Mouse Adaptation of Human Inflammatory Bowel Diseases Microbiota Enhances Colonization Efficiency and Alters Microbiome Aggressiveness Depending on Recipient Colonic Inflammatory Environment.

Understanding the cause vs consequence relationship of gut inflammation and microbial dysbiosis in inflammatory bowel diseases (IBD) requires a reproducible mouse model of human-microbiota-driven experimental colitis. Our study demonstrated that human fecal microbiota transplant (FMT) transfer efficiency is an underappreciated source of experimental variability in human microbiota associated (HMA) mice. Pooled human IBD patient fecal microbiota engrafted germ-free (GF) mice with low amplicon sequence variant (ASV)-level transfer efficiency, resulting in high recipient-to-recipient variation of microbiota composition and colitis severity in HMA Il-10-/- mice. In contrast, mouse-to-mouse transfer of mouse-adapted human IBD patient microbiota transferred with high efficiency and low compositional variability resulting in highly consistent and reproducible colitis phenotypes in recipient Il-10-/- mice. Human-to-mouse FMT caused a population bottleneck with reassembly of microbiota composition that was host inflammatory environment specific. Mouse-adaptation in the inflamed Il-10-/- host reassembled a more aggressive microbiota that induced more severe colitis in serial transplant to Il-10-/- mice than the distinct microbiota reassembled in non-inflamed WT hosts. Our findings support a model of IBD pathogenesis in which host inflammation promotes aggressive resident bacteria, which further drives a feed-forward process of dysbiosis exacerbated gut inflammation. This model implies that effective management of IBD requires treating both the dysregulated host immune response and aggressive inflammation-driven microbiota. We propose that our mouse-adapted human microbiota model is an optimized, reproducible, and rigorous system to study human microbiome-driven disease phenotypes, which may be generalized to mouse models of other human microbiota-modulated diseases, including metabolic syndrome/obesity, diabetes, autoimmune diseases, and cancer.

Estimates of interaural attenuation in children and the implications for masking in clinical audiometry.

OBJECTIVE: The aim of this study was to provide estimates of interaural attenuation (IA) in children, under clinical test conditions for supra-aural and insert earphones. DESIGN: This was a retrospective review of clinical audiograms for children aged 8 months to 16 years. STUDY SAMPLE: There were between 2 and 21 subjects, depending on the transducer and stimulus frequency. RESULTS: For insert earphones, younger age groups had smaller IA estimates (mean 60 dB, minimum 40 dB) compared to older children (mean 78 dB, minimum 60 dB). The insert IA estimates for older children were similar to published adult IA data. There was no significant effect of age on the children's estimated IA for supra-aural earphones. CONCLUSIONS: Under the clinical conditions of this study, cross-hearing should be considered when the difference between the better ear and poorer ear not-masked air conduction thresholds are ≥ 40 dB for inserts with foam tips in children under 13 years. Smaller estimates of IA in younger children compared to older children may be due to difficulties achieving deep insertion of foam tips in smaller ears and less cooperative subjects under these conditions. Limitations of the study, including lack of bone conduction threshold data, are discussed.

Identifying cases of spinal cord injury or disease in a primary care electronic medical record database.

OBJECTIVE: To identify cases of spinal cord injury or disease (SCI/D) in an Ontario database of primary care electronic medical records (EMR). DESIGN: A reference standard of cases of chronic SCI/D was established via manual review of EMRs; this reference standard was used to evaluate potential case identification algorithms for use in the same database. SETTING: Electronic Medical Records Primary Care (EMRPC) Database, Ontario, Canada. PARTICIPANTS: A sample of 48,000 adult patients was randomly selected from 213,887 eligible patients in the EMRPC database. INTERVENTIONS: N/A. MAIN OUTCOME MEASURE(S): Candidate algorithms were evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F-score. RESULTS: 126 cases of chronic SCI/D were identified, forming the reference standard. Of these, 57 were cases of traumatic spinal cord injury (TSCI), and 67 were cases of non-traumatic spinal cord injury (NTSCI). The optimal case identification algorithm used free-text keyword searches and a physician billing code, and had 70.6% sensitivity (61.9-78.4), 98.5% specificity (97.3-99.3), 89.9% PPV (82.2-95.0), 94.7% NPV (92.8-96.3), and an F-score of 79.1. CONCLUSIONS: Identifying cases of chronic SCI/D from a database of primary care EMRs using free-text entries is feasible, relying on a comprehensive case definition. Identifying a cohort of patients with SCI/D will allow for future study of the epidemiology and health service utilization of these patients.

