Savitz, Samuel T.

AbstractObjectiveTo evaluate the impact of a virtual registered nurse (ViRN) model on safety and care outcomes. ViRN is a telemedicine intervention that enables an experienced virtual nurse to assist the in‐person care team in providing care to patients.Data Sources and Study SettingElectronic health records data were utilized from the Mayo Clinic during the intervention (December 2020–November 2021) and historical periods (December 2018–November 2019). ViRN was implemented on general medical units at the Mayo Clinic Rochester. We used general medical units at the Mayo Clinic Arizona as the comparison group.Study DesignThis study used a difference‐in‐differences design to evaluate the impact of ViRN compared to usual care on transfer to the intensive care unit (ICU), inpatient mortality, and length of stay (LOS). We used logistic regression for transfer to the ICU and inpatient mortality and negative binomial regression for LOS. We controlled for demographics, patient interaction with the health system, clinical characteristics, and admission characteristics. We clustered standard errors to account for patients who have multiple admissions during the study period.Principal FindingsThere were no significant differences for transfer to the ICU (average marginal effect (AME) −0.08 percentage point [95% confidence interval (CI): −1.34, 1.18]), inpatient mortality (AME 0.43 percentage point [95% CI: −0.33, 1.18]), or LOS (AME −0.20 days [95% CI: −0.57, 0.17]). The findings were mostly consistent across the sensitivity analyses.ConclusionsOur results suggest that ViRN led to similar outcomes as usual care in general medical units. These findings support the potential to develop more advanced models of ViRN at the Mayo Clinic and the dissemination of the ViRN model to other systems. In the context of staffing shortages and other disruptions to the delivery of nursing care, it is critical to understand whether new models like ViRN provide nurse staffing alternatives without negatively affecting outcomes.

Background Among patients with heart failure (HF), social risk factors (SRFs) are associated with poor outcomes. However, less is known about how co‐occurrence of SRFs affect all‐cause health care utilization for patients with HF. The objective was to address this gap using a novel approach to classify co‐occurrence of SRFs. Methods and Results This was a cohort study of residents living in an 11‐county region of southeast Minnesota, aged ≥18 years with a first‐ever diagnosis for HF between January 2013 and June 2017. SRFs, including education, health literacy, social isolation, and race and ethnicity, were obtained via surveys. Area‐deprivation index and rural‐urban commuting area codes were determined from patient addresses. Associations between SRFs and outcomes (emergency department visits and hospitalizations) were assessed using Andersen‐Gill models. Latent class analysis was used to identify subgroups of SRFs; associations with outcomes were examined. A total of 3142 patients with HF (mean age, 73.4 years; 45% women) had SRF data available. The SRFs with the strongest association with hospitalizations were education, social isolation, and area‐deprivation index. We identified 4 groups using latent class analysis, with group 3, characterized by more SRFs, at increased risk of emergency department visits (hazard ratio [HR], 1.33 [95% CI, 1.23–1.45]) and hospitalizations (HR, 1.42 [95% CI, 1.28–1.58]). Conclusions Low educational attainment, high social isolation, and high area‐deprivation index had the strongest associations. We identified meaningful subgroups with respect to SRFs, and these subgroups were associated with outcomes. These findings suggest that it is possible to apply latent class analysis to better understand the co‐occurrence of SRFs among patients with HF.

AbstractIntroductionCOVID‐19 has created additional challenges for the analysis of non‐randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically tailored meals (MTM) intervention at Kaiser Permanente Northwest (KPNW) that began in April 2020.MethodsWe identified both a historical and concurrent comparison group. The historical comparison group included patients living in the same area as the MTM recipients prior to COVID‐19. The concurrent comparison group included patients admitted to contracted non‐KPNW hospitals or admitted to a KPNW facility and living outside the service area for the intervention but otherwise eligible. We used two alternative propensity score methods in response to the loss of sample size with exact matching to evaluate the intervention.ResultsWe identified 452 patients who received the intervention, 3873 patients in the historical comparison group, and 5333 in the concurrent comparison group. We were able to mostly achieve balance on observable characteristics for the intervention and the two comparison groups.ConclusionsLessons learned included: (a) The use of two different comparison groups helped to triangulate results; (b) the meaning of utilization measures changed pre‐ and post‐COVID‐19; and (c) that balance on observable characteristics can be achieved, especially when the comparison groups are meaningfully larger than the intervention group. These findings may inform the design for future evaluations of interventions during COVID‐19.

