Harnessing health information technology to promote equitable care for patients with limited English proficiency and complex care needs.

BACKGROUND: Patients with language barriers encounter healthcare disparities, which may be alleviated by leveraging interpreter skills to reduce cultural, language, and literacy barriers through improved bidirectional communication. Evidence supports the use of in-person interpreters, especially for interactions involving patients with complex care needs. Unfortunately, due to interpreter shortages and clinician underuse of interpreters, patients with language barriers frequently do not get the language services they need or are entitled to. Health information technologies (HIT), including artificial intelligence (AI), have the potential to streamline processes, prompt clinicians to utilize in-person interpreters, and support prioritization. METHODS: From May 1, 2023, to June 21, 2024, a single-center stepped wedge cluster randomized trial will be conducted within 35 units of Saint Marys Hospital & Methodist Hospital at Mayo Clinic in Rochester, Minnesota. The units include medical, surgical, trauma, and mixed ICUs and hospital floors that admit acute medical and surgical care patients as well as the emergency department (ED). The transitions between study phases will be initiated at 60-day intervals resulting in a 12-month study period. Units in the control group will receive standard care and rely on clinician initiative to request interpreter services. In the intervention group, the study team will generate a daily list of adult inpatients with language barriers, order the list based on their complexity scores (from highest to lowest), and share it with interpreter services, who will send a secure chat message to the bedside nurse. This engagement will be triggered by a predictive machine-learning algorithm based on a palliative care score, supplemented by other predictors of complexity including length of stay and level of care as well as procedures, events, and clinical notes. DISCUSSION: This pragmatic clinical trial approach will integrate a predictive machine-learning algorithm into a workflow process and evaluate the effectiveness of the intervention. We will compare the use of in-person interpreters and time to first interpreter use between the control and intervention groups. TRIAL REGISTRATION: NCT05860777. May 16, 2023.

Centralized Multipatient Dashboards' Impact on Intensive Care Unit Clinician Performance and Satisfaction: A Systematic Review.

BACKGROUND: Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety. OBJECTIVES: This systematic review assesses the impact of centralized multipatient dashboards on ICU clinician performance, perceptions regarding the use of these tools, and patient outcomes. METHODS: A literature search was conducted on February 9, 2023, using the EBSCO CINAHL, Cochrane Central Register of Controlled Trials, Embase, IEEE Xplore, MEDLINE, Scopus, and Web of Science Core Collection databases. Eligible studies that included ICU clinicians as participants and tested the effect of dashboards designed for use by multiple users to manage multiple patients on user performance and/or satisfaction compared with the standard practice. We narratively synthesized eligible studies following the SWiM (Synthesis Without Meta-analysis) guidelines. Studies were grouped based on dashboard type and outcomes assessed. RESULTS: The search yielded a total of 2,407 studies. Five studies met inclusion criteria and were included. Among these, three studies evaluated interactive displays in the ICU, one study assessed two dashboards in the pediatric ICU (PICU), and one study examined centralized monitor in the PICU. Most studies reported several positive outcomes, including reductions in data gathering time before rounds, a decrease in misrepresentations during multidisciplinary rounds, improved daily documentation compliance, faster decision-making, and user satisfaction. One study did not report any significant association. CONCLUSION: The multipatient dashboards were associated with improved ICU clinician performance and were positively perceived in most of the included studies. The risk of bias was high, and the certainty of evidence was very low, due to inconsistencies, imprecision, indirectness in the outcome measure, and methodological limitations. Designing and evaluating multipatient tools using robust research methodologies is an important focus for future research.

Individualized prediction of critical illness in older adults: Validation of an elders risk assessment model.

