Facilitators and barriers for implementing screening brief intervention and referral for health promotion in a rural hospital in Alberta: using consolidated framework for implementation research.

BACKGROUND: Screening, brief intervention, and referral (SBIR) is an evidence-based, comprehensive health promotion approach commonly implemented to reduce alcohol and substance use. Implementation research on SBIR demonstrate that patients find it acceptable, reduces hospital costs, and it is effective. However, SBIR implementation in hospital settings for multiple risk factors (fruit and vegetable consumption, physical activity, alcohol and tobacco use) is still emergent. More evidence is needed to guide SBIR implementation for multiple risk factors in hospital settings. OBJECTIVE: To explore the facilitators and barriers of SBIR implementation in a rural hospital using the Consolidated Framework for Implementation Research (CFIR). METHODS: We conducted a descriptive qualitative investigation consisting of both inductive and deductive analyses. We conducted virtual, semi-structured interviews, guided by the CFIR framework. All interviews were audio-recorded, and transcribed verbatim. NVivo 12 Pro was used to organize and code the raw data. RESULTS: A total of six key informant semi-structured interviews, ranging from 45 to 60 min, were carried out with members of the implementation support team and clinical implementers. Implementation support members reported that collaborating with health departments facilitated SBIR implementation by helping (a) align health promotion risk factors with existing guidelines; (b) develop training and educational resources for clinicians and patients; and (c) foster leadership buy-in. Conversely, clinical implementers reported several barriers to SBIR implementation including, increased and disrupted workflow due to SBIR-related documentation, a lack of knowledge on patients' readiness and motivation to change, as well as perceived patient stigma in relation to SBIR risk factors. CONCLUSION: The CFIR provided a comprehensive framework to gauge facilitators and barriers relating to SBIR implementation. Our pilot investigation revealed that future SBIR implementation must address organizational, clinical implementer, and patient readiness to implement SBIR at all phases of the implementation process in a hospital.

How Does the Facilitation Effort of Clinical Educators Interact With Aspects of Organizational Context to Affect Research Use in Long-term Care? Evidence From CHAID Analysis.

PURPOSE: Organizational context influences the effect of facilitation efforts on research use in care settings. The interactions of these factors are complex. Therefore, the use of traditional statistical methods to examine their interrelationships is often impractical. Big Data analytics can automatically detect patterns within the data. We applied the chi-squared automatic interaction detection (CHAID) algorithm and classification tree technique to explore the dynamic and interdependent relationships between the implementation science concepts-context, facilitation, and research use. DESIGN: Observational, cross-sectional study based on survey data collected from a representative sample of nursing homes in western Canada. METHODS: We assessed three major constructs: (a) Conceptual research utilization (CRU) using the CRU scale; (b) facilitation of research use measured by the frequency of contacts between the frontline staff and a clinical educator, or person who brings new ideas to the care unit; and (c) organizational context at the unit level using the Alberta Context Tool (ACT). CHAID analysis was performed to detect the interactions between facilitation and context variables. Results were illustrated in a classification tree to provide a straightforward visualization. FINDINGS: Data from 312 care units in three provinces were included in the final analysis. Results indicate significant multiway interactions between facilitation and various aspects of the organizational context, including leadership, culture, evaluation, structural resources, and organizational slack (staffing). Findings suggested the preconditions of the care settings where research use can be maximized. CONCLUSIONS: CHAID analysis helped transform data into usable knowledge. Our findings provide insight into the dynamic relationships of facilitators' efforts and organizational context, and how these factors' interplay and their interdependence together may influence research use. CLINICAL RELEVANCE: Knowledge of the combined effects of facilitators' efforts and various aspects of organizational context on research use can contribute to effective strategies to narrow the evidence-practice gap in care settings.

Bringing Together Research and Quality Improvement: The Saskatchewan Approach.

