The viral hepatitis B care cascade: A population-based comparison of immigrant groups.

BACKGROUND AND AIMS: The global burden of viral hepatitis B is substantial, and monitoring infections across the care cascade is important for elimination efforts. There is little information on care disparities by immigration status, and we aimed to quantify disease burden among immigrant subgroups. APPROACH AND RESULTS: In this population-based, retrospective cohort study, we used linked laboratory and health administrative records to describe the HBV care cascade in five distinct stages: (1) lifetime prevalence; (2) diagnosis; (3) engagement with care; (4) treatment initiation; and (5) treatment continuation. Infections were identified based on at least one reactive antigen or nucleic acid test, and lifetime prevalence was estimated as the sum of diagnosed and estimated undiagnosed cases. Care cascades were compared between long-term residents and immigrant groups, including subgroups born in hepatitis B endemic countries. Stratified analyses and multivariable Poisson regression were used to identify drivers for cascade progression. Between January 1997 and December 2014, 2,014,470 persons were included, 50,475 with infections, of whom 30,118 were engaged with care, 11,450 initiated treatment, and 6554 continued treatment >1 year. Lifetime prevalence was estimated as 163,309 (1.34%) overall, 115,722 (3.42%) among all immigrants, and 50,876 (9.37%) among those from highly endemic countries. Compared to long-term residents, immigrants were more likely to be diagnosed (adjusted rate ratio [aRR], 4.55; 95% CI, 4.46, 4.63), engaged with care (aRR, 1.07; 95% CI, 1.04, 1.09), and initiate treatment (aRR, 1.09; 95% CI, 1.03, 1.16). CONCLUSIONS: In conclusion, immigrants fared well compared to long-term residents along the care cascade, having higher rates of diagnosis and slightly better measures in subsequent cascade stages, although intensified screening efforts and better strategies to facilitate linkage to care are still needed.

Medication clusters at hospital discharge and risk of adverse drug events at 30 days postdischarge: A population-based cohort study of older adults.

AIMS: Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30-day posthospital discharge. METHODS: All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30-day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics. RESULTS: In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71-84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6-13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12 680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08-1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77-0.87). CONCLUSION: This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri-hospital discharge interventions aimed at reducing ADEs.

Up-to-date on cancer screening among Ontario patients seen by walk-in clinic physicians: A retrospective cohort study.

Walk-in clinics are typically viewed as high-volume locations for managing acute issues but also may serve as a location for primary care, including cancer screening, for patients without a family physician. In this population-based cohort study, we compared breast, cervical and colorectal cancer screening up-to-date status for people living in the Canadian province of Ontario who were formally enrolled to a family physician versus those not enrolled but who had at least one encounter with a walk-in clinic physician in the previous year. Using provincial administrative databases, we created two mutually exclusive groups: i) those who were formally enrolled to a family physician, ii) those who were not enrolled but had at least one visit with a walk-in clinic physician from April 1, 2019 to March 31, 2020. We compared up to date status for three cancer screenings as of April 1, 2020 among screen-eligible people. We found that people who were not enrolled and had seen a walk-in clinic physician in the previous year consistently were less likely to be up to date on cancer screening than Ontarians who were formally enrolled with a family physician (46.1% vs. 67.4% for breast, 45.8% vs. 67.4% for cervical, 49.5% vs. 73.1% for colorectal). They were also more likely to be foreign-born and to live in structurally marginalized neighbourhoods. New methods are needed to enable screening for people who are reliant on walk-in clinics and to address the urgent need in Ontario for more primary care providers who deliver comprehensive, longitudinal care.

Physician antimicrobial prescribing and patient outcomes on general medical wards: a multicentre retrospective cohort study.

BACKGROUND: Variability in antimicrobial prescribing may indicate an opportunity for improvement in antimicrobial use. We sought to measure physician-level antimicrobial prescribing in adult general medical wards, assess the contribution of patient-level factors to antimicrobial prescribing and evaluate the association between antimicrobial prescribing and clinical outcomes. METHODS: Using the General Medicine Inpatient Initiative (GEMINI) database, we conducted a retrospective cohort study of physician-level volume and spectrum of antimicrobial prescribing in adult general medical wards in 4 academic teaching hospitals in Toronto, Ontario, between April 2010 and December 2019. We stratified physicians into quartiles by hospital site based on volume of antimicrobial prescribing (days of therapy per 100 patient-days and antimicrobial-free days) and antibacterial spectrum (modified spectrum score). The modified spectrum score assigns a value to each antibacterial agent based on the breadth of coverage. We assessed patient-level differences among physician quartiles using age, sex, Laboratory-based Acute Physiology Score, discharge diagnosis and Charlson Comorbidity Index. We evaluated the association of clinical outcomes (in-hospital 30-day mortality, length of stay, intensive care unit [ICU] transfer and hospital readmission) with antimicrobial volume and spectrum using multilevel modelling. RESULTS: The cohort consisted of 124 physicians responsible for 124 158 hospital admissions. The median physician-level volume of antimicrobial prescribing was 56.1 (interquartile range 51.7-67.5) days of therapy per 100 patient-days. We did not find any differences in baseline patient characteristics by physician prescribing quartile. The difference in mean prescribing between quartile 4 and quartile 1 was 15.8 days of therapy per 100 patient-days (95% confidence interval [CI] 9.6-22.0), representing 30% higher antimicrobial prescribing in the fourth quartile than the first quartile. Patient in-hospital deaths, length of stay, ICU transfer and hospital readmission did not differ by physician quartile. In-hospital mortality was higher among patients cared for by prescribers with higher modified spectrum scores (odds ratio 1.13, 95% CI 1.04-1.24). INTERPRETATION: We found that physician-level variability in antimicrobial prescribing was not associated with differences in patient characteristics or outcomes in academic general medicine wards. These findings provide support for considering the lowest quartile of physician antimicrobial prescribing within each hospital as a target for antimicrobial stewardship.

Recent functional decline and outpatient follow-up after hospital discharge: a cohort study.

BACKGROUND: Functional decline is common following acute hospitalization and is associated with hospital readmission, institutionalization, and mortality. People with functional decline may have difficulty accessing post-discharge medical care, even though early physician follow-up has the potential to prevent poor outcomes and is integral to high-quality transitional care. We sought to determine whether recent functional decline was associated with lower rates of post-discharge physician follow-up, and whether this association changed during the COVID-19 pandemic, given that both functional decline and COVID-19 may affect access to post-discharge care. METHOD: We conducted a retrospective cohort study using health administrative data from Ontario, Canada. We included patients over 65 who were discharged from an acute care facility during March 1st, 2019 - January 31st, 2020 (pre-COVID-19 period), and March 1st, 2020 - January 31st, 2021 (COVID-19 period), and who were assessed for home care while in hospital. Patients with and without functional decline were compared. Our primary outcome was any physician follow-up visit within 7 days of discharge. We used propensity score weighting to compare outcomes between those with and without functional decline. RESULTS: Our study included 21,771 (pre-COVID) and 17,248 (COVID) hospitalized patients, of whom 15,637 (71.8%) and 12,965 (75.2%) had recent functional decline. Pre-COVID, there was no difference in physician follow-up within 7 days of discharge (Functional decline 45.0% vs. No functional decline 44.0%; RR = 1.02, 95% CI 0.98-1.06). These results did not change in the COVID-19 period (Functional decline 51.1% vs. No functional decline 49.4%; RR = 1.03, 95% CI 0.99-1.08, Z-test for interaction p = 0.72). In the COVID-19 cohort, functional decline was associated with having a 7-day physician virtual visit (RR 1.15; 95% CI 1.08-1.24) and a 7-day physician home visit (RR 1.64; 95% CI 1.10-2.43). CONCLUSIONS: Functional decline was not associated with reduced 7-day post-discharge physician follow-up in either the pre-COVID-19 or COVID-19 periods. In the COVID-19 period, functional decline was positively associated with 7-day virtual and home-visit follow-up.

Characteristics and Health Care Use of Patients Attending Virtual Walk-in Clinics in Ontario, Canada: Cross-sectional Analysis.

