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CD4+ T cells can either enhance or inhibit tumour immunity. Although regulatory T cells have long been known to impede antitumour responses1-5, other CD4+ T cells have recently been implicated in inhibiting this response6,7. Yet, the nature and function of the latter remain unclear. Here, using vaccines containing MHC class I (MHC-I) neoantigens (neoAgs) and different doses of tumour-derived MHC-II neoAgs, we discovered that whereas the inclusion of vaccines with low doses of MHC-II-restricted peptides (LDVax) promoted tumour rejection, vaccines containing high doses of the same MHC-II neoAgs (HDVax) inhibited rejection. Characterization of the inhibitory cells induced by HDVax identified them as type 1 regulatory T (Tr1) cells expressing IL-10, granzyme B, perforin, CCL5 and LILRB4. Tumour-specific Tr1 cells suppressed tumour rejection induced by anti-PD1, LDVax or adoptively transferred tumour-specific effector T cells. Mechanistically, HDVax-induced Tr1 cells selectively killed MHC-II tumour antigen-presenting type 1 conventional dendritic cells (cDC1s), leading to low numbers of cDC1s in tumours. We then documented modalities to overcome this inhibition, specifically via anti-LILRB4 blockade, using a CD8-directed IL-2 mutein, or targeted loss of cDC2/monocytes. Collectively, these data show that cytotoxic Tr1 cells, which maintain peripheral tolerance, also inhibit antitumour responses and thereby function to impede immune control of cancer.
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Antígenos de Neoplasias , Linfocitos T CD4-Positivos , Citotoxicidad Inmunológica , Inmunoterapia , Neoplasias , Linfocitos T Reguladores , Animales , Femenino , Humanos , Masculino , Ratones , Antígenos de Neoplasias/inmunología , Vacunas contra el Cáncer/inmunología , Vacunas contra el Cáncer/uso terapéutico , Linfocitos T CD4-Positivos/inmunología , Linfocitos T CD4-Positivos/metabolismo , Línea Celular Tumoral , Quimiocina CCL5/metabolismo , Células Dendríticas/inmunología , Granzimas/metabolismo , Antígenos de Histocompatibilidad Clase I/inmunología , Antígenos de Histocompatibilidad Clase II/inmunología , Interleucina-10/metabolismo , Interleucina-10/inmunología , Ratones Endogámicos C57BL , Neoplasias/inmunología , Neoplasias/terapia , Linfocitos T Reguladores/inmunología , Receptores Inmunológicos/antagonistas & inhibidores , Glicoproteínas de Membrana/antagonistas & inhibidores , Tolerancia Inmunológica , Linfocitos T CD8-positivos/inmunologíaRESUMEN
BACKGROUND: People with schizophrenia are less likely than those without to be treated for cardiovascular disease. We aimed to evaluate the association between schizophrenia and secondary preventive care after ischemic stroke. METHODS AND RESULTS: In this retrospective cohort study, we used linked population-based administrative data to identify adults who survived 1 year after ischemic stroke hospitalization in Ontario, Canada between 2004 and 2017. Outcomes were screening, treatment, and control of risk factors, and receipt of outpatient physician services. We used modified Poisson regression to model the relative risk of each outcome among people with and without schizophrenia, adjusting for age and other factors. Among 81 163 people with ischemic stroke, 844 (1.04%) had schizophrenia. Schizophrenia was associated with lower rates of screening for hyperlipidemia (60.5% versus 66.0%, adjusted relative risk [aRR] 0.88 [95% CI, 0.84-0.93]) and diabetes (69.4% versus 73.9%, aRR 0.93 [95% CI, 0.89-0.97]), prescription of antihypertensive medications (91.2% versus 94.7%, aRR 0.96 [95% CI, 0.93-0.99]), achievement of target lipid levels (low-density lipoprotein <2 mmol/L) (30.6% versus 34.6%, aRR 0.86 [95% CI, 0.78-0.96]), and outpatient specialist visits (55.3% versus 67.8%, aRR 0.78 [95% CI, 0.74-0.83]) or primary care physician visits (94.5% versus 98.5%; aRR 0.96 [95% CI, 0.95-0.98]) within 1 year. There were no differences in prescription of antilipemic, antiglycemic, or anticoagulant medications, or in achievement of target hemoglobin A1c ≤7%. CONCLUSIONS: People with stroke and schizophrenia are less likely than those without to receive secondary preventive care. This may inform interventions to improve poststroke care and outcomes in those with schizophrenia.
