Estimated mortality risk and use of palliative care services among home care clients during the last 6 months of life: a retrospective cohort study.

BACKGROUND: In Canada, only 15% of patients requiring palliative care receive such services in the year before death. We describe health care utilization patterns among home care users in their last 6 months of life to inform care planning for older people with varying mortality risks and evolving care needs as they decline. METHODS: Using population health administrative data from Ontario, we performed a retrospective cohort study involving home care clients aged 50 years and older who received at least 1 interRAI (Resident Assessment Instrument) Home Care assessment between April 2018 and September 2019. We report the proportion of clients who used acute care, long-term care, and palliative home care services within 6 months of their assessment, stratified by their predicted 6-month mortality risk using a prognostic tool called the Risk Evaluation for Support: Predictions for Elder-life in their Communities Tool (RESPECT) and vital status. RESULTS: The cohort included 247 377 adults, 11.9% of whom died within 6 months of an assessment. Among decedents, 50.6% of those with a RESPECT-estimated median survival of fewer than 3 months received at least 1 nonphysician palliative home care visit before death. This proportion declined to 38.7% and 29.5% among decedents with an estimated median survival between 3 and 6 months and between 6 and 12 months, respectively. INTERPRETATION: Many older adults in Ontario do not receive any palliative home care before death. Prognostic tools such as RESPECT may improve recognition of reduced life expectancies and palliative care needs of individuals in their final years of life.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017. OBJECTIVES: To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach. SEARCH METHODS: We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022. SELECTION CRITERIA: We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention. DATA COLLECTION AND ANALYSIS: Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence. MAIN RESULTS: This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015. AUTHORS' CONCLUSIONS: Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.

Development and Evaluation of the Dietary Pattern Calculator (DiPaC) for Personalized Assessment and Feedback.

This study aimed to develop and validate a diet assessment screener - the Dietary Pattern Calculator (DiPaC). A scoping review identified currently available short diet quality assessment tools. Twenty-one articles covering 19 unique tools were included. The current tools mainly focused on individual nutrients or food groups or were developed for a specific population, and few ascertained overall dietary patterns. The 24-hour dietary recalls from the nationally representative Canadian Community Health Survey (CCHS)-Nutrition 2015 (n = 13,958) were used to derive and validate a personalized dietary pattern informed by the scoping review using weighted partial least squares. The dominant dietary pattern in CCHS-Nutrition 2015 was characterized by high consumption of fast foods, carbonated drinks, and salty snacks and low consumption of whole fruits, orange vegetables, other vegetables and juices, whole grains, dark green vegetables, legumes, and soy. The dietary pattern assessment was used to create and evaluate DiPaC following an agile and user-centred research and development approach. DiPaC, which demonstrated high validity and intermediate reliability (internal consistency = 0.47-0.51), is publicly available at https://www.projectbiglife.ca/. DiPaC can be used by the public, clinicians, and researchers for quick and robust assessment of diet quality, providing immediate feedback with the advantage of being easy to implement.

Mortality and Life Expectancy Lost in Canada Attributable to Dietary Patterns: Evidence From Canadian National Nutrition Survey Linked to Routinely Collected Health Administrative Databases.

Using 5 diet quality indexes, we estimated the mortality and life expectancy lost, at the national level, attributable to poor dietary patterns, which had previously been largely unknown. We used the Canadian Community Health Survey 2004, linked to vital statistics (n = 16,212 adults; representing n = 22,898,880). After a median follow-up of 7.5 years, 1,722 deaths were recorded. Population attributable fractions were calculated to estimate the mortality burden of poor dietary patterns (Dietary Guidelines for Americans Adherence Index 2015, Dietary Approaches to Stop Hypertension, Healthy Eating Index, Alternative Healthy Eating Index, and Mediterranean Style Dietary Pattern Score). Better diet quality was associated with a 32%-51% and 21%-43% reduction in all-cause mortality among adults aged 45-80 years and ≥20 years, respectively. Projected life expectancy at 45 years was longer for Canadians adhering to a healthy dietary pattern (average of 5.2-8.0 years (men) and 1.6-4.1 (women)). At the population level, 26.5%-38.9% (men) and 8.9%-22.9% (women) of deaths were attributable to poor dietary patterns. Survival benefit was greater for individuals with higher scores on all diet indexes, even with relatively small intake differences. The large attributable burden was likely from assessing overall dietary patterns instead of a limited range of foods and nutrients.

