Identifying personalized barriers for hypertension self-management from TASKS framework.

OBJECTIVE: Effective management of hypertension requires not only medical intervention but also significant patient self-management. The challenge, however, lies in the diversity of patients' personal barriers to managing their condition. The objective of this research is to identify and categorize personalized barriers to hypertension self-management using the TASKS framework (Task, Affect, Skills, Knowledge, Stress). This study aims to enhance patient-centered strategies by aligning support with each patient's specific needs, recognizing the diversity in their unique circumstances, beliefs, emotional states, knowledge levels, and access to resources. This research is based on observations from a single study focused on eight patients, which may have been a part of a larger project. RESULTS: The analysis of transcripts from eight patients and the Global Hypertension Practice Guidelines revealed 69 personalized barriers. These barriers were distributed as follows: emotional barriers (49%), knowledge barriers (24%), logical barriers (17%), and resource barriers (10%). The findings highlight the significant impact of emotional and knowledge-related challenges on hypertension self-management, including difficulties in home blood pressure monitoring and the use of monitoring tools. This study emphasizes the need for tailored interventions to address these prevalent barriers and improve hypertension management outcomes.

Development of Data Quality Indicators for Improving Hospital International Classification of Diseases-Coded Health Data Quality Globally.

BACKGROUND: Hospital inpatient data, coded using the International Classification of Diseases (ICD), is widely used to monitor diseases, allocate resources and funding, and evaluate patient outcomes. As such, hospital data quality should be measured before use; however, currently, there is no standard and international approach to assess ICD-coded data quality. OBJECTIVE: To develop a standardized method for assessing hospital ICD-coded data quality that could be applied across countries: Data quality indicators (DQIs). RESEARCH DESIGN: To identify a set of candidate DQIs, we performed an environmental scan, reviewing gray and academic literature on data quality frameworks and existing methods to assess data quality. Indicators from the literature were then appraised and selected through a 3-round Delphi process. The first round involved face-to-face group and individual meetings for idea generation, while the second and third rounds were conducted remotely to collect online ratings. Final DQIs were selected based on the panelists' quantitative and qualitative feedback. SUBJECTS: Participants included international experts with expertise in administrative health data, data quality, and ICD coding. RESULTS: The resulting 24 DQIs encompass 5 dimensions of data quality: relevance, accuracy and reliability; comparability and coherence; timeliness; and Accessibility and clarity. These will help stakeholders (eg, World Health Organization) to assess hospital data quality using the same standard across countries and highlight areas in need of improvement. CONCLUSIONS: This novel area of research will facilitate international comparisons of ICD-coded data quality and be valuable to future studies and initiatives aimed at improving hospital administrative data quality.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Evaluating the coding accuracy of type 2 diabetes mellitus among patients with non-alcoholic fatty liver disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) describes a spectrum of chronic fattening of liver that can lead to fibrosis and cirrhosis. Diabetes has been identified as a major comorbidity that contributes to NAFLD progression. Health systems around the world make use of administrative data to conduct population-based prevalence studies. To that end, we sought to assess the accuracy of diabetes International Classification of Diseases (ICD) coding in administrative databases among a cohort of confirmed NAFLD patients in Calgary, Alberta, Canada. METHODS: The Calgary NAFLD Pathway Database was linked to the following databases: Physician Claims, Discharge Abstract Database, National Ambulatory Care Reporting System, Pharmaceutical Information Network database, Laboratory, and Electronic Medical Records. Hemoglobin A1c and diabetes medication details were used to classify diabetes groups into absent, prediabetes, meeting glycemic targets, and not meeting glycemic targets. The performance of ICD codes among these groups was compared to this standard. Within each group, the total numbers of true positives, false positives, false negatives, and true negatives were calculated. Descriptive statistics and bivariate analysis were conducted on identified covariates, including demographics and types of interacted physicians. RESULTS: A total of 12,012 NAFLD patients were registered through the Calgary NAFLD Pathway Database and 100% were successfully linked to the administrative databases. Overall, diabetes coding showed a sensitivity of 0.81 and a positive predictive value of 0.87. False negative rates in the absent and not meeting glycemic control groups were 4.5% and 6.4%, respectively, whereas the meeting glycemic control group had a 42.2% coding error. Visits to primary and outpatient services were associated with most encounters. CONCLUSION: Diabetes ICD coding in administrative databases can accurately detect true diabetic cases. However, patients with diabetes who meets glycemic control targets are less likely to be coded in administrative databases. A detailed understanding of the clinical context will require additional data linkage from primary care settings.

