scholarly journals The HOSPITAL score as a predictor of 30 day readmission in a retrospective study at a university affiliated community hospital

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2441 ◽  
Author(s):  
Robert Robinson
Keyword(s):  
Retrospective Study ◽  
High Risk ◽  
Hospital Readmission ◽  
Goodness Of Fit ◽  
Medical Center ◽  
Hospital Readmissions ◽  
Assessment Tools ◽  
Brier Score ◽  
Goodness Of Fit Test ◽  
Discriminatory Ability

IntroductionHospital readmissions are common, expensive, and a key target of the Medicare Value Based Purchasing (VBP) program. Risk assessment tools have been developed to identify patients at high risk of hospital readmission so they can be targeted for interventions aimed at reducing the rate of readmission. One such tool is the HOSPITAL score that uses seven readily available clinical variables to predict the risk of readmission within 30 days of discharge. The HOSPITAL score has been internationally validated in large academic medical centers. This study aims to determine if the HOSPITAL score is similarly useful in a moderate sized university affiliated hospital in the midwestern United States.Materials and MethodsAll adult medical patients discharged from the SIU-SOM Hospitalist service from Memorial Medical Center (MMC) from October 15, 2015 to March 16, 2016, were studied retrospectively to determine if the HOSPITAL score was a significant predictor of hospital readmission within 30 days.ResultsDuring the study period, 998 discharges were recorded for the hospitalist service. The analysis includes data for the 931 discharges. Patients who died during the hospital stay, were transferred to another hospital, or left against medical advice were excluded. Of these patients, 109 (12%) were readmitted to the same hospital within 30 days. The patients who were readmitted were more likely to have a length of stay greater than or equal to 5 days (55% vs. 41%,p= 0.005) and were more likely to have been admitted more than once to the hospital within the last year (100% vs. 49%,p< 0.001). A receiver operating characteristic evaluation of the HOSPITAL score for this patient population shows a C statistic of 0.77 (95% CI [0.73–0.81]), indicating good discrimination for hospital readmission. The Brier score for the HOSPITAL score in this setting was 0.10, indicating good overall performance. The Hosmer–Lemeshow goodness of fit test shows aχ2value of 1.63 with apvalue of 0.20.DiscussionThis single center retrospective study indicates that the HOSPITAL score has good discriminatory ability to predict hospital readmissions within 30 days for a medical hospitalist service at a university-affiliated hospital. This data for all causes of hospital readmission is comparable to the discriminatory ability of the HOSPITAL score in the international validation study (C statistics of 0.72 vs. 0.77) conducted at considerably larger hospitals (975 average beds vs. 507 at MMC) for potentially avoidable hospital readmissions.ConclusionsThe internationally validated HOSPITAL score may be a useful tool in moderate sized community hospitals to identify patients at high risk of hospital readmission within 30 days. This easy to use scoring system using readily available data can be used as part of interventional strategies to reduce the rate of hospital readmission.

scholarly journals The HOSPITAL score as a predictor of 30 day readmission in a university affiliated community hospital

2016 ◽  
Author(s):  
Robert Robinson
Keyword(s):  
High Risk ◽  
Hospital Readmission ◽  
Medical Center ◽  
Hospital Readmissions ◽  
Assessment Tools ◽  
Medical Patients ◽  
Value Based Purchasing ◽  
Discriminatory Ability ◽  
Kaplan Meier ◽  
Increased Risk

