Bayesian Hierarchical Models for the Design and Analysis of Studies to Individualize Healthcare [Methods Study], United States, 2015-2020 (ICPSR 39613)
When choosing a treatment, doctors often look at research results that show how well the treatment worked in large groups of people. But many factors can affect how well a treatment works for an individual patient. These factors may include the patient's sex, age, other health problems, or how they responded to treatments in the past. Some patient data sources, such as electronic health records, have this information. But existing statistical methods may not use these data well. For example, existing methods may not be able to take advantage of data that include measurements of a patient's health from more than one point in time.
For this project, the research team developed new methods to analyze data that includes measurements of a patient's health from different points in time. To develop the new methods, the team used a Bayesian approach. Bayesian approaches include findings from previous studies in the analysis, which can make results more accurate.
To access the software and methods, please visit the Neuroconductor website and neuroc_travis GitHub.
Emergency Medicine Palliative Care Access (EMPallA), United States, 2018-2022 (ICPSR 39115)
According to the World Health Organization, palliative care is "an approach that improves the quality of life of patients and their families facing the problems associated with life-threatening illness, through the prevention and relief of suffering by means of early identification and impeccable assessment and treatment of pain and other problems, physical, psycho-social and spiritual." The goal of the study was to generate comparative effectiveness research evidence to support the delivery of coordinated, community-based palliative care that effectively implements care plans consistent with the goals and preferences of older adults with advanced illness and their caregivers.
This study included a pragmatic, two-arm, multi-site randomized controlled trial of older adults (50+ years) with either poor prognosis cancer or end-stage organ failure who were recruited during an emergency department (ED) visit, along with their informal caregivers, to compare nurse-led telephonic case management to facilitated, outpatient specialty palliative care on: 1) quality of life in patients, 2) loneliness, 3) healthcare use in the 12 months following enrollment, 4) symptom burden, 5) caregiver strain, 6) caregiver quality of life, and 7) bereavement.
Matching Complex Patients to Treatments: Innovative Statistical Scoring Methods for Treatment Selection [Methods Study], 2015-2020 (ICPSR 39580)
Patients may respond differently to the same treatment due to differences in personal traits such as age, gender, or the number and type of health problems they have. Researchers use statistical methods to predict how well a treatment may work for patients based on their personal traits. But current methods may not work well if patients have many health problems or are taking other medicines.
In this project, the research team created new methods to figure out which patient traits are related to treatment benefits to help doctors and patients understand the likely treatment benefits for individual patients.
To access the methods, software, and R package, please visit the personalized CRAN webpage and personalized GitHub