Building a National Standard for Outreach and Assistance to At-Risk Patients During Large-Scale Disasters.

Health care institutions play an essential role in community resilience. As one of the largest health care systems in the United States, the Veterans Health Administration (VHA) plays a critical role in supporting medically vulnerable Veterans during disasters. Disasters require large-scale outreach to individuals in affected areas, including the capability to identify patients, establish contact, determine needs, and deliver required services. Here we describe the development and implementation of VHA's Vulnerable Patient Care, Access, and Response in Emergencies (VP CARE) program, a data-driven system of outreach to preidentified medically vulnerable patients, which seeks to streamline this process. VP CARE was inspired by the VHA's Home-Based Primary Care (HBPC) program and the US Department of Health and Human Services' emPOWER program. It seeks to enhance Veteran patients' well-being and continuity of care during disasters using 3 components: (1) improving the readiness and resilience of vulnerable patients and their caregivers; (2) establishing an organization, policies, procedures, and competency-based training exercises to guide outreach and assistance; and (3) creating and implementing standardized 1- and 2-way outreach technology and reporting. Using Geographic Information Systems embedded in VP CARE, VHA can generate a list of high-risk patients and deploy a 2-way texting capability to contact and receive responses from them. VP CARE automatically tracks patient contact and responses, reducing duplication of effort and freeing up VA staff to focus on patients with immediate needs. Patients and their caregivers benefit from the reassurance of knowing that VHA is focused on their well-being and available to support them. The technologies deployed in VP CARE improve the efficiency of outreach efforts and reduce the risk of life-threatening harm, while reducing the cost and demands on VA staff. This article concludes with lessons learned that may be instructive for other health care systems seeking to establish similar outreach capabilities.

Proportion of SARS-CoV-2 positive tests and vaccination in Veterans Affairs Community Living Centers.

BACKGROUND/OBJECTIVES: COVID-19 has caused significant morbidity and mortality in nursing homes. Vaccination against SARS-COV-2 holds promise for reduction in COVID-19. This operational analysis describes the proportion of SARS-COV-2 positive tests before, during, and after vaccination. DESIGN: Retrospective longitudinal cohort analysis from October 1, 2020 until February 14, 2021. SETTING: A total of 130 Department of Veterans Affairs (VA) Community Living Centers (CLC), analogous to nursing homes. INTERVENTION: Vaccination for SARS-CoV-2. MEASUREMENTS: The primary measure is the proportion of SARS-CoV-2 positive tests among CLC residents. In a pooled analysis of weekly testing and vaccine data, the proportion of positive tests was compared for the unvaccinated, first dose, and second dose. For each CLC, we identified the week in which 50% of CLC residents were vaccinated (index week). The analysis aligned the index week for CLCs and examined the proportion of SARS-CoV-2 positive tests at the CLC level before and after. As a reference, we plotted the proportion of positive tests in nursing homes in the same county as the CLC using publicly reported data. RESULTS: Within the pooled VA CLCs, the first SARS-CoV-2 vaccine dose was delivered to 50% of CLC residents within 1 week of availability and second dose within 5 weeks. Relative to the index week, the risk ratio of SARS-CoV-2 positive tests in the vaccinated relative to unvaccinated was significantly lower in Week 4 (relative risk 0.37, 95% confidence interval 0.20-0.68). Throughout the study period, the proportion of SARS-CoV-2 positive tests in community nursing homes was higher compared to VA CLC and also declined after vaccine availability. CONCLUSION: The proportion of SARS-CoV-2 positive tests significantly declined in VA CLCs 4 weeks after vaccine delivery and continued to decline in vaccinated and unvaccinated residents. The results describe the importance of SARS-CoV-2 surveillance and vaccination in VA nursing home residents.

Modeling Patient No-Show History and Predicting Future Appointment Behavior at the Veterans Administration's Outpatient Mental Health Clinics: NIRMO-2.