Improving health and health services requires both better knowledge (a key function of research) and better action to adapt and use what is already known (quality improvement). However, organizational and cultural divides between academic research institutions and health system organizations too often result in missed opportunities to integrate research and improvement. The Saskatchewan Health Quality Council's experience and relationships, from linking research, quality improvement and patient engagement in its leadership of the province's healthcare quality improvement journey, provided core support and leadership in the development of Saskatchewan's Strategy for Patient-Oriented Research SUPPORT Unit. The vision is for the SUPPORT Unit to integrate research and quality improvement into a continuous learning health system.

Comparison of the accuracy of classification models to estimate healthcare use and costs associated with COPD exacerbations in Saskatchewan, Canada: A retrospective cohort study.

OBJECTIVE: COPD is a high-cost disease and results in frequent contacts with the healthcare system. The study objective was to compare the accuracy of classification models with different covariates for classifying COPD patients into cost groups. METHODS: Linked health administrative databases from Saskatchewan, Canada, were used to identify a cohort of newly diagnosed COPD patients (April 1, 2007 to March 31, 2011) and their episodes of healthcare encounters for disease exacerbations. Total costs of the first and follow-up episodes were computed and patients were categorized as persistently high cost, occasionally high cost, and persistently low cost based on cumulative cost distribution ranking using the 75th percentile cutoff for high-cost status. Classification accuracy was compared for seven multinomial logistic regression models containing socio-demographic characteristics (i.e., base model), and socio-demographic and prior healthcare use characteristics (i.e., comparator models). RESULTS: Of the 1182 patients identified, 8.5% were classified as persistently high cost, 26.1% as occasionally high cost, and the remainder as persistently low cost. The persistently high-cost and occasionally high-cost patients incurred 10 times ($12 449 vs $1263) and seven times ($9334 vs $1263) more costs in their first exacerbation episode than persistently low-cost patients, respectively. Classification accuracy was 0.67 for the base model, whereas the comparator model containing socio-demographic and number of prior hospital admissions had the highest accuracy (0.72). CONCLUSIONS: Costs associated with COPD exacerbation episodes are substantial. Adding prior hospitalization to socio-demographic characteristics produced the highest improvements in classification accuracy. Accurate classification models are important for identifying potential healthcare cost management strategies.

Simultaneous temporal trends in dementia incidence and prevalence, 2005-2013: a population-based retrospective cohort study in Saskatchewan, Canada.

BACKGROUND: Original studies published over the last decade regarding time trends in dementia report mixed results. The aims of the present study were to use linked administrative health data for the province of Saskatchewan for the period 2005/2006 to 2012/2013 to: (1) examine simultaneous temporal trends in annual age- and sex-specific dementia incidence and prevalence among individuals aged 45 and older, and (2) stratify the changes in incidence over time by database of identification. METHODS: Using a population-based retrospective cohort study design, data were extracted from seven provincial administrative health databases linked by a unique anonymized identification number. Individuals 45 years and older at first identification of dementia between April 1, 2005 and March 31, 2013 were included, based on case definition criteria met within any one of four administrative health databases (hospital, physician, prescription drug, and long-term care). RESULTS: Between 2005/2006 and 2012/2013, the 12-month age-standardized incidence rate of dementia declined significantly by 11.07% and the 12-month age-standardized prevalence increased significantly by 30.54%. The number of incident cases decreased from 3,389 to 3,270 and the number of prevalent cases increased from 8,795 to 13,012. Incidence rate reductions were observed in every database of identification. CONCLUSIONS: We observed a simultaneous trend of decreasing incidence and increasing prevalence of dementia over a relatively short 8-year time period from 2005/2006 to 2012/2013. These trends indicate that the average survival time of dementia is lengthening. Continued observation of these time trends is warranted given the short study period.

Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care.

BACKGROUND: A patient's trajectory through the healthcare system affects resource use and outcomes. Data fields in population-based administrative health databases are potentially valuable resources for constructing care trajectories for entire populations, provided they can capture patient transitions between healthcare services. This study describes patient transitions from the emergency department (ED) to other healthcare settings, and ascertains whether the discharge disposition field recorded in the ED data was a reliable source of patient transition information from the emergency to the acute care settings. METHODS: Administrative health databases from the province of Saskatchewan, Canada (population 1.1 million) were used to identify patients with at least one ED visit to provincial teaching hospitals (n = 5) between April 1, 2006 and March 31, 2012. Discharge disposition from ED was described using frequencies and percentages; and it includes categories such as home, transfer to other facilities, and died. The kappa statistic with 95 % confidence intervals (95 % CIs) was used to measure agreement between the discharge disposition field in the ED data and hospital admission records. RESULTS: We identified N = 1,062,861 visits for 371,480 patients to EDs over the six-year study period. Three-quarters of the discharges were to home, 16.1 % were to acute care in the same facility in which the ED was located, and 1.6 % resulted in a patient transfer to a different acute care facility. Agreement between the discharge disposition field in the ED data and hospital admission records was good when the emergency and acute care departments were in the same facility (κ = 0.77, 95 % CI 0.77, 0.77). For transfers to a different acute care facility, agreement was only fair (κ = 0.36, 95 % CI 0.35, 0.36). CONCLUSIONS: The majority of patients who attended EDs did not transition to another healthcare setting. For those who transitioned to acute care, accuracy of the discharge disposition field depended on whether the two services were provided in the same facility. Using the hospital data as reference, we conclude that the discharge disposition field in the ED data is not reliable for measuring transitions from ED to acute care.

Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study.

BACKGROUND: Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. METHODS: Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen's κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. RESULTS: The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen's κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. CONCLUSIONS: Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations.

Incidence and prevalence of dementia in linked administrative health data in Saskatchewan, Canada: a retrospective cohort study.

BACKGROUND: Determining the epidemiology of dementia among the population as a whole in specific jurisdictions - including the long-term care population-is essential to providing appropriate care. The objectives of this study were to use linked administrative databases in the province of Saskatchewan to determine the 12-month incidence and prevalence of dementia for the 2012/13 period (1) among individuals aged 45 and older in the province of Saskatchewan, (2) according to age group and sex, and (3) according to diagnosis code and other case definition criteria. METHODS: We used a population-based retrospective cohort study design and extracted data from 10 provincial health databases linked by a unique health services number. The cohort included individuals 45 years and older at first identification of dementia between April 1, 2001 and March 31, 2013 based on case definitions met within any one of four administrative health databases (Hospital Discharge Abstracts, Physician Service Claims, Prescription Drug, and RAI-MDS, i.e., Long-term Care). RESULTS: A total of 3,270 incident cases of dementia (7.28 per 1,000 PAR) and 13,012 prevalent cases (28.16 per 1,000 PAR) were identified during 2012/13. This study found the incidence rate increased by 2.8 to 5.1 times and the prevalence rate increased by 2.6 to 4.6 times every 10 years after 45 years of age. Overall, the age-standardised incidence rate was significantly lower among females than males (7.04 vs. 7.65 per 1,000 PAR) and the age-standardised prevalence rate was significantly higher among females than males (28.92 vs. 26.53 per 1,000 PAR). Over one-quarter (28 %) of all incident cases were admitted to long-term care before a diagnosis was formally recorded in physician or hospital data, and nearly two-thirds of these cases were identified at admission with impairment at the moderate to very severe level or a disease category of Alzheimer's disease/other dementia. CONCLUSIONS: Linking multiple sources of registry data contributes to our understanding of the epidemiology of dementia across multiple segments of the population, inclusive of individuals residing in long-term care. This information is foundational for public awareness and policy recommendations, health promotion and prevention strategies, appropriate health resource planning, and research priorities.

An international cross-sectional survey on the Quality and Costs of Primary Care (QUALICO-PC): recruitment and data collection of places delivering primary care across Canada.

BACKGROUND: Performance reporting in primary health care in Canada is challenging because of the dearth of concise and synthesized information. The paucity of information occurs, in part, because the majority of primary health care in Canada is delivered through a multitude of privately owned small businesses with no mechanism or incentives to provide information about their performance. The purpose of this paper is to report the methods used to recruit family physicians and their patients across 10 provinces to provide self-reported information about primary care and how this information could be used in recruitment and data collection for future large scale pan-Canadian and other cross-country studies. METHODS: Canada participated in an international large scale study-the QUALICO-PC (Quality and Costs of Primary Care) study. A set of four surveys, designed to collect in-depth information regarding primary care activities was collected from: practices, providers, and patients (experiences and values). Invitations (telephone, electronic or mailed) were sent to family physicians. Eligible participants were sent a package of surveys. Provincial teams kept records on the number of: invitation emails/letters sent, physicians who registered, practices that were sent surveys, and practices returning completed surveys. Response and cooperation rates were calculated. RESULTS: Invitations to participate were sent to approximately 23,000 family physicians across Canada. A total of 792 physicians and 8,332 patients from 772 primary care practices completed the surveys, including 1,160 participants completing a Patient Values survey and 7,172 participants completing a Patient Experience survey. Overall, the response rate was very low ranging from 2% (British Columbia) to 21% (Nova Scotia). However, the participation rate was high, ranging from 72% (Ontario) to 100% (New Brunswick/Prince Edward Island and Newfoundland & Labrador). CONCLUSIONS: The difficulties obtaining acceptable response rates by family physicians for survey participation is a universal challenge. This response rate for the QUALICO-PC arm in Canada was similar to rates found in other countries such as Australia and New Zealand. Even though most family physicians operate as self-employed small businesses, they could be supported to routinely submit data through a collective effort and provincial mandate. The groundwork in setting up pan-Canadian collaboration in primary care has been established through this study.

Proton pump inhibitors and the risk of hospitalisation for community-acquired pneumonia: replicated cohort studies with meta-analysis.

OBJECTIVE: Previous observational studies suggest that the use of proton pump inhibitors (PPIs) may increase the risk of hospitalisation for community-acquired pneumonia (HCAP). However, the potential presence of confounding and protopathic biases limits the conclusions that can be drawn from these studies. Our objective was, therefore, to examine the risk of HCAP with PPIs prescribed prophylactically in new users of non-steroidal anti-inflammatory drugs (NSAIDs). DESIGN: We formed eight restricted cohorts of new users of NSAIDs, aged ≥40 years, using a common protocol in eight databases (Alberta, Saskatchewan, Manitoba, Ontario, Quebec, Nova Scotia, US MarketScan and the UK's General Practice Research Database (GPRD)). This specific patient population was studied to minimise bias due to unmeasured confounders. High-dimensional propensity scores were used to estimate site-specific adjusted ORs (aORs) for HCAP at 6 months in PPI patients compared with unexposed patients. Fixed-effects meta-analytic models were used to estimate overall effects across databases. RESULTS: Of the 4,238,504 new users of NSAIDs, 2.3% also started a PPI. The cumulative 6-month incidence of HCAP was 0.17% among patients prescribed PPIs and 0.12% in unexposed patients. After adjustment, PPIs were not associated with an increased risk of HCAP (aOR=1.05; 95% CI 0.89 to 1.25). Histamine-2 receptor antagonists yielded similar results (aOR=0.95, 95% CI 0.75 to 1.21). CONCLUSIONS: Our study does not support the proposition of a pharmacological effect of gastric acid suppressors on the risk of HCAP.

Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents.

BACKGROUND: This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs). METHODS: Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen's κ was used to estimate agreement between the two data sources. RESULTS: 23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions. CONCLUSIONS: RAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities.

Measurement of quality and safety in healthcare: the past decade and the next.

The author calls for a critical assessment of the impact of investments made in the measurement of quality and safety, and reflects on whether a reorientation of some of this investment is required to realize the healthcare quality and safety improvement the system seeks. This article also reflects on several Canadian initiatives that have been typical and draws on the experience of health systems that have used measurement to great effect to suggest how investments in healthcare quality and safety measurement should be focused in the future.

Barriers and facilitators of implementing a multicomponent intervention to improve faecal immunochemical test (FIT) colorectal cancer screening in primary care clinics, Alberta.

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) screening is effective at reducing the incidence and mortality of CRC. To address suboptimal CRC screening rates, a faecal immunochemical test (FIT) multicomponent intervention was piloted in four urban multidisciplinary primary care clinics in Alberta from September 2021 to April 2022. The interventions included in-clinic distribution of FIT kits, along with FIT-related patient education and follow-up. This study explored barriers and facilitators to implementing the intervention in four primary clinics using the Consolidated Framework for Implementation Research (CFIR). METHODS: In-depth qualitative semistructured key informant interviews, guided by the CFIR, were conducted with 14 participants to understand barriers and facilitators of the FIT intervention implementation. Key informants were physicians, quality improvement facilitators and clinical staff. Interviews were analysed following an inductive-deductive approach. Implementation barriers and facilitators were organised and interpreted using the CFIR to facilitate the identification of strategies to mitigate barriers and leverage facilitators for implementation at the clinic level. RESULTS: Key implementation facilitators reported by participants were patient perceived needs being met; the clinics' readiness to implement FIT, including staff's motivation, skills, knowledge, and resources to implement; intervention characteristics-evidence-based, adaptable and compatible with existing workflows; regular staff communications; and use of the electronic medical record (EMR) system. Key barriers to implementation were patient's limited awareness of FIT screening for CRC and discomfort with stool sample collection; the impacts of COVID-19 (patients missed appointment, staff coordination and communication were limited due to remote work); and limited clinic capacity (knowledge and skills using EMR system, staff turnover and shortage). CONCLUSION: Findings from the study facilitate the refinement and adaption of future FIT intervention implementation. Future research will explore implementation barriers and facilitators in rural settings and from patients' perspectives to enhance the spread and scale of the intervention.

Predictive performance of comorbidity measures in administrative databases for diabetes cohorts.

BACKGROUND: The performance of comorbidity measures for predicting mortality in chronic disease populations and using ICD-9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with ICD-10 data and for other health outcomes. This study investigated predictive performance of five comorbidity measures for population-based diabetes cohorts in administrative data. The objectives were to evaluate performance for: (a) disease-specific and general health outcomes, (b) data based on the ICD-9 and ICD-10 diagnoses, and (c) different age groups. METHODS: Performance was investigated for heart attack, stroke, amputation, renal disease, hospitalization, and death in all-age and age-specific cohorts. Hospital records, physician billing claims, and prescription drug records from one Canadian province were used to identify diabetes cohorts and measure comorbidity. The data were analysed using multiple logistic regression models and summarized using measures of discrimination, accuracy, and fit. RESULTS: In Cohort 1 (n = 29,058), for which only ICD-9 diagnoses were recorded in administrative data, the Elixhauser index showed good or excellent prediction for amputation, renal disease, and death and performed better than the Charlson index. Number of diagnoses was a good predictor of hospitalization. Similar results were obtained for Cohort 2 (n = 41,925), in which both ICD-9 and ICD-10 diagnoses were recorded in administrative data, although predictive performance was sometimes higher. For age-specific models of mortality, the Elixhauser index resulted in the largest improvement in predictive performance in all but the youngest age group. CONCLUSIONS: Cohort age and the health outcome under investigation, but not the diagnosis coding system, may influence the predictive performance of comorbidity measure for studies about diabetes populations using administrative health data.

An evaluation of data quality in Canada's Continuing Care Reporting System (CCRS): secondary analyses of Ontario data submitted between 1996 and 2011.

BACKGROUND: Evidence informed decision making in health policy development and clinical practice depends on the availability of valid and reliable data. The introduction of interRAI assessment systems in many countries has provided valuable new information that can be used to support case mix based payment systems, quality monitoring, outcome measurement and care planning. The Continuing Care Reporting System (CCRS) managed by the Canadian Institute for Health Information has served as a data repository supporting national implementation of the Resident Assessment Instrument (RAI 2.0) in Canada for more than 15 years. The present paper aims to evaluate data quality for the CCRS using an approach that may be generalizable to comparable data holdings internationally. METHODS: Data from the RAI 2.0 implementation in Complex Continuing Care (CCC) hospitals/units and Long Term Care (LTC) homes in Ontario were analyzed using various statistical techniques that provide evidence for trends in validity, reliability, and population attributes. Time series comparisons included evaluations of scale reliability, patterns of associations between items and scales that provide evidence about convergent validity, and measures of changes in population characteristics over time. RESULTS: Data quality with respect to reliability, validity, completeness and freedom from logical coding errors was consistently high for the CCRS in both CCC and LTC settings. The addition of logic checks further improved data quality in both settings. The only notable change of concern was a substantial inflation in the percentage of long term care home residents qualifying for the Special Rehabilitation level of the Resource Utilization Groups (RUG-III) case mix system after the adoption of that system as part of the payment system for LTC. CONCLUSIONS: The CCRS provides a robust, high quality data source that may be used to inform policy, clinical practice and service delivery in Ontario. Only one area of concern was noted, and the statistical techniques employed here may be readily used to target organizations with data quality problems in that (or any other) area. There was also evidence that data quality was good in both CCC and LTC settings from the outset of implementation, meaning data may be used from the entire time series. The methods employed here may continue to be used to monitor data quality in this province over time and they provide a benchmark for comparisons with other jurisdictions implementing the RAI 2.0 in similar populations.

Implementing Screening, Brief Intervention and Referral Intervention for Health Promotion and Disease Prevention in Hospital Settings in Alberta: A Pilot Study.

Objective: This study assessed the feasibility of implementing screening, brief intervention and referral (SBIR) intervention in hospital settings. Methods: This cross-sectional study evaluated the implementation of the SBIR intervention in a hospital in Alberta for tobacco use, alcohol intake, physical inactivity, and insufficient vegetable and fruit consumption. Patients were interviewed approximately 4-month later to collect data on the acceptability and effectiveness of the intervention received (n = 108). The data were primarily analyzed using descriptive statistics. Results: Of 108 patients, >80% agreed that "they were ok with being screened" for the risk factors during their hospital visit. Up to 68% of patients recalled the provider's brief education. At the follow-up, 20% of patients quit tobacco, 50% reduced alcohol use, 30% increased physical activity, and 25% increased vegetable and fruit intake. Conclusion: Risk factor screening was acceptable for patients. Patients recalled the brief education they received from healthcare providers. Patients reported risk-reducing changes in their risk factors. Our future work will integrate the SBIR approach within the Electronic Clinical Information System and use robust research methods to investigate the impact of SBIR on patients' behavior change.

Patterns of up-to-date status for colorectal cancer screening in Alberta: a cross-sectional study using survey data.

BACKGROUND: Regular screening for colorectal cancer (CRC) reduces its mortality. We explored patterns of use of different CRC screening modalities and quantified the association between having a regular primary care provider and being up to date for CRC screening in a community-based population in Alberta, Canada. METHODS: We conducted a cross-sectional study of adults between 50 and 74 years of age in Alberta, using Canadian Community Health Survey data (2015-2016). We defined being up to date for CRC screening as having completed a fecal occult blood test (FOBT) or fecal immunochemical test (FIT) within the previous 2 years, or having a colonoscopy or sigmoidoscopy in the previous 5 years before the survey. We analyzed data using multivariable logistic regression models. RESULTS: Of 4600 surveyed adults, 62.6% were up to date for CRC screening, with 45.1% having completed a FIT or FOBT (45.1%), and 34.1% having undergone a colonoscopy or sigmoidoscopy. The adjusted odds ratio of being up to date for CRC screening was 0.25 (95% confidence interval 0.17-0.38) and the absolute probability of being up to date for CRC screening was 34.4% lower for adults who had no regular primary care provider, compared with those who had. This pattern was observed in both male and female subgroups. INTERPRETATION: Our findings suggest a suboptimal uptake of CRC screening overall in Alberta, with high disparity between adults with and without a regular primary care provider. The use of customized, multicomponent intervention strategies that are shown to be effective in increasing participation in CRC screening may address this issue.

