Association of Healthcare Access With Intensive Care Unit Utilization and Mortality in Patients of Hispanic Ethnicity Hospitalized With COVID-19

The Impact of Language on Hospital Outcomes for COVID-19 Patients: A Study of Non-English Speaking Hispanic Patients

BACKGROUND

The COVID-19 pandemic has highlighted and exacerbated health inequities, as demonstrated by the disproportionate rates of infection, hospitalization, and death in marginalized racial and ethnic communities. Although non-English speaking (NES) patients have substantially higher rates of COVID-19 positivity than other groups, research has not yet examined primary language, as determined by the use of interpreter services, and hospital outcomes for patients with COVID-19.

METHODS

Data were collected from 1,770 patients with COVID-19 admitted to an urban academic health medical center in the Chicago, Illinois area from March 2020 to April 2021. Patients were categorized as non-Hispanic White, non-Hispanic Black, NES Hispanic, and English-speaking (ES) Hispanic using NES as a proxy for English language proficiency. Multivariable logistic regression was used to compare the predicted probability for each outcome (i.e., ICU admission, intubation, and in-hospital death) by race/ethnicity.

RESULTS

After adjusting for possible confounders, NES Hispanic patients had the highest predicted probability of ICU admission (p-value < 0.05). Regarding intubation and in-hospital death, NES Hispanic patients had the highest probability, although statistical significance was inconclusive, compared to White, Black, and ES Hispanic patients.

CONCLUSIONS

Race and ethnicity, socioeconomic status, and language have demonstrated disparities in health outcomes. This study provides evidence for heterogeneity within the Hispanic population based on language proficiency that may potentially further contribute to disparities in COVID-19-related health outcomes within marginalized communities.

Demographic, social, and clinical aspects associated with access to COVID-19 health care in Pará province, Brazilian Amazon

Internal social disparities in the Brazilian Amazon became more evident during the COVID-19 pandemic. The aim of this work was to examine the demographic, social and clinical factors associated with access to COVID-19 health care in Pará Province in the Brazilian Amazon. This was an observational, cross-sectional, analytical study using a quantitative method through an online survey conducted from May to August 2023. People were eligible to participate if they were current residents of Pará, 18-years-old or older, with self-reported diagnoses of COVID-19 through rapid or laboratory tests. Participants completed an electronic survey was developed using Research Electronic Data Capture (REDCap) software-The adapted questionnaire "COVID-19 Global Clinical Platform: Case Report Form for Post-COVID Condition". Questions focused on access to COVID-19 treatment, demographic characteristics, COVID-19 vaccine and clinical characteristics. Respondent-driven sampling was applied to recruit participants. Multiple logistic regression was utilized to identify the associated factors. Overall, a total of 638 participants were included. The average age was 31.1 years. Access to COVID-19 health care was 68.65% (438/638). The participants most likely to access health care were those with moderate or severe COVID-19 (p = 0.000; OR: 19.8) and females (p = 0.001; OR: 1.99). Moreover, participants who used homemade tea or herbal medicines were less likely to receive health care for COVID-19 in health services (p = 0.002; OR: 0.54). Ensuring access to healthcare is important in a pandemic scenario.

Dissecting Clinical Features of COVID-19 in a Cohort of 21,312 Acute Care Patients

COVID-19 has resulted in over 645 million hospitalization and 7 million deaths globally. However, many questions still remain about clinical complications in COVID-19 and if these complications changed with different circulating SARS-CoV-2 strains. We analyzed a 2.5-year retrospective cohort of 47,063 encounters for 21,312 acute care patients at five Central Texas hospitals and define distinct trajectory groups (TGs) with latent class mixed modeling, based on the World Health Organization COVID-19 Ordinal Scale. Using this TG framework, we evaluated the association of demographics, diagnoses, vitals, labs, imaging, consultations, and medications with COVID-19 severity and broad clinical outcomes. Patients within 6 distinct TGs differed in manifestations of multi-organ disease and multiple clinical factors. The proportion of mild patients increased over time, particularly during Omicron waves. Age separated mild and fatal patients, though did not distinguish patients with severe versus critical disease. Male and Hispanic/Latino demographics were associated with more severe/critical TGs. More severe patients had a higher rate of neuropsychiatric diagnoses, consultations, and brain imaging, which did not change significantly in severe patients across SARS-CoV-2 variant waves. More severely affected patients also demonstrated an immunological signature of high neutrophils and immature granulocytes, and low lymphocytes and monocytes. Interestingly, low albumin was one of the best lab predictors of COVID-19 severity in association with higher malnutrition in severe/critical patients, raising concern of nutritional insufficiency influencing COVID-19 outcomes. Despite this, only a small fraction of severe/critical patients had nutritional labs checked (pre-albumin, thiamine, Vitamin D, B vitamins) or received targeted interventions to address nutritional deficiencies such as vitamin replacement. Our findings underscore the significant link between COVID-19 severity, neuropsychiatric complications, and nutritional insufficiency as key risk factors of COVID-19 outcomes and raise the question of the need for more widespread early assessment of patients' neurological, psychiatric, and nutritional status in acute care settings to help identify those at risk of severe disease outcomes.

