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BACKGROUND: Patient admissions at a U.S. tertiary care hospital occur via the emergency department (ED), or transfer center. We aim to compare the clinical outcomes of patients admitted from the ED to admissions coordinated by the transfer center. METHODS: Admissions to Mayo Clinic Hospital, Rochester, MN, between July 2019 to June 2021 were identified in this retrospective study and categorized into two cohorts-transfer center and ED. The two cohorts were then matched for age, sex, admitting service, and Charlson Comorbidity Index. Univariate and multivariate analyses were performed to compare hospital length of stay (LOS), mortality, 30-day mortality, and 30-day readmissions between the two cohorts. RESULTS: 73,685 admissions were identified, of which 24,262 (33%) were transfer center admissions. In the matched cohorts (n = 19,093, each), in-hospital mortality (2.4% versus 1.9%), 30-day mortality (5.4% versus 3.9%), 30-day readmission (12.7% versus 7.2%), and LOS (6.4 days versus 5.1 days) were significantly higher ( P < 0.001) among the admissions coordinated by transfer center. A higher palliative care consultation rate (9.4% versus 6.2%, P < 0.001), and a lower proportion of home discharges home (76.2% versus 82.5%, P < 0.001) among transfer center admissions was observed. Similar findings were noted in multivariate analysis, even when adjusting for LOS. CONCLUSIONS: Transfer center admissions had higher in-hospital mortality, LOS, 30-day mortality, and 30-day readmission compared to ED admissions. This study also highlights new considerations for palliative care consultation before transfer acceptance, especially to avoid futile transfers. Additional studies analyzing factors behind the outcomes of transfer center admissions are required.
Subject(s)
Emergency Service, Hospital , Hospital Mortality , Length of Stay , Patient Transfer , Tertiary Care Centers , Humans , Female , Male , Emergency Service, Hospital/statistics & numerical data , Retrospective Studies , Middle Aged , Tertiary Care Centers/statistics & numerical data , Aged , Patient Transfer/statistics & numerical data , Length of Stay/statistics & numerical data , Patient Admission/statistics & numerical data , Patient Readmission/statistics & numerical data , United States , Aged, 80 and over , AdultABSTRACT
BACKGROUND: Older adults presenting with trauma have worse outcomes than younger adults. Starting in 2016, we provided geriatrics consultation (GC) to older adults admitted to the trauma service. We aimed to analyze the impact of GC on patient outcomes. METHODS: We performed a retrospective pre-post study and year-matched cohort study. We identified patients from the trauma registry at our level 1 trauma center. In the pre-post study, we compared patients who received GC (2016-2022) with controls (2011-2015). In the cohort study (2016-2022), we compared patients who received GC with controls. We matched for age, race, sex, and injury severity score (ISS) in both studies, as well as admission year in the cohort study. Outcome variables included mortality (in-hospital, 30-day, 90-day), length of stay (LOS), discharge disposition, and hospital readmission rates (30-day, 90-day). RESULTS: We analyzed 1968 patients in the pre-post study and 2544 patients in the cohort study. Patients were similar in age, race, and sex. GC patients had a slightly higher ISS score and a higher rate of ICU stay. Delirium occurrence was lower among GC patients. GC patients had lower in-hospital mortality compared to controls (pre-post OR 0.27, p < 0.001; cohort OR 0.31, p < 0.001) and increased LOS (6 days vs 4 days, p < 0.001; both studies). GC patients in the cohort study also had lower 30- and 90-day mortality (OR 0.52 and 0.65, p < 0.01) and were less likely to return home (OR 0.81, p < 0.01); similar trends, though not statistically significant, were noted in the pre-post study. Lower readmission rates (statistically non-significant) were noted in the GC group across both studies. CONCLUSIONS: GC in older adults with trauma has proven benefit with reduced mortality and a trend toward lower readmission rates but was associated with increased LOS and higher rates of discharge to skilled facility.
