The Impact of Primary Care Clinic and Family Physician Continuity on Patient Health Outcomes: A Retrospective Analysis From Alberta, Canada.

PURPOSE: Continuity of care is broadly associated with better patient health outcomes. The relative contributions of continuity with an individual physician and with a practice, however, have not generally been distinguished. This retrospective observational study examined the impact of continuity of care for patients seen at their main clinic but by different family physicians. METHODS: We analyzed linked health administrative data from 2015-2018 from Alberta, Canada to explore the association of physician and clinic continuity with rates of emergency department (ED) visits and hospitalizations across varying levels of patient complexity. Physician continuity was calculated using the known provider of care index and clinic continuity with an analogous measure. We developed zero-inflated negative binomial models to assess the association of each with all-cause ED visits and hospitalizations. RESULTS: High physician continuity was associated with lower ED use across all levels of patient complexity and with fewer hospitalizations for highly complex patients. Broadly, no (0%) clinic continuity was associated with increased use and complete (100%) clinic continuity with decreased use, with the largest effect seen for the most complex patients. Levels of clinic continuity between 1% and 50% were generally associated with slightly higher use, and levels of 51% to 99% with slightly lower use. CONCLUSIONS: The best health care outcomes (measured by ED visits and hospitalizations) are associated with consistently seeing one's own primary family physician or seeing a clinic partner when that physician is unavailable. The effect of partial clinic continuity appears complex and requires additional research. These results provide some reassurance for part-time and shared practices, and guidance for primary care workforce policy makers.

Rural-Urban Disparities in Realized Spatial Access to General Practitioners, Orthopedic Surgeons, and Physiotherapists among People with Osteoarthritis in Alberta, Canada.

Rural Canadians have high health care needs due to high prevalence of osteoarthritis (OA) but lack access to care. Examining realized access to three types of providers (general practitioners (GPs), orthopedic surgeons (Ortho), and physiotherapists (PTs)) simultaneously helps identify gaps in access to needed OA care, inform accessibility assessment, and support health care resource allocation. Travel time from a patient's postal code to the physician's postal code was calculated using origin-destination network analysis. We applied descriptive statistics to summarize differences in travel time, hotspot analysis to explore geospatial patterns, and distance decay function to examine the travel pattern of health care utilization by urbanicity. The median travel time in Alberta was 11.6 min (IQR = 4.3-25.7) to GPs, 28.9 (IQR = 14.8-65.0) to Ortho, and 33.7 (IQR = 23.1-47.3) to PTs. We observed significant rural-urban disparities in realized access to GPs (2.9 and IQR = 0.0-92.1 in rural remote areas vs. 12.6 and IQR = 6.4-21.0 in metropolitan areas), Ortho (233.3 and IQR = 171.3-363.7 in rural remote areas vs. 21.3 and IQR = 14.0-29.3 in metropolitan areas), and PTs (62.4 and IQR = 0.0-232.1 in rural remote areas vs. 32.1 and IQR = 25.2-39.9 in metropolitan areas). We identified hotspots of realized access to all three types of providers in rural remote areas, where patients with OA tend to travel longer for health care. This study may provide insight on the choice of catchment size and the distance decay pattern of health care utilization for further studies on spatial accessibility.

Rural-Urban Differences in Non-Local Primary Care Utilization among People with Osteoarthritis: The Role of Area-Level Factors.

The utilization of non-local primary care physicians (PCP) is a key primary care indicator identified by Alberta Health to support evidence-based healthcare planning. This study aims to identify area-level factors that are significantly associated with non-local PCP utilization and to examine if these associations vary between rural and urban areas. We examined rural-urban differences in the associations between non-local PCP utilization and area-level factors using multivariate linear regression and geographically weighted regression (GWR) models. Global Moran's I and Gi* hot spot analyses were applied to identify spatial autocorrelation and hot spots/cold spots of non-local PCP utilization. We observed significant rural-urban differences in the non-local PCP utilization. Both GWR and multivariate linear regression model identified two significant factors (median travel time and percentage of low-income families) with non-local PCP utilization in both rural and urban areas. Discontinuity of care was significantly associated with non-local PCP in the southwest, while the percentage of people having university degree was significant in the north of Alberta. This research will help identify gaps in the utilization of local primary care and provide evidence for health care planning by targeting policies at associated factors to reduce gaps in OA primary care provision.

