Further Evidence That COVID-19 Disproportionately Impacts African American, Hispanic, and Low-Income Populations
Dustin D. French, Andrew Chin, and Pooja Kathail
Utilizing consumer data, mortality data, and medical claims data from the COVID-19 Research Database, French, Chin, and Kathail helped quantify the disproportionate impact that COVID-19 has across different racial and socioeconomic groups. For instance, the bottom quartile of income distribution (under $49,000 in annual income) have 30 percent of COVID cases and 46 percent of COVID deaths. Meanwhile, the top quartile (over $144,000 in annual income) had only 11 percent of COVID deaths.
Socioeconomic Network Heterogeneity and Pandemic Policy Response
Mohammad Akbarpour, Cody Cook, Aude Marzuoli, Simon Mongey, Abhishek Nagaraj, Matteo Saccarolak, Pietro Tebaldi, Shoshana Vasserman, and Hanbin Yang
Researchers from Harvard, Stanford, the University of Chicago, and Berkeley created a methodology for deciding which locations in a city to re-open and which to keep closed. The authors utilized a wide variety of data sources to build their models, including electronic medical records from the COVID-19 Research Database. After its completion, the model was then tested across three different cities: Chicago, Sacramento, and New York.
Computable Phenotype Implementation for a National, Multicenter Pragmatic Clinical Trial: Lessons Learned From ADAPTABLE
Faraz S. Ahmad, Iben M. Ricket, Bradley G. Hammill, Lisa Eskenazi, Holly R. Robertson, Lesley H. Curtis, Cecilia D. Dobi, Saket Girotra, Kevin Haynes, Jorge R. Kizer, Sunil Kripalani, Mathew T. Roe, Christianne L. Roumie, Russ Waitman, W. Schuyler Jones, and Mark G. Weiner
This study outlines the recruitment process for the ADAPTABLE study (Aspirin Dosing: a Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness), a pragmatic, randomized, open-label clinical trial that tested the optimal dose of aspirin for secondary prevention of atherosclerotic cardiovascular disease events. Investigators identified 650,000 potential eligible patients and recruited them at community sites, linking together data from the 40 sites in the Patient-Centered Outcomes Research Network to understand eligibility. The study was ultimately able to successfully enroll 15,076 patients in a significantly lower-cost way than most trials.
Daily Deaths During Coronavirus Pandemic by State
John Hargraves and Daniel Kurowski
Using mortality data, the Health Care Cost Institute found that daily deaths in the United States were over 10 percent higher in 2020 than they had been in previous years. The data showed dramatic variations by geography. Since the end of March, New York daily death figures were double those from previous years. While New York deaths appeared to be declining by April, other states were on the rise.
How America’s Health Data Infrastructure is Being Used to Fight COVID-19
As part of the tragedy of COVID-19, tens of thousands of new cases are diagnosed in the US each day. In America, the data from these patients are captured across electronic medical records, medical claims, diagnostic tests, pharmacies, and mortality records. Buried in this data are the answers to many…
Use of Administrative Claims to Assess Outcomes and Treatment Effect in Randomized Clinical Trials for Transcatheter Aortic Valve Replacement: Findings from the Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study
Jordan B. Strom, Kamil F. Faridi, Neel M. Butala, Yuansong Zhao, Hector Tamez, Linda R. Valsdottir, J. Matthew Brennan, Changyu Shen, Jeffrey J. Popma, Dhruv S. Kazi, and Robert W. Yeh
The study attempted to see whether passively collected data could substitute for adjudicated outcomes to reproduce the magnitude and direction of treatment effect observed in cardiovascular clinical trials. By linking together a variety of data sets, including clinical trials and medicare inpatient claims, the researchers concluded that the clinical trial and the claims data produced magnitudinally and directionally consistent results for the primary endpoints, though less so for the secondary endpoints.
Privacy-Preserving Record Linkage to Identify Fragmented Electronic Medical Records in the All of Us Research Program
Abel N. Kho, Jingzhi Yu, Molly Scannell Bryan, Charon Gladfelter, Howard S. Gordon, Shaun Grannis, Margaret Madden, Eneida Mendonca, Vesna Mitrovic, Raj Shah, Umberto Tachinardi, and Bradley Taylor
In conjunction with the All of Us Research Program, the authors looked at Electronic Health Records to understand how fragmented patient data was across a variety of health provider organizations, using a Privacy-Preserving Record Linkage tool in participating sites to generate a unique set of keyed encrypted hashes. Of the 5,831,238 individuals, 458,680 patients had data at more than one institution. Patients with some care fragmentation were almost 10 times as likely to have conflicting or inconsistent demographic data.
Health Care Utilization Among Homeless Veterans in Chicago
Jason H. Raad, Elizabeth Tarlov, Abel N. Kho, and Dustin D. French
The VA does not capture health encounters that occur outside its facilities. Therefore, any analyses of health-care utilization will miss certain data; this is particularly important for at-risk populations, where understanding utilization will enable better and less fragmented care. VA data was linked with Chicago’s HealthLNK Data Repository to find that of the 13,948 veterans who were homeless or at risk of becoming homeless, 17 percent of those veterans received some or all of their care in the community.
The Golden Age of Middleware: Why Visa Has Always Been a Great Middleware Company [And Why Buying Plaid Makes Sense]
Author’s Note: I am a huge fan of middleware companies. Datavant is a middleware company connecting health data; my last startup, LiveRamp (now NYSE:RAMP), is the largest marketing middleware company; and I am an investor in a number of middleware companies across industries. The Visa/Plaid combination is a great example of what…