Nursing homes (NHs) are complex health care systems that serve increasingly sick patients with advanced comorbid conditions. NHs are often charged with guiding these patients through decisions about the direction of their treatment. NH patients commonly get aggressive care that may be inconsistent with their preferences and of little clinical benefit. Identifying effective approaches that NHs can use to better promote goal-directed care and optimize resources, is a research, public health, and clinical priority. Advance care planning (ACP) is the most consistent modifiable factor associated with better palliative care outcomes. Traditional ACP relies on verbal descriptions of hypothetical health states and treatments. This approach is limited because complex scenarios are difficult to envision, counseling is inconsistent, and verbal explanations are hindered by literacy and language barriers. To address these shortcomings, we developed ACP video decision support tools and have shown their efficacy in small randomized controlled trials (RCTs). While several large health care systems, including the state of Hawaii, have begun to adopt the videos, these efforts are being not designed to rigorously evaluate outcomes;a critical step prior to widespread implementation. The overall objective of this proposal is to plan and conduct a pragmatic cluster RCT to evaluate the effectiveness of ACP video decision support tools in the NH setting by partnering with 2 large health care systems which operate 492 NHs nationwide. Over an 18-month period, a suite of ACP video decision support tools will be implemented facility-wide in the intervention NHs. Control NHs will employ their usual ACP practices. All outcomes will be assessed using established data sources, namely, state-of-the-art electronic medical records linked to Medicare and Minimum Data Set databases. The UH2 planning phase aims are to establish the project's organizational and leadership structure (Aim 1) develop all processes and infrastructure to conduct the trial (Aim 2), and pilot test the protocol in 2 NHs (Aim 3). In the U3 implementation phase, we will conduct the trial in up to 266 NHs (133/arm) (Aim 1). Outcomes will be compared in the intervention vs. control NHs among 3 patient groups;i. long-stay residents with targeted advanced chronic illnesses (dementia, heart failure, and chronic obstructive lung disease) (Aim 2), ii. post-acute care admissions with these advanced illnesses (Aim 3), and iii. all other NH patients without the targeted advanced illnesses (Aim 4). Outcomes will include: 1. hospital transfers, 2. advance directives, 3. other burdensome treatments, and 4. hospice use. Hospital transfers over 12-months in the long-stay advanced illness cohort, is the primary trial outcome. IMPACT: NHs serve the most frail and vulnerable patients. Interventions to deliver more patient-focused, cost- effective care in this setting are needed. Better ACP offers an opportunity to improve NH care. Video decision support is a practical and innovative approach to uniformly provide ACP. This work has the potential to improve the care provided to millions of older Americans in NHs and enable future pragmatic trials in this setting.
NHs serve the most frail and vulnerable patients. Interventions to deliver more patient-focused, cost-effective care in this setting are needed. Better advanced care planning offers an opportunity to improve NH care. Video decision support is a practical and innovative approach to uniformly provide advanced care planning. This work has the potential to improve the care provided to millions of older Americans in NHs and enable future pragmatic trials in this setting.
|McCreedy, Ellen; Loomer, Lacey; Palmer, Jennifer A et al. (2018) Representation in the Care Planning Process for Nursing Home Residents With Dementia. J Am Med Dir Assoc 19:415-421|
|Weinfurt, Kevin P; Hernandez, Adrian F; Coronado, Gloria D et al. (2017) Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory. BMC Med Res Methodol 17:144|
|Simon, Gregory E; Coronado, Gloria; DeBar, Lynn L et al. (2017) Data Sharing and Embedded Research. Ann Intern Med 167:668-670|