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Esquizofrenia , Prevención Secundaria , Humanos , Esquizofrenia/complicaciones , Esquizofrenia/epidemiología , Masculino , Femenino , Estudios Retrospectivos , Persona de Mediana Edad , Prevención Secundaria/métodos , Ontario/epidemiología , Anciano , Factores de Riesgo , Accidente Cerebrovascular Isquémico/prevención & control , Accidente Cerebrovascular Isquémico/epidemiología , Accidente Cerebrovascular Isquémico/diagnóstico , Adulto , Accidente Cerebrovascular/prevención & control , Accidente Cerebrovascular/epidemiología , Accidente Cerebrovascular/etiologíaRESUMEN
OBJECTIVE: Current scores for predicting sepsis outcomes are limited by generalizability, complexity, and electronic medical record (EMR) integration. Here, we validate a simple EMR-based score for sepsis outcomes in a large multi-centre cohort. DESIGN: A simple electronic medical record-based predictor of illness severity in sepsis (SEPSIS) score was developed (4 additive lab-based predictors) using a population-based retrospective cohort study. SETTING: Internal medicine services across four academic teaching hospitals in Toronto, Canada from April 2010-March 2015 (primary cohort) and 2015-2019 (secondary cohort). PATIENTS: We identified patients admitted with sepsis based upon receipt of antibiotics and positive cultures. MEASUREMENTS AND MAIN RESULTS: The primary outcome was in-hospital mortality and secondary outcomes were ICU admission at 72 hours, and hospital length of stay (LOS). We calculated the area under the receiver operating curve (AUROC) for the SEPSIS score, qSOFA, and NEWS2. We then evaluated the SEPSIS score in a secondary cohort (2015-2019) of hospitalized patients receiving antibiotics. Our primary cohort included 1,890 patients with a median age of 72 years (IQR: 56-83). 9% died during hospitalization, 18.6% were admitted to ICU, and mean LOS was 12.7 days (SD: 21.5). In the primary and secondary (2015-2019, 4811 patients) cohorts, the AUROCs of the SEPSIS score for predicting in-hospital mortality were 0.63 and 0.64 respectively, which were similar to NEWS2 (0.62 and 0.67) and qSOFA (0.62 and 0.68). AUROCs for predicting ICU admission at 72 hours, and length of stay > 14 days, were similar between scores, in the primary and secondary cohorts. All scores had comparable calibration for predicting mortality. CONCLUSIONS: An EMR-based SEPSIS score shows a similar ability to predict important clinical outcomes compared with other validated scores (qSOFA and NEWS2). Because of the SEPSIS score's simplicity, it may prove a useful tool for clinical and research applications.
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Registros Electrónicos de Salud , Mortalidad Hospitalaria , Sepsis , Índice de Severidad de la Enfermedad , Humanos , Sepsis/mortalidad , Sepsis/diagnóstico , Masculino , Anciano , Femenino , Persona de Mediana Edad , Estudios Retrospectivos , Anciano de 80 o más Años , Tiempo de Internación , Unidades de Cuidados Intensivos , Curva ROCRESUMEN
BACKGROUND: Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. OBJECTIVE: To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. METHODS: We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. RESULTS: Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium. CONCLUSIONS: Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.