Subject(s)
Hospital Mortality , Length of Stay , Referral and Consultation , Trauma Centers , Wounds and Injuries , Humans , Female , Male , Aged , Retrospective Studies , Wounds and Injuries/mortality , Wounds and Injuries/therapy , Trauma Centers/statistics & numerical data , Referral and Consultation/statistics & numerical data , Length of Stay/statistics & numerical data , Aged, 80 and over , Geriatrics , Patient Readmission/statistics & numerical data , Injury Severity Score , Geriatric Assessment , Registries , Hospitalization/statistics & numerical data , Inpatients/statistics & numerical dataABSTRACT
Objective: To systematically review contemporary prediction models for hospital mortality developed or validated in general medical patients. Methods: We screened articles in five databases, from January 1, 2010, through April 7, 2022, and the bibliography of articles selected for final inclusion. We assessed the quality for risk of bias and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and extracted data using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. Two investigators independently screened each article, assessed quality, and extracted data. Results: From 20,424 unique articles, we identified 15 models in 8 studies across 10 countries. The studies included 280,793 general medical patients and 19,923 hospital deaths. Models included 7 early warning scores, 2 comorbidities indices, and 6 combination models. Ten models were studied in all general medical patients (general models) and 7 in general medical patients with infection (infection models). Of the 15 models, 13 were developed using logistic or Poisson regression and 2 using machine learning methods. Also, 4 of 15 models reported on handling of missing values. None of the infection models had high discrimination, whereas 4 of 10 general models had high discrimination (area under curve >0.8). Only 1 model appropriately assessed calibration. All models had high risk of bias; 4 of 10 general models and 5 of 7 infection models had low concern for applicability for general medical patients. Conclusion: Mortality prediction models for general medical patients were sparse and differed in quality, applicability, and discrimination. These models require hospital-level validation and/or recalibration in general medical patients to guide mortality reduction interventions.
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Objective: To determine whether a postdischarge video visit with patients, conducted by hospital medicine advanced practice providers, improves adherence to hospital discharge recommendations. Patients and Methods: We conducted a single-institution 2-site randomized clinical trial with 1:1 assignment to intervention vs control, with enrollment from August 10, 2020, to June 23, 2022. Hospital medicine patients discharged home or to an assisted living facility were randomized to a video visit 2-5 days postdischarge in addition to usual care (intervention) vs usual care (control). During the video visit, advanced practice providers reviewed discharge recommendations. Both intervention and control groups received telephone follow-up 3-6 days postdischarge to ascertain the primary outcome of adherence to all discharge recommendations for new and chronic medication management, self-management and action plan, and home support. Results: Among 1190 participants (594 intervention; 596 control), the primary outcome was ascertained in 768 participants (314 intervention; 454 control). In intervention vs control, there was no difference in the proportion of participants with the primary outcome (76.7% vs 72.5%; P=.19) or in the individual domains of the primary outcome: new and chronic medication management (94.1% vs 92.8%; P=.50), self-management and action plan (76.5% vs 71.5%; P=.18), and home support (94.1% vs 94.3%; P=.94). Women receiving intervention vs control had higher adherence to recommendations (odds ratio, 1.77; 95% CI, 1.08-2.91). Conclusion: In hospital medicine patients, a postdischarge video visit did not improve adherence to discharge recommendations. Potential gender differences in adherence require further investigation.Clinicaltrials.gov number, NCT04547803.
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OBJECTIVE: The Coronavirus Disease-19 (COVID-19) pandemic caused a decline in hospitalist wellness. The COVID-19 pandemic has evolved, and new outbreaks (i.e. Mpox) have challenged healthcare systems. The objective of the study was to assess changes in hospitalist wellness and guide interventions. METHODS: We surveyed hospitalists (physicians and advanced practice providers [APPs]), in May 2021 and September 2022, at a healthcare system's 16 hospitals in four US states using PROMIS® measures for global well-being, anxiety, social isolation, and emotional support. We compared wellness score between survey periods; in the September 2022 survey, we compared wellness scores between APPs and physicians and evaluated the associations of demographic and hospital characteristics with wellness using logistic (global well-being) and linear (anxiety, social isolation, emotional support) regression models. RESULTS: In May 2021 vs. September 2022, respondents showed no statistical difference in top global well-being for mental health (68.4% vs. 57.4%) and social activities and relationships (43.8% vs. 44.3%), anxiety (mean difference: +0.8), social isolation (mean difference: +0.5), and emotional support (mean difference: -1.0) (all, p ≥ 0.05). In September 2022, in logistic regression models, APPs, compared with physicians, had lower odds for top (excellent or very good) global well-being mental health (odds ratio [95% CI], 0.31 [0.13-0.76]; p < 0.05). In linear regression models, age <40 vs. ≥40 years was associated with higher anxiety (estimate ± standard error, 2.43 ± 1.05; p < 0.05), and concern about contracting COVID-19 at work was associated with higher anxiety (3.74 ± 1.10; p < 0.01) and social isolation (3.82 ± 1.21; p < 0.01). None of the characteristics showed association with change in emotional support. In September 2022, there was low concern for contracting Mpox in the community (4.6%) or at work (10.0%). CONCLUSION: In hospitalists, concern about contracting COVID-19 at work was associated with higher anxiety and social isolation. The unchanged wellness scores between survey periods identified opportunities for intervention. Mpox had apparently minor impact on wellness.
