Population-based cohort study of hospital delivery volume, geographic accessibility, and obstetric outcomes.

OBJECTIVE: To determine associations between geographic accessibility, delivery volume, and obstetric outcomes. METHODS: Population-based cohort study of linked hospital administrative, census, and geospatial data (2006-2009) from all Canadian jurisdictions except Quebec. Perinatal mortality and major maternal morbidity/mortality were compared across categories of road distance and hospital delivery volume. RESULTS: Among 820 761 mothers delivering 827 504 neonates, travel distance had minimal effect on perinatal mortality. Compared with mothers travelling 0-9 km, the odds of adverse maternal outcomes was decreased for women travelling modest distances (20-49 km, odds ratio, 0.80 [95% confidence interval, 0.75-0.86]), and increased thereafter (50-99 km, 0.99 [0.89-1.10]; 200-299 km, 1.44 [1.10-1.87]; >400 km, 2.22 [1.06-4.63]). Relative to high-volume hospitals (>2500 deliveries/year), adverse maternal outcomes were less likely for hospitals with 1000-2499 (0.90 [0.86-0.95]), and roughly equivalent for hospitals with 200-499 (1.34 [1.22-1.48]) and 500-999 (1.27 [1.17-1.39]) deliveries/year. Odds of perinatal mortality ranged from 1.04 (0.73-1.49; 100-199 deliveries/year) to 1.50 (1.04-2.16; 50-99 deliveries/year); the pattern did not suggest causality. CONCLUSION: Maternal outcomes worsen when travel distance is greater than 200 km, and improve when delivery volume exceeds 1000 deliveries per year.

Patients' perspectives on BETTER 2 prevention and screening: qualitative findings from Newfoundland & Labrador.

BACKGROUND: Chronic disease prevention and screening (CDPS) has been identified as a top priority in primary care. However, primary care providers often lack time, evidence-based tools, and consistent guidelines to effectively address CDPS. Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care (BETTER) is a novel approach that introduces a new role, that of the prevention practitioner; the prevention practitioner meets with patients, one on one, to undertake a personalised CDPS visit. Understanding patients' perspectives is important for clinicians and other stakeholders aiming to address and integrate CDPS. AIM: To describe patients' perspectives regarding visits with a prevention practitioner in BETTER 2, an implementation study that was carried out after the BETTER trial and featured a higher proportion of patients in rural and remote locations. DESIGN & SETTING: Qualitative description based on patient feedback surveys, completed by patients in three primary care clinics (urban, rural, and remote) in Newfoundland and Labrador, Canada. METHOD: Patients' perspectives were assessed based on responses from 91 feedback forms. In total, 154 patients (aged 40-65 years) received ≥1 prevention visit(s) from a prevention practitioner and were asked to provide written feedback. In addition to demographics, patients were asked what they liked about their visit(s), what they would have liked to be different, and invited to make any other comments. Qualitative description was used to analyse the data. RESULTS: Four main themes emerged from patients' feedback: value of visit (patients appreciated the visit with a prevention practitioner); visit characteristics (the visit was personalised, comprehensive, and sufficiently long); prevention practitioners' characteristics (professionalism and interpersonal skills); and patients' concerns (termination of the programme and access to preventative care). CONCLUSION: Patients appreciated the visits they received with a prevention practitioner and expressed their desire to receive sustained CDPS in primary care.

An investigation of cancer rates in the Argentia region, Newfoundland and Labrador: an ecological study.

BACKGROUND: The Argentia region of Newfoundland and Labrador, Canada, was home to a US naval base during a 40-year period between the 1940s and the 1990s. Activities on the base resulted in contamination of the soil and groundwater in the region with chemicals such as heavy metals and dioxins, and residents have expressed concern about higher rates of cancer in their community. This study investigated the rate of cancer diagnosis that is disproportionately high in the Argentia region. METHODS: Cases of cancer diagnosed between 1985 and 2011 were obtained for the Argentia region, two comparison communities, and the province of Newfoundland and Labrador. Crude and age-standardized incidence rates of cancer diagnosis were calculated and compared. The crude incidence rate was adjusted for differences in age demographics using census data, and age-standardized incidence rates were compared. RESULTS: Although the Argentia region had a higher crude rate of cancer diagnosis, the age-standardized incidence rate did not differ significantly from the comparison communities or the provincial average. Argentia has an aging population, which may have influenced the perception of increased cancer diagnosis in the community. CONCLUSIONS: We did not detect an increased burden of cancer in the Argentia region.

Hidden Markov model using Dirichlet process for de-identification.

For the 2014 i2b2/UTHealth de-identification challenge, we introduced a new non-parametric Bayesian hidden Markov model using a Dirichlet process (HMM-DP). The model intends to reduce task-specific feature engineering and to generalize well to new data. In the challenge we developed a variational method to learn the model and an efficient approximation algorithm for prediction. To accommodate out-of-vocabulary words, we designed a number of feature functions to model such words. The results show the model is capable of understanding local context cues to make correct predictions without manual feature engineering and performs as accurately as state-of-the-art conditional random field models in a number of categories. To incorporate long-range and cross-document context cues, we developed a skip-chain conditional random field model to align the results produced by HMM-DP, which further improved the performance.

Outcomes of deliveries by family physicians or obstetricians: a population-based cohort study using an instrumental variable.

BACKGROUND: Previous research has suggested that obstetric outcomes are similar for deliveries by family physicians and obstetricians, but many of these studies were small, and none of them adjusted for unmeasured selection bias. We compared obstetric outcomes between these provider types using an econometric method designed to adjust for unobserved confounding. METHODS: We performed a retrospective population-based cohort study of all Canadian (except Quebec) hospital births with delivery by family physicians and obstetricians at more than 20 weeks gestational age, with birth weight greater than 500 g, between Apr. 1, 2006, and Mar. 31, 2009. The primary outcomes were the relative risks of in-hospital perinatal death and a composite of maternal mortality and major morbidity assessed with multivariable logistic regression and instrumental variable-adjusted multivariable regression. RESULTS: After exclusions, there were 3600 perinatal deaths and 14,394 cases of maternal morbidity among 799,823 infants and 793,053 mothers at 390 hospitals. For deliveries by family physicians v. obstetricians, the relative risk of perinatal mortality was 0.98 (95% confidence interval [CI] 0.85-1.14) and of maternal morbidity was 0.81 (95% CI 0.70-0.94) according to logistic regression. The respective relative risks were 0.97 (95% CI 0.58-1.64) and 1.13 (95% CI 0.65-1.95) according to instrumental variable methods. INTERPRETATION: After adjusting for both observed and unobserved confounders, we found a similar risk of perinatal mortality and adverse maternal outcome for obstetric deliveries by family physicians and obstetricians. Whether there are differences between these groups for other outcomes remains to be seen.

Recognizing National Hockey League greatness with an ignorance-based heuristic.

This study examined whether people adhered to the recognition heuristic (i.e., inferred that a recognized hockey player had more total career points than an unrecognized player) and whether using this heuristic could yield accurate decisions. On paired comparisons, having participants report whether they recognized each player plus any knowledge they had about each player permitted players to be classified as either unrecognized (UR), merely recognized (MR), or recognized with additional knowledge (RK), thus producing six possible trial types. Participants adhered to the recognition heuristic on 95% of MR-UR trials and were accurate on 81% of those trials. They chose the recognized player on 98% of RK-UR trials, yielding 94% accuracy. Women had less knowledge and recognized fewer players than men, yet they were nearly as accurate as men. Future research should examine the conditions under which the recognition heuristic is an adaptive strategy.