Improving Prediction of Long-Term Care Utilization Through Patient-Reported Measures: Cross-Sectional Analysis of High-Need U.S. Veterans Affairs Patients

2021 ◽  
pp. 107755872110624
Author(s):  
Josephine C. Jacobs ◽  
Matthew L. Maciejeweski ◽  
Todd H. Wagner ◽  
Courtney H. Van Houtven ◽  
Jeanie Lo ◽  
...  
Keyword(s):  
Social Support ◽  
Long Term Care ◽  
Model Performance ◽  
Veterans Affairs ◽  
Information Criteria ◽  
Health Administration ◽  
Term Care ◽  
Patient Reported ◽  
Patient Reported Measures

This article examines the relative merit of augmenting an electronic health record (EHR)-derived predictive model of institutional long-term care (LTC) use with patient-reported measures not commonly found in EHRs. We used survey and administrative data from 3,478 high-risk Veterans aged ≥65 in the U.S. Department of Veterans Affairs, comparing a model based on a Veterans Health Administration (VA) geriatrics dashboard, a model with additional EHR-derived variables, and a model that added survey-based measures (i.e., activities of daily living [ADL] limitations, social support, and finances). Model performance was assessed via Akaike information criteria, C-statistics, sensitivity, and specificity. Age, a dementia diagnosis, Nosos risk score, social support, and ADL limitations were consistent predictors of institutional LTC use. Survey-based variables significantly improved model performance. Although demographic and clinical characteristics found in many EHRs are predictive of institutional LTC, patient-reported function and partnership status improve identification of patients who may benefit from home- and community-based services.

scholarly journals A Cross-Sectional Study on the Impacts of Perceived Job Value, Job Maintenance, and Social Support on Burnout among Long-Term Care Staff in Hawaii

2021 ◽  
Vol 18 (2) ◽  
pp. 476
Author(s):  
Bum Jung Kim ◽  
Sun-young Lee
Keyword(s):  
Social Support ◽  
Long Term Care ◽  
Cross Sectional Study ◽  
Care Staff ◽  
Hierarchical Regression ◽  
Sectional Study ◽  
Cross Sectional ◽  
Term Care ◽  
The Impact

Extensive research has demonstrated the factors that influence burnout among social service employees, yet few studies have explored burnout among long-term care staff in Hawaii. This study aimed to examine the impact of job value, job maintenance, and social support on burnout of staff in long-term care settings in Hawaii, USA. This cross-sectional study included 170 long-term care staff, aged 20 to 75 years, in Hawaii. Hierarchical regression was employed to explore the relationships between the key independent variables and burnout. The results indicate that staff with a higher level of perceived job value, those who expressed a willingness to continue working in the same job, and those with strong social support from supervisors or peers are less likely to experience burnout. Interventions aimed at decreasing the level of burnout among long-term care staff in Hawaii may be more effective through culturally tailored programs aimed to increase the levels of job value, job maintenance, and social support.

America Loves and Cares for Veterans

2021 ◽  
Vol 36 (1) ◽  
pp. 63-63
Author(s):  
Paul Baldwin
Keyword(s):  
Long Term Care ◽  
Veterans Affairs ◽  
State Funding ◽  
Department Of Veterans Affairs ◽  
Term Care ◽  
Us Veterans

The author discusses benefits available to US Veterans starting with the Department of Veterans Affairs and going into state funding and long-term care benefits.

scholarly journals Automated Nationwide Benchmarking Dashboard for Antimicrobial Stewardship Programs within the Veterans’ Health Administration

2021 ◽  
Vol 1 (S1) ◽  
pp. s23-s24
Author(s):  
Michihiko Goto ◽  
Eli Perencevich ◽  
Alexandre Marra ◽  
Bruce Alexander ◽  
Brice Beck ◽  
...  
Keyword(s):  
Acute Care ◽  
Antimicrobial Stewardship ◽  
Risk Adjustment ◽  
Long Term Care ◽  
Antimicrobial Use ◽  
Veterans Health ◽  
Health Administration ◽  
Term Care ◽  
Patient Level