Subject(s)
COVID-19 , Hospitalists , Mpox (monkeypox) , Humans , COVID-19/epidemiology , Pandemics , Anxiety/epidemiology , Anxiety/psychology , Disease Outbreaks , Social IsolationABSTRACT
BACKGROUND: Routinely collected patient experience scores may inform risk of patient outcomes. The objective of the study was to evaluate the risk of hospital admission within 30-days following third-party receipt of the patient experience survey and guide interventions. METHODS: In this retrospective cohort study, we analyzed Hospital Consumer Assessment of Healthcare Providers and Systems surveys, January 2016-July 2019, from an institution's 20 hospitals in four U.S. states. Surveys were routinely sent to patients using census sampling. We analyzed surveys received ≤60 days following discharge from patients living ≤60 miles of any of the institution's hospitals. The exposures were 19 survey items. The outcome was hospital admission within 30 days after third-party receipt of the survey. We evaluated the association of favorable (top-box) vs unfavorable (non-top-box) score for survey items with risk of 30-day hospital admission in models including patient and hospitalization characteristics and reported adjusted odds ratios (aOR [95% confidence interval]). RESULTS: Among 40,162 respondents (mean age ± standard deviation: 68.1 ± 14.0 years), 49.8% were women and 4.3% had 30-day hospital admission. Patients with 30-day hospital admission, compared to those not admitted, were more likely to be discharged from a medical service line (62.9% vs 42.3%; P < 0.001) and have a higher Elixhauser index. Favorable vs unfavorable score for hospital rating was associated with lower odds of 30-day hospital admission in the overall cohort (0.88 [0.77-0.99]; P = 0.04), medical service line (0.81 [0.70-0.94]; P = 0.007), and upper tertile of Elixhauser index (0.79 [0.67-0.92]; P = 0.003). Favorable score for recommend hospital was associated with lower odds of 30-day hospital admission in the medical service line (0.83 [0.71-0.97]; P = 0.02) but for others (e.g. cleanliness of hospital environment) showed no association. CONCLUSION: In routinely collected patient experience scores, favorable hospital rating was associated with lower odds of 30-day hospital admission and may inform risk stratification and interventions. Evidence-based survey items linked to patient outcomes may also inform future surveys.