COVID-19 infodemic and health-related quality of life in patients with chronic respiratory diseases: A multicentre, observational study

Background

The explosion of information, misinformation and disinformation (the "infodemic") related to the coronavirus disease 2019 (COVID-19) pandemic on digital and social media is reported to affect mental health and quality of life. However, reports assessing the COVID-19 infodemic on health-related quality of life (HRQL) in patients with chronic diseases are scarce. In this study, we investigated the associations between the infodemic and HRQL in uninfected individuals with pre-existing chronic respiratory diseases (CRDs) such as asthma, chronic obstructive pulmonary disease (COPD) and other CRDs.

Methods

We conducted a multi-national, cross-sectional, observational study in Canada, India, New Zealand and the United Kingdom where we distributed a set of digitised questionnaires among 1018 participants with chronic respiratory diseases who were not infected with the SARS-CoV-2 virus at least three months prior to the study. We collected information about the infodemic such as news watching or social media use more than usual during the pandemic. HRQL was assessed using the short form of the chronic respiratory questionnaire (SF-CRQ). Demographic information, comorbidities, compliance, mental health, behavioural function, and social support were also recorded. We analysed the direct and indirect relationships between infodemic and HRQL using structural equation models (SEM).

Results

Of all participants, 54% were females and had a mean (standard deviation (SD)) age of 53 (17) years. We found that higher infodemic was associated with worse emotional function (regression coefficient β = -0.08; 95% confidence interval (CI) = -0.14 to -0.01), which means a one SD change of the higher infodemic latent variable was associated with a 0.08 SD change of emotional function level. The association between higher infodemic and worse emotional function was mediated by worse mental health and behavioural functions but is marginally ameliorated by improved social support. In stratification analysis, we found significant disease and country-wise variations in the associations between infodemic and SF-CRQ domain scores.

Conclusions

These results provide new evidence that the COVID-19 infodemic significantly influences the HRQL in patients with CRDs through a complex interplay between mental health, behavioural function, and social support. This new dimension of research also opens avenues for further research on infodemic-related health effects in other chronic diseases.

Physical Activity Message Framing and Ethnicity Before and During COVID-19

People of Black ethnicities are well known to be disproportionately burdened by coronavirus and have poorer health outcomes. Public health messages encouraged physical activity during the pandemic as it is evidenced to positively affect the immune system, however people of Black ethnicities are often reported as failing to achieve the recommended daily amount. Health message framing during COVID-19 specifically in relation to ethnicity and physical activity motivation has yet to be investigated. Two studies examined message frame effect on physical activity motivation prior to and at the onset of the pandemic and how this differed by ethnicity. Gain framed messages were found to positively affect physical activity motivation pre-COVID-19 and during the pandemic fear framed messages were found to positively affect physical activity motivation. Neither of these effects differed by ethnicity. Implications for future physical activity health message framing are discussed.

Factors Associated with Severe COVID-19 Among Patients with Rheumatoid Arthritis: A Large, Nationwide Electronic Health Record Cohort Study in the United States

INTRODUCTION

To evaluate factors associated with severe coronavirus disease 2019 (COVID-19) among patients with rheumatoid arthritis (RA) in the US.

