Chronic disease prevention and screening outcomes for patients with and without financial difficulty: a secondary analysis of the BETTER WISE cluster randomised controlled trial.

OBJECTIVE: Building on Existing Tools To improvE chronic disease pRevention and screening in primary care Wellness of cancer survIvorS and patiEnts (BETTER WISE) was designed to assess the effectiveness of a cancer and chronic disease prevention and screening (CCDPS) programme. Here, we compare outcomes in participants living with and without financial difficulty. DESIGN: Secondary analysis of a cluster-randomised controlled trial. SETTING: Patients of 59 physicians from 13 clinics enrolled between September 2018 and August 2019. PARTICIPANTS: 596 of 1005 trial participants who responded to a financial difficulty screening question at enrolment. INTERVENTION: 1-hour CCDPS visit versus usual care. OUTCOME MEASURES: Eligibility for a possible 24 CCDPS actions was assessed at baseline and the primary outcome was the percentage of eligible items that were completed at 12-month follow-up. We also compared the change in response to the financial difficulty screening question between baseline and follow-up. RESULTS: 55 of 265 participants (20.7%) in the control group and 69 of 331 participants (20.8%) in the intervention group reported living with financial difficulty. The primary outcome was 29% (95% CI 26% to 33%) for intervention and 23% (95% CI 21% to 26%) for control participants without financial difficulty (p=0.01). Intervention and control participants with financial difficulty scored 28% (95% CI 24% to 32%) and 32% (95% CI 27% to 38%), respectively (p=0.14). In participants who responded to the financial difficulty question at both time points (n=302), there was a net decrease in the percentage of participants who reported financial difficulty between baseline (21%) and follow-up (12%, p<0.001) which was similar in the control and intervention groups. The response rate to this question was only 51% at follow-up. CONCLUSION: The BETTER intervention improved uptake of CCDPS manoeuvres in participants without financial difficulty, but not in those living with financial difficulty. Improving CCDPS for people living with financial difficulty may require a different clinical approach or that social determinants be addressed concurrently with clinical and lifestyle needs or both. TRIAL REGISTRATION NUMBER: ISRCTN21333761.

Patient Experience With Resident Versus Staff Physicians: Results From a Cross-Sectional Patient Survey From Canadian Family Medicine Residencies.

BACKGROUND AND OBJECTIVES: We compared experiences of patients who reported usually being seen by a resident with those usually seen by a staff physician. METHODS: We analyzed responses to a patient experience survey distributed at 13 family medicine teaching practices affiliated with the University of Toronto between May and June 2020. We analyzed responses to seven questions pertaining to timely access, continuity, and patient-centeredness. We compared responses between two types of usual primary care clinicians and calculated odds ratios before and after adjustment for patient characteristics. RESULTS: We analyzed data from 6,545 unique surveys; 18.6% reported their usual clinician was a resident physician. Resident patients were more likely to be older, born outside of Canada, report a high school education or less, and report having difficulty making ends meet. Compared to patients of staff physicians, patients of resident physicians had lower odds of being able to see their preferred primary care clinician and lower odds of getting nonurgent care in a reasonable time. They also had lower odds of reporting patient-centered care, but we found no significant differences in whether the time for an urgent appointment was about right or whether accessing care after hours was easy. CONCLUSIONS: In our setting, patients who reported usually seeing resident physicians had worse continuity of care and timeliness for nonurgent care than patients who reported usually seeing staff physicians despite resident patients being older, sicker, and having a lower socioeconomic position. Postgraduate training programs need to test models to support access and continuity for resident patient panels.

Key informants perspectives on creating a high impact research department in family and community medicine: a qualitative project.

