Development and Validation of a Measure to Assess Patient Experiences With Video Care Encounters

Importance

As video-based care expands in many clinical settings, assessing patient experiences with this care modality will help optimize health care quality, safety, and communication.

Objective

To develop and assess the psychometric properties of the video visit user experience (VVUE) measure, a patient-reported measure of experiences with video-based technology.

Design, Setting, and Participants

In this survey study, veterans completed a web-based, mail, or telephone survey about their use of Veterans Healthcare Administration (VHA) virtual care between September 2021 and January 2022. The survey was completed by patients who reported having a VHA video visit on their own device or a VHA-issued device and linked to VHA utilization data for the 6 months following the survey. Data analysis was performed from March 2022 to February 2023.

Main Outcomes and Measures

The survey included 19 items about experiences with video visits that were rated using a 4-point Likert-type scale (strongly disagree to strongly agree). First, an exploratory factor analysis was conducted to determine the factor structure and parsimonious set of items, using the McDonald Omega test to assess internal consistency reliability. Then, a confirmatory factor analysis was conducted to test structural validity, and bivariate correlations between VVUE and VHA health care engagement were calculated to test concurrent validity. Finally, predictive validity was assessed using logistic regression to determine whether VVUE was associated with future VHA video visit use.

Results

Among 1887 respondents included in the analyses, 83.2% (95% CI, 81.5%-84.8%) were male, 41.0% (95% CI, 38.8%-43.1%) were aged 65 years or older, and the majority had multiple chronic medical and mental health conditions. The exploratory factor analysis identified a 10-item single-factor VVUE measure (including questions about satisfaction, user-centeredness, technical quality, usefulness, and appropriateness), explaining 96% of the total variance, with acceptable internal consistency reliability (ω = 0.95). The confirmatory factor analysis results confirmed a single-factor solution (standardized root mean squared residual = 0.04). VVUE was positively associated with VHA health care engagement (ρ = 0.47; P < .001). Predictive validity models demonstrated that higher VVUE measure scores were associated with future use of video visits, where each 1-point increase on VVUE was associated with greater likelihood of having a video visit in subsequent 6 months (adjusted odds ratio, 1.04; 95% CI, 1.02-1.06).

Conclusions and Relevance

The findings of this study of veterans using video visits suggest that a brief measure is valid to capture veterans' experiences receiving VHA virtual care.

Patterns and predictors of mental health service use among older veterans with alcohol use disorder who received a video-enabled tablet

Objectives: Video-based telehealth may expand access to mental health services among older veterans with alcohol use disorder (AUD). We examined the modalities through which mental health services were rendered, and predictors of video visits before and after video-enabled tablet receipt from the Veterans Health Administration. Method: 11,210 veterans aged 60 or older with a diagnosis of AUD who received a tablet between 1 April 2020 and 25 October 2021 were identified. The electronic health record was used to characterized encounters by modality of mental health care delivery in the six months pre/post tablet receipt. Logistic regression examined predictors of a video visit for mental health. Results: Phone was the most common modality; however, the proportion of video encounters increased from 8.7% to 26.2% after tablet receipt. Individuals who were older, male, and had more physical health conditions, were less likely to have a video visit. Individuals who were married, resided in urban areas, had a history of housing instability, and had more mental health conditions, were more likely to have a video visit. Conclusion: Video-enabled tablets may help older adults with AUD overcome access barriers to mental health services, although targeted support for certain groups may be necessary.

Overcoming Obstacles: Barriers to Virtual Care Use Among Video-Enabled Tablet Recipients in the Veterans Health Administration

INTRODUCTION

The Veterans Health Administration (VHA) distributes video-enabled tablets to individuals with barriers to accessing care. Data suggests that many tablets are under-used. We surveyed Veterans who received a tablet to identify barriers that are associated with lower use, and evaluated the impact of a telephone-based orientation call on reported barriers and future video use.

METHODS

We used a national survey to assess for the presence of 13 barriers to accessing video-based care, and then calculated the prevalence of the barriers stratified by video care utilization in the 6 months after survey administration. We used multivariable modeling to examine the association between each barrier and video-based care use and evaluated whether a telephone-based orientation modified this association.

RESULTS

The most prevalent patient-reported barriers to video-based care were not knowing how to schedule a visit, prior video care being rescheduled/canceled, and past problems using video care. Following adjustment, individuals who reported vision or hearing difficulties and those who reported that video care does not provide high-quality care had a 19% and 12% lower probability of future video care use, respectively. Individuals who reported no interest in video care, or did not know how to schedule a video care visit, had an 11% and 10% lower probability of being a video care user, respectively. A telephone-based orientation following device receipt did not improve the probability of being a video care user.

DISCUSSION

Barriers to engaging in virtual care persist despite access to video-enabled devices. Targeted interventions beyond telephone-based orientation are needed to facilitate adoption and engagement in video visits.

Association between patient-reported social and behavioral risks and health care costs in high-risk Veterans health administration patients

OBJECTIVE

Social risks complicate patients' ability to manage their conditions and access healthcare, but their association with health expenditures is not well established. To identify patient-reported social risk, behavioral, and health factors associated with health expenditures in Veterans Affairs (VA) patients at high risk for hospitalization or death.

DATA SOURCES, STUDY SETTING, AND STUDY DESIGN

Prospective cohort study among high-risk Veterans obtaining VA care. Patient-reported social risk, function, and other measures derived from a 2018 survey sent to 10,000 VA patients were linked to clinical and demographic characteristics extracted from VA data. Response-weighted generalized linear and marginalized two-part models were used to examine VA expenditures (total, outpatient, medication, inpatient) 1 year after survey completion in adjusted models.

PRINCIPAL FINDINGS

Among 4680 survey respondents, the average age was 70.9 years, 6.3% were female, 16.7% were African American, 20% had body mass index ≥35, 42.4% had difficulty with two or more basic or instrumental activities of daily living, 19.3% reported transportation barriers, 12.5% reported medication insecurity and 21.8% reported food insecurity. Medication insecurity was associated with lower outpatient expenditures (-$1859.51 per patient per year, 95% confidence interval [CI]: -3200.77 to -518.25) and lower total expenditures (-$4304.99 per patient per year, 95% CI: -7564.87 to -1045.10). Transportation barriers were negatively associated with medication expenditures (-$558.42, 95% CI: -1087.93 to -31.91). Patients with one functional impairment had higher outpatient expenditures ($2997.59 per patient year, 95% CI: 1185.81-4809.36) than patients without functional impairments. No social risks were associated with inpatient expenditures.