METHODS

Adults with RA who had a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, based on molecular or antigen test or clinical diagnosis, were identified from the Optum® COVID-19 Electronic Health Record dataset (March 1, 2020-April 28, 2021). The primary outcome was the occurrence of severe COVID-19 (hospitalization or death) within 30 days from SARS-CoV-2 infection. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression models to assess the association between severe COVID-19 and patient characteristics, including demographics, baseline comorbidities, and recent RA treatments.

RESULTS

During the study period, 6769 SARS-CoV-2 infections were identified in patients with RA, among whom 1460 (22%) developed severe COVID-19. Multivariable logistic regression analysis showed that being older, male, and non-White and having diabetes and cardiovascular conditions are associated with greater odds of severe COVID-19. In addition, compared with no use, the adjusted odds of severe COVID-19 were lower with recent use of tumor necrosis factor inhibitors (aOR 0.60, 95% CI 0.41-0.86) and higher with recent use of corticosteroids (aOR 1.38, 95% CI 1.13-1.69) or rituximab (aOR 2.87, 95% CI 1.60-5.14), respectively.

CONCLUSION

Nearly one in five patients with RA developed severe COVID-19 disease within 30 days after SARS-CoV-2 infection. In patients with RA, recent use of corticosteroids and rituximab were two factors associated with a greater risk of severe COVID-19 in addition to the risk factors among demographics and comorbidities previously identified in the general population.

Socio-Economic Factors Associated with Ethnic Disparities in SARS-CoV-2 Infection and Hospitalization

BACKGROUND

There is evidence that non-Italians presented higher incidence of infection and worse health outcomes if compared to native populations in the COVID-19 pandemic. The aim of the study was to compare Italian- and non-Italian-born health outcomes, accounting for socio-economic levels.

METHODS

We analyzed data relative to 906,463 people in Umbria (Italy) from 21 February 2020 to 31 May 2021. We considered the National Deprivation Index, the Urban-Rural Municipalities Index and the Human Development Index (HDI) of the country of birth. We used a multilevel logistic regression model to explore the influence of these factors on SARS-CoV-2 infection and hospitalization rates. Diagnosis in the 48 h preceding admission was an indicator of late diagnosis among hospitalized cases.

RESULTS

Overall, 54,448 persons tested positive (6%), and 9.7% of them were hospitalized. The risk of hospital admission was higher among non-Italians and was inversely related to the HDI of the country of birth. A diagnosis within 48 h before hospitalization was more frequent among non-Italians and correlated to the HDI level.

CONCLUSIONS

COVID-19 had unequal health outcomes among the population in Umbria. Reduced access to primary care services in the non-Italian group could explain our findings. Policies on immigrants' access to primary healthcare need to be improved.

Racial and Regional Disparities Surrounding In-Hospital Mortality among Patients with 2019 Novel Coronavirus Disease (COVID-19): Evidence from NIS Sample in 2020

OBJECTIVE

This study explores differences in COVID-19 in-hospital mortality rates by patient and geographic factors to identify at-risk populations and analyze how strained health disparities were exacerbated during the pandemic.

METHODS

The latest 2020 United States National Inpatient Sample (NIS) data was used to obtain a population-based estimate for patients with COVID-19. We conducted a cross-sectional retrospective data analysis, and sampling weights were used for all statistical analyses to represent nationwide in-hospital mortality of patients with COVID-19. We used multivariate logistic regression models to identify predictors for how patients with COVID-19 are associated with in-hospital death.

RESULTS

Of 200,531 patients, 88.9% did not have an in-hospital death (n=178,369), and 11.1% had in-hospital death (n=22,162). Patients older than 70 were 10 times more likely to have an in-hospital death than patients younger than 40 (p<0.001). Male patients were 37% more likely to have an in-hospital death than female patients (p<0.001). Hispanic patients were 25% more likely to have in-hospital deaths than White patients (p<0.001). In the sub-analysis, Hispanic patients in the 50-60, 60-70, and 70 age groups were 32%, 34%, and 24%, respectively, more likely to have in-hospital death than White patients (p<0.001). Patients with hypertension and diabetes were 69% and 29%, respectively, more likely to have in-hospital death than patients without hypertension and diabetes.

CONCLUSION

Health disparities in the COVID-19 pandemic occurred across races and regions and must be addressed to prevent future deaths. Age and comorbidities like diabetes have a well-established link to increased disease severity, and we have linked both to higher mortality risk. Low-income patients had a significantly increased risk of in-hospital death starting at over 40 years old.