BACKGROUND: Funding changes in response to the COVID-19 pandemic supported the growth of direct-to-consumer virtual walk-in clinics in several countries. Little is known about patients who attend virtual walk-in clinics or how these clinics contribute to care continuity and subsequent health care use. OBJECTIVE: The objective of the present study was to describe the characteristics and measure the health care use of patients who attended virtual walk-in clinics compared to the general population and a subset that received any virtual family physician visit. METHODS: This was a retrospective, cross-sectional study in Ontario, Canada. Patients who had received a family physician visit at 1 of 13 selected virtual walk-in clinics from April 1 to December 31, 2020, were compared to Ontario residents who had any virtual family physician visit. The main outcome was postvisit health care use. RESULTS: Virtual walk-in patients (n=132,168) had fewer comorbidities and lower previous health care use than Ontarians with any virtual family physician visit. Virtual walk-in patients were also less likely to have a subsequent in-person visit with the same physician (309/132,168, 0.2% vs 704,759/6,412,304, 11%; standardized mean difference [SMD] 0.48), more likely to have a subsequent virtual visit (40,030/132,168, 30.3% vs 1,403,778/6,412,304, 21.9%; SMD 0.19), and twice as likely to have an emergency department visit within 30 days (11,003/132,168, 8.3% vs 262,509/6,412,304, 4.1%; SMD 0.18), an effect that persisted after adjustment and across urban/rural resident groups. CONCLUSIONS: Compared to Ontarians attending any family physician virtual visit, virtual walk-in patients were less likely to have a subsequent in-person physician visit and were more likely to visit the emergency department. These findings will inform policy makers aiming to ensure the integration of virtual visits with longitudinal primary care.

Development of Multivariable Prediction Models for the Identification of Patients Admitted to Hospital with an Exacerbation of COPD and the Prediction of Risk of Readmission: A Retrospective Cohort Study using Electronic Medical Record Data.

BACKGROUND: Approximately 20% of patients who are discharged from hospital for an acute exacerbation of COPD (AECOPD) are readmitted within 30 days. To reduce this, it is important both to identify all individuals admitted with AECOPD and to predict those who are at higher risk for readmission. OBJECTIVES: To develop two clinical prediction models using data available in electronic medical records: 1) identifying patients admitted with AECOPD and 2) predicting 30-day readmission in patients discharged after AECOPD. METHODS: Two datasets were created using all admissions to General Internal Medicine from 2012 to 2018 at two hospitals: one cohort to identify AECOPD and a second cohort to predict 30-day readmissions. We fit and internally validated models with four algorithms. RESULTS: Of the 64,609 admissions, 3,620 (5.6%) were diagnosed with an AECOPD. Of those discharged, 518 (15.4%) had a readmission to hospital within 30 days. For identification of patients with a diagnosis of an AECOPD, the top-performing models were LASSO and a four-variable regression model that consisted of specific medications ordered within the first 72 hours of admission. For 30-day readmission prediction, a two-variable regression model was the top performing model consisting of number of COPD admissions in the previous year and the number of non-COPD admissions in the previous year. CONCLUSION: We generated clinical prediction models to identify AECOPDs during hospitalization and to predict 30-day readmissions after an acute exacerbation from a dataset derived from available EMR data. Further work is needed to improve and externally validate these models.

Diagnosis of Chronic Hepatitis B Pericomplication: Risk factors and Trends Over Time.

BACKGROUND AND AIMS: Hepatitis B virus (HBV) is a major cause of chronic liver disease, which can progress to cirrhosis, hepatocellular carcinoma, and death. A timely diagnosis allows for antiviral treatment, which can prevent liver-related complications. Conversely, a late diagnosis signals a missed opportunity for earlier care and treatment. Our objective was to measure the proportion of chronic HBV diagnoses that are made within 6 months of presentation with a liver disease-related complication and examine associated factors and trends over time. APPROACH AND RESULTS: We used provincial laboratory data to identify patients with chronic HBV diagnosed from 2003 to 2014. We measured the proportion who experienced a liver disease complication (decompensated cirrhosis, hepatocellular carcinoma, or liver transplant) within ±6 months of their HBV diagnosis date. A multivariable logistic regression model was used to identify factors associated with HBV diagnosis pericomplication. Of 18,434 patients with chronic HBV, 1,279 (6.9%) developed an HBV-related complication during the follow-up period. Among these, 570 (44.6%) had a first diagnosis pericomplication. HBV diagnosis pericomplication did not decrease over time and was independently associated with older age at HBV diagnosis, rural residence, alcohol use, and moderate to high levels of comorbidity. Female patients, immigrants, and those with more outpatient physician visits were less likely to have an HBV diagnosis pericomplication. CONCLUSIONS: A high proportion of patients with HBV-related complications are first diagnosed with HBV pericomplication. These signal missed opportunities for earlier detection and treatment. Our findings support expansion of HBV screening.