Sodium, added sugar and saturated fat intake in relation to mortality and CVD events in adults: Canadian National Nutrition Survey linked with vital statistics and health administrative databases.

This study aimed to determine whether higher intakes of Na, added sugars and saturated fat are prospectively associated with all-cause mortality and CVD incidence and mortality in a diverse population. The nationally representative Canadian Community Health Survey-Nutrition 2004 was linked with the Canadian Vital Statistics - Death Database and the Discharge Abstract Database (2004-2011). Outcomes were all-cause mortality and CVD incidence and mortality. There were 1722 mortality cases within 115 566 person-years of follow-up (median (interquartile range) of 7·48 (7·22-7·70) years). There was no statistically significant association between Na density or energy from saturated fat and all-cause mortality or CVD events for all models investigated. The association of usual percentage of energy from added sugars and all-cause mortality was significant in the base model with participants consuming 11·47 % of energy from added sugars having 1·34 (95 % CI 1·01, 1·77) times higher risk of all-cause mortality compared with those consuming 4·17 % of energy from added sugars. Overall, our results did not find statistically significant associations between the three nutrients and risk of all-cause mortality or CVD events at the population level in Canada. Large-scale linked national nutrition datasets may not have the discrimination to identify prospective impacts of nutrients on health measures.

Comparison of mortality hazard ratios associated with health behaviours in Canada and the United States: a population-based linked health survey study.

BACKGROUND: Modern health surveillance and planning requires an understanding of how preventable risk factors impact population health, and how these effects vary between populations. In this study, we compare how smoking, alcohol consumption, diet and physical activity are associated with all-cause mortality in Canada and the United States using comparable individual-level, linked population health survey data and identical model specifications. METHODS: The Canadian Community Health Survey (CCHS) (2003-2007) and the United States National Health Interview Survey (NHIS) (2000, 2005) linked to individual-level mortality outcomes with follow up to December 31, 2011 were used. Consistent variable definitions were used to estimate country-specific mortality hazard ratios with sex-specific Cox proportional hazard models, including smoking, alcohol, diet and physical activity, sociodemographic indicators and proximal factors including disease history. RESULTS: A total of 296,407 respondents and 1,813,884 million person-years of follow-up from the CCHS and 58,232 respondents and 497,909 person-years from the NHIS were included. Absolute mortality risk among those with a 'healthy profile' was higher in the United States compared to Canada, especially among women. Adjusted mortality hazard ratios associated with health behaviours were generally of similar magnitude and direction but often stronger in Canada. CONCLUSION: Even when methodological and population differences are minimal, the association of health behaviours and mortality can vary across populations. It is therefore important to be cautious of between-study variation when aggregating relative effect estimates from differing populations, and when using external effect estimates for population health research and policy development.

Linkage of the nationally representative Canadian Community Health Survey - Nutrition 2004 to routinely collected mortality records.

Introduction: The Canadian Community Health Survey (CCHS) - Nutrition 2004 (n=35,107; interview dates from January 2004 to January 2005) linked to the Canadian Vital Statistics - Death Database (CVSD) (2011) represents a novel linkage of a population-based, nationally representative nutrition survey with routinely collected mortality records (including date and cause of death). The linkage was done through individual tax data in Canada, and contains longitudinal records for 29,897 Canadians aged 0 years and older-1,753 of whom died-in the 10 provinces of Canada. The median follow-up time was 7.49 years, with 102,953 person-years among males and 114,876 person-years among females (unweighted), and included a special sampling survey weight (for linked data) to account for those who did not agree to share and link their information. The CCHS - Nutrition 2004 linked to CVSD has been used to evaluate associations between lifestyle and sociodemographic characteristics and mortality. Using these data, statistical methods have been developed and tested to control random and systematic measurement errors when evaluating the relationship between different dietary exposures (evaluated using repeated 24-hour dietary recalls) and health outcomes. The linked data are available through Statistics Canada's Research Data Centres.

Predicting death in home care users: derivation and validation of the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT).

