Association of race and acute kidney injury among patients admitted with Coronavirus disease of 2019 (COVID-19).

BACKGROUND: COVID-19 is a multi-organ system disease, and rates of acute kidney injury (AKI) have varied significantly. Our objective was to evaluate the prevalence of AKI among hospitalized COVID-19-positive patients in a large hospital system in the Southeast of the USA. MATERIALS AND METHODS: This was a cohort study of admitted patients discharged between March 1, 2020 and April 30, 2020 at Atrium Health who had tested positive for COVID-19 by polymerase chain reaction testing of a nasopharyngeal swab. The positive test had been within 2 weeks prior to or after admission. AKI was defined and staged using the Kidney Disease Improving Global Outcomes (KDIGO) 2012 AKI criteria. Patient-level data including demographic characteristics, Charlson Comorbidity Index, and other comorbidities were also obtained. RESULTS: Of the admitted patients with COVID-19, 74 of 254 (29.1%, 95% CI 23.6 - 35.1%) had AKI. Participants with AKI compared to those without AKI tended to be ≥ 65 years of age (57 vs. 39%; p = 0.01), male (62 vs. 46%; p = 0.02), African American (70 vs. 45%; p < 0.01), have a diagnosis of chronic kidney disease (28 vs. 15%; p = 0.01), and a higher median Charlson Comorbidity Index score (6.5 vs. 4.0; p < 0.01). After adjusting for other factors, African Americans had three times the odds of developing AKI compared to other racial groups among patients admitted with a COVID-19 diagnosis (OR 3.09; 95% CI 1.49 - 6.41). CONCLUSION: Among the 254 patients hospitalized with COVID-19, we observed a high prevalence of AKI. However, a majority of survivors demonstrated renal recovery at the time of discharge. African American race was strongly associated with development of AKI and portended a poor prognosis.

Aiming to Improve Readmissions Through InteGrated Hospital Transitions (AIRTIGHT): a Pragmatic Randomized Controlled Trial.

BACKGROUND: Despite years of intense focus, inpatient and observation readmission rates remain high and largely unchanged. Hospitals have little, robust evidence to guide the selection of interventions effective at reducing 30-day readmissions in real-world settings. OBJECTIVE: To evaluate if implementation of recent recommendations for hospital transition programs is effective at reducing 30-day readmissions in a population discharged to home and at high-risk for readmission. DESIGN: A non-blinded, pragmatic randomized controlled trial ( Clinicaltrials.gov : NCT02763202) conducted at two hospitals in Charlotte, North Carolina. PATIENTS: A total of 1876 adult patients, under the care of a hospitalist, and at high risk for readmissions. INTERVENTION: Random allocation to a Transition Services (TS) program (n = 935) that bridges inpatient, outpatient, and home settings, providing patients virtual and in-person access to a dedicated multidisciplinary team for 30-days, or usual care (n = 941). MAIN MEASURE: Thirty-day, unplanned, inpatient, or observation readmission rate. KEY RESULTS: The 30-day readmission rate was 15.2% in the TS group and 16.3% in the usual care group (RR 0.93; 95% [CI, 0.76 to 1.15]; P = 0.52). There were no significant differences in readmissions at 60 and 90 days or in 30-day Emergency Department visit rates. Patients, who were referred to TS and readmitted, had less Intensive Care Unit admissions 15.5% vs. 26.8% (RR 0.74; 95% [CI, 0.59 to 0.93]; P = 0.02). CONCLUSIONS: An intervention inclusive of contemporary recommendations does not reduce a high-risk population's 30-day readmission rate. The high crossover to usual care (74.8%) reflects the challenge of non-participation that is ubiquitous in the real-world implementation of population health interventions. TRIAL REGISTRY: ClinicalTrials.gov ; registration ID number: NCT02763202, URL: https://clinicaltrials.gov/ct2/show/NCT02763202.

A Retrospective Evaluation of the Impacts of a Multidisciplinary Care Model for Managing Patients with Advanced Illness on Acute Care Utilization and Quality of Care at End of Life.