Abstract Background: To describe the process of developing an evolving database for Mayo Clinic primary care patients who screen positive for depression. The databases will support a broad use of these data for current and future quality improvement and research efforts. The description of their development will serve as an example for other institutions attempting to create similar data resources. Methods: The adult database (patients aged ³ 18) has data from 2007 and the adolescent database (patients aged 12 to < 18) from 2011. To be included, a patient had to be eligible for collaborative care model as a primary care patient with at least moderate symptoms of unipolar depression. The patient did not have to be enrolled in collaborative care model. The main domains of measurement are demographics, social determinants of health, mental health and substance abuse conditions, other comorbidities, interaction with collaborative care model, and questionnaire results. The data is being continuously updated as new data becomes available. Results: The adult database currently includes 117,619 unique patients with a mean age of 44.7 years, and is 66.4% female, and 88.1% non-Hispanic white. The adolescent database includes 14,684 unique patients with a mean age of 14.8 years, is 66.7% female, and 79.7% non-Hispanic white. Conclusions: These large, longitudinal, and evolving databases are a key step towards developing a learning environment to improve quality of care and conduct population-based research for patients with depression in primary care settings.

Background: Health systems are increasingly recognizing the importance of collecting social determinants of health (SDoH) data. However, gaps remain in our understanding of facilitators or barriers to collection. To address these gaps, we evaluated a real-world implementation of a SDoH screening tool. Methods: We conducted a retrospective analysis of the implementation of the SDoH screening tool at Mayo Clinic in 2019. The outcomes are: (1) completion of screening and (2) the modality used (MyChart: filled out on patient portal; WelcomeTablet: filled out by patient on a PC-tablet; EpicCare: data obtained directly by provider and entered in chart). We conducted logistic regression for completion and multinomial logistic regression for modality. The factors of interest included race and ethnicity, use of an interpreter, and whether the visit was for primary care. Results: Overall, 58.7% (293,668/499,931) of screenings were completed. Patients using interpreters and racial/ethnic minorities were less likely to complete the screening. Primary care visits were associated with an increase in completion compared with specialty care visits. Patients who used an interpreter, racial and ethnic minorities, and primary care visits were all associated with greater WelcomeTablet and lower MyChart use. Conclusion: Patient and system-level factors were associated with completion and modality. The lower completion and greater WelcomeTablet use among patients who use interpreters and racial and ethnic minorities points to the need to improve screening in these groups and that the availability of the WelcomeTablet may have prevented greater differences. The higher completion in primary care visits may mean more outreach is needed for specialists.

555 Background: Women with early-stage breast cancer (BCa) are living longer, and survivorship issues including second primary cancers (SPCs) are therefore increasingly important. This study seeks to determine the risk of SPCs, including contralateral breast cancer (CBCa), in women with early-stage invasive lobular carcinoma (ILC). Methods: The study population consisted of women with BCa diagnosis between 2000-2018 within the NCI Surveillance, Epidemiology, and End Results (SEER v 3.2.9) registry and between 2000-2021 in the Mayo Clinic Cancer Registry. In the SEER registry, the standardized incidence ratios (SIR) for SPCs were estimated for adult women with histologically confirmed early stage (I-III) ILC compared to the development of any primary cancer in the general population. For reference, SIRs for SPCs for a similar patient population with invasive ductal carcinoma (IDC) of the breast were also estimated. For comparison of CBCa between ILC and IDC, follow up records from the Mayo Clinic Cancer Registry were evaluated among adult women who underwent lumpectomy or unilateral mastectomy for early stage ILC or IDC. A multivariable Cox proportional hazards regression was performed to compare the risk of CBCa between ILC and IDC while adjusting for the age at diagnosis, race/ethnicity and estrogen receptor status of the primary tumor. Results: An increased incidence (p<0.05) of any SPCs and second BCa was noted for both ILC and IDC compared to the expected rate of primary cancer in the general population (Table). Interestingly, women with ILC were observed to have a significantly increased incidence of subsequent gastric cancer which was not seen for women with IDC. An SIR >1.5 was noted for subsequent risk of sarcoma, myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) for both ILC and IDC (Table). In the Mayo Clinic Cancer Registry of 2,218 women with ILC and 14,629 women with IDC meeting the inclusion criteria, the 5-year risk of CBCa was 2.6% and 1.5% (log rank statistic p-value =0.001) for ILC and IDC respectively. A significantly increased risk of CBCa was noted in women with ILC (Hazard Ratio 1.82, 95% CI 1.34-2.47, p<0.001) compared to women with IDC in the multivariable analysis. Conclusions: Women with ILC may have an increased risk of SPC and second BCa compared to the risk of any primary cancer in the general population. The increased incidence of gastric cancer and the higher risk of CBCa in ILC survivors compared to women with IDC is intriguing and needs to be investigated further including evaluation of the role of germline genetic factors. [Table: see text]