Incident Cancer Detection During the COVID-19 Pandemic.

BACKGROUND: Resource restrictions were established in many jurisdictions to maintain health system capacity during the COVID-19 pandemic. Disrupted healthcare access likely impacted early cancer detection. The objective of this study was to assess the impact of the pandemic on weekly reported cancer incidence. PATIENTS AND METHODS: This was a population-based study involving individuals diagnosed with cancer from September 25, 2016, to September 26, 2020, in Ontario, Canada. Weekly cancer incidence counts were examined using segmented negative binomial regression models. The weekly estimated backlog during the pandemic was calculated by subtracting the observed volume from the projected/expected volume in that week. RESULTS: The cohort consisted of 358,487 adult patients with cancer. At the start of the pandemic, there was an immediate 34.3% decline in the estimated mean cancer incidence volume (relative rate, 0.66; 95% CI, 0.57-0.75), followed by a 1% increase in cancer incidence volume in each subsequent week (relative rate, 1.009; 95% CI, 1.001-1.017). Similar trends were found for both screening and nonscreening cancers. The largest immediate declines were seen for melanoma and cervical, endocrinologic, and prostate cancers. For hepatobiliary and lung cancers, there continued to be a weekly decline in incidence during the COVID-19 period. Between March 15 and September 26, 2020, 12,601 fewer individuals were diagnosed with cancer, with an estimated weekly backlog of 450. CONCLUSIONS: We estimate that there is a large volume of undetected cancer cases related to the COVID-19 pandemic. Incidence rates have not yet returned to prepandemic levels.

Incident Cancer Detection During Multiple Waves of COVID-19: The Tsunami After the Earthquake.

No population-based study exists to demonstrate the full-spectrum impact of COVID-19 on hindering incident cancer detection in a large cancer system. Building upon our previous publication in JNCCN, we conducted an updated analysis using 12 months of new data accrued in the pandemic era (extending the study period from September 26, 2020, to October 2, 2021) to demonstrate how multiple COVID-19 waves affected the weekly cancer incidence volume in Ontario, Canada, and if we have fully cleared the backlog at the end of each wave.

"Bring the Hoses to Where the Fire Is!": Differential Impacts of Marginalization and Socioeconomic Status on COVID-19 Case Counts and Healthcare Costs.

OBJECTIVES: Local health leaders and the Director General of the World Health Organization alike have observed that COVID-19 "does not discriminate." Nevertheless, the disproportionate representation of people of low socioeconomic status among those infected resembles discrimination. This population-based retrospective cohort study examined COVID-19 case counts and publicly funded healthcare costs in Ontario, Canada, with a focus on marginalization. METHODS: Individuals with their first positive severe acute respiratory syndrome coronavirus 2 test from January 1, 2020 to June 30, 2020, were linked to administrative databases and matched to negative/untested controls. Mean net (COVID-19-attributable) costs were estimated for 30 days before and after diagnosis, and differences among strata of age, sex, comorbidity, and measures of marginalization were assessed using analysis of variance tests. RESULTS: We included 28 893 COVID-19 cases (mean age 54 years, 56% female). Most cases remained in the community (20 545, 71.1%) or in long-term care facilities (4478, 15.5%), whereas 944 (3.3%) and 2926 (10.1%) were hospitalized, with and without intensive care unit, respectively. Case counts were skewed across marginalization strata with 2 to 7 times more cases in neighborhoods with low income, high material deprivation, and highest ethnic concentration. Mean net costs after diagnosis were higher for males ($4752 vs $2520 for females) and for cases with higher comorbidity ($1394-$7751) (both P < .001) but were similar across levels of most marginalization dimensions (range $3232-$3737, all P ≥ .19). CONCLUSIONS: This study suggests that allocating resources unequally to marginalized individuals may improve equality in outcomes. It highlights the importance of reducing risk of COVID-19 infection among marginalized individuals to reduce overall costs and increase system capacity.

Peri-complication diagnosis of hepatitis C infection: Risk factors and trends over time.