BACKGROUND: Primary care is integral to the health system and population health. Primary care research is still in development and most academic departments lack effective research investments. High impact primary care research programs are needed to advance the field to ensure a robust primary care system for the future. The project objective was to understand key informants' views of structures, functions, and processes required to create a high impact research program in an academic primary care department. METHODS: A descriptive qualitative project with key informants from research programs in primary care. Participants included international research leaders in primary care (n = 10), department of family and community researchers (n = 37) and staff (n = 9) in an academic primary care department, other university leaders (n = 3) and members of the departmental executive leadership team (1 department; 25 members). Semi-structured interviews (n = 27), and focus groups (n = 6) were audio recorded, transcribed, and analyzed using thematic analysis. We used a socioecological framework which described micro, meso, macro levels of influence. RESULTS: At the micro level despite barriers with respect to funding, protected time and lack of formal mentorship, personal motivation was a key factor. At the meso level, the organizational structure that promoted collaboration and a sense of connection emerged as a key factor. Specifically research leaders identified a research faculty development pipeline based on equity, diversity, inclusion, indigeneity, and accessibility principles with thematic areas of focus as key enablers. Lastly, at the macro level, an overarching culture and policies that promoted funding and primary care research was associated with high impact programs. CONCLUSION: The alignment/complementarity of micro, meso, and macro level factors influenced the creation of a high impact research department in primary care. High impact research in primary care is facilitated by the development of researchers through formalized and structured mentorship/sponsorship and a department culture that promote primary care research.

Assessment of Resident and AI Chatbot Performance on the University of Toronto Family Medicine Residency Progress Test: Comparative Study.

BACKGROUND: Large language model (LLM)-based chatbots are evolving at an unprecedented pace with the release of ChatGPT, specifically GPT-3.5, and its successor, GPT-4. Their capabilities in general-purpose tasks and language generation have advanced to the point of performing excellently on various educational examination benchmarks, including medical knowledge tests. Comparing the performance of these 2 LLM models to that of Family Medicine residents on a multiple-choice medical knowledge test can provide insights into their potential as medical education tools. OBJECTIVE: This study aimed to quantitatively and qualitatively compare the performance of GPT-3.5, GPT-4, and Family Medicine residents in a multiple-choice medical knowledge test appropriate for the level of a Family Medicine resident. METHODS: An official University of Toronto Department of Family and Community Medicine Progress Test consisting of multiple-choice questions was inputted into GPT-3.5 and GPT-4. The artificial intelligence chatbot's responses were manually reviewed to determine the selected answer, response length, response time, provision of a rationale for the outputted response, and the root cause of all incorrect responses (classified into arithmetic, logical, and information errors). The performance of the artificial intelligence chatbots were compared against a cohort of Family Medicine residents who concurrently attempted the test. RESULTS: GPT-4 performed significantly better compared to GPT-3.5 (difference 25.0%, 95% CI 16.3%-32.8%; McNemar test: P<.001); it correctly answered 89/108 (82.4%) questions, while GPT-3.5 answered 62/108 (57.4%) questions correctly. Further, GPT-4 scored higher across all 11 categories of Family Medicine knowledge. In 86.1% (n=93) of the responses, GPT-4 provided a rationale for why other multiple-choice options were not chosen compared to the 16.7% (n=18) achieved by GPT-3.5. Qualitatively, for both GPT-3.5 and GPT-4 responses, logical errors were the most common, while arithmetic errors were the least common. The average performance of Family Medicine residents was 56.9% (95% CI 56.2%-57.6%). The performance of GPT-3.5 was similar to that of the average Family Medicine resident (P=.16), while the performance of GPT-4 exceeded that of the top-performing Family Medicine resident (P<.001). CONCLUSIONS: GPT-4 significantly outperforms both GPT-3.5 and Family Medicine residents on a multiple-choice medical knowledge test designed for Family Medicine residents. GPT-4 provides a logical rationale for its response choice, ruling out other answer choices efficiently and with concise justification. Its high degree of accuracy and advanced reasoning capabilities facilitate its potential applications in medical education, including the creation of exam questions and scenarios as well as serving as a resource for medical knowledge or information on community services.

An assessment of marine, estuarine, and riverine habitat vulnerability to climate change in the Northeast U.S.