Acute and post-acute sequelae of SARS-CoV-2 infection: a review of risk factors and social determinants

SARS-CoV-2 infection leading to Coronavirus Disease 2019 (COVID-19) has caused more than 762 million infections worldwide, with 10-30% of patients suffering from post-acute sequelae of SARS-CoV-2 infections (PASC). Initially thought to primarily affect the respiratory system, it is now known that SARS-CoV-2 infection and PASC can cause dysfunction in multiple organs, both during the acute and chronic stages of infection. There are also multiple risk factors that may predispose patients to worse outcomes from acute SARS-CoV-2 infection and contribute to PASC, including genetics, sex differences, age, reactivation of chronic viruses such as Epstein Barr Virus (EBV), gut microbiome dysbiosis, and behavioral and lifestyle factors, including patients' diet, alcohol use, smoking, exercise, and sleep patterns. In addition, there are important social determinants of health, such as race and ethnicity, barriers to health equity, differential cultural perspectives and biases that influence patients' access to health services and disease outcomes from acute COVID-19 and PASC. Here, we review risk factors in acute SARS-CoV-2 infection and PASC and highlight social determinants of health and their impact on patients affected with acute and chronic sequelae of COVID-19.

Multimorbidity and social determinants of health in the US prior to the COVID-19 pandemic and implications for health outcomes: a cross-sectional analysis based on NHANES 2017-2018

Multimorbidity increases the risk of all-cause mortality, and along with age, is an independent risk factor for severe disease and mortality from COVID-19. Inequities in the social determinants of health contributed to increased mortality from COVID-19 among disadvantaged populations. This study aimed to evaluate the prevalence of multimorbid conditions and associations with the social determinants of health in the US prior to the pandemic.Methods Data from the 2017-18 cycle of NHANES were used to determine the prevalence of 13 chronic conditions, and the prevalence of having 0, 1, or 2 or more of those conditions, among the US adult population aged ≥ 20 years. Multimorbidity was defined as having 2 or more of these conditions. Data were stratified according to demographic, socioeconomic and indicators of health access, and analyses including logistic regression, performed to determine the factors associated with multimorbidity.Results The prevalence of multimorbidity was 58.4% (95% CI 55.2 to 61.7). Multimorbidity was strongly associated with age and was highly prevalent among those aged 20-29 years at 22.2% (95% CI 16.9 to 27.6) and continued to increase with older age. The prevalence of multimorbidity was highest in those defined as Other or multiple races (66.9%), followed in decreasing frequency by rates among non-Hispanic Whites (61.2%), non-Hispanic Blacks (57.4%), Hispanic (52.0%) and Asian (41.3%) groups.Logistic regression showed a statistically significant relationship between multimorbidity and age, as expected. Asian race was associated with a reduced likelihood of 2 or more chronic conditions (OR 0.4; 95% CI 0.35 to 0.57; P < 0.0001). Socioeconomic factors were related to multimorbidity. Being above the poverty level (OR 0.64; 95% CI 0.46 to 0.91, p = 0.013); and a lack of regular access to health care (OR 0.61 (95% CI 0.42 to 0.88, p = 0.008) were both associated with a reduced likelihood of multimorbidity. Furthermore, there was a borderline association between not having health insurance and reduced likelihood of multimorbidity (OR 0.63; 95% CI 0.40 to 1.0; p = 0.053).Conclusions There are high levels of multimorbidity in the US adult population, evident from young adulthood and increasing with age. Cardiometabolic causes of multimorbidity were highly prevalent, especially obesity, hyperlipidemia, hypertension, and diabetes; conditions subsequently found to be associated with severe disease and death from COVID-19. A lack of access to care was paradoxically associated with reduced likelihood of comorbidity, likely linked to underdiagnosis of chronic conditions. Obesity, poverty, and lack of access to healthcare are factors related to multimorbidity and were also relevant to the health impact of the COVID-19 pandemic, that must be addressed through comprehensive social and public policy measures. More research is needed on the etiology and determinants of multimorbidity, on those affected, patterns of co-morbidity, and implications for individual health and impact on health systems and society to promote optimal outcomes. Comprehensive public health policies are needed to tackle multimorbidity and reduce disparities in the social determinants of health, as well as to provide universal access to healthcare.