Introduction: Guideline-directed medical therapy (GDMT) dramatically improves outcomes in heart failure with reduced ejection fraction (HFrEF). Our goal was to examine GDMT use in community patients with newly diagnosed HFrEF. Methods: We performed a population-based, retrospective cohort study of all Olmsted County, Minnesota residents with newly diagnosed HFrEF (EF≤40%) 2007-2017. We excluded patients with contraindications to medication initiation (allergy, intolerance, heart rate<50 for beta blockers, SBP <80mm Hg for beta blockers, ACEi/ARB/ARNI; high creatinine (>3 mg/dL ACEi/ARB/ARNI, >2.5 men or >2.0 mg/dL women for mineralocorticoid receptor antagonists, MRAs) or hyperkalemia (potassium >5 meQ/L for ACEi/ARB/ARNI, MRA). We examined use and peak dose achieved for beta blockers, HF beta blockers (metoprolol succinate, carvedilol, bisoprolol), ACEi/ARB/ARNI, and MRA in the first year after HFrEF diagnosis. We used logistic regression to evaluate predictors of GDMT use. Results: From 2007-2017, 1160 patients were diagnosed with HFrEF (mean age 69.7 years, 65.6% men). Most eligible patients received beta blockers (92.1%) and ACEi/ARB/ARNI (86.5%) in the first year after HFrEF. However, only 63.6% of patients were treated with a HF beta blocker, and most did not receive MRAs (82.6%). The percentage of treated patients reaching medication target doses was 20.5% for HF beta blockers, 25.3% for ACEi/ARB/ARNI, and 11.2% for MRA. Compared to patients not seen in an HF clinic, patients seen in an HF clinic (n=380, 32.8%) were at greater odds of receiving beta blockers (OR 3.85, 95% CI 1.79-8.33); HF beta blockers (OR 3.85, 95% CI 2.63-5.26); ACEi/ARB/ARNIs (OR 3.85, 95% CI 2.17-6.67); and MRAs (OR 3.03, 95% CI 2.08-4.35). Other independent predictors of GDMT use included younger age (beta blockers, ACEi/ARB/ARNI), male gender (MRAs), higher SBP (beta blockers, ACEi/ARB/ARNI), lower EF (HF beta blockers), higher BMI (MRAs), and diabetes (ACEi/ARB/ARNI, p<0.05 for each). Conclusions: In this population-based study, most patients with newly diagnosed HFrEF received beta blockers and ACEi/ARB/ARNIs, but goal doses were usually not achieved. GDMT use was much higher in patients referred to an HF clinic.

AbstractBackgroundObservational analyses comparing coronary artery bypass surgery (CABG) and percutaneous coronary intervention (PCI) among elderly or frail patients are likely biased by treatment selection. PCI is typically chosen for frail patients, while CABG is more common for patients with good recovery potential.HypothesisWe hypothesized that skilled nursing facility (SNF) use after revascularization is a measure of relative frailty associated with outcomes following coronary revascularization.MethodsWe used a 20 percent sample of Medicare beneficiaries aged 65 years or older who received inpatient PCI or CABG between 2007–2014. Key explanatory variables were the revascularization strategy and SNF use after revascularization. We used Cox regression to evaluate death and repeat revascularization within one year and logistic regression to evaluate SNF use and 30‐day readmissions/death.ResultsCABG patients were 25.1 percentage points [95% confidence interval: 24.7, 25.5] more likely to use SNF following revascularization than inpatient PCI patients. SNF use was associated with a higher death rate (hazard ratio (HR): 3.19 [3.02, 3.37]) and a 16.2 percentage point (15.5, 16.9) increase in 30‐day readmissions/death. Among patients with SNF use, CABG was associated with a decrease in 30‐day readmissions/death compared to PCI.ConclusionsWhile CABG was associated with higher rates of SNF use and 30‐day readmission/death overall, CABG was associated with significantly lower rates of 30‐day readmissions/death among patients with SNF use. The findings suggest that caution is needed in treatment selection for patients at high‐risk for SNF use and that selection of inpatient PCI over CABG may be associated with frailty and worse outcomes for some patients.