Climate change is impacting the function and distribution of habitats used by marine, coastal, and diadromous species. These impacts often exacerbate the anthropogenic stressors that habitats face, particularly in the coastal environment. We conducted a climate vulnerability assessment of 52 marine, estuarine, and riverine habitats in the Northeast U.S. to develop an ecosystem-scale understanding of the impact of climate change on these habitats. The trait-based assessment considers the overall vulnerability of a habitat to climate change to be a function of two main components, sensitivity and exposure, and relies on a process of expert elicitation. The climate vulnerability ranks ranged from low to very high, with living habitats identified as the most vulnerable. Over half of the habitats examined in this study are expected to be impacted negatively by climate change, while four habitats are expected to have positive effects. Coastal habitats were also identified as highly vulnerable, in part due to the influence of non-climate anthropogenic stressors. The results of this assessment provide regional managers and scientists with a tool to inform habitat conservation, restoration, and research priorities, fisheries and protected species management, and coastal and ocean planning.

Changes in family medicine visits across sociodemographic groups after the onset of the COVID-19 pandemic in Ontario: a retrospective cohort study.

BACKGROUND: It has been suggested that the COVID-19 pandemic has worsened socioeconomic disparities in access to primary care. Given these concerns, we investigated whether the pandemic affected visits to family physicians differently across sociodemographic groups. METHODS: We conducted a retrospective cohort study using electronic medical records from family physician practices within the University of Toronto Practice-Based Research Network. We evaluated primary care visits for a fixed cohort of patients who were active within the database as of Jan. 1, 2019, to estimate the number of patients who visited their family physician (visitor rate) and the number of distinct visits (visit volume) between Jan. 1, 2019, to June 30, 2020. We compared trends in visitor rate and visit volume during the pandemic (Mar. 14 to June 30, 2020) with the same period in the previous year (Mar. 14 to June 30, 2019) across sociodemographic factors, including age, sex, neighbourhood income, material deprivation and ethnic concentration. RESULTS: We included 365 family physicians and 372 272 patients. Compared with the previous year, visitor rates during the pandemic period dropped by 34.5%, from 357 visitors per 1000 people to 292 visitors per 1000 people. Declines in visit volume during the pandemic were less pronounced (21.8% fewer visits), as the mean number of visits per patient increased during the pandemic (from 1.64 to 1.96). The declines in visitor rate and visit volume varied based on patient age and sex, but not socioeconomic status. INTERPRETATION: Although the number of visits to family physicians dropped substantially during the first few weeks of the COVID-19 pandemic in Ontario, patients from communities with low socioeconomic status did not appear to be disproportionately affected. In this primary care setting, the pandemic appears not to have worsened socioeconomic disparities in access to care.

The association between varying levels of palliative care involvement on costs during terminal hospitalizations in Canada from 2012 to 2015.

BACKGROUND: Inpatient palliative care is associated with lower inpatient costs; however, this has yet to be studied using a more nuanced, multi-tiered measure of inpatient palliative care and a national population-representative dataset. Using a population-based cohort of Canadians who died in hospital, our objectives were to: describe patients' receipt of palliative care and active interventions in their terminal hospitalization; and examine the relationship between inpatient palliative care and hospitalization costs. METHODS: Retrospective cohort study using data from the Discharge Abstract Database in Canada between fiscal years 2012 and 2015. The cohort were Canadian adults (age ≥ 18 years) who died in hospital between April 1st, 2012 and March 31st, 2015 (N = 250,640). The exposure was level of palliative care involvement defined as: medium-high, low, or no palliative care. The main measure was acute care costs calculated using resource intensity weights multiplied by the cost of standard hospital stay, represented in 2014 Canadian dollars (CAD). Descriptive statistics were represented as median (IQR), and n(%). We modelled cost as a function of palliative care using a gamma generalized estimating equation (GEE) model, accounting for clustering by hospital. RESULTS: There were 250,640 adults who died in hospital. Mean age was 76 (SD 14), 47% were female. The most common comorbidities were: metastatic cancer (21%), heart failure (21%), and chronic obstructive pulmonary disease (16%). Of the decedents, 95,450 (38%) had no palliative care involvement, 98,849 (38%) received low involvement, and 60,341 (24%) received medium to high involvement. Controlling for age, sex, province and predicted hospital mortality risk at admission, the cost per day of a terminal hospitalization was: $1359 (95% CI 1323: 1397) (no involvement), $1175 (95% CI 1146: 1206) (low involvement), and $744 (95% CI 728: 760) (medium-high involvement). CONCLUSIONS: Increased involvement of palliative care was associated with lower costs. Future research should explore whether this relationship holds for non-terminal hospitalizations, and whether palliative care in other settings impacts inpatient costs.

Association between high cost user status and end-of-life care in hospitalized patients: A national cohort study of patients who die in hospital.

BACKGROUND: Studies comparing end-of-life care between patients who are high cost users of the healthcare system compared to those who are not are lacking. AIM: The objective of this study was to describe and measure the association between high cost user status and several health services outcomes for all adults in Canada who died in acute care, compared to non-high cost users and those without prior healthcare use. SETTINGS AND PARTICIPANTS: We used administrative data for all adults who died in hospital in Canada between 2011 and 2015 to measure the odds of admission to the intensive care unit (ICU), receipt of invasive interventions, major surgery, and receipt of palliative care during the hospitalization in which the patient died. High cost users were defined as those in the top 10% of acute healthcare costs in the year prior to a person's hospitalization in which they died. RESULTS: Among 252,648 people who died in hospital, 25,264 were high cost users (10%), 112,506 were non-high cost users (44.5%) and 114,878 had no prior acute care use (45.5%). After adjustment for age and sex, high cost user status was associated with a 14% increased odds of receiving an invasive intervention, a 15% increased odds of having major surgery, and an 8% lower odds of receiving palliative care compared to non-high cost users, but opposite when compared to patients without prior healthcare use. CONCLUSIONS: Many patients receive aggressive elements of end-of-life care during the hospitalization in which they die and a substantial number do not receive palliative care. Understanding how this care differs between those who were previously high- and non-high cost users may provide an opportunity to improve end of life care for whom better care planning and provision ought to be an equal priority.

Describing the characteristics and healthcare use of high-cost acute care users at the end of life: a pan-Canadian population-based study.

BACKGROUND: A minority of individuals use a large portion of health system resources, incurring considerable costs, especially in acute-care hospitals where a significant proportion of deaths occur. We sought to describe and contrast the characteristics, acute-care use and cost in the last year of life among high users and non-high users who died in hospitals across Canada. METHODS: We conducted a population-based retrospective-cohort study of Canadian adults aged ≥18 who died in hospitals across Canada between fiscal years 2011/12-2014/15. High users were defined as patients within the top 10% of highest cumulative acute-care costs in each fiscal year. Patients were categorized as: persistent high users (high-cost in death year and year prior), non-persistent high users (high-cost in death year only) and non-high users (never high-cost). Discharge abstracts were used to measure characteristics and acute-care use, including number of hospitalizations, admissions to intensive-care-unit (ICU), and alternate-level-of-care (ALC). RESULTS: We identified 191,310 decedents, among which 6% were persistent high users, 41% were non-persistent high users, and 46% were non-high users. A larger proportion of high users were male, younger, and had multimorbidity than non-high users. In the last year of life, persistent high users had multiple hospitalizations more often than other groups. Twenty-eight percent of persistent high users had ≥2 ICU admissions, compared to 8% of non-persistent high users and only 1% of non-high users. Eleven percent of persistent high users had ≥2 ALC admissions, compared to only 2% of non-persistent high users and < 1% of non-high users. High users received an in-hospital intervention more often than non-high users (36% vs. 19%). Despite representing only 47% of the cohort, persistent and non-persistent high users accounted for 83% of acute-care costs. CONCLUSIONS: High users - persistent and non-persistent - are medically complex and use a disproportionate amount of acute-care resources at the end of life. A greater understanding of the characteristics and circumstances that lead to persistently high use of inpatient services may help inform strategies to prevent hospitalizations and off-set current healthcare costs while improving patient outcomes.

Opioid agonist therapy during residential treatment of opioid use disorder: Cohort study on access and outcomes.

