidence of AMI was higher in the MS population than in the matched population (IRR 1.18; 95% CI 1.03–1.36). After adjustment, the hazard of AMI was 60% higher in the MS population than in the matched population (hazard ratio 1.63; 95% CI 1.43–1.87).ConclusionThe risk of AMI is elevated in MS, and this risk may not be accounted for by traditional vascular risk factors.

Many studies of critical illness outcomes have been restricted to short-term outcomes, selected diagnoses, and patients in one or a few intensive care units (ICUs).Evaluate a range of relevant outcomes in a population-based cohort of patients admitted to ICUs.Among all adult residents of the Canadian province of Manitoba admitted to ICUs over a 9-year period, we assessed ICU, hospital, 30-day, and 180-day mortality rates; ICU and hospital lengths-of-stay; Post-hospital use of hospital care, ICU care, outpatient physician care, medications, and home care; and Post-hospital residence location. We explored data stratified by age, sex, and separate categories of geocoded income for urban and rural residents. For Post-hospital use variables we compared ICU patients with those admitted to hospitals without the need for ICU care.After ICU admission there was a high initial death rate, which declined between 30 and 180 days and thereafter remained at the lower value. Hospital mortality was 19.0%, with 21.7% dying within 6 months of ICU admission. Women had higher hospital mortality than men (20.8 vs. 17.8%; P = 0.0008). Among urban residents there was a steady gradient of declining hospital mortality with rising income (P 0.0001). Mean ICU length of stay was 3.96 days, increasing 0.11 d/yr over the study period (P = 0.001); median ICU length of stay was 2.33 days and did not change over time. In the year after ICU care, 41% were rehospitalized, 10% were readmitted to an ICU, 98% had outpatient physician visits, 96% used prescription medications, and 27% used home care services. Although most of these parameters were statistically higher than for hospitalizations not requiring ICU care, differences were generally small. Among hospital survivors, 2.7% were discharged to chronic care facilities, with 2.5% living in such facilities 3 months later.Post-hospital medical resource use among ICU survivors is substantial, although similar to that after non-ICU hospitalization. Although the fraction of survivors unable to live independently was small, a larger fraction required home care services. Identifying Post-hospital supports needed by ICU survivors can be useful for policy makers and others responsible for healthcare planning.

Background The aim of this study was to estimate primary adherence for epinephrine autoinjector (EA) prescriptions in primary care practices in Manitoba, Canada. Methods A retrospective analysis of electronic medical record and administrative data was performed to determine primary adherence, defined as dispensation of a new EA prescription within 90 days of the date the prescription was written. Multivariable logistic regression models were used to test predictors of filling an EA prescription. Results Of 1212 EA prescriptions written between 2012 and 2014, only 69.9% (N = 847) were filled. An increased number of prescriptions for non-EA mediations was associated with an increased odds ratio of not filling an EA prescription. Interpretation This is the first study in Canada to examine adherence for EA prescriptions. The non-adherence rate identified is higher than rates previously reported in the literature, and indicates that many EA prescriptions for adults seen in primary care may never be filled. It also suggests that prescriptions of EAs for all patients at risk of anaphylaxis in community settings should consistently be accompanied by concise information about the importance of having the EA prescription filled and having the EA readily available.

ObjectivesCanadians are investing heavily in electronic medical records (EMRs) to inform primary care practice improvements. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is a national practice-based network that has enrolled more than one million patients to date. Accurate CPCSSN EMR data are essential for unbiased research about chronic disease prevention and management. The study purpose was to test the accuracy of chronic disease case definitions in EMR data from one CPCSSN site. ApproachThis study linked CPCSSN EMR data, hospital records, physician billing claims, prescription drug records, and population registration files for the province of Manitoba. Individuals who had at least one encounter with a CPCSSN practice between 1998 and 2012, were at least 18 years of age, and had a minimum of two years of healthcare coverage before and after the study index date were included. Separate cohorts were defined for the following chronic diseases: chronic obstructive pulmonary disease (COPD), depression, diabetes, hypertension, and osteoarthritis. Validated case definitions based on diagnoses in physician and hospital records and prescription drug data were used estimate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa of each EMR chronic disease case definition. ResultsMore than 74,000 individuals were included in each cohort, except for COPD which had 51,000. Approximately half of each cohort was comprised of urban residents. The average age ranged from 45.9 years for individuals with depression to 65.3 years for individuals with COPD. Hypertension had the highest prevalence (22.0%) in EMR data followed by depression (14.6%). Estimates of agreement (i.e., kappa) for EMR and administrative data ranged from 0.47 for COPD to 0.58 for diabetes. Sensitivity of the EMR data was lowest for COPD (37.4%; 95% CI 36.0-38.8) and highest for diabetes (57.6%; 95% confidence interval [CI] 56.6-58.6). PPV estimates were lowest for osteoarthritis (66.9%; 95% CI 66.0-67.8) and highest for hypertension (78.3%; 95% CI 77.7-78.9). Specificity estimates were consistently above 90% and NPV estimates were always greater than 80%. Validity estimates for the EMR case definitions were associated with demographic and comorbidity characteristics of the study cohorts. ConclusionsValidity of EMR data, when compared to administrative health data, for ascertaining five different chronic diseases was fair to good; it varied with the disease under investigation. Further research is needed to identify methods for improving the accuracy of chronic disease case definitions in EMR data.

Fracture Risk Assessment (FRAX) tools are calibrated from country-specific fracture epidemiology. Although hip fracture data are usually available, data on non-hip fractures for most countries are often lacking. In such cases, rates are often estimated by assuming similar non-hip to hip fracture ratios from historical (1987 to 1996) Swedish data. Evidence that countries share similar fracture ratios is limited. Using data from Manitoba, Canada (2000 to 2007, population 1.2 million), we identified 21,850 incident major osteoporotic fractures (MOF) in men and women aged >50 years. Population-based age- and sex-specific ratios of clinical vertebral, forearm, and humerus fractures to hip fractures were calculated, along with odds ratios (ORs) and 95% confidence intervals (CIs). All ratios showed decreasing trends with increasing age for both men and women. Men and women showed similar vertebral/hip fracture ratios (all p > 0.1, with ORs 0.86 to 1.25). Forearm/hip and humerus/hip fracture ratios were significantly lower among men than women (forearm/hip ratio: p

Diverging international trends in fracture rates have been observed, with most reports showing that fracture rates have stabilized or decreased in North American and many European populations. We studied two complementary population-based historical cohorts from the Province of Manitoba, Canada (1996-2006) to determine whether declining osteoporotic fracture rates in Canada are attributable to trends in obesity, osteoporosis treatment, or bone mineral density (BMD). The Population Fracture Registry included women aged 50 years and older with major osteoporotic fractures, and was used to assess impact of changes in osteoporosis treatment. The BMD Registry included all women aged 50 years and older undergoing BMD tests, and was used to assess impact of changes in obesity and BMD. Model-based estimates of temporal changes in fracture rates (Fracture Registry) were calculated. Temporal changes in obesity and BMD and their association with fracture rates (BMD Registry) were estimated. In the Fracture Registry (n=27,341), fracture rates declined 1.6% per year (95% confidence interval [CI], 1.3% to 2.0%). Although osteoporosis treatment increased from 5.6% to 17.4%, the decline in fractures was independent of osteoporosis treatment. In the BMD Registry (n=36,587), obesity increased from 12.7% to 27.4%. Femoral neck BMD increased 0.52% per year and lumbar spine BMD increased 0.32% per year after covariate adjustment (p

Our objective was to describe changes in glucocorticoid-induced osteoporosis (GIOP) preventive care from 1998-2008 including rates and correlates of bone mineral density (BMD) testing and osteoporosis treatment in new long-term glucocorticoid initiations.A population-based study of adults aged 20 yr or older in Manitoba, Canada, was conducted using linked healthcare databases. Subjects with new long-term (≥90 d) systemic glucocorticoid initiations were identified within each fiscal year. High-quality GIOP preventive care was defined by the composite of BMD testing or osteoporosis treatment within 6 months of starting glucocorticoids. For each initiation, we identified sociodemographic and clinical characteristics, prednisone dose equivalents, and prescriber specialty. Multivariable Poisson regression models were used to calculate adjusted incidence rate ratios (aIRR).We studied 17,736 new long-term glucocorticoid initiations; one third were at least 10 mg prednisone daily, and most (64%) were prescribed by general practitioners. Overall, 6-month rates of BMD testing were 6%, osteoporosis treatment 22%, and the composite of testing or treatment 25%. From 1998-2008, there were modest increases in BMD testing (from 4 to 6%), osteoporosis treatment (from 15 to 24%), and testing or treatment [from 17 to 27%; aIRR = 1.51; 95% confidence interval (CI) = 1.40-1.63]. High-quality GIOP preventive care varied significantly by age (16% for those50 yr vs. 27% for those ≥70 yr; aIRR = 0.57; 95% CI = 0.52-0.63), sex (13% for men vs. 34% for women; aIRR = 0.40; 95% CI = 0.37-0.43), and prescriber (23% general practice vs. 44% rheumatology; aIRR = 0.56; 95% CI = 0.52-0.60).Quality of GIOP preventive care has improved but remains suboptimal with only one quarter of those starting long-term glucocorticoids receiving BMD testing or osteoporosis treatment. Interventions to improve GIOP prevention, especially targeting younger patients, men, and nonspecialists, are needed.