Introduction Hospital readmissions are common, expensive, and a key target of the Medicare Value Based Purchasing (VBP) program. Risk assessment tools have been developed to identify patients at high risk of hospital readmission so they can be targeted for interventions aimed at reducing the rate of readmission. One such tool is the HOSPITAL score that uses 7 readily available clinical variables to predict the risk of readmission within 30 days of discharge. The HOSPITAL score has been internationally validated in large academic medical centers. This study aims to determine if the HOSPITAL score is similarly useful in a moderate sized university affiliated hospital in the midwestern United States. Materials and Methods All adult medical patients discharged from the SIU-SOM Hospitalist service from Memorial Medical Center from October 15, 2015 to March 16, 2016, were studied retrospectively to determine if the HOSPITAL score was a significant predictor of hospital readmission within 30 days. Results During the study period, 998 discharges were recorded for the SIU-SOM Hospitalist service. The analysis includes data for the 963 patients who were discharged alive. Of these patients, 118 (12%) were readmitted to the same hospital within 30 days. The patients who were readmitted were less likely to have a length of stay greater than or equal to 5 days (45% vs. 59%, p = 0.003) but were more likely to have been admitted to the hospital within the last year. A receiver operating characteristic evaluation of the HOSPITAL score for this patient population shows a C statistic of 0.762 (95% CI 0.720 - 0.805), indicating good discrimination for hospital readmission. Kaplan-Meier analysis of 30-day readmission free survival showed a significant (p < 0.001) increase in the risk of readmission in patients with a HOSPITAL score of 5 or more. Discussion This single center retrospective study indicates that the HOSPITAL score has good discriminatory ability to predict hospital readmissions within 30 days for a medical hospitalist service a university-affiliated hospital. This data for all causes of hospital readmission is comparable to the discriminatory ability of the HOSPITAL score in the international validation study (C statistics of 0.72 vs. 0.762) conducted at considerably larger hospitals (975 average beds vs 507 at Memorial Medical Center) for potentially avoidable hospital readmissions. Higher risk patients, identified as having a HOSPITAL score of 5 or more, clearly show an increased risk of hospital readmission within 30 days. Conclusions The internationally validated HOSPITAL score may be a useful tool in moderate sized community hospitals to identify patients at high risk of hospital readmission within 30 days. This easy to use scoring system using readily available data can be used as part of interventional strategies to reduce the rate of hospital readmission.

scholarly journals The HOSPITAL score and LACE index as predictors of 30 day readmission in a retrospective study at a university-affiliated community hospital

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3137 ◽  
Author(s):  
Robert Robinson ◽  
Tamer Hudali
Keyword(s):  
Retrospective Study ◽  
High Risk ◽  
Hospital Readmission ◽  
Patient Population ◽  
Goodness Of Fit ◽  
Operating Characteristic ◽  
Brier Score ◽  
Goodness Of Fit Test ◽  
C Statistic ◽  
Overall Performance

IntroductionHospital readmissions are common, expensive, and a key target of the Medicare Value Based Purchasing (VBP) program. Validated risk assessment tools such as the HOSPITAL score and LACE index have been developed to identify patients at high risk of hospital readmission so they can be targeted for interventions aimed at reducing the rate of readmission. This study aims to evaluate the utility of HOSPITAL score and LACE index for predicting hospital readmission within 30 days in a moderate-sized university affiliated hospital in the midwestern United States.Materials and MethodsAll adult medical patients who underwent one or more ICD-10 defined procedures discharged from the SIU-SOM Hospitalist service from Memorial Medical Center (MMC) from October 15, 2015 to March 16, 2016, were studied retrospectively to determine if the HOSPITAL score and LACE index were a significant predictors of hospital readmission within 30 days.ResultsDuring the study period, 463 discharges were recorded for the hospitalist service. The analysis includes data for the 432 discharges. Patients who died during the hospital stay, were transferred to another hospital, or left against medical advice were excluded. Of these patients, 35 (8%) were readmitted to the same hospital within 30 days. A receiver operating characteristic evaluation of the HOSPITAL score for this patient population shows a C statistic of 0.75 (95% CI [0.67–0.83]), indicating good discrimination for hospital readmission. The Brier score for the HOSPITAL score in this setting was 0.069, indicating good overall performance. The Hosmer–Lemeshow goodness of fit test shows a χ2value of 3.71 with apvalue of 0.59. A receiver operating characteristic evaluation of the LACE index for this patient population shows a C statistic of 0.58 (95% CI [0.48–0.68]), indicating poor discrimination for hospital readmission. The Brier score for the LACE index in this setting was 0.082, indicating good overall performance. The Hosmer–Lemeshow goodness of fit test shows a χ2value of 4.97 with apvalue of 0.66.DiscussionThis single center retrospective study indicates that the HOSPITAL score has superior discriminatory ability when compared to the LACE index as a predictor of hospital readmission within 30 days at a medium-sized university-affiliated teaching hospital.ConclusionsThe internationally validated HOSPITAL score may be superior to the LACE index in moderate-sized community hospitals to identify patients at high risk of hospital readmission within 30 days.