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Delirio , Clasificación Internacional de Enfermedades , Humanos , Delirio/diagnóstico , Delirio/epidemiología , Masculino , Femenino , Anciano , Estudios Retrospectivos , Persona de Mediana Edad , Anciano de 80 o más Años , Ontario/epidemiología , Hospitalización , Estudios de CohortesRESUMEN
OBJECTIVE: To determine whether presence of a psychiatric comorbidity impacts use of inpatient imaging tests and subsequent wait times. METHODS: This was a retrospective cohort study of all patients admitted to General Internal Medicine (GIM) at five academic hospitals in Toronto, Ontario from 2010 to 2019. Exposure was presence of a coded psychiatric comorbidity on admission. Primary outcome was time to test, as calculated from the time of test ordering to time of test completion, for computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, or peripherally inserted central catheter (PICC) insertion. Multilevel mixed-effects models were used to identify predictors of time to test, and marginal effects were used to calculate differences in absolute units (h). Secondary outcome was the rate of each type of test included. Subgroup analyses were performed according to type of psychiatric comorbidity: psychotic, mood/anxiety, or substance use disorder. RESULTS: There were 196,819 GIM admissions from 2010to 2019. In 77,562 admissions, ≥1 advanced imaging test was performed. After adjusting for all covariates, presence of any psychiatric comorbidity was associated with increased time to test for MRI (adjusted difference: 5.3 h, 95% confidence interval [CI]: 3.9-6.8), PICC (adjusted difference: 3.7 h, 95% CI: 1.6-5.8), and ultrasound (adjusted difference: 3.0 h, 95% CI: 2.3-3.8), but not for CT (adjusted difference: 0.1 h, 95% CI: -0.3 to 0.5). Presence of any psychiatric comorbidity was associated with lower rate of ordering for all test types (adjusted difference: -17.2 tests per 100 days hospitalization, interquartile range: -18.0 to -16.3). CONCLUSIONS: There was a lower rate of ordering of advanced imaging among patients with psychiatric comorbidity. Once ordered, time to test completion was longer for MRI, ultrasound, and PICC. Further exploration, such as quantifying rates of cancelled tests and qualitative studies evaluating hospital, provider, and patient barriers to timely advanced imaging, will be helpful in elucidating causes for these disparities.
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Pacientes Internos , Trastornos Relacionados con Sustancias , Humanos , Estudios Retrospectivos , Comorbilidad , AnsiedadRESUMEN
OBJECTIVE: To examine how project Extension for Community Healthcare Outcomes-Integrated Mental and Physical Health (ECHO-IMPH) influences the attitudes and approaches of primary care providers and other participants towards patients. METHODS: An exploratory qualitative approach was undertaken using semistructured interviews conducted between August 2020 and March 2021. One hundred and sixty-four individuals from two cycles of ECHO-IMPH were invited to participate, and 22 (n = 22) agreed to participate. Data were analyzed using the Braun and Clarke method for thematic analysis. RESULTS: Three major themes were identified: 1) enhanced knowledge and skills; 2) changes in attitude and approach; 3) space for reflection and exploration. When participants were asked about areas for improvement, suggestions were focused on the structure of the sessions. Participants identified that ECHO-IMPH helped them to view patients more holistically, which led to greater patient-centered care in their practice. Additionally, skills gained in ECHO-IMPH gave participants the concrete tools needed to have more empathetic interactions with patients with complex needs. CONCLUSIONS: ECHO-IMPH created a safe space for participants to reflect on their practice with patients with complex needs. Participants applied newly acquired knowledge and skills to provide more empathetic and patient-centered care for patients with complex needs. Based on the shift in perspectives described by participants, transformative learning theory was proposed as a model for how ECHO-IMPH created change in participants' practice.