INTRODUCTION: No-shows are detrimental to both patients' health and health care systems. Literature documents no-show rates ranging from 10% in primary care clinics to over 60% in mental health clinics. Our model predicts the probability that a mental health clinic outpatient appointment will not be completed and identifies actionable variables associated with lowering the probability of no-show. MATERIALS AND METHODS: We were granted access to de-identified administrative data from the Veterans Administration Corporate Data Warehouse related to appointments at 13 Veterans Administration Medical Centers. Our modeling data set included 1,206,271 unique appointment records scheduled to occur between January 1, 2013 and February 28, 2017. The training set included 846,668 appointment records scheduled between January 1, 2013 and December 31, 2015. The testing set included 359,603 appointment records scheduled between January 1, 2016 and February 28, 2017. The dependent binary variable was whether the appointment was completed or not. Independent variables were categorized into seven clusters: patient's demographics, appointment characteristics, patient's attendance history, alcohol use screening score, medications and medication possession ratios, prior diagnoses, and past utilization of Veterans Health Administration services. We used a forward stepwise selection, based on the likelihood ratio, to choose the variables in the model. The predictive model was built using the SAS HPLOGISTIC procedure. RESULTS: The best indicator of whether someone will miss an appointment is their historical attendance behavior. The top three variables associated with higher probabilities of a no-show were: the no-show rate over the previous 2 years before the current appointment, the no-show probability derived from the Markov model, and the age of the appointment. The top three variables that decrease the chance of no-showing were: the appointment was a new consult, the appointment was an overbook, and the patient had multiple appointments on the same day. The average of the areas under the receiver operating characteristic curves was 0.7577 for the training dataset, and 0.7513 for the test set. CONCLUSIONS: The National Initiative to Reduce Missed Opportunities-2 confirmed findings that previous patient attendance is one of the key predictors of a future attendance and provides an additional layer of complexity for analyzing the effect of a patient's past behavior on future attendance. The National Initiative to Reduce Missed Opportunities-2 establishes that appointment attendance is related to medication adherence, particularly for medications used for treatment of mood disorders or to block the effects of opioids. However, there is no way to confirm whether a patient is actually taking medications as prescribed. Thus, a low medication possession ratio is an informative, albeit not a perfect, measure. It is our intention to further explore how diagnosis and medications can be better captured and used in predictive modeling of no-shows. Our findings on the effects of different factors on no-show rates can be used to predict individual no-show probabilities, and to identify patients who are high risk for missing appointments. The ability to predict a patient's risk of missing an appointment would allow for both advanced interventions to decrease no-shows and for more efficient scheduling.

A Novel Approach for Ovine Primary Alveolar Epithelial Type II Cell Isolation and Culture from Fresh and Cryopreserved Tissue Obtained from Premature and Juvenile Animals.

The in vivo ovine model provides a clinically relevant platform to study cardiopulmonary mechanisms and treatments of disease; however, a robust ovine primary alveolar epithelial type II (ATII) cell culture model is lacking. The objective of this study was to develop and optimize ovine lung tissue cryopreservation and primary ATII cell culture methodologies for the purposes of dissecting mechanisms at the cellular level to elucidate responses observed in vivo. To address this, we established in vitro submerged and air-liquid interface cultures of primary ovine ATII cells isolated from fresh or cryopreserved lung tissues obtained from mechanically ventilated sheep (128 days gestation-6 months of age). Presence, abundance, and mRNA expression of surfactant proteins was assessed by immunocytochemistry, Western Blot, and quantitative PCR respectively on the day of isolation, and throughout the 7 day cell culture study period. All biomarkers were significantly greater from cells isolated from fresh than cryopreserved tissue, and those cultured in air-liquid interface as compared to submerged culture conditions at all time points. Surfactant protein expression remained in the air-liquid interface culture system while that of cells cultured in the submerged system dissipated over time. Despite differences in biomarker magnitude between cells isolated from fresh and cryopreserved tissue, cells isolated from cryopreserved tissue remained metabolically active and demonstrated a similar response as cells from fresh tissue through 72 hr period of hyperoxia. These data demonstrate a cell culture methodology using fresh or cryopreserved tissue to support study of ovine primary ATII cell function and responses, to support expanded use of biobanked tissues, and to further understanding of mechanisms that contribute to in vivo function of the lung.

Lucinactant attenuates pulmonary inflammatory response, preserves lung structure, and improves physiologic outcomes in a preterm lamb model of RDS.