CONCLUSIONS

In this study of VA patients at high risk for hospitalization and mortality, few social and functional measures were independently associated with the costs of VA care. Individuals with functional limitations and those with barriers to accessing medications and transportation may benefit from targeted interventions to ensure that they are receiving the services that they need.

Associations Between Social Risks and Primary Care Utilization Among Medically Complex Veterans

BACKGROUND

Social risks contribute to poor health outcomes, especially for patients with complex medical needs. These same risks may impact access to primary care services.

OBJECTIVE

To study associations between social risks and primary care utilization among patients with medical complexity.

DESIGN

Prospective cohort study of respondents to a 2018 mailed survey, followed up to 2 years after survey completion.

PARTICIPANTS

Nationally representative sample of 10,000 primary care patients in the Veterans Affairs (VA) health care system, with high (≥ 75th percentile) 1-year risk of hospitalization or death.

MAIN MEASURES

Survey-based exposures were low social support, no family member/friend involved in health care, unemployment, transportation problem, food insecurity, medication insecurity, financial strain, low medical literacy, and less than high school graduate. Electronic health record-based outcomes were number of primary care provider (PCP) encounters, number of primary care team encounters (PCP, nurse, clinical pharmacist, and social worker), and having ≥ 1 social work encounter.

KEY RESULTS

Among 4680 respondents, mean age was 70.3, 93.7% were male, 71.8% White non-Hispanic, and 15.8% Black non-Hispanic. Unemployment was associated with fewer PCP and primary care team encounters (incident rate ratio 0.77, 95% CI 0.65-0.91; p = 0.002 and 0.75, 0.59-0.95; p = 0.02, respectively), and low medical literacy was associated with more primary care team encounters (1.17, 1.05-1.32; p = 0.006). Among those with one or more social risks, 18.4% had ≥ 1 social work encounter. Low medical literacy (OR 1.95, 95% CI 1.45-2.61; p < 0.001), transportation problem (1.42, 1.10-1.83; p = 0.007), and low social support (1.31, 1.06-1.63; p = 0.01) were associated with higher odds of  ≥ 1 social work encounter.

CONCLUSIONS

We found few differences in PCP and primary care team utilization among medically complex VA patients by social risk. However, social work use was low, despite its central role in addressing social risks. More work is needed to understand barriers to social work utilization.

Variation in initial and continued use of primary, mental health, and specialty video care among Veterans

OBJECTIVE

To identify which Veteran populations are routinely accessing video-based care.

DATA SOURCES AND STUDY SETTING

National, secondary administrative data from electronic health records at the Veterans Health Administration (VHA), 2019-2021.

STUDY DESIGN

This retrospective cohort analysis identified patient characteristics associated with the odds of using any video care; and then, among those with a previous video visit, the annual rate of video care utilization. Video care use was reported overall and stratified into care type (e.g., primary, mental health, and specialty video care) between March 10, 2020 and February 28, 2021.

DATA COLLECTION

Veterans active in VA health care (>1 outpatient visit between March 11, 2019 and March 10, 2020) were included in this study.

PRINCIPAL FINDINGS

Among 5,389,129 Veterans in this evaluation, approximately 27.4% of Veterans had at least one video visit. We found differences in video care utilization by type of video care: 14.7% of Veterans had at least one primary care video visit, 10.6% a mental health video visit, and 5.9% a specialty care video visit. Veterans with a history of housing instability had a higher overall rate of video care driven by their higher usage of video for mental health care compared with Veterans in stable housing. American Indian/Alaska Native Veterans had reduced odds of video visits, yet similar rates of video care when compared to White Veterans. Low-income Veterans had lower odds of using primary video care yet slightly elevated rates of primary video care among those with at least one video visit when compared to Veterans enrolled at VA without special considerations.

CONCLUSIONS

Variation in video care utilization patterns by type of care identified Veteran populations that might require greater resources and support to initiate and sustain video care use. Our data support service specific outreach to homeless and American Indian/Alaska Native Veterans.

Association between patient-reported social, behavioral, and health factors and emergency department visits in high-risk VA patients

RESEARCH OBJECTIVE

To identify patient-reported social risk, behavioral, and health factors associated with emergency department (ED) utilization in high-risk Veterans Affairs (VA) patients.

DATA SOURCES

Patient survey, VA, Medicare data.

STUDY DESIGN

Prospective cohort study using multivariable logistic regression to identify patient-reported factors associated with all-cause and ambulatory care sensitive condition (ACSC)-related ED visits among VA patients at high risk for hospitalization or death.

DATA EXTRACTION METHODS

Patient-reported measures derived from a 2018 survey sent to 10,000 VA patients; clinical and demographic characteristics derived from VA data; ED visits derived from VA and Medicare claims.

PRINCIPAL FINDINGS

Among 4680 survey respondents, 52.5% and 16.3% experienced an all-cause or ACSC-related ED visit in the following year, respectively. An ED visit was more likely among individuals with functional status limitations (6.0% points (Confidence Interval [CI] 0.017-0.103)) and transportation barriers (5.2% points [CI 0.005-0.099]). An ACSC-related ED visit was more likely among individuals with functional status limitations (3.2% points [CI 0.003-0.062]) and self-rated poorer health (7.4% points (CI 0.030-0.119) poor; 6.2% points (CI 0.029-0.096) fair; 4.1% points (CI 0.009-0.073) good; compared with excellent/very good).

CONCLUSIONS

Patient-reported factors not present in most electronic health records were significantly associated with future ED visits in high-risk VA patients.

Distinct health care use patterns of patients with chronic gastrointestinal diseases

OBJECTIVES

Patients with complex chronic conditions have varying multidisciplinary care needs and utilization patterns, which limit the effectiveness of initiatives designed to improve continuity of care (COC) and reduce utilization. Our objective was to categorize patients with complex chronic conditions into distinct groups by pattern of outpatient care use and COC to tailor interventions.

STUDY DESIGN

Observational cohort study from 2014 to 2015.

METHODS

We identified patients whose 1-year hospitalization risk was in at least the 90th percentile in 2014 who had a chronic gastrointestinal disease (cirrhosis, inflammatory bowel disease, chronic pancreatitis) as case examples of complex chronic disease. We described frequency of office visits, number of outpatient providers, and 2 COC measures (usual provider of care, Bice-Boxerman COC indices) over 12 months. We used latent profile analysis, a statistical method for identifying distinct subgroups, to categorize patients based on overall, primary care, gastroenterology, and mental health continuity patterns.