BACKGROUND: The electronic health record (EHR) presents new opportunities for the timely identification of patients at high risk of critical illness and the implementation of preventive strategies. This study aims to externally validate an EHR-based Elders Risk Assessment (ERA) score to identify older patients at high risk of future critical illness during a primary care visit. METHODS: This historical cohort study included patients aged ≥65 years who had primary care visits at Mayo Clinic Rochester, MN, between July 2019 and December 2021. The ERA score at the time of the primary care visit was used to predict critical illness, defined as death or ICU admission within 1 year of the visit. RESULTS: A total of 12,885 patients were included in the analysis. The median age at the time of the primary care visit was 75 years, with 44.6% being male. 93.7% of participants were White, and 64.2% were married. The median (25th, 75th percentile) ERA score was 4 (0, 9). 11.3% of study participants were admitted to the ICU or died within 1 year of the visit. The ERA score predicted critical illness within 1 year of a primary care visit with an area under the receiver operating characteristic curve of 0.84 (95% CI 0.83-0.85), which indicates good discrimination. An ERA score of 9 was identified as optimal for implementing and testing potential preventive strategies, with the odds ratio of having the primary outcome in patients with ERA score ≥9 being 11.33 (95%CI 9.98-12.87). CONCLUSIONS: This simple EHR-based risk assessment model can predict critical illness within 1 year of primary care visits in older patients. The findings of this study can serve as a basis for testing and implementation of preventive strategies to promote the well-being of older adults at risk of critical illness and its consequences.

Association Between Ethnicity and Mortality Outcomes in Patients with COVID-19: A Mayo Clinic VIRUS Registry Cohort Study.

Hispanic populations face significant disparities in health and healthcare. The COVID-19 pandemic highlighted and sometimes further exacerbated these disparities. We conducted a multisite, retrospective cohort study of 6494 hospitalized adult patients admitted between March 2020 and January 2022 with a diagnosis of COVID-19 from five sites including academic hospitals in MN, AZ, and FL and community hospitals in MN and WI. This is an ancillary project of the Viral Infection and Respiratory illness Universal Study (VIRUS) registry, supplemented by electronic health record data. We compared in-hospital mortality and length of stay outcomes between Hispanic and non-Hispanic populations admitted with COVID-19 using propensity matched scores to account for imbalances in demographic and clinical covariables. Among a total of 6494 patients, 512 (7.9%) patients were reported deceased and 5982 (92.1%) alive at discharge. We did not find a statistically significant difference between in-hospital mortality nor length of stay between the two groups.

Psychological reactance, misinformation, and distrust: A mixed methods analysis of COVID-19 vaccine uptake.

Background: Assessing perceptions of the COVID-19 vaccines is essential for understanding vaccine hesitancy and for improving uptake during public health emergencies. In the complicated landscape of COVID-19 vaccine mandates and rampant misinformation, many individuals faced challenges during vaccination decision-making. The purpose of our mixed methods study is to elucidate factors affecting vaccine decision-making and to highlight the discourse surrounding the COVID-19 vaccines in diverse and underserved communities. Methods: This mixed methods study was conducted in Arizona, Florida, Minnesota, and Wisconsin between March and November 2021, combining a cross-sectional survey (n = 3593) and focus groups (n = 47). Results: The groups least likely to report receiving a vaccination were non-Hispanic Whites, Indigenous people, males, and those with moderate socioeconomic status (SES). Those indicating high and low SES reported similar vaccination uptake. Focus group data highlighted resistance to mandates, distrust, misinformation, and concerns about the rapid development surrounding the COVID-19 vaccines. Psychological reactance theory posits that strongly persuasive messaging and social pressure can be perceived as a threat to freedom, encouraging an individual to take action to restore that freedom. Conclusion: Our findings indicate that a subsection of participants felt pressured to get the vaccine, which led to weaker intentions to vaccinate. These results suggest that vaccine rollout strategies should be reevaluated to improve and facilitate informed decision-making.

Early Prevention of Critical Illness in Older Adults: Adaptation and Pilot Testing of an Electronic Risk Score and Checklist.