Objectives The aim was to construct and validate algorithms for osteoporosis case ascertainment from administrative databases and to estimate the population prevalence of osteoporosis for these algorithms. Study Design and Setting Artificial neural networks, classification trees, and logistic regression were applied to hospital, physician, and pharmacy data from Manitoba, Canada. Discriminative performance and calibration (i.e., error) were compared for algorithms defined from different sets of diagnosis, prescription drug, comorbidity, and demographic variables. Algorithms were validated against a regional bone mineral density testing program. Results Discriminative performance and calibration were poorer and sensitivity was generally lower for algorithms based on diagnosis codes alone than for algorithms based on an expanded set of data features that included osteoporosis prescriptions and age. Validation measures were similar for neural networks and classification trees, but prevalence estimates were lower for the former model. Conclusion Multiple features of administrative data generally resulted in improved sensitivity of osteoporosis case-detection algorithm without loss of specificity. However, prevalence estimates using an expanded set of features were still slightly lower than estimates from a population-based study with primary data collection. The classification methods developed in this study can be extended to other chronic diseases for which there may be multiple markers in administrative data.

Dans cette étude, on a estimé la concordance entre les données des populations administratives et les données des populations d'enquête lorsqu'il s'agit de déterminer les cas d'arthrite, d'asthme, de diabète, de cardiopathie, d'hypertension et d'accident vasculaire cérébral. Des définitions de cas de maladies chroniques, qui variaient de par la source des données, le nombre d'années de données et les codes de diagnostic et de médicaments prescrits employés, ont été élaborées à partir des données administratives du Manitoba. Un recoupement a ensuite été fait entre ces données et celles tirées de l'Enquête sur la santé dans les collectivités canadiennes. La concordance entre ces deux sources de données, estimée par le coefficient κ, a été calculée pour chaque définition de cas, et les différences ont été testées. Les variables socio-démographiques et les variables liées à la comorbidité en lien avec la concordance ont été testées au moyen d'une régression logistique pondérée. C'est pour le diabète et l'hypertension que l'on a observé la concordance la plus élevée, et pour l'arthrite que l'on a observé la concordance la plus faible. Les éléments de la définition de cas qui contribuaient à la concordance la plus élevée entre les deux sources de données des populations variaient selon les maladies chroniques. Il est probable que les données administratives et les données d'enquête concordent peu dans le cas des affections qui sont difficiles à diagnostiquer, mais cette concordance est aussi influencée par les caractéristiques socio-démographiques et l'état de santé des individus. Toute définition de cas de maladie chronique fondée sur des données administratives devrait être accompagnée d'une justification du choix de chacun de ses éléments.

This study estimated agreement between population-based administrative and survey data for ascertaining cases of arthritis, asthma, diabetes, heart disease, hypertension and stroke. Chronic disease case definitions that varied by data source, number of years and number of diagnosis or prescription drug codes were constructed from Manitoba's administrative data. These data were linked to the Canadian Community Health Survey. Agreement between the two data sources, estimated by the κ coefficient, was calculated for each case definition, and differences were tested. Socio-demographic and comorbidity variables associated with agreement were tested using weighted logistic regression. Agreement was strongest for diabetes and hypertension and lowest for arthritis. The case definition elements that contributed to the highest agreement between the two population-based data sources varied across the chronic diseases. Low agreement between administrative and survey data is likely to occur for conditions that are difficult to diagnose, but will be mediated by individual socio-demographic and health status characteristics. Construction of a chronic disease case definition from administrative data should be accompanied by a justification for the choice of each of its elements.

This study investigated the use of population-based administrative databases for stroke surveillance. First, a meta-analysis was conducted of four studies, identified via a PubMed search, which estimated the sensitivity and specificity of hospital data for ascertaining cases of stroke when clinical registries or medical charts were the gold standard. Subsequently, case-ascertainment algorithms based on hospital, physician and prescription drug records were developed and applied to Manitoba's administrative data, and prevalence estimates were obtained for fiscal years 1995/96 to 2003/04 by age group, sex, region of residence and income quintile. The meta-analysis results revealed some over-ascertainment of stroke cases from hospital data when the algorithm was based on diagnosis codes for any type of cerebrovascular disease (Mantel-Haenszel Odds-Ratio [OR] – 1.70 [95% confidence interval (CI): 1.53 – 1.88]). Analyses of Manitoba administrative data revealed that while the total number of stroke cases varied substantially across the algorithms, the trend in prevalence was stable regardless of the algorithm adopted.