BACKGROUND: Prognostication tools that report personalized mortality risk and survival could improve discussions about end-of-life and advance care planning. We sought to develop and validate a mortality risk model for older adults with diverse care needs in home care using self-reportable information - the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT). METHODS: Using a derivation cohort that comprised adults living in Ontario, Canada, aged 50 years and older with at least 1 Resident Assessment Instrument for Home Care (RAI-HC) record between Jan. 1, 2007, and Dec. 31, 2012, we developed a mortality risk model. The primary outcome was mortality 6 months after a RAI-HC assessment. We used proportional hazards regression with robust standard errors to account for clustering by the individual. We validated this algorithm for a second cohort of users of home care who were assessed between Jan. 1 and Dec. 31, 2013. We used Kaplan-Meier survival curves to estimate the observed risk of death at 6 months for assessment of calibration and median survival. We constructed 61 risk groups based on incremental increases in the estimated median survival of about 3 weeks among adults at high risk and 3 months among adults at lower risk. RESULTS: The derivation and validation cohorts included 435 009 and 139 388 adults, respectively. We identified a total of 122 823 deaths within 6 months of a RAI-HC assessment in the derivation cohort. The mean predicted 6-month mortality risk was 10.8% (95% confidence interval [CI] 10.7%-10.8%) and ranged from 1.54% (95% CI 1.53%-1.54%) in the lowest to 98.1% (95% CI 98.1%-98.2%) in the highest risk group. Estimated median survival spanned from 28 days (11 to 84 d at the 25th and 75th percentiles) in the highest risk group to over 8 years (1925 to 3420 d) in the lowest risk group. The algorithm had a c-statistic of 0.753 (95% CI 0.750-0.756) in our validation cohort. INTERPRETATION: The RESPECT mortality risk prediction tool that makes use of readily available information can improve the identification of palliative and end-of-life care needs in a diverse older adult population receiving home care.

Smoking patterns based on birth-cohort-specific histories from 1965 to 2013, with projections to 2041.

BACKGROUND: Characterizing smoking patterns over time is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality. Beginning with a 1920s birth cohort, smoking histories (i.e., estimates of smoking initiation and cessation, and prevalence of current and former smokers) were generated. DATA: The Ontario sample (n = 238,411) of the 2003 to 2013 cycles of the Canadian Community Health Survey, which is conducted biennially, was used to obtain cross-sectional information on current smoking behaviour. METHODS: Age at smoking initiation and age at smoking cessation were used to construct smoking histories for each respondent, up to the survey date. An age-period-cohort model was generated and used to examine survival differences by smoking status. Using the model, and adjusting for survival differences in smoking status, the prevalence of current, former and never smokers was estimated in cohorts from 1920 to 1985. Smoking initiation, cessation and intensity were then estimated for age-specific distributions of each birth cohort. These rates were projected forward through to 2041. Smoking patterns by highest level of education were generated using education-stratified models. RESULTS: Smoking histories show clear trends over time by sex, cohort and age. If current patterns persist, smoking prevalence is projected to decline to single digits (below 10%) by 2023 for women and 2040 for men. DISCUSSION: Birth-cohort-specific smoking histories can be generated using cross-sectional health surveys. These cohort histories can describe smoking patterns over time and into the future. In turn, these histories can be used in micro-simulation models to evaluate historic or planned tobacco control interventions, and to project smoking prevalence.

International population-based health surveys linked to outcome data: A new resource for public health and epidemiology.

BACKGROUND: National health surveys linked to vital statistics and health care information provide a growing source of individual-level population health data. Pooling linked surveys across jurisdictions would create comprehensive datasets that are larger than most existing cohort studies, and that have a unique international and population perspective. This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies. DATA AND METHODS: The design, methodologies and content of the Canadian Community Health Survey (2003 to 2008), the United States National Health Interview Survey (2000, 2005) and the Scottish Health Survey (SHeS) (2003, 2008 to 2010) were examined for comparability and consistency. The feasibility of creating common variables for measuring smoking, alcohol consumption, physical activity and diet was assessed. Sample size and estimated mortality events were collected. RESULTS: The surveys have comparable purposes, designs, sampling and administration methodologies, target populations, exclusions, and content. Similar health behaviour questions allow for comparable variables to be created across the surveys. However, the SHeS uses a more detailed risk factor evaluation for alcohol consumption and diet data. Therefore, comparisons of alcohol consumption and diet data between the SHeS and the other two surveys should be performed with caution. Pooling these linked surveys would create a dataset with over 350,000 participants, 28,424 deaths and over 2.4 million person-years of follow-up. DISCUSSION: Pooling linked national population health surveys could improve population health research and surveillance. Innovative methodologies must be used to account for survey dissimilarities, and further discussion is needed on how to best access and analyze data across jurisdictions.