OBJECTIVE: Given limited critical care resources and an aging population, early interventions to prevent critical illness are vital. In this work, we measured post-implementation outcomes after introducing a novel electronic scoring system (Elders Risk Assessment-ERA) and a risk-factor checklist, Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN), to detect older patients at high risk of critical illness in a primary care setting. METHODS: The study was conducted at a family medicine clinic in Kasson, MN. The ADAPT-ITT framework was used to modify the CERTAIN checklist for primary care during 2 co-design workshops involving interdisciplinary clinicians, held in April 2023. The ERA score and modified CERTAIN checklist were implemented between May and July 2023 and identify and assess all patients age ≥60 years at risk of critical illness during their primary care visits. Implementation outcomes were evaluated at the end of the study via an anonymous survey and EHR data extraction. RESULTS: Fourteen clinicians participated in 2 co-design workshops. A total of 19 clinicians participated in a post-pilot survey. All survey items were rated on a 5-point Likert type scale. Mean acceptability of the ERA score and checklist was rated 3.35 (SD = 0.75) and 3.09 (SD = 0.64), respectively. Appropriateness had a mean rating of 3.38 (SD = 0.82) for the ERA score and 3.19 (SD = 0.59) for the checklist. Mean feasibility was rated 3.38(SD = 0.85) and 2.92 (SD = 0.76) for the ERA score and checklist, respectively. The adoption rate was 50% (19/38) among clinicians, but the reach was low at 17% (49/289) of eligible patients. CONCLUSIONS: This pilot study evaluated the implementation of an intervention that introduced the ERA score and CERTAIN checklist into a primary care practice. Results indicate moderate acceptability, appropriateness, and feasibility of the ERA score, and similar ratings for the checklist, with slightly lower feasibility. While checklist adoption was moderate, reach was limited, indicating inconsistent use. RECOMMENDATIONS: We plan to use the open-ended resurvey responses to further modify the CERTAIN-FM checklist and implementation process. The ADAPT-ITT framework is a useful model for adapting the checklist to meet the primary care clinician needs.

Patient experiences with prenatal cell-free DNA screening in a safety net setting.

OBJECTIVES: Thirty-five states, including Florida, now cover cell-free DNA (cfDNA) screening of fetuses for all pregnant patients enrolled in state public insurance programs. We interviewed Black and Hispanic obstetric patients at a safety net clinic in Florida shortly after the state rolled out cfDNA as a first-tier screening method for publicly insured patients. METHODS: Black and Hispanic patients receiving prenatal care from a prenatal or maternal fetal medicine clinic at a federally qualified health center in Jacksonville, FL were invited to participate in a qualitative interview in English or Spanish to explore experiences and perceptions of prenatal cfDNA screening. Participants were recruited following their first prenatal visit when cfDNA is typically introduced. Interview transcripts were qualitatively analyzed for iterative themes based on principles of grounded theory. RESULTS: One hundred Black and Hispanic patients (n = 51 non-Hispanic Black, n = 43 Hispanic, n = 3 Hispanic Black, n = 3 Not Reported/Other) completed an interview. Participants described minimal opportunity for pre-screening counseling and limited health literacy about cfDNA or its uses. Some believed that cfDNA could positively impact pregnancy health. Many were unsure if they had received cfDNA even though they were aware of the information provided by it. Most participants expressed an interest in cfDNA as a means for early detection of fetal sex and as an additional indication of general fetal health. CONCLUSIONS: Patient experiences indicate limited informed consent and decision-making for cfDNA, discordant with professional guidelines on pre-screen counseling. Our findings suggest that there should be additional investment in implementing cfDNA in safety net settings to ensure that patients and providers receive the support necessary for effective patient counseling and follow-on care for the ethical implementation of cfDNA.

Learning to collaborate with medical interpreters in health professions education: A systematic review of training programs.

BACKGROUND: Working effectively with medical interpreters is an increasingly valuable skill for clinicians to provide high-quality medical care. We aimed to assess the effectiveness of existing training programs that teach optimal collaboration practices between clinicians and interpreters during patient encounters. METHODS: We searched MEDLINE, EMBASE, Scopus, and Cochrane Central for studies published from 1945 through June 21, 2022. RESULTS: Out of the 1689 studies screened, we identified 19 studies that met inclusion criteria. Participants were from diverse professions, medical specialities, and training levels. Interpreter involvement in the development or delivery of the program was mentioned in 63% of the evaluated studies. There was substantial variability in training design, assessment methods, and reported outcomes. Only 10 of the programs included an objective knowledge or skills assessment. Only one study conducted a longitudinal assessment of skill maintenance over time. The training programs were generally well received. CONCLUSIONS: There is a critical need for structured programs to train clinicians to effectively collaborate with medical interpreters to reduce healthcare disparities. An effective training program should involve interpreters in the development and delivery of the program, practical skills development through interactive activities, structured clinical skill assessment, and both in-person and virtual components.