Dans la présente étude, nous nous sommes penchés sur l'utilisation des bases de données administratives en matière de population dans la surveillance des accidents vasculaires cérébraux. Nous avons tout d'abord effectué une méta-analyse de quatre études, relevées au moyen d'une recherche dans PubMed, qui visaient à évaluer la sensibilité et la spécifi cité des données des hôpitaux dans la détermination des cas d'accident vasculaire cérébral lorsque les registres cliniques ou les dossiers médicaux étaient la méthode de référence. Nous avons ensuite mis au point des algorithmes de détermination des cas fondés sur les données des hôpitaux ainsi que les données relatives aux médecins et aux médicaments de prescription. Enfin, nous avons appliqué ces algorithmes aux données administratives du Manitoba, ce qui a permis d'obtenir des estimations de la prévalence pour les années fi nancières 1995-1996 à 2003-2004, par groupe d'âge, sexe, région de résidence et quintile de revenu. Les résultats de la méta-analyse ont fait ressortir une certaine surdétermination des cas d'accident vasculaire cérébral à partir des données des hôpitaux, lorsque l'algorithme était fondé sur les codes de diagnostic applicables à n'importe quel type de maladie vasculaire cérébrale (rapport de cotes de Mantel-Haenszel [RC] = 1,70 [intervalle de confiance (IC) à 95 % : 1,53-1,88]). Les analyses des données administratives du Manitoba ont révélé que même si le nombre total de cas d'accident vasculaire cérébral variait considérable ment selon l'algorithme, la tendance de la prévalence était stable indépendamment de l'algorithme utilisé.

ObjectivesWe sought to determine whether lung uptake of technetium-99m (99mTc)-based myocardial perfusion tracers predicts cardiac events.BackgroundIncreased lung uptake of thallium-201 during myocardial perfusion scintigraphy can predict important clinical outcomes. It is unclear whether lung uptake of 99mTc-based myocardial perfusion tracers can be used in a similar way.MethodsStress lung-to-heart ratio (sLHR) was determined in 718 patients undergoing 99mTc-sestamibi single-photon emission computed tomographic stress imaging. The primary outcome was acute myocardial infarction or death.ResultsDuring a mean follow-up of 5.6 years, a primary end point occurred in 114 patients (16%). The sLHR was significantly greater in those with an adverse outcome (p < 0.00001). The likelihood of an adverse outcome increased by a factor of 1.5 (95% confidence interval 1.2 to 1.7) for each standard deviation increase in sLHR after adjustment for all other variables. The sLHR provided a small but significant improvement in risk stratification when added to clinical, stress test, perfusion, and left ventricular volume information (global chi-square 168.6 vs. 150.7, p < 0.00001).ConclusionsStress LHR is an adjunctive prognostic measure in patients with known or suspected coronary artery disease.

Because the rate of fracture among patients with inflammatory bowel disease (IBD) is only slightly higher than that in the general population, it is important to define high-risk groups worthy of diagnostic evaluation or prophylactic interventions. Corticosteroid use has been considered in other diseases to be a risk for fracture, although not all studies in IBD are concordant on this point. We aimed to determine whether patients with IBD drawn from a population-based database who sustain fractures are more likely to have been using corticosteroids than a matched group of IBD patients who did not fracture.We extracted from our population-based University of Manitoba Inflammatory Bowel Disease Epidemiology Database the number of patients with a new diagnosis of fracture between the years 1997-2000. From within our Inflammatory Bowel Disease Epidemiology Database, we extracted a control group of IBD patients who did not develop fractures matched to the case group who did by age, gender, diagnosis, year of diagnosis, and geographic area of residence. We linked our cohorts with Manitoba Health's Drug Program Information Network to study corticosteroid use within 2 yr before fracture diagnosis. The Drug Program Information Network is a population-based database, established in 1995, which records all prescription drugs.Fractures were identified in 13 patients with Crohn's disease and in 28 patients with ulcerative colitis. The control group included 103 Crohn's disease and 173 ulcerative colitis patients who did not fracture. In Crohn's disease, for the group who fractured compared with the controls who did not fracture, corticosteroid use before fracture was evident in seven (54%) compared with 21 (22%) who did not fracture (chi(2) = 4.45, df = 1, p = 0.035). In ulcerative colitis, for the group who fractured compared with the controls who did not fracture, corticosteroid use before fracture was evident in five (18%) compared with 37 (21%) who did not fracture (chi(2) = 0.031, df = 1, p = 0.861). Fracture cases were more likely to be exposed to oral corticosteroids (OR = 1.75; 95% CI = 0.82-3.75), but this result is not significant. Regarding corticosteroid dosing among the 12 patients with IBD who fractured and used corticosteroids, the mean total days supply was 314 days +/- 236 days compared with 258 days +/- 278 days in those who did not fracture (p = 0.16). The prescribed daily dose among corticosteroid users was comparable for those who fractured versus those who did not fracture (18 mg/day vs 21 mg/day, p = 0.90).Patients who require corticosteroids in Crohn's disease should be considered at risk for fracture. Further research is required to delineate after how much corticosteroid use are subjects at risk and/or after what duration of active disease.

