Faculty Bibliography

STATEMENT OF PROBLEM OR QUESTION (ONE SENTENCE): In order to describe quality improvement (QI) methods for health systems, we report on 10-years of using Unannounced Standardized Patient (USP) visits as the core of a program of education, training, and improvement in a system serving vulnerable patients in partnership with an academic medical center. LEARNING OBJECTIVES 1: Consider methods for supporting learning healthcare systems LEARNING OBJECTIVES 2: Identify performance data to improve care DESCRIPTION OF PROGRAM/INTERVENTION, INCLUDING ORGANIZATIONAL CONTEXT (E.G. INPATIENT VS. OUTPATIENT, PRACTICE OR COMMUNITY CHARACTERISTICS): The IOM defines a Learning Healthcare System (LHCS) as one in which science, informatics, incentives and culture are aligned for continuous improvement and innovation and where best practices are seamlessly embedded in the delivery process and new knowledge is captured as an integral by-product of the delivery experience. As essential as electronic health records are to LHCS, such data fail to capture all actionable information needed to sustain learning within complex systems. USPs are trained actors who present to clinics, incognito, to portray standardized chief complaints, histories, and characteristics. We designed and delivered USP visits to two urban, safety net clinics, focusing on assessing physician, team, and clinical micro system functioning. MEASURES OF SUCCESS (DISCUSS QUALITATIVE AND/OR QUANTITATIVEMETRICSWHICHWILL BE USEDTOEVALUATE PROGRAM/INTERVENTION): Behaviorally anchored assessments are used to assess core clinical skills (e.g., communication, information gathering, patient education, adherence to guidelines, patient centeredness, and patient activation). Team functioning assessments include professionalism and coordination. Micro system assessment focuses on safety issues like identity confirmation, hand washing, and navigation. Data from these visits has been provided to the residency, primary care teams, and to leadership and have been used to drive education, team training, and QI. FINDINGS TO DATE (IT IS NOT SUFFICIENT TO STATE FINDINGS WILL BE DISCUSSED): 1111 visits have been sent to internal medicine and primary care residents and their teams/clinics. At the resident level, needs for additional education and training in depression management, opioid prescribing, smoking cessation, and patient activation were identified and informed education. Chart reviews found substantial variation in ordering of labs and tests. At the team level, USPs uncovered needs for staff training, enhanced communication, and better processes for eliciting and documenting Social Determinants of Health (SDoH). Audit/feedback reports on provider responses to embedded SDoH combined with targeted education/resources, were associated with increased rates of eliciting and effectively responding to SDoH. In the early COVID wave, USPs tested clinic response to a potentially infectious patient. Currently, USPs are being deployed to understand variability in patients' experience of telemedicine given the rapid transformation to this modality. Finally, generalizable questions about underlying principles of medical education and quality improvement are being asked & answered using USP data to foster deeper understanding of levers for change. KEY LESSONS FOR DISSEMINATION (WHAT CAN OTHERS TAKE AWAY FOR IMPLEMENTATION TO THEIR PRACTICE OR COMMUNITY): A comprehensive USP program can provide unique insights for driving QI and innovation and help sustain a LHCS

Background Little is known about the economic burden of NP lupus. We estimated direct and indirect costs (DC, IC) associated with NP events attributed to SLE and non-SLE causes using multistate modelling. Methods Patients fulfilling ACR classification criteria for SLE from 31 centres in 11 countries were enrolled within 15 months of diagnosis. NP events were documented annually using ACR NP definitions and attributed to SLE or non-SLE causes. At each assessment and for SLE and non-SLE events, patients were stratified into 1 of 3 NP states (no, resolved, or new/ongoing NP event). The change in NP status characterized by transition rates between states was analyzed using multistate modelling (doi:10.1002/art.41876). At each assessment, annual DC and IC were based on health resource use and lost work-force/non-work-force productivity over the preceding year. Resource use was costed using 2021 Canadian prices and lost productivity using Statistics Canada age-and-sex specific wages. Costs associated with SLE and non-SLE NP states were calculated by averaging all observations in each NP state. Multiple regressions adjusted for possible confounding of age at diagnosis, sex, race/ethnicity, disease duration, geographic region, education, and smoking on the association of annual DC and IC and NP state. 5 and 10-year cumulative costs for NP states were predicted by multiplying adjusted annual costs for each state by the expected state duration, forecasted using multistate modelling. Results 1697 patients (89% female, 51% non-Caucasian race/ ethnicity, mean age at enrolment 35.1 years) were followed a mean of 8.8 years. 1971 NP events occurred in 956 patients, 32% attributed to SLE. For SLE NP events, annual DC were higher in those with new/ongoing vs no events ($10,809 vs $6715) (table 1). Annual and 5-yr IC were higher in new/ ongoing vs no events and new/ongoing vs resolved events (5- yr: new/ongoing vs no: $172,674 vs $136,970). For non-SLE NP events, annual IC were higher in new/ongoing vs no events, new/ongoing vs resolved events, and resolved vs no events and 5 and 10-yr IC were higher in new/ongoing vs no events (10-yr: new/ongoing vs no: $342,434 vs $279,874). For all NP states, IC exceeded DC 2.8 to 4-fold. Conclusion IC are 1.3-fold higher in patients with new/ ongoing vs no NP events. While DC trended higher in new/ ongoing events, they were not significantly higher across all NP states and times. Impaired productivity associated with ongoing and resolved NP lupus is substantial, contributing to the previously documented reduced quality of life