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Atención Dirigida al Paciente , Humanos , OntarioRESUMEN
Importance: The COVID-19 pandemic caused large disruptions to health care for hospitalized older adults. The incidence and management of delirium may have been affected by high rates of COVID-19 infection, staffing shortages, overwhelmed hospital capacity, and changes to visitor policies. Objective: To measure changes in rates of delirium and related medication prescribing during the COVID-19 pandemic among hospitalized older adults. Design, Setting, and Participants: This population-based, repeated cross-sectional study used linked databases to measure rates of delirium and related medication prescriptions among adults aged 66 years or older hospitalized before and during the COVID-19 pandemic (January 1, 2017, to March 31, 2022) in Ontario, Canada. Exposure: The first 2 years of the COVID-19 pandemic (March 1, 2020, to March 31, 2022). Main Outcomes and Measures: The main outcomes were weekly rates of delirium per 1000 admitted population and monthly rates of new antipsychotic and benzodiazepine prescriptions per 1000 discharged population. Observed rates were compared with projected rates based on modeling from 3 years before pandemic onset. Results: Among 2â¯128â¯411 hospitalizations of older adults over the 5-year study period (50.7% female; mean [SD] age, 78.9 [8.3] years), absolute rates of delirium increased from 35.9 per 1000 admitted population during the prepandemic period to 41.5 per 1000 admitted population throughout the pandemic. The adjusted rate ratio (ARR) of delirium during the pandemic compared with the projected rate was 1.15 (95% CI, 1.11-1.19). Monthly rates of new antipsychotic prescriptions increased from 6.9 to 8.8 per 1000 discharged population and new benzodiazepine prescriptions from 4.4 to 6.0 per 1000 discharged population and were significantly higher during the pandemic compared with projected rates (antipsychotics: ARR, 1.28; 95% CI, 1.19-1.38; benzodiazepines: ARR, 1.37; 95% CI, 1.20-1.57). Rates were highest during pandemic waves 1 (March to June 2020), 3 (March to June 2021), and 5 (December 2021 to February 2022) and remained elevated above projected levels throughout the first 2 years of the pandemic. Conclusions and Relevance: In this repeated cross-sectional study of hospitalized older adults, there was a temporal association between COVID-19 pandemic onset and significant increases in rates of delirium in the hospital and new antipsychotic and benzodiazepine prescriptions after hospital discharge. Rates remained elevated over 2 years. Pandemic-related changes such as visitor restrictions, staff shortages, isolation practices, and reduced staff time at the bedside may have contributed to these trends.
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Antipsicóticos , COVID-19 , Delirio , Humanos , Femenino , Anciano , Masculino , Benzodiazepinas/uso terapéutico , COVID-19/epidemiología , Antipsicóticos/uso terapéutico , Pandemias , Estudios Transversales , Ontario/epidemiología , Delirio/tratamiento farmacológico , Delirio/epidemiologíaRESUMEN
BACKGROUND: Reducing laboratory test overuse is important for high quality, patient-centred care. Identifying priorities to reduce low value testing remains a challenge. OBJECTIVE: To develop a simple, data-driven approach to identify potential sources of laboratory overuse by combining the total cost, proportion of abnormal results and physician-level variation in use of laboratory tests. DESIGN, SETTING AND PARTICIPANTS: A multicentre, retrospective study at three academic hospitals in Toronto, Canada. All general internal medicine (GIM) hospitalisations between 1 April 2010 and 31 October 2017. RESULTS: There were 106 813 GIM hospitalisations during the study period, with median hospital length-of-stay of 4.6 days (IQR: 2.33-9.19). There were 21 tests which had a cumulative cost >US$15 400 at all three sites. The costliest test was plasma electrolytes (US$4 907 775), the test with the lowest proportion of abnormal results was red cell folate (0.2%) and the test with the greatest physician-level variation in use was antiphospholipid antibodies (coefficient of variation 3.08). The five tests with the highest cumulative rank based on greatest cost, lowest proportion of abnormal results and highest physician-level variation were: (1) lactate, (2) antiphospholipid antibodies, (3) magnesium, (4) troponin and (5) partial thromboplastin time. In addition, this method identified unique tests that may be a potential source of laboratory overuse at each hospital. CONCLUSIONS: A simple multidimensional, data-driven approach combining cost, proportion of abnormal results and physician-level variation can inform interventions to reduce laboratory test overuse. Reducing low value laboratory testing is important to promote high value, patient-centred care.
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Pacientes Internos , Médicos , Humanos , Estudios Retrospectivos , Hospitalización , Medicina InternaRESUMEN
BACKGROUND: There is increasing interest in collecting sociodemographic and social needs data in hospital settings to inform patient care and health equity. However, few studies have examined inpatients' views on this data collection and what should be done to address social needs. This study describes internal medicine inpatients' perspectives on the collection and use of sociodemographic and social needs information. METHODS: A qualitative interpretive description methodology was used. Semi-structured interviews were conducted with 18 patients admitted to a large academic hospital in Toronto, Canada. Participants were recruited using maximum variation sampling for diverse genders, races, and those with and without social needs. Interviews were coded using a predominantly inductive approach and a thematic analysis was conducted. RESULTS: Patients expressed that sociodemographic and social needs data collection is important to offer actionable solutions to address their needs. Patients described a gap between their ideal care which would attend to social needs, versus the reality that hospital-based teams are faced with competing priorities and pressures that make it unfeasible to provide such care. They also believed that this data collection could facilitate more holistic, integrated care. Patients conveyed a need to have a trusting and transparent relationship with their provider to alleviate concerns surrounding bias, discrimination, and confidentiality. Lastly, they indicated that sociodemographic and social needs data could be useful to inform care, support research to inspire social change, and assist them with navigating community resources or creating in-hospital programs to address unmet social needs. CONCLUSIONS: While the collection of sociodemographic and social needs information in hospital settings is generally acceptable, there were varied views on whether hospital staff should intervene, as their priority is medical care. The results can inform the implementation of social data collection and interventions in hospital settings.