Data harmonization and data pooling from cohort studies: a practical approach for data management.

Data pooling from pre-existing datasets can be useful to increase study sample size and statistical power in order to answer a research question. However, individual datasets may contain variables that measure the same construct differently, posing challenges for data pooling. Variable harmonization, an approach that can generate comparable datasets from heterogeneous sources, can address this issue in some circumstances. As an illustrative example, this paper describes the data harmonization strategies that helped generate comparable datasets across two Canadian pregnancy cohort studies: All Our Families; and the Alberta Pregnancy Outcomes and Nutrition. Variables were harmonized considering multiple features across the datasets: the construct measured; question asked/response options; the measurement scale used; the frequency of measurement; timing of measurement, and the data structure. Completely matching, partially matching, and completely un-matching variables across the datasets were determined based on these features. Variables that were an exact match were pooled as is. Partially matching variables were harmonized or processed under a common format across the datasets considering the frequency of measurement, the timing of measurement, the measurement scale used, and response options. Variables that were completely unmatching could not be harmonized into a single variable. The variable harmonization strategies that were used to generate comparable cohort datasets for data pooling are applicable to other data sources. Future studies may employ or evaluate these strategies, which permit researchers to answer novel research questions in a statistically efficient, timely, and cost-efficient manner that could not be achieved using a single data source.

Geographic Variation in the Prevalence of Rheumatoid Arthritis in Alberta, Canada.

OBJECTIVES: Timely access to rheumatologists remains a challenge in Alberta, a Canadian province with vast rural areas, whereas rheumatologists are primarily clustered in metro areas. To address the goal of timely and equitable access to rheumatoid arthritis (RA) care, health planners require information at the regional and local level to determine the RA prevalence and the associated health care needs. METHODS: Using Alberta Health administrative databases, we identified RA-prevalent cases (April 1, 2015-March 31, 2016) on the basis of a validated case definition. Age- and sex-standardized prevalence rates per 1000 population members and the standardized rates ratio (SRR) were calculated. We applied Global Moran's I and Gi* hotspot analysis using three different weight matrices to explore the geospatial pattern of RA prevalence in Alberta. RESULTS: Among 38 350 RA cases (68% female; n = 26 236), the prevalence rate was 11.81 cases per 1000 population members (95% confidence interval [CI] 11.80-11.81) after age and sex standardization. Approximately 60% of RA cases resided in metro (Calgary and Edmonton) and moderate metro areas. The highest rate was observed in rural areas (14.46; 95% CI 14.45-14.47; SRR 1.28), compared with the lowest in metro areas (10.69; 95% CI 10.68-10.69; SRR 0.82). The RA prevalence across local geographic areas ranged from 4.7 to 30.6 cases. The Global Moran's I index was 0.15 using three different matrices (z-score 3.96-4.24). We identified 10 hotspots in the south and north rural areas and 18 cold spots in metro and moderate metro Calgary. CONCLUSION: The findings highlight notable rural-urban variation in RA prevalence in Alberta. Our findings can inform strategies aimed at reducing geographic disparities by targeting areas with high health care needs.

Assessment of anxiety during pregnancy: are existing multiple anxiety scales suitable and comparable in measuring anxiety during pregnancy?

BACKGROUND: This study examined the performance of multiple anxiety scales in measuring anxiety during pregnancy, an important issue due to the possible effect of pregnancy-related symptoms on the measurement of anxiety. METHODS: Secondary data on anxiety, measured by the State-Trait Anxiety Inventory-State (STAI-S) 20-item and six-item scales, the Edinburgh Postnatal Depression Scale-Anxiety Subscale (EPDS-3A) and the Symptoms Checklist-90-Anxiety Subscale (SCL-90), were obtained from two pregnancy cohort studies. Both cohorts completed the EPDS-3A, while 3341 women completed the STAI-S and 2187 women completed the SCL-90, with 231 women participating in both cohorts. Data were analyzed using confirmatory factor analysis and Spearman correlation. RESULTS: The STAI-6 had adequate model fit, while the STAI-20 and the SCL-90 had inadequate model fit. Model fitness for the EPDS-3A could not be assessed due to its low number of items. The correlation between the STAI-20 and STAI-6 was excellent (r = 0.93). The correlation of EPDS-3A with other anxiety scales was low to moderate (r (STAI-20) = 0.57, r (STAI-6) = 0.53 and r (SCL-90) = 0.44). The correlation of SCL-90 with both STAI-20 and STAI-6 was low (r < 0.50). CONCLUSION: Findings indicate that these scales do not measure anxiety as a single dimension and that these scales are incomparable and may conceptualize anxiety differently.

