Building to learn: Information technology innovations to enable rapid pragmatic evaluation in a learning health system.

Background: Learning health systems (LHSs) iteratively generate evidence that can be implemented into practice to improve care and produce generalizable knowledge. Pragmatic clinical trials fit well within LHSs as they combine real-world data and experiences with a degree of methodological rigor which supports generalizability. Objectives: We established a pragmatic clinical trial unit ("RapidEval") to support the development of an LHS. To further advance the field of LHS, we sought to further characterize the role of health information technology (HIT), including innovative solutions and challenges that occur, to improve LHS project delivery. Methods: During the period from December 2021 to February 2023, eight projects were selected out of 51 applications to the RapidEval program, of which five were implemented, one is currently in pilot testing, and two are in planning. We evaluated pre-study planning, implementation, analysis, and study closure approaches across all RapidEval initiatives to summarize approaches across studies and identify key innovations and learnings by gathering data from study investigators, quality staff, and IT staff, as well as RapidEval staff and leadership. Implementation Results: Implementation approaches spanned a range of HIT capabilities including interruptive alerts, clinical decision support integrated into order systems, patient navigators, embedded micro-education, targeted outpatient hand-off documentation, and patient communication. Study approaches include pre-post with time-concordant controls (1), randomized stepped-wedge (1), cluster randomized across providers (1) and location (3), and simple patient level randomization (2). Conclusions: Study selection, design, deployment, data collection, and analysis required close collaboration between data analysts, informaticists, and the RapidEval team.

A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.

OBJECTIVE: To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease 2019 (COVID-19) in the emergency department (ED). METHODS: We developed in a 12-hospital system a model using training and validation followed by a real-time assessment. The LASSO guided feature selection included demographics, comorbidities, home medications, vital signs. We constructed a logistic regression-based ML algorithm to predict "severe" COVID-19, defined as patients requiring intensive care unit (ICU) admission, invasive mechanical ventilation, or died in or out-of-hospital. Training data included 1,469 adult patients who tested positive for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within 14 days of acute care. We performed: 1) temporal validation in 414 SARS-CoV-2 positive patients, 2) validation in a PUI set of 13,271 patients with symptomatic SARS-CoV-2 test during an acute care visit, and 3) real-time validation in 2,174 ED patients with PUI test or positive SARS-CoV-2 result. Subgroup analysis was conducted across race and gender to ensure equity in performance. RESULTS: The algorithm performed well on pre-implementation validations for predicting COVID-19 severity: 1) the temporal validation had an area under the receiver operating characteristic (AUROC) of 0.87 (95%-CI: 0.83, 0.91); 2) validation in the PUI population had an AUROC of 0.82 (95%-CI: 0.81, 0.83). The ED CDS system performed well in real-time with an AUROC of 0.85 (95%-CI, 0.83, 0.87). Zero patients in the lowest quintile developed "severe" COVID-19. Patients in the highest quintile developed "severe" COVID-19 in 33.2% of cases. The models performed without significant differences between genders and among race/ethnicities (all p-values > 0.05). CONCLUSION: A logistic regression model-based ML-enabled CDS can be developed, validated, and implemented with high performance across multiple hospitals while being equitable and maintaining performance in real-time validation.

'Trying to fly the plane while we were building it'. Applying a learning health systems approach to evaluate early-stage barriers and facilitators to implementing primary care transformation: a qualitative study.

OBJECTIVE: A learning health system (LHS) uses data to generate evidence and answer questions required to continually improve system performance and patient care. Given the complexities of practice transformation, an area where LHS is particularly important is the study of primary care transformation (PCT) as PCT generates several practice-level questions that require study where the findings can be readily implemented. In May 2019, a large integrated health delivery system in Minnesota began implementation of a population management PCT in two of its 40 primary care clinics. In this model of care, patients are grouped into one of five service bundles based on their complexity of care; patient appointment lengths and services provided are then tailored to each service bundle. The objective of this study was to examine the use of a LHS in PCT by utilising the Consolidated Framework for Implementation Research (CFIR) to categorise implementation lessons from the initial two PCT clinics to inform further implementation of the PCT within the health system. DESIGN: This was a formative evaluation in which semistructured qualitative interviews were carried out. Observational field notes were also taken. Inductive coding of the data was performed and resultant codes were mapped to the CFIR. SETTING: Two suburban primary care clinics in the Twin Cities, Minnesota. PARTICIPANTS: Twenty-two care team members from the first two clinics to adopt the PCT. RESULTS: Seventeen codes emerged to describe care team members' perceived implementation influences. Codes occurred in each of the five CFIR domains (intervention characteristics, outer setting, inner setting, characteristics of individuals and process), with most codes occurring in the 'inner setting' domain. CONCLUSIONS: Using an LHS approach to determine early-stage implementation influences is key to guiding further PCT implementation, understanding modifications that need to be made and additional research that needs to occur.

Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study.

BACKGROUND: Studies evaluating strategies for the rapid development, implementation, and evaluation of clinical decision support (CDS) systems supporting guidelines for diseases with a poor knowledge base, such as COVID-19, are limited. OBJECTIVE: We developed an anticoagulation clinical practice guideline (CPG) for COVID-19, which was delivered and scaled via CDS across a 12-hospital Midwest health care system. This study represents a preplanned 6-month postimplementation evaluation guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework. METHODS: The implementation outcomes evaluated were reach, adoption, implementation, and maintenance. To evaluate effectiveness, the association of CPG adherence on hospital admission with clinical outcomes was assessed via multivariable logistic regression and nearest neighbor propensity score matching. A time-to-event analysis was conducted. Sensitivity analyses were also conducted to evaluate the competing risk of death prior to intensive care unit (ICU) admission. The models were risk adjusted to account for age, gender, race/ethnicity, non-English speaking status, area deprivation index, month of admission, remdesivir treatment, tocilizumab treatment, steroid treatment, BMI, Elixhauser comorbidity index, oxygen saturation/fraction of inspired oxygen ratio, systolic blood pressure, respiratory rate, treating hospital, and source of admission. A preplanned subgroup analysis was also conducted in patients who had laboratory values (D-dimer, C-reactive protein, creatinine, and absolute neutrophil to absolute lymphocyte ratio) present. The primary effectiveness endpoint was the need for ICU admission within 48 hours of hospital admission. RESULTS: A total of 2503 patients were included in this study. CDS reach approached 95% during implementation. Adherence achieved a peak of 72% during implementation. Variation was noted in adoption across sites and nursing units. Adoption was the highest at hospitals that were specifically transformed to only provide care to patients with COVID-19 (COVID-19 cohorted hospitals; 74%-82%) and the lowest in academic settings (47%-55%). CPG delivery via the CDS system was associated with improved adherence (odds ratio [OR] 1.43, 95% CI 1.2-1.7; P<.001). Adherence with the anticoagulation CPG was associated with a significant reduction in the need for ICU admission within 48 hours (OR 0.39, 95% CI 0.30-0.51; P<.001) on multivariable logistic regression analysis. Similar findings were noted following 1:1 propensity score matching for patients who received adherent versus nonadherent care (21.5% vs 34.3% incidence of ICU admission within 48 hours; log-rank test P<.001). CONCLUSIONS: Our institutional experience demonstrated that adherence with the institutional CPG delivered via the CDS system resulted in improved clinical outcomes for patients with COVID-19. CDS systems are an effective means to rapidly scale a CPG across a heterogeneous health care system. Further research is needed to investigate factors associated with adherence at low and high adopting sites and nursing units.

Coronary artery disease surveillance among childhood, adolescent and young adult cancer survivors: A systematic review and recommendations from the International Late Effects of Childhood Cancer Guideline Harmonization Group.

BACKGROUND: Coronary artery disease (CAD) is a concerning late outcome for cancer survivors. However, uniform surveillance guidelines are lacking. AIM: To harmonise international recommendations for CAD surveillance for survivors of childhood, adolescent and young adult (CAYA) cancers. METHODS: A systematic literature review was performed and evidence graded using the Grading of Recommendations, Assessment, Development and Evaluation criteria. Eligibility included English language studies, a minimum of 20 off-therapy cancer survivors assessed for CAD, and 75% diagnosed prior to age 35 years. All study designs were included, and a multidisciplinary guideline panel formulated and graded recommendations. RESULTS: 32 of 522 identified articles met eligibility criteria. The prevalence of CAD ranged from 0 to 72% and was significantly increased compared to control populations. The risk of CAD was increased among survivors who received radiotherapy exposing the heart, especially at doses ≥15 Gy (moderate-quality evidence). The guideline panel agreed that healthcare providers and CAYA cancer survivors treated with radiotherapy exposing the heart should be counselled about the increased risk for premature CAD. While the evidence is insufficient to support primary screening, monitoring and early management of modifiable cardiovascular risk factors are recommended. Initiation and frequency of surveillance should be based on the intensity of treatment exposures, family history, and presence of co-morbidities but at least by age 40 years and at a minimum of every 5 years. All were strong recommendations. CONCLUSION: These systematically assessed and harmonised recommendations for CAD surveillance will inform care and guide research concerning this critical outcome for CAYA cancer survivors.

Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles.

PURPOSE: Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. METHODS: This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. RESULTS: The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30-fold (HR:7.30, 95% CI:(3.11-17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10-6.00), p = 0.03) increases in hazard of death relative to phenotype III. CONCLUSION: We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design.

Metformin and risk of mortality in patients hospitalised with COVID-19: a retrospective cohort analysis.

BACKGROUND: Type 2 diabetes and obesity, as states of chronic inflammation, are risk factors for severe COVID-19. Metformin has cytokine-reducing and sex-specific immunomodulatory effects. Our aim was to identify whether metformin reduced COVID-19-related mortality and whether sex-specific interactions exist. METHODS: In this retrospective cohort analysis, we assessed de-identified claims data from UnitedHealth Group (UHG)'s Clinical Discovery Claims Database. Patient data were eligible for inclusion if they were aged 18 years or older; had type 2 diabetes or obesity (defined based on claims); at least 6 months of continuous enrolment in 2019; and admission to hospital for COVID-19 confirmed by PCR, manual chart review by UHG, or reported from the hospital to UHG. The primary outcome was in-hospital mortality from COVID-19. The independent variable of interest was home metformin use, defined as more than 90 days of claims during the year before admission to hospital. Covariates were comorbidities, medications, demographics, and state. Heterogeneity of effect was assessed by sex. For the Cox proportional hazards, censoring was done on the basis of claims made after admission to hospital up to June 7, 2020, with a best outcome approach. Propensity-matched mixed-effects logistic regression was done, stratified by metformin use. FINDINGS: 6256 of the 15 380 individuals with pharmacy claims data from Jan 1 to June 7, 2020 were eligible for inclusion. 3302 (52·8%) of 6256 were women. Metformin use was not associated with significantly decreased mortality in the overall sample of men and women by either Cox proportional hazards stratified model (hazard ratio [HR] 0·887 [95% CI 0·782-1·008]) or propensity matching (odds ratio [OR] 0·912 [95% CI 0·777-1·071], p=0·15). Metformin was associated with decreased mortality in women by Cox proportional hazards (HR 0·785, 95% CI 0·650-0·951) and propensity matching (OR 0·759, 95% CI 0·601-0·960, p=0·021). There was no significant reduction in mortality among men (HR 0·957, 95% CI 0·82-1·14; p=0·689 by Cox proportional hazards). INTERPRETATION: Metformin was significantly associated with reduced mortality in women with obesity or type 2 diabetes who were admitted to hospital for COVID-19. Prospective studies are needed to understand mechanism and causality. If findings are reproducible, metformin could be widely distributed for prevention of COVID-19 mortality, because it is safe and inexpensive. FUNDING: National Heart, Lung, and Blood Institute; Agency for Healthcare Research and Quality; Patient-Centered Outcomes Research Institute; Minnesota Learning Health System Mentored Training Program, M Health Fairview Institutional Funds; National Center for Advancing Translational Sciences; and National Cancer Institute.

The Lapidus Arthrodesis: Examining the Effect of the Metatarsal Base Transfixion Screw.

The modified Lapidus bunionectomy is a useful and highly powerful procedure for correcting hallux abducto valgus. Traditionally reserved for "severe" deformities, this procedure has seen a recent resurgence in the podiatric community for its unique ability to achieve tri-planar correction of this challenging deformity. Although this procedure has been extensively studied in both biomechanical labs and the clinical arenas, no clear consensus has been achieved regarding optimal fixation for this thought-provoking procedure. The current study examined the differences in strength between commercially available 5-hole locking plates with interfragmentary compression vs a crossed-screw with a third "transfixation" screw construct in a controlled setting. Ten fresh-frozen cadaveric match pair limbs (20 total limbs) were used to complete this study. Ten limbs were randomly assigned to a 3-screw construct. The other 10 contralateral limbs were assigned to a commercially available 5-hole locking plate (5 stainless steel and 5 titanium alloy) with an interfragmentary lag screw construct. The first rays were then isolated and potted into a 4-point bending device. The specimens were loaded to failure in a servohydraulic load frame at a controlled rate. Failure was defined as catastrophic or 3 mm of plantar gapping at the arthrodesis site. The mean maximal load to failure was 310.9 ± 109.4 N for the 3-screw construct. The mean maximal load to failure for the locking plate constructs was 264.1 ± 100.9 N. This difference was not statistically significant (p = .328). These results suggest that a 3-screw construct for Lapidus arthrodesis is as strong as commercially available locking plate constructs.