Using artificial intelligence to promote equitable care for inpatients with language barriers and complex medical needs: clinical stakeholder perspectives.

OBJECTIVES: Inpatients with language barriers and complex medical needs suffer disparities in quality of care, safety, and health outcomes. Although in-person interpreters are particularly beneficial for these patients, they are underused. We plan to use machine learning predictive analytics to reliably identify patients with language barriers and complex medical needs to prioritize them for in-person interpreters. MATERIALS AND METHODS: This qualitative study used stakeholder engagement through semi-structured interviews to understand the perceived risks and benefits of artificial intelligence (AI) in this domain. Stakeholders included clinicians, interpreters, and personnel involved in caring for these patients or for organizing interpreters. Data were coded and analyzed using NVIVO software. RESULTS: We completed 49 interviews. Key perceived risks included concerns about transparency, accuracy, redundancy, privacy, perceived stigmatization among patients, alert fatigue, and supply-demand issues. Key perceived benefits included increased awareness of in-person interpreters, improved standard of care and prioritization for interpreter utilization; a streamlined process for accessing interpreters, empowered clinicians, and potential to overcome clinician bias. DISCUSSION: This is the first study that elicits stakeholder perspectives on the use of AI with the goal of improved clinical care for patients with language barriers. Perceived benefits and risks related to the use of AI in this domain, overlapped with known hazards and values of AI but some benefits were unique for addressing challenges with providing interpreter services to patients with language barriers. CONCLUSION: Artificial intelligence to identify and prioritize patients for interpreter services has the potential to improve standard of care and address healthcare disparities among patients with language barriers.

Impact of SARS-CoV-2 Vaccine Rollout on Hispanic and Non-Hispanic Admission and Mortality Trends: An Interrupted Time Series Analysis.

BACKGROUND: Challenges with SARS-CoV-2 vaccine prioritization, access, and hesitancy have influenced vaccination uptake. RESEARCH QUESTION: Was the impact of SARS-CoV-2 vaccine rollout on COVID-19 monthly admission and mortality trends different between Hispanic and non-Hispanic populations? STUDY DESIGN AND METHODS: We used interrupted time series analysis to conduct an ancillary study of the Viral Infection and Respiratory Illness Universal Study registry supplemented by electronic health record data from five participating Mayo Clinic sites in Florida, Arizona, Minnesota, and Wisconsin. We included hospitalized patients with COVID-19 admitted between April 2020 and December 2021. Our primary outcome was the impact of vaccine rollout on admission trends. Our secondary outcome was the impact of vaccine rollout on mortality trends. RESULTS: This interrupted time series analysis includes 6,442 patients. Vaccine rollout was associated with improved monthly hospital admission trends among both Hispanic and non-Hispanic patients. Among Hispanic patients, pre-vaccine rollout, monthly admissions increased by 12.9% (95% CI, 8.1%-17.9%). Immediately after vaccine rollout, patient admissions declined by -66.3% (95% CI, -75.6% to -53.9%). Post-vaccine rollout, monthly admissions increased by 3.7% (95% CI, 0.2%-7.3%). Among non-Hispanic patients, pre-vaccine rollout, monthly admissions increased by 35.8% (95% CI, 33.4%-38.1%). Immediately after vaccine rollout, patient admissions declined by -75.2% (95% CI, -77.6% to -72.7%). Post-vaccine rollout, monthly admissions increased by 5.6% (95% CI, 4.5%-6.7%). These pre-vaccine rollout admission trends were significantly different (P < .001). Post-vaccine rollout, the change in admission trend was significantly different (P < .001). The associated beneficial impact from vaccine rollout on monthly hospital admission trends among Hispanic patients was significantly lower. The trend in monthly mortality rate was fourfold greater (worse) among Hispanic patients (8.3%; 95% CI, 3.6%-13.4%) vs non-Hispanic patients (2.2%; 95% CI, 0.6%-3.8%), but this was not shown to be related to vaccine rollout. INTERPRETATION: SARS-CoV-2 vaccine rollout was associated with improved COVID-19 admission trends among non-Hispanic vs Hispanic patients. Vaccine rollout was not shown to influence mortality trends in either group, which were four times higher among Hispanic patients. Improved vaccine rollout may have reduced disparities in admission trends for Hispanic patients, but other factors influenced their mortality trends.