RESULTS

The 26,751 veterans in the cohort had a mean (SD) of 13.3 (8.6) office visits and 7.2 (3.8) providers in 2014. Patients were classified into 5 subgroups: (1) high gastroenterology-specific COC with mental health use; (2) high gastroenterology-specific COC without mental health use; (3) high overall utilization with mental health use; (4) low overall COC with mental health use; and (5) low overall COC without mental health use. These groups varied in their sociodemographic characteristics and risk for hospitalization, emergency department use, and mortality.

CONCLUSIONS

Patients at high risk for health care utilization with specialty care needs can be grouped by varying propensity for health care continuity patterns.

Association Between Mental Health Conditions and Outpatient Care Fragmentation: a National Study of Older High-Risk Veterans

BACKGROUND

Healthcare fragmentation may lead to adverse consequences and may be amplified among older, sicker patients with mental health (MH) conditions.

OBJECTIVE

To determine whether older Veterans with MH conditions have more fragmented outpatient non-MH care, compared with older Veterans with no MH conditions.

DESIGN

Retrospective cohort study using FY2014 Veterans Health Administration (VHA) administrative data linked to Medicare data.

PARTICIPANTS

125,481 VHA patients ≥ 65 years old who were continuously enrolled in Medicare Fee-for-Service Parts A and B and were at high risk for hospitalization.

MAIN OUTCOME AND MEASURES

The main outcome was non-MH care fragmentation as measured by (1) non-MH provider count and (2) Usual Provider of Care (UPC), the proportion of care with the most frequently seen non-MH provider. We tested the association between no vs. any MH conditions and outcomes using Poisson regression and fractional regression with logit link, respectively. We also compared Veterans with no MH condition with each MH condition and combinations of MH conditions, adjusting for sociodemographics, comorbidities, and drive-time to VHA specialty care.

KEY RESULTS

In total, 47.3% had at least one MH condition. Compared to those without MH conditions, Veterans with MH conditions had less fragmented care, with fewer non-MH providers (IRR = 0.96; 95% CI: 0.96-0.96) and more concentrated care with their usual provider (OR = 1.08 for a higher UPC; 95% CI: 1.07, 1.09) in adjusted models. Secondary analyses showed that those with individual MH conditions (e.g., depression) had fewer non-MH providers (IRR range: 0.86-0.98) and more concentrated care (OR range: 1.04-1.20). A similar pattern was observed when examining combinations of MH conditions (IRR range: 0.80-0.90; OR range: 1.16-1.30).

CONCLUSIONS

Contrary to expectations, having a MH condition was associated with less fragmented non-MH care among older, high-risk Veterans. Further research will determine if this is due to different needs, underuse, or appropriate use of healthcare.

Disparities in virtual cardiology visits among Veterans Health Administration patients during the COVID-19 pandemic

Objective

In response to the coronavirus disease 2019 (COVID-19) pandemic, the Veterans Health Administration (VA) rapidly expanded virtual care (defined as care delivered by video and phone), raising concerns about technology access disparities (ie, the digital divide). Virtual care was somewhat established in primary care and mental health care prepandemic, but video telehealth implementation was new for most subspecialties, including cardiology. We sought to identify patient characteristics of virtual and video-based care users in VA cardiology clinics nationally during the first year of the COVID-19 pandemic.

Materials and Methods

Cohort study of Veteran patients across all VA facilities with a cardiology visit January 1, 2019-March 10, 2020, with follow-up January 1, 2019-March 10, 2021. Main measures included cardiology visits by visit type and likelihood of receiving cardiology-related virtual care, calculated with a repeated event survival model.

Results

416 587 Veterans with 1 689 595 total cardiology visits were analyzed; average patient age was 69.6 years and 4.3% were female. Virtual cardiology care expanded dramatically early in the COVID-19 pandemic from 5% to 70% of encounters. Older, lower-income, and rural-dwelling Veterans and those experiencing homelessness were less likely to use video care (adjusted hazard ratio for ages 75 and older 0.80, 95% confidence interval (CI) 0.75-0.86; for highly rural residents 0.77, 95% CI 0.68-0.87; for low-income status 0.94, 95% CI 0.89-0.98; for homeless Veterans 0.85, 95% CI 0.80-0.92).

Conclusion

The pandemic worsened the digital divide for cardiology care for many vulnerable patients to the extent that video visits represent added value over phone visits. Targeted interventions may be necessary for equity in COVID-19-era access to virtual cardiology care.

Emotion recognition and eye tracking of static and dynamic facial affect: Acomparison of individuals with and without traumatic brain injury

Diminished social functioning is often seen after traumatic brain injury (TBI). Mechanisms contributing to these deficits are poorly understood but thought to relate to impaired ability to recognize facial expressions. Static stimuli are often used to investigate ability post-TBI, and there is less evidence using more real-life dynamic stimuli. In addition, most studies rely on behavioral responses alone. The present study investigated the performance of a TBI group and matched non-TBI group on static and dynamic tasks using eye-tracking technology alongside behavioral measures. This is the first study to use eye tracking methodology alongside behavioral measures in emotion recognition tasks in people with brain injury. Eighteen individuals with heterogeneous TBI and 18 matched non-TBI participants were recruited. Stimuli representing six core emotions (Anger, Disgust, Fear, Happy, Sad, and Surprise faces) were selected from the Amsterdam Dynamic Facial Expression Set (ADFES). Participants were instructed to identify the emotion displayed correctly whilst eye movement metrics were recorded.

RESULTS

Results of analyses showed that TBI patients had First Fixation to nose for all emotion stimuli, shorter Fixation Duration and lower Fixation Count to eyes, were generally slower to classify stimuli, and less accurate than non-TBI group for the static task. Those with TBI were also less accurate at identifying Angry, Disgust, and Fear stimulus faces compared to the non-TBI group during the dynamic unfolding of an emotion.

CONCLUSION

In the present study, those with TBI had atypical eye scan patterns during emotion identification in the static emotion recognition task compared to the non-TBI group and were associated with lower identification accuracy on behavioral measures in both static and dynamic tasks. Findings suggest potential disruption to oculomotor systems vital for first stage perceptual processing. Arguably, these impairments may contribute to diminished social functioning.

