Did the COVID-19 pandemic result in more family physicians stopping practice? Results from Ontario, Canada

AbstractPurposeTo understand changes in family physician practice patterns and whether more family physicians stopped working during the COVID-19 pandemic compared to previous years.MethodsWe analyzed administrative data from Ontario, Canada two ways: cross-sectional and longitudinal. First, we identified the percentage and characteristics of all family physicians who had a minimum of 50 billing days in 2019 but no billings during the first six months of the pandemic. Second, for each year from 2010 to 2020, we calculated the percentage of physicians who billed for services in the first quarter of the calendar year but submitted no bills between April and September of the given year.ResultsWe found 3.1% of physicians working in 2019 (N=385/12,247) reported no billings in the first six months of the pandemic. Compared with other family physicians, a higher portion were age 75 or older (13.0% vs. 3.4%, p<0.001), had fee-for-service reimbursement (38% vs 25%, p<0.001), and had a panel size under 500 patients (40% vs 25%, p<0.001). Between 2010 and 2019, an average of 1.6% of physicians who practiced in the first quarter had no billings in each of the second and third quarters of the calendar year compared to 3.0% in 2020 (p<0.001).ConclusionsApproximately twice as many family physicians stopped work in Ontario, Canada during COVID-19 compared to previous years, but the absolute number was small and those who did had smaller patient panels. More research is needed to understand the impact on primary care attachment and access to care.

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P3-211: Improving dementia care in primary care: Impact of a training program on physician practice patterns

Alzheimer s & Dementia ◽

10.1016/j.jalz.2013.05.1284 ◽

2013 ◽

Vol 9 ◽

pp. P633-P633

Author(s):

Philip Sloane ◽

Christine Lathren ◽

David Reed ◽

Daniel Kaufer ◽

Sheryl Zimmerman

Keyword(s):

Primary Care ◽

Training Program ◽

Practice Patterns ◽

Dementia Care ◽

Physician Practice ◽

Physician Practice Patterns

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PSA screening: determinants of primary-care physician practice patterns

Prostate Cancer and Prostatic Diseases ◽

10.1038/pcan.2011.59 ◽

2011 ◽

Vol 15 (2) ◽

pp. 189-194 ◽

Cited By ~ 17

Author(s):

G E Tasian ◽

M R Cooperberg ◽

M B Potter ◽

J E Cowan ◽

K L Greene ◽

...

Keyword(s):

Primary Care ◽

Primary Care Physician ◽

Practice Patterns ◽

Care Physician ◽

Physician Practice ◽

Physician Practice Patterns ◽

Psa Screening

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Prevention in Primary Care: Variability in Physician Practice Patterns in New York City

American Journal of Preventive Medicine ◽

10.1016/s0749-3797(18)31333-3 ◽

1986 ◽

Vol 2 (4) ◽

pp. 226-234 ◽

Cited By ~ 62

Author(s):

Donald H. Gemson ◽

Jack Elinson

Keyword(s):

Primary Care ◽

New York ◽

New York City ◽

York City ◽

Practice Patterns ◽

Physician Practice ◽

Physician Practice Patterns

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Physician Practice Patterns in Holding Inflammatory Bowel Disease Medications due to COVID-19, in the SECURE-IBD Registry

Journal of Crohn s and Colitis ◽

10.1093/ecco-jcc/jjaa243 ◽

2020 ◽

Author(s):

Manasi Agrawal ◽

Erica J Brenner ◽

Xian Zhang ◽

Jean-Frederic Colombel ◽

Michael D Kappelman ◽

...