Rationale: Many studies of critical illness outcomes have been restricted to short-term outcomes, selected diagnoses, and patients in one or a few Intensive Care Units (ICUs). Objective: Evaluate a range of relevant outcomes in a population-based cohort of patients admitted to ICUs. Methods: Among all adult residents of the Canadian province of Manitoba admitted to ICUs over a nine year period we assessed ICU, hospital, 30 day and 180 day mortality rates; ICU and hospital lengths-of-stay; post-hospital utilization of hospital care, ICU care, outpatient physician care, medications, and home care; and post-hospital residence location. We explored data stratified by age, sex, and separate categories of geocoded income for urban and rural residents. For post-hospital utilization variables we compared ICU patients with those admitted to hospitals without the need for ICU care. Measurements and Main Results: After ICU admission there was a high initial death rate, which declined between 30 and 180 days and ther...

Objective To compare methods of characterizing intensive care unit (ICU) bed use and estimate the number of beds needed. Study Setting Three geographic regions in the Canadian province of Manitoba. Study Design Retrospective analysis of population-based data from April 1, 2000, to March 31, 2007. Methods We compared three methods to estimate ICU bed requirements. Method 1 analyzed yearly patient-days. Methods 2 and 3 analyzed day-to-day fluctuations in patient census; these differed by whether each hospital needed to independently fulfill its own demand or this resource was shared across hospitals. Principal Findings Three main findings were as follows: (1) estimates based on yearly average usage generally underestimated the number of beds needed compared to analysis of fluctuations in census, especially in the smaller regions where underestimation ranged 25–58 percent; (2) 4–29 percent fewer beds were needed if it was acceptable for demand to exceed supply 18 days/year, versus 4 days/year; and (3) 13–36 percent fewer beds were needed if hospitals within a region could effectively share ICU beds. Conclusions Compared to using yearly averages, analyzing day-to-day fluctuations in patient census gives a more accurate picture of ICU bed use. Failing to provide adequate “surge capacity” can lead to demand that frequently and severely exceeds supply.

To identify the determinants of short-term and long-term survival in adult patients admitted to intensive care units (ICUs). This population-based, observational cohort study included all eleven adult ICUs in the Winnipeg Health Region of Manitoba, Canada, analyzing initial ICU admissions during the period 1999–2010 of all Manitobans ≥17 years old. Analysis included Kaplan–Meier survival curves and multivariable regression models of 30-day mortality and post-90-day survival among those who survived to day 90. We used likelihood ratios to compare the predictive power of clusters of variables in these models. After 33,324 initial ICU admissions, mortality rates within 30 and 90 days were 15.9 and 19.5 %, respectively. The survival curve demonstrated an early phase with a high rate of death, followed by a markedly lower death rate that was only clearly established after several months. 30-day mortality was predominantly determined by characteristics of the acute illness; with its relative contribution set at 1.00, the next largest contributors were age (0.19) and comorbidity (0.16). In contrast, post-90-day mortality was mainly determined by age (relative contribution 1.00) and comorbidity (0.95); the next largest contributor was characteristics of acute illness (0.28). We observed two phases of survival related to critical illness. Short-term mortality was mainly determined by the acute illness, but its effect decayed relatively rapidly. Mortality beyond 3 months, among those who survived to that point, was mainly determined by age and comorbidity. Recognition of these findings is relevant to discussions with patients and surrogates about achievable goals of care.

Background Prior studies of patients leaving hospital against medical advice (AMA) have been limited by not being population-based or assessing only one type of patient. Methods We used administrative data at the Manitoba Centre for Health Policy to evaluate all adult residents of Manitoba, Canada discharged alive from acute care hospitals between April 1, 1990 and February 28, 2009. We identified the rate of leaving AMA, and used multivariable logistic regression to identify socio-demographic and diagnostic variables associated with leaving AMA. Results Of 1 916 104 live hospital discharges, 21 417 (1.11%) ended with the patient leaving AMA. The cohort contained 610 187 individuals, of whom 12 588 (2.06%) left AMA once and another 2 986 (0.49%) left AMA more than once. The proportion of AMA discharges did not change over time. Alcohol and drug abuse was the diagnostic group with the highest proportion of AMA discharges, at 11.71%. Having left AMA previously had the strongest association with leaving AMA (odds ratio 170, 95% confidence interval 156–185). Leaving AMA was more common among men, those with lower average household incomes, histories of alcohol or drug abuse or HIV/AIDS. Major surgical procedures were associated with a much lower chance of leaving the hospital AMA. Conclusions The rate of leaving hospital AMA did not systematically change over time, but did vary based on patient and illness characteristics. Having left AMA in the past was highly predictive of subsequent AMA events.