Outpatient Care Fragmentation and Acute Care Utilization in Veterans Affairs Home-Based Primary Care

Importance

Veterans Affairs (VA) Home-Based Primary Care (HBPC) provides comprehensive, interdisciplinary primary care at home to patients with complex, chronic, disabling disease, but little is known about care fragmentation patterns and consequences among these patients.

Objective

To examine outpatient care fragmentation patterns and subsequent acute care among HBPC-engaged patients at high risk of hospitalization or death.

Design, Setting, and Participants

This retrospective cohort study included VA patients aged at least 65 years who were enrolled in the VA and Medicare, whose risk of hospitalization or death was in the top 10%, and who had at least 4 outpatient visits between October 1, 2013, and September 30, 2014. HBPC engagement was defined as having at least 2 HBPC encounters between July 1, 2014, and September 30, 2014. Data were analyzed from March 2020 to March 2022.

Exposures

Two indices of outpatient care fragmentation: practitioner count and the Usual Provider Continuity Index (UPC), based on VA and non-VA health care use from October 1, 2013, to September 30, 2014. All care delivered by HBPC clinicians was analyzed as coming from a single practitioner.

Main Outcomes and Measures

Emergency department (ED) visits and hospitalizations for ambulatory care sensitive conditions (ACSC) from VA records and Medicare claims from October 1, 2014, to September 30, 2015.

Results

Among 8908 identified HBPC patients, 8606 (96.6%) were male, 1562 (17.5%) were Black, 249 (2.8%) were Hispanic, 6499 (73.0%) were White, 157 (1.8%) were other race or ethnicity, and 441 (5.0%) had unknown race or ethnicity; the mean (SD) age was 80.0 (9.02) years; patients had a mean (SD) of 11.25 (3.87) chronic conditions, and commonly had disabling conditions such as dementia (38.8% [n = 3457]). In adjusted models, a greater number of practitioners was associated with increased odds of an ED visit (adjusted odds ratio [aOR], 1.05 [95% CI, 1.03-1.07]) and hospitalization for an ACSC (aOR, 1.04 [95% CI, 1.02-1.06]), whereas more concentrated care with a higher UPC was associated with reduced odds of these outcomes (highest vs lowest tertile of UPC: aOR for ED visit, 0.77 [95% CI, 0.67-0.88], aOR for ACSC hospitalization, 0.78 [95% CI, 0.68-0.88]).

Conclusions and Relevance

Among patients in HBPC, fragmented care was associated with more ED visits and ACSC hospitalizations. These findings suggest that consolidating or coordinating fragmented care may be a target for reducing preventable acute care.

Anticipating VA/non-VA care coordination demand for Veterans at high risk for hospitalization

U.S. Veterans Affairs (VA) patients' multi-system use can create challenges for VA clinicians who are responsible for coordinating Veterans' use of non-VA care, including VA-purchased care ("Community Care") and Medicare.To examine the relationship between drive distance and time-key eligibility criteria for Community Care-and VA reliance (proportion of care received in VA versus Medicare and Community Care) among Veterans at high risk for hospitalization. We used prepolicy data to anticipate the impact of the 2014 Choice Act and 2018 Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION Act), which expanded access to Community Care.Cross-sectional analysis using fractional logistic regressions to examine the relationship between a Veteran's reliance on VA for outpatient primary, mental health, and other specialty care and their drive distance/time to a VA facility.Thirteen thousand seven hundred three Veterans over the age of 65 years enrolled in VA and fee-for-service Medicare in federal fiscal year 2014 who were in the top 10th percentile for hospitalization risk.Key explanatory variables were patients' drive distance to VA > 40 miles (Choice Act criteria) and drive time to VA ≥ 30 minutes for primary and mental health care and ≥60 minutes for specialty care (MISSION Act criteria).Veterans at high risk for hospitalization with drive distance eligibility had increased odds of an outpatient specialty care visit taking place in VA when compared to Veterans who did not meet Choice Act eligibility criteria (odds ratio = 1.10, 95% confidence interval 1.05-1.15). However, drive time eligibility (MISSION Act criteria) was associated with significantly lower odds of an outpatient specialty care visit taking place in VA (odds ratio = 0.69, 95% confidence interval 0.67, 0.71). Neither drive distance nor drive time were associated with reliance for outpatient primary care or mental health care.VA patients who are at high risk for hospitalization may continue to rely on VA for outpatient primary care and mental health care despite access to outside services, but may increase use of outpatient specialty care in the community in the MISSION era, increasing demand for multi-system care coordination.

Outpatient care fragmentation in Veterans Affairs patients at high-risk for hospitalization

OBJECTIVE

To examine outpatient care fragmentation and its association with future hospitalization among patients at high risk for hospitalization.

DATA SOURCES

Veterans Affairs (VA) and Medicare data.

STUDY DESIGN

We conducted a longitudinal study, using logistic regression to examine how outpatient care fragmentation in FY14 (as measured by number of unique providers, Breslau's Usual Provider of Care (UPC), Bice-Boxerman's Continuity of Care Index (COCI), and Modified Modified Continuity Index (MMCI)) was associated with all-cause hospitalizations and hospitalizations related to ambulatory care sensitive conditions (ACSC) in FY15. We also examined how fragmentation varied by patient's age, gender, race, ethnicity, marital status, rural status, history of homelessness, number of chronic conditions, Medicare utilization, and mental healthcare utilization.

DATA EXTRACTION METHODS

We extracted data for 130,704 VA patients ≥65 years old with a hospitalization risk ≥90th percentile and ≥ four outpatient visits in the baseline year.

PRINCIPAL FINDINGS

Mean (standard deviation) of FY14 outpatient visits was 13.2 (8.6). Fragmented care (more providers, less care with a usual provider, more dispersed care based on COCI) was more common among patients with more chronic conditions and those receiving mental health care. In adjusted models, most fragmentation measures were not associated with all-cause hospitalization, and patients with low levels of fragmentation (more concentrated care based on UPC, COCI, and MMCI) had a higher likelihood of an ACSC-related hospitalization (AOR, 95% CI = 1.21 (1.09-1.35), 1.27 (1.14-1.42), and 1.28 (1.18-1.40), respectively).