COVID-19 stressors for Hispanic/Latino patients living with type 2 diabetes: a qualitative study

Background and aim

During the early stages of the COVID-19 pandemic, nationwide lockdowns caused disruption in the diets, physical activities, and lifestyles of patients with type 2 diabetes. Previous reports on the possible association between race/ethnicity, COVID-19, and mortality have shown that Hispanic/Latino patients with type 2 diabetes who are socioeconomically disadvantaged are disproportionately affected by this novel virus. The aim of this study was to explore stressors associated with changes in diabetes self-management behaviors. Our goal was to highlight the health disparities in these vulnerable racial/ethnic minority communities and underscore the need for effective interventions.

Methods and participants

Participants were enrolled in part of a larger randomized controlled trial to compare diabetes telehealth management (DTM) with comprehensive outpatient management (COM) in terms of critical patient-centered outcomes among Hispanic/Latino patients with type 2 diabetes. We conducted a thematic analysis using patient notes collected from two research nurses between March 2020 and March 2021. Two authors read through the transcripts independently to identify overarching themes. Once the themes had been identified, both authors convened to compare themes and ensure that similar themes were identified within the transcripts. Any discrepancies were discussed by the larger study team until a consensus was reached.

Results

Six themes emerged, each of which can be categorized as either a source or an outcome of stress. Sources of stress associated with the COVID-19 pandemic were (1) fear of contracting COVID-19, (2) disruptions from lockdowns, and (3) financial stressors (e.g., loss of income). Outcomes of COVID-19 stressors were (1) reduced diabetes management (e.g., reduced diabetes monitoring and physical activity), (2) suboptimal mental health outcomes (e.g., anxiety and depression), and (3) outcomes of financial stressors.

Conclusion

The findings indicated that underserved Hispanic/Latino patients with type 2 diabetes encountered a number of stressors that led to the deterioration of diabetes self-management behaviors during the pandemic.

Evaluating Racial/Ethnic Differences in Care Escalation Among COVID-19 Patients in a Home-Based Hospital

The novel coronavirus disease 2019 (COVID-19) has infected over 414 million people worldwide with 5.8 million deaths, as of February 2022. Telemedicine-based interventions to expand healthcare systems' capacity and reduce infection risk have rapidly increased during the pandemic, despite concerns regarding equitable access. Atrium Health Hospital at Home (AH-HaH) is a home-based program that provides advanced, hospital-level medical care and monitoring for patients who would otherwise be hospitalized in a traditional setting. Our retrospective cohort study of positive COVID-19 patients who were admitted to AH-HaH aims to investigate whether the rate of care escalation from AH-HaH to traditional hospitalization differed based on patients' racial/ethnic backgrounds. Logistic regression was used to examine the association between care escalation within 14 days from index AH-HaH admission and race/ethnicity. We found approximately one in five patients receiving care for COVID-19 in AH-HaH required care escalation within 14 days. Odds of care escalation were not significantly different for Hispanic or non-Hispanic Blacks compared to non-Hispanic Whites. However, secondary analyses showed that both Hispanic and non-Hispanic Black patients were younger and with fewer comorbidities than non-Hispanic Whites. The study highlights the need for new care models to vigilantly monitor for disparities, so that timely and tailored adaptations can be implemented for vulnerable populations.

Mortality by Education Before and During the COVID-19 Pandemic, U.S., 2017-2020

INTRODUCTION

Mortality disparities by SES, including education, have steadily increased in the U.S. over the past decades. This study examined whether these disparities overall and for 7 major causes of death were exacerbated in 2020, coincident with the emergence of the COVID-19 pandemic.

METHODS

Using data on 7,123,254 U.S. deaths from 2017 to 2020, age-standardized death rates and mortality rate differences per 100,000 population and rate ratios comparing least with most educated were calculated by sex and race/ethnicity.