Background: A home-based goal-concordant care model targeting patients with advanced illnesses may reduce acute care utilization and improve quality outcomes at end of life. Aim: Study aim was to determine impact of the Advanced Illness Management (AIM) program on end-of-life utilization and quality of care. Design: A retrospective observational study design using propensity score fine stratum weighting methodologies was applied to decedent patients identified for AIM enrollment/eligibility in 2018 to 2019. Setting/Participants: A total of 3859 decedents, 216 of whom were AIM enrollees, were identified from a metropolitan health system's electronic medical records (EMR) and met study eligibility criteria. Results: Compared with usual care, AIM enrollees spent more days away from acute care in the last 30, 90, and 180 days of life. Furthermore, AIM enrollees were less likely to expire in an acute care hospital. Conclusions: Enrollment in programs such as AIM should be considered for patients with advanced illnesses approaching end of life.

Association between body mass index and arsenic methylation efficiency in adult women from southwest U.S. and northwest Mexico.

Human arsenic methylation efficiency has been consistently associated with arsenic-induced disease risk. Interindividual variation in arsenic methylation profiles is commonly observed in exposed populations, and great effort has been put into the study of potential determinants of this variability. Among the factors that have been evaluated, body mass index (BMI) has not been consistently associated with arsenic methylation efficiency; however, an underrepresentation of the upper BMI distribution was commonly observed in these studies. This study investigated potential factors contributing to variations in the metabolism of arsenic, with specific interest in the effect of BMI where more than half of the population was overweight or obese. We studied 624 adult women exposed to arsenic in drinking water from three independent populations. Multivariate regression models showed that higher BMI, arsenic (+3 oxidation state) methyltransferase (AS3MT) genetic variant 7388, and higher total urinary arsenic were significantly associated with low percentage of urinary arsenic excreted as monomethylarsonic acid (%uMMA) or high ratio between urinary dimethylarsinic acid and uMMA (uDMA/uMMA), while AS3MT genetic variant M287T was associated with high %uMMA and low uDMA/uMMA. The association between BMI and arsenic methylation efficiency was also evident in each of the three populations when studied separately. This strong association observed between high BMI and low %uMMA and high uDMA/uMMA underscores the importance of BMI as a potential arsenic-associated disease risk factor, and should be carefully considered in future studies associating human arsenic metabolism and toxicity.

Modifying Provider Vitamin D Screening Behavior in Primary Care.

PURPOSE: Clinical evidence shows minimal benefit to vitamin D screening and subsequent treatment in the general population. This study aims to assess the effectiveness of 2 light-touch interventions on reducing vitamin D test orders. METHODS: The outcomes were weekly average vitamin D rates, computed from adult primary care encounters (preventive or nonpreventive) with a family medicine (FM) or internal medicine (IM) provider from June 14, 2018 through December 12, 2018. We conducted an interrupted time series analysis and estimated the cost impact of the interventions. The interventions consisted of an educational memo (August 9, 2018) distributed to providers and removal of the vitamin D test (FM: August 15, 2018; IM: October 17, 2018) from the providers' quick order screen in the electronic health record. Change in order rates were analyzed among physicians (MDs and DOs), physician assistants (PAs), and nurse practitioners (NPs). RESULTS: There were 587,506 primary care encounters (FM = 367,947; IM = 219,559). Vitamin D order rates decreased from 6.9% (FM = 5.1%; IM = 9.9%) to 5.2% (FM = 4% [P < .01], IM = 7.9% [P < .01]). For FM, the vitamin D test order rate continued to fall at a 0.08% per week rate after the interventions (end of study: 2.73%). The education intervention showed a relative decrease in each provider type (FM-physician = 16% [P < .01], FM-PA = 47% [P < .01], FM-NP = 20% [P = .01], IM-physician = 14% [P = .02], IM-PA = 52% [P < .01], IM-NP = 34% [P = .04]). Annualized savings was approximately 1 million dollars. CONCLUSIONS: Emailed evidence-based provider education may be an effective tool for modifying providers' vitamin D test ordering behavior. The lack of the effectiveness of the vitamin D test removal from the quick order screen found for IM highlights the challenges facing simple electronic health record interventions when multiple alternate ordering pathways exist.

Effect of a Virtual Patient Navigation Program on Behavioral Health Admissions in the Emergency Department: A Randomized Clinical Trial.