Characterizing COVID-19 Clinical Phenotypes and Associated Comorbidities and Complication Profiles.

BACKGROUND: There is limited understanding of heterogeneity in outcomes across hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of distinct clinical phenotypes may facilitate tailored therapy and improve outcomes. OBJECTIVE: Identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. DESIGN, SETTINGS, AND PARTICIPANTS: Retrospective analysis of 1,022 COVID-19 patient admissions from 14 Midwest U.S. hospitals between March 7, 2020 and August 25, 2020. METHODS: Ensemble clustering was performed on a set of 33 vitals and labs variables collected within 72 hours of admission. K-means based consensus clustering was used to identify three clinical phenotypes. Principal component analysis was performed on the average covariance matrix of all imputed datasets to visualize clustering and variable relationships. Multinomial regression models were fit to further compare patient comorbidities across phenotype classification. Multivariable models were fit to estimate the association between phenotype and in-hospital complications and clinical outcomes. Main outcomes and measures: Phenotype classification (I, II, III), patient characteristics associated with phenotype assignment, in-hospital complications, and clinical outcomes including ICU admission, need for mechanical ventilation, hospital length of stay, and mortality. RESULTS: The database included 1,022 patients requiring hospital admission with COVID-19 (median age, 62.1 [IQR: 45.9-75.8] years; 481 [48.6%] male, 412 [40.3%] required ICU admission, 437 [46.7%] were white). Three clinical phenotypes were identified (I, II, III); 236 [23.1%] patients had phenotype I, 613 [60%] patients had phenotype II, and 173 [16.9%] patients had phenotype III. When grouping comorbidities by organ system, patients with respiratory comorbidities were most commonly characterized by phenotype III (p=0.002), while patients with hematologic (p<0.001), renal (p<0.001), and cardiac (p<0.001) comorbidities were most commonly characterized by phenotype I. The adjusted odds of respiratory (p<0.001), renal (p<0.001), and metabolic (p<0.001) complications were highest for patients with phenotype I, followed by phenotype II. Patients with phenotype I had a far greater odds of hepatic (p<0.001) and hematological (p=0.02) complications than the other two phenotypes. Phenotypes I and II were associated with 7.30-fold (HR: 7.30, 95% CI: (3.11-17.17), p<0.001) and 2.57-fold (HR: 2.57, 95% CI: (1.10-6.00), p=0.03) increases in the hazard of death, respectively, when compared to phenotype III. CONCLUSION: In this retrospective analysis of patients with COVID-19, three clinical phenotypes were identified. Future research is urgently needed to determine the utility of these phenotypes in clinical practice and trial design.

Observational Study of Metformin and Risk of Mortality in Patients Hospitalized with Covid-19.

Background Type 2 diabetes (T2DM) and obesity are significant risks for mortality in Covid19. Metformin has been hypothesized as a treatment for COVID19. Metformin has sex specific immunomodulatory effects which may elucidate treatment mechanisms in COVID-19. In this study we sought to identify whether metformin reduced mortality from Covid19 and if sex specific interactions exist. Methods De-identified claims data from UnitedHealth were used to identify persons with at least 6 months continuous coverage who were hospitalized with Covid-19. Persons in the metformin group had at least 90 days of metformin claims in the 12 months before hospitalization. Unadjusted and multivariate models were conducted to assess risk of mortality based on metformin as a home medication in individuals with T2DM and obesity, controlling for pre-morbid conditions, medications, demographics, and state. Heterogeneity of effect was assessed by sex. Results 6,256 persons were included; 52.8% female; mean age 75 years. Metformin was associated with decreased mortality in women by logistic regression, OR 0.792 (0.640, 0.979); mixed effects OR 0.780 (0.631, 0.965); Cox proportional-hazards: HR 0.785 (0.650, 0.951); and propensity matching, OR of 0.759 (0.601, 0.960). TNF-alpha inhibitors were associated with decreased mortality in the 38 persons taking them, by propensity matching, OR 0.19 (0.0378, 0.983). Conclusions Metformin was significantly associated with reduced mortality in women with obesity or T2DM in observational analyses of claims data from individuals hospitalized with Covid-19. This sex-specific finding is consistent with metformin reducing TNF-alpha in females over males, and suggests that metformin conveys protection in Covid-19 through TNF-alpha effects. Prospective studies are needed to understand mechanism and causality.

