Depressive symptoms are associated with higher rates of readmission or mortality after medical hospitalization: A systematic review and meta-analysis.
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ABSTRACT:
SUBMITTER: Pederson JL
PROVIDER: S-EPMC5066695 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
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Depressive symptoms are associated with higher rates of readmission or mortality after medical hospitalization: A systematic review and meta-analysis.
Pederson Jenelle L JL Warkentin Lindsey M LM Majumdar Sumit R SR McAlister Finlay A FA
Journal of hospital medicine 20160129 5
Depressive symptoms during a medical hospitalization may be an overlooked prognostic factor for adverse events postdischarge. Our aim was to evaluate whether depressive symptoms predict 30-day readmission or death after medical hospitalization. We conducted a systematic review of studies that compared postdischarge outcomes by in-hospital depressive status. We assessed study quality and pooled published and unpublished data using random effects models. Overall, one-third of 6104 patients dischar ...[more]
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Project description:ObjectivesHigher education students in Germany are vulnerable to depressive symptoms. Despite ample evidence, no comprehensive review has recently been conducted. Thus, our systematic review and meta-analysis aims at describing the extent to which students are affected by depressive symptoms.MethodsWe searched three databases for articles reporting the prevalence rates of depressiveness among students in Germany published between 2002 and 2023. Pooled prevalence rates were calculated using random effects models, both for the overall sample and for subgroups categorized by gender, study setting, assessment instrument, and whether the study was conducted before or during the COVID-19 pandemic.ResultsThe search yielded 992 records. After screening, 60 articles remained for data extraction. About one out of five students (21.1%) exhibits depressive symptoms. Pooled prevalence rates differ between subgroups, with higher rates during the COVID-19 pandemic than before (30.6% versus 18.0%) and with females being more affected than their male counterparts (29.0% versus 23.1%).ConclusionThis review underlines the urgency with which the mental health of students should be addressed at the (higher educational) policy level.Clinical Trial Registration: PROPSPERO, Identifier CRD42022384066.
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Project description:Importance:Depression is highly prevalent among physicians and has been associated with increased risk of medical errors. However, questions regarding the magnitude and temporal direction of these associations remain open in recent literature. Objective:To provide summary relative risk (RR) estimates for the associations between physician depressive symptoms and medical errors. Data Sources:A systematic search of Embase, ERIC, PubMed, PsycINFO, Scopus, and Web of Science was performed from database inception to December 31, 2018. Study Selection:Peer-reviewed empirical studies that reported on a valid measure of physician depressive symptoms associated with perceived or observed medical errors were included. No language restrictions were applied. Data Extraction and Synthesis:Study characteristics and RR estimates were extracted from each article. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using subgroup meta-analysis and metaregression. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed. Main Outcomes and Measures:Relative risk estimates for the associations between physician depressive symptoms and medical errors. Results:In total, 11 studies involving 21 517 physicians were included. Data were extracted from 7 longitudinal studies (64%; with 5595 individuals) and 4 cross-sectional studies (36%; with 15 922 individuals). The overall RR for medical errors among physicians with a positive screening for depression was 1.95 (95% CI, 1.63-2.33), with high heterogeneity across the studies (χ2 = 49.91; P < .001; I2 = 82%; τ2 = 0.06). Among the variables assessed, study design explained the most heterogeneity across studies, with lower RR estimates associated with medical errors in longitudinal studies (RR, 1.62; 95% CI, 1.43-1.84; χ2 = 5.77; P = .33; I2 = 13%; τ2 < 0.01) and higher RR estimates in cross-sectional studies (RR, 2.51; 95% CI, 2.20-2.83; χ2 = 5.44; P = .14; I2 = 45%; τ2 < 0.01). Similar to the results for the meta-analysis of physician depressive symptoms associated with subsequent medical errors, the meta-analysis of 4 longitudinal studies (involving 4462 individuals) found that medical errors associated with subsequent depressive symptoms had a pooled RR of 1.67 (95% CI, 1.48-1.87; χ2 = 1.85; P = .60; I2 = 0%; τ2 = 0), suggesting that the association between physician depressive symptoms and medical errors is bidirectional. Conclusions and Relevance:Results of this study suggest that physicians with a positive screening for depressive symptoms are at higher risk for medical errors. Further research is needed to evaluate whether interventions to reduce physician depressive symptoms could play a role in mitigating medical errors and thus improving physician well-being and patient care.
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Project description:BACKGROUND: Many clinical trials examine a composite outcome of admission to hospital and death, or infer a relationship between hospital admission and survival benefit. This assumes concordance of the outcomes "hospital admission" and "death." However, whether the effects of a treatment on hospital admissions and readmissions correlate to its effect on serious outcomes such as death is unknown. We aimed to assess the correlation and concordance of effects of medical interventions on admission rates and mortality. METHODS: We searched the Cochrane Database of Systematic Reviews from its inception to January 2012 (issue 1, 2012) for systematic reviews of treatment comparisons that included meta-analyses for both admission and mortality outcomes. For each meta-analysis, we synthesized treatment effects on admissions and death, from respective randomized trials reporting those outcomes, using random-effects models. We then measured the concordance of directions of effect sizes and the correlation of summary estimates for the 2 outcomes. RESULTS: We identified 61 meta-analyses including 398 trials reporting mortality and 182 trials reporting admission rates; 125 trials reported both outcomes. In 27.9% of comparisons, the point estimates of treatment effects for the 2 outcomes were in opposite directions; in 8.2% of trials, the 95% confidence intervals did not overlap. We found no significant correlation between effect sizes for admission and death (Pearson r = 0.07, p = 0.6). Our results were similar when we limited our analysis to trials reporting both outcomes. INTERPRETATION: In this metaepidemiological study, admission and mortality outcomes did not correlate, and discordances occurred in about one-third of the treatment comparisons included in our analyses. Both outcomes convey useful information and should be reported separately, but extrapolating the benefits of admission to survival is unreliable and should be avoided.
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Project description:BackgroundHospital readmission rates are being used to evaluate performance. A survey of the present rates is needed before policies can be developed to decrease incidence of readmission. We address three questions: What is the present rate of 30-day readmission in orthopedics? How do factors such as orthopedic specialty, data source, patient insurance, and time of data collection affect the 30-day readmission rate? What are the causes and risk factors for 30-day readmissions?Methods/findingsA review was first registered with Prospero (CRD42014010293, 6/17/2014) and a meta-analysis was performed to assess the current 30-day readmission rate in orthopedics. Studies published after 2006 were retrieved, and 24 studies met the inclusion criteria. The 30-day readmission rate was extrapolated from each study along with the orthopedic subspecialty, data source, patient insurance, time of collection, patient demographics, and cause of readmission. A sensitivity analysis was completed on the stratified groups. The overall 30-day readmission rate across all orthopedics was 5.4 percent (95% confidence interval: 4.8,6.0). There was no significant difference between subspecialties. Studies that retrieved data from a multicenter registry had a lower 30-day readmission rate than those reporting data from a single hospital or a large national database. Patient populations that only included Medicare patients had a higher 30-day readmission rate than populations of all insurance. The 30-day readmission rate has decreased in the past ten years. Age, length of stay, discharge to skilled nursing facility, increased BMI, ASA score greater than 3, and Medicare/Medicaid insurance showed statistically positive correlation with increased 30-day readmissions in greater than 75 percent of studies. Surgical site complications accounted for 46 percent of 30-day readmissions.ConclusionsThis meta-analysis shows the present rate of 30-day readmissions in orthopedics. Demonstrable heterogeneity between studies underlines the importance of uniform collection and reporting of readmission rates for hospital evaluation and reimbursement.
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Project description:ImportanceMedical students are at high risk for depression and suicidal ideation. However, the prevalence estimates of these disorders vary between studies.ObjectiveTo estimate the prevalence of depression, depressive symptoms, and suicidal ideation in medical students.Data sources and study selectionSystematic search of EMBASE, ERIC, MEDLINE, psycARTICLES, and psycINFO without language restriction for studies on the prevalence of depression, depressive symptoms, or suicidal ideation in medical students published before September 17, 2016. Studies that were published in the peer-reviewed literature and used validated assessment methods were included.Data extraction and synthesisInformation on study characteristics; prevalence of depression or depressive symptoms and suicidal ideation; and whether students who screened positive for depression sought treatment was extracted independently by 3 investigators. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using stratified meta-analysis and meta-regression.Main outcomes and measuresPoint or period prevalence of depression, depressive symptoms, or suicidal ideation as assessed by validated questionnaire or structured interview.ResultsDepression or depressive symptom prevalence data were extracted from 167 cross-sectional studies (n = 116 628) and 16 longitudinal studies (n = 5728) from 43 countries. All but 1 study used self-report instruments. The overall pooled crude prevalence of depression or depressive symptoms was 27.2% (37 933/122 356 individuals; 95% CI, 24.7% to 29.9%, I2 = 98.9%). Summary prevalence estimates ranged across assessment modalities from 9.3% to 55.9%. Depressive symptom prevalence remained relatively constant over the period studied (baseline survey year range of 1982-2015; slope, 0.2% increase per year [95% CI, -0.2% to 0.7%]). In the 9 longitudinal studies that assessed depressive symptoms before and during medical school (n = 2432), the median absolute increase in symptoms was 13.5% (range, 0.6% to 35.3%). Prevalence estimates did not significantly differ between studies of only preclinical students and studies of only clinical students (23.7% [95% CI, 19.5% to 28.5%] vs 22.4% [95% CI, 17.6% to 28.2%]; P = .72). The percentage of medical students screening positive for depression who sought psychiatric treatment was 15.7% (110/954 individuals; 95% CI, 10.2% to 23.4%, I2 = 70.1%). Suicidal ideation prevalence data were extracted from 24 cross-sectional studies (n = 21 002) from 15 countries. All but 1 study used self-report instruments. The overall pooled crude prevalence of suicidal ideation was 11.1% (2043/21 002 individuals; 95% CI, 9.0% to 13.7%, I2 = 95.8%). Summary prevalence estimates ranged across assessment modalities from 7.4% to 24.2%.Conclusions and relevanceIn this systematic review, the summary estimate of the prevalence of depression or depressive symptoms among medical students was 27.2% and that of suicidal ideation was 11.1%. Further research is needed to identify strategies for preventing and treating these disorders in this population.
