Administrative data are increasingly used to conduct research on depression and inform health services and health policy. Depression surveillance using administrative data is an alternative to surveys, which can be more resource-intensive. The objectives of this study were to: (1) systematically review the literature on validated case definitions to identify depression using International Classification of Disease and Related Health Problems (ICD) codes in administrative data and (2) identify individuals with and without depression in administrative data and develop an enhanced case definition to identify persons with depression in ICD-coded hospital data. (1) Systematic review: We identified validation studies using ICD codes to indicate depression in administrative data up to January 2013. (2) Validation: All depression case definitions from the literature and an additional three ICD-9-CM and three ICD-10 enhanced definitions were tested in an inpatient database. The diagnostic accuracy of all case definitions was calculated [sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV)]. (1) Systematic review: Of 2,014 abstracts identified, 36 underwent full-text review and three met eligibility criteria. These depression studies used ICD-9 and ICD-10 case definitions. (2) Validation: 4,008 randomly selected medical charts were reviewed to assess the performance of new and previously published depression-related ICD case definitions. All newly tested case definitions resulted in Sp >99%, PPV >89% and NPV >91%. Sensitivities were low (28-35%), but higher than for case definitions identified in the literature (1.1-29.6%). Validating ICD-coded data for depression is important due to variation in coding practices across jurisdictions. The most suitable case definitions for detecting depression in administrative data vary depending on the context. For surveillance purposes, the most inclusive ICD-9 & ICD-10 case definitions resulted in PPVs of 89.7% and 89.5%, respectively. In cases where diagnostic certainty is required, the least inclusive ICD-9 and −10 case definitions are recommended, resulting in PPVs of 92.0% and 91.1%. All proposed case definitions resulted in suboptimal levels of sensitivity (ranging from 28.9%-35.6%). The addition of outpatient data (such as pharmacy records) for depression surveillance is recommended and should result in improved measures of validity.

Rationale: Delirium is common in the ICU and portends worse ICU and hospital outcomes. The effect of delirium in the ICU on post–hospital discharge mortality and health resource use is less well known. Objectives: To estimate mortality and health resource use 2.5 years after hospital discharge in critically ill patients admitted to the ICU. Methods: This was a population-based, propensity score–matched, retrospective cohort study of adult patients admitted to 1 of 14 medical–surgical ICUs from January 1, 2014, to June 30, 2016. Delirium was measured by using the 8-point Intensive Care Delirium Screening Checklist. The primary outcome was mortality. The secondary outcome was a composite measure of subsequent emergency department visits, hospital readmission, or mortality. Measurements and Main Results: There were 5,936 propensity score–matched patients with and without a history of incident delirium who survived to hospital discharge. Delirium was associated with increased mortality 0–30 days after hospital discharge (hazard ratio, 1.44 [95% confidence interval, 1.08–1.92]). There was no significant difference in mortality more than 30 days after hospital discharge (delirium: 3.9%, no delirium: 2.6%). There was a persistent increased risk of emergency department visits, hospital readmissions, or mortality after hospital discharge (hazard ratio, 1.12 [95% confidence interval, 1.07–1.17]) throughout the study period. Conclusions: ICU delirium is associated with increased mortality 0–30 days after hospital discharge.

Use systematic review methodology to summarize risk factors and outcomes for each delirium subtype (hypoactive, hyperactive and mixed) in an adult ICU population. We searched the MEDLINE, Embase, CINAHL, SCOPUS, Web of Science and PsycINFO databases from database inception until August 13, 2018, with no restrictions. Of 9635 abstracts, 20 studies were included. Older age was not associated with any delirium subtype in 4/7 (57%) studies. Sex was not associated with any delirium subtype in 4/4 (100%) studies. Mortality was consistently associated with hypoactive delirium in 4/7 (57%) studies. The evidence supporting the association of APACHE-II score, mechanical ventilation, length of stay, duration of delirium and removal of tubes were inconsistent across studies. Although included studies reported on many subtype-specific risk factors and outcomes, heterogeneity in reporting and methodological quality limited the generalizability of the results and the evidence for many subtype-specific risk factors or outcomes is inconsistent across studies. Standardized methodology and the creation of a universal template for collecting data in ICU delirium studies are essential moving forward; helping to identify subtype-specific risk factors or outcomes and strengthen the association of potential risk factors or outcomes.

