Prospective, population-based studies that recruit participants in mid-life are valuable resources for dementia research. Follow-up in these studies is often through linkage to routinely-collected healthcare datasets. We investigated the accuracy of these datasets for dementia case ascertainment in a validation study using data from UK Biobank—an open access, population-based study of > 500,000 adults aged 40–69 years at recruitment in 2006–2010. From 17,198 UK Biobank participants recruited in Edinburgh, we identified those with ≥ 1 dementia code in their linked primary care, hospital admissions or mortality data and compared their coded diagnoses to clinical expert adjudication of their full-text medical record. We calculated the positive predictive value (PPV, the proportion of cases identified that were true positives) for all-cause dementia, Alzheimer’s disease and vascular dementia for each dataset alone and in combination, and explored algorithmic code combinations to improve PPV. Among 120 participants, PPVs for all-cause dementia were 86.8%, 87.3% and 80.0% for primary care, hospital admissions and mortality data respectively and 82.5% across all datasets. We identified three algorithms that balanced a high PPV with reasonable case ascertainment. For Alzheimer’s disease, PPVs were 74.1% for primary care, 68.2% for hospital admissions, 50.0% for mortality data and 71.4% in combination. PPV for vascular dementia was 43.8% across all sources. UK routinely-collected healthcare data can be used to identify all-cause dementia in prospective studies. PPVs for Alzheimer’s disease and vascular dementia are lower. Further research is required to explore the geographic generalisability of these findings. Electronic supplementary material The online version of this article (10.1007/s10654-019-00499-1) contains supplementary material, which is available to authorized users.

IntroductionProspective, population-based studies can be rich resources for dementia research. Follow-up in many such studies is through linkage to routinely collected, coded health-care data sets. We evaluated the accuracy of these data sets for dementia case identification.MethodsWe systematically reviewed the literature for studies comparing dementia coding in routinely collected data sets to any expert-led reference standard. We recorded study characteristics and two accuracy measures—positive predictive value (PPV) and sensitivity.ResultsWe identified 27 eligible studies with 25 estimating PPV and eight estimating sensitivity. Study settings and methods varied widely. For all-cause dementia, PPVs ranged from 33%–100%, but 16/27 were >75%. Sensitivities ranged from 21% to 86%. PPVs for Alzheimer's disease (range 57%–100%) were generally higher than those for vascular dementia (range 19%–91%).DiscussionLinkage to routine health-care data can achieve a high PPV and reasonable sensitivity in certain settings. Given the heterogeneity in accuracy estimates, cohorts should ideally conduct their own setting-specific validation.

ObjectiveIn UK Biobank (UKB), a large population-based prospective study, cases of many diseases are ascertained through linkage to routinely collected, coded national health datasets. We assessed the accuracy of these for identifying incident strokes.MethodsIn a regional UKB subpopulation (n = 17,249), we identified all participants with ≥1 code signifying a first stroke after recruitment (incident stroke-coded cases) in linked hospital admission, primary care, or death record data. Stroke physicians reviewed their full electronic patient records (EPRs) and generated reference standard diagnoses. We evaluated the number and proportion of cases that were true-positives (i.e., positive predictive value [PPV]) for all codes combined and by code source and type.ResultsOf 232 incident stroke-coded cases, 97% had EPR information available. Data sources were 30% hospital admission only, 39% primary care only, 28% hospital and primary care, and 3% death records only. While 42% of cases were coded as unspecified stroke type, review of EPRs enabled a pathologic type to be assigned in >99%. PPVs (95% confidence intervals) were 79% (73%–84%) for any stroke (89% for hospital admission codes, 80% for primary care codes) and 83% (74%–90%) for ischemic stroke. PPVs for small numbers of death record and hemorrhagic stroke codes were low but imprecise.ConclusionsStroke and ischemic stroke cases in UKB can be ascertained through linked health datasets with sufficient accuracy for many research studies. Further work is needed to understand the accuracy of death record and hemorrhagic stroke codes and to develop scalable approaches for better identifying stroke types.

H ealth care-associated infections represent substantial burden on health care systems in highly developed countries, including Canada. 1-3 In 2002, health careassociated infection developed in an estimated 5% of patients admitted to hospital in the United States, resulting in 1.7 million infections and 98 000 deaths. 1 A study using 2015 data from the European Antimicrobial Resistance Surveillance Network (EARS-Net) from 30 countries estimated 426 277 infections with antibioticresistant bacteria were associated with health care, with an attributable mortality of 33 110. 2 A point-prevalence study conducted in 2015 estimated that there were 687 200 health careassociated infections in US hospitals. 3 Timely data on the occurrence of health care-associated infections and antimicrobial resistant organisms in Canadian hospitals are essential to the response to an evolving epidemiologic situation. Internationally, prevalence surveys are widely used to estimate the incidence and burden of disease from these infections. 3-10 The Canadian Nosocomial Infection Surveillance Program RESEARCH HEALTH SERVICES

OBJECTIVE To evaluate hospital administrative data to identify potential surgical site infections (SSIs) following primary elective total hip or knee arthroplasty. DESIGN Retrospective cohort study. SETTING All acute care facilities in Alberta, Canada. METHODS Diagnosis and procedure codes for 6 months following total hip or knee arthroplasty were used to identify potential SSI cases. Medical charts of patients with potential SSIs were reviewed by an infection control professional at the acute care facility where the patient was identified with a diagnosis or procedure code. For SSI decision, infection control professionals used the National Healthcare Safety Network SSI definition. The performance of traditional surveillance methods and administrative data-triggered medical chart review was assessed. RESULTS Of the 162 patients identified by diagnosis or procedure code, 46 (28%) were confirmed as an SSI by an infection control professional. More SSIs were identified following total hip vs total knee arthroplasty (42% vs16%). Of 46 confirmed SSI cases, 20 (43%) were identified at an acute care facility different than their procedure facility. Administrative data-triggered medical chart review with infection control professional confirmation resulted in a 1.1- to 1.7-fold increase in SSI rate compared with traditional surveillance. SSIs identified by administrative data resulted in sensitivity of 90% and specificity of 99%. CONCLUSION Medical chart review for cases identified through administrative data is an efficient supplemental SSI surveillance strategy. It improves case-finding by increasing SSI identification and making identification consistent across facilities, and in a provincial surveillance network it identifies SSIs presenting at nonprocedure facilities. Infect Control Hosp Epidemiol 2016;37:699-703.

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The Canadian Nosocomial Infection Surveillance Program has been performing surveillance of antibiotic-resistant organisms in Canada since 1994. The authors of this study compared two point-prevalence surveys of antimicrobial use that were conducted in hospitals that were participating in the program in 2002 and 2009. The authors compared the use of antimicrobials between these two surveys. The changes in antimicrobial use over time are presented, in addition to potential reasons for and consequences of these changes.

Nodes and corridors of activity in Calgary were detected in correlation studies of the 2001 Census variables used. The core (high prevalence) areas should be the areas targeted for sexually transmitted infection prevention and control. This can be done at the community level through measures such as more sexually transmitted infection clinics operating with longer hours in areas identified from this mapping.