Keyword(s):

Inflammatory Bowel Disease ◽

Bowel Disease ◽

Practice Patterns ◽

Physician Practice ◽

Physician Practice Patterns ◽

Aminosalicylic Acid ◽

Factor Therapy ◽

Multivariable Analyses ◽

Inflammatory Bowel ◽

The Impact

Abstract Background We aimed to describe physician practice patterns in holding or continuing IBD therapy in the setting of COVID-19 infection, using the Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease [SECURE-IBD] registry. Methods IBD medications that were stopped due to COVID-19 were recorded in the SECURE-IBD registry in addition to demographic and clinical data. We conducted descriptive analyses to understand characteristics associated with stopping IBD medications in response to active COVID-19 infection. Results Of 1499 patients, IBD medications were stopped in 518 [34.6%] patients. On bivariate and multivariable analyses, a diagnosis of ulcerative colitis or IBD-unspecified was associated with a lower odds of stopping medication compared with Crohn’s disease (adjusted odds ratio [aOR] 0.6, 95% confidence interval [CI] 0.48, 0.75). When evaluating specific medications, 5-aminosalicylic acid was more likely to be continued [p <0.001] whereas anti-tumour necrosis factor therapy and immunomodulator therapy were more likely to be stopped [global p <0.001]. Other demographic and clinical characteristics did not affect prescription patterns. Conclusions IBD medications other than immunomodulators were continued in the majority of IBD patients with COVID-19, in the international SECURE-IBD registry. Future studies are needed to understand the impact of stopping or continuing IBD medications on IBD- and COVID-19 related outcomes.

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Time modifier billing code - an interrupted time series analysis

Canadian Journal of Emergency Nursing ◽

10.29173/cjen137 ◽

2021 ◽

Vol 44 (2) ◽

pp. 17

Author(s):

Terrence McDonald ◽

Brendan Lethebe ◽

Alistair McGuire ◽

Lee Green

Keyword(s):

Primary Care ◽

Time Series ◽

Family Physicians ◽

Primary Care Providers ◽

Emergency Department Visits ◽

Fee For Service ◽

Care Providers ◽

Interrupted Time Series Analysis ◽

Cross Sectional ◽

Billing Code

Time modifier billing code: Interrupted time series analysis. Terrence McDonald, Brendan Cord Lethebe, Alistair McGuire, Lee Green Background: Alberta has the highest percentage of fee-for-service Family Physicians in Canada at over 80%. In 2019 as part of a cost containment strategy, the Alberta government proposed a policy change to eliminate the most used fee code that compensates family physicians for extended visit times (16-25 minutes). Optimal length for patient visit times varies throughout the world and countries with health systems that place emphasis on relational continuity demonstrate a trend towards longer appointment times. In Canada, the relationship between visit length and outcomes is not known. Implementation: What would be the likely consequences of eliminating the extended visit code? We examined this question using two different observational methods, to improve confidence in our findings: a retrospective longitudinal cohort (time series) around the time the code was introduced in 2009, and a cross-sectional cohort at current time. We explored the usage patterns of that fee code, its association with the outcomes of emergency department visits and hospitalizations, along with physician billings. Results: We found rates of emergency department visits decreased after the time-modifier code was implemented starting in 2010. This effect was maintained in the years that followed. A similar but less pronounced effect was observed in the hospitalization rates. The cross-sectional analysis had to include an interaction term because family physicians selectively extend visits for patients at risk, but when that is accounted for, the same effect is observed as in longitudinal results. The code was not used ubiquitously among primary care providers, especially in rural areas. Female physicians used it more often. Users use it for an average of 40% of 03.03A office visits. Non-users of the code earned more income than their user-colleagues. Conclusion: We believe our findings will fill an important gap in informing the importance of an extended time service billing code in a fee-for-service system in reducing ED visits and hospitalizations. Advice and Lessons Learned: The fee-for-service time-modifier code, introduced in 2009, resulted in reduced ED visits and hospitalizations. It is likely that discontinuing the code would result in increased ED and hospital utilization, costing much more than removing the code would save. Usage of the time-modifier code was not uniform among primary care. Users of the code had different practice patterns and provider demographics. Our next step is to model the uptake of the code by primary care providers and explore the health system utilization and down-stream costs between users and non-users of the code.

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