BACKGROUND & AIMS: Hepatitis C virus (HCV) is a common and treatable cause of cirrhosis and its complications, yet many chronically infected individuals remain undiagnosed until a late stage. We sought to identify the frequency of and risk factors for HCV diagnosis peri-complication, that is within six months of an advanced liver disease complication. METHODS: This was a retrospective cohort study of Ontario residents diagnosed with chronic HCV infection between 2003 and 2014. HCV diagnosis peri-complication was defined as the occurrence of decompensated cirrhosis, hepatocellular carcinoma or liver transplant within ±6 months of HCV diagnosis. Multivariable logistic regression was used to identify risk factors for peri-complication diagnosis among all those diagnosed with HCV infection. RESULTS: Our cohort included 39,515 patients with chronic HCV infection, of whom 4.2% (n = 1645) were diagnosed peri-complication; these represented 31.6% of the 5,202 patients who developed complications in the follow-up period. Peri-complication diagnosis became more common over the study period and was associated with increasing age among baby boomers, alcohol use, diabetes mellitus, chronic HBV co-infection and moderate to high levels of morbidity. Female sex, immigrant status, having more previous outpatient physician visits, a previous emergency department visit, a history of drug use or mental health visits were associated with reduced risk of peri-complication diagnosis. CONCLUSIONS: Over a quarter of HCV-infected patients with complications were diagnosed peri-complication. This problem increased over time, suggesting a need to further expand HCV screening.

Viral hepatitis C cascade of care: A population-level comparison of immigrant and long-term residents.

BACKGROUND & AIMS: Viral hepatitis C represents a major global burden, particularly among immigrant-receiving countries such as Canada, where knowledge of disparities in hepatitis C virus among immigrant groups for micro-elimination efforts is lacking. We quantify the hepatitis C cascades of care among immigrants and long-term residents prior to the introduction of direct-acting antiviral medications. METHODS: Using laboratory and health administrative records, we described the hepatitis C virus cascades of care in terms of diagnosis, engagement with care, treatment initiation, and clearance in Ontario, Canada (1997-2014). We stratified the cascade by immigrant and long-term resident groups and identify drivers at each stage using multivariable Poisson regression. RESULTS: We included 940 245 individuals in the study with an estimated hepatitis C prevalence of 167 923 (1.4%) overall, 23 759 (0.7%) among all immigrants, and 6019 (1.1%) among immigrants from hepatitis C endemic countries. Overall there were 104 616 individuals with reactive antibody results, 73 861 tested for viral RNA, 52 388 with viral RNA detected, 50 805 genotyped, 13 159 on treatment and 3919 with evidence of viral clearance. Compared to long-term residents, immigrants showed increased nucleic-acid testing (aRR: 1.09 [95%CI: 1.08, 1.10]), treatment initiation (aRR: 1.46 [95%CI: 1.38, 1.54]), and higher clearance rates (aRR: 1.07 [95%CI: 1.03, 1.11]). CONCLUSIONS: Hepatitis C virus is more prevalent among long-term residents compared to immigrants overall, however, immigrants from endemic countries are an important subgroup to consider for future screening and linkage to care initiatives. These findings are prior to the introduction of newer medications and provide a population-based benchmark for follow-up studies and evaluation of treatment programs and surveillance activities.

Characteristics and outcomes of hospital admissions for COVID-19 and influenza in the Toronto area.

BACKGROUND: Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described. METHODS: We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical-surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19. RESULTS: There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56-4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25-1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25-1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70-1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration. INTERPRETATION: During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.

Effects of hospital funding reform on wait times for hip fracture surgery: a population-based interrupted time-series analysis.