Cerebrovascular disease case identification in inpatient electronic medical record data using natural language processing.

BACKGROUND: Abstracting cerebrovascular disease (CeVD) from inpatient electronic medical records (EMRs) through natural language processing (NLP) is pivotal for automated disease surveillance and improving patient outcomes. Existing methods rely on coders' abstraction, which has time delays and under-coding issues. This study sought to develop an NLP-based method to detect CeVD using EMR clinical notes. METHODS: CeVD status was confirmed through a chart review on randomly selected hospitalized patients who were 18 years or older and discharged from 3 hospitals in Calgary, Alberta, Canada, between January 1 and June 30, 2015. These patients' chart data were linked to administrative discharge abstract database (DAD) and Sunrise™ Clinical Manager (SCM) EMR database records by Personal Health Number (a unique lifetime identifier) and admission date. We trained multiple natural language processing (NLP) predictive models by combining two clinical concept extraction methods and two supervised machine learning (ML) methods: random forest and XGBoost. Using chart review as the reference standard, we compared the model performances with those of the commonly applied International Classification of Diseases (ICD-10-CA) codes, on the metrics of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULT: Of the study sample (n = 3036), the prevalence of CeVD was 11.8% (n = 360); the median patient age was 63; and females accounted for 50.3% (n = 1528) based on chart data. Among 49 extracted clinical documents from the EMR, four document types were identified as the most influential text sources for identifying CeVD disease ("nursing transfer report," "discharge summary," "nursing notes," and "inpatient consultation."). The best performing NLP model was XGBoost, combining the Unified Medical Language System concepts extracted by cTAKES (e.g., top-ranked concepts, "Cerebrovascular accident" and "Transient ischemic attack"), and the term frequency-inverse document frequency vectorizer. Compared with ICD codes, the model achieved higher validity overall, such as sensitivity (25.0% vs 70.0%), specificity (99.3% vs 99.1%), PPV (82.6 vs. 87.8%), and NPV (90.8% vs 97.1%). CONCLUSION: The NLP algorithm developed in this study performed better than the ICD code algorithm in detecting CeVD. The NLP models could result in an automated EMR tool for identifying CeVD cases and be applied for future studies such as surveillance, and longitudinal studies.

A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population.

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta's Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.

Health data governance for research use in Alberta.

Alberta has rich clinical and health services data held under the custodianship of Alberta Health and Alberta Health Services (AHS), which is not only used for clinical and administrative purposes but also disease surveillance and epidemiological research. Alberta is the largest province in Canada with a single payer centralised health system, AHS, and a consolidated data and analytics team supporting researchers across the province. This paper describes Alberta's data custodians, data governance mechanisms, and streamlined processes followed for research data access. AHS has created a centralised data repository from multiple sources, including practitioner claims data, hospital discharge data, and medications dispensed, available for research use through the provincial Data and Research Services (DRS) team. The DRS team is integrated within AHS to support researchers across the province with their data extraction and linkage requests. Furthermore, streamlined processes have been established, including: 1) ethics approval from a research ethics board, 2) any necessary operational approvals from AHS, and 3) a tripartite legal agreement dictating terms and conditions for data use, disclosure, and retention. This allows researchers to gain timely access to data. To meet the evolving and ever-expanding big-data needs, the University of Calgary, in partnership with AHS, has built high-performance computing (HPC) infrastructure to facilitate storage and processing of large datasets. When releasing data to researchers, the analytics team ensures that Alberta's Health Information Act's guiding principles are followed. The principal investigator also ensures data retention and disposition are according to the plan specified in ethics and per the terms set out by funding agencies. Even though there are disparities and variations in the data protection laws across the different provinces in Canada, the streamlined processes for research data access in Alberta are highly efficient.

Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning.

BACKGROUND: Prognostic information for patients with hypertension is largely based on population averages. The purpose of this study was to compare the performance of four machine learning approaches for personalized prediction of incident hospitalization for cardiovascular disease among newly diagnosed hypertensive patients. METHODS: Using province-wide linked administrative health data in Alberta, we analyzed a cohort of 259,873 newly-diagnosed hypertensive patients from 2009 to 2015 who collectively had 11,863 incident hospitalizations for heart failure, myocardial infarction, and stroke. Linear multi-task logistic regression, neural multi-task logistic regression, random survival forest and Cox proportional hazard models were used to determine the number of event-free survivors at each time-point and to construct individual event-free survival probability curves. The predictive performance was evaluated by root mean squared error, mean absolute error, concordance index, and the Brier score. RESULTS: The random survival forest model has the lowest root mean squared error value at 33.94 and lowest mean absolute error value at 28.37. Machine learning methods provide similar discrimination and calibration in the personalized survival prediction of hospitalizations for cardiovascular events in patients with hypertension. Neural multi-task logistic regression model has the highest concordance index at 0.8149 and lowest Brier score at 0.0242 for the personalized survival prediction. CONCLUSIONS: This is the first personalized survival prediction for cardiovascular diseases among hypertensive patients using administrative data. The four models tested in this analysis exhibited a similar discrimination and calibration ability in predicting personalized survival prediction of hypertension patients.

Integrating Care from Home to Hospital to Home: Using Participatory Design to Develop a Provincial Transitions in Care Guideline.

Introduction: Patients worldwide experience fragmented and uncoordinated care as they transition between primary and acute care. To improve system integration and outcomes for patients, in 2017/2018 Alberta Health Services (largest health services delivery organization in Canada) called for a coordinated approach to improve transitions in care (TiC). Healthcare leadership responded by initiating the development of a province-wide guideline outlining core components of effective transitions in care. This case study highlights the extensive design process used to develop this guideline, with a focus on the participatory design (PD) approach used throughout. Methods: An iterative, mixed methods PD approach was used to engage over 750 stakeholders through the following activities to establish Guideline content: i) learning collaborative; ii) design-team; iii) targeted online surveys; iv) primary care stakeholder consultation; v) modified Delphi panel; and vi) patient advisory committee. Results: The result was Alberta's first guideline for supporting patients through TiC: "Alberta's Home to Hospital to Home Transitions Guideline". Conclusion: The extensive design process used to create the Guideline was instrumental in establishing content, encouraging system integration, and creating conditions to support provincial implementation. While intended to improve and standardize patient care in Alberta, the methods used and lessons learned throughout the development of the Guideline are applicable internationally.

Supporting wild pollinators in agricultural landscapes through targeted legume mixtures.