Group Name: VHA Center for Antimicrobial Stewardship and Prevention of Antimicrobial Resistance (CASPAR) Background: Antimicrobial stewardship programs (ASPs) are advised to measure antimicrobial consumption as a metric for audit and feedback. However, most ASPs lack the tools necessary for appropriate risk adjustment and standardized data collection, which are critical for peer-program benchmarking. We created a system that automatically extracts antimicrobial use data and patient-level factors for risk-adjustment and a dashboard to present risk-adjusted benchmarking metrics for ASP within the Veterans’ Health Administration (VHA). Methods: We built a system to extract patient-level data for antimicrobial use, procedures, demographics, and comorbidities for acute inpatient and long-term care units at all VHA hospitals utilizing the VHA’s Corporate Data Warehouse (CDW). We built baseline negative binomial regression models to perform risk-adjustments based on patient- and unit-level factors using records dated between October 2016 and September 2018. These models were then leveraged both retrospectively and prospectively to calculate observed-to-expected ratios of antimicrobial use for each hospital and for specific units within each hospital. Data transformation and applications of risk-adjustment models were automatically performed within the CDW database server, followed by monthly scheduled data transfer from the CDW to the Microsoft Power BI server for interactive data visualization. Frontline antimicrobial stewards at 10 VHA hospitals participated in the project as pilot users. Results: Separate baseline risk-adjustment models to predict days of therapy (DOT) for all antibacterial agents were created for acute-care and long-term care units based on 15,941,972 patient days and 3,011,788 DOT between October 2016 and September 2018 at 134 VHA hospitals. Risk adjustment models include month, unit types (eg, intensive care unit [ICU] vs non-ICU for acute care), specialty, age, gender, comorbidities (50 and 30 factors for acute care and long-term care, respectively), and preceding procedures (45 and 24 procedures for acute care and long-term care, respectively). We created additional models for each antimicrobial category based on National Healthcare Safety Network definitions. For each hospital, risk-adjusted benchmarking metrics and a monthly ranking within the VHA system were visualized and presented to end users through the dashboard (an example screenshot in Figure 1). Conclusions: Developing an automated surveillance system for antimicrobial consumption and risk-adjustment benchmarking using an electronic medical record data warehouse is feasible and can potentially provide valuable tools for ASPs, especially at hospitals with no or limited local informatics expertise. Future efforts will evaluate the effectiveness of dashboards in these settings.Funding: NoDisclosures: None

scholarly journals A Qualitative Work System Analysis Using a Human Factors Engineering Approach to Evaluate Environmental Cleaning in Veterans’ Affairs Hospitals

2021 ◽  
Vol 1 (S1) ◽  
pp. s62-s63
Author(s):  
Linda McKinley ◽  
Cassie Goedken ◽  
Erin Balkenende ◽  
Stacey Hockett Sherlock ◽  
Heather Reisinger ◽  
...  
Keyword(s):  
Human Factors ◽  
System Analysis ◽  
Long Term Care ◽  
Veterans Affairs ◽  
Human Factors Engineering ◽  
Term Care ◽  
Environmental Cleaning ◽  
Veterans Affairs Hospitals ◽  
Environmental Surfaces

Background: Environmental cleaning is important in the interruption of pathogen transmission and subsequent infection. Although recent initiatives have targeted cleaning of high-touch surfaces and incorporated audit-and-feedback monitoring of cleaning practices, practice variations exist and compliance is still reportedly low. Evaluation of human factors influencing variations in cleaning practices can be valuable in developing interventions, leading to standardized practices and improved compliance. We conducted a work system analysis using a human-factors engineering framework [the Systems Engineering Initiative for Patient Safety (SEIPS) model] to identify barriers and facilitators to current environmental cleaning practices within Veterans’ Affairs hospitals. Methods: We conducted semistructured interviews with key stakeholders (ie, environmental staff, nursing, and infection preventionists) at 3 VA facilities across acute-care and long-term care settings. Interviews were conducted among 18 healthcare workers, audio recorded, and transcribed verbatim. Transcripts were analyzed for thematic content within the SEIPS constructs (ie, person, environment, organization, tasks, and tools). Results: Within the SEIPS domain ‘person,’ we found that many environment service (EVS) staff were veterans and were highly motivated to serve fellow veterans, especially to prevent them from acquiring infections. However, the hiring of service members as EVS staff comes with significant hurdles that affect staffing. Within the domain of ‘environment’, EVS staff reported rooms that were either occupied by the patient or were multibed, were more difficult to clean. Conversely, they reported that it was easier to clean in settings where the patient was more likely to be out of bed (eg, long-term care residents). Patient flow and/or movement greatly influenced workload within the ‘organizational’ domain. Workload also changed by patient population and setting (eg, the longer the stay or more critical the patient), increased their workload. EVS staff felt that staffing consistency and experience improved cleaning practices. Within the ‘task’ domain, EVS staff were motivated for cleaning high-touch surfaces; however, knowledge of these surfaces varied. Finally, within the ‘tool’ domain, most EVS staff described having effective cleaning products; however, sometimes in limited supply. Most sites reported some form of monitoring of their cleaning process; however, there was variation in type and frequency. Conclusions: Human-factors analysis identified barriers to and facilitators of cleaning compliance. Incorporating environmental cleaning practices that address barriers and facilitators identified may facilitate standardized cleaning of environmental surfaces. Standardized procedures for cleaning multibed rooms and environmental surfaces surrounding occupied beds may improve cleaning compliance. Future research should evaluate standardized cleaning procedures or bundles that incorporate these best practices and steps to overcoming barriers and pilot feasibility.Funding: NoDisclosures: None

