Shah, Nilay D.

AbstractObjectiveTo test the hypotheses that use of the Head CT Choice decision aid would be similarly effective in all parent/patient dyads but parents with high (vs low) numeracy experience a greater increase in knowledge while those with low (vs high) health literacy experience a greater increase in trust.MethodsThis was a secondary analysis of a cluster randomized trial conducted at seven sites. One hundred seventy‐two clinicians caring for 971 children at intermediate risk for clinically important traumatic brain injuries were randomized to shared decision making facilitated by the DA (n = 493) or to usual care (n = 478). We assessed for subgroup effects based on patient and parent characteristics, including socioeconomic status (health literacy, numeracy and income). We tested for interactions using regression models with indicators for arm assignment and study site.ResultsThe decision aid did not increase knowledge more in parents with high numeracy (P for interaction [Pint] = 0.14) or physician trust more in parents with low health literacy (Pint = 0.34). The decision aid decreased decisional conflict more in non‐white parents (decisional conflict scale, −8.14, 95% CI: −12.33 to −3.95; Pint = 0.05) and increased physician trust more in socioeconomically disadvantaged parents (trust in physician scale, OR: 8.59, 95% CI: 2.35‐14.83; Pint = 0.04).ConclusionsUse of the Head CT Choice decision aid resulted in less decisional conflict in non‐white parents and greater physician trust in socioeconomically disadvantaged parents. Decision aids may be particularly effective in potentially vulnerable parents.

AbstractImportanceIt is critical to develop a better understanding of the strategies provider organizations use to improve the performance of frontline clinicians and whether ACO participation is associated with differential adoption of these tools.ObjectivesCharacterize the strategies that physician practices use to improve clinician performance and determine their association with ACOs and other payment reforms.Data SourcesThe National Survey of Healthcare Organizations and the National Survey of ACOs fielded 2017‐2018 (response rates = 47 percent and 48 percent).Study DesignDescriptive analysis for practices participating and not participating in ACOs among 2190 physician practice respondents. Linear regressions to examine characteristics associated with counts of performance domains for which a practice used data for feedback, quality improvement, or physician compensation as dependent variables. Logistic and fractional regression to examine characteristics associated with use of peer comparison and shares of primary care and specialist compensation accounted for by performance bonuses, respectively.Principal FindingsACO‐affiliated practices feed back clinician‐level information and use it for quality improvement and compensation on more performance domains than non‐ACO‐affiliated practices. Performance measures contribute little to physician compensation irrespective of ACO participation.ConclusionACO‐affiliated practices are using more performance improvement strategies than other practices, but base only a small fraction of compensation on quality or cost.

BackgroundPrior studies in oncology have shown that a higher annual facility patient volume is associated with reduced mortality. Because classic Hodgkin lymphoma is uncommon but highly curable, this study used the National Cancer Database (2003‐2014) to analyze whether such a relationship exists for this disease.MethodsThe facilities were classified by quartiles, and random intercepts were used to account for clustering of patients within facilities. A Cox regression model was used to determine the volume‐outcome relationship.ResultsThere were 47,633 patients with classic Hodgkin lymphoma treated at 1310 facilities. The first quartile (Q1), which included 58.4% of the facilities, treated 3 or fewer patients per year, whereas the fourth quartile (Q4), which included 5.9% of the facilities, treated more than 9 patients per year. Compared with the patients treated at Q4 facilities, those treated at lower quartile facilities had a higher risk of death (hazard ratio for the third quartile [HR], 1.19; 95% confidence interval [CI], 1.1‐1.29; HR for the second quartile, 1.28; 95% CI, 1.19‐1.38; HR for Q1, 1.29; 95% CI, 1.2‐1.39) after adjustments for all other factors (P < .0001). Compared with facilities treating 10 patients per year, facilities treating 40 patients per year had approximately 27% lower overall mortality rates.ConclusionsPatients with classic Hodgkin lymphoma treated at high‐volume centers had lower overall mortality than those treated at lower volume centers. Because this is a highly curable malignancy, such differences may suggest a benefit from referral to higher volume facilities or the emulation of their care models.