Fracture Risk Assessment (FRAX) tools are calibrated from country-specific fracture epidemiology. Although hip fracture data are usually available, data on non-hip fractures for most countries are often lacking. In such cases, rates are often estimated by assuming similar non-hip to hip fracture ratios from historical (1987 to 1996) Swedish data. Evidence that countries share similar fracture ratios is limited. Using data from Manitoba, Canada (2000 to 2007, population 1.2 million), we identified 21,850 incident major osteoporotic fractures (MOF) in men and women aged50 years. Population-based age- and sex-specific ratios of clinical vertebral, forearm, and humerus fractures to hip fractures were calculated, along with odds ratios (ORs) and 95% confidence intervals (CIs). All ratios showed decreasing trends with increasing age for both men and women. Men and women showed similar vertebral/hip fracture ratios (all p 0.1, with ORs 0.86 to 1.25). Forearm/hip and humerus/hip fracture ratios were significantly lower among men than women (forearm/hip ratio: p 0.01 for all age groups, with ORs 0.29 to 0.53; humerus/hip ratio: p 0.05 for all age groups [except 80 to 84 years] with ORs 0.46 to 0.86). Ratios for any MOF/hip fracture were also significantly lower among men than women in all but two subgroups (p 0.05 for all age groups [except 80 to 84 and 90+ years] with ORs 0.48 to 0.87). Swedish vertebral/hip fracture ratios were similar to the Canadian fracture ratios (within 7%) but significantly lower for other sites (men and women: 46% and 35% lower for forearm/hip ratios, 19% and 15% lower for humerus/hip ratios, and 19% and 23% lower for any MOF/hip ratios). These differences have implications for updating and calibrating FRAX tools, fracture risk estimation, and intervention rates. Moreover, wherever possible, it is important that countries try to collect accurate non-hip fracture data.

Background: Leaving hospital against medical advice may have adverse consequences. Previous studies have been limited by evaluating specific types of patients, small sample sizes and incomplete determination of outcomes. We hypothesized that leaving hospital against medical advice would be associated with increases in subsequent readmission and death. Methods: In a population-based analysis involving all adults admitted to hospital and discharged alive in Manitoba from Apr. 1, 1990, to Feb. 28, 2009, we evaluated all-cause 90-day mortality and 30-day hospital readmission. We used multivariable regression, adjusted for age, sex, socioeconomic status, year of hospital admission, patient comorbidities, hospital diagnosis, past frequency of admission to hospital, having previously left hospital against medical advice and data clustering (patients with multiple admissions). For readmission, we assessed both between-person and within-person effects of leaving hospital against medical advice. Results: Leaving against medical advice occurred in 21 417 of 1 916 104 index hospital admissions (1.1%), and was associated with higher adjusted rates of 90-day mortality (odds ratio [OR] 2.51, 95% confidence interval [CI] 2.18–2.89), and 30-day hospital readmission (within-person OR 2.10, CI 1.99–2.21; between-person OR 3.04, CI 2.79–3.30). In our additional analyses, elevated rates of readmission and death associated with leaving against medical advice were manifest within 1 week and persisted for at least 180 days after discharge. Interpretation: Adults who left the hospital against medical advice had higher rates of hospital readmission and death. The persistence of these effects suggests that they are not solely a result of incomplete treatment of acute illness. Interventions aimed at reducing these effects may need to include longitudinal interventions extending beyond admission to hospital.