Subject(s)
Hospitalization , Patient Satisfaction , Humans , Female , Male , Retrospective Studies , Hospitals , Patient Outcome Assessment , Patient ReadmissionABSTRACT
OBJECTIVES: The COVID-19 pandemic impacted the availability and accessibility of outpatient care following hospital discharge. Hospitalists (physicians) and hospital medicine advanced practice providers (HM-APPs) coordinate discharge care of hospitalized patients; however, it is unknown if they can deliver post-discharge virtual care and overcome barriers to outpatient care. The objective was to develop and provide post-discharge virtual care for patients discharged from hospital medicine services. METHODS: We developed the Post-discharge Early Assessment with Remote video Link (PEARL) initiative for HM-APPs to conduct a post-discharge video visit (to review recommendations) and telephone follow-up (to evaluate adherence) with patients 2-6 days following hospital discharge. Participants included patients discharged from hospital medicine services at an institution's hospitals in Rochester (May 2020-August 2020) and Austin (November 2020-February 2021) in Minnesota, US. HM-APPs also interviewed patients about their experience with the video visit and completed a survey on their experience with PEARL. RESULTS: Of 386 eligible patients, 61.4% were enrolled (n = 237/386) including 48.1% women (n = 114/237). In patients with complete video visit and telephone follow-up (n = 141/237), most were prescribed new medications (83.7%) and took them as prescribed (93.2%). Among five classes of chronic medications, patient-reported adherence ranged from 59.2% (narcotics) to 91.5% (anti-hypertensives). Patient-reported self-management of 12 discharge recommendations ranged from 40% (smoking cessation) to 100% (checking rashes). Patients reported benefit from the video visit (agree: 77.3%) with an equivocal preference for video visits over clinic visits. Among HM-APPs who responded to the survey (88.2%; n = 15/17), 73.3% reported benefit from visual contact with patients but were uncertain if video visits would reduce emergency department visits. CONCLUSION: In this novel initiative, HM-APPs used video visits to provide care beyond their hospital role, reinforce discharge recommendations for patients, and reduce barriers to outpatient care. The effect of this initiative is under evaluation in a randomized controlled trial.
Subject(s)
COVID-19 , Hospital Medicine , Humans , Female , Male , Patient Discharge , Pandemics , AftercareABSTRACT
BACKGROUND: Delirium prediction can augment and optimize care of older adults. Mayo Delirium Prediction (MDP) tool is a robust tool, developed from a large retrospective data set. The MDP tool predicts delirium risk for hospitalized older adults, within 24 hours of hospital admission, based on risk factor information available from electronic health record. OBJECTIVE: We intend to validate the prediction performance of this tool and optimize the tool for clinical use. METHODS: This is an observational cohort study conducted at Mayo Clinic Hospitals, Rochester, MN. All hospitalized older adults (age >50 years) from December 2019 to June 2020 were included. Patients with an admitting diagnosis of substance use disorder were excluded. The original MDP tool was modified to adjust for the fall risk variable as a binary variable that will facilitate broader applicability across different fall risk tools. The modified MDP tool was validated in the retrospective derivation and validation data set which yielded similar prediction capability (area under the receiver operating curve = 0.85 and 0.83, respectively). Diagnosis of delirium was captured by flowsheet diagnosis of delirium documented by nursing staff in the medical record. Predictive variable data were collected daily. RESULTS: A total of 8055 patients were included in the study (median age 71 y). Delirium prediction of the modified MDP tool compared to delirium occurrence was 4% in the low-risk group, 17.8% in the medium-risk group, and 45.3% in the high-risk group (area under receiver operating curve of 0.80). Recalibration of the tool was attempted to further optimize the tool which resulted in both simplification and increased performance (area under receiver operating curve 0.82). The simplified tool was able to predict delirium in hospitalized patients admitted to both medical and surgical services. CONCLUSIONS: Validation of the modified MDP tool revealed good prediction capabilities. Recalibration resulted in simplification with increased performance of the tool in both medical and surgical hospitalized patients.
Subject(s)
Delirium , Humans , Aged , Middle Aged , Delirium/diagnosis , Delirium/epidemiology , Retrospective Studies , Cohort Studies , Hospitalization , Risk FactorsABSTRACT
Objective: To survey barriers in prescribing naltrexone for alcohol use disorder. Methods: A 12-question survey related to naltrexone prescribing patterns, perceptions, and knowledge was sent to 770 prescribers in the departments of internal medicine, family medicine, and psychiatry across a health system with sites in Arizona, Florida, and Minnesota. Results: Responses were obtained and included for 146/770 prescribers (19.0% response rate). Most respondents were in the department of internal medicine (n = 94, 64.4%), but the departments of psychiatry (n = 22, 15.1%) and family medicine (n = 30, 20.5%) were also represented. Only 34 (23.3%) respondents indicated they had prescribed naltrexone in the previous 3 months. The most common reasons for not prescribing naltrexone were "unfamiliarity with naltrexone for treatment of alcohol use disorder" and "patients do not have appropriate follow-up or are not in a formal treatment program." Compared with those representing internal/family medicine, psychiatry respondents were more likely to prescribe naltrexone and answer knowledge questions correctly. Conclusion: In this survey among primarily non-addiction-trained prescribers, a disparity was shown for prescribing naltrexone and in knowledge barriers between staff in internal/family medicine and psychiatry. There exist opportunities for education and quality improvement that promote the prescribing of naltrexone for alcohol use disorder by non-addiction specialists.