CONCLUSIONS

Contrary to expectations, outpatient care fragmentation was not associated with elevated all-cause hospitalization rates among VA patients in the top 10th percentile for risk of admission; in fact, fragmented care was linked to lower rates of hospitalization for ACSCs. In integrated settings such as the VA, multiple providers and dispersed care might offer access to timely or specialized care that offsets risks of fragmentation, particularly for conditions that are sensitive to ambulatory care.

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

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.

The association of alcohol use with all-cause and cardiovascular disease-related hospitalizations or death in older, high-risk Veterans

BACKGROUND

The prevalence of alcohol misuse among older adults has grown dramatically in the past decade, yet little is known about the association of alcohol misuse with hospitalization and death in this patient population.

METHODS

We examined the association between alcohol use (measured by a screening instrument in primary care) and rates of all-cause and cardiovascular disease (CVD)-related 6-month hospitalization or death via electronic health records (EHRs) in a nationally representative sample of older, high-risk Veterans. Models were adjusted for sociodemographic and clinical characteristics, including frailty and comorbid conditions.

RESULTS

The all-cause hospitalization or death rate at 6 months was 14.9%, and the CVD-related hospitalization or death rate was 1.8%. In adjusted analyses, all-cause hospitalization or death was higher in older Veterans who were nondrinkers or harmful use drinkers compared to moderate use drinkers, but CVD-related hospitalization or death was similar in all categories of drinking.

CONCLUSIONS

These findings suggest that the complex association between alcohol and all-cause acute healthcare utilization found in the broader population is similar in older, high-risk Veteran patients. These findings do not support an association between alcohol consumption and CVD-specific hospitalizations.

Subgroups of High-Risk Veterans Affairs Patients Based on Social Determinants of Health Predict Risk of Future Hospitalization

OBJECTIVE

Population segmentation has been recognized as a foundational step to help tailor interventions. Prior studies have predominantly identified subgroups based on diagnoses. In this study, we identify clinically coherent subgroups using social determinants of health (SDH) measures collected from Veterans at high risk of hospitalization or death.

STUDY DESIGN AND SETTING

SDH measures were obtained for 4684 Veterans at high risk of hospitalization through mail survey. Eleven self-report measures known to impact hospitalization and amenable to intervention were chosen a priori by the study team to identify subgroups through latent class analysis. Associations between subgroups and demographic and comorbidity characteristics were calculated through multinomial logistic regression. Odds of 180-day hospitalization were compared across subgroups through logistic regression.

RESULTS

Five subgroups of high-risk patients emerged-those with: minimal SDH vulnerabilities (8% hospitalized), poor/fair health with few SDH vulnerabilities (12% hospitalized), social isolation (10% hospitalized), multiple SDH vulnerabilities (12% hospitalized), and multiple SDH vulnerabilities without food or medication insecurity (10% hospitalized). In logistic regression, the "multiple SDH vulnerabilities" subgroup had greater odds of 180-day hospitalization than did the "minimal SDH vulnerabilities" reference subgroup (odds ratio: 1.53, 95% confidence interval: 1.09-2.14).

CONCLUSION

Self-reported SDH measures can identify meaningful subgroups that may be used to offer tailored interventions to reduce their risk of hospitalization and other adverse events.

Organizational and External Factors Associated with Video Telehealth Use in the Veterans Health Administration Before and During the COVID-19 Pandemic

Objectives: To identify organizational and external factors associated with medical center video telehealth uptake (i.e., the proportion of patients using telemedicine) before and early in the coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods: We conducted a retrospective, observational study using cross-sectional data for all 139 U.S. Veterans Affairs Medical Centers (VAMCs). We used logistic regression analyses to identify factors that predicted whether a VAMC was in the top quartile of VA Video Connect (VVC) telehealth uptake for primary care and mental health care. Results: All 139 VAMCs increased their VVC uptake at least 2-fold early in the pandemic, with most increasing uptake between 5- and 10-fold. Pre-COVID-19, higher VVC uptake in primary care was weakly and positively associated with having more high-risk patients, negatively associated with having more long-distance patients, and positively associated with the prior fiscal year's VVC uptake. During COVID-19, the positive association with high-risk patients and the negative association with long-distance patients strengthened, while weaker broadband coverage was negatively associated with VVC uptake. For mental health care, having more long-distance patients was positively associated with higher VVC uptake pre-COVID-19, but this relationship reversed during COVID-19. Discussion: Despite the marked increase in VVC uptake early in the COVID-19 pandemic, significant VAMC-level variation indicates that VVC adoption was more difficult for some medical centers, particularly those with poorer broadband coverage and less prior VVC experience. Conclusions and Relevance: These findings highlight opportunities for medical centers, VA Central Office, and other federal entities to ensure equitable access to video telehealth.

Virtual care expansion in the Veterans Health Administration during the COVID-19 pandemic: clinical services and patient characteristics associated with utilization

Objectives

To describe the shift from in-person to virtual care within Veterans Affairs (VA) during the early phase of the COVID-19 pandemic and to identify at-risk patient populations who require greater resources to overcome access barriers to virtual care.

Materials and Methods

Outpatient encounters (N = 42 916 349) were categorized by care type (eg, primary, mental health, etc) and delivery method (eg, in-person, video). For 5 400 878 Veterans, we used generalized linear models to identify patient sociodemographic and clinical characteristics associated with: 1) use of virtual (phone or video) care versus no virtual care and 2) use of video care versus no video care between March 11, 2020 and June 6, 2020.

Results

By June, 58% of VA care was provided virtually compared to only 14% prior. Patients with lower income, higher disability, and more chronic conditions were more likely to receive virtual care during the pandemic. Yet, Veterans aged 45–64 and 65+ were less likely to use video care compared to those aged 18–44 (aRR 0.80 [95% confidence interval (CI) 0.79, 0.82] and 0.50 [95% CI 0.48, 0.52], respectively). Rural and homeless Veterans were 12% and 11% less likely to use video care compared to urban (0.88 [95% CI 0.86, 0.90]) and nonhomeless Veterans (0.89 [95% CI 0.86, 0.92]).

Discussion

Veterans with high clinical or social need had higher likelihood of virtual service use early in the COVID-19 pandemic; however, older, homeless, and rural Veterans were less likely to have video visits, raising concerns for access barriers.

Conclusions and Relevance

While virtual care may expand access, access barriers must be addressed to avoid exacerbating disparities.

