Sex Disparities in Operating Room use Among Cataract Surgeons: A 10-Year Retrospective Population-Based Analysis.

PURPOSE: To evaluate sex differences in operating room (OR) time and case volumes among comprehensive cataract surgeons in Ontario, Canada's most populated province. DESIGN: Retrospective, population-based cohort study. METHODS: Physician billing data of active comprehensive cataract surgeons between 2010 and 2019 were analyzed to identify all cataract surgeries in this timeframe. The number of OR days and case volume were the primary outcomes. Data were stratified by surgeon sex and career stage. RESULTS: Between 2010 and 2019, approximately 1.05 million cataract surgeries were performed in Ontario. There were an average of 195 ± 3 comprehensive cataract surgeons per year, of which 39 ± 5 were female. The proportion of female surgeons increased from 16.8% of all surgeons in 2010 to 24.4% in 2019. The greatest proportion of male surgeons were in the late phase of their career, whereas the greatest proportion of female surgeons were in the early stage of their career. On average, male surgeons had 44.9 ± 1.90 OR days per year and females had 32 ± 1.90 OR days per year, resulting in female surgeons averaging 12.45 ± 1.90 fewer OR days per year. This OR distribution remained consistent across career stages. Average case volumes per OR day were similar across sexes, but male surgeons performed on average 172.7 ± 30.6 more surgeries per year. CONCLUSIONS: Despite performing similar average case volumes per OR day, female surgeons had less OR time compared to their male counterparts per year, and this remained consistent across career stages and over the 10-year period. Metrics for OR allocation and use should be well defined and transparent.

Referring and Specialist Physician Gender and Specialist Billing.

Importance: While a gender pay gap in medicine has been well documented, relatively little research has addressed mechanisms that mediate gender differences in referral income for specialists. Objective: To examine gender-based disparities in medical and surgical specialist referrals in Ontario, Canada. Design, Setting, and Participants: This cross-sectional study included referrals for specialist care ascertained from Ontario Health Insurance Plan physician billings for fiscal year 2018 to 2019. Participants were specialist physicians who received new patient consultations from April 1, 2018, to March 31, 2019, and the associated referring physicians. Data were analyzed from April 2018 to March 2020, including a 12-month follow-up period. Exposures: Specialist and referring physician gender (female or male). Main Outcomes and Measures: Revenue per referral was defined based on an episode-of-care approach as total billings for a 12-month period from the initial consultation. Mean total billings for female and male specialists were compared and the differential divided into the portion owing to referral volume vs referral revenue. Difference-in-differences multivariable regression analysis was used to estimate gender-based differences in revenue per referral. For each referring physician, gender-based differences in referral patterns were examined using case-control analysis, in which specialists who received a referral were compared with matched control specialists who did not receive a referral. This analysis considered the gender of the specialist and concordance between the gender of the referring physician and specialist, among other characteristics. Results: Of 7 621 365 new referrals, 32 824 referring physicians, of whom 13 512 (41.2%) were female (mean [SD] age, 46.3 [11.6] years) and 19 312 (58.8%) were male (mean [SD] age, 52.9 [13.5] years), made referrals to 13 582 specialists, of whom 4890 (36.0%) were female (mean [SD] age, 45.6 [11.0] years) and 8692 (64.0%) were male (mean [SD] age, 51.8 [13.0] years). Male specialists received more mean (SD) referrals than did female specialists (633 [666] vs 433 [515]), and the mean (SD) revenue per referral was higher for males ($350 [$474]) compared with females ($316 [$393]). Adjusted analysis demonstrated a -4.7% (95% CI, -4.9% to -4.5%) difference in the revenue per referral between male and female specialists. Multivariable regression analysis found that physicians referred more often to specialists of the same gender (odds ratio, 1.04; 95% CI, 1.03-1.04) but had higher odds of referring to male specialists (odds ratio, 1.10; 95% CI, 1.09-1.11). Conclusions and Relevance: In this cross-sectional study of the gender pay gap in specialist referral income, the number and revenue from referrals received differed by gender, as did the odds of receiving a referral from a physician of the same gender. Future research should examine the effectiveness of different policies to address this gap, such as a centralized, gender-blinded referral system.

Association between virtual primary care and emergency department use during the first year of the COVID-19 pandemic in Ontario, Canada.

BACKGROUND: Uptake of virtual care increased substantially during the first year of the COVID-19 pandemic. The aim of this study was to evaluate whether a shift from in-person to virtual visits by primary care physicians was associated with increased use of emergency departments among their enrolled patients. METHODS: We conducted an observational study of monthly virtual visits and emergency department visits from Apr. 1, 2020, to Mar. 31, 2021, using administrative data from Ontario, Canada. We used multivariable regression analysis to estimate the association between the proportion of a physician's visits that were delivered virtually and the number of emergency department visits among their enrolled patients. RESULTS: The proportion of virtual visits was higher among female, younger and urban physicians, and the number of emergency department visits was lower among patients of female and urban physicians. In an unadjusted analysis, a 1% increase in a physician's proportion of virtual visits was found to be associated with 11.0 (95% confidence interval [CI] 10.1-11.8) fewer emergency department visits per 1000 rostered patients. After controlling for covariates, we observed no statistically significant change in emergency department visits per 1% increase in the proportion of virtual visits (0.2, 95% CI -0.5 to 0.9). INTERPRETATION: We did not find evidence that patients substituted emergency department visits in the context of decreased availability of in-person care with their family physician during the first year of the COVID-19 pandemic. Future research should focus on the long-term impact of virtual care on access and quality of patient care.

COVID-19 and the duration of operating room procedures in Ontario: a population-based retrospective study.

BACKGROUND: Studies have estimated that a large backlog of procedures was generated by emergency measures implemented in Ontario, Canada, at the onset of the COVID-19 pandemic, when nonessential and scheduled procedures were postponed. Understanding the impact of the COVID-19 pandemic on the time needed to perform a procedure may help to determine the resources needed to tackle the substantial backlog caused by the deferral of cases. The purpose of this study was to examine the duration of operating room (OR) procedures before and after the onset of the COVID-19 pandemic to inform planning around changes in required resources. METHODS: A population-based, retrospective cohort study was conducted using Ontario Health Insurance Plan claims data and other administrative health care data from Apr. 1, 2019, to Sept. 30, 2020. Statistical analysis was conducted using multivariate regression, with procedure duration as the outcome variable. RESULTS: Results showed that the average duration of nonelective procedures increased by 34 minutes during the COVID-19 period and by 19 minutes after the resumption of scheduled procedures. Controlling for physician, patient and hospital characteristics, and the procedure code submitted, procedure duration increased by 12 minutes in the nonelective COVID-19 period and by 5 minutes when scheduled procedures resumed, compared with the pre-COVID-19 period. CONCLUSION: Procedures may take longer in the COVID-19 period. This will affect wait times, which had already increased because of the deferral of procedures at the beginning of the pandemic, and will have an impact on Ontario's ability to provide patients with timely care.

Supply and demographic characteristics of Ontario's ophthalmologists from 2010 to 2019: a population-based analysis.

BACKGROUND: With an aging population in Ontario, ophthalmologists provide most of their care to older adults, which has prominent human resource implications. In this study, we sought to investigate the supply and demographic characteristics of Ontario's ophthalmologists. METHODS: In this retrospective, population-based analysis, we evaluated cohort demographics, including sex and career stage, of Ontario's ophthalmologists from 2010 to 2019, which we reported using descriptive statistics. Similarly, we detailed ophthalmologist supply within different areas of care using descriptive statistics. RESULTS: Over the study period, a median of 464 ophthalmologists were practising in Ontario each year. The proportion of female ophthalmologists increased from 18.7% in 2010 to 24.1% in 2019. The proportion of late-career ophthalmologists (aged > 55 yr) significantly increased by 6.4% over the study period and constituted 45.3% of the workforce in 2019. Comprehensive cataract surgery was the most common area of care. Although the number of ophthalmologists per 100 000 people remained stable over the study period (3.27 ophthalmologists/100 000 people in 2019), the number of ophthalmologists per 100 000 people aged 65 years and older fell by 18.4% from 2010 to 2019. The greatest supply reduction was among moderate-volume comprehensive cataract surgeons (-20.2% overall and -35.4% relative to the population aged ≥ 65 yr). INTERPRETATION: Between 2010 and 2019, the overall number of ophthalmologists in Ontario remained stable; however, we observed declines in the number of ophthalmologists per 100 000 people aged 65 years and older for most areas of care. Nearly half of the ophthalmology workforce is now older than 55 years and female representation is increasing.

Disparities in Physician Compensation by Gender in Ontario, Canada.

Importance: Men and women should earn equal pay for equal work. An examination of the magnitude of pay disparities could inform strategies for remediation. Objective: To examine gender-based differences in pay within a large, comprehensive physician population practicing within a variety of payment systems. Design, Setting, and Participants: This cross-sectional study used data from the Ontario Health Insurance Plan (OHIP) in the 2017 to 2018 fiscal year to estimate differences in gross payments between men and women physicians in Ontario, Canada. Pay gaps were calculated annually and daily. Regression analyses were used to control for observable practice characteristics that could account for individual differences in daily pay. In Canada's largest province, Ontario, medical services are predominantly provided by self-employed physicians who bill the province's single payer, OHIP. All physicians who submitted claims to OHIP were included. Data were analyzed from January 2020 to July 2021. Exposures: Physician gender, obtained from the OHIP Corporate Provider Database. Gender is recorded as male or female. Main Outcomes and Measures: Gross clinical payments were tabulated for individual physicians on a daily and annual basis in conjunction with each physician's practice characteristics, setting, and specialty. Results: A total of 31 481 physicians were included in the study sample (12 604 [40.0%] women; 18 877 [60.0%] men; mean [SD] time since graduation, 23.3 [13.6] years), representing 99% of active physicians in Ontario. The unadjusted differences in clinical payments between male and female physicians were 32.8% (95% CI, 30.8%-34.6%) annually and 22.5% (95% CI, 21.2%-23.8%) daily. After accounting for practice characteristics, region, and specialty, the overall daily payment gap was 13.5% (95% CI, 12.3%-14.8%). The pay gap persisted with differing magnitudes when examined by specialty (ranging from 6.6% to 37.6%), practice setting (8.3% to 17.2%), payment model (13.4% to 22.8% for family medicine; 8.0% to 11.6% for other specialties), and rurality (8.0% to 16.5%). Conclusions and Relevance: This cross-sectional study examined differences in magnitude of annual and daily payment gaps and between unadjusted and adjusted gaps. Comparing the gaps for different specialties, geography, and payment systems illustrated the complexity of the issue by showing that the pay gap varied for physicians in different practice settings. As such, multiple directed interventions will be necessary to ensure that all physicians are paid equally for equal work, regardless of gender.

Adoption of a laboratory EMR system and inappropriate laboratory testing in Ontario: a cross-sectional observational study.

BACKGROUND: Electronic medical record (EMR) systems have the potential to facilitate appropriate laboratory testing. We examined three common medical tests in primary care-hemoglobin A1c (HbA1c), lipid, and thyroid stimulating hormone (TSH)- to assess whether adoption of a laboratory EMR system in Ontario had an impact on the rate of inappropriate testing among primary care physicians. METHODS: We used FY2016-17 population-level laboratory data to estimate the association between adoption of a laboratory EMR system and the rate of inappropriate testing. Inappropriate testing was assessed based on recommendations for screening, monitoring, and follow-up that take into account risk factors related to patient age and certain clinical conditions. To overcome the problem of potential endogeneity of physician choice to use the EMR, the EMR penetration rate in the physician's geographical area of practice was used as an instrumental variable in an ordinary least squares (OLS) regression. We then simulated the change in the rate of inappropriate testing, by physician payment model, as the EMR penetration rate increased from the baseline percentage. RESULTS: The simulation models showed that an increase in the rate of EMR penetration from a baseline average was associated with a statistically significant decrease in inappropriate hbA1c and lipid testing, but a statistically insignificant increase in inappropriate TSH testing. The impact of EMR penetration also varied by payment model. CONCLUSIONS: This study demonstrated a positive association between availability of an EMR system and appropriate service utilization. Varying impacts of the EMR system availability by primary care payment model may be reflective of different incentives or attributes inherent in payment models. Policies to encourage physicians to increase their use of laboratory EMR systems could improve the quality and continuity of patient care.

Trends in prevalence of chronic disease and multimorbidity in Ontario, Canada.

BACKGROUND: New case-mix tools from the Canadian Institute for Health Information offer a novel way of exploring the prevalence of chronic disease and multimorbidity using diagnostic data. We took a comprehensive approach to determine whether the prevalence of chronic disease and multimorbidity has been rising in Ontario, Canada. METHODS: In this observational study, we applied case-mix methodology to a population-based cohort. We used 10 years of patient-level data (fiscal years 2008/09 to 2017/18) from multiple care settings to compute the rolling 5-year prevalence of 85 chronic diseases and multimorbidity (i.e., the co-occurrence of 2 or more diagnoses). Diseases were further classified based on type and severity. We report both crude and age- and sex-standardized trends. RESULTS: The number of patients with chronic disease increased by 11.0% over the 10-year study period to 9.8 million in 2017/18, and the number with multimorbidity increased 12.2% to 6.5 million. Overall increases from 2008/09 to 2017/18 in the crude prevalence of chronic conditions and multimorbidity were driven by population aging. After adjustments for age and sex, the prevalence of patients with ≥ 1 chronic conditions decreased from 70.2% to 69.1%, and the prevalence of multimorbidity decreased from 47.1% to 45.6%. This downward trend was concentrated in minor and moderate diseases, whereas the prevalence of many major chronic diseases rose, along with instances of extreme multimorbidity (≥ 8 conditions). Age- and sex-standardized resource intensity weights, which reflect relative expected costs associated with patient diagnostic profiles, increased 4.6%. INTERPRETATION: Evidence of an upward trend in the prevalence of chronic disease was mixed. However, the change in case mix toward more serious conditions, along with increasing patient resource intensity weights overall, may portend a future need for population health management and increased health system spending above that predicted by population aging.

Effect of Strict and Soft Policy Interventions on Laboratory Diagnostic Testing in Ontario, Canada: A Bayesian Structural Time Series Analysis.

Applications of behavioral economics targeted at optimizing laboratory utilization among physicians have been implemented in Ontario through different types of nonfinancial interventions. Strict policy interventions restrict Ontario Health Insurance Plan (OHIP) payment for tests to patients with specific conditions or limit ordering to particular physician specialties, while soft policy interventions involve modifications to the laboratory requisition form. This study evaluates the effectiveness of these interventions in terms of changing physician ordering behavior for eight tests that were subject to a strict or soft policy intervention during the study period. We use a Bayesian structural time series model applied to Ontario laboratory claims data for FY2006 through FY2017. Results show a 16-75% reduction in laboratory services with a strict policy intervention and an 8-36% reduction in laboratory services with a soft policy intervention. Although the overall magnitude of change was smaller for soft policy interventions, interventions designed with soft or strict policy mechanisms addressing laboratory utilization management are effective at influencing physicians' test ordering behavior.

Use of the Population Grouping Methodology of the Canadian Institute for Health Information to predict high-cost health system users in Ontario.

BACKGROUND: Prior research has consistently shown that the heaviest users account for a disproportionate share of health care costs. As such, predicting high-cost users may be a precondition for cost containment. We evaluated the ability of a new health risk predictive modelling tool, which was developed by the Canadian Institute for Health Information (CIHI), to identify future high-cost cases. METHODS: We ran the CIHI model using administrative health care data for Ontario (fiscal years 2014/15 and 2015/16) to predict the risk, for each individual in the study population, of being a high-cost user 1 year in the future. We also estimated actual costs for the prediction period. We evaluated model performance for selected percentiles of cost based on the discrimination and calibration of the model. RESULTS: A total of 11 684 427 individuals were included in the analysis. Overall, 10% of this population had annual costs exceeding $3050 per person in fiscal year 2016/17, accounting for 71.6% of total expenditures; 5% had costs above $6374 (58.2% of total expenditures); and 1% exceeded $22 995 (30.5% of total expenditures). Model performance increased with higher cost thresholds. The c-statistic was 0.78 (reasonable), 0.81 (strong) and 0.86 (very strong) at the 10%, 5% and 1% cost thresholds, respectively. INTERPRETATION: The CIHI Population Grouping Methodology was designed to predict the average user of health care services, yet performed adequately for predicting high-cost users. Although we recommend the development of a purpose-designed tool to improve model performance, the existing CIHI Population Grouping Methodology may be used - as is or in concert with additional information - for many applications requiring prediction of future high-cost users.

Using Diagnoses to Estimate Health Care Cost Risk in Canada.

OBJECTIVE: Until recently, the options for summarizing Canadian patient complexity were limited to health risk predictive modeling tools developed outside of Canada. This study aims to validate a new model created by the Canadian Institute for Health Information (CIHI) for Canada's health care environment. RESEARCH DESIGN: This was a cohort study. SUBJECTS: The rolling population eligible for coverage under Ontario's Universal Provincial Health Insurance Program in the fiscal years (FYs) 2006/2007-2016/2017 (12-13 million annually) comprised the subjects. MEASURES: To evaluate model performance, we compared predicted cost risk at the individual level, on the basis of diagnosis history, with estimates of actual patient-level cost using "out-of-the-box" cost weights created by running the CIHI software "as is." We next considered whether performance could be improved by recalibrating the model weights, censoring outliers, or adding prior cost. RESULTS: We were able to closely match model performance reported by CIHI for their 2010-2012 development sample (concurrent R=48.0%; prospective R=8.9%) and show that performance improved over time (concurrent R=51.9%; prospective R=9.7% in 2014-2016). Recalibrating the model did not substantively affect prospective period performance, even with the addition of prior cost and censoring of cost outliers. However, censoring substantively improved concurrent period explanatory power (from R=53.6% to 66.7%). CONCLUSIONS: We validated the CIHI model for 2 periods, FYs 2010/2011-2012/2013 and FYs 2014/2015-2016/2017. Out-of-the-box model performance for Ontario was as good as that reported by CIHI for the development sample based on 3-province data (British Columbia, Alberta, and Ontario). We found that performance was robust to variations in model specification, data sources, and time.

Physician Payment Contracts in the Presence of Moral Hazard and Adverse Selection: The Theory and Its Application in Ontario.

We develop a stylized principal-agent model with moral hazard and adverse selection to provide a unified framework for understanding some of the most salient features of the recent physician payment reform in Ontario and its impact on physician behavior. These features include the following: (i) physicians can choose a payment contract from a menu that includes an enhanced fee-for-service contract and a blended capitation contract; (ii) the capitation rate is higher, and the cost-reimbursement rate is lower in the blended capitation contract; (iii) physicians sort selectively into the contracts based on their preferences; and (iv) physicians in the blended capitation model provide fewer services than physicians in the enhanced fee-for-service model. Copyright © 2015 John Wiley & Sons, Ltd.

Risk selection and cost shifting in a prospective physician payment system: evidence from Ontario.

We study the risk-selection and cost-shifting behavior of physicians in a unique capitation payment model in Ontario, using the incentive to enroll and care for complex and vulnerable patients as a case study. This incentive, which is incremental to the regular capitation payment, ceases after the first year of patient enrollment and may therefore impact on the physician's decision to continue to enroll the patient. Furthermore, because the enrolled patients in Ontario can seek care from any provider, the enrolling physician may shift some treatment costs to other providers. Using longitudinal administrative data and a control group of physicians in the fee-for-service model who were eligible for the same incentive, we find no evidence of either patient 'dumping' or cost shifting. These results highlight the need to re-examine the conventional wisdom about risk selection for physician payment models that significantly deviate from the stylized capitation model.

Link between pay for performance incentives and physician payment mechanisms: evidence from the diabetes management incentive in Ontario.

Pay for performance (P4P) incentives for physicians are generally designed as additional payments that can be paired with any existing payment mechanism such as a salary, fee-for-services and capitation. However, the link between the physician response to performance incentives and the existing payment mechanisms is still not well understood. In this article, we study this link using the recent primary care physician payment reform in Ontario as a natural experiment and the Diabetes Management Incentive as a case study. Using a comprehensive administrative data strategy and a difference-in-differences matching strategy, we find that physicians in a blended capitation model are more responsive to the Diabetes Management Incentive than physicians in an enhanced fee-for-service model. We show that this result implies that the optimal size of P4P incentives vary negatively with the degree of supply-side cost-sharing. These results have important implications for the design of P4P programs and the cost of their implementation.

Enhanced fee-for-service model and physician productivity: evidence from Family Health Groups in Ontario.

We study an enhanced fee-for-service model for primary care physicians in the Family Health Groups (FHG) in Ontario, Canada. In contrast to the traditional fee-for-service (FFS) model, the FHG model includes targeted fee increases, extended hours, performance-based initiatives, and patient enrolment. Using a long panel of claims data, we find that the FHG model significantly increases physician productivity relative to the FFS model, as measured by the number of services, patient visits, and distinct patients seen. We also find that the FHG physicians have lower referral rates and treat slightly more complex patients than the comparable FFS physicians. These results suggest that the FHG model offers a promising alternative to the FFS model for increasing physician productivity.