Research Scientist

The Research Scientist at the School of Public Health is responsible for the investigation of deficits within scientific knowledge. The Research Scientist will devise, formulate, and execute investigative protocols and disseminate their insights through the publishing of findings in authoritative publications and documents. They create and research and presentations; spearhead data collection, analysis, and interpretation; and function as co-lead for joint research undertakings.

The Research Scientist works within the center of Center for Gerontology & Health Care Research with PIs Andrew Zullo, PharmD, PhD, Kaley Hayes, PharmD, PhD, and Nina Joyce, PhD, faculty in the Departments of Epidemiology and Health Services, Policy, and Practice at the Brown University School of Public Health. Individuals in the position will also work with a variety of collaborators at other institutions, including the Hebrew SeniorLife Hinda and Arthur Marcus Institute For Aging Research, the University of Pennsylvania Perelman School of Medicine, the Duke University Department of Medicine, and the Indiana University Center for Aging Research.

This position will involve working on two or more of the following National Institute on Aging-funded projects:

• Post-Acute Care Medication Use and Functional Recovery in Heart Failure (R01AG088522): Although many older adults require rehabilitation in skilled nursing facilities (SNFs) following a hospitalization for heart failure, research on how medications enhance or interfere with rehabilitation is scarce. This project will rigorously examine the effects of using individual medications for heart failure and other common conditions (e.g., pain) as well as using multiple medications together on physical function and successful discharge from SNFs to home. Findings from this project will 1) inform prescribing and deprescribing interventions to sustain optimal physical function following a hospitalization for heart failure and 2) open new frontiers in aging and heart failure research by establishing a novel data resource that can be re-used to conduct previously impossible medication-related studies in SNFs.
• Prescribing Cascades among Nursing Home Residents with ADRD (RF1AG089541): Prescribing cascades are an insidious type of suboptimal medication prescribing that occurs when adverse events from one medication are misinterpreted as symptoms of a new medical condition and result in the addition of a new unnecessary medication, thereby predisposing patients to additional adverse events and major harms. This research will identify important prescribing cascades and rigorously examine their effects on health outcomes in older nursing home residents with Alzheimer's Disease and Related Dementias. Study findings will provide evidence that directly informs medication prescribing, deprescribing, and management to improve the safe use of medications among nursing home residents with Alzheimer's Disease and Related Dementias.
• Models of Post-Acute Care in Complex Older Adults with Fracture (PCORI; NCT06304428): This study will compare two care models that have previously been shown to improve care in skilled nursing facilities. One model is a Fracture Liaison Service, in which recommendations are given to manage osteoporosis (weak bones) with medications. The second model is a Deprescribing Care Model, which helps patients reduce medications that cause falls. Both models are led by a remote nurse who will review electronic health records and consult with an external team of experts to devise a personalized medication treatment plan. The nurse will provide information about osteoporosis treatment and/or reducing medications to patients and families by phone so that they can decide together what changes to make. The nurse will communicate recommendations to the skilled nursing facility staff and/or the community primary care providers. Involving patients and providers in the decision-making process will ensure that medication changes represent the values of the patient.
• The NH Explanatory Trials Network: Supporting Transformation by Enhancing Partnerships (The NEXT STEPS) (U24AG087939): Nursing homes (NHs) continue to be a critical component of the U.S. system of post-acute and long-term care for people with multiple chronic conditions (MCCs), Alzheimer’s disease and related dementias (ADRD), serious illness, and functional impairment, yet numerous challenges remain to achieving consistent quality care that optimizes resident outcomes. There is widespread, long-standing consensus that NHs are a challenging setting for research. The NEXT STEPs (Nursing Home EXplanatory Clinical Trials: Supporting Transformation by Enhancing Partnerships) Network creates a national infrastructure that will address systemic barriers to conducting research in NHs.

Education and Experience

Doctoral Degree and 5 years’ experience or equivalent combination of education and experience.

Job Competencies

• Expertise and demonstrated experience in observational and/or experimental study design.
• Proficiency and demonstrated experience in quantitative and/or qualitative research.
• Proficiency with or a willingness to learn about the Open Science Framework and Github, including topics such as the need for registration of pre-analysis plans.
• Some knowledge of or a willingness to learn about the United States Health Care System, including standard healthcare coding systems such as International Classification of Diseases versions 9 and 10 (ICD-9 and ICD 10), Current Procedural Terminology (CPT), Healthcare Common Procedure Coding System (HCPCS), and Diagnosis Related Group (DRG) codes
• Some experience with or a willingness to learn about ICD-9 to ICD-10 General Equivalence Mappings (GEMs) and Healthcare Cost and Utilization Project (HCUP) Clinical Classifications Software for Services and Procedures Experience with CMS claims and beneficiary assessment data, particularly prescription drug claims (e.g., Medicare Part D), as well as familiarity with means of deriving medication use and adherence estimates from claims data.
• Some experience analyzing and managing large complex data sets, specifically healthcare claims or electronic health record datasets.
• Some prior experience with using a statistical programming language (i.e., R, Python, Stata, SAS, or similar).

• Strong communication skills, in both written and verbal formats.
• Strong interpersonal skills, including the ability to develop and maintain relationships.

• Must be able to accurately write and report on empirical findings in peer-reviewed manuscripts and conference presentations.
• Must be observant and self-motivated, able to think critically and problem solve.

• Must be able to deploy well-developed time management skills.
• Excellent computer skills: Microsoft Word, Creation of charts & graphs using Microsoft Excel and Power Point, and analysis of data.
• Some interest in mentoring trainees, junior faculty, and staff.

Additional physical demands and working conditions: Hybrid Eligible.
 

All candidates must possess a willingness and ability to support a diverse and inclusive environment.
 

All offers of employment are contingent upon a criminal background check and education verification that are satisfactory to Brown University.
 

This full-time fixed-term position has an end-date of December 31, 2029 and may be extended based on the availability of grant funding.