Background: Restricted visitation policies in acute care settings because of the COVID-19 pandemic have negative consequences. The objective of this scoping review is to identify impacts of restricted visitation policies in acute care settings, and describe perspectives and mitigation approaches among patients, families, and healthcare professionals.Methods: We searched Medline, Embase, PsycINFO, Healthstar, CINAHL, Cochrane Central Register of Controlled Trials on January 01/2021, unrestricted, for published primary research records reporting any study design. We included secondary (e.g., reviews) and non-research records (e.g., commentaries), and performed manual searches in web-based resources. We excluded records that did not report primary data. Two reviewers independently abstracted data in duplicate.Results: Of 7810 citations, we included 155 records. Sixty-six records (43%) were primary research; 29 (44%) case reports or case series, and 26 (39%) cohort studies; 21 (14%) were literature reviews and 8 (5%) were expert recommendations; 54 (35%) were commentary, editorial, or opinion pieces. Restricted visitation policies impacted coping and daily function (n = 31, 20%) and mental health outcomes (n = 29, 19%) of patients, families, and healthcare professionals. Participants described a need for coping and support (n = 107, 69%), connection and communication (n = 107, 69%), and awareness of state of well-being (n = 101, 65%). Eighty-seven approaches to mitigate impact of restricted visitation were identified, targeting families (n = 61, 70%), patients (n = 51, 59%), and healthcare professionals (n = 40, 46%).Conclusions: Patients, families, and healthcare professionals were impacted by restricted visitation polices in acute care settings during COVID-19. The consequences of this approach on patients and families are understudied and warrant evaluation of approaches to mitigate their impact. Future pandemic policy development should include the perspectives of patients, families, and healthcare professionals.Trial registration: The review was registered on PROSPERO (CRD42020221662) and a protocol peer-reviewed prior to data extraction.

Caregivers may promote the uptake of science into patient care and the practice of evidence-informed medicine. The purpose of this study was to determine whether caregiver-mediated (non-clinical caregiver-delivered) interventions are effective in improving patient, caregiver, provider, or health system outcomes. We searched the MEDLINE, Embase, PsycINFO, Cumulative Index of Nursing and Allied Health, and Scopus databases from inception to February 27, 2017. Interventions (with a comparison group) reporting on a quality improvement intervention mediated by a caregiver and directed to a patient, in all ages and patient-care settings, were selected for inclusion. A three-category framework was developed to characterize caregiver-mediated interventions: inform (e.g., provide knowledge), activate (e.g., prompt action), and collaborate (e.g., lead to interaction between caregivers and other groups [e.g., care providers]). Fifty-six studies met the inclusion criteria, and 64% were randomized controlled trials (RCTs). The most commonly assessed outcomes were patient- (n = 40) and caregiver-oriented (n = 33); few health system- (n = 10) and provider-oriented (n = 2) outcomes were reported. Patient outcomes (e.g., satisfaction) were most improved by caregiver-mediated interventions that provided condition and treatment education (e.g., symptom management information) and practical condition-management support (e.g., practicing medication protocol). Caregiver outcomes (e.g., stress-related/psychiatric outcomes) were most improved by interventions that activated caregiver roles (e.g., monitoring blood glucose) and provided information related to that action (e.g., why and how to monitor). The risk of bias was generally high, and the overall quality of the evidence was low-moderate, based on Grading of Recommendations Assessment Development and Evaluation ratings. There is a large body of research, including many RCTs, to support the use of caregiver-mediated interventions that inform and activate caregivers to improve patient and caregiver outcomes. Select caregiver-mediated interventions improve patient (inform-activate) and caregiver (inform-activate-collaborate) outcomes and should be considered by all researchers implementing patient- and family-oriented research. PROSPERO, CRD42016052509 .