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BACKGROUND: The early phase of the coronavirus disease 2019 (COVID-19) pandemic had a negative impact on the wellness of hospitalists and hospital medicine advanced practice providers (APPs). However, the burden of the pandemic has evolved and the change in hospitalist and hospital medicine APP wellness is unknown. OBJECTIVE: To evaluate the longitudinal trend in wellness of hospitalists and hospital medicine APPs during the COVID-19 pandemic and guide wellness interventions. DESIGN, SETTING AND PARTICIPANTS: Between May 4, 2020, and June 6, 2021, we administered three surveys to Internal Medicine hospitalists (physicians) and hospital medicine APPs (nurse practitioners and physician assistants) at 16 Mayo Clinic hospitals in four U.S. states. MEASUREMENTS: We evaluated the association of hospitalist and hospital medicine APP characteristics with PROMIS® measures of global wellbeing-mental health, global wellbeing-social activities and relationships, anxiety, social isolation, and emotional support, using logistic and linear regression models. RESULTS: The response rates were 52.2% (n=154/295; May 2020), 37.1% (n=111/299; October 2020) and 35.5% (n=114/321; May 2021). In mixed models that included hospitalist and hospital medicine APP characteristics and survey period, APPs, compared with physicians, had lower odds of top global wellbeing-social activities and relationships (adjusted odds ratio 0.42 [0.22-0.82]; p = .01), whereas survey period showed no association. The survey period showed an independent association with higher anxiety (May 2020 vs. others) and higher social isolation (October 2020 vs. others), whereas profession showed no association. Concern about contracting COVID-19 at work was significantly associated with lower odds of top global wellbeing-mental health and global wellbeing-social activities and relationships, and with higher anxiety and social isolation. Hospitalist and hospital medicine APP characteristics showed no association with levels of emotional support. CONCLUSIONS: In this longitudinal assessment of hospitalists and hospital medicine APPs, concern about contracting COVID-19 at work remained a determinant of wellness. The trend for global wellbeing, anxiety, and social isolation may guide wellness interventions.
Subject(s)
COVID-19 , Hospital Medicine , Hospitalists , COVID-19/epidemiology , Hospitalists/psychology , Hospitals , Humans , PandemicsABSTRACT
OBJECTIVES: Hospitalists, comprising PAs, NPs, and physicians, manage patients hospitalized with COVID-19. To guide the development of support programs, this study compared the psychologic wellness of hospitalist PAs, NPs, and physicians during the COVID-19 pandemic. METHODS: We surveyed hospitalists in 16 hospitals at Mayo Clinic, from May 4 to 25, 2020. We used PROMIS surveys for self-reported global well-being (two single-item measures), anxiety, social isolation, and emotional support, before and during the pandemic. Linear and logistic regression models were adjusted for personal and professional factors. RESULTS: The response rate was 52.2% (N = 154/295). In adjusted linear regression models, the change in scores (before minus during pandemic) for anxiety, social isolation, and emotional support was similar for PAs and NPs compared with physicians. In adjusted logistic regression models, physicians, compared with PAs and NPs, had a higher odds of top global well-being for mental health (adjusted odds ratio [95% confidence interval]: 2.82 [1.12, 7.13]; P = .03) and top global well-being for social activities and relationships (adjusted odds ratio 4.08 [1.38, 12.08]; P = .01). CONCLUSIONS: During the COVID-19 pandemic, global well-being was lower for PAs and NPs compared with physician hospitalists. These results can guide support programs for hospitalists.