Association Between Mental Health Conditions and Care Fragmentation: A National Study of High-Risk Older Veterans

Fragmented healthcare causes information loss, duplicative tests, and unwieldy self-care regimens. These challenges may be amplified among older, high-risk patients with co-occurring mental health conditions (MHC). We compared healthcare fragmentation for chronic physical conditions among Veterans with and without MHC (depression, PTSD, schizophrenia, bipolar disorder, anxiety, personality disorder, or psychosis based on ICD-9 codes). Sample included Veterans who were □65y, at high risk for 1-year hospitalization, and had □4 non-MHC visits during FY14. Visits were covered by Veterans Affairs (VA), VA-purchased care (both from VA Corporate Data Warehouse), or Medicare Parts A/B (claims data from VA Information Resource Center). Outcomes were two fragmentation measures calculated in FY15: 1) non-mental health provider count, where a higher number indicates more fragmentation, and 2) Usual Provider of Care (UPC), the proportion of care with the most frequently seen provider, where a higher number indicates less fragmentation. We used Poisson regression and GLM with binomial distribution and logit link to test the association between MHC status and fragmentation, controlling for sociodemographic characteristics (e.g., age), medical comorbidity, and driving distance to VA. Of the 125,481 Veterans included, 47.3% had 1+ MHC. Compared to older, high-risk Veterans without MHC, those with MHC saw fewer providers (pseudo R2 = 0.02) and had a higher UPC (more concentrated care; OR = 1.07). Within the VA, older, high-risk Veterans with MHC do not experience greater healthcare fragmentation. Further research is needed to determine if this is due to different needs, underuse, or appropriate use of healthcare across the groups.

Use of Video-Enabled Tablet for Virtual Care Among Older Veterans

With the proliferation of virtual care, healthcare systems are exploring ways to bridge the digital divide among vulnerable patients. Department of Veterans Affairs (VA) is distributing devices for qualifying Veterans to enable video visits with medical providers at home, yet their use among older patients is unknown. This retrospective cohort study used administrative data to characterize the use of VA-loaned iPads among older Veterans compared to younger Veterans and identify demographic predictors of utilization. Among 16,385 patients who were shipped a VA-loaned iPad in 2014-2019, 33.66% (n=5,516) were over 65 years old, and 3.1% (n=503) were over the age of 85. Two thirds (n=6799) of younger patients had a video visit (mean=3 visits) with provider using iPad in the 6 months since shipment, compared to 50% (n=253) of 85+ year-olds (mean=1.8 visits). Most common types of virtual visits for the oldest old patients were for geriatrics or home-based primary care, compared to mental health visits among younger patients. Logistic regression identified characteristics of older patients who were more likely to use iPads, such a marital status, urban location, and lower disease burden, which is similar to their younger counterparts. While older age groups used VA-loaned tablets less frequently, those who engaged with the devices were similar in demographics as their younger counterparts. Older patients used iPads differently, with higher engagement in geriatric and primary care services. Providing devices for virtual care may allow health systems to more easily reach older patients in the comfort of their home.

Patient-Reported Social and Behavioral Determinants of Health and Estimated Risk of Hospitalization in High-Risk Veterans Affairs Patients

IMPORTANCE

Despite recognition of the association between individual social and behavioral determinants of health (SDH) and patient outcomes, little is known regarding the value of SDH in explaining variation in outcomes for high-risk patients.

OBJECTIVE

To describe SDH factors among veterans who are at high risk for hospitalization, and to determine whether adding patient-reported SDH measures to electronic health record (EHR) measures improves estimation of 90-day and 180-day all-cause hospital admission.

DESIGN, SETTING, AND PARTICIPANTS

A survey was mailed between April 16 and June 29, 2018, to a nationally representative sample of 10 000 Veterans Affairs (VA) patients whose 1-year risk of hospitalization or death was in the 75th percentile or higher based on a VA EHR-derived risk score. The survey included multiple SDH measures, such as resilience, social support, health literacy, smoking status, transportation barriers, and recent life stressors.

MAIN OUTCOMES AND MEASURES

The EHR-based characteristics of survey respondents and nonrespondents were compared using standardized differences. Estimation of 90-day and 180-day hospital admission risk was assessed for 3 logistic regression models: (1) a base model of all prespecified EHR-based covariates, (2) a restricted model of EHR-based covariates chosen via forward selection based on minimizing Akaike information criterion (AIC), and (3) a model of EHR- and survey-based covariates chosen via forward selection based on AIC minimization.

RESULTS

In total, 4685 individuals (response rate 46.9%) responded to the survey. Respondents were comparable to nonrespondents in most characteristics, but survey respondents were older (eg, >80 years old, 881 [18.8%] vs 800 [15.1%]), comprised a higher percentage of men (4391 [93.7%] vs 4794 [90.2%]), and were composed of more White non-Hispanic individuals (3366 [71.8%] vs 3259 [61.3%]). Based on AIC, the regression model with survey-based covariates and EHR-based covariates better estimated hospital admission at 90 days (AIC, 1947.7) and 180 days (AIC, 2951.9) than restricted models with only EHR-based covariates (AIC, 1980.2 at 90 days; AIC, 2981.9 at 180 days). This result was due to inclusion of self-reported measures such as marital or partner status, health-related locus of control, resilience, smoking status, health literacy, and medication insecurity.

CONCLUSIONS AND RELEVANCE

Augmenting EHR data with patient-reported social information improved estimation of 90-day and 180-day hospitalization risk, highlighting specific SDH factors that might identify individuals who are at high risk for hospitalization.

Identification of Emergency Care-Sensitive Conditions and Characteristics of Emergency Department Utilization

IMPORTANCE

Monitoring emergency care quality requires understanding which conditions benefit most from timely, quality emergency care.

OBJECTIVES

To identify a set of emergency care-sensitive conditions (ECSCs) that are treated in most emergency departments (EDs), are associated with a spectrum of adult age groups, and represent common reasons for seeking emergency care and to provide benchmark national estimates of ECSC acute care utilization.

DESIGN, SETTING, AND PARTICIPANTS

A modified Delphi method was used to identify ECSCs. In a cross-sectional analysis, ECSC-associated visits by adults (aged ≥18 years) were identified based on International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes and analyzed with nationally representative data from the 2016 US Nationwide Emergency Department Sample. Data analysis was conducted from January 2018 to December 2018.

MAIN OUTCOMES AND MEASURES

Identification of ECSCs and ECSC-associated ED utilization patterns, length of stay, and charges.