Background Databases used to study the care of patients in hospitals and Intensive Care Units (ICUs) typically contain a separate entry for each segment of hospital or ICU care. However, it is not uncommon for patients to be transferred between hospitals and/or ICUs, and when transfers occur it is necessary to combine individual entries to accurately reconstruct the complete episodes of hospital and ICU care. Failure to do so can lead to erroneous lengths-of-stay, and rates of admissions, readmissions, and death. Methods This study used a clinical ICU database and administrative hospital abstracts for the adult population of Manitoba, Canada from 2000–2008. We compared five methods for identifying patient transfers and constructing hospital episodes, and the ICU episodes contained within them. Method 1 ignored transfers. Methods 2–5 considered the time gap between successive entries (≤1 day vs. ≤2 days), with or without use of data fields indicating inter-hospital transfer. For the five methods we compared the resulting number and lengths of hospital and ICU episodes. Results During the study period, 48,551 hospital abstracts contained 53,246 ICU records. For Method 1 these were also the number of hospital and ICU episodes, respectively. Methods 2–5 gave remarkably similar results, with transfers included in approximately 25% of ICU-containing hospital episodes, and 10% of ICU episodes. Comparison with Method 1 showed that failure to account for such transfers resulted in overestimating the number of episodes by 7-10%, and underestimating mean or median lengths-of-stay by 9-30%. Conclusions In Manitoba is it not uncommon for critically ill patients to be transferred between hospitals and between ICUs. Failure to account for transfers resulted in inaccurate assessment of parameters relevant to researchers, clinicians, and policy-makers. The details of the method used to identify transfers, at least among the variations tested, made relatively little difference. In addition, we showed that these methods for constructing episodes of hospital and ICU care can be implemented in a large, complex dataset.

Background A prerequisite for using administrative data to study the care of critically ill patients in intensive care units (ICUs) is that it accurately identifies such care. Only limited data exist on this subject. Objective To assess the accuracy of administrative data in the Canadian province of Manitoba for identifying the existence, number, and timing of admissions to adult ICUs. Research design For the period 1999 to 2008, we compared information about ICU care from Manitoba hospital abstracts, with the criterion standard of a clinical ICU database that includes all admissions to adult ICUs in its largest city of Winnipeg. Comparisons were made before and after a national change in administrative data requirements that mandated specific data elements identifying the existence and timing of ICU care. Results In both time intervals, hospital abstracts were extremely accurate in identifying the presence of ICU care, with positive predictive values exceeding 98% and negative predictive values exceeding 99%. Administrative data correctly identified the number of separate ICU admissions for 93% of ICU-containing hospitalizations; inaccuracy increased with more ICU stays per hospitalization. Hospital abstracts were highly accurate for identifying the timing of ICU care, but only for hospitalizations containing a single ICU admission. Conclusions Under current national-reporting requirements, hospital administrative data in Canada can be used to accurately identify and quantify ICU care. The high accuracy of Manitoba administrative data under the previous reporting standards, which lacked standardized coding elements specific to ICU care, may not be generalizable to other Canadian jurisdictions.

The post-fracture care gap has not narrowed in recent years. Following an initial improvement, rates of medication initiation have actually declined.The current study characterizes temporal changes in post-fracture bone mineral density (BMD) testing or osteoporosis treatment initiation from 1996/1997 to 2007/2008.A population-based administrative data repository for Manitoba, Canada was accessed to identify non-traumatic fractures in individuals aged 50 years and older. Outcomes included BMD testing or dispensation of an osteoporosis medication in the 12 months following the fracture.Thirty thousand nine hundred and twenty (30,920) fracture events met the inclusion criteria; 15,670 affected major osteoporotic fracture sites. Based on either BMD testing or treatment initiation, intervention rates reached a maximum of only 15.5% in 2003/2004, compared with 6.3% in 1996/1997, and 13.2% in 2007/2008 (p-for-trend0.001). Post-fracture BMD testing increased from 0.7% in 1996/1997 to 8.9% 2007/2008 (p-for-trend0.001). Osteoporosis medication use increased from 6.1% in 1996/1997 to 12.3% in 2001/2002 and then progressively declined to 5.9% by 2007/2008 (p-for-trend = 0.025). Similar trends were observed when only major osteoporotic fractures were included. The initiation of BMD testing or medication varied according to age, gender, geographic region, and income.Despite increased attention to gaps in osteoporosis management post-fracture in the last 10 years, the situation has not improved: in 2007/20008, fewer than 20% of untreated individuals with a low-trauma fracture received intervention. Novel strategies are required to disseminate and implement best practices at the point of care to reduce the risk of recurrent fractures.

A simple case definition for osteoporosis case diagnosis is feasible based upon administrative health data. This may facilitate implementation of a population-based osteoporosis surveillance program, providing information that could help to inform and guide screening, prevention, and treatment resources. Our aim was to construct and validate a simplified algorithm for osteoporosis case ascertainment from administrative databases that would be suitable for disease surveillance. Multiple classification rules were applied to different sets of hospital diagnosis, physician claims diagnosis, and prescription drug variables from Manitoba, Canada. Algorithms were validated against results from a regional bone mineral density testing program that identified bone mineral density (BMD) measurements in 4,015 women age 50 years and older with at least one BMD test between April 1, 2000 and March 31, 2001. Sensitivity as high as 93.3% was achieved with 3 years of data. Specificity ranged from 50.8% to 91.4% overall, and from 81.2% to 99.1% for discriminating osteoporotic from normal BMD. Sensitivity and overall accuracy were generally lower for algorithms based on diagnosis codes alone than for algorithms that included osteoporosis prescriptions. In the subgroup without prior osteoporotic fractures or chronic corticosteroid use, one simple algorithm (one hospital diagnosis, physician claims diagnosis, or osteoporosis prescription within 1 year) gave accuracy measures exceeding 90% for discriminating osteoporosis from normal BMD across a wide range of disease prevalence. A relatively simple case definition for osteoporosis surveillance based upon administrative health data can achieve an acceptable level of sensitivity, specificity, and accuracy. Performance is enhanced when the case definition includes osteoporosis medication use in the formulation.