IMPORTANCE: The number of patients presenting to emergency departments (EDs) for psychiatric care continues to increase. Psychiatrists often make a conservative recommendation to admit patients because robust outpatient services for close follow-up are lacking. OBJECTIVE: To assess whether the availability of a 45-day behavioral health-virtual patient navigation program decreases hospitalization among patients presenting to the ED with a behavioral health crisis or need. DESIGN, SETTING, AND PARTICIPANTS: This randomized clinical trial enrolled 637 patients who presented to 6 EDs spanning urban and suburban locations within a large integrated health care system in North Carolina from June 12, 2017, through February 14, 2018; patients were followed up for up to 45 days. Eligible patients were aged 18 years or older, with a behavioral health crisis and a completed telepsychiatric ED consultation. The availability of the behavioral health-virtual patient navigation intervention was randomly allocated to specific days (Monday through Friday from 7 am to 7 pm) so that, in a 2-week block, there were 5 intervention days and 5 usual care days; 323 patients presented on days when the program was offered, and 314 presented on usual care days. Data analysis was performed from March 7 through June 13, 2018, using an intention-to-treat approach. INTERVENTIONS: The behavioral health-virtual patient navigation program included video contact with a patient while in the ED and telephonic outreach 24 to 72 hours after discharge and then at least weekly for up to 45 days. MAIN OUTCOMES AND MEASURES: The primary outcome was the conversion of an ED encounter to hospital admission. Secondary outcomes included 45-day follow-up encounters with a self-harm diagnosis and postdischarge acute care use. RESULTS: Among 637 participants, 358 (56.2%) were men, and the mean (SD) age was 39.7 (16.6) years. The conversion rates were 55.1% (178 of 323) in the intervention group vs 63.1% (198 of 314) in the usual care group (odds ratio, 0.74; 95% CI, 0.54-1.02; P = .06). The percentage of patient encounters with follow-up encounters having a self-harm diagnosis was significantly lower in the intervention group compared with the usual care group (36.8% [119 of 323] vs 45.5% [143 of 314]; P = .03). CONCLUSIONS AND RELEVANCE: Although the primary result did not reach statistical significance, there is a strong signal of potential positive benefit in an area that lacks evidence, suggesting that there should be additional investment and inquiry into virtual behavioral health programs. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03204643.

A Population Health Approach to Transitional Care Management for High-Risk Patients with Diabetes: Outcomes at a Rural Hospital.

Patient transitions from inpatient to home care are an important area of focus for reducing costly unplanned hospital readmissions. In rural settings, the challenge of reducing unplanned readmissions is amplified by limited access to both ambulatory and acute care as well as high levels of social disadvantage. In addition, there is a scarcity of evidence regarding strategies that have been proven to improve care transitions and related patient outcomes in this setting. This paper describes the process for implementation and results of a telephone-based transitional care management (TCM) program designed to reduce readmissions for patients with diabetes in a rural hospital in Scotland County, North Carolina. Data were collected from July 2016 to January 2019 using billing records to identify adult patients with high or very high risk of readmission based on length of stay, acuity, comorbidity, and emergency department visits (LACE) scores. Care managers contacted eligible patients by phone after discharge to review discharge instructions, assess need for home health services and transportation assistance, and schedule primary care follow-up visits. Overall, 13.8% of 15,271 discharges were targeted for TCM; 68.2% of these involved a patient with diabetes. The post-intervention 30-day readmission rate was 18.0% among patients identified as high or very high risk versus 8.8% among the overall population and did not differ significantly between TCM participants with diabetes and those without (22.9% vs.18.8%; P = 0.525). Findings highlight challenges with implementing transition of care interventions in rural settings, which include staffing, patient volume, and accessing data from out-of-network providers.

A comparison of methodologies for the real-time identification of hospitalized patients with acute exacerbations of COPD.

Background: COPD is a lung disease characterized by chronic, irreversible airway obstruction that can precipitate into acute exacerbations of COPD (AECOPD) often requiring hospitalization. Improving these outcomes will require proactive innovations in care delivery to at-risk populations. Data-driven models to identify patients with AECOPD on admission to the hospital are needed, but do not exist. Objective: This study aimed to compare the performance of several models designed to identify patients with AECOPD within 24 hours of hospital admission. Methods: Clinical factors associated with admissions for AECOPD that are available within 24 hours of an encounter were combined into six different models and then tested retrospectively to evaluate each model's performance in predicting AECOPD. The data set incorporated billing and clinical data from patients who were older than 40 years of age with an inpatient or observation encounter in 2016 at one of the nine hospitals within a large integrated healthcare system. Results: Of the 116,329 encounters, 6,383 had a billing diagnosis for AECOPD. The models showed a wide range of sensitivity (0.473 vs 0.963) and positive predictive value (0.190 vs 0.827). Conclusion: It is possible to leverage clinical and administrative data to identify patients admitted with AECOPD in real-time for quality improvement or research purposes. Because models relied on clinical data, local variation in care delivery also likely contributed to performance variation across hospitals. These findings emphasize the importance of testing model performance on local data and choosing the model that best aligns with the specific goals of the targeted initiative.