Background Prior studies of SLE clusters based on autoantibodies have utilized cross-sectional data from single centers. We applied clustering techniques to longitudinal and comprehensive autoantibody data from a large multinational, multiethnic inception cohort of well characterized SLE patients to identify clusters associated with disease outcomes. Methods We used demographic, clinical, and serological data at enrolment and follow-up visits years 3 and 5 from 805 patients who fulfilled the 1997 Updated ACR SLE criteria and were enrolled within 15 months of diagnosis. For each visit, ANA, dsDNA, Sm, U1-RNP, SSA/Ro60, SSB/La, Ro52/ TRIM21, histones, ribosomal P, Jo-1, centromere B, PCNA, anti-DFS70, lupus anticoagulant (LAC), IgG and IgM for anticardiolipin, anti-b2GP1, and aPS/PT, and IgG anti-b2GP1 D1 were performed at a single lab (except LAC). K-means clustering algorithm on principal component analysis (10 dimensions) transformed longitudinal ANA/autoantibody profiles was used. We compared cluster demographic/clinical outcomes, including longitudinal disease activity (total and adjusted mean SLEDAI- 2K), SLICC/ACR damage index and organ-specific domains, SLE therapies, and survival, using one-way ANOVA test and a Benjamini-Hochberg correction with false discovery rate alpha=0.05. Results were visualized using t-distributed stochastic neighbor embedding. Results Four unique patient clusters were identified (table 1). Cluster 1, characterized by high frequency of anti-Sm and anti-RNP over time, was the youngest group at disease onset with a high proportion of subjects of Asian and African ancestry. At year 5, they had the highest disease activity, were more likely to have active hematologic and mucocutaneous involvement, and to be on/exposed to immunosuppressants/ biologics. Cluster 2, the largest cluster, had low frequency of anti-dsDNA, were oldest at disease onset, and at year 5, had the lowest disease activity, and were least likely to have nephritis and be on/exposed to immunosuppressants/biologics. Cluster 3 had the highest frequency of antiphospholipid antibodies over time, were more likely to be of European ancestry, have an elevated BMI, be former smokers, and by year 5, to have nephritis, neuropsychiatric involvement, including strokes and seizures (SLICC/ACR damage index). Cluster 4 was characterized by anti-SSA/Ro60, SSB/La, Ro52/TRIM21, histone antibodies, and low complements at year 5. Overall, survival of the 805 subjects was 94% at 5 years, and none of the clusters predicted survival. Conclusions Four SLE patient clusters associated with disease activity, organ involvement, and treatment were identified in this analysis of longitudinal ANA/autoantibody profiles in relation to SLE outcomes, suggesting these subsets might be identifiable based on extended autoantibody profiles early in disease and carry prognostic information

LEARNING OBJECTIVE #1: Know the possible drug interactions of HMG CoA reductase inhibitor (statin) and commonly used antiplatelet agents LEARNING OBJECTIVE #2: Understand options for statin therapy in people with statin induced myopathy CASE: A 75-year-old man presented to his primary care physician (PCP) with two weeks of progressively worsening bilateral anterior thigh pain causing difficulty with ambulation. One month prior to presentation, he had been hospitalized for non-ST elevation myocardial infarction and in-stent thrombosis after he self-discontinued aspirin therapy. Upon discharge, he was switched to ticagrelor after he was found to be a non-responder to clopidogrel on platelet function tests. One day prior to admission his PCP discovered AST and ALT elevations to over 400 U/L (normal ranges 11-39 U/L and 11-35 U/L) and instructed the patient to present to the emergency room for further workup. In the emergency room (ED), the patient reported his symptoms started after he started taking ticagrelor, and he denied alcohol use. Past medical history includes hypertension and coronary artery disease treated with five drug eluting stents. He reported adherence medication regimen, which consisted of aspirin, ticagrelor, atorvastatin, amlodipine, hydrochlorothiazide, losartan, and metoprolol. He denied shortness of breath, dyspnea on exertion, abdominal pain, and leg edema. Vital signs were normal. Physical exam was most notable for tenderness to palpation of the thighs bilaterally. AST and ALT were 228 U/L and 158 U/L respectively, and CK was 4600 U/L (normal range: 45-245 U/L). Urinalysis revealed small blood with 0-4 red blood cells; urine culture produced no growth. Liver ultrasound found a normal liver and biliary tree. Hepatitis B and C serologies were negative. Troponin I was 0.07 ng/mL (normal range: <0.06 ng/mL), though there were no EKG changes from his prior admission. Once admitted to the floor, his atorvastatin was discontinued. The next day his AST and ALT decreased to 57 U/L and 121 U/L, and his CK fell to 715 U/L. IMPACT/DISCUSSION: Both myopathy and hepatitis occurred in this patient after initiation of ticagrelor, which is a known inhibitor of CYP P450 3A4. The levels of atorvastatin, which is metabolized by CYP P450 3A4, likely increased and caused a dose dependent toxicity, causing the patient's symptoms and lab abnormalities. He was subsequently discharged with improvement of thigh pain.
CONCLUSION(S): The drug-drug interaction of atorvastatin and ticagrelor has been established. This submission focuses on increasing knowledge of this common interaction. In this case, atorvastatin was discontinued and rosuvastatin was started as it is not metabolized by CYP P450 3A4. This combination is often better tolerated when combined with ticagrelor. The patient returned for outpatient follow-up and was started on rosuvastatin 5 mg with repeat liver function tests ordered with plans titrate as tolerated