Geospatial patterns of comorbidity prevalence among people with osteoarthritis in Alberta Canada.

BACKGROUND: Knowledge of geospatial pattern in comorbidities prevalence is critical to an understanding of the local health needs among people with osteoarthritis (OA). It provides valuable information for targeting optimal OA treatment and management at the local level. However, there is, at present, limited evidence about the geospatial pattern of comorbidity prevalence in Alberta, Canada. METHODS: Five administrative health datasets were linked to identify OA cases and comorbidities using validated case definitions. We explored the geospatial pattern in comorbidity prevalence at two standard geographic areas levels defined by the Alberta Health Services: descriptive analysis at rural-urban continuum level; spatial analysis (global Moran's I, hot spot analysis, cluster and outlier analysis) at the local geographic area (LGA) level. We compared area-level indicators in comorbidities hotspots to those in the rest of Alberta (non-hotspots). RESULTS: Among 359,638 OA cases in 2013, approximately 60% of people resided in Metro and Urban areas, compared to 2% in Rural Remote areas. All comorbidity groups exhibited statistically significant spatial autocorrelation (hypertension: Moran's I index 0.24, z score 4.61). Comorbidity hotspots, except depression, were located primarily in Rural and Rural Remote areas. Depression was more prevalent in Metro (Edmonton-Abbottsfield: 194 cases per 1000 population, 95%CI 192-195) and Urban LGAs (Lethbridge-North: 169, 95%CI 168-171) compared to Rural areas (Fox Creek: 65, 95%CI 63-68). Comorbidities hotspots included a higher percentage of First Nations or Inuit people. People with OA living in hotspots had lower socioeconomic status and less access to care compared to non-hotspots. CONCLUSIONS: The findings highlight notable rural-urban disparities in comorbidities prevalence among people with OA in Alberta, Canada. Our study provides valuable evidence for policy and decision makers to design programs that ensure patients with OA receive optimal health management tailored to their local needs and a reduction in current OA health disparities.

Patient-Physician Relational Continuity and Health System Utilization among Patients in Alberta.

In Alberta, no standardized processes exist to identify patients with chronic diseases (CDs) who do not have a family physician. This study examined the association between relational continuity (continuity of care) and healthcare utilization patterns in this population. Relational continuity was assessed using health administrative data to calculate a Usual Provider Continuity (UPC) Index. The majority of patients with no or a low UPC Index were male, did not have CD and were healthy or non-users of healthcare. When grouped by UPC Index, regression modelling revealed that emergency department visits and unplanned hospitalization declined with increased continuity of care. Advanced state of disease(s) and location of residence increased the likelihood of utilization of these services in the low- and moderate-continuity groups.

Neighbourhood socioeconomic status modifies the association between anxiety and depression during pregnancy and preterm birth: a Community-based Canadian cohort study.

OBJECTIVE: This study examined the association of anxiety alone, depression alone and the presence of both anxiety and depression with preterm birth (PTB) and further examined whether neighbourhood socioeconomic status (SES) modified this association. DESIGN: Cohort study using individual-level data from two community-based prospective pregnancy cohort studies (All Our Families; AOF) and Alberta Pregnancy Outcomes and Nutrition (APrON) and neighbourhood SES data from the 2011 Canadian census. SETTING: Calgary, Alberta, Canada. PARTICIPANTS: Overall, 5538 pregnant women who were <27 weeks of gestation and >15 years old were enrolled in the cohort studies between 2008 and 2012. 3341 women participated in the AOF study and 2187 women participated in the APrON study, with 231 women participated in both studies. Women who participated in both studies were only counted once. PRIMARY AND SECONDARY OUTCOME MEASURES: PTB was defined as delivery prior to 37 weeks of gestation. Depression was defined as an Edinburgh Postnatal Depression Scale (EPDS) score of ≥13, anxiety was defined as an EPDS-anxiety subscale score of ≥6, and the presence of both anxiety and depression was defined as meeting both anxiety and depression definitions. RESULTS: Overall, 7.3% of women delivered preterm infants. The presence of both anxiety and depression, but neither of these conditions alone, was significantly associated with PTB (OR 1.6, 95% CI 1.1 to 2.3) and had significant interaction with neighbourhood deprivation (p=0.004). The predicted probability of PTB for women with both anxiety and depression was 10.0%, which increased to 15.7% if they lived in the most deprived neighbourhoods and decreased to 1.4% if they lived in the least deprived neighbourhoods. CONCLUSIONS: Effects of anxiety and depression on risk of PTB differ depending on where women live. This understanding may guide the identification of women at increased risk for PTB and allocation of resources for early identification and management of anxiety and depression.

Does neighborhood socioeconomic status predict the risk of preterm birth? A community-based Canadian cohort study.

OBJECTIVE: This study developed and internally validated a predictive model for preterm birth (PTB) to examine the ability of neighbourhood socioeconomic status (SES) to predict PTB. DESIGN: Cohort study using individual-level data from two community-based prospective pregnancy cohort studies (All Our Families (AOF) and Alberta Pregnancy Outcomes and Nutrition (APrON)) and neighbourhood SES data from the 2011 Canadian census. SETTING: Calgary, Alberta, Canada. PARTICIPANTS: Pregnant women who were <24 weeks of gestation and >15 years old were enrolled in the cohort studies between 2008 and 2012. Overall, 5297 women participated in at least one of these cohorts: 3341 women participated in the AOF study, 2187 women participated in the APrON study and 231 women participated in both studies. Women who participated in both studies were only counted once. PRIMARY AND SECONDARY OUTCOME MEASURES: PTB (delivery prior to 37 weeks of gestation). RESULTS: The rates of PTB in the least and most deprived neighbourhoods were 7.54% and 10.64%, respectively. Neighbourhood variation in PTB was 0.20, with an intra-class correlation of 5.72%. Neighbourhood SES, combined with individual-level predictors, predicted PTB with an area under the receiver-operating characteristic curve (AUC) of 0.75. The sensitivity was 91.80% at a low-risk threshold, with a high false-positive rate (71.50%), and the sensitivity was 5.70% at a highest risk threshold, with a low false-positive rate (0.90%). An agreement between the predicted and observed PTB demonstrated modest model calibration. Individual-level predictors alone predicted PTB with an AUC of 0.60. CONCLUSION: Although neighbourhood SES combined with individual-level predictors improved the overall prediction of PTB compared with individual-level predictors alone, the detection rate was insufficient for application in clinical or public health practice. A prediction model with better predictive ability is required to effectively find women at high risk of preterm delivery.

High-volume general practitioners in Alberta: a descriptive analysis.

BACKGROUND: Alberta is considering capping daily fee-for-service physician billings, but little is known about high-volume practice in the province and its impact on patient health outcomes. In this initial study, we conducted a descriptive analysis of general practitioners' patient volumes and billing practices in relation to associated practitioner demographic characteristics. METHODS: We conducted a retrospective descriptive analysis of the associations of practitioner characteristics, including full-time versus non-full-time practice, provider sex, years in practice, geographic location and international medical graduate status, with high-volume (> 50 visits/d) practice using general practice billing data from 2011 to 2016. Use of general practitioner service codes was described and compared by general practitioner volume status, with adjustment for physician demographic characteristics and geographic parameters. RESULTS: We included 3465 general practitioners practising fee-for-service in Alberta between 2011 and 2016, of whom 233 (6.7%) were identified as high-volume providers. Physicians who had been in practice longer (odds ratio [OR] 1.04 per year, 95% confidence interval [CI] 1.02-1.05) and international medical graduates (OR 1.89, 95% CI 1.40-2.54) were more likely to exceed 50 patient visits/day. Female physicians were less likely to exceed 50 patient visits/day (OR 0.14, 95% CI 0.07-0.28). Rural practice location was negatively associated with high-volume practice (OR 0.87, 95% CI 0.79-0.95) when we controlled for zone within the province. Zone 5 (North) was associated with high-volume practice (OR 1.95, 95% CI 1.06-3.58). Less than full-time practice was prevalent (1836 providers [53.0%]). High-volume general practitioners billed fewer service codes requiring longer visits, except for the most highly remunerated code (patients with complex health issues). INTERPRETATION: These results can inform policy-makers when considering payment system changes. Our next step is to examine the association of high-volume practice with outcomes important to patients, such as evidence of treatment failure (emergency department visits and hospital admissions) for conditions sensitive to primary care management.