Humanizing the Intensive Care Unit: Perspectives of Patients and Families on the Get to Know Me Board.

In this qualitative study, we explored perspectives of patients in the intensive care unit (ICU) and their families on the Get to Know Me board (GTKMB). Of the 46 patients approached, 38 consented to participate. Of the 66 family members approached, 60 consented to participate. Most patients (26, 89%) and family members (52, 99%) expressed that GTKMB was important in recognizing patient's humanity. Most patients (20, 68%) and families (39, 74%) said that it helped to build a better relationship with the provider team. 60% of patients and families commented that the GTKMB was used as a platform by providers to interact with them. Up to 45 (85%) of the family members supported specific contents of the GTKMB. In structured interviews (11 patients, 7 family members), participants additionally commented on ways providers used the GTKMB to communicate, support patient's personhood, and on caveats in interacting with GTKMB. Critically ill patients and families found the GTKMB helpful in preserving personhood of patient, fostering communication, and building relationships with clinicians.

A Public Health Ethics Framework for Populations with Limited English Proficiency.

25.6 Million people in the United States have Limited English Proficiency (LEP), defined as insufficient ability to read, write, or understand English. We will (1) Delineate the merits of approaching language as a social determinant of health, (2) highlight pertinent public health values and guidelines which are most relevant to the plight of populations with LEP and (3) Use the COVID-19 pandemic as an example of how a breakdown in public health ethics values created harm for populations and patients with LEP. We define a framework to tease out public health responsibilities given some populations' limited proficiency in a society's predominant language. The American Public Health Association (APHA) public health ethics core values serve as a framework to interrogate current practices. We use the COVID-19 case to illustrate gaps between health policy and healthcare disparities experienced by populations with LEP.

Who needs clinician attention first? A qualitative study of critical care clinicians' needs that enable the prioritization of care for populations of acutely ill patients.

BACKGROUND: To adequately care for groups of acutely ill patients, clinicians maintain situational awareness to identify the most acute needs within the entire intensive care unit (ICU) population through constant reappraisal of patient data from electronic medical record and other information sources. Our objective was to understand the information and process requirements of clinicians caring for multiple ICU patients and how this information is used to support their prioritization of care among populations of acutely ill patients. Additionally, we wanted to gather insights on the organization of an Acute care multi-patient viewer (AMP) dashboard. METHODS: We conducted and audio-recorded semi-structured interviews of ICU clinicians who had worked with the AMP in three quaternary care hospitals. The transcripts were analyzed with open, axial, and selective coding. Data was managed using NVivo 12 software. RESULTS: We interviewed 20 clinicians and identified 5 main themes following data analysis: (1) strategies used to enable patient prioritization, (2) strategies used for optimizing task organization, (3) information and factors helpful for situational awareness within the ICU, (4) unrecognized or missed critical events and information, and (5) suggestions for AMP organization and content. Prioritization of critical care was largely determined by severity of illness and trajectory of patient clinical status. Important sources of information were communication with colleagues from the previous shift, bedside nurses, and patients, data from the electronic medical record and AMP, and physical presence and availability in the ICU. CONCLUSIONS: This qualitative study explored ICU clinicians' information and process requirements to enable the prioritization of care among populations of acutely ill patients. Timely recognition of patients who need priority attention and intervention provides opportunities for improvement of critical care and for preventing catastrophic events in the ICU.

Evaluation of Digital Health Strategy to Support Clinician-Led Critically Ill Patient Population Management: A Randomized Crossover Study.