Interventions to Increase Colorectal Cancer Screening Uptake in Primary Care: A Systematic Review.

OBJECTIVE: We systematically reviewed and summarized previous studies that examined facilitators and barriers to implementing interventions to increase CRCS uptake in primary care practice. METHODS: We searched PubMed, Medline (EBSCO), and CINAHL databases, from the inception of these databases to April 2020. The search strategy combined a set of terms related to facilitators/barriers, intervention implementation, CRCS, and uptake/participation. A priori set inclusion and exclusion criteria were used during both title/abstract screening and full-text screening phases to identify the eligible studies. Quality of the included studies was appraised using quality assessment tools, and data were extracted using a predetermined data extraction tool. We classified facilitators and barriers according to the Consolidated Framework for Implementation Research domains and constructs and identified the common facilitators and barriers looking at how common they were across studies. RESULTS: A total of 12 studies were included in the review. Engagement of the clinic team, leadership team, and partners, clinics' motivation to improve CRCS rates, use of the EMR system, continuous monitoring and feedback system, and having a supportive environment for implementation were the most commonly reported implementation facilitators. Limited time for the clinic team to devote to a new project, challenges in getting accurate, timely data related to CRCS, limited capacity/support to use the EMR system, and disconnect between clinic team members were the most commonly reported implementation barriers. CONCLUSIONS: The synthesized findings improve our understanding of facilitators of and barriers to the implementation of interventions to increase CRCS participation in primary care practice, and inform the customized implementation strategies. Many of the included studies had limited use of rigorous implementation science frameworks to guide their implementation and evaluation, which precludes a comprehensive understanding of the implementation factors specific to CRCS interventions in primary care. Future studies assessing the CRCS intervention implementation factors would benefit from the use of implementation science frameworks.

Comparing comorbidity measures for predicting mortality and hospitalization in three population-based cohorts.

BACKGROUND: Multiple comorbidity measures have been developed for risk-adjustment in studies using administrative data, but it is unclear which measure is optimal for specific outcomes and if the measures are equally valid in different populations. This research examined the predictive performance of five comorbidity measures in three population-based cohorts. METHODS: Administrative data from the province of Saskatchewan, Canada, were used to create the cohorts. The general population cohort included all Saskatchewan residents 20+ years, the diabetes cohort included individuals 20+ years with a diabetes diagnosis in hospital and/or physician data, and the osteoporosis cohort included individuals 50+ years with diagnosed or treated osteoporosis. Five comorbidity measures based on health services utilization, number of different diagnoses, and prescription drugs over one year were defined. Predictive performance was assessed for death and hospitalization outcomes using measures of discrimination (c-statistic) and calibration (Brier score) for multiple logistic regression models. RESULTS: The comorbidity measures with optimal performance were the same in the general population (n = 662,423), diabetes (n = 41,925), and osteoporosis (n = 28,068) cohorts. For mortality, the Elixhauser index resulted in the highest c-statistic and lowest Brier score, followed by the Charlson index. For hospitalization, the number of diagnoses had the best predictive performance. Consistent results were obtained when we restricted attention to the population 65+ years in each cohort. CONCLUSIONS: The optimal comorbidity measure depends on the health outcome and not on the disease characteristics of the study population.