HashSeq: a Simple, Scalable, and Conservative De Novo Variant Caller for 16S rRNA Gene Data Sets.

16S rRNA gene sequencing is a common and cost-effective technique for characterization of microbial communities. Recent bioinformatics methods enable high-resolution detection of sequence variants of only one nucleotide difference. In this study, we utilized a very fast HashMap-based approach to detect sequence variants in six publicly available 16S rRNA gene data sets. We then use the normal distribution combined with locally estimated scatterplot smoothing (LOESS) regression to estimate background error rates as a function of sequencing depth for individual clusters of sequences. This method is computationally efficient and produces inference that yields sets of variants that are conservative and well supported by reference databases. We argue that this approach to inference is fast, simple, and scalable to large data sets and provides a high-resolution set of sequence variants which are less likely to be the result of sequencing error. IMPORTANCE Recent bioinformatics development has enabled the detection of sequence variants with a high resolution of only one single-nucleotide difference in 16S rRNA gene sequence data. Despite this progress, there are several limitations that can be associated with variant calling pipelines, such as producing a large number of low-abundance sequence variants which need to be filtered out with arbitrary thresholds in downstream analyses or having a slow runtime. In this report, we introduce a fast and scalable algorithm which infers sequence variants based on the estimation of a normally distributed background error as a function of sequencing depth. Our pipeline has attractive performance characteristics, can be used independently or in parallel with other variant callers, and provides explicit P values for each variant evaluating the hypothesis that a variant is caused by sequencing error.

Health Care Utilization for Musculoskeletal Issues During the Prediagnosis Period in Psoriatic Arthritis: A Population-Based Study.

OBJECTIVE: Information about the prediagnosis period in psoriatic arthritis (PsA) is limited. The present study was undertaken to compare health care utilization related to musculoskeletal issues during a 5-year period prior to the diagnosis of PsA versus that of subjects with no prior inflammatory arthritis within a primary care setting. METHODS: We conducted a population-based, matched cohort study using electronic medical records and administrative data in Ontario, Canada. Age- and sex-matched cohorts of PsA patients and comparators from the same family physicians were assembled. Comparators were not allowed to have prior spondyloarthritis, ankylosing spondylitis, or rheumatoid arthritis billing code diagnoses. The study outcomes included health care utilization and costs related to nonspecific musculoskeletal issues during a 5-year period prior to the index date. RESULTS: We studied 462 PsA patients and 2,310 matched comparators. The odds ratio (OR) related to visiting a primary care physician for nonspecific musculoskeletal issues in patients with PsA was 2.14 (95% confidence interval 1.73-2.64) in the year immediately preceding the index date and was similarly elevated up to 5 years prior. The OR related to using other musculoskeletal-related health care services, including musculoskeletal specialists visits, joint injections, joint imaging, and emergency department visits, was higher in PsA as early as 5 years preceding the index date. Total and musculoskeletal-related health care costs prior to the index date were higher for patients with PsA versus comparators. CONCLUSION: A prodromal PsA phase characterized by nonspecific musculoskeletal symptoms may exist. Further study is needed to determine if this represents a window for earlier diagnosis of PsA.

Validation of a type 1 diabetes algorithm using electronic medical records and administrative healthcare data to study the population incidence and prevalence of type 1 diabetes in Ontario, Canada.