Background Administrative and survey data are two key data sources for population-based research about chronic disease. The objectives of this methodological paper are to: (1) estimate agreement between the two data sources for irritable bowel syndrome (IBS) and compare the results to those for inflammatory bowel disease (IBD); (2) compare the frequency of IBS-related diagnoses in administrative data for survey respondents with and without self-reported IBS, and (3) estimate IBS prevalence from both sources. Methods This retrospective cohort study used linked administrative and health survey data for 5,134 adults from the province of Manitoba, Canada. Diagnoses in hospital and physician administrative data were investigated for respondents with self-reported IBS, IBD, and no bowel disorder. Agreement between survey and administrative data was estimated using the κ statistic. The χ2 statistic tested the association between the frequency of IBS-related diagnoses and self-reported IBS. Crude, sex-specific, and age-specific IBS prevalence estimates were calculated from both sources. Results Overall, 3.0% of the cohort had self-reported IBS, 0.8% had self-reported IBD, and 95.3% reported no bowel disorder. Agreement was poor to fair for IBS and substantially higher for IBD. The most frequent IBS-related diagnoses among the cohort were anxiety disorders (34.4%), symptoms of the abdomen and pelvis (26.9%), and diverticulitis of the intestine (10.6%). Crude IBS prevalence estimates from both sources were lower than those reported previously. Conclusions Poor agreement between administrative and survey data for IBS may account for differences in the results of health services and outcomes research using these sources. Further research is needed to identify the optimal method(s) to ascertain IBS cases in both data sources.

To investigate rates of assessment and treatment of osteoporosis among older women during the year after they have had fractures.Observational, historical, population-based cohort study.Manitoba, which maintains a comprehensive population-based repository of health care services provided and has a publicly funded health care system.Women 50 years old and older who had suffered fractures between 1997 and 2002. These women were chosen from among approximately 175,000 women of this age in Manitoba.We examined each woman's annual medical record between April 1, 1997, and March 31, 2002, to find any International Classification of Diseases fracture codes that have been consistently associated with osteoporosis. We looked for postfracture care during the first 12 months after fractures: bone mineral density (BMD) testing or treated with osteoporosis pharmacotherapy. Analysis was stratified by type of fracture: designated type 1 fractures (spine or hip) and type 2 fractures (not spine or hip).Use of BMD testing or osteoporosis pharmacotherapy during the first 12 months following fractures.For type 1 fractures, BMD assessment during the first year after fracture increased from 2.6% in 1997-1998 to 4.6% in 2001-2002 (P for trend .0004). Rates of therapy with osteoporosis medication increased from 4.9% in 1997-1998 to 17.6% in 2001-2002 (P for trend.0001). Results were similar for type 2 fractures. In the final year of the study, only 20.5% of women with either type of fracture underwent any identifiable intervention (BMD assessment or osteoporosis pharmacotherapy). The intervention rate was substantially higher among women 50 to 64 years old (26.4%) than among those 75 years old or older (17.9%, P for trend.0001).Women at highest risk of future fractures are assessed infrequently for osteoporosis with BMD testing and given pharmacotherapy to prevent future fractures just as infrequently. This gap in care was particularly striking for BMD testing despite the fact that testing is free in Manitoba's publicly funded system. Data from this study could be educational for physicians treating osteoporosis and should encourage them to improve their practice patterns and optimize patient care.

Medication use is recognized as the least expensive, most cost-effective health care intervention. In older adults this is especially important, as they are the largest consumer of prescription medications. We describe the use of a linked data set including pharmaceutical, medical, and hospital claims to examine pharmaceutical use in the population of older adults and then give several examples of its application. Indicators to describe the population's overall use of medication and the appropriate use of specific medication have been developed. Indicators of appropriate use are characterized using the dispensation of benzodiazepines to older adults. We have found that a significant proportion of new users of benzodiazepines are still prescribed a long-acting version (over 10%), signifying potential inappropriate use. The data are also able to describe some significant outcomes from the use of pharmaceuticals such as death, fracture, and population-based clinical measures where available.