BACKGROUND: Acute inflammatory responses to supplemental oxygen and mechanical ventilation have been implicated in the pathophysiological sequelae of respiratory distress syndrome (RDS). Although surfactant replacement therapy (SRT) has contributed to lung stability, the effect on lung inflammation is inconclusive. Lucinactant contains sinapultide (KL4), a novel synthetic peptide that functionally mimics surfactant protein B, a protein with anti-inflammatory properties. We tested the hypothesis that lucinactant may modulate lung inflammatory response to mechanical ventilation in the management of RDS and may confer greater protection than animal-derived surfactants. METHODS: Preterm lambs (126.8 ± 0.2 SD d gestation) were randomized to receive lucinactant, poractant alfa, beractant, or no surfactant and studied for 4 h. Gas exchange and pulmonary function were assessed serially. Lung inflammation biomarkers and lung histology were assessed at termination. RESULTS: SRT improved lung compliance relative to no SRT without significant difference between SRT groups. Lucinactant attenuated lung and systemic inflammatory response, supported oxygenation at lower ventilatory requirements, and preserved lung structural integrity to a greater degree than either no SRT or SRT with poractant alfa or beractant. CONCLUSION: These data suggest that early intervention with lucinactant may more effectively mitigate pulmonary pathophysiological sequelae of RDS than the animal-derived surfactants poractant alfa or beractant.

Hyperoxia during one lung ventilation: inflammatory and oxidative responses.

BACKGROUND: It is common practice during one lung ventilation (OLV) to use 100% oxygen, although this may cause hyperoxia- and oxidative stress-related lung injury. We hypothesized that lower oxygen (FiO(2) ) during OLV will result in less inflammatory and oxidative lung injury and improved lung function. METHODS: Twenty pigs (8.88 ± 0.84 kg; 38 ± 4.6 days) were assigned to either the hyperoxia group (n = 10; FiO(2) = 100%) or the normoxia group (n = 10; FiO(2) < 50%). Both groups were subjected to 3 hr of OLV. Blood samples were tested for pro-inflammatory cytokines and lung tissue was tested for these cytokines and oxidative biomarkers. RESULTS: There were no differences between groups for partial pressure of CO(2) , tidal volume, end-tidal CO(2) , plasma cytokines, or respiratory compliance. Total respiratory resistance was greater in the hyperoxia group (P = 0.02). There were higher levels of TNF-α, IL-1ß, and IL-6 in the lung homogenates of the hyperoxia group than in the normoxia group (P ≤ 0.01, 0.001, and 0.001, respectively). Myeloperoxidase and protein carbonyls (PC) were higher (P = 0.03 and P = 0.01, respectively) and superoxide dismutase (SOD) was lower in the lung homogenates of the hyperoxia group (P ≤ 0.001). CONCLUSION: Higher myeloperoxidase, PC, and cytokine levels, and lower SOD availability indicate a greater degree of injury in the lungs of the hyperoxia animals, possibly from using 100% oxygen. In this translational study using a pig model, FiO(2) ≤ 50% during OLV reduced hyperoxic injury and improved function in the lungs.

Prototype hybrid systems for neonatal warming: in vitro comparisons to standard of care devices.

Preterm infants lack necessary thermoregulation. An ideal incubator should maintain a uniform and constant thermal environment. We compared the effectiveness of a supplemental heating blanket to improve the heating characteristics of two different incubator warming devices using assessment of their respective function alone as controls. Device A and device B, with and without a heating blanket (Harvard Apparatus), were instrumented with a distribution matrix of multiple temperature (n = 11) and humidity probes. These data were serially measured during warm up to 37.5 °C and through a series of open-door perturbations. The time constant, temperature variation, and change in air temperature were calculated. Data were analyzed for significance by 2-factor ANOVA for each respective incubator either turned on or off with either the heating blanket turned on or off. Device A warms faster (33.87% ; p < 0.05) than device B, but has a greater (37.27% ; p < 0.05) temperature variation during warmup. The heating blanket enhances the thermal response of device A during warmup, but does not alter those of device B. With the side door open, device A shows a smaller (-16.5% ; p < 0.05) temperature variation than device B; the heating blanket attenuates the temperature change in both devices. These results demonstrate that the use of a supplemental heating blanket, as well as device-related differences, may impact clinical control of a thermal environment.