INTRODUCTION: We aimed to develop algorithms distinguishing type 1 diabetes (T1D) from type 2 diabetes in adults ≥18 years old using primary care electronic medical record (EMRPC) and administrative healthcare data from Ontario, Canada, and to estimate T1D prevalence and incidence. RESEARCH DESIGN AND METHODS: The reference population was a random sample of patients with diabetes in EMRPC whose charts were manually abstracted (n=5402). Algorithms were developed using classification trees, random forests, and rule-based methods, using electronic medical record (EMR) data, administrative data, or both. Algorithm performance was assessed in EMRPC. Administrative data algorithms were additionally evaluated using a diabetes clinic registry with endocrinologist-assigned diabetes type (n=29 371). Three algorithms were applied to the Ontario population to evaluate the minimum, moderate and maximum estimates of T1D prevalence and incidence rates between 2010 and 2017, and trends were analyzed using negative binomial regressions. RESULTS: Of 5402 individuals with diabetes in EMRPC, 195 had T1D. Sensitivity, specificity, positive predictive value and negative predictive value for the best performing algorithms were 80.6% (75.9-87.2), 99.8% (99.7-100), 94.9% (92.3-98.7), and 99.3% (99.1-99.5) for EMR, 51.3% (44.0-58.5), 99.5% (99.3-99.7), 79.4% (71.2-86.1), and 98.2% (97.8-98.5) for administrative data, and 87.2% (81.7-91.5), 99.9% (99.7-100), 96.6% (92.7-98.7) and 99.5% (99.3-99.7) for combined EMR and administrative data. Administrative data algorithms had similar sensitivity and specificity in the diabetes clinic registry. Of 11 499 711 adults in Ontario in 2017, there were 24 789 (0.22%, minimum estimate) to 102 140 (0.89%, maximum estimate) with T1D. Between 2010 and 2017, the age-standardized and sex-standardized prevalence rates per 1000 person-years increased (minimum estimate 1.7 to 2.56, maximum estimate 7.48 to 9.86, p<0.0001). In contrast, incidence rates decreased (minimum estimate 0.1 to 0.04, maximum estimate 0.47 to 0.09, p<0.0001). CONCLUSIONS: Primary care EMR and administrative data algorithms performed well in identifying T1D and demonstrated increasing T1D prevalence in Ontario. These algorithms may permit the development of large, population-based cohort studies of T1D.

Assessing the completeness of infant and childhood immunizations within a provincial registry populated by parental reporting: A study using linked databases in Ontario, Canada.

INTRODUCTION: In Ontario, Canada, parents have the responsibility to report their child's routine infant and childhood vaccines to the provincial immunization registry (the Digital Health Immunization Repository; DHIR) without healthcare provider validation. Despite its use in routine immunization coverage monitoring, no study has previously examined the completeness of immunization data within the DHIR. METHODS: We assessed the completeness of DHIR immunizations, as compared to immunizations within the Electronic Medical Records-Primary Care (EMRPC) database, also known as EMRALD, a network of family physician electronic medical records (EMRs). We linked client records from the DHIR and EMRPC to a centralized population file. To create the study cohort, we examined children born during 2005-2008 and further defined the cohort based on those rostered to an EMRPC physician, visit criteria to ensure ongoing care by an EMRPC provider, and school attendance in Ontario at age 7. We calculated up-to-date (UTD) immunization coverage at age 7 for individual vaccines and overall using data from the DHIR and EMRPC separately, and compared the estimates. RESULTS: The analytic cohort to assess DHIR data completeness included 2,657 children. Overall UTD coverage (all vaccines assessed) was 82.0% in the DHIR and 67.6% in EMRPC. UTD coverage was higher in the DHIR for all vaccines assessed individually, with the exception of meningococcal C conjugate vaccine (difference = 0.3%). After excluding two EMRPC sites with irregularities in immunization data, the difference in overall UTD coverage between systems decreased from 14.4% to 6.6% INTERPRETATION: These results validate the use of DHIR for coverage assessment but also suggest that bidirectional exchange of immunization information has the potential to increase immunization data completeness in both systems.

Identifying and Characterizing Psoriasis and Psoriatic Arthritis Patients in Ontario Administrative Data: A Population-based Study From 1991 to 2015.