scholarly journals The HOSPITAL score as a predictor of 30 day readmission in a university affiliated community hospital

2016 ◽  
Author(s):  
Robert Robinson
Keyword(s):  
High Risk ◽  
Hospital Readmission ◽  
Medical Center ◽  
Hospital Readmissions ◽  
Assessment Tools ◽  
Medical Patients ◽  
Value Based Purchasing ◽  
Discriminatory Ability ◽  
Kaplan Meier ◽  
Increased Risk

Introduction Hospital readmissions are common, expensive, and a key target of the Medicare Value Based Purchasing (VBP) program. Risk assessment tools have been developed to identify patients at high risk of hospital readmission so they can be targeted for interventions aimed at reducing the rate of readmission. One such tool is the HOSPITAL score that uses 7 readily available clinical variables to predict the risk of readmission within 30 days of discharge. The HOSPITAL score has been internationally validated in large academic medical centers. This study aims to determine if the HOSPITAL score is similarly useful in a moderate sized university affiliated hospital in the midwestern United States. Materials and Methods All adult medical patients discharged from the SIU-SOM Hospitalist service from Memorial Medical Center from October 15, 2015 to March 16, 2016, were studied retrospectively to determine if the HOSPITAL score was a significant predictor of hospital readmission within 30 days. Results During the study period, 998 discharges were recorded for the SIU-SOM Hospitalist service. The analysis includes data for the 963 patients who were discharged alive. Of these patients, 118 (12%) were readmitted to the same hospital within 30 days. The patients who were readmitted were less likely to have a length of stay greater than or equal to 5 days (45% vs. 59%, p = 0.003) but were more likely to have been admitted to the hospital within the last year. A receiver operating characteristic evaluation of the HOSPITAL score for this patient population shows a C statistic of 0.762 (95% CI 0.720 - 0.805), indicating good discrimination for hospital readmission. Kaplan-Meier analysis of 30-day readmission free survival showed a significant (p < 0.001) increase in the risk of readmission in patients with a HOSPITAL score of 5 or more. Discussion This single center retrospective study indicates that the HOSPITAL score has good discriminatory ability to predict hospital readmissions within 30 days for a medical hospitalist service a university-affiliated hospital. This data for all causes of hospital readmission is comparable to the discriminatory ability of the HOSPITAL score in the international validation study (C statistics of 0.72 vs. 0.762) conducted at considerably larger hospitals (975 average beds vs 507 at Memorial Medical Center) for potentially avoidable hospital readmissions. Higher risk patients, identified as having a HOSPITAL score of 5 or more, clearly show an increased risk of hospital readmission within 30 days. Conclusions The internationally validated HOSPITAL score may be a useful tool in moderate sized community hospitals to identify patients at high risk of hospital readmission within 30 days. This easy to use scoring system using readily available data can be used as part of interventional strategies to reduce the rate of hospital readmission.

scholarly journals The HOSPITAL score and LACE index for predicting the risk of hospital readmission do not show sex discrimination in a retrospective study

2020 ◽  
Author(s):  
Robert Robinson
Keyword(s):  
Decision Making ◽  
Retrospective Study ◽  
Risk Prediction ◽  
Hospital Readmission ◽  
Medical Center ◽  
Hospital Readmissions ◽  
Sex Discrimination ◽  
Medical Patients ◽  
Rapid Improvement ◽  
Prediction Tools