Differences in caesarean rates across women's socio-economic status by diverse obstetric indications: Cross-sectional study.

BACKGROUND: The existing inconsistent association between the caesarean rate and maternal socio-economic status (SES) may be the result of a failure to examine the association across indications for caesarean. This study examined the variation in caesarean rates by maternal SES across diverse obstetric-indications. METHODS: Data on demographics, education, insurance status, medical-conditions, and obstetric characteristics needed to classify deliveries according to Robson's 10 obstetric-groups were extracted from the 2015 US birth certificate data (n = 3 988 733). Multivariable log-binomial regression was used to analyse the data adjusting for confounders. RESULTS: The caesarean rate was 34.1% for women with high SES and 26.8% for those with low SES. After adjustment for confounders, the rate was similar between women with graduate degrees and those who did not complete high school (relative risk (RR) 1.0, 95% confidence interval (CI) 0.9, 1.1). However, different rates of caesareans across SES were observed for particular obstetric-indications. Notably, women with graduate education compared to those who did not complete high school were more likely to have a caesarean (RR 3.0, 95% CI 2.9, 3.1) for a low-risk condition (group 1: nulliparous women with single, cephalic, ≥37 gestational weeks, and spontaneous labour). Women with private insurance were more likely to have a caesarean in almost all obstetric groups, compared to those without private insurance or Medicaid. CONCLUSION: Examining the overall caesarean rate obscures the relationship between SES and the use of caesarean for particular obstetric-indications. The unequal utilisation of caesareans across SES highlights overuse and potential underuse of the caesareans among American women.

Drip and ship versus direct to endovascular thrombectomy: The impact of treatment times on transport decision-making.

INTRODUCTION: In ischaemic stroke care, fast reperfusion is essential for disability free survival. It is unknown if bypassing thrombolysis centres in favour of endovascular thrombectomy (mothership) outweighs transport to the nearest thrombolysis centre for alteplase and then transfer for endovascular thrombectomy (drip-and-ship). We use conditional probability modelling to determine the impact of treatment times on transport decision-making for acute ischaemic stroke. MATERIALS AND METHODS: Probability of good outcome was modelled using a previously published framework, data from the Irish National Stroke Register, and an endovascular thrombectomy registry at a tertiary referral centre in Ireland. Ireland was divided into 139 regions, transport times between each region and hospital were estimated using Google's Distance Matrix Application Program Interface. Results were mapped using ArcGIS 10.3. RESULTS: Using current treatment times, drip-and-ship rarely predicts best outcomes. However, if door to needle times are reduced to 30 min, drip-and-ship becomes more favourable; even more so if turnaround time (time from thrombolysis to departure for the endovascular thrombectomy centre) is also reduced. Reducing door to groin puncture times predicts better outcomes with the mothership model. DISCUSSION: This is the first case study modelling pre-hospital transport for ischaemic stroke utilising real treatment times in a defined geographic area. A moderate improvement in treatment times results in significant predicted changes to the optimisation of a national acute stroke patient transport strategy. CONCLUSIONS: Modelling patient transport for system-level planning is sensitive to treatment times at both thrombolysis and thrombectomy centres and has important implications for the future planning of thrombectomy services.

Variation in Maternal Co-morbidities and Obstetric Interventions across Area-Level Socio-economic Status: A Cross-Sectional Study.

BACKGROUND: Multiple studies indicate a significant association between area-level socio-economic status (SES) and adverse maternal health outcomes; however, the impact of area-level SES on maternal co-morbidities and obstetric interventions has not been examined. OBJECTIVE: To examine the variation in maternal co-morbidities and obstetric interventions across area-level SES. METHODS: This study used data from the Discharge Abstract Database that comprised birth data in Alberta between 2005-2007 (n = 120 285). Co-morbidities and obstetric interventions were identified using validated case-definitions. Material deprivation index was obtained for each dissemination area through linkage of hospitalisation and census data. Multilevel logistic regression was used to analyse the data adjusting for potential confounding variables. RESULTS: The prevalence of any co-morbidity varied across area-level SES. Drug abuse odds ratio (OR) 2.5 (95% confidence interval (CI) 1.8, 3.5), pre-existing diabetes OR 1.7 (95% CI 1.1, 2.6), and prolonged hospital stay OR 1.5 (95% CI 1.4, 1.6) were significantly more likely to occur in the most deprived areas compared to the least deprived areas. In contrast, caesarean delivery OR 0.9 (95% CI 0.8, 0.9) was less likely to occur in the most deprived areas compared to the least deprived areas. Area-level deprivation explained area-level variance of drug abuse, HIV, and other mental diseases only. CONCLUSION: Many co-morbidities and obstetric interventions vary at the area-level, but only some are associated with area-level SES, and few of them vary due to the area-level SES. This indicates that other area-level factors, in addition to area-level SES, need to be considered when investigating maternal health and use of health interventions.