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Pacientes Internos , Humanos , Masculino , Femenino , Investigación Cualitativa , Recolección de Datos , CanadáRESUMEN
OBJECTIVE: Throughout the COVID-19 pandemic, there have been concerns about the mental health of health care workers (HCW). Although numerous studies have investigated the level of distress among HCW, few studies have explored programs to improve their mental well-being. In this paper, we describe the implementation and evaluation of a program to support the mental health of HCW at University Health Network (UHN), Canada's largest healthcare network. METHODS: Using a quality improvement approach, we conducted a needs assessment and then created and evaluated a modified stepped-care model to address HCW mental health during the pandemic. This included: online resources focused on psychoeducation and self-management, access to online support and psychotherapeutic groups, and self-referral for individual care from a psychologist or psychiatrist. We used ongoing mixed-methods evaluation, combining quantitative and qualitative analysis, to improve program quality. RESULTS: The program is ongoing, running continuously throughout the pandemic. We present data up to November 30, 2021. There were over 12,000 hits to the UHN's COVID mental health intranet web page, which included self-management resources and information on group support. One hundred and sixty-six people self-referred for individual psychological or psychiatric care. The mean wait time from referral to initial appointment was 5.4 days, with an average of seven appointments for each service user. The majority had moderate to severe symptoms of depression and anxiety at referral, with over 20% expressing thoughts of self-harm or suicide. Post-care user feedback, collected through self-report surveys and semistructured interviews, indicated that the program is effective and valued. CONCLUSIONS: Development of a high-quality internal mental health support for HCW program is feasible, effective, and highly valued. By using early and frequent feedback from multiple perspectives and stakeholders to address demand and implement changes responsively, the program was adjusted to meet HCW mental health needs as the pandemic evolved.
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COVID-19 , Salud Mental , Humanos , Pandemias , Personal de Salud , Derivación y ConsultaRESUMEN
BACKGROUND: Delirium is an acute neurocognitive disorder that affects up to half of older hospitalized medical patients and can lead to dementia, longer hospital stays, increased health costs, and death. Although delirium can be prevented and treated, it is difficult to identify and predict. OBJECTIVE: This study aimed to improve machine learning models that retrospectively identify the presence of delirium during hospital stays (eg, to measure the effectiveness of delirium prevention interventions) by using the natural language processing (NLP) technique of sentiment analysis (in this case a feature that identifies sentiment toward, or away from, a delirium diagnosis). METHODS: Using data from the General Medicine Inpatient Initiative, a Canadian hospital data and analytics network, a detailed manual review of medical records was conducted from nearly 4000 admissions at 6 Toronto area hospitals. Furthermore, 25.74% (994/3862) of the eligible hospital admissions were labeled as having delirium. Using the data set collected from this study, we developed machine learning models with, and without, the benefit of NLP methods applied to diagnostic imaging reports, and we asked the question "can NLP improve machine learning identification of delirium?" RESULTS: Among the eligible 3862 hospital admissions, 994 (25.74%) admissions were labeled as having delirium. Identification and calibration of the models were satisfactory. The accuracy and area under the receiver operating characteristic curve of the main model with NLP in the independent testing data set were 0.807 and 0.930, respectively. The accuracy and area under the receiver operating characteristic curve of the main model without NLP in the independent testing data set were 0.811 and 0.869, respectively. Model performance was also found to be stable over the 5-year period used in the experiment, with identification for a likely future holdout test set being no worse than identification for retrospective holdout test sets. CONCLUSIONS: Our machine learning model that included NLP (ie, sentiment analysis in medical image description text mining) produced valid identification of delirium with the sentiment analysis, providing significant additional benefit over the model without NLP.