Systemic and tumor-directed therapy for oligometastatic prostate cancer: study protocol for a phase II trial for veterans with de novo oligometastatic disease.

BACKGROUND: The treatment paradigm for metastatic hormone-sensitive prostate cancer (mHSPC) patients is evolving. PET/CT now offers improved sensitivity and accuracy in staging. Recent randomized trial data supports escalated hormone therapy, local primary tumor therapy, and metastasis-directed therapy. The impact of combining such therapies into a multimodal approach is unknown. This Phase II single-arm clinical trial sponsored and funded by Veterans Affairs combines local, metastasis-directed, and systemic therapies to durably render patients free of detectable disease off active therapy. METHODS: Patients with newly-diagnosed M1a/b prostate cancer (PSMA PET/CT staging is permitted) and 1-5 radiographically visible metastases (excluding pelvic lymph nodes) are undergoing local treatment with radical prostatectomy, limited duration systemic therapy for a total of six months (leuprolide, abiraterone acetate with prednisone, and apalutamide), metastasis-directed stereotactic body radiotherapy (SBRT), and post-operative fractionated radiotherapy if pT ≥ 3a, N1, or positive margins are present. The primary endpoint is the percent of patients achieving a serum PSA of < 0.05 ng/mL six months after recovery of serum testosterone ≥150 ng/dL. Secondary endpoints include time to biochemical progression, time to radiographic progression, time to initiation of alternative antineoplastic therapy, prostate cancer specific survival, health related quality-of-life, safety and tolerability. DISCUSSION: To our knowledge, this is the first trial that tests a comprehensive systemic and tumor directed therapeutic strategy for patients with newly diagnosed oligometastatic prostate cancer. This trial, and others like it, represent the critical first step towards curative intent therapy for a patient population where palliation has been the norm. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT03298087 (registration date: September 29, 2017).

Development and validation of a cardiovascular disease risk-prediction model using population health surveys: the Cardiovascular Disease Population Risk Tool (CVDPoRT).

BACKGROUND: Routinely collected data from large population health surveys linked to chronic disease outcomes create an opportunity to develop more complex risk-prediction algorithms. We developed a predictive algorithm to estimate 5-year risk of incident cardiovascular disease in the community setting. METHODS: We derived the Cardiovascular Disease Population Risk Tool (CVDPoRT) using prospectively collected data from Ontario respondents of the Canadian Community Health Surveys, representing 98% of the Ontario population (survey years 2001 to 2007; follow-up from 2001 to 2012) linked to hospital admission and vital statistics databases. Predictors included body mass index, hypertension, diabetes, and multiple behavioural, demographic and general health risk factors. The primary outcome was the first major cardiovascular event resulting in hospital admission or death. Death from a noncardiovascular cause was considered a competing risk. RESULTS: We included 104 219 respondents aged 20 to 105 years. There were 3709 cardiovascular events and 818 478 person-years follow-up in the combined derivation and validation cohorts (5-year cumulative incidence function, men: 0.026, 95% confidence interval [CI] 0.025-0.028; women: 0.018, 95% 0.017-0.019). The final CVDPoRT algorithm contained 12 variables, was discriminating (men: C statistic 0.82, 95% CI 0.81-0.83; women: 0.86, 95% CI 0.85-0.87) and was well-calibrated in the overall population (5-year observed cumulative incidence function v. predicted risk, men: 0.28%; women: 0.38%) and in nearly all predefined policy-relevant subgroups (206 of 208 groups). INTERPRETATION: The CVDPoRT algorithm can accurately discriminate cardiovascular disease risk for a wide range of health profiles without the aid of clinical measures. Such algorithms hold potential to support precision medicine for individual or population uses. Study registration: ClinicalTrials.gov, no. NCT02267447.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Decision aids are interventions that support patients by making their decisions explicit, providing information about options and associated benefits/harms, and helping clarify congruence between decisions and personal values. OBJECTIVES: To assess the effects of decision aids in people facing treatment or screening decisions. SEARCH METHODS: Updated search (2012 to April 2015) in CENTRAL; MEDLINE; Embase; PsycINFO; and grey literature; includes CINAHL to September 2008. SELECTION CRITERIA: We included published randomized controlled trials comparing decision aids to usual care and/or alternative interventions. For this update, we excluded studies comparing detailed versus simple decision aids. DATA COLLECTION AND ANALYSIS: Two reviewers independently screened citations for inclusion, extracted data, and assessed risk of bias. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made and the decision-making process.Secondary outcomes were behavioural, health, and health system effects.We pooled results using mean differences (MDs) and risk ratios (RRs), applying a random-effects model. We conducted a subgroup analysis of studies that used the patient decision aid to prepare for the consultation and of those that used it in the consultation. We used GRADE to assess the strength of the evidence. MAIN RESULTS: We included 105 studies involving 31,043 participants. This update added 18 studies and removed 28 previously included studies comparing detailed versus simple decision aids. During the 'Risk of bias' assessment, we rated two items (selective reporting and blinding of participants/personnel) as mostly unclear due to inadequate reporting. Twelve of 105 studies were at high risk of bias.With regard to the attributes of the choice made, decision aids increased participants' knowledge (MD 13.27/100; 95% confidence interval (CI) 11.32 to 15.23; 52 studies; N = 13,316; high-quality evidence), accuracy of risk perceptions (RR 2.10; 95% CI 1.66 to 2.66; 17 studies; N = 5096; moderate-quality evidence), and congruency between informed values and care choices (RR 2.06; 95% CI 1.46 to 2.91; 10 studies; N = 4626; low-quality evidence) compared to usual care.Regarding attributes related to the decision-making process and compared to usual care, decision aids decreased decisional conflict related to feeling uninformed (MD -9.28/100; 95% CI -12.20 to -6.36; 27 studies; N = 5707; high-quality evidence), indecision about personal values (MD -8.81/100; 95% CI -11.99 to -5.63; 23 studies; N = 5068; high-quality evidence), and the proportion of people who were passive in decision making (RR 0.68; 95% CI 0.55 to 0.83; 16 studies; N = 3180; moderate-quality evidence).Decision aids reduced the proportion of undecided participants and appeared to have a positive effect on patient-clinician communication. Moreover, those exposed to a decision aid were either equally or more satisfied with their decision, the decision-making process, and/or the preparation for decision making compared to usual care.Decision aids also reduced the number of people choosing major elective invasive surgery in favour of more conservative options (RR 0.86; 95% CI 0.75 to 1.00; 18 studies; N = 3844), but this reduction reached statistical significance only after removing the study on prophylactic mastectomy for breast cancer gene carriers (RR 0.84; 95% CI 0.73 to 0.97; 17 studies; N = 3108). Compared to usual care, decision aids reduced the number of people choosing prostate-specific antigen screening (RR 0.88; 95% CI 0.80 to 0.98; 10 studies; N = 3996) and increased those choosing to start new medications for diabetes (RR 1.65; 95% CI 1.06 to 2.56; 4 studies; N = 447). For other testing and screening choices, mostly there were no differences between decision aids and usual care.The median effect of decision aids on length of consultation was 2.6 minutes longer (24 versus 21; 7.5% increase). The costs of the decision aid group were lower in two studies and similar to usual care in four studies. People receiving decision aids do not appear to differ from those receiving usual care in terms of anxiety, general health outcomes, and condition-specific health outcomes. Studies did not report adverse events associated with the use of decision aids.In subgroup analysis, we compared results for decision aids used in preparation for the consultation versus during the consultation, finding similar improvements in pooled analysis for knowledge and accurate risk perception. For other outcomes, we could not conduct formal subgroup analyses because there were too few studies in each subgroup. AUTHORS' CONCLUSIONS: Compared to usual care across a wide variety of decision contexts, people exposed to decision aids feel more knowledgeable, better informed, and clearer about their values, and they probably have a more active role in decision making and more accurate risk perceptions. There is growing evidence that decision aids may improve values-congruent choices. There are no adverse effects on health outcomes or satisfaction. New for this updated is evidence indicating improved knowledge and accurate risk perceptions when decision aids are used either within or in preparation for the consultation. Further research is needed on the effects on adherence with the chosen option, cost-effectiveness, and use with lower literacy populations.