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Project description:Reduction in 30-day readmission rate after chronic obstructive pulmonary disease (COPD)-related hospitalization is a national objective. However, little is known about trends in readmission rates in recent years, particularly in priority populations defined by the Agency for Healthcare Research and Quality (AHRQ)(e.g., the elderly, women, racial/ethnic minorities, low-income and rural populations, and populations with chronic illnesses).We conducted a retrospective cohort study using data from the State Inpatient Database of eight geographically-dispersed US states (Arkansas, California, Florida, Iowa, Nebraska, New York, Utah, and Washington) from 2006 through 2012. We identified all COPD-related hospitalizations by patients ?40 years old. The primary outcome was any-cause readmission within 30 days of discharge from the index hospitalization for COPD.From 2006 to 2012, a total of 845,465 hospitalizations at risk for 30-day readmissions were identified. Overall, 30-day readmission rate for COPD-related hospitalization decreased modestly from 20.0% in 2006 to 19.2% in 2012, an 0.8% absolute decrease (OR 0.991, 95%CI 0.989-0.995, Ptrend<0.001). This modest decline remained statistically significant after adjusting for patient demographics and comorbidities (adjusted OR 0.981, 95%CI 0.977-0.984, Ptrend<0.001). Similar to the overall population, the readmission rate over the 7-year period remained persistently high in most of AHRQ-defined priority populations.Our observations provide a benchmark for future investigation of the impact of Hospital Readmissions Reduction Program on readmissions after COPD hospitalization. Our findings encourage researchers and policymakers to develop effective strategies aimed at reducing readmissions among patients with COPD in an already-stressed healthcare system.
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Project description:PurposeDischarge from an intensive care unit (ICU) out of hours is common. We undertook a systematic review and meta-analysis to explore the association between time of discharge and mortality/ICU readmission.MethodsWe searched Medline, Embase, Web of Knowledge, CINAHL, the Cochrane Library and OpenGrey to June 2017. We included studies reporting in-hospital mortality and/or ICU readmission rates by ICU discharge "out-of-hours" and "in-hours". Inclusion was limited to patients aged???16 years discharged alive from a non-specialist ICU to a lower level of hospital care. Studies restricted to specific diseases were excluded. We assessed study quality using the Newcastle Ottowa Scale. We extracted published data, summarising using a random-effects meta-analysis.ResultsOur searches identified 1961 studies. We included unadjusted data from 1,191,178 patients from 18 cohort studies (presenting data from 1994 to 2014). "Out of hours" had multiple definitions, beginning between 16:00 and 22:00 and ending between 05:59 and 09:00. Patients discharged out of hours had higher in-hospital mortality [relative risk (95% CI) 1.39 (1.24, 1.57) p?<?0.0001] and readmission rates [1·30 (1.19, 1.42), p?<?0.001] than patients discharged in hours. Heterogeneity was high (I2 90.1% for mortality and 90.2% for readmission), resulting from differences in effect size rather than the presence of an effect.ConclusionsOut-of-hours discharge from an ICU is strongly associated with both in-hospital death and ICU readmission. These effects persisted across all definitions of "out of hours" and across healthcare systems in different geographical locations. Whether these increases in mortality and readmission result from patient differences, differences in care, or a combination remains unclear.
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Project description:ImportanceThe Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown.ObjectiveTo examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge.Design, setting, and participantsRetrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014.ExposureThirty-day risk-adjusted readmission rate (RARR).Main outcomes and measuresThirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition.ResultsIn 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality.Conclusions and relevanceAmong Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.
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