Geographic Clustering of Acute Complications and Sociodemographic Factors in Adults with Type 1 Diabetes.

OBJECTIVES: To assess the geographic distribution of acute complications in patients with type 1 diabetes in a large urban centre; and to assess the association between acute complications and community-level sociodemographic factors. METHODS: Adults (aged ≥18 years old) with type 1 diabetes and acute complications were identified between 2004 and 2008 by using a diabetes centre clinical database or discharge abstracts for acute complications (diabetic ketoacidosis or hypoglycemia). Using a geographic information system, hot-spot analysis was used to identify spatial clusters of acute complications in a large urban centre. The association between acute complications and community-level sociodemographic factors were assessed by Spearman rank correlation. RESULTS: We identified 1779 patients with type 1 diabetes, of whom 456 had been hospitalized for acute complications. The mean age of patients was 40.9±16.0 years, and men were more likely to have acute complications (59.2% vs. 52.3%; p<0.01). Spatial clusters of high values and low values were identified. Higher median family income (r=-0.36; p<0.0001) and higher education levels (r=-0.30; p<0.0001) were associated with lower rates of acute complications. CONCLUSIONS: This study demonstrated geographic clusters of hospitalizations for acute complications and important community sociodemographic factors. Prevention strategies and interventions targeting these geographic and sociodemographic disparities need to be explored as a means of minimizing hospitalizations for acute complications.

Validity and utility of ICD-10 administrative health data for identifying ST- and non-ST-elevation myocardial infarction based on physician chart review.

BACKGROUND: Health care administrative databases are useful for assessing the population-level burden of disease and examining issues related to access, costs and quality of care. In these databases, the diagnoses and procedures are coded with the use of the World Health Organization International Classification of Diseases (ICD). We examined the validity of 2 ICD-10 coding definitions for categorizing patients with acute myocardial infarction (MI) as having ST-elevation MI (STEMI) or non-ST-elevation MI (non-STEMI). METHODS: Charts of patients with acute MI discharged between April and June 2007 from 3 hospitals in Edmonton, were reviewed to define the acute MI subtype (i.e., STEMI v. non-STEMI). The agreement between clinician chart review and STEMI/non-STEMI classification based on the standard (ICD-10 I21.x) and the supplementary electrocardiogram (ECG) codes (R94.3x) was determined. We assessed the effect of these alternative definitions on in-hospital mortality estimates by applying them to the data for all patients with acute MI admitted to hospital in the province from April 2007 to March 2010. RESULTS: Of the 297 patients, 49.2% were identified as having STEMI based on chart review, 44.4% using the standard definition, and 44.1% using the ECG definition. Both the standard and ECG definitions provided high agreement (92% for STEMI and 100% for non-STEMI) with the chart review classification. In the larger population-level cohort (n = 15 148), use of the standard definition or the ECG definition did not affect in-hospital mortality estimates for patients with STEMI and those with non-STEMI. INTERPRETATION: The standard definition appears equivalent to the definition using supplementary ECG codes to subcategorize patients with acute MI as having STEMI or non-STEMI. These findings may be relevant for the development of later versions of ICD codes.

Postoperative complications and emergent readmission in children and adults with inflammatory bowel disease who undergo intestinal resection: a population-based study.