Measuring Burden of Unhealthy Behaviours Using a Multivariable Predictive Approach: Life Expectancy Lost in Canada Attributable to Smoking, Alcohol, Physical Inactivity, and Diet.

BACKGROUND: Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death. METHODS: A predictive algorithm for 5 y risk of death-the Mortality Population Risk Tool (MPoRT)-was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model. FINDINGS: The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867-0.881]; females 0.875 [0.868-0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation). CONCLUSIONS: Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population.

Population health impact of statin treatment in Canada.

BACKGROUND: Statins are prescribed to treat dyslipidemia (abnormal amount of lipids such as cholesterol and/or fat in the blood) and reduce cardiovascular disease (CVD) risk. This study describes the CVD risk profile of Canadians aged 20 to 79, compares current treatment patterns with guideline recommendations, and investigates the population health impact of statin treatment. DATA AND METHODS: The baseline CVD risk of the Canadian population aged 20 to 79 was estimated by applying population-weighted risk factor data from the 2007 to 2011 Canadian Health Measures Survey (CHMS) to the Framingham Risk Score. Estimates of statin effectiveness from the literature were applied to baseline risk to assess the number of CVD events avoided owing to actual (CHMS-reported) and recommended (2012 Canadian Cardiovascular Society guidelines) statin treatment. RESULTS: An estimated 2.8 million Canadian adults (about 1 in 10) were treated with statin drugs. The mean 10-year CVD risk of those treated was 27%. Assuming optimal adherence, it was estimated that statin treatment avoided around 18,900 CVD events annually and yielded a number-needed-to-treat (average number of patients treated to prevent one additional CVD event) of 15 over 10 years. In comparison, 6.5 million Canadian adults (about 1 in 4) were recommended for treatment under the 2012 guidelines. The mean 10-year CVD risk of those recommended for treatment was 24%, which translates into a number-needed-to-treat of 17 over 10 years, or approximately 38,600 CVD events avoided annually. The largest gaps in treatment and potential CVD events avoided were among people at high and intermediate risk for CVD. INTERPRETATION: Canadians' CVD risk could be lessened with enhanced targeting of statin treatment to individuals at high and intermediate risk. Such a strategy would likely require additional investments.

Reducing PSA-Based Prostate Cancer Screening in Men Aged 75 Years and Older with the Use of Highly Specific Computerized Clinical Decision Support.

INTRODUCTION: In 2012, the Veterans Health Administration (VHA) implemented guidelines seeking to reduce PSA-based screening for prostate cancer in men aged 75 years and older. OBJECTIVES: To reduce the use of inappropriate PSA-based prostate cancer screening among men aged 75 and over. SETTING: The Veterans Affairs Greater Los Angeles Healthcare System (VA GLA) PROGRAM DESCRIPTION: We developed a highly specific computerized clinical decision support (CCDS) alert to remind providers, at the moment of PSA screening order entry, of the current guidelines and institutional policy. We implemented the tool in a prospective interrupted time series study design over 15 months, and compared the trends in monthly PSA screening rate at baseline to the CCDS on and off periods of the intervention. RESULTS: A total of 30,150 men were at risk, or eligible, for screening, and 2,001 men were screened. The mean monthly screening rate during the 15-month baseline period was 8.3%, and during the 15-month intervention period, was 4.6%. The screening rate declined by 38% during the baseline period and by 40% and 30%, respectively, during the two periods when the CCDS tool was turned on. The screening rate ratios for the baseline and two periods when the CCDS tool was on were 0.97, 0.78, and 0.90, respectively, with a significant difference between baseline and the first CCDS-on period (p < 0.0001), and a trend toward a difference between baseline and the second CCDS-on period (p = 0.056). CONCLUSION: Implementation of a highly specific CCDS tool alone significantly reduced inappropriate PSA screening in men aged 75 years and older in a reproducible fashion. With this simple intervention, evidence-based guidelines were brought to bear at the point of care, precisely for the patients and providers for whom they were most helpful, resulting in more appropriate use of medical resources.

Improving the estimation of the burden of risk factors: an illustrative comparison of methods to measure smoking-attributable mortality.

