Uncertainty as a Key Influence in the Decision To Admit Patients with Transient Ischemic Attack.

BACKGROUND: Patients with transient ischemic attacks (TIA) are at high risk of subsequent vascular events. Hospitalization improves quality of care, yet admission rates for TIA patients vary considerably. OBJECTIVES: We sought to identify factors associated with the decision to admit patents with TIA. DESIGN: We conducted a secondary analysis of a prior study's data including semi-structured interviews, administrative data, and chart review. PARTICIPANTS: We interviewed multidisciplinary clinical staff involved with TIA care. Administrative data included information for TIA patients in emergency departments or inpatient settings at VA medical centers (VAMCs) for fiscal years (FY) 2011 and 2014. Chart reviews were conducted on a subset of patients from 12 VAMCs in FY 2011. APPROACH: For the qualitative data, we focused on interviewees' responses to the prompt: "Tell me what influences you in the decision to or not to admit TIA patients." We used administrative data to identify admission rates and chart review data to identify ABCD2 scores (a tool to classify stroke risk after TIA). KEY RESULTS: Providers' decisions to admit TIA patients were related to uncertainty in several domains: lack of a facility TIA-specific policy, inconsistent use of ABCD2 score, and concerns about facilities' ability to complete a timely workup. There was a disconnect between staff perceptions about TIA admission and facility admission rates. According to chart review data, staff at facilities with higher admission rates in FY 2011 reported consistent reliance on ABCD2 scores and related guidelines in admission decision-making. CONCLUSIONS: Many factors contributed to decisions regarding admitting a patient with TIA; however, clinicians' uncertainty appeared to be a key driver. Further quality improvement interventions for TIA care should focus on facility adoption of TIA protocols to address uncertainty in TIA admission decision-making and to standardize timely evaluation of TIA patients and delivery of secondary prevention strategies.

A second wave of COVID-19 in Cook County: What lessons can be applied?

During the ongoing public health crisis, many agencies are reporting COVID-19 health outcome information based on the overall population. This practice can lead to misleading results and underestimation of high risk areas. To gain a better understanding of spatial and temporal distribution of COVID-19 deaths; the long term care facility (LTCF) and household population (HP) deaths must be used. This approach allows us to better discern high risk areas and provides policy makers with reliable information for community engagement and mitigation strategies. By focusing on high-risk LTCFs and residential areas, protective measures can be implemented to minimize COVID-19 spread and subsequent mortality.  These areas should be a high priority target when COVID-19 vaccines become available.

Cost analysis of the Geriatric Resources for Assessment and Care of Elders care management intervention.

OBJECTIVES: To provide, from the healthcare delivery system perspective, a cost analysis of the Geriatric Resources for Assessment and Care of Elders (GRACE) intervention, which is effective in improving quality of care and outcomes. DESIGN: Randomized controlled trial with physicians as the unit of randomization. SETTING: Community-based primary care health centers. PARTICIPANTS: Nine hundred fifty-one low-income seniors aged 65 and older; 474 participated in the intervention and 477 in usual care. INTERVENTION: Home-based care management for 2 years by a nurse practitioner and social worker who collaborated with the primary care physician and a geriatrics interdisciplinary team and were guided by 12 care protocols for common geriatric conditions. MEASUREMENTS: Chronic and preventive care costs, acute care costs, and total costs in the full sample (n5951) and predefined high-risk (n5226) and low-risk (n5725) groups. RESULTS: Mean 2-year total costs for intervention patients were not significantly different from those for usual care patients in the full sample ($14,348 vs $11,834; P=.20) and high-risk group ($17,713 vs $18,776; P=.38). In the high-risk group, increases in chronic and preventive care costs were offset by reductions in acute care costs, and the intervention was cost saving during the postintervention, or third, year ($5,088 vs $6,575; P<.001). Mean 2- year total costs were higher in the low-risk group ($13,307 vs $9,654; P=.01). CONCLUSION: In patients at high risk of hospitalization, the GRACE intervention is cost neutral from the healthcare delivery system perspective. A cost-effectiveness analysis is needed to guide decisions about implementation in low-risk patients.