Subject(s)
COVID-19 , Hospitalists , COVID-19/epidemiology , Hospitalists/psychology , Hospitalization , Humans , Mental Health , PandemicsABSTRACT
Delirium is reported to be one of the manifestations of coronavirus infectious disease 2019 (COVID-19) infection. COVID-19 hospitalized patients are at a higher risk of delirium. Pathophysiology behind the association of delirium and COVID-19 is uncertain. We analyzed the association of delirium occurrence with outcomes in hospitalized COVID-19 patients, across all age groups, at Mayo Clinic hospitals.A retrospective study of all hospitalized COVID-19 patients at Mayo Clinic between March 1, 2020 and December 31, 2020 was performed. Occurrence of delirium and outcomes of mortality, length of stay, readmission, and 30-day mortality after hospital discharge were measured. Chi-square test, student t-test, survival analysis, and logistic regression analysis were performed to measure and compare outcomes of delirium group adjusted for age, sex, Charlson comorbidity score, and COVID-19 severity with no-delirium group.A total of 4351 COVID-19 patients were included in the study. Delirium occurrence in the overall study population was noted to be 22.4%. The highest occurrence of delirium was also noted in patients with critical COVID-19 illness severity. A statistically significant OR 4.35 (3.27-5.83) for in-hospital mortality and an OR 4.54 (3.25-6.38) for 30-day mortality after discharge in the delirium group were noted. Increased hospital length of stay, 30-day readmission, and need for skilled nursing facility on discharge were noted in the delirium group. Delirium in hospitalized COVID-19 patients is a marker for increased mortality and morbidity. In this group, outcomes appear to be much worse when patients are older and have a critical severity of COVID-19 illness.
Subject(s)
COVID-19/mortality , Delirium/epidemiology , Hospitalization/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/complications , Child , Child, Preschool , Delirium/complications , Humans , Infant , Infant, Newborn , Intensive Care Units , Length of Stay , Male , Middle Aged , Minnesota/epidemiology , Retrospective Studies , SARS-CoV-2 , Young AdultABSTRACT
Previous studies show that patient complaints can identify gaps in quality of care, but it is difficult to identify trends without categorization. We conducted a review of complaints relating to admissions on hospital internal medicine (HIM) services over a 26-month period. Data were collected on person characteristics and key features of the complaint. The complaints were also categorized into a previously published taxonomy. Seventy-six unsolicited complaints were identified, (3.5 per 1000 hospital admissions). Complaints were more likely on resident services. The mean duration between encounter and complaint was 18 days, and it took an average of 12 days to resolve the complaint. Most patients (59%) had a complaint in the Relationship domain. Thirty-nine percent of complaints mentioned a specific clinician. When a clinician was mentioned, complaints regarding communication and humaneness predominated (68%). The results indicate that the efforts to reduce patient complaints in HIM should focus on the Relationships domain.
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Alcohol use disorder (AUD) is a highly prevalent health issue in the United States. The number of those receiving medication-assisted treatment (MAT) is limited, despite strong evidence for their effectiveness. The inpatient setting may represent an important opportunity to initiate MAT. The goal of this study was to summarize the data on naltrexone initiation in the emergency department or inpatient setting for the management of AUDs. We searched ClinicalTrials.gov, Ovid EBM Reviews, Ovid Embase, Ovid Medline, Ovid PsycINFO, Scopus, and Web of Science from inception through October 31, 2019. Search strategies were created using a combination of keywords (Supplemental Appendix 1, available online at http://www.mcpiqojournal.org) and standardized index terms related to naltrexone therapy for medically hospitalized patients with AUD. Two uncontrolled pre-post study designs evaluated naltrexone prescription rates, 30-day readmission rates, and rehospitalization rates. Two authors independently abstracted data on study characteristics, results, and study-level risk of bias. The research team collaborated to assess the strength of evidence across studies. Two studies reported that implementing a protocol for naltrexone initiation increased MAT rates, with one study noting a substantial decrease in 30-day hospital readmissions. Overall, we found that there is a paucity of data on naltrexone initiation in the inpatient setting for AUDs. This likely reflects the nature of current clinical practice and prescriber comfortability. There is a need for further studies evaluating MAT initiation in the inpatient setting. Furthermore, efforts to increase provider knowledge of these therapeutic options are in need of further exploration.