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BACKGROUND: The mental health of healthcare workers (HCWs) has been at the forefront throughout the COVID-19 pandemic. While workplace-based support programs have been developed in hospitals globally, few systematically collected data. While critical to their success, information on these programs and the experience of mental healthcare providers (MHP) who support colleagues is limited. The objective of this study was to explore the experiences of MHP caring for HCW colleagues within a novel workplace-based mental health support program during the COVID-19 pandemic, to provide insights on facilitators, areas for improvement and barriers to program sustainability. METHODS: This qualitative study used semi-structured interviews conducted by videoconference between September 2020 to October 2021. UHN CARES (University Health Network Coping and Resilience for Employees and Staff) Program was developed during the first wave of the COVID-19 pandemic in March 2020. It supports over 21,000 staff members within the UHN, Canada's largest academic health research institution, in Toronto, Canada. Purposive sampling was used to select 10 of the 22 MHP in the UHN CARES Program (n = 10). Using a critical realism framework, key components required to sustain a successful workplace-based mental health support program for HCWs and balance the needs of MHP were determined. RESULTS: Six psychiatrists and four psychologists (n = 10) with varying roles at UHN participated in 17 interviews, including seven repeat interviews exploring changes over time within the pandemic and program. Components which facilitated the success of the program included flexibility in scheduling, confidential health record storage, comprehensive administrative support, availability of resources and adaptive quality improvement approach. Recommendations for improvement included opportunities for peer supervision, triaging of cases, and managing HCW expectations. MHP found caring for HCWs to be meaningful and they utilized existing clinical skills during sessions. Challenges included working in a virtual setting, navigating boundaries when caring for colleagues, and managing the range of service users and their needs. CONCLUSIONS: These findings suggest how support programs can be structured for HCWs, how to provide support, and how to sustain this support, allowing health systems to balance the needs of HCWs and MHPs in preparation for future public health emergencies.
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COVID-19 , Desastres , Humanos , Pandemias , Salud Pública , Urgencias Médicas , Personal de Salud/psicologíaRESUMEN
Background: COVID-19 has had a significant impact on the wellbeing of healthcare workers, with quantitative studies identifying increased stress, anxiety, depression, insomnia, and PTSD in a wide range of settings. Limited qualitative data so far has offered in-depth details concerning what underlies these challenges, but none provide comprehensive comparison across different healthcare systems. Objective: To explore qualitative findings relating to healthcare worker distress from two different countries to understand the nuanced similarities and differences with respect to the sources and impact of distress relating to COVID-19. Method: A comparative interpretive thematic analysis was carried out between two qualitative data sets examining healthcare workers' experiences of distress during the COVID-19 pandemic. Data from Canada and the UK were collected in parallel and analyzed in an iterative, collaborative process. Results: A number of sources of distress cut across both study settings including concerns about safety and patient care, challenges at home or in one's personal life, communication issues, work environment, media and public perception, and government responses to the pandemic. These sit on a spectrum from individual to institutional sources and were mutually reinforcing. Our analysis also suggested that common mechanisms such as exacerbations in uncertainty, hypervigilance, and moral injury underpinned these sources, which contributed to how they were experienced as distressing. Conclusion: This is the first international collaboration utilising qualitative data to examine this pressing issue. Despite differences in the political, social, health service, and pandemic-related context, the sources and mechanisms of distress experienced by healthcare workers in Canada and the UK were remarkably similar. HIGHLIGHTS This international comparative qualitative study explores how mechanisms that lead to distress are shared across different geographies and cultures, even as the local context shapes the sources of distress themselves.
Antecedentes: La COVID-19 ha tenido un impacto significativo en el bienestar de los trabajadores de la salud, con estudios cuantitativos que identifican un aumento del estrés, la ansiedad, la depresión, el insomnio, y el TEPT en una amplia variedad de entornos. Hasta ahora, los datos cualitativos son limitados y han ofrecido un profundo detalle sobre lo que subyace a estos desafíos, pero ninguno proporciona una comparación exhaustiva entre los diferentes sistemas de atención de salud.Objetivo: Explorar los hallazgos cualitativos relacionados con la angustia de los trabajadores de la salud de dos países diferentes para comprender las sutiles similitudes y diferencias con respecto a las fuentes y el impacto de la angustia relacionada con la COVID-19.Método: Se llevó a cabo un análisis temático interpretativo comparativo entre dos conjuntos de datos cualitativos que examinaron las experiencias de angustia de los trabajadores de la salud durante la pandemia de la COVID-19. Los datos de Canadá y el Reino Unido se recopilaron en paralelo y se analizaron en un proceso colaborativo iterativo.Resultados: Una serie de fuentes de angustia atraviesan ambos entornos de estudio, incluidas las preocupaciones sobre la seguridad y el cuidado del paciente, los desafíos en el hogar o en la vida personal, los problemas de comunicación, el entorno laboral, la percepción pública y de los medios de comunicación, y las respuestas gubernamentales a la pandemia. Estos se ubican en un espectro desde fuentes individuales hasta institucionales y se reforzaron mutuamente. Nuestro análisis también sugirió que mecanismos comunes como las exacerbaciones de la incertidumbre, la hipervigilancia, y el daño moral sustentaban estas fuentes, lo que contribuyó a que se experimentaran como angustiosas.Conclusión: Esta es la primera colaboración internacional que utiliza datos cualitativos para examinar este apremiante problema. A pesar de las diferencias en el contexto político, social, de servicios de salud y relacionado con la pandemia, las fuentes y los mecanismos de angustia experimentados por los trabajadores de la salud en Canadá y el Reino Unido fueron notablemente similares.
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COVID-19 , Personal de Salud , Humanos , Pandemias , Investigación Cualitativa , Reino Unido/epidemiologíaRESUMEN
Delirium is an acute neurocognitive disorder, which is difficult to identify and predict. Using GEMINI, Canada's largest hospital data and analytics study, we had a labeled sample of around 4,000 cases with approximately 25% of cases being labeled as having delirium. Based on this labeled data, we developed machine learning (ML) models and interacted with physicians to interpret the ML models and their predictions. We developed a preliminary Explainable Artificial Intelligence (XAI) framework for physician experience design (PXD) to improve the uptake of ML models by improving the transparency of model results, thereby increasing physician trust in models as well as the uptake of model results for clinical decision making. We developed our PXD approach first with Conceptual Investigation to collect and extract physicians' feedback on ML models and their evaluation requirements. We carried out a case study, working closely with the physicians in a participatory design process to develop a dashboard that presents ML delirium identification results interactively based on physician selections and inputs. In this approach a physician-preferred ML model for clinical decision making is selected through PXD evaluation.
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BACKGROUND: Project Extension for Community Healthcare Outcomes (ECHO) is a virtual training and capacity building model that uses videoconferencing to link expert interdisciplinary teams with primary care clinicians in local communities. In this study, we evaluated ECHO Ontario Integrated Mental and Physical Health (ECHO-IMPH). This is the first consultation-liaison psychiatrist-led Project ECHO explicitly designed to support health care providers (HCPs) within primary care in delivering better care for patients with co-occurring mental and physical health needs. We assessed the impact of ECHO-IMPH on HCP engagement, learning, and practice change. METHODS: Using Moore's Evaluation Framework, we used attendance logs and weekly surveys to investigate HCP engagement and satisfaction with ECHO-IMPH, as well as questionnaires to assess impact on their learning, self-efficacy, and practice change with respect to patient care. A pre-post design was used to assess change in the latter. RESULTS: A total of 322 HCPs participated in ECHO-IMPH across five cycles. High mean ratings were observed for satisfaction across all five cycles (4.35 ± 0.59). Precycle and postcycle questionnaires were available for 145 participants, allowing for paired comparison. Mean self-efficacy scores were significantly higher after the cycle than that before (64.26 ± 15.63 to 78.15 ± 11.44; t(144) = 11.61, P < 0.001, d = 1.03). Over 80% of participants reported changes in their professional practice post ECHO-IMPH. CONCLUSIONS: This is the first study to describe the impact of a Project ECHO led by consultation-liaison psychiatrists focused on integrated mental and physical health care and to demonstrate that this can be effective in changing HCP professional practice and self-efficacy, with high engagement and satisfaction.