BACKGROUND: Although the nature and frequency of postoperative complications after intestinal resection in patients with inflammatory bowel disease have been previously described, short-term readmission has not been characterized in population-based studies. We therefore assessed the risk of postoperative complications and emergent readmissions after discharge from an intestinal resection. METHODS: We used a Canadian provincial-wide inpatient hospitalization database to identify 2638 Crohn's disease (CD) and 559 ulcerative colitis (UC) admissions with intestinal resection from 2002 to 2011. We identified the cumulative risk of in-hospital complication and emergent readmission within 90 days after discharge along with predictors for both outcomes using a Poisson regression for binary outcomes. RESULTS: The cumulative risks of in-hospital postoperative complications and 90-day emergent readmission were 23.8% and 12.6%, respectively in CD and 33.3% and 11.1%, respectively in UC. The predictors for in-hospital postoperative complications for CD and UC included older age, comorbidities, and open laparatomy for CD, additional predictors included emergent admission, stoma surgery, and concurrent resection of both small and large bowel. The predictors for 90-day readmission for CD included a postoperative complication (risk ratio, 1.61; 95% confidence interval, 1.30-2.01), emergent admission (risk ratio, 1.39; 95% confidence interval, 1.12-1.73), and stoma formation (risk ratio, 1.49; 95% confidence interval, 1.15-1.93) at the hospitalization requiring surgery. CONCLUSIONS: Readmission and postoperative complications are common after intestinal resection in CD and UC. Clinicians should closely monitor surgical patients who required emergent admission, undergo surgery with stoma formation, or develop in-hospital postoperative complications to anticipate need for readmission or interventions to prevent readmission.

Association between diabetic ketoacidosis hospitalizations and driving distance to outpatient diabetes centres in adults with type 1 diabetes mellitus.

OBJECTIVE: The purpose of this study was to assess the relationship between diabetic ketoacidosis (DKA) hospitalization and driving distance from home to outpatient diabetes care in adults with type 1 diabetes mellitus. METHODS: We identified adults with type 1 diabetes using clinical and administrative databases living in Calgary, Alberta. The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, codes were used to identify DKA hospitalizations, and geographic information systems were used to obtain road distance. Multivariate logistic regression was used to assess the association between driving distance (exposure) to diabetes care sites and the outcome of DKA hospitalization. RESULTS: We identified 1467 patients (151 patients with DKA) with type 1 diabetes. Patients with DKA hospitalizations were younger (35.6 vs. 41.0 years), had shorter duration of diabetes (13.6 vs. 18.7 years) and higher glycated hemoglobin (9.2% vs. 8.4%). Driving distance from home to diabetes centre 1 (adjusted odds ratio 1.02 per 1 km; 95% confidence interval, 0.96 to 1.07), diabetes centre 2 (adjusted odds ratio 1.01; 95% confidence interval, 0.99 to 1.04) or closest general practitioner (adjusted odds ratio 0.9; 95% confidence interval, 0.63 to 1.25) was not associated with DKA hospitalization. Driving distance was also not associated with glycemic control. CONCLUSIONS: Within a large urban city, driving distance to diabetes centres does not appear to be protective of DKA hospitalization. However, this work does not preclude the role of local travel distance and diabetes outcomes. More research is required to explore the role of other individual, neighbourhood and community factors that influence DKA hospitalization.

A validation of ground ambulance pre-hospital times modeled using geographic information systems.

BACKGROUND: Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. METHODS: The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. RESULTS: There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. CONCLUSIONS: The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area.

Temporal associations of early patient transfers and mortality with the implementation of a regional myocardial infarction care model.

BACKGROUND: In order to reduce the delays encountered through patient transfer, regional care models have been developed that directly transport subsets of acute myocardial infarction (AMI) patients to hospitals with percutaneous coronary intervention (PCI) facilities. Calgary is a Canadian city that implemented this type of model in 2004. METHODS: The study population included 9768 AMI patients admitted to Calgary hospitals between 1997 and 2007. Administrative data were used to define patients who were directly admitted to the PCI hospital and those transferred there after initial admission to a hospital without specialized cardiac care. The differences in clinical characteristics and mortality trends of patients grouped by hospital delivery site and transfer practice are described. RESULTS: The proportion of patients directly admitted to a PCI hospital has increased with the implementation of a regional care model. Among patients admitted to non-PCI facilities, the patients who are transferred are younger, more likely to be male, have a shorter length of stay, and have lower proportions of several comorbid conditions. The risk-adjusted in-hospital mortality odds ratio for patients who received care at the PCI hospital postmodel relative to those treated at non-PCI hospitals premodel was 0.38 (95% confidence interval, 0.31-0.47). The corresponding adjusted odds ratio was 0.60 (0.47-0.76). CONCLUSIONS: Our results suggest changing care over time and trends toward improved outcomes. Patients' clinical characteristics appear to play a major role in the decision to transfer. Avoidance of the risk treatment paradox through refinement of regional transfer protocols ought to be a priority.