BACKGROUND: Health care funding reforms are being used worldwide to improve system performance but may invoke unintended consequences. We assessed the effects of introducing a targeted hospital funding model, based on fixed price and volume, for hip fractures. We hypothesized the policy change was associated with reduction in wait times for hip fracture surgery, increase in wait times for non-hip fracture surgery, and increase in the incidence of after-hours hip fracture surgery. METHODS: This was a population-based, interrupted time series analysis of 49,097 surgeries for hip fractures, 10,474 for ankle fractures, 1,594 for tibial plateau fractures, and 40,898 for appendectomy at all hospitals in Ontario, Canada between April 2012 and March 2017. We used segmented regression analysis of interrupted monthly time series data to evaluate the impact of funding reform enacted April 1, 2014 on wait time for hip fracture repair (from hospital presentation to surgery) and after-hours provision of surgery (occurring between 1700 and 0700 h). To assess potential adverse consequences of the reform, we also evaluated two control procedures, ankle and tibial plateau fracture surgery. Appendectomy served as a non-orthopedic tracer for assessment of secular trends. RESULTS: The difference (95 % confidence interval) between the actual mean wait time and the predicted rate had the policy change not occurred was - 0.46 h (-3.94 h, 3.03 h) for hip fractures, 1.46 h (-3.58 h, 6.50 h) for ankle fractures, -3.22 h (-39.39 h, 32.95 h) for tibial plateau fractures, and 0.33 h (-0.57 h, 1.24 h) for appendectomy (Figure 1; Table 3). The difference (95 % confidence interval) between the actual and predicted percentage of surgeries performed after-hours - 0.90 % (-3.91 %, 2.11 %) for hip fractures, -3.54 % (-11.25 %, 4.16 %) for ankle fractures, 7.09 % (-7.97 %, 22.14 %) for tibial plateau fractures, and 1.07 % (-2.45 %, 4.59 %) for appendectomy. CONCLUSIONS: We found no significant effects of a targeted hospital funding model based on fixed price and volume on wait times or the provision of after-hours surgery. Other approaches for improving hip fracture wait times may be worth pursuing instead of funding reform.

Who elects the weekend?

Chaim M. Bell and Lauren Lapointe-Shaw discuss the meaning of the "weekend effect" in outcomes for hospital admissions and surgeries, and comment on surprising new results published in PLOS Medicine this week.

Value of routine echocardiography in the management of stroke.

BACKGROUND: Transthoracic echocardiography is routinely performed in patients with stroke or transient ischemic attack (TIA) to help plan secondary stroke management, but recent data evaluating its usefulness in this context are lacking. We sought to evaluate the value of echocardiography for identifying clinically actionable findings for secondary stroke prevention. METHODS: We conducted a multicentre cohort study of patients admitted to hospital with stroke or TIA between 2010 and 2015 at 2 academic hospitals in Toronto, Ontario, Canada. Clinically actionable echocardiographic findings for secondary stroke prevention included cardiac thrombus, patent foramen ovale, atrial myxoma or valvular vegetation. We identified patient characteristics associated with clinically actionable findings using logistic regression. RESULTS: Of the 1862 patients with stroke or TIA we identified, 1272 (68%) had at least 1 echocardiogram. Nearly all echocardiograms were transthoracic; 1097 (86%) were normal, 1 (0.08%) had an atrial myxoma, 2 (0.2%) had a valvular vegetation, 11 (0.9%) had a cardiac thrombus and 66 (5.2%) had a PFO. Patent foramen ovale was less likely among patients older than 60 years (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.20-0.57), with prior stroke or TIA (adjusted OR 0.31, 95% CI 0.09-0.76) or with dyslipidemia (adjusted OR 0.39, 95% CI 0.15-0.84). Among the 130 patients with cryptogenic stroke who had an echocardiogram (n = 110), a PFO was detected in 19 (17%) on transthoracic echocardiogram. INTERPRETATION: Most patients with stroke or TIA had a normal echocardiogram, with few having clinically actionable findings for secondary stroke prevention. Clinically actionable findings, specifically PFO, were more common in patients with cryptogenic stroke.

Prevalence and Costs of Discharge Diagnoses in Inpatient General Internal Medicine: a Multi-center Cross-sectional Study.

