The prevalence of inflammatory bowel diseases (IBD) in older adults (?65y) is rising, and there is limited evidence-based guidance on treating these older adults. In older patients with multi-morbidity, treatment decisions should factor in not only risk of disease complications, but also treatment complications and non-IBD, extra-intestinal complications. Hence, to inform optimal treatment approach, a comprehensive assessment of comparative effects of different therapies on all of these outcomes is warranted. Existing single-center observational studies are limited by small sample size, and missing data due to fragmented health care, whereas administrative claims-based studies are limited by lack of detailed clinical data; these limitations can be overcome by linking the two data sources. In this patient-oriented mentored career development award proposal, Dr. Siddharth Singh proposes to:
(Aim #1. 1) characterize disease burden and treatment patterns, (Aim #1.2) assess and predict risks of death, disease, treatment and extra-intestinal complications using machine-learning algorithms and (Aim #2.1) compare overall effectiveness and (Aim #2.2) safety of different treatment strategies in older patients with IBD. This will be studied using a highly innovative informatics-based approach in a multi-site, electronic medical record (EMR)-based cohort of older patients with IBD, linked to their corresponding Medicare claims. The EMR-based cohort will facilitate phenotyping and disease severity assessment, and linkage to Medicare claims will augment exposure and outcome ascertainment, overcoming challenges of fragmentation of healthcare and short follow-up. The central hypothesis is that, that older adults have systematically different risk profiles than younger adults, and using biologic monotherapy is a safer and more effective approach to treating IBD, as compared to using long-term corticosteroids alone, non-biologic immunomodulator monotherapy, and combination therapy of biologics and immunomodulators. The access to the advanced infrastructure of pSCANNER (Patient-centered Scalable National Network for Effectiveness Research), one of 13 PCORI-funded Clinical Data Research Networks, and entire Medicare database, in a highly supportive and conducive environment at UCSD, with cross-disciplinary mentorship by a collaborative and experienced team of mentors and advisors from diverse backgrounds (clinical informatics, comparative effectiveness research, IBD therapeutics) is a key strength of this application. Besides directly informing clinical practice on treatment approaches in older patients with IBD, this proposal will enhance the career of the candidate by providing unique skills in applied clinical informatics, privacy-preserving record linkage techniques, predictive analytics, and comparative effectiveness research, and create a multi-institutional, EMR- based cohort of well-characterized IBD patients, linked with Medicare claims. This will ultimately contribute to the candidate's long-term goal of establishing an independent IBD research career focusing on comparative effectiveness research and population health management using novel informatics-based approaches.

Public Health Relevance

The information on comparative effectiveness and safety of different therapies in the context of patients' risk profile generated using this novel informatics-based approach in a unique linked EMR-Medicare database, will directly inform treatment of older patients with IBD, and enhance comparative effectiveness research methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
5K23DK117058-03
Application #
9919547
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Saslowsky, David E
Project Start
2018-07-01
Project End
2023-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093