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Background: Hospitalists, comprised of nurse practitioners and physician assistants (collectively, advanced practice providers [APPs]) and physicians, have opportunities to counsel patients and reduce SARS-CoV-2 related coronavirus disease 2019 (COVID-19) vaccine hesitancy. However, hospitalist perspectives on the COVID-19 vaccine and potential differences between APPs and physicians are unknown. Understanding hospitalist perspectives could help to address vaccine hesitancy among patients.Methods: We conducted an online survey of hospitalists at Mayo Clinic sites in Arizona, Florida, Minnesota, and Wisconsin from 14 December 2020 through 4 January 2021. We collected demographic information and assessed perspectives on the COVID-19 vaccine and, for comparison, on the influenza vaccine. Descriptive statistics were used to compare responses between APPs and physicians.Results: The overall response rate was 42.7% (n = 128/300) and comprised of 53.9% women (n = 69/128) and 41.4% APPs (n = 53/128). Most hospitalists reported receiving or planning to receive vaccination against COVID-19 (93.7%; n = 119/128) and influenza (97.7%; n = 125/128). Most hospitalists reported they would advise 100% of patients to receive the COVID-19 vaccine (66% for APPs; 74.7% for physicians) and influenza vaccine (83% for APPs; 80% for physicians). Barriers to recommending the COVID-19 vaccine included patient health status and vaccine safety profile. Hospitalists reported that patients and coworkers receiving the COVID-19 vaccine would reduce their anxiety (~80% of hospitalists), social isolation (~64% of hospitalists), and improve their emotional support (~40% of hospitalists). APP and physician responses were similar. The possible reduction in social isolation was associated with higher odds of hospitalists advising all patients to receive the COVID-19 vaccine (adjusted odds ratio 2.95 [95% confidence interval, 1.32-6.59]; P< .008), whereas hospitalist age, gender, and profession showed no association.Conclusion: Most hospitalists would reportedly advise patients to receive the COVID-19 vaccine. Barriers to this recommendation included patient health status and vaccine safety. Hospitalists are an important resource to provide patient education and reduce COVID-19 vaccine hesitancy.
Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Hospitalists/psychology , Influenza Vaccines/administration & dosage , Influenza, Human/prevention & control , Adult , COVID-19 Vaccines/adverse effects , Female , Health Status , Humans , Influenza Vaccines/adverse effects , Male , Middle Aged , Nurse Practitioners/psychology , Physician Assistants/psychology , Physicians/psychology , SARS-CoV-2 , Social Isolation , Socioeconomic FactorsABSTRACT
OBJECTIVE: To develop a delirium risk-prediction tool that is applicable across different clinical patient populations and can predict the risk of delirium at admission to hospital. METHODS: This retrospective study included 120,764 patients admitted to Mayo Clinic between January 1, 2012, and December 31, 2017, with age 50 and greater. The study group was randomized into a derivation cohort (n=80,000) and a validation cohort (n=40,764). Different risk factors were extracted and analyzed using least absolute shrinkage and selection operator (LASSO) penalized logistic regression. RESULTS: The area under the receiver operating characteristic curve (AUROC) for Mayo Delirium Prediction (MDP) tool using derivation cohort was 0.85 (95% confidence interval [CI], .846 to .855). Using the regression coefficients obtained from the derivation cohort, predicted probability of delirium was calculated for each patient in the validation cohort. For the validation cohort, AUROC was 0.84 (95% CI, .834 to .847). Patients were classified into 1 of the 3 risk groups, based on their predicted probability of delirium: low (≤5%), moderate (6% to 29%), and high (≥30%). In the derivation cohort, observed incidence of delirium was 1.7%, 12.8%, and 44.8% (low, moderate, and high risk, respectively), which is similar to the incidence rates in the validation cohort of 1.9%, 12.7%, and 46.3%. CONCLUSION: The Mayo Delirium Prediction tool was developed from a large heterogeneous patient population with good validation results and appears to be a reliable automated tool for delirium risk prediction with hospitalization. Further prospective validation studies are required.