Objective: Experts cautioned that patients affected by the November 2010 withdrawal of the opioid analgesic propoxyphene might receive riskier prescriptions. To explore this, we compared drug receipts and outcomes among propoxyphene users before and aftermarket withdrawal. Study Design: Using OptumLabs data, we studied 3 populations: commercial, Medicare Advantage (MA) aged (age 65+ y) and MA disabled (age below 65 y) enrollees. The exposed enrollees received propoxyphene in the 3 months before market withdrawal (n=13,622); historical controls (unexposed) received propoxyphene 1 year earlier (n=9971). Regression models estimated daily milligrams morphine equivalent (MME), daily prescription acetaminophen dose, potentially toxic acetaminophen doses, nonopioid prescription analgesics receipt, emergency room visits, and diagnosed falls, motor vehicle accidents, and hip fractures. Principal Findings: Aged MA enrollees illustrate the experience of all 3 populations examined. Following the market withdrawal, propoxyphene users in the exposed cohort experienced an abrupt decline of 69% in average daily MME, compared with a 14% decline in the unexposed. Opioids were discontinued by 34% of the exposed cohort and 18% of the unexposed. Tramadol and hydrocodone were the most common opioids substituted for propoxyphene. The proportion of each group receiving ≥4 g of prescription acetaminophen per day decreased from 12% to 2% in the exposed group but increased from 6% to 8% among the unexposed. Adverse events were rare and not significantly different in exposed versus unexposed groups. Conclusions: After propoxyphene market withdrawal, many individuals experienced abrupt discontinuation of opioids. Policymakers might consider supporting appropriate treatment transitions and monitoring responses following drug withdrawals.

Abstract Background Hodgkin lymphoma is a rare hematological malignancy, with 8,500 new cases per year in the United States. Prior studies in oncology have shown that higher patient volume, whether at the treatment facility or provider level, is associated with reduced mortality and improved overall survival (OS). We used a national oncology data set to test our hypothesis that a volume-outcome relationship may also exist in classical Hodgkin lymphoma. Methods Using the National Cancer Data Base (NCDB), we identified patients diagnosed with classical Hodgkin lymphoma between 2003 and 2014. The NCDB is a nationwide oncology outcomes database for ~70% of newly diagnosed cases from more than 1,500 accredited cancer programs in the United States and Puerto Rico. We classified the facilities by quartiles (Q; mean patients with HL treated per year): Q1: < 3.19, Q2: 3.2 to 5.0, Q3: 5.01 to 9.19, and Q4: ≥9.2. Our primary outcome of interest was all-cause mortality. We used random intercepts to account for clustering of patients within facilities and a Cox regression model to determine the volume-outcome relationship, adjusting for demographic (sex, age, race, ethnicity), socioeconomic (income, education, insurance type), geographic (area of residence, treatment facility location, travel distance), and comorbid (Charlson-Deyo score) factors, as well as year of diagnosis. Kaplan-Meier analysis was performed to examine the impact of patient volume (by quartile) on overall survival. Results There were 47,633 patients with classical Hodgkin lymphoma treated at 1,310 facilities. The median age at diagnosis was 40 years, and 54.2% were men. The median annual facility volume was 2.7 patients per year (range, 1 to 42.8). The distribution of facilities according to patient volume was: Q1: 58.4%, Q2: 22.4%, Q3: 13.3%, and Q4: 5.9%. After a median follow-up of 58 months, the highest volume quartile (Q4) had significantly higher 5- and 12-year overall survival rates compared to Q1-Q3 (Table 1). Overall survival by quartile is depicted as a Kaplan-Meier curve (Figure 1). Compared to the patients treated at Q4 facilities, those treated at lower-quartile facilities had a higher risk of death (Q3 hazard ratio [HR], 1.18 [95% CI, 1.10 to 1.27]; Q2 HR, 1.21 [95% CI, 1.13 to 1.30]; Q1 HR, 1.19 [95% CI, 1.11 to 1.28]) after adjustment for the sociodemographic factors discussed in our methods. Multivariable analysis showed that facility volume as a continuous variable was independently associated with all-cause mortality (Figure 2) (P<0.0001). Compared with facilities treating 10 patients per year, facilities treating 20, 30, and 40 patients per year had approximately 10%, 17%, and 23% lower overall mortality rates. Conclusions Patients treated for classical Hodgkin lymphoma at higher-volume facilities had a lower risk of mortality compared with those treated at lower-volume facilities. This adds to the growing body of evidence that a volume-outcomes relationship exists in some of the less common hematologic malignancies. Further research is needed to ascertain whether such differences in survival are related to provider-level or facility-level attributes, and whether patients with Hodgkin lymphoma will benefit from referral to high-volume centers. Disclosures No relevant conflicts of interest to declare.