Combining Lean and Applied Research methods to improve rigor and efficiency in acute care outcomes research: A case study.

Hospital care is the single, largest contributor to health spending, yet evidence to guide value transformation is lacking. The large, real-world studies required to fill this void are challenging to conduct in the complex and fast-paced acute care environment. To address these challenges, we created a framework that combines Lean manufacturing methodology and Applied Research principles. We deployed this framework to design, pilot, and iteratively improve a study protocol testing the effectiveness of an innovative care pathway for patients hospitalized with acute exacerbations of Chronic Obstructive Pulmonary Disease. Over a three month period, the protocol was successfully piloted and refined at a single site, subsequently becoming the basis for a large system-wide randomized controlled trial. This framework combining Lean and Applied Research methods resulted in synergies that neither method could accomplish alone and may serve as a template for learning healthcare systems to efficiently generate real-world evidence in the acute care setting.

Aiming to Improve Readmissions Through InteGrated Hospital Transitions (AIRTIGHT): study protocol for a randomized controlled trial.

BACKGROUND: Hospital readmissions remain highly prevalent despite being the target of policies and financial penalties. Evidence comparing the effectiveness and costs of interventions to reduce readmissions is lacking, leaving healthcare systems with little guidance on how to improve quality and avoid costly penalties. Effective interventions likely need to bridge inpatient and outpatient settings, incorporate information technology, and use dedicated providers. Such complex innovations will require rigorous evaluation. The framework of quality improvement research provides an approach that both improves care locally and contributes to closing the current knowledge gaps for readmissions. In this trial, we will study a comprehensive intervention that incorporates these recommendations into an integrated practice unit, called transition services, with an aim of reducing 30-day readmission rates. METHODS/DESIGN: We describe a nonblinded, pragmatic, controlled trial with two parallel groups comprising an evaluation of the effect of referral to a provider-led integrated practice unit, inclusive of comprehensive multidisciplinary care, dedicated paramedicine providers, and virtual visits, on 30-day readmission rates for high-risk hospitalized patients. An automated risk-scoring system will randomly generate referrals to either transition services or usual care for 1520 hospitalized patients who score as high-risk for readmission. Transition services will then engage with patients in the hospital setting using a patient navigator and provide bridging outpatient services for the 30 days following discharge. All outcome data are retrieved electronically from administrative medical records. After reapplication of inclusion and exclusion criteria at the time of hospital discharge, analyses will follow the intention-to-treat principle such that patients will be analyzed on the basis of the referral group to which they were initially randomized. DISCUSSION: The hospital transition program under study is complex and integrates the latest recommendations for readmission reduction strategies. As healthcare systems innovate to address readmissions through such complex interventions, there is significant benefit for stakeholders to have a clear understanding of the potential reach, cost, and real-world effectiveness. The pragmatic methods described here provide a template for conducting quality improvement research that fits seamlessly into existing care delivery and improvement efforts, leading to better-informed strategic decisions and the investments necessary to transform care and value for patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02763202 . Registered 3 March 2016 (retrospectively registered).

Relation of dietary inorganic arsenic to serum matrix metalloproteinase-9 (MMP-9) at different threshold concentrations of tap water arsenic.

Arsenic (As) exposure is associated with cancer, lung and cardiovascular disease, yet the mechanisms involved are not clearly understood. Elevated matrix metalloproteinase-9 (MMP-9) levels are also associated with these diseases, as well as with exposure to water As. Our objective was to evaluate the effects of dietary components of inorganic As (iAs) intake on serum MMP-9 concentration at differing levels of tap water As. In a cross-sectional study of 214 adults, dietary iAs intake was estimated from 24-h dietary recall interviews using published iAs residue data; drinking and cooking water As intake from water samples and consumption data. Aggregate iAs intake (food plus water) was associated with elevated serum MMP-9 in mixed model regression, with and without adjustment for covariates. In models stratified by tap water As, aggregate intake was a significant positive predictor of serum MMP-9 in subjects exposed to water As≤10 µg/l. Inorganic As from food alone was associated with serum MMP-9 in subjects exposed to tap water As≤3 µg/l. Exposure to iAs from food and water combined, in areas where tap water As concentration is ≤10 µg/l, may contribute to As-induced changes in a biomarker associated with toxicity.