RESULTS

An expert panel rated 51 condition groups as emergency care sensitive. Emergency care-sensitive conditions represented 16 033 359 of 114 323 044 ED visits (14.0%) in 2016. On average, 8 535 261 of 17 886 220 ED admissions (47.7%) were attributed to ECSCs. The most common ECSC ED visits were for sepsis (1 716 004 [10.7%]), chronic obstructive pulmonary disease (1 273 319 [7.9%]), pneumonia (1 263 971 [7.9%]), asthma (970 829 [6.1%]), and heart failure (911 602 [5.7%]) but varied by age group. Median (interquartile range) length of stay for ECSC ED admissions was longer than non-ECSC ED admissions (3.2 [1.7-5.8] days vs 2.7 [1.4-4.9] days; P < .001). In 2016, median (interquartile range) ED charges per visit for ECSCs were $2736 ($1684-$4605) compared with $2179 ($1118-$4359) per visit for non-ECSC ED visits (P < .001).

CONCLUSIONS AND RELEVANCE

This comprehensive list of ECSCs can be used to guide indicator development for pre-ED, intra-ED, and post-ED care and overall assessment of the adult, non-mental health, acute care system. Health care utilization and costs among patients with ECSCs are substantial and warrant future study of validation, variations in care, and outcomes associated with ECSCs.

Access to mental health care among women Veterans: is VA meeting women's needs?

BACKGROUND

Patient-centered access to mental health describes the fit between patient needs and resources of the system. To date, little data are available to guide implementation of services to women veterans, an underrepresented minority within Department of Veteran Affairs (VA) health care. The current study examines access to mental health care among women veterans, and identifies gender-related indicators of perceived access to mental health care.

METHODS

A population-based sample of 6287 women veterans using VA primary care services participated in a survey of past year perceived need for mental health care, mental health utilization, and gender-related mental health care experiences. Subjective rating of how well mental health care met their needs was used as an indicator of perceived access.

RESULTS

Half of all women reported perceived mental health need; 84.3% of those women received care. Nearly all mental health users (90.9%) used VA services, although only about half (48.8%) reported that their mental health care met their needs completely or very well. Gender related experiences (availability of female providers, women-only treatment settings, women-only treatment groups, and gender-related comfort) were each associated with 2-fold increased odds of perceived access, and associations remained after adjusting for ease of getting care.

CONCLUSIONS

Women VA users demonstrate very good objective access to mental health services. Desire for, and access to specialized mental health services for women varies across the population and are important aspects of shared decision making in referral and treatment planning for women using VA primary care.

Institutional Profile: USF Health: the power of creativity, the passion to improve health

USF Health (FL, USA) is home to a broad spectrum of health experts - from doctors to public health scientists to nurses to pharmacists - working together to envision a new kind of healthcare. USF Health encompasses the University of South Florida's Colleges of Medicine, Nursing, Public Health and Pharmacy. One of the only campuses in the nation with such a broad vision of health, USF Health is designed to reflect a future in which patient care, education and research benefit from a cooperative approach. USF Health focuses on leading changes in healthcare with bold, energetic and creative programs. Innovative initiatives include a new partnership with The Jackson Laboratory; a new medical degree program that emphasizes leadership, undertaken with the Lehigh Valley Health System in Pennsylvania; and 'Bringing Science Home', a new program to help patients who suffer from chronic disease live more optimistic and fulfilling lives.

Gonococcal NAATs: what is the current state of play in England and Wales?

The aim of this study was to determine how widespread the use is of dual nucleic acid amplification tests (NAATs) for the diagnosis of both Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) in England and Wales. A structured telephone questionnaire was used to collect information on the method of dual testing used by laboratories, the patient groups tested, the types of specimens obtained and the use of GC culture. Of the 108 laboratories participating, 29% performed dual CT and GC NAAT assays. The platforms used included: (i) BD Probetec (19/31), (ii) Aptima Combo 2 (9/31) and (iii) COBAS AMPLICOR (2/31). GC-positive specimens were either repeated using the same test (21) or an alternative target (9). Most laboratories confirmed positive GC NAATs by performing culture (26/31). Laboratories performed dual NAAT testing on specimens sourced from both community and genitourinary medicine clinic settings, and on a wide variety of different specimen types. This survey highlights a lack of consistency in the current use of dual NAAT platforms in the UK and the need for national guidelines.

Precision and accuracy of low-dose CT protocols in the evaluation of skull landmarks

OBJECTIVES

It was proposed to design a series of low-dose three-dimensional (3D) CT protocols with an effective dose similar to that of the conventional radiographic series (0.011-0.032 mSv) used to assess craniofacial asymmetry. It was then aimed to assess the precision and accuracy for skull landmarks recorded ex vivo using these CT protocols.

METHODS

Four ultra low-dose CT protocols (5 mAs, pitch 1.375/1.75; 10 mAs, pitch 1.375/1.75) were constructed on the basis of published data, dose calculations and measurements. A high-dose CT protocol was used as a reference standard examination. The protocols were used to scan a skull immersed in water. For each protocol, two observers evaluated 17 skull landmarks on two separate occasions. 3D and two-dimensional (2D) accuracy relative to the reference standard examination and inter- and intraobserver precision was calculated.

RESULTS

The 2D accuracy was superior for the 10 mAs protocols and the 10 mAs/1.375 pitch protocol allowed one observer to achieve an accuracy of less than 2 mm for all landmarks. The 2D interrater precision for the 10 mAs/1.375 pitch protocol was superior to the other low-dose protocols and also the high-dose protocol, achieving precision less than 2 mm for 15/17 points. The 10 mAs protocols enabled greater 2D intrarater precision than the 5 mAs protocols for both observers.

CONCLUSIONS

Using the 10 mAs/1.375 pitch CT protocol, it was possible to achieve 2D accuracy of less than 2 mm for almost all skull landmarks with an interrater precision similar to a high-dose CT protocol. Although the estimated effective dose of 0.035 mSv was slightly greater than that of the conventional radiographic series (0.011-0.032 mSv), there was the additional benefit of a 3D data set. The 10 mAs protocols allowed accuracy and precision superior to that of the 5 mAs protocols and hence they are more likely to be clinically applicable.

HIV, sexually transmitted infections, and risk behaviours in male sex workers in London over a 10 year period

OBJECTIVES

To describe changing characteristics of men who sold sex in London between 1994 and 2003.

METHODS

A baseline survey of 823 male sex workers attending a specialist clinic, plus follow up of 628 men for 1379 person years.

RESULTS

Men recruited earlier (1994 to 1996) were more likely than those recruited later (2000 to 2003) to be UK born and to self define as homosexual. Later recruits included more men from South/Central America and eastern Europe and a higher proportion reported regular female partners. Baseline prevalence of HIV was 9% (59/636), and multivariate analysis showed an associated with injecting drug use and unprotected sex with a casual partner. During follow up there were 49 incident cases of HIV. Survival analysis showed earlier recruitment (1994-6) to be associated with a higher incidence of HIV. The prevalence of gonorrhoea increased over time.

CONCLUSIONS

Men who sell sex are at risk of HIV and other STIs, but these risks do not appear to be directly linked to sex work. The changing demographics of these men is associated with different patterns of infection and poses challenges for service delivery.

Hepatitis B vaccination for male sex workers: the experience of a specialist GUM service

BACKGROUND

Male sex workers are at risk of blood borne viruses but may have limited access to sexual health services, including vaccination. We explore factors associated with hepatitis B vaccination uptake among male sex workers in London

METHODS

Follow up study of men attending the Working Men's Project, a specialist health project for men who sell sex, between 1994 and 2003.

RESULTS

At baseline 797 men were screened for hepatitis B; 308 were not eligible for vaccination because of past or current infection (155, 19.4%) or previous vaccination 153 (19.2%). Of the 489 men eligible for a full course of vaccination 292 (59.8%) completed the course. Completion rates fell over time: men recruited up to 1999 were more likely to complete the course than those recruited more recently (177/259, 68.3% compared with 115/229, 50.2%, OR 2.14, 95% CI 1.48 to 3.09).

CONCLUSION

This specialist service achieved a high rate of vaccine completion in the early years, but the decline is a concern. It may reflect wider availability of vaccination elsewhere and a more mobile population of sex workers. Shorter courses may achieve a higher completion.

Large cell neuroendocrine carcinoma of the larynx: a case report and a review of the classification of this neoplasm

This report describes a case of large cell neuroendocrine carcinoma (LCNEC) of the larynx. A 74 year old man who presented with otalgia underwent direct laryngoscopy with biopsy, which revealed an invasive poorly differentiated carcinoma. Laryngectomy with bilateral neck dissections revealed invasion of the pre-epiglottic space by the tumour, with metastases to bilateral lymph nodes (AJCC T3N2c). The tumour was characterised by large cells with vesicular chromatin and prominent nucleoli. The cells were arranged in organoid and trabecular patterns with a background of extensive necrosis and numerous mitotic figures. Immunohistochemical and ultrastructural analyses confirmed the neuroendocrine nature of the tumour. Metastatic disease was present in the liver, and the patient died within weeks of surgery. LCNEC carcinoma is a rare tumour of the larynx. Recognition at this site is essential so that proper patient management can be initiated.

Active commuting to and from school and BMI in elementary school children-preliminary data

BACKGROUND

United States National Health Objectives include increasing the proportion of trips made by walking to and from school for children who live within 1.6 km to 50%. The purpose of this objective is to increase the level of physical activity among children. However, the impact of walking, bicycling or skating (active commuting) to and from school on the prevalence of overweight is unknown.

METHODS

Body mass index (BMI) was measured for 320 children (age 10.2+/-0.7 years) in September. Over 5 months, an active commuting index (SI) and daily physical activity were estimated via questionnaire. In April, BMI and body fat were measured.

RESULTS

A significant positive association was found between April BMI and SI adjusting for September BMI (partial r=0.03, P<0.05). Positive associations were found between SI and physical activity before school (r=0.17, P<0.05) and daily moderate intensity physical activity (r=0.13, P<0.05). There were no significant association between SI and BF (P>0.05).

CONCLUSIONS

This preliminary data suggests that active commuting does not appear to provide sufficient amounts of physical activity to attenuate BMI; however, it may contribute to the attainment of physical activity recommendations. Future research is needed to objectively measure the impact of active commuting on the prevalence of overweight.

The Conners' Parent Rating Scales: a critical review of the literature

The Conners' Parent Rating Scales (CPRS) have undergone a considerable amount of scrutiny--and subsequent refining, reshaping, and revising--since their development in 1970. While such longitudinal scrutiny has ultimately led to a more reliable, valid assessment tool, it has left behind a wake of literature filled with misinformation and ambiguity. Multiple versions of the Conners' Rating Scales (CRS), their misuse, and inaccurate reporting by researchers have created a body of literature that is difficult to interpret and misleading to both researchers and clinicians. This review is aimed at clarifying issues regarding the proper use of the CPRS as both a diagnostic instrument and a research tool.

Readmission to the intensive care unit after liver transplantation

OBJECTIVE

We undertook this study to understand the factors at our transplant center that contribute to patients' return to the ICU after their liver transplant and their initial discharge from that unit. Patients who, after liver transplantation, fail discharge from the Intensive Care Unit (ICU) and must be readmitted to that unit may well utilize many more resources than those patients who are well enough to stay out of the ICU.

DESIGN

A retrospective review of a prospectively maintained liver transplant research database followed by a retrospective review of (a subgroup) patient charts and contemporaneous controls.

SETTING

A large metropolitan tertiary care center and adult liver transplant center.

PATIENTS

A total of 1,197 consecutive adult patients who underwent their initial liver transplantation from 1984 to 1996.

INTERVENTION

Readmission to the intensive care unit after adult liver transplantation and discharge from that unit.

MAIN RESULTS

Only recipient age, pretransplant synthetic function labs (protime and albumin), bilirubin levels, and intraoperative blood product requirements could be statistically linked to the group requiring ICU readmission. The primary etiology for ICU readmission was cardiopulmonary deterioration. Readmission was associated with significantly lower patient and graft survivals. A detailed review of 23 patients transplanted from October 1994 to June 1996 was made, with special emphasis on cardiopulmonary status (hemodynamics, respiratory variables, and chest radiograph findings). This subgroup was compared with 30 temporally matched controls who were not readmitted to the ICU. Intravascular fluid overload and lower inspiratory capacity were significant factors related to ICU readmission. Readmitted patients had a longer hospitalization with higher hospital charges than the control group.

CONCLUSIONS

We conclude that the most important means of preventing ICU readmission in liver transplantation patients is to optimize cardiopulmonary function and status. Close monitoring of fluid balance to avoid hypervolemia is essential. Readmitted patients have a greater resource utilization and have lower survival rates.