Abstract Breast cancer survivorship guidelines recommend at least annual follow-up visits, yet the degree to which this occurs in clinical practice is uncertain. Claims data from a US commercial insurance database (OptumLabs) were used to identify women treated with curative intent surgery for newly diagnosed breast cancer between 2006 and 2014. In 25 035 women, median follow-up was 3 years. In the second year after surgery, 9.6% of the patients did not visit a primary care provider, an oncologist, or a surgeon (guideline-nonadherent). The guideline-nonadherent proportion increased from 7.8% in women diagnosed in 2006 to 12.2% in those diagnosed in 2014 (two-sided Wald P &lt; .001). During years 2–6, guideline-nonadherence was also associated with older age, nonwhite race, no radiation, no chemotherapy, no endocrine therapy, and increasing time after surgery. There is a substantial and increasing rate of inadequate follow-up among breast cancer survivors. This has the potential to impair outcomes.

Abstract Background: Non-Hodgkin lymphoma (NHL) is a relatively uncommon cancer with annual incidence of ~70,000 cases but with over 50 distinct subtypes. The goal of this study was to determine the extent to which the number of NHL patients treated annually in a facility (facility volume) affects overall survival (OS). This study used the National Cancer Data Base (NCDB), a nationwide oncology database covering 70% of the US cancer population, to address this question. Methods: We used the NCDB to identify patients with NHL diagnosed from 1998 to 2006. Year 2006 was used as a cut-off in order to allow a minimum of five years of follow-up for all patients. Only patients treated at facilities with continuous annual reporting to NCDB were included. We classified treatment facilities by quartiles based on facility volume (mean patients/year): Quartile 1 (Q1: 2-13), Quartile 2 (Q2: 14-20), Quartile 3 (Q3: 21-32) and Quartile 4 (Q4: ≥33). We used Pearson correlation methods to examine collinearity, unadjusted Kaplan-Meier methods to estimate OS rates, log rank test to compare survival distributions, and multivariable Cox proportional hazards model to examine the associations between hospital volume and OS adjusting for other covariates of interest. We also included random effects for hospital to more fully adjust for clustering of outcomes within hospitals. To examine non-linear effects of hospital volume, we utilized smoothing splines. Results: There were 278,985 NHL patients cared for at 1,151 facilities. The distribution of patients according to facility volume was Q1 (10.7%), Q2 (13.5%), Q3 (23.3%) and Q4 (52.5%) and according to facility type was academic (31.2%), comprehensive community (55.9%), community (10.6%) and other (2.3%) centers. The unadjusted median OS by facility volume was: Q1: 61.8 months, Q2: 65.9 months, Q3: 71.4 months and Q4: 83.6 months. After multivariable analysis adjusting for demographic (sex, age, race, ethnicity), socioeconomic (income, insurance type), geographic (area of residence), disease-specific (NHL subtype, stage) and facility-specific (type and location) factors, we show that facility volume remains an independent predictor of all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower quartile facilities had a worse OS (Q3HR: 1.05 [95% CI, 1.04-1.06]; Q2HR: 1.08 [1.07-1.10]; Q1HR: 1.14 [1.11-1.17]). We adjusted for hospital as a random effect, performed sensitivity analyses removing primary payor and facility type (due to collinearity with age and facility volume, respectively), and adjusted for Charlson-Deyo co-morbidity score (available only for patients diagnosed after 2003) in secondary models and found similar results. Using smoothing splines, we found a significant non-linear effect of hospital volume on OS (P &lt;0.001). This is depicted in the Figure wherein the hazard ratio of 1.0 corresponded to the average predicted hazard, which occurred at a hospital volume of 59 patients per year. Conclusions: Patients who were treated for NHL at higher volume facilities had longer OS than those who were treated at facilities with a lower volume. This is the first study in the US using a national sample to show that a volume-outcome relationship exists in the medical management of cancer. Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.