Changes in antibiotic use following implementation of a telehealth stewardship pilot program

2019 ◽  
Vol 40 (7) ◽  
pp. 810-814 ◽  
Author(s):  
Brigid M. Wilson ◽  
Richard E. Banks ◽  
Christopher J. Crnich ◽  
Emma Ide ◽  
Roberto A. Viau ◽  
...  
Keyword(s):  
Antibiotic Stewardship ◽  
Long Term Care ◽  
Antibiotic Use ◽  
Veterans Affairs ◽  
Term Care ◽  
Medical Centers ◽  
Stewardship Program ◽  
Days Of Therapy ◽  
Veterans Affairs Medical Centers

AbstractStarting in 2016, we initiated a pilot tele-antibiotic stewardship program at 2 rural Veterans Affairs medical centers (VAMCs). Antibiotic days of therapy decreased significantly (P < .05) in the acute and long-term care units at both intervention sites, suggesting that tele-stewardship can effectively support antibiotic stewardship practices in rural VAMCs.

scholarly journals 1238. A National Comparison of Antibiograms Between Veterans Affairs Long-Term Care Facilities and Affiliated Hospitals

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S376-S377 ◽  
Author(s):  
Maria-Stephanie Tolg ◽  
Aisling Caffrey ◽  
Haley Appaneal ◽  
Robin Jump ◽  
Vrishali Lopes ◽  
...  
Keyword(s):  
Long Term Care ◽  
Veterans Affairs ◽  
Self Report ◽  
Chi Square ◽  
Term Care ◽  
E Coli ◽  
Care Facilities ◽  
National Comparison ◽  
Research Grant

Abstract Background Long-term care facilities (LTCFs) face several barriers to creating antibiograms. Here, we evaluate if LTCFs can use antibiograms from affiliated hospitals as their own antibiogram. Methods Facility-specific antibiograms were created for all Veterans Affairs (VA) LTCFs and VA Medical Centers (VAMCs) for 2017. LTCFs and affiliated VAMCs were paired and classified as being on the same campus or geographically distinct campuses based on self-report. For each pair, Escherichia coli susceptibility rates (%S) to cefazolin, ceftriaxone, cefepime, ciprofloxacin, nitrofurantoin, sulfamethoxazole/trimethoprim, ampicillin/sulbactam, piperacillin/tazobactam, and imipenem were compared. As guidelines discourage empiric use of antibiotics if susceptibility rates are &lt;80%, we assessed clinical discordance between each LTCF and affiliated VAMC antibiogram at a threshold of 80% susceptible. The proportions of concordant susceptibilities between LTCFs and VAMCs on the same campus vs. geographically distinct campuses were compared using Chi-square tests. Results A total of 119 LTCFs and their affiliated VAMCs were included in this analysis, with 70.6% (n = 84) of facilities located on the same campus and 29.4% (n = 35) on geographically distinct campuses. The table below shows the overall clinical concordance (agreement) of LTCFs with their affiliated VAMC in regards to E. coli %S to the compared antibiotics. No significant differences were found when comparing LTCFs on the same campus vs. geographically distinct campuses. Conclusion Antibiograms between LTCFs and affiliated VAMCs had a high concordance, except for sulfamethoxazole/trimethoprim, cefazolin and ceftriaxone in regards to susceptibility rates of E. coli. Facilities on the same campus were found to have similar concordance rates to geographically distinct facilities. Future studies are needed to investigate how the various approaches to creating LTCF-specific antibiograms are associated with clinical outcomes. Disclosures M. S. Tolg, Veterans Affairs: Investigator, Research grant. A. Caffrey, Veterans Affairs: Investigator, Research grant. H. Appaneal, Veterans Affairs: Grant Investigator, Research grant. R. Jump, Veterans Affairs: Investigator, Research grant. V. Lopes, Veterans Affairs: Investigator, Research grant. D. Dosa, Veterans Affairs: Grant Investigator, Research grant. K. LaPlante, Veterans Affairs: Investigator, Research grant.

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