OBJECTIVES: We assessed the accuracy of case definition algorithms for psoriasis and psoriatic arthritis (PsA) in health administrative data and used primary care electronic medical records (EMR) to describe disease and treatment characteristics of these patients. METHODS: We randomly sampled 30,424 adult Ontario residents from the Electronic Medical Record Primary Care database and identified 2215 patients with any possible psoriatic disease-related terms in their EMR. The relevant patient records were chart abstracted to confirm diagnoses of psoriasis or PsA. This validation set was then linked to health administrative data to assess the performance of different algorithms for physician billing diagnosis codes, hospitalization diagnosis codes, and medications for psoriatic disease. We report the performance of selected case definition algorithms and describe the disease characteristics of the validation set. RESULTS: Our reference standard identified 1028 patients with psoriasis and 77 patients with PsA, for an overall prevalence of 3.4% for psoriasis and 0.3% for PsA. Most patients with PsA (66%) had a rheumatology-confirmed diagnosis, while only 30% of the patients with psoriasis had dermatology-confirmed diagnosis. The use of systemic medications was much more common with PsA than with psoriasis. All algorithms had excellent specificity (97-100%). The sensitivity and positive predictive value were moderate and varied between different algorithms (34-72%). CONCLUSION: The accuracy of case definition algorithms for psoriasis and PsA varies widely. However, selected algorithms produced population prevalence estimates that were within the expected ranges, suggesting that they may be useful for future research purposes.

Infant feeding practices within a large electronic medical record database.

BACKGROUND: The emerging adoption of the electronic medical record (EMR) in primary care enables clinicians and researchers to efficiently examine epidemiological trends in child health, including infant feeding practices. METHODS: We completed a population-based retrospective cohort study of 8815 singleton infants born at term in Ontario, Canada, April 2002 to March 2013. Newborn records were linked to the Electronic Medical Record Administrative data Linked Database (EMRALD™), which uses patient-level information from participating family practice EMRs across Ontario. We assessed exclusive breastfeeding patterns using an automated electronic search algorithm, with manual review of EMRs when the latter was not possible. We examined the rate of breastfeeding at visits corresponding to 2, 4 and 6 months of age, as well as sociodemographic factors associated with exclusive breastfeeding. RESULTS: Of the 8815 newborns, 1044 (11.8%) lacked breastfeeding information in their EMR. Rates of exclusive breastfeeding were 39.5% at 2 months, 32.4% at 4 months and 25.1% at 6 months. At age 6 months, exclusive breastfeeding rates were highest among mothers aged ≥40 vs. < 20 years (rate ratio [RR] 2.45, 95% confidence interval [CI] 1.62-3.68), urban vs. rural residence (RR 1.35, 95% CI 1.22-1.50), and highest vs. lowest income quintile (RR 1.18, 95% CI 1.02-1.36). Overall, immigrants had similar rates of exclusive breastfeeding as non-immigrants; yet, by age 6 months, among those residing in the lowest income quintile, immigrants were more likely to exclusively breastfeed than their non-immigrant counterparts (RR 1.43, 95% CI 1.12-1.83). CONCLUSIONS: We efficiently determined rates and factors associated with exclusive breastfeeding using data from a large EMR database.

Improving Care for Patients With or at Risk for Chronic Kidney Disease Using Electronic Medical Record Interventions: A Pragmatic Cluster-Randomized Trial Protocol.

BACKGROUND: Many patients with or at risk for chronic kidney disease (CKD) in the primary care setting are not receiving recommended care. OBJECTIVE: The objective of this study is to determine whether a multifaceted, low-cost intervention compared with usual care improves the care of patients with or at risk for CKD in the primary care setting. DESIGN: A pragmatic cluster-randomized trial, with an embedded qualitative process evaluation, will be conducted. SETTING: The study population comes from the Electronic Medical Record Administrative data Linked Database®, which includes clinical data for more than 140 000 rostered adults cared for by 194 family physicians in 34 clinics across Ontario, Canada. The 34 primary care clinics will be randomized to the intervention or control group. INTERVENTION: The intervention group will receive resources from the "CKD toolkit" to help improve care including practice audit and feedback, printed educational materials for physicians and patients, electronic decision support and reminders, and implementation support. MEASUREMENTS: Patients with or at risk for CKD within participating clinics will be identified using laboratory data in the electronic medical records. Outcomes will be assessed after dissemination of the CKD tools and after 2 rounds of feedback on performance on quality indicators have been sent to the physicians using information from the electronic medical records. The primary outcome is the proportion of patients aged 50 to 80 years with nondialysis-dependent CKD who are on a statin. Secondary outcomes include process of care measures such as screening tests, CKD recognition, monitoring tests, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker prescriptions, blood pressure targets met, and nephrologist referral. Hierarchical analytic modeling will be performed to account for clustering. Semistructured interviews will be conducted with a random purposeful sample of physicians in the intervention group to understand why the intervention achieved the observed effects. CONCLUSIONS: If our intervention improves care, then the CKD toolkit can be adapted and scaled for use in other primary care clinics which use electronic medical records. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02274298.