Preoperative Anesthetic Considerations in the Podiatric Surgical Candidate.

There are multiple challenges the podiatric surgeon faces while attempting to treat patients in the perioperative setting. Given the aging and increasingly complex surgical population, preoperative evaluation is of utmost importance to mitigate unnecessary risks and to optimize patient outcomes. This article reviews key preoperative considerations, patient evaluation, and factors affecting selection of anesthetic technique.

Complications after Living Donor Hepatectomy: Analysis of 176 Cases at a Single Center.

BACKGROUND: Living liver donation is one of the most selfless and humane acts a person can perform. Few single-center reports have been published specifically evaluating complications and quality of life post-donation. STUDY DESIGN: We conducted a retrospective analysis of outcomes of 176 living liver donors at our center to determine the incidence, type, and Clavien grade of complications, as well as long-term quality of life. RESULTS: Of 176 living donors, 154 underwent right hepatectomy, 4 underwent left hepatectomy lobectomy, and 18 underwent left lateral segmentectomy. Mean follow-up time was 4.8 years. Complications were more frequent among right-lobe donors than left-lateral segmentectomy and left-lobe donors (p = 0.003). Of note, 82% of complications were Clavien grade 1 or 2. Of the 154 right-lobe donors, 3 had Clavien grade 3a complications, 9 had grade 3b complications (4 had bile leaks, 3 had intra-abdominal bleeding, and 2 had pleural effusions). No donor had complications that were Clavien grade 4 or higher. Per multivariate regression, resected graft volume (p = 0.0498) and post-donation international normalized ratio >2 (p = 0.00499) were significantly associated with a higher risk of Clavien grade 3 complications; however, sex, age, previous abdominal operation, post-donation bilirubin >6 mg/dL, and aspartate transaminase >650 IU/L were not. Per our 36-item Short-Form Health Survey results, donors (mean 8.3 years post-donation) reported above-average quality of life compared with standard US population. In a liver donation survey sent between 1 and 15 years post-donation, the most frequently reported problems were incisional discomfort and intolerance to fatty meals. CONCLUSIONS: In our single-center study, early complication rates were comparable with those of multicenter reports. Most complications (82%) were Clavien grade 1 or 2. During a long follow-up period, our donors continue to have improved quality of life.

The pediatrics milestones: initial evidence for their use as learning road maps for residents.

OBJECTIVE: As the next step in competency-based medical education, the Pediatrics Milestone Project seeks to provide a learner-centered approach to training and assessment. To help accomplish this goal, this study sought to determine how pediatric residents understand, interpret, and respond to the Pediatrics Milestones. METHODS: Cognitive interviews with 48 pediatric residents from all training levels at 2 training programs were conducted. Each participant reviewed one Pediatrics Milestone document (PMD). Eight total Pediatrics Milestones, chosen for their range of complexity, length, competency domain, and primary author, were included in this study. Six residents, 2 from each year of residency training, reviewed each PMD. Interviews were transcribed and coded using inductive methods, and codes were grouped into themes that emerged. RESULTS: Four major themes emerged through coding and analysis: 1) the participants' degree of understanding of the PMDs is sufficient, often deep; 2) the etiology of participants' understanding is rooted in their experiences; 3) there are qualities of the PMD that may contribute to or detract from understanding; and 4) participants apply their understanding by noting the PMD describes a developmental progression that can provide a road map for learning. Additionally, we learned that residents are generally comfortable being placed in the middle of a series of developmental milestones. Two minor themes focusing on interest and practicality were also identified. CONCLUSIONS: This study provides initial evidence for the Pediatrics Milestones as learner-centered documents that can be used for orientation, education, formative feedback, and, ultimately, assessment.