Subject(s)
Clinical Decision Rules , Delirium/diagnosis , Delirium/etiology , Health Status Indicators , Aged , Aged, 80 and over , Female , Hospitalization , Humans , Logistic Models , Male , Middle Aged , Reproducibility of Results , Retrospective Studies , Risk Assessment , Risk FactorsABSTRACT
OBJECTIVE: To identify demographic trends associated with patient utilization and healthcare provider request for spiritual care services and to describe the impact of spiritual care on the quality of life (QoL), spiritual well-being (SWB) and level of satisfaction (SAT) of hospitalized patients. PATIENTS AND METHODS: A systematic search of Ovid MEDLINE, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Scopus, was combined with review of relevant bibliographies. A total of 464 titles and abstracts were reviewed. Data were independently extracted by reviewers according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data on the effects of spiritual interventions on QoL, SWB and SAT were extracted, along with demographic data reflecting chaplain services. The results of the studies are presented narratively and in a qualitative manner. RESULTS: Observational or experimental studies investigating chaplain utilization demographics (n = 12), patient satisfaction (n = 9) and QoL/SWB (n = 3) were included. Perceived severity of illness, average length of stay and older age were consistently found to be predictors of higher need for spiritual care. Receipt of spiritual care was correlated with increased patient and family satisfaction, independent of clinical outcome. Chaplain interventions were associated with improvement in perceived QoL and SWB. In spite of this, healthcare workers rarely attempt to explore the patient's or family's need for spiritual care, with the majority of chaplaincy consults occurring in the final day of the patient's life, potentially leading to a failure to meet the spiritual needs of non-terminal patients who have spiritual trauma related to their resolving illnesses. CONCLUSION: Attention to the spiritual needs of hospitalized patients is an essential yet often overlooked aspect of patient care. Chaplains serve as spiritual care specialists whose services can enhance the hospital experience, improve patient satisfaction and help to bridge potential gaps between the patient and medical providers.
Subject(s)
Inpatients , Quality of Life , Aged , Clergy , Humans , Patient Satisfaction , SpiritualityABSTRACT
BACKGROUND: Home telemonitoring has been used with discharged patients in an attempt to reduce 30-day readmissions with mixed results. OBJECTIVE: To assess whether home 30-day telemonitoring after discharge for patients at high risk of readmission would reduce readmissions or mortality. DESIGN: Prospective, randomized controlled trial. PATIENTS: We compared 30-day readmission rates and mortality for patients at high risk for readmission who received home telemonitoring versus standard care between November 1, 2014, and November 30, 2018, in 2 tertiary care hospitals. INTERVENTIONS: The intervention group received home-installed equipment to measure blood pressure, heart rate, pulse oximetry, weight if heart failure was present, and glucose if diabetes was present. Results were transmitted daily and reviewed by a nurse. Both groups received standard care. MAIN MEASURES: The primary outcome was a composite end point of hospital readmission or death within 30 days after discharge. The secondary outcome was an emergency department visit within 30 days after discharge. KEY RESULTS: A total of 1380 participants (mean [SD] age, 66 [14] years; 722 [52.3%] men and 658 [47.7%] women) participated in this study. Using a modified intention-to-treat analysis, the risk of readmission or death within 30 days among patients at high readmission risk was 23.7% (137/578) in the control group and 18.2% (87/477) in the telemonitoring group (absolute risk difference, - 5.5% [95% CI, - 10.4 to - 0.6%]; relative risk, 0.77 [95% CI, 0.61 to 0.98]; P = .03). Emergency department visits occurred within 30 days after discharge in 14.2% (81/570) of patients in the control group and 8.6% (40/464) of patients in the telemonitoring group (absolute risk difference, - 5.6% [95% CI, - 9.4 to - 1.8%]; relative risk, 0.61 [95% CI, 0.42 to 0.87]; P = .005). CONCLUSIONS: Thirty days of postdischarge telemonitoring may reduce readmissions of high-risk patients. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02136186.
Subject(s)
Aftercare , Patient Readmission , Aged , Female , Humans , Intention to Treat Analysis , Male , Patient Discharge , Prospective StudiesABSTRACT
Prescribing the right medication, at the right dose, to the right patient is the goal of every physician. Pharmacogenomic information is an emerging tool that can be used to deliver precision medicine. In this review, we discuss the pharmacogenomics of available PPIs, racial differences of CYP2C19 and how PPI pharmacogenomics affects the treatment of common gastrointestinal diseases. We also provide practical guidance on when to order pharmacogenomic testing, which test to order, and how to modify treatment based on published guidelines.