Integrating Geriatric Assessment for Older Patients Diagnosed With Acute Myelogenous Leukemia
Purpose
Despite the suggestions that GA and frailty indices could be used to guide therapy selection, the ability to effectively incorporate the use of GA in older patients diagnosed with AML in a real-world clinic environment has not yet been established. Thus, in this study, the investigators seek to describe the feasibility of using this shorter GA tool, the mGA, administered via patient self-report on a touchscreen computer, as well as the real-time use and utility by clinicians and the correlation of mGA results on treatment decision-making.
Condition
- Acute Myeloid Leukemia
Eligibility
- Eligible Ages
- Over 60 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- All participants must be adults ages 18 years of age or older. - Patient participants must have a diagnosis of AML. - Patients may be newly diagnosed, needing a new line of therapy and have not yet made a treatment decision, or on treatment and being assessed for potential new treatment - All participants must be able to understand English.
Exclusion Criteria
- Any patient who cannot understand written or spoken English. - Any prisoner and/or other vulnerable persons as defined by NIH (45 CFR 46, Subpart B, C and D).
Study Design
- Phase
- N/A
- Study Type
- Interventional
- Allocation
- N/A
- Intervention Model
- Single Group Assignment
- Primary Purpose
- Health Services Research
- Masking
- None (Open Label)
More Details
- Status
- Completed
- Sponsor
- Carevive Systems, Inc.
Study Contact
Detailed Description
This outcomes study has a two-part intervention that includes 1) provider education and 2) patient and provider use of Carevive Treatment Care Planning technology. The provider education component of the intervention highlights evidenced guidelines and investigational agents in the treatment of AML in older adults. The Carevive CPS will be used for the second component of the intervention. The results of this study will provide important information about drivers of treatment decision-making and practice patterns, feasibility of a technology platform to incorporate important, but under-utilized components of value-based care into practice, and healthcare utilization data.