Contribution of diet to aggregate arsenic exposures-an analysis across populations.

The relative contribution of dietary arsenic (As) to aggregate daily exposure has not been well-characterized, especially in relation to the current EPA maximum contaminant level (MCL) of 10 p.p.b. for As in drinking water. Our objectives were to: (1) model exposure to inorganic and total As among non-seafood eaters using subject-specific data, (2) compare the contribution of food, drinking and cooking water to estimated aggregate exposure in households with variable background tap water As levels, and (3) describe the upper distribution of potential dose at different thresholds of tap water As. Dietary As intake was modeled in regional study populations and NHANES 2003-2004 using dietary records in conjunction with published food As residue data. Water As was measured in the regional studies. Among subjects exposed to tap water As >10 p.p.b., aggregate inorganic exposure was 24.5-26.1 µg/day, with approximately 30% of intake from food. Among subjects living in homes with tap water As ≤10, 5 or 3 p.p.b., aggregate inorganic As exposure was 8.6-11.8 µg/day, with 54-85% of intake from food. Median inorganic As potential dose was 0.42-0.50 µg/kg BW/day in subjects exposed to tap water As >10 p.p.b. and less than half that among subjects exposed to tap water As ≤10 p.p.b. The majority of inorganic and total As exposure is attributable to diet in subjects with tap water As

Environmental arsenic exposure and serum matrix metalloproteinase-9.

The objective of this study was to evaluate the relationship between environmental arsenic exposure and serum matrix metalloproteinase (MMP)-9, a biomarker associated with cardiovascular disease and cancer. In a cross-sectional study of residents of Arizona, USA (n=215) and Sonora, Mexico (n=163), drinking water was assayed for total arsenic, and daily drinking water arsenic intake was estimated. Urine was speciated for arsenic, and concentrations were adjusted for specific gravity. Serum was analyzed for MMP-9 using ELISA. Mixed model linear regression was used to assess the relation among drinking water arsenic concentration, drinking water arsenic intake, urinary arsenic sum of species (the sum of arsenite, arsenate, monomethylarsonic acid and dimethylarsinic acid), and MMP-9, controlling for autocorrelation within households. Drinking water arsenic concentration and intake were positively associated with MMP-9, both in crude analysis and after adjustment for gender, country/ethnicity, age, body mass index, current smoking, and diabetes. Urinary arsenic sum of species was positively associated with MMP-9 in multivariable analysis only. Using Akaike's Information Criterion, arsenic concentration in drinking water provided a better fitting model of MMP-9 than either urinary arsenic or drinking water arsenic intake. In conclusion, arsenic exposure evaluated using all three exposure metrics was positively associated with MMP-9.

Binational arsenic exposure survey: methodology and estimated arsenic intake from drinking water and urinary arsenic concentrations.

The Binational Arsenic Exposure Survey (BAsES) was designed to evaluate probable arsenic exposures in selected areas of southern Arizona and northern Mexico, two regions with known elevated levels of arsenic in groundwater reserves. This paper describes the methodology of BAsES and the relationship between estimated arsenic intake from beverages and arsenic output in urine. Households from eight communities were selected for their varying groundwater arsenic concentrations in Arizona, USA and Sonora, Mexico. Adults responded to questionnaires and provided dietary information. A first morning urine void and water from all household drinking sources were collected. Associations between urinary arsenic concentration (total, organic, inorganic) and estimated level of arsenic consumed from water and other beverages were evaluated through crude associations and by random effects models. Median estimated total arsenic intake from beverages among participants from Arizona communities ranged from 1.7 to 14.1 µg/day compared to 0.6 to 3.4 µg/day among those from Mexico communities. In contrast, median urinary inorganic arsenic concentrations were greatest among participants from Hermosillo, Mexico (6.2 µg/L) whereas a high of 2.0 µg/L was found among participants from Ajo, Arizona. Estimated arsenic intake from drinking water was associated with urinary total arsenic concentration (p < 0.001), urinary inorganic arsenic concentration (p < 0.001), and urinary sum of species (p < 0.001). Urinary arsenic concentrations increased between 7% and 12% for each one percent increase in arsenic consumed from drinking water. Variability in arsenic intake from beverages and urinary arsenic output yielded counter intuitive results. Estimated intake of arsenic from all beverages was greatest among Arizonans yet participants in Mexico had higher urinary total and inorganic arsenic concentrations. Other contributors to urinary arsenic concentrations should be evaluated.