Insect-pollinated legumes are rich in plant-based proteins making them a vital constituent of sustainable healthy diets for people and livestock. Furthermore, they deliver or support a range of ecosystem services that underpin agricultural production and their prevalence in agricultural landscapes is likely to increase. Under typical implementation and management, the value of legumes to pollinators has, however, been questioned. Through exploring a range of legume crops, grown as monocultures and mixtures, this study aims to identify multifunctional legume cropping systems that optimise forage availability for a diversity of wild pollinators whilst delivering a wide range of agronomic and environmental benefits. This study innovatively explores legume mixtures concurrently with monocultures of the component species using replicated small-plot field trials established in two geographical locations. Observational plots assessed the richness and abundance of floral resources, and wild pollinators (i.e. bumblebees and hoverflies) throughout the peak flowering period. Densely flowering, highly profitable legumes (e.g. Trifolium incarnatum and Trifolium mixes) supported abundant and rich pollinator assemblages. The functional makeup of floral visitors was strongly influenced by flower structure and hoverflies, with their shorter proboscises, were largely constrained to legumes with shallower corolla and open weed species. Floral richness was not a key driver of pollinator assemblages; however, clear intra-specific differences were observed in flowering phenology. Combining functionally distinct legumes with respect to flower structure and phenology, will support a wider suite of pollinating insects and help stabilise the temporal availability of forage. For highly competitive legumes (e.g. Vicia faba and Vicia sativa), planting in discrete patches is recommended to reduce the risk of less competitive species failing in mixtures. Legumes can provide valuable forage for pollinators; however, they fail to meet all resource requirements. They should therefore be used in combination with agri-environmental measures targeted to promote early-season forage (e.g. hedgerows and farm woodlands), open flowers for hoverflies, saprophytic hoverfly larval resources (e.g. ditches and ponds) and nesting habitats (e.g. undisturbed field margins).

Methane-derived carbon flows into host-virus networks at different trophic levels in soil.

The concentration of atmospheric methane (CH4) continues to increase with microbial communities controlling soil-atmosphere fluxes. While there is substantial knowledge of the diversity and function of prokaryotes regulating CH4 production and consumption, their active interactions with viruses in soil have not been identified. Metagenomic sequencing of soil microbial communities enables identification of linkages between viruses and hosts. However, this does not determine if these represent current or historical interactions nor whether a virus or host are active. In this study, we identified active interactions between individual host and virus populations in situ by following the transfer of assimilated carbon. Using DNA stable-isotope probing combined with metagenomic analyses, we characterized CH4-fueled microbial networks in acidic and neutral pH soils, specifically primary and secondary utilizers, together with the recent transfer of CH4-derived carbon to viruses. A total of 63% of viral contigs from replicated soil incubations contained homologs of genes present in known methylotrophic bacteria. Genomic sequences of 13C-enriched viruses were represented in over one-third of spacers in CRISPR arrays of multiple closely related Methylocystis populations and revealed differences in their history of viral interaction. Viruses infecting nonmethanotrophic methylotrophs and heterotrophic predatory bacteria were also identified through the analysis of shared homologous genes, demonstrating that carbon is transferred to a diverse range of viruses associated with CH4-fueled microbial food networks.

Association between continuity and access in primary care: a retrospective cohort study.

BACKGROUND: Continuity of care is a tenet of primary care. Our objective was to explore the relation between a change in access to a primary care physician and continuity of care. METHODS: We conducted a retrospective cohort study among physicians in a primary care network in southwest Alberta who measured access consistently between 2009 and 2016. We used time to the third next available appointment as a measure of access to physicians. We calculated the provider and clinic continuity, discontinuity and emergency department use based on the physicians' own panels. Physicians who improved, worsened or maintained their level of access within a given year were assessed in multilevel models to determine the association with continuity of care at the physician and clinic levels and the emergency department. RESULTS: We analyzed data from 190 primary care physicians. Physicians with improved access increased provider continuity by 6.8% per year, reduced discontinuity by 2.1% per year, and decreased emergency department encounters by 78 visits per 1000 patients per year compared to physicians with stable access. Physicians with worsening access had a 6.2% decrease in provider continuity and an increased number of emergency department encounters (64 visits per 1000 panelled patients per year) compared to physicians with stable access. INTERPRETATION: Changes in access to primary care can affect whether patients seek care from their own physician, from another clinic or at the emergency department. Improving access by reducing the delay in obtaining an appointment with one's primary care physician may be one mechanism to improve continuity of care.

Evaluation of the nutritive value of legume alternatives to soybean meal for broiler chickens.

