scholarly journals Developing a practical suicide risk prediction model for targeting high‐risk patients in the Veterans health Administration

2017 ◽  
Vol 26 (3) ◽  
Author(s):  
Ronald C. Kessler ◽  
Irving Hwang ◽  
Claire A. Hoffmire ◽  
John F. McCarthy ◽  
Maria V. Petukhova ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Risk Prediction ◽  
Suicide Risk ◽  
Veterans Health Administration ◽  
Risk Prediction Model ◽  
Veterans Health ◽  
Health Administration ◽  
High Risk Patients ◽  
Risk Patients

The Management of Newly-Diagnosed Non-muscle Invasive Bladder Cancer in Veterans Integrated Services Network 02 of the Veterans Health Administration

2019 ◽  
Author(s):  
Joseph M Caputo ◽  
George Moran ◽  
Benjamin Muller ◽  
Alison T Keller ◽  
Gen Li ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Veterans Health Administration ◽  
Veterans Health ◽  
Newly Diagnosed ◽  
Health Administration ◽  
Muscle Invasive Bladder Cancer ◽  
High Risk Patients ◽  
Risk Patients ◽  
Muscle Invasive

Abstract Introduction Over 1,500 bladder cancers were diagnosed among US Veterans in 2010, the majority of which were non-muscle invasive bladder cancer (NMIBC). Little is known about NMIBC treatment within the Veterans Health Administration. The objective of the study was to assess the quality of care for Veterans with newly-diagnosed NMIBC within Veterans Integrated Service Network (VISN) 02. Materials and Methods We used ICD-9 and ICD-10 codes to identify patients with newly-diagnosed bladder cancer from 1/2016–8/2017. We risk-stratified the patients into low, intermediate, and high-risk based on the 2016 American Urological Association Guidelines on NMIBC. Our primary objectives were percentages of transurethral resection of bladder tumors (TURBTs) with detrusor, repeat TURBT in high-risk and T1 disease, high-risk NMIBC treated with induction intravesical therapy (IVT), and responders treated with maintenance IVT. We performed logistic regression for association between distance to diagnosing hospital and receipt of induction IVT in high-risk patients. Results There were 121 newly-diagnosed NMIBC patients; 16% low-risk, 28% intermediate-risk, and 56% high-risk. Detrusor was present in 80% of all initial TURBTs and 84% of high-risk patients. Repeat TURBT was performed in 56% of high-risk NMIBC and 60% of T1. Induction IVT was given to 66% of high-risk patients and maintenance IVT was given to 59% of responders. On multivariate logistic regression, distance to medical center was not associated with receipt of induction IVT (OR = 0.99, 95% CI [0.97,1.01], p = 0.52). Conclusions We observed high rates of sampling of detrusor in the first TURBT specimen, utilization of repeat TURBT, and administration of induction and maintenance intravesical BCG for high-risk patients among a regional cohort of US Veterans with NMIBC. While not a comparative study, our findings suggest high quality NMIBC care in VA VISN 02.

scholarly journals A prospective study of acute kidney injury in the intensive care unit: development and validation of a risk prediction model

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Qi Wang ◽  
Yi Tang ◽  
Jiaojiao Zhou ◽  
Wei Qin
Keyword(s):  
Chronic Kidney Disease ◽  
Acute Kidney Injury ◽  
Intensive Care ◽  
High Risk ◽  
Prediction Model ◽  
Risk Prediction ◽  
Validation Cohort ◽  
Kidney Injury ◽  
Risk Prediction Model ◽  
Risk Patients

Abstract Background Acute kidney injury (AKI) has high morbidity and mortality in intensive care units (ICU). It can also lead to chronic kidney disease (CKD), more costs and longer hospital stay. Early identification of AKI is important. Methods We conducted this monocenter prospective observational study at West China Hospital, Sichuan University, China. We recorded information of each patient in the ICU within 24 h after admission and updated every two days. Patients who reached the primary outcome were accepted into the AKI group. Of all patients, we randomly drew 70% as the development cohort and the remaining 30% as the validation cohort. Using binary logistic regression we got a risk prediction model of the development cohort. In the validation cohort, we validated its discrimination by the area under the receiver operator curve (AUROC) and calibration by a calibration curve. Results There were 656 patients in the development cohorts and 280 in the validation cohort. Independent predictors of AKI in the risk prediction model including hypertension, chronic kidney disease, acute pancreatitis, cardiac failure, shock, pH ≤ 7.30, CK > 1000 U/L, hypoproteinemia, nephrotoxin exposure, and male. In the validation cohort, the AUROC is 0.783 (95% CI 0.730–0.836) and the calibration curve shows good calibration of this prediction model. The optimal cut-off value to distinguish high-risk and low-risk patients is 4.5 points (sensitivity is 78.4%, specificity is 73.2% and Youden’s index is 0.516). Conclusions This risk prediction model can help to identify high-risk patients of AKI in ICU to prevent the development of AKI and treat it at the early stages. Trial registration TCTR, TCTR20170531001. Registered 30 May 2017, http://www.clinicaltrials.in.th/index.php?tp=regtrials&menu=trialsearch&smenu=fulltext&task=search&task2=view1&id=2573

An Intervention With Meaning

Crisis ◽  
2017 ◽  
Vol 38 (6) ◽  
pp. 376-383 ◽  
Author(s):  
Brooke A. Levandowski ◽  
Constance M. Cass ◽  
Stephanie N. Miller ◽  
Janet E. Kemp ◽  
Kenneth R. Conner
Keyword(s):  
High Risk ◽  
Qualitative Methodology ◽  
Veterans Health Administration ◽  
Veterans Health ◽  
Safety Planning ◽  
Health Administration ◽  
Suicide Method ◽  
Treatment Providers ◽  
Interactive Nature ◽  
Behavioral Health Treatment

Abstract. Background: The Veterans Health Administration (VHA) health-care system utilizes a multilevel suicide prevention intervention that features the use of standardized safety plans with veterans considered to be at high risk for suicide. Aims: Little is known about clinician perceptions on the value of safety planning with veterans at high risk for suicide. Method: Audio-recorded interviews with 29 VHA behavioral health treatment providers in a southeastern city were transcribed and analyzed using qualitative methodology. Results: Clinical providers consider safety planning feasible, acceptable, and valuable to veterans at high risk for suicide owing to the collaborative and interactive nature of the intervention. Providers identified the types of veterans who easily engaged in safety planning and those who may experience more difficulty with the process. Conclusion: Additional research with VHA providers in other locations and with veteran consumers is needed.

Association between acute psychiatric bed availability in the Veterans Health Administration and veteran suicide risk: a retrospective cohort study

2021 ◽  
pp. bmjqs-2020-012975
Author(s):  
Peter J Kaboli ◽  
Matthew R Augustine ◽  
Bjarni Haraldsson ◽  
Nicholas M Mohr ◽  
M Bryant Howren ◽  
...  
Keyword(s):  
Mental Health ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Suicide Risk ◽  
Veterans Health Administration ◽  
Veterans Health ◽  
Health Administration ◽  
Bed Occupancy ◽  
Increased Risk

BackgroundVeteran suicides have increased despite mental health investments by the Veterans Health Administration (VHA).ObjectiveTo examine relationships between suicide and acute inpatient psychiatric bed occupancy and other community, hospital and patient factors.MethodsRetrospective cohort study using administrative and publicly available data for contextual community factors. The study sample included all veterans enrolled in VHA primary care in 2011–2016 associated with 111 VHA hospitals with acute inpatient psychiatric units. Acute psychiatric bed occupancy, as a measure of access to care, was the main exposure of interest and was categorised by quarter as per cent occupied using thresholds of ≤85%, 85.1%–90%, 90.1%–95% and >95%. Hospital-level analyses were conducted using generalised linear mixed models with random intercepts for hospital, modelling number of suicides by quarter with a negative binomial distribution.ResultsFrom 2011 to 2016, the national incidence of suicide among enrolled veterans increased from 39.7 to 41.6 per 100 000 person-years. VHA psychiatric bed occupancy decreased from a mean of 68.2% (IQR 56.5%–82.2%) to 65.4% (IQR 53.9%–79.9%). VHA hospitals with the highest occupancy (>95%) in a quarter compared with ≤85% had an adjusted incident rate ratio (IRR) for suicide of 1.10 (95% CI 1.01 to 1.19); no increased risk was observed for 85.1%–90% (IRR 0.96; 95% CI 0.89 to 1.03) or 90.1%–95% (IRR 0.96; 95% CI 0.89 to 1.04) compared with ≤85% occupancy. Of hospital and community variables, suicide risk was not associated with number of VHA or non-VHA psychiatric beds or amount spent on community mental health. Suicide risk increased by age categories, seasons, geographic regions and over time.ConclusionsHigh VHA hospital occupancy (>95%) was associated with a 10% increased suicide risk for veterans whereas absolute number of beds was not, suggesting occupancy is an important access measure. Future work should clarify optimal bed occupancy to meet acute psychiatric needs and ensure adequate bed distribution.

Suicide Mortality Among Veterans Health Administration Care Recipients With Suicide Risk Record Flags

2021 ◽  
pp. appi.ps.2020007
Author(s):  
Tyler C. Hein ◽  
Talya Peltzman ◽  
Juliana Hallows ◽  
Nicole Theriot ◽  
John F. McCarthy
Keyword(s):  
Suicide Risk ◽  
Veterans Health Administration ◽  
Suicide Mortality ◽  
Veterans Health ◽  
Health Administration ◽  
Care Recipients

scholarly journals Development and Validation of a Clostridium difficile Infection Risk Prediction Model

2011 ◽  
Vol 32 (4) ◽  
pp. 360-366 ◽  
Author(s):  
Erik R. Dubberke ◽  
Yan Yan ◽  
Kimberly A. Reske ◽  
Anne M. Butler ◽  
Joshua Doherty ◽  
...  
Keyword(s):  
High Risk ◽  
Clostridium Difficile ◽  
Prediction Model ◽  
Risk Prediction ◽  
Predictive Accuracy ◽  
Medical Center ◽  
Tertiary Care ◽  
Risk Prediction Model ◽  
Brier Score ◽  
Tertiary Care Medical Center

Objective.To develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease.Design and Setting.Retrospective cohort study in a tertiary care medical center.Patients.Patients admitted to the hospital for at least 48 hours during the calendar year 2003.Methods.Data were collected electronically from the hospital's Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients' risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic curve was calculated to evaluate potential risk cutoffs.Results.A total of 35,350 admitted patients, including 329 with CDI, were studied. Variables in the risk prediction model were age, CDI pressure, times admitted to hospital in the previous 60 days, modified Acute Physiology Score, days of treatment with high-risk antibiotics, whether albumin level was low, admission to an intensive care unit, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index, 0.88; Brier score, 0.009).Conclusions.The CDI risk prediction model performed well. Further study is needed to determine whether it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs.

scholarly journals The Impact Prediction Models of Neoplasia for Lung Nodules in High-Risk Patients

2020 ◽  
Vol 3 (3) ◽  
pp. 138-146
Author(s):  
Camilla Matos Pedreira ◽  
José Alves Barros Filho ◽  
Carolina Pereira ◽  
Thamine Lessa Andrade ◽  
Ricardo Mingarini Terra ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Prediction Models ◽  
Lung Nodule ◽  
Smoking History ◽  
Predictive Values ◽  
Impact Prediction ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact

Objectives: This study aims to evaluate the impact of using three predictive models of lung nodule malignancy in a population of patients at high-risk for neoplasia according to previous analysis by physicians, as well as evaluate the clinical and radiological malignancy-predictors of the images. Material and Methods: This is a retrospective cohort study, with 135 patients, undergone surgical in the period from 01/07/2013 to 10/05/2016. The study included nodules with dimensions between 5mm and 30mm, excluding multiple nodules, alveolar consolidation, pleural effusion, and lymph node enlargement. The main variables analyzed were age, sex, smoking history, extrathoracic cancer, diameter, location, and presence of spiculation. The calculation of the area under the ROC curve assessed the accuracy of each prediction model. Results: The study analyzed 135 individuals, of which 96 (71.1%) had malignant nodules. The areas under the ROC curves for each prediction model were: Swensen 0.657; Brock 0.662; and Herder 0.633. The models Swensen, Brock, and Herder presented positive predictive values in high-risk patients, corresponding to 83.3%, 81.8%, and 82.9%, respectively. Patients with the intermediate and low-risk presented a high malignant nodule rate, ranging from 69.3-72.5% and 42.8-52.6%, respectively. Conclusion: None of the three quantitative models analyzed in this study was considered satisfactory (AUC> 0.7) and should be used with caution after specialized evaluation to avoid underestimation of the risk of neoplasia. The pretest calculations might not contemplate other factors than those predicted in the regressions, that could present a role in the clinical decision of resection.

Sign in / Sign up

Export Citation Format

Share Document