To investigate whether a novel acute care multipatient viewer (AMP), created with an understanding of clinician information and process requirements, could reduce time to clinical decision-making among clinicians caring for populations of acutely ill patients compared with a widely used commercial electronic medical record (EMR). DESIGN: Single center randomized crossover study. SETTING: Quaternary care academic hospital. SUBJECTS: Attending and in-training critical care physicians, and advanced practice providers. INTERVENTIONS: AMP. MEASUREMENTS AND MAIN RESULTS: We compared ICU clinician performance in structured clinical task completion using two electronic environments-the standard commercial EMR (Epic) versus the novel AMP in addition to Epic. Twenty subjects (10 pairs of clinicians) participated in the study. During the study session, each participant completed the tasks on two ICUs (7-10 beds each) and eight individual patients. The adjusted time for assessment of the entire ICU and the adjusted total time to task completion were significantly lower using AMP versus standard commercial EMR (-6.11; 95% CI, -7.91 to -4.30 min and -5.38; 95% CI, -7.56 to -3.20 min, respectively; p < 0.001). The adjusted time for assessment of individual patients was similar using both the EMR and AMP (0.73; 95% CI, -0.09 to 1.54 min; p = 0.078). AMP was associated with a significantly lower adjusted task load (National Aeronautics and Space Administration-Task Load Index) among clinicians performing the task versus the standard EMR (22.6; 95% CI, -32.7 to -12.4 points; p < 0.001). There was no statistically significant difference in adjusted total errors when comparing the two environments (0.68; 95% CI, 0.36-1.30; p = 0.078). CONCLUSIONS: When compared with the standard EMR, AMP significantly reduced time to assessment of an entire ICU, total time to clinical task completion, and clinician task load. Additional research is needed to assess the clinicians' performance while using AMP in the live ICU setting.

Comparative costs for critically ill patients with limited English proficiency versus English proficiency.

OBJECTIVES: To conduct comparative cost analysis of hospital care for critically ill patients with Limited English Proficiency (LEP) versus patients with English proficiency (controls). PATIENTS AND METHODS: We conducted a historical cohort study using propensity matching at Mayo Clinic Rochester, a quaternary care academic center. We included hospitalized patients who had at least one admission to ICU during a 10-year period between 1/1/2008-12/31/2017. RESULTS: Due to substantial differences in baseline characteristics of the groups, propensity matching for the covariates age, sex, race, ethnicity, APACHE 3 score, and Charlson Comorbidity score was used, and we achieved the intended balance. The final cohort included 80,404 patients, 4,246 with LEP and 76,158 controls. Patients with LEP had higher costs during hospital admission to discharge, with a mean cost difference of $3861 (95% CI $822 to $6900, p = 0.013) and also higher costs during index ICU admission to hospital discharge, with a mean cost difference of $3166 (95% CI $231 to $6101, p = 0.035). A propensity matched cohort including only those that survived showed those with LEP had significantly greater mean costs for all outcomes. Sensitivity analysis revealed that international patients with LEP had significantly greater overall hospital costs of $9,240 than patients with LEP who resided in the US (95% CI $3341 to $15,140, p = 0.002). CONCLUSION: This is the first study to demonstrate significantly higher costs for patients with LEP experiencing a critical illness. The causes for this may be increased healthcare utilization secondary to communication deficiencies that impede timely decision making about care.

A multisite exploration of the association between critical care implementation factors and clinical outcomes during the COVID-19 pandemic.

Background: Little is known about strategies to implement new critical care practices in response to COVID-19. Moreover, the association between differing implementation climates and COVID-19 clinical outcomes has not been examined. The purpose of this study was to evaluate the relationship between implementation determinants and COVID-19 mortality rates. Methods: We used mixed methods guided by the Consolidated Framework for Implementation Research (CFIR). Semi-structured qualitative interviews were conducted with critical care leaders and analyzed to rate the influence of CFIR constructs on the implementation of new care practices. Qualitative and quantitative comparisons of CFIR construct ratings were performed between hospital groups with low- versus high-mortality rates. Results: We found associations between various implementation factors and clinical outcomes of critically ill COVID-19 patients. Three CFIR constructs (implementation climate, leadership engagement, and engaging staff) had both qualitative and statistically significant quantitative correlations with mortality outcomes. An implementation climate governed by a trial-and-error approach was correlated with high COVID-19 mortality, while leadership engagement and engaging staff were correlated with low mortality. Another three constructs (needs of patient; organizational incentives and rewards; and engaging implementation leaders) were qualitatively different across mortality outcome groups, but these differences were not statistically significant. Conclusions: Improving clinical outcomes during future public health emergencies will require reducing identified barriers associated with high mortality and harnessing salient facilitators associated with low mortality. Our findings suggest that collaborative and engaged leadership styles that promote the integration of new yet evidence-based critical care practices best support COVID-19 patients and contribute to lower mortality.