Five experiments were conducted to investigate the nutritional value of various legumes and a faba beans processing co-product for broilers. In Expt. 1 and 3, metabolizable energy (AME) content was evaluated for 2 batches of bean starch concentrate (BSC) that differed in physical and chemical characteristics. Standardized ileal amino acid digestibility (SIAAD) was determined for BSC in Expt. 2, and for corn, soybean meal (SBM), organic and conventional faba beans, and quinoa (Expt. 4). The growth performance response of broiler chickens to partial replacement of wheat and SBM with various legumes was investigated in Expt. 5. The AME of the BSC assayed in Expt. 1 was lower (P < 0.01) than that of the BSC assayed in Expt. 3. The SIAAD was generally high for BSC in Expt. 2 although the content and digestibility of sulfur amino acids were low. In Expt. 4, there was no difference in SIAAD of Arg, Phe, Asp, and Gly among the different feedstuffs assayed. SIAAD was largely similar for both conventional and organic faba bean. The SIAADs of Met, Thr, Ser, and Tyr were lower (P < 0.05) for quinoa compared with SBM or corn. In Expt. 5, FCR was greater (P < 0.05) for broiler chickens receiving faba beans+barley mix or lupins compared with the wheat-SBM control diet. Amino acid digestibility was greater (P < 0.01) for the diets containing lupins compared with the other diets except for Lys, Met, Thr, Ala, Asp, and Ser. On the other hand, amino acid digestibility in diet with faba beans+barley mix was lower (P < 0.05) compared with all the other diets, except for Arg, Asp, Lys, and Thr. It was concluded from the current studies that there is scope for using the assayed legumes, co-products, and quinoa in broiler chickens to partly replace SBM as protein feedstuffs.

ACSC Indicator: testing reliability for hypertension.

BACKGROUND: With high-quality community-based primary care, hospitalizations for ambulatory care sensitive conditions (ACSC) are considered avoidable. The purpose of this study was to test the inter-physician reliability of judgments of avoidable hospitalizations for one ACSC, uncomplicated hypertension, derived from medical chart review. METHODS: We applied the Canadian Institute for Health Information's case definition to obtain a random sample of patients who had an ACSC hospitalization for uncomplicated hypertension in Calgary, Alberta. Medical chart review was conducted by three experienced internal medicine specialists. Implicit methods were used to judge avoidability of hospitalization using a validated 5-point scale. RESULTS: There was poor agreement among three physicians raters when judging the avoidability of 82 ACSC hospitalizations for uncomplicated hypertension (κ = 0.092). The κ also remained low when assessing agreement between raters 1 and 3 (κ = 0.092), but the κ was lower (less than chance agreement) for raters 1 and 2 (κ = -0.119) and raters 2 and 3 (κ = -0.008). When the 5-point scale was dichotomized, there was fair agreement among three raters (κ = 0.217). The proportion of ACSC hospitalizations for uncomplicated hypertension that were rated as avoidable was 32.9%, 6.1% and 26.8% for raters 1, 2, and 3, respectively. CONCLUSIONS: This study found a low proportion of ACSC hospitalization were rated as avoidable, with poor to fair agreement of judgment between physician raters. This suggests that the validity and utility of this health indicator is questionable. It points to a need to abandon the use of ACSC entirely; or alternatively to work on the development of explicit criteria for judging avoidability of hospitalization for ACSC such as hypertension.

A Comparative Nitrogen Balance and Productivity Analysis of Legume and Non-legume Supported Cropping Systems: The Potential Role of Biological Nitrogen Fixation.

