RESUMEN
BACKGROUND: The United States faces a growing challenge with over 6.5 million people living with dementia (PLwD). PLwD and their caregivers struggle with cognitive, functional, behavioral, and psychosocial issues. As dementia care shifts to home settings, caregivers receive inadequate support but bear increasing responsibilities, leading to higher healthcare costs. In response, the Centers for Medicare & Medicaid Services (CMS) introduced the Guiding an Improving Dementia Experience (GUIDE) Model. The study explores the real-world implementation of the Cedars-Sinai C.A.R.E.S. Program, a pragmatic dementia care model, detailing its recruitment process and initial outcomes. METHODS: The Cedars-Sinai C.A.R.E.S. Program was integrated into the Epic electronic health record system and focused on proactive patient identification, engagement, interdisciplinary collaboration, care transitions, and ongoing care management. Eligible patients with a dementia diagnosis were identified through electronic health record and invited to join the program. Nurse practitioners with specialized training in dementia care performed comprehensive assessments using the CEDARS-6 tool, leading to personalized care plans developed in consultation with primary care providers. Patients benefited from a multidisciplinary team and support from care navigators. RESULTS: Of the 781 eligible patients identified, 431 were enrolled in the C.A.R.E.S. PROGRAM: Enrollees were racially diverse, with lower caregiver strain and patient behavioral and psychological symptoms of dementia (BPSD) severity compared to other programs dementia care programs. Healthcare utilization, including hospitalizations, emergency department (ED) admissions, and urgent care visits showed a downward trend over time. Completion of advanced directives and Physician Order of Life-Sustaining Treatment (POLST) increased after enrollment. CONCLUSION: The Cedars-Sinai C.A.R.E.S. Program offers a promising approach to dementia care. Its real-world implementation demonstrates the feasibility of enrolling a diverse population and achieving positive outcomes for PLwD and their caregivers, supporting the goals of national dementia care initiatives.
RESUMEN
BACKGROUND: While patients with dementia entering the hospital have worse outcomes than those without dementia, early detection of dementia in the inpatient setting is less than 50%. We developed and assessed the positive predictive value (PPV) and feasibility of a novel electronic health record (EHR) banner to identify patients with dementia who present to the inpatient setting using data from the medical record. METHODS: We developed and implemented an EHR algorithm to flag hospitalized patients age ≥65 years with potential cognitive impairment in the Epic EHR system using dementia ICD-10 codes, FDA-approved medications, and the use of the term "dementia" in the emergency department physician note. Medical records were reviewed for all patients who were flagged with an EHR banner from October 2022 to May 2023. RESULTS: A total of 344 individuals were identified who had a banner on their chart of which 280 (81.4%) were either diagnosed with dementia or were on an FDA-approved dementia medication. Forty-three individuals who had confirmed dementia were identified by a medication only (15.4%). Of the patients without confirmed dementia, the majority (N = 33, 9.6%) had a diagnosis of altered mental status, cognitive dysfunction, or mild cognitive impairment. Only 31 individuals (9.0%) had no indication of dementia or cognitive decline in their problem list, past medical history, or medication list. CONCLUSIONS: We found that it was feasible to implement an EHR algorithm for prospective dementia identification with a high PPV. These types of algorithms provide an opportunity to accurately identify hospitalized older individuals for inclusion in quality improvement projects, clinical trials, pay-for-performance programs, and other initiatives.