CONTEXTE: On observe que de nombreux patients atteints ou à risque de développer de l'insuffisance rénale chronique (IRC) ne reçoivent pas les soins recommandés dans le cadre des soins de première ligne. OBJECTIF: L'étude vise à déterminer si le recours à une intervention multidimensionnelle et moins coûteuse par rapport aux soins habituellement dispensés améliore les soins prodigués aux patients atteints ou susceptibles de développer de l'IRC dans le cadre des soins primaires. MODÈLE D'ÉTUDE: Il s'agit d'un essai pragmatique randomisé par grappes, auquel on a incorporé une évaluation qualitative. CADRE DE L'ÉTUDE: La population étudiée provient de la base de données EMRALD® (Electronic Medical Record Administrative data Linked Database), qui inclut les données cliniques de plus de 140 000 adultes inscrits soignés par 194 médecins de famille répartis dans 34 cliniques partout en Ontario. Les 34 cliniques de soins de santé de première ligne seront randomisées aléatoirement dans le groupe contrôle ou le groupe d'intervention. GROUPE D'INTERVENTION: Les participants du groupe d'intervention recevront des ressources provenant d'une « boîte d'outils IRC ¼ visant à améliorer les soins. Ce guide comprendra notamment un audit de la pratique et de la rétroaction, du matériel didactique imprimé destiné aux médecins et aux patients, des outils électroniques d'aide à la décision, des rappels par voie électronique ainsi que du soutien à la mise en œuvre. MESURES: Les patients atteints ou à risque de développer de l'IRC au sein des cliniques participantes seront sélectionnés à l'aide des données de laboratoire inscrites dans les dossiers médicaux électroniques. Les résultats seront évalués après la distribution des « boîtes d'outils IRC ¼ et deux rondes de rétroaction sur le rendement des indicateurs de qualité qui auront été envoyés aux médecins à l'aide des informations contenues dans les dossiers médicaux électroniques. Le résultat principal attendu sera une différence entre les deux groupes dans la proportion de patients âgés de 50 à 80 ans atteints d'IRC, non dépendants de la dialyse, et sous traitement par une statine. Les résultats secondaires comprendront les processus de mesure des soins tels que les tests de dépistage, la constatation de l'IRC, les tests de contrôle, une ordonnance d'un inhibiteur de l'enzyme de conversion de l'angiotensine ou d'un antagoniste du récepteur de l'angiotensine, la rencontre d'une valeur cible de tension artérielle, et le référencement pour un suivi par un néphrologue. La modélisation analytique hiérarchique sera effectuée en prenant compte de la randomisation. Des entretiens semi-directifs seront menés auprès d'un échantillon aléatoire ciblé de médecins du groupe d'intervention afin de comprendre pourquoi l'intervention a permis d'atteindre les effets observés. CONCLUSIONS: Si notre modèle d'intervention parvient à améliorer les soins, la « boîte d'outils IRC ¼ pourra être adaptée et échelonnée en vue d'une utilisation dans d'autres cliniques de soins de première ligne qui utilisent des dossiers médicaux électroniques. ENREGISTREMENT DES ESSAIS: Identifiant ClinicalTrials.gov: NCT02274298.

Quality indicators for the detection and management of chronic kidney disease in primary care in Canada derived from a modified Delphi panel approach.