OBJECTIVE: To determine access to opioid agonist therapy (OAT) for those entering residential treatment for opioid use disorder; to report on treatment outcomes for those taking OAT and those not taking OAT; and to determine the association between OAT use and residential treatment completion. DESIGN: Retrospective cohort study. SETTING: Ontario. PARTICIPANTS: Patients with opioid use disorder admitted to publicly funded residential treatment programs in the province of Ontario between January 1, 2013, and December 31, 2016. MAIN OUTCOME MEASURES: Access to OAT during residential treatment using descriptive statistics. Treatment outcomes (ie, completed the program, voluntarily left early, involuntary discharged, and other) for the entire cohort and for the OAT and non-OAT groups using descriptive statistics. Association between OAT use at admission and treatment completion (a binary outcome) using bivariate and multivariate models. RESULTS: Among an identified cohort of 1910 patients with opioid use disorder, 52.8% entered programs that permitted access to OAT. Overall, 56.8% of patients completed treatment, 23.3% voluntarily left early (eg, were no-shows, dropped out), 17.0% were involuntarily discharged, and 2.9% were discharged early for other reasons. Those taking OAT were as likely to complete treatment as those not taking OAT (53.9% vs 57.5%, respectively; adjusted odds ratio of 1.07, 95% CI 0.77 to 1.38). CONCLUSION: This study demonstrates 2 large gaps in care for patients with opioid use disorder. First, these patients have poor access to OAT-the first-line treatment of opioid use disorder-while in publicly funded residential treatment programs; and second, many are involuntarily discharged from treatment. Additionally, this study indicates that patients taking OAT have similar likelihood of completing residential treatment as those not taking OAT do. Limitations of this study are that it is based on observational data for patients who self-selected before admission to use OAT or not, and it is likely not all confounders were accounted for.

Responsiveness to Change of the Montreal Cognitive Assessment, Mini-Mental State Examination, and SCOPA-Cog in Non-Demented Patients with Parkinson's Disease.

BACKGROUND: Clinical monitoring of patients with Parkinson's disease (PD) for cognitive decline is an important element of care. The Montreal Cognitive Assessment (MoCA) has been proposed to be a sensitive tool for assessing cognitive impairment in PD. The aim of our study was to compare the responsiveness of the MoCA to decline in cognition to the responsiveness of the Mini Mental State Examination (MMSE) and the Scales for Outcomes of Parkinson's disease-cognition (SCOPA-Cog). METHODS: PD patients without dementia were enrolled at 6 North American movement disorders centers between 2008 and 2011. Participants received annual evaluations including the MoCA, MMSE, and SCOPA-Cog followed by formal neuropsychological testing. The gold standard for change in cognition was defined as the change on the neuropsychological test scores over the annual assessments. The Reliable Change Method was used to provide an estimate of the probability that a given difference score would be obtained by chance. The sensitivity of the MoCA, MMSE, and SCOPA-Cog to change was quantified using receiver operating characteristics (ROC) curves. RESULTS: One hundred seventeen patients were included in the analysis. Participants were followed at mean intervals of 11 ± 2 months for a median of 2 (maximum 5) visits. According to the reliable change index, 56 intervals of cognitive testing showed a decline in global cognition. ROC analysis of change in MoCA, MMSE, and SCOPA-Cog global scores compared to gold standard testing found an area under the curve (AUC) of 0.55 (95% CI 0.48-0.62), 0.56 (0.48-0.63), and 0.63 (0.55-0.70) respectively. There were no significant differences in the AUCs across the tests. The sensitivity of the MoCA, MMSE, and SCOPA-Cog to change at various thresholds for decline in scores reached a maximum of 71% for a cut-off of 1 point change on the SCOPA-Cog. CONCLUSION: Using neuropsychological testing as a gold standard comparator, the performance of the MoCA, MMSE, and SCOPA-Cog for detecting decline in non-demented PD patients over a 1-year interval is poor. This has implications for clinical practice; stable scores may not be taken as reassurance of the absence of cognitive decline.

The BETTER WISE protocol: building on existing tools to improve cancer and chronic disease prevention and screening in primary care for wellness of cancer survivors and patients - a cluster randomized controlled trial embedded in a mixed methods design.

BACKGROUND: There is a pressing need to reduce the burden of chronic disease and improve healthcare system sustainability through improved cancer and chronic disease prevention and screening (CCDPS) in primary care. We aim to create an integrated approach that addresses the needs of the general population and the special concerns of cancer survivors. Building on previous research, we will develop, implement, and test the effectiveness of an approach that proactively targets patients to attend an individualized CCDPS intervention delivered by a Prevention Practitioner (PP). The objective is to determine if patients randomized to receive an individualized PP visit (vs standard care) have improved cancer surveillance and CCDPS outcomes. Implementation frameworks will help identify and address facilitators and barriers to the approach and inform future dissemination and uptake. METHODS/DESIGN: The BETTER WISE project is a pragmatic two-arm cluster randomized controlled trial embedded in a mixed methods design, including a qualitative evaluation and an economic assessment. The intervention, informed by the expanded chronic care model and previous research, will be refined by engaging researchers, practitioners, policy makers, and patients. The BETTER WISE tool kit includes blended care pathways for cancer survivors (breast, colorectal, prostate) and CCDPS including lifestyle risk factors and screening for poverty. Patients aged 40-65, including both cancer survivors and general population patients, will be randomized at the physician level to an intervention group or to a wait-list control group. Once the intervention is completed, patients randomized to wait-list control will be invited to receive a prevention visit. The main outcome, calculated at 12-months follow-up, will be an individual patient-level summary composite index, defined as the proportion of CCDPS actions achieved relative to those for which the patient was eligible at baseline. A qualitative evaluation will capture information related to program outcome, implementation (facilitators and barriers), and sustainability. An economic assessment will examine the projected cost-benefit impact of investing in the BETTER WISE approach. DISCUSSION: This project builds on existing work and engages end users throughout the process to develop, implement, and determine the effectiveness of a multi-faceted intervention that addresses CCDPS and cancer survivorship in primary care settings. TRIAL REGISTRATION: ISRCTN21333761 . Registered on December 19, 2016.

Does clinical exposure matter? Pilot assessment of patient visits in an urban family medicine residency program.

OBJECTIVE: To determine the number of patient visits, patient demographic information, and diagnoses in an urban ambulatory care setting in a family medicine residency program, and assess the correlation between the number of patient visits and residents' in-training examination (ITE) scores. DESIGN: Retrospective analysis of data from resident practice profiles, electronic medical records, and residents' final ITE scores. SETTING: Family medicine teaching unit in a community hospital in Barrie, Ont. PARTICIPANTS: Practice profile data were from family medicine residents enrolled in the program from July 1, 2013, to June 30, 2014, and electronic medical record and ITE data were from those enrolled in the program from July 1, 2010, to June 30, 2015. MAIN OUTCOME MEASURES: Number of patient visits, patient characteristics (eg, sex, age), priority topics addressed in clinic, resident characteristics (eg, age, sex, level of residency), and residents' final ITE scores. RESULTS: Between July 1, 2013, and June 30, 2014, there were 11 115 patient visits. First-year residents had a mean of 5.48 patient visits per clinic, and second-year residents had a mean of 5.98 patient visits per clinic. A Pearson correlation coefficient of 0.68 was found to exist between the number of patients seen and the final ITE scores, with a 10.5% difference in mean score between residents who had 1251 or more visits and those who had 1150 or fewer visits. Three diagnoses (ie, epistaxis, meningitis, and neck pain) deemed important for Certification by the College of Family Physicians of Canada were not seen by any of the residents in clinic. CONCLUSION: There is a moderate correlation between the number of patients seen by residents in ambulatory care and ITE scores in family medicine. It is important to assess patients' demographic information and diagnoses made in resident practices to ensure an adequate clinical experience.

Use of thyroid-stimulating hormone tests for identifying primary hypothyroidism in family medicine patients.

OBJECTIVE: To assess the use of thyroid-stimulating hormone (TSH) tests for identifying primary hypothyroidism in 2 academic family medicine settings. DESIGN: Descriptive study involving a retrospective electronic chart review of family medicine patients who underwent TSH testing. SETTING: Two academic family practice sites: one site is within a tertiary hospital in Toronto, Ont, and the other is within a community hospital in Newmarket, Ont. PARTICIPANTS: A random sample of 205 adult family medicine patients who had 1 or more TSH tests for identifying potential primary hypothyroidism between July 1, 2009, and September 15, 2013. Exclusion criteria included a previous diagnosis of any thyroid condition or abnormality, as well as pregnancy or recent pregnancy within the year preceding the study period. MAIN OUTCOME MEASURES: The proportion of normal TSH test results and the proportion of TSH tests that did not conform to test-ordering guidelines. RESULTS: Of the 205 TSH test results, 200 (97.6%, 95% CI 94.4% to 99.2%) showed TSH levels within the normal range. All 5 patients with abnormal TSH test results had TSH levels above the upper reference limits. Nearly one-quarter (22.4%, 95% CI 16.9% to 28.8%) of tests did not conform to test-ordering guidelines. All TSH tests classified as not conforming to test-ordering guidelines showed TSH levels within normal limits. There was a significant difference (P < .001) between the proportions of nonconforming TSH tests at the tertiary site (14.3%, 95% CI 8.2% to 22.5%) and the community site (31.0%, 95% CI 22.1% to 41.0%). Preliminary analyses examining which variables might be associated with abnormal TSH levels showed that only muscle cramps or myalgia (P = .0286) and a history of an autoimmune disorder (P = .0623) met or approached statistical significance. CONCLUSION: In this study, the proportion of normal TSH test results in the context of primary hypothyroidism case finding and screening was high, and the overall proportion of TSH tests that did not conform to test-ordering guidelines was relatively high as well. These results highlight a need for more consistent TSH test-ordering guidelines for primary hypothyroidism and perhaps some educational interventions to help curtail the overuse of TSH tests in the family medicine setting.

On the analysis of composite measures of quality in medical research.

Composite endpoints are commonplace in biomedical research. The complex nature of many health conditions and medical interventions demand that composite endpoints be employed. Different approaches exist for the analysis of composite endpoints. A Monte Carlo simulation study was employed to assess the statistical properties of various regression methods for analyzing binary composite endpoints. We also applied these methods to data from the BETTER trial which employed a binary composite endpoint. We demonstrated that type 1 error rates are poor for the Negative Binomial regression model and the logistic generalized linear mixed model (GLMM). Bias was minimal and power was highest in the binomial logistic regression model, the linear regression model, the Poisson (corrected for over-dispersion) regression model and the common effect logistic generalized estimating equation (GEE) model. Convergence was poor in the distinct effect GEE models, the logistic GLMM and some of the zero-one inflated beta regression models. Considering the BETTER trial data, the distinct effect GEE model struggled with convergence and the collapsed composite method estimated an effect, which was greatly attenuated compared to other models. All remaining models suggested an intervention effect of similar magnitude. In our simulation study, the binomial logistic regression model (corrected for possible over/under-dispersion), the linear regression model, the Poisson regression model (corrected for over-dispersion) and the common effect logistic GEE model appeared to be unbiased, with good type 1 error rates, power and convergence properties.

Association between socio-economic status and hemoglobin A1c levels in a Canadian primary care adult population without diabetes.