The potential of biological nitrogen fixation (BNF) to provide sufficient N for production has encouraged re-appraisal of cropping systems that deploy legumes. It has been argued that legume-derived N can maintain productivity as an alternative to the application of mineral fertilizer, although few studies have systematically evaluated the effect of optimizing the balance between legumes and non N-fixing crops to optimize production. In addition, the shortage, or even absence in some regions, of measurements of BNF in crops and forages severely limits the ability to design and evaluate new legume-based agroecosystems. To provide an indication of the magnitude of BNF in European agriculture, a soil-surface N-balance approach was applied to historical data from 8 experimental cropping systems that compared legume and non-legume crop types (e.g., grains, forages and intercrops) across pedoclimatic regions of Europe. Mean BNF for different legume types ranged from 32 to 115 kg ha-1 annually. Output in terms of total biomass (grain, forage, etc.) was 30% greater in non-legumes, which used N to produce dry matter more efficiently than legumes, whereas output of N was greater from legumes. When examined over the crop sequence, the contribution of BNF to the N-balance increased to reach a maximum when the legume fraction was around 0.5 (legume crops were present in half the years). BNF was lower when the legume fraction increased to 0.6-0.8, not because of any feature of the legume, but because the cropping systems in this range were dominated by mixtures of legume and non-legume forages to which inorganic N as fertilizer was normally applied. Forage (e.g., grass and clover), as opposed to grain crops in this range maintained high outputs of biomass and N. In conclusion, BNF through grain and forage legumes has the potential to generate major benefit in terms of reducing or dispensing with the need for mineral N without loss of total output.

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems.

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers.

Relationship between primary care physician visits and hospital/emergency use for uncomplicated hypertension, an ambulatory care-sensitive condition.

BACKGROUND: Hospitalizations for ambulatory care-sensitive conditions (ACSCs) represent an indirect measure of access and quality of community care. The purpose of this study was to examine the association between one ACSC, uncomplicated hypertension, and previous primary care physician (PCP) utilization. METHODS: A cohort of patients with hypertension was identified using administrative databases in Alberta between fiscal years 1994 and 2008. We applied the Canadian Institute for Health Information's case definition to detect patients with uncomplicated hypertension as the most responsible reason for hospitalization and/or Emergency Department (ED) visit. We assessed hypertension-related and all-cause PCP visits. RESULTS: The overall adjusted rate of ACSC hospitalizations and ED visits for uncomplicated hypertension was 7.1 and 13.9 per 10,000 hypertensive patients, respectively. The likelihood of ACSC hospitalization for uncomplicated hypertension was associated with age, household income quintile, region of residence, and Charlson comorbidity status (all P < 0.0001). The adjusted rate of ACSC hospitalizations for uncomplicated hypertension increased from 4.8 per 10,000 hypertensive patients for those without hypertension-related PCP visits before diagnosis to 10.5 per 10,000 hypertensive patients for those with 5 or more hypertension-related PCP visits. The rate of ACSC hospitalizations and/or ED visits for uncomplicated hypertension increased as the number of hypertension-related PCP visits increased even after stratifying according to demographic and clinical characteristics. CONCLUSIONS: As the frequency of hypertension-related PCP visits increased, the rate of ACSC hospitalizations and/or ED visits for uncomplicated hypertension increased. This suggests that ACSC hospitalization for uncomplicated hypertension might not be a particularly good indicator for access to primary care.

Hospitalization for uncomplicated hypertension: an ambulatory care sensitive condition.

BACKGROUND: Hospitalizations for ambulatory care sensitive conditions (ACSC) represent an indirect measure of access and quality of community care. This study explored hospitalization rates for 1 ACSC, uncomplicated hypertension, and the factors associated with hospitalization. METHODS: A cohort of patients with incident hypertension, and their covariates, was defined using validated case definitions applied to International Classification of Disease administrative health data in 4 Canadian provinces between fiscal years 1997 and 2004. We applied the Canadian Institute for Health Information's case definition to detect all patients who had an ACSC hospitalization for uncomplicated hypertension. We employed logistic regression to assess factors associated with an ACSC hospitalization for uncomplicated hypertension. RESULTS: The overall rate of hospitalizations for uncomplicated hypertension in the 4 provinces was 3.7 per 1000 hypertensive patients. The risk-adjusted rate was lowest among those in an urban setting (2.6 per 1000; 95% confidence interval [CI], 2.3-2.7), the highest income quintile (3.4 per 1000; 95% CI, 2.8-4.2), and those with no comorbidities (3.6 per 1000; 95% CI, 3.2-3.9). Overall, Newfoundland had the highest adjusted rate (5.7 per 1000; 95% CI, 4.9-6.7), and British Columbia had the lowest (3.7 per 1000; 95% CI, 3.4-4.2). The adjusted rate declined from 5.9 per 1000 in 1997 to 3.7 per 1000 in 2004. CONCLUSIONS: We found that the rate of hospitalizations for uncomplicated hypertension has decreased over time, which might reflect improvements in community care. Geographic variations in the rate of hospitalizations indicate disparity among the provinces and those residing in rural regions.