AbstractIntroductionThe perceived absence of human implicit and explicit biases, scalability, and the potential for rapid improvement with algorithmic decision-making systems make compelling arguments for the widespread use of this technology. Unfortunately, real-world performance of some algorithmic decision-making systems demonstrates the reinforcement of discriminatory human biases in a way that is hidden from the human user. This study aims to retrospectively investigate if the widely used HOSPITAL score and LACE index used to predict hospital readmissions exhibit bias on the basis of sex.Materials and MethodsAll adult medical patients discharged from the SIU-School of Medicine (SIU-SOM) Hospitalist service from Memorial Medical Center from January 1, 2015, to January 1, 2017, were studied retrospectively to determine if patient sex had an influence on the ability of the HOSPTIAL score and LACE index to predict the likelihood of any cause hospital readmission within 30 days. Receiver operating characteristic (ROC) curves were constructed comparing risk prediction tool performance by sex by measuring the area under the curve (AUC).ResultsThe analysis includes data for the 1781 discharges for 1410 individual patients that met inclusion criteria. Of these discharges, 456 (27%) were readmitted to the same hospital within 30 days. The overall study population was 47% women, had an average age of 63 years and spent an average of 7.9 days in the hospital. Comparison of the performance of the LACE index in women and men showed no differences between AUCs (0.565 and 0.578, p = 0.613) and an ABROCA of 0.013. Sensitivity (67% and 70%), specificity (46% and 46%), PPV (30% and 31%), NPV (80% and 82%) and accuracy (51% and 52%) for the LACE index are very similar for women and men.Comparison of the performance of the HOSPITAL in women and men showed no differences between AUCs (0.56 and 0.58, p = 0.407) and an ABROCA of 0.008 indicating highly similar performance. Sensitivity (16% and 21%), specificity (96% and 95%), PPV (59% and 57%), NPV (77% and 78%) and accuracy (76% and 76%) for the HOSPITAL score are very similar for women and men.Discussion and ConclusionsThe performance of the HOSPITAL and LACE readmission risk prediction tools appears to have equivalent performance when used for women or men in this small, single-center, retrospective study. Further research is needed to explore the potential of bias and discrimination on risk prediction tools used in healthcare.

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.

Is the EuroSCORE II reliable in surgical mitral valve repair? A single-centre validation study

2020 ◽  
Author(s):  
Davide Carino ◽  
Paolo Denti ◽  
Guido Ascione ◽  
Benedetto Del Forno ◽  
Elisabetta Lapenna ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Mitral Valve Repair ◽  
Goodness Of Fit ◽  
Area Under The Curve ◽  
High Volume ◽  
Brier Score ◽  
Calibration Plot ◽  
Valve Repair ◽  
Goodness Of Fit Test ◽  
High Level

Abstract OBJECTIVES The EuroSCORE II is widely used to predict 30-day mortality in patients undergoing open and transcatheter cardiac surgery. The aim of this study is to evaluate the discriminatory ability of the EuroSCORE II in predicting 30-day mortality in a large cohort of patients undergoing surgical mitral valve repair in a high-volume centre. METHODS A retrospective review of our institutional database was carried on to find all patients who underwent mitral valve repair in our department from January 2012 to December 2019. Discrimination of the EuroSCORE II was assessed using receiver operating characteristic curves. The maximum Youden’s Index was employed to define the optimal cut-point. Calibration was assessed by generating calibration plot that visually compares the predicted mortality with the observed mortality. Calibration was also tested with the Hosmer–Lemeshow goodness-of-fit test. Finally, the accuracy of the models was tested calculating the Brier score. RESULTS A total of 2645 patients were identified, and the median EuroSCORE II was 1.3% (0.6–2.0%). In patients with degenerative mitral regurgitation (MR), the EuroSCORE II showed low discrimination (area under the curve 0.68), low accuracy (Brier score 0.27) and low calibration with overestimation of the 30-day mortality. In patients with secondary MR, the EuroSCORE II showed a good overall performance estimating the 30-day mortality with good discrimination (area under the curve 0.88), good accuracy (Brier score 0.003) and good calibration. CONCLUSIONS In patients with degenerative MR operated on in a high-volume centre with a high level of expertise in mitral valve repair, the EuroSCORE II significantly overestimates the 30-day mortality.

scholarly journals Rates and Types of Medication-Related Problems in Patients Rehospitalized Within 30 Days of Discharge From a Community Hospital

2019 ◽  
Vol 36 (2) ◽  
pp. 47-53
Author(s):  
Julie B. Cooper ◽  
Elizabeth Jeter ◽  
Cory John Sessoms
Keyword(s):  
Internal Medicine ◽  
Hospital Readmission ◽  
Adverse Drug Events ◽  
Community Hospital ◽  
Medical Center ◽  
Hospital Readmissions ◽  
Readmission Rates ◽  
General Internal ◽  
Hospital Readmission Rates ◽  
Context Specific

Background: Impact of medication-related problems (MRPs) