Do Psychiatric Comorbidities Influence Inpatient Death, Adverse Events, and Discharge After Lower Extremity Fractures?

Menendez, Mariano E.; Neuhaus, Valentin; Bot, Arjan G.J.; Vrahas, Mark; Ring, David

doi:10.1007/s11999-013-3138-9

Cited by 40 publications

(42 citation statements)

References 40 publications

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“…A diagnosis of dementia appears to condemn hospitalized patients to be discharged to another medical facility rather than home [33,34]. In a previous large cross-sectional survey in Japan, patients with dementia were more likely to be discharged from an intermediate care facility to places other than home [35].…”

Section: Discussionmentioning

confidence: 99%

Association between dementia and discharge status in patients hospitalized with pneumonia

Yasunaga

Sasabuchi

et al. 2017

BMC Pulm Med

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Background: Pneumonia is the most common cause of death in patients with dementia, but the outcomes of patients with dementia hospitalized with pneumonia are poorly understood. We sought to illuminate the association between dementia and in-hospital mortality and discharge status in patients hospitalized with pneumonia. Methods: We used the Diagnosis Procedure Combination database, a national inpatient database in Japan, to identify retrospectively patients aged ≥60 years admitted to hospital with pneumonia during the study period of May 1, 2010 to March 31, 2014. We recorded their sex, age, body mass index, severity of pneumonia and comorbidities (including dementia). The outcomes were in-hospital mortality and discharge home. Multivariable Cox regression analysis was performed to analyze factors influencing discharge home. Results: We identified 470,829 patients hospitalized with pneumonia; 45,031 were recorded as having dementia (9.6%). In-hospital mortality was 13.1% and 13.4% in patients with and without dementia, respectively (P = 0.63). The proportions of patients discharged home were 52.9% and 71.3% in patients with and without dementia, respectively (P < 0.001). The adjusted hazard ratio for discharge home for patients with dementia was 0.68 (95% confidence interval, 0.67-0.69; P < 0.001). Conclusions: In-hospital mortality from pneumonia did not differ significantly between patients with and without dementia; however, those with dementia were less likely to be discharged home.

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Section: Discussionmentioning

confidence: 99%

Association between dementia and discharge status in patients hospitalized with pneumonia

Yasunaga

Sasabuchi

et al. 2017

BMC Pulm Med

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“…First, the NHDS dataset is based on billing data from ICD-9-CM codes, and such a coding system may not fully capture the patient population of interest [1]. In particular, it has been suggested that administrative databases tend to underreport chronic medical conditions that are considered less acute in the perioperative orthopaedic surgery setting [16,31,33,34,39]. Second, the possibility of errors in coding of the diagnoses and procedures cannot be avoided [7]; however, misclassification mistakes distribute evenly in large-scale studies [53].…”

Section: Discussionmentioning

confidence: 99%

“…Patient demographic information, hospital characteristics, and inpatient outcomes such as discharge disposition and hospital length of stay also were collected. Recognizing its utility to answer valuable clinical questions, the NHDS has been used extensively to analyze data associated with a wide range of diagnoses and procedures across different medical specialties [3,25,33,34,38,44,48]. Because of prior adequate data deidentification, our study was exempt from institutional review board approval.…”

Section: Methodsmentioning

confidence: 99%

“…Our secondary outcome variables, in-hospital adverse events and nonroutine discharge, were analyzed in an analogous fashion to in-hospital mortality. In-hospital adverse events were defined by ICD-9 codes (Appendix), following a coding approach used in other studies [34,38]. A nonroutine discharge was defined as discharge to a skilled nursing facility or rehabilitation center.…”

Section: Methodsmentioning

confidence: 99%

“…Large administrative inpatient databases have been used to assess the effect of baseline comorbidity status on surgical care outcomes targeted in pay-for-performance initiatives such as mortality, morbidity, and discharge disposition [14,22,[32][33][34][37][38][39]. The Charlson Comorbidity Index [5] encompasses 19 medical conditions and is the most widely used comorbidity risk adjustment model in orthopaedic surgery.…”

Section: Introductionmentioning

confidence: 99%

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The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Menendez

Neuhaus

Dijk

et al. 2014

Clinical Orthopaedics &Amp; Related Research

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442

292

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Background Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are wellknown risk adjustment models, yet the optimal score for orthopaedic patients remains unclear. Questions/purposes We determined whether there was a difference in the accuracy of the Charlson and Elixhauser comorbidity-based measures in predicting (1) in-hospital mortality after major orthopaedic surgery, (2) in-hospital adverse events, and (3) nonroutine discharge. Methods Among an estimated 14,007,813 patients undergoing orthopaedic surgery identified in the National Hospital Discharge Survey (1990Survey ( -2007, 0.80% died in the hospital. The association of each Charlson comorbidity measure and Elixhauser comorbidity measure with mortality was assessed in bivariate analysis. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and one of the two comorbidity-based measures (and age, sex, and year of surgery) as independent variables. A base model that included only age, sex, and year of surgery also was evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC). The AUC quantifies the ability of our models to assign a high probability of mortality to patients who die. Values range from 0.50 to 1.0, with 0.50 indicating no ability to discriminate and 1.0 indicating perfect discrimination. Results Elixhauser comorbidity adjustment provided a better prediction of in-hospital case mortality (AUC, 0.86; 95% CI, 0.86-0.86) compared with the Charlson model (AUC, 0.83; 95% CI, and to the base model with no comorbidities (AUC, 0.81; 95% CI, 0.81-0.81). In terms of relative improvement in predictive performance, the Elixhauser measure performed 60% better than the Charlson score in predicting mortality. The Elixhauser model discriminated inpatient morbidity better than the Charlson measure, but the discriminative ability of the model was poor and the difference in the absolute improvement in predictive power between the two models (AUC, 0.01) is of dubious clinical importance. Both comorbidity models exhibited the same degree of discrimination for estimating nonroutine discharge (AUC, 0.81; 95% CI, 0.81-0.82 for both models). Conclusions Provider-specific outcomes, particularly inpatient mortality, may be evaluated differently depending on the comorbidity risk adjustment model selected. Future research assessing and comparing the performance of the

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Length of hospital stay and dementia: A systematic review of observational studies

Möllers

Stocker

Wei

et al. 2018

Int J Geriat Psychiatry

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Objective Hospitalizations of people with dementia (PWD) are often accompanied by complications or functional loss and can lead to adverse outcomes. Unsystematic findings suggest an influence of comorbidities on the extent of differences in the length of hospital stay (LOS). This systematic review aimed to identify and evaluate all studies reporting LOS in PWD as compared to PwoD in general hospitals. Methods A systematic review of observational studies using PubMed and ISI Web of Knowledge. Inclusion criteria comprised original studies written in English or German, assessment of diagnosis of dementia, measurement of LOS, and comparison of people with and without dementia. Results Fifty‐two of 60 studies reported a longer hospitalization time for PWD compared to PwoD. The extent of the difference in LOS varied between and within countries as well as by type of primary morbidity (eg, injuries, cardiovascular diseases). The range of the LOS difference for studies without restriction to a primary morbidity was −2 to +22 days after matching or adjustment for a variable number and selection of potentially relevant covariates. For studies with injuries/fractures/medical procedures and infectious/vascular disease as the primary morbidity, the range was −2.9 to +12.4 and −11.2 to +21.8 days, respectively. Conclusions The majority of studies reported a longer hospitalization of PWD compared to PwoD. Length of hospital stay seems to be influenced by a variety of medical, social, organizational factors, including reasons for hospital admission, whose role should be explored in detail in further research.

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Do Psychiatric Comorbidities Influence Inpatient Death, Adverse Events, and Discharge After Lower Extremity Fractures?

Cited by 40 publications

References 40 publications

Association between dementia and discharge status in patients hospitalized with pneumonia

Association between dementia and discharge status in patients hospitalized with pneumonia

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Length of hospital stay and dementia: A systematic review of observational studies

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