Research

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.

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.

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.

Melanie Canterberry, Alan F. Kaul, Satyender Goel, Pi-I Debby Lin, Jason P. Block, Vinit P. Nair, Qianli Ma, and Thomas W. Carton
The Patient-Centered Outcomes Research Network (PCORnet) connects health systems, health plans, EHR data, and claims data to facilitate real-world clinical research. Datavant powers the linking of PCORnet. In this study, the authors looked to identify and understand the extent to which a clinical data research network and a health plan network contained consistent data on the patient level. Of the 549 patients from the EHR record who had claims with the health plan, sixty percent had consistent antibiotic exposure while 43.1% had a matched claims record.

Nikhilesh R. Mazumder, Kofi Atiemo, Amna Daud, Abel Kho, Michael Abecassis, Josh Levitsky, and Daniela P. Ladner
Most patients with cirrhosis have low Model for End-Stage Liver Disease-Sodium (MELD-Na) scores. The ability for the MELD-Na score to predict patient outcomes at low scores remains unclear. The researchers were able to link data from across Chicago to understand what patients might be eligible; from there, 7922 patients were identified, with 3999 patients having low MELD-Na scores. Further analyses were performed to show that, though patients with high MELD-Na scores had higher rates of mortality and were more likely to die of liver-related causes, even patients with low MELD-Na scores had high rates of liver-related mortality.

Qinli Ma, Haechung Chung, Sonali Shambhu, Matthew Roe, Mark Cziraky, W. Schuyler Jones, and Kevin Haynes
This study examined a retrospective cohort as part of the ADAPTABLE trial (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness). The trial was designed to compare the efficacy of different doses of Aspirin for the prevention of atherosclerotic cardiovascular disease events. By linking claims data from Anthem with data from the Patient-Centered Outcomes Research Network (PCORnet), the investigators were able to follow participants and understand their health outcomes without direct follow-up or bringing them into a trial site.

Kofi Atiemo, Nikhilesh R. Mazumder, Juan C. Caicedo, Daniel Ganger, Elisa Gordon, Samantha Montag, Haripriya Maddur, Lisa B. VanWagner, Satyender Goel, Abel Kho, Michael Abecassis, Lihui Zhao, and Daniela Ladner
Despite lower socioeconomic status, Hispanics in the United States have equal or higher survival rates compared to non-Hispanic whites (NHW). The authors attempted to understand whether this “Hispanic Paradox” applied to survival rates of liver cirrhosis. Using retrospective data from 20,121 patients in a Chicago-wide database linked together through Datavant technology, the researchers established that, controlling for age, sex, comorbidities, etiology of cirrhosis, and insurance status, Hispanics did indeed have higher survival rates than NHW.

Brandon A. Francis, Jennifer Beaumont, Matthew B. Maas, Eric M. Liotta, David Cella, Shyam Prabhakaran, Jane Holl, Abel Kho, and Andrew M. Naidech
Depressive symptoms in patients with intracerebral hemorrhage (ICH) are common and are associated with worse outcomes. However, those symptoms are often not accurately screened for or diagnosed. By linking together data from multiple EHR centers in Chicago, the researchers were able to see how often patients were treated for depressive symptoms; simultaneously, they performed depression screenings on study patients. After comparing the two data sets, the researchers concluded that depressive symptoms are significantly more common than the ICD codes or subsequent medical treatment would suggest.

Lindsay P. Zimmerman, Satyender Goel, Shazia Sathar, Charon E. Gladfelter, Alejandra Onate, Lindsey L. Kane, Shelly Sital, Jasmin Phua, Paris Davis, Helen Margellos-Anast, David O. Meltzer, Tamar S. Polonsky, Raj C. Shah, William E. Trick, Faraz S. Ahmad, and Abel N. Kho
This paper outlined a novel workflow for recruiting potential trial patients. Members of the community were identified, surveyed, and then assigned an encrypted and hashed identifier. Concurrently, data from a variety of hospitals was linked together at the patient level. Via the encrypted and hashed identifier, the investigators could connect data from the hospital systems to understand whether someone was eligible for the study. The method of recruitment was significantly more efficient than the typical process for most clinical trials.