BACKGROUND: Hgb A1c levels may be higher in persons without diabetes of lower socio-economic status (SES) but evidence about this association is limited; there is therefore uncertainty about the inclusion of SES in clinical decision support tools informing the provision and frequency of Hgb A1c tests to screen for diabetes. We studied the association between neighborhood-level SES and Hgb A1c in a primary care population without diabetes. METHODS: This is a retrospective study using data routinely collected in the electronic medical records (EMRs) of forty six community-based family physicians in Toronto, Ontario. We analysed records from 4,870 patients without diabetes, age 45 and over, with at least one clinical encounter between January 1st 2009 and December 31st 2011 and one or more Hgb A1c report present in their chart during that time interval. Residential postal codes were used to assign neighborhood deprivation indices and income levels by quintiles. Covariates included elements known to be associated with an increase in the risk of incident diabetes: age, gender, family history of diabetes, body mass index, blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and fasting blood glucose. RESULTS: The difference in mean Hgb A1c between highest and lowest income quintiles was -0.04% (p = 0.005, 95% CI -0.07% to -0.01%), and between least deprived and most deprived was -0.05% (p = 0.003, 95% CI -0.09% to -0.02%) for material deprivation and 0.02% (p = 0.2, 95% CI -0.06% to 0.01%) for social deprivation. After adjustment for covariates, a marginally statistically significant difference in Hgb A1c between highest and lowest SES quintile (p = 0.04) remained in the material deprivation model, but not in the other models. CONCLUSIONS: We found a small inverse relationship between Hgb A1c and the material aspects of SES; this was largely attenuated once we adjusted for diabetes risk factors, indicating that an independent contribution of SES to increasing Hgb A1c may be limited. This study does not support the inclusion of SES in clinical decision support tools that inform the use of Hgb A1c for diabetes screening.

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

BACKGROUND: In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. METHODS: In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. RESULTS: If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the response data are generated from a discrete multinomial distribution with support on (0,1). CONCLUSIONS: The linear regression model, the variable-dispersion beta regression model and the fractional logit regression model all perform well across the simulation experiments under consideration. When employing beta regression to estimate covariate effects on (0,1) response data, researchers should ensure their dispersion sub-model is properly specified, else inferential errors could arise.

Improving chronic disease prevention and screening in primary care: results of the BETTER pragmatic cluster randomized controlled trial.

BACKGROUND: Primary care provides most of the evidence-based chronic disease prevention and screening services offered by the healthcare system. However, there remains a gap between recommended preventive services and actual practice. This trial (the BETTER Trial) aimed to improve preventive care of heart disease, diabetes, colorectal, breast and cervical cancers, and relevant lifestyle factors through a practice facilitation intervention set in primary care. METHODS: Pragmatic two-way factorial cluster RCT with Primary Care Physicians' practices as the unit of allocation and individual patients as the unit of analysis. The setting was urban Primary Care Team practices in two Canadian provinces. Eight Primary Care Team practices were randomly assigned to receive the practice-level intervention or wait-list control; 4 physicians in each team (32 physicians) were randomly assigned to receive the patient-level intervention or wait-list control. Patients randomly selected from physicians' rosters were stratified into two groups: 1) general and 2) moderate mental illness. The interventions involved a multifaceted, evidence-based, tailored practice-level intervention with a Practice Facilitator, and a patient-level intervention involving a one-hour visit with a Prevention Practitioner where patients received a tailored 'prevention prescription'. The primary outcome was a composite Summary Quality Index of 28 evidence-based chronic disease prevention and screening actions with pre-defined targets, expressed as the ratio of eligible actions at baseline that were met at follow-up. A cost-effectiveness analysis was conducted. RESULTS: 789 of 1,260 (63%) eligible patients participated. On average, patients were eligible for 8.96 (SD 3.2) actions at baseline. In the adjusted analysis, control patients met 23.1% (95% CI: 19.2% to 27.1%) of target actions, compared to 28.5% (95% CI: 20.9% to 36.0%) receiving the practice-level intervention, 55.6% (95% CI: 49.0% to 62.1%) receiving the patient-level intervention, and 58.9% (95% CI: 54.7% to 63.1%) receiving both practice- and patient-level interventions (patient-level intervention versus control, P < 0.001). The benefit of the patient-level intervention was seen in both strata. The extra cost of the intervention was $26.43CAN (95% CI: $16 to $44) per additional action met. CONCLUSIONS: A Prevention Practitioner can improve the implementation of clinically important prevention and screening for chronic diseases in a cost-effective manner.

Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.

BACKGROUND: Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. METHODS: Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic. RESULTS: The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases. CONCLUSION: Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.