BACKGROUND: The detection and management of chronic kidney disease lies within primary care; however, performance measures applicable in the Canadian context are lacking. We sought to develop a set of primary care quality indicators for chronic kidney disease in the Canadian setting and to assess the current state of the disease's detection and management in primary care. METHODS: We used a modified Delphi panel approach, involving 20 panel members from across Canada (10 family physicians, 7 nephrologists, 1 patient, 1 primary care nurse and 1 pharmacist). Indicators identified from peer-reviewed and grey literature sources were subjected to 3 rounds of voting to develop a set of quality indicators for the detection and management of chronic kidney disease in the primary care setting. The final indicators were applied to primary care electronic medical records in the Electronic Medical Record Administrative data Linked Database (EMRALD) to assess the current state of primary care detection and management of chronic kidney disease in Ontario. RESULTS: Seventeen indicators made up the final list, with 1 under the category Prevalence, Incidence and Mortality; 4 under Screening, Diagnosis and Risk Factors; 11 under Management; and 1 under Referral to a Specialist. In a sample of 139 993 adult patients not on dialysis, 6848 (4.9%) had stage 3 or higher chronic kidney disease, with the average age of patients being 76.1 years (standard deviation [SD] 11.0); 62.9% of patients were female. Diagnosis and screening for chronic kidney disease were poorly performed. Only 27.1% of patients with stage 3 or higher disease had their diagnosis documented in their cumulative patient profile. Albumin-creatinine ratio testing was only performed for 16.3% of patients with a low estimated glomerular filtration rate (eGFR) and for 28.5% of patients with risk factors for chronic kidney disease. Family physicians performed relatively better with the management of chronic kidney disease, with 90.4% of patients with stage 3 or higher disease having an eGFR performed in the previous 18 months and 83.1% having a blood pressure recorded in the previous 9 months. INTERPRETATION: We propose a set of measurable indicators to evaluate the quality of the management of chronic kidney disease in primary care. These indicators may be used to identify opportunities to improve current practice in Canada.

Primary Care Screening and Comorbidity Management in Rheumatoid Arthritis in Ontario, Canada.

OBJECTIVE: Quality measurement for rheumatoid arthritis (RA) patients has largely focused on care provided by rheumatologists. Our aim was to develop and assess quality measures related to the screening and management of comorbidity in RA patients in primary care. METHODS: We used the primary care Electronic Medical Record Administrative data Linked Database in Ontario, Canada. We harmonized Canadian general population and RA clinical recommendations to develop and assess screening, process, and outcome measures. For each RA patient, 10 non-RA patients were matched by age and sex. Stratified analyses were performed, comparing patients with RA to those without RA, to assess the performance of quality measures. RESULTS: We compared 1,405 RA patients to 14,050 matched non-RA patients (72.8% female; mean age 62.5 years). Compared to non-RA patients, RA patients more frequently had influenza (44.9% versus 40.0%) and pneumococcal (40.4% versus 34.1%) vaccinations and bone mineral density testing (67.4% versus 58.1%). Herpes zoster vaccinations were less frequent among RA patients (13.8% versus 19.5%), as was screening for cervical cancer (58.6% versus 64.0%). No significant differences were observed between RA and non-RA patients in screenings for breast (70.7% versus 73.8%) or colorectal (31.7% versus 34.5%) cancers. Only a quarter of RA patients had a comprehensive cardiovascular risk assessment. No definitive differences were detected in the management of patients who had co-occurring cardiovascular disease or diabetes mellitus. CONCLUSION: For both RA and non-RA patients, compliance with Canadian recommendations for preventive medical services and screening for comorbid conditions in primary care was less than optimal. This indicates key targets for improvement.

Improving stroke prevention therapy for patients with atrial fibrillation in primary care: protocol for a pragmatic, cluster-randomized trial.