BACKGROUND: Prevention efforts are informed by the numbers of deaths or cases of disease caused by specific risk factors, but these are challenging to estimate in a population. Fortunately, an increasing number of jurisdictions have increasingly rich individual-level, population-based data linking exposures and outcomes. These linkages enable multivariable approaches to risk assessment. We demonstrate how this approach can estimate the population burden of risk factors and illustrate its advantages over often-used population-attributable fraction methods. METHODS: We obtained risk factor information for 78,597 individuals from a series of population-based health surveys. Each respondent was linked to death registry (568,997 person-years of follow-up, 6,399 deaths).Two methods were used to obtain population-attributable fractions. First, the mortality rate difference between the entire population and the population of non-smokers was divided by the total mortality rate. Second, often-used attributable fraction formulas were used to combine summary measures of smoking prevalence with relative risks of death for select diseases. The respective fractions were then multiplied to summary measures of mortality to obtain smoking-attributable mortality. Alternatively, for our multivariable approach, we created algorithms for risk of death, predicted by health behaviors and various covariates (age, sex, socioeconomic position, etc.). The burden of smoking was determined by comparing the predicted mortality of the current population with that of a counterfactual population where smoking is eliminated. RESULTS: Our multivariable algorithms accurately predicted an individual's risk of death based on their health behaviors and other variables in the models. These algorithms estimated that 23.7% of all deaths can be attributed to smoking in Ontario. This is higher than the 20.0% estimated using population-attributable risk methods that considered only select diseases and lower than the 35.4% estimated from population-attributable risk methods that examine the excess burden of all deaths due to smoking. CONCLUSIONS: The multivariable algorithms presented have several advantages, including: controlling for confounders, accounting for complexities in the relationship between multiple exposures and covariates, using consistent definitions of exposure, and using specific measures of risk derived internally from the study population. We propose the wider use of multivariable risk assessment approach as an alternative to population-attributable fraction methods.

The Population Health Model (POHEM): an overview of rationale, methods and applications.

The POpulation HEalth Model (POHEM) is a health microsimulation model that was developed at Statistics Canada in the early 1990s. POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals' disease states, risk factors, and health determinants, in order to describe and project health outcomes, including disease incidence, prevalence, life expectancy, health-adjusted life expectancy, quality of life, and healthcare costs. Additionally, POHEM was conceptualized and built with the ability to assess the impact of policy and program interventions, not limited to those taking place in the healthcare system, on the health status of Canadians. Internationally, POHEM and other microsimulation models have been used to inform clinical guidelines and health policies in relation to complex health and health system problems. This paper provides a high-level overview of the rationale, methodology, and applications of POHEM. Applications of POHEM to cardiovascular disease, physical activity, cancer, osteoarthritis, and neurological diseases are highlighted.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. OBJECTIVES: To assess the effects of decision aids for people facing treatment or screening decisions. SEARCH METHODS: For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). SELECTION CRITERIA: We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. DATA COLLECTION AND ANALYSIS: Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. MAIN RESULTS: This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies).A) Criteria involving 'choice made' attributes:Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).B) Criteria involving 'decision-making process' attributes:Decision aids compared to usual care interventions resulted in:a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); andc) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable.The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. AUTHORS' CONCLUSIONS: There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values.New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.

Exploring perceptions of online calculators for identifying community-dwelling older people at risk of dying: A qualitative study.

Objectives: This study aimed to assess the acceptability, value, and perceived barriers of using electronic risk calculators for predicting and communicating the risk of death in community-dwelling older adults. Methods: One focus group and eight interviews were conducted with 16 participants with experience caring for patients or family members at end of life. A prototype mortality risk tool was used to anchor discussions. Data were analysed using a qualitative content analysis approach. Results: Five themes emerged: acceptability, communication, barriers to use, broadening the circle of care, and tool limitations. Participants found the tool helpful for preparation, planning, and providing care, but disagreed on its community availability. Personalized risk estimates were valued for facilitating early goals of care conversations and normalizing discussions about death. However, concerns were raised about the tool's interpretation for individuals with different language, cultural, or educational backgrounds. Conclusions: While electronic risk calculators were found to be acceptable, balancing autonomy with varying preferences for receiving the information and potential need for support is crucial. Innovation: Providing patient-oriented life-expectancy estimates can enhance decisional capacity and facilitate shared decision-making between patients, their families, and healthcare professionals. Further research is needed to explore effective communication of personalized risk tools and additional benefits, harms, and barriers to implementation.