RESULTS

All-cause death rates were approximately 2 times higher among adults with least than among those with most education. Disparities in all-cause mortality by educational attainment slightly increased from 2017 (rate ratio=1.97; 95% CI=1.95, 1.98; rate difference=739.9) to 2019 (rate ratio=2.04; 95% CI=2.03, 2.06; rate difference=761.3) and then greatly increased in 2020 overall (rate ratio=2.32; 95% CI=2.30, 2.33; rate difference=1,042.9) and when excluding COVID-19 deaths (rate ratio=2.27; 95% CI=2.25, 2.28; rate difference=912.3). Similar patterns occurred across race/ethnicity and sex, although Hispanic individuals had the greatest relative increase in disparities for all-cause mortality from 2019 (rate ratio=1.47; 95% CI=1.43, 1.51; rate difference=282.4) to 2020 overall (rate ratio=2.00; 95% CI=1.94, 2.06; rate difference=652.3) and when excluding COVID-19 deaths (rate ratio=1.84; 95% CI=1.79, 1.90; rate difference=458.7). Disparities in cause-specific mortality by education were generally stable from 2017 to 2019, followed by a considerable increase from 2019 to 2020 for heart disease, cancer, cerebrovascular disease, and unintentional injury. Among these causes of death, the relative increase in rate ratio from 2019 to 2020 was greatest for unintentional injury (24.8%; from 3.41 [95% CI=3.23, 3.60] to 4.26 [95% CI=3.99, 4.53]).

CONCLUSIONS

Mortality disparities by education widened in the U.S. in 2020, during the COVID-19 pandemic. Further research is warranted to understand the reasons for these widened disparities.

The association between non-English primary language and COVID-19 clinical trial eligibility and enrollment: A retrospective cohort study

BACKGROUND

Establishing equitable access to COVID-19 clinical trials is an important step in mitigating outcomes disparities. Historically, language has served as a barrier to equitable clinical trial participation.

METHODS

A centralized research infrastructure was established at our institution to screen potential trial participants and to promote efficient and equitable access to COVID-19 clinical trials. Rates of eligibility and enrollment in COVID-19 clinical trials by primary language between April 9 and July 31, 2020 (during the first regional COVID-19 surge) were evaluated using logistic regression. Estimates were adjusted for potential confounders including age, sex, and time.

RESULTS

A total of 1245 patients were admitted to the hospital with COVID-19 during the study period and screened for clinical trial eligibility. Among all screened patients, 487 (39%) had a non-English primary language. After adjustment, patients with a non-English primary language had 1.98 times higher odds (CI 1.51 to 2.59) of being eligible for 1 or more COVID-19 clinical trials. Among eligible patients, those with a non-English primary language had 1.83 times higher odds (CI 1.36 to 2.47) of enrolling in COVID-19 clinical trials than patients with English as the primary language.

CONCULSION

These findings suggest that there are modifiable barriers that can be addressed to lessen the impact of language discordance on access to clinical trials and provide an opportunity to further investigate factors associated with clinical trial participation for patients whose primary language is not English.

Evaluating the Medication Regimen Complexity Score as a Predictor of Clinical Outcomes in the Critically Ill

Background: Medication Regimen Complexity (MRC) refers to the combination of medication classes, dosages, and frequencies. The objective of this study was to examine the relationship between the scores of different MRC tools and the clinical outcomes. Methods: We conducted a retrospective cohort study at Roger William Medical Center, Providence, Rhode Island, which included 317 adult patients admitted to the intensive care unit (ICU) between 1 February 2020 and 30 August 2020. MRC was assessed using the MRC Index (MRCI) and MRC for the Intensive Care Unit (MRC-ICU). A multivariable logistic regression model was used to identify associations among MRC scores, clinical outcomes, and a logistic classifier to predict clinical outcomes. Results: Higher MRC scores were associated with increased mortality, a longer ICU length of stay (LOS), and the need for mechanical ventilation (MV). MRC-ICU scores at 24 h were significantly (p < 0.001) associated with increased ICU mortality, LOS, and MV, with ORs of 1.12 (95% CI: 1.06−1.19), 1.17 (1.1−1.24), and 1.21 (1.14−1.29), respectively. Mortality prediction was similar using both scoring tools (AUC: 0.88 [0.75−0.97] vs. 0.88 [0.76−0.97]. The model with 15 medication classes outperformed others in predicting the ICU LOS and the need for MV with AUCs of 0.82 (0.71−0.93) and 0.87 (0.77−0.96), respectively. Conclusion: Our results demonstrated that both MRC scores were associated with poorer clinical outcomes. The incorporation of MRC scores in real-time therapeutic decision making can aid clinicians to prescribe safer alternatives.