BACKGROUND: The prevalence of atrial fibrillation (AF) is growing as the population ages, and at least 15% of ischemic strokes are attributed to AF. However, many high-risk AF patients are not offered guideline-recommended stroke prevention therapy due to a variety of system, provider, and patient-level barriers. METHODS: We will conduct a pragmatic, cluster-randomized controlled trial randomizing primary care clinics to test a "toolkit" of quality improvement interventions in primary care. In keeping with the recommendations of the chronic care model to simultaneously activate patients and facilitate proactive care by providers, the toolkit includes provider-focused strategies (education, audit and feedback, electronic decision support, and reminders) plus patient-directed strategies (educational letters and reminders). The trial will include two feedback cycles at baseline and approximately 6 months and a final data collection at approximately 12 months. The study will be powered to show a difference of 10% in the primary outcome of proportion of patients receiving guideline-recommended stroke prevention therapy. Analysis will follow the intention-to-treat principle and will be blind to treatment allocation. Unit of analysis will be the patient; models will use generalized estimating equations to account for clustering at the clinical level. DISCUSSION: Stroke prevention therapy using anticoagulation in patients with AF is known to reduce strokes by two thirds or more in clinical trials, but most studies indicate under-use of this treatment in real-world practice. If the toolkit successfully improves care for patients with AF, stakeholders will be engaged to facilitate broader application to maximize the potential to improve patient outcomes. The intervention toolkit tested in this project could also provide a model to improve quality of care for other chronic cardiovascular conditions managed in primary care. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT01927445 ). Registered August 14, 2014 at https://clinicaltrials.gov/ .

A nurse-led model of chronic disease management in general practice: Patients' perspectives.

BACKGROUND: Evidence suggests that current models of chronic disease management within general practice are not effective in meeting the needs of the community. OBJECTIVE: The objective of this article is to examine patients' perceptions of a nurse-led collaborative model of care trialled in three general practices in Australia. METHODS: This article reports on the second phase of a mixed-methods study in which semi-structured interviews with purposively selected patients were conducted to elicit information about their perceptions of nurse-led care. RESULTS: Three themes emerged from the data - time, ambiance and dimensions of the nurse role. DISCUSSION: The results suggest that general practice nurses had a positive impact on patients' ability to manage their chronic disease. This infers that there is scope for general practice nurses to expand their role in chronic disease management to assist patients to better self-manage their chronic diseases.

Parkinson's audit is a call to action for nurses.

There are 127,000 people living with Parkinson's in the UK. The condition is particularly prevalent among older people, and the ageing UK population means this number is expected to rise.

Identification of Physician-Diagnosed Alzheimer's Disease and Related Dementias in Population-Based Administrative Data: A Validation Study Using Family Physicians' Electronic Medical Records.

BACKGROUND: Population-based surveillance of Alzheimer's and related dementias (AD-RD) incidence and prevalence is important for chronic disease management and health system capacity planning. Algorithms based on health administrative data have been successfully developed for many chronic conditions. The increasing use of electronic medical records (EMRs) by family physicians (FPs) provides a novel reference standard by which to evaluate these algorithms as FPs are the first point of contact and providers of ongoing medical care for persons with AD-RD. OBJECTIVE: We used FP EMR data as the reference standard to evaluate the accuracy of population-based health administrative data in identifying older adults with AD-RD over time. METHODS: This retrospective chart abstraction study used a random sample of EMRs for 3,404 adults over 65 years of age from 83 community-based FPs in Ontario, Canada. AD-RD patients identified in the EMR were used as the reference standard against which algorithms identifying cases of AD-RD in administrative databases were compared. RESULTS: The highest performing algorithm was "one hospitalization code OR (three physician claims codes at least 30 days apart in a two year period) OR a prescription filled for an AD-RD specific medication" with sensitivity 79.3% (confidence interval (CI) 72.9-85.8%), specificity 99.1% (CI 98.8-99.4%), positive predictive value 80.4% (CI 74.0-86.8%), and negative predictive value 99.0% (CI 98.7-99.4%). This resulted in an age- and sex-adjusted incidence of 18.1 per 1,000 persons and adjusted prevalence of 72.0 per 1,000 persons in 2010/11. CONCLUSION: Algorithms developed from health administrative data are sensitive and specific for identifying older adults with AD-RD.

Are family physicians comprehensively using electronic medical records such that the data can be used for secondary purposes? A Canadian perspective.

BACKGROUND: With the introduction and implementation of a variety of government programs and policies to encourage adoption of electronic medical records (EMRs), EMRs are being increasingly adopted in North America. We sought to evaluate the completeness of a variety of EMR fields to determine if family physicians were comprehensively using their EMRs and the suitability of use of the data for secondary purposes in Ontario, Canada. METHODS: We examined EMR data from a convenience sample of family physicians distributed throughout Ontario within the Electronic Medical Record Administrative data Linked Database (EMRALD) as extracted in the summer of 2012. We identified all physicians with at least one year of EMR use. Measures were developed and rates of physician documentation of clinical encounters, electronic prescriptions, laboratory tests, blood pressure and weight, referrals, consultation letters, and all fields in the cumulative patient profile were calculated as a function of physician and patient time since starting on the EMR. RESULTS: Of the 167 physicians with at least one year of EMR use, we identified 186,237 patients. Overall, the fields with the highest level of completeness were for visit documentations and prescriptions (>70%). Improvements were observed with increasing trends of completeness overtime for almost all EMR fields according to increasing physician time on EMR. Assessment of the influence of patient time on EMR demonstrated an increasing likelihood of the population of EMR fields overtime, with the largest improvements occurring between the first and second years. CONCLUSIONS: All of the data fields examined appear to be reasonably complete within the first year of adoption with the biggest increase occurring the first to second year. Using all of the basic functions of the EMR appears to be occurring in the current environment of EMR adoption in Ontario. Thus the data appears to be suitable for secondary use.

Canadian administrative health data can identify patients with myasthenia gravis.

INTRODUCTION: Incidence and prevalence estimates for myasthenia gravis (MG) have varied widely, and the ability of administrative health data (AHD) records to accurately identify cases of MG is yet to be ascertained. The goal of the current study was to validate an algorithm to identify patients with MG in Ontario, Canada using AHD - thereby enabling future disease surveillance. METHODS: A reference standard population was established using automated key word searching within EMRALD (Electronic Medical Record Administrative data Linked Database) and chart review of potential cases. AHD algorithms were generated and tested against the reference standard. The data was used to calculate MG prevalence rates. RESULTS: There were 123,997 eligible adult patients, and 49 patients had definite MG (forming the reference standard). An algorithm requiring: (1 hospital discharge abstract with MG listed as a reason for hospitalization or a comorbid condition), or (5 outpatient MG visits and 1 relevant diagnostic test, within 1 year), or (3 pyridostigmine prescriptions, within 1 year) identified MG with sensitivity = 81.6%, specificity = 100%, positive predictive value = 80.0% and negative predictive value = 100%. The population prevalence within our cohort was 0.04%. CONCLUSIONS: This novel validation method demonstrates the feasibility of using administrative health data to identify patients with myasthenia gravis among the Ontario population.

Development and validation of an administrative data algorithm to estimate the disease burden and epidemiology of multiple sclerosis in Ontario, Canada.

BACKGROUND: Few studies have assessed the accuracy of administrative data for identifying multiple sclerosis (MS) patients. OBJECTIVES: To validate administrative data algorithms for MS, and describe the burden and epidemiology over time in Ontario, Canada. METHODS: We employed a validated search strategy to identify all MS patients within electronic medical records, to identify patients with and without MS (reference standard). We then developed and validated different combinations of administrative data for algorithms. The most accurate algorithm was used to estimate the burden and epidemiology of MS over time. RESULTS: The accuracy of the algorithm of one hospitalisation or five physician billings over 2 years provided both high sensitivity (84%) and positive predictive value (86%). Application of this algorithm to provincial data demonstrated an increasing cumulative burden of MS, from 13,326 patients (0.14%) in 2000 to 24,647 patients in 2010 (0.22%). Age-and-sex standardised prevalence increased from 133.9 to 207.3 MS patients per 100,000 persons in the population, from 2000 - 2010. During this same period, age-and-sex-standardised incidence varied from 17.9 to 19.4 patients per 100,000 persons. CONCLUSIONS: MS patients can be accurately identified from administrative data. Our findings illustrated a rising prevalence of MS over time. MS incidence rates also appear to be rising since 2009.