BACKGROUND: Understanding the most common and costly conditions treated by inpatient general medical services is important for implementing quality improvement, developing health policy, conducting research, and designing medical education. OBJECTIVE: To determine the prevalence and cost of conditions treated on general internal medicine (GIM) inpatient services. DESIGN: Retrospective cross-sectional study involving 7 hospital sites in Toronto, Canada. PARTICIPANTS: All patients discharged between April 1, 2010 and March 31, 2015 who were admitted to or discharged from an inpatient GIM service. MAIN MEASURES: Hospital administrative data were used to identify diagnoses and costs associated with admissions. The primary discharge diagnosis was identified for each admission and categorized into clinically relevant and mutually exclusive categories using the Clinical Classifications Software (CCS) tool. KEY RESULTS: Among 148,442 admissions, the most common primary discharge diagnoses were heart failure (5.1%), pneumonia (5.0%), urinary tract infection (4.6%), chronic obstructive pulmonary disease (4.5%), and stroke (4.4%). The prevalence of the 20 most common conditions was significantly correlated across hospitals (correlation coefficients ranging from 0.55 to 0.95, p ≤ 0.01 for all comparisons). No single condition represented more than 5.1% of all admissions or more than 7.9% of admissions at any hospital site. The costliest conditions were stroke (median cost $7122, interquartile range 5587-12,354, total cost $94,199,422, representing 6.0% of all costs) and the group of delirium, dementia, and cognitive disorders (median cost $12,831, IQR 9539-17,509, total cost $77,372,541, representing 4.9% of all costs). The 10 most common conditions accounted for only 36.2% of hospitalizations and 36.8% of total costs. The remaining hospitalizations included 223 different CCS conditions. CONCLUSIONS: GIM services care for a markedly heterogeneous population but the most common conditions were similar across 7 hospitals. The diversity of conditions cared for in GIM may be challenging for healthcare delivery and quality improvement. Initiatives that cut across individual diseases to address processes of care, patient experience, and functional outcomes may be more relevant to a greater proportion of the GIM population than disease-specific efforts.

Mediation analysis with a time-to-event outcome: a review of use and reporting in healthcare research.

BACKGROUND: Mediation analysis tests whether the relationship between two variables is explained by a third intermediate variable. We sought to describe the usage and reporting of mediation analysis with time-to-event outcomes in published healthcare research. METHODS: A systematic search of Medline, Embase, and Web of Science was executed in December 2016 to identify applications of mediation analysis to healthcare research involving a clinically relevant time-to-event outcome. We summarized usage over time and reporting of important methodological characteristics. RESULTS: We included 149 primary studies, published from 1997 to 2016. Most studies were published after 2011 (n = 110, 74%), and the annual number of studies nearly doubled in the last year (from n = 21 to n = 40). A traditional approach (causal steps or change in coefficient) was most commonly taken (n = 87, 58%), and the majority of studies (n = 114, 77%) used a Cox Proportional Hazards regression for the outcome. Few studies (n = 52, 35%) mentioned any of the assumptions or limitations fundamental to a causal interpretation of mediation analysis. CONCLUSION: There is increasing use of mediation analysis with time-to-event outcomes. Current usage is limited by reliance on traditional methods and the Cox Proportional Hazards model, as well as low rates of reporting of underlying assumptions. There is a need for formal criteria to aid authors, reviewers, and readers reporting or appraising such studies.

Effectiveness of a financial incentive to physicians for timely follow-up after hospital discharge: a population-based time series analysis.

BACKGROUND: Timely follow-up after hospital discharge may decrease readmission to hospital. Financial incentives to improve follow-up have been introduced in the United States and Canada, but it is unknown whether they are effective. Our objective was to evaluate the impact of an incentive program on timely physician follow-up after hospital discharge. METHODS: We conducted an interventional time series analysis of all medical and surgical patients who were discharged home from hospital between Apr. 1, 2002, and Jan. 30, 2015, in Ontario, Canada. The intervention was a supplemental billing code for physician follow-up within 14 days of discharge from hospital, introduced in 2006. The primary outcome was an outpatient visit within 14 days of discharge. Secondary outcomes were 7-day follow-up and a composite of emergency department visits, nonelective hospital readmission and death within 14 days. RESULTS: We included 8 008 934 patient discharge records. The incentive code was claimed in 31% of eligible visits by 51% of eligible physicians, and cost $17.5 million over the study period. There was no change in the average monthly rate of outcomes in the year before the incentive was introduced compared with the year following introduction: 14-day follow-up (66.5% v. 67.0%, overall p = 0.5), 7-day follow-up (44.9% v. 44.9%, overall p = 0.5) and composite outcome (16.7% v. 16.9%, overall p = 0.2). INTERPRETATION: Despite uptake by physicians, a financial incentive did not alter follow-up after hospital discharge. This lack of effect may be explained by features of the incentive or by extra-physician barriers to follow-up. These barriers should be considered by policymakers before introducing similar initiatives.