Outcomes among 3.5 million newly diagnosed hypertensive Canadians.

BACKGROUND: This population-based study assessed rates of all-cause mortality, myocardial infarction, heart failure, and stroke for up to 12 years of follow-up in 3.5 million Canadian adults newly diagnosed with hypertension. METHODS: Hypertension cohort, outcomes, and covariates were defined using validated case definitions applied to inpatient and outpatient administrative health databases. Factors associated with each outcome were identified using Cox proportional hazards models. RESULTS: Of 3,531,089 adults newly diagnosed with hypertension and without a previous history of cardiovascular disease, 29.4% were younger than 50 years of age; 48.2% were male, and 17.2% resided in a rural area. Over a median follow-up length of 6.1 years, the crude all-cause mortality rate was 22.4 per 1000 person-years. The incidence of hospitalized myocardial infarction (8.4 per 1000 person-years) and hospitalized heart failure (8.5 per 1000 person-years) was higher than stroke (6.9 per 1000 person-years). The incidence rate for any cardiovascular hospitalization was 19.3 per 1000 person-years. Older age, male sex, lower income, rural residence, and a higher number of Charlson comorbidities were each independently associated with a higher risk of mortality and incident cardiovascular disease hospitalizations. CONCLUSIONS: In a nationally-representative incident cohort of hypertensive adults we have demonstrated higher mortality rates and poorer outcomes for the elderly, males, and those living in rural or low income locations. Innovative approaches to the provision of care for these high-risk individuals will lead to improved patient outcomes.

Incidence, cardiovascular complications and mortality of hypertension by sex and ethnicity.

OBJECTIVE: To compare ethnic and sex difference in the incidence of newly diagnosed hypertension, and subsequent risk of cardiovascular disease outcomes among South Asian, Chinese and white patients. METHODS: We identified patients with newly diagnosed hypertension aged ≥20 years. Patients were followed for 1-9 years for all-cause mortality and cardiovascular disease with myocardial infarction, heart failure and stroke. Cox proportional hazard models stratified by sex and adjusted for age, median income and co-morbid conditions, were constructed to determine the independent association between ethnicity and the development of the combined cardiovascular endpoint as well as death. RESULTS: There were 39 175 South Asian (49.4% men, 34.4% age ≥65), 49 892 Chinese (48.1% men, 36.7% age ≥65) and 841 277 white (47.9% men, 38.8% age ≥65) patients with newly diagnosed hypertension. Age and sex adjusted incidence of hypertension was highest in South Asian patients and lowest in Chinese patients. Compared with white patients, South Asian and Chinese patients had a lower mortality (adjusted HR (aHR) 0.91 and 0.66) and risk of cardiovascular disease outcomes (aHR 0.94 and 0.49). Compared to men, women had significantly lower mortality (aHR: 0.83 for Chinese, 0.78 for South Asian and 0.77 for white) and cardiovascular disease outcomes (0.72 for Chinese, 0.63 for South Asian and 0.65 for white). CONCLUSIONS: South Asian patients had higher rates of hypertension compared to the other ethnic groups. South Asian and Chinese patients had a lower risk of death and developing cardiovascular outcomes compared to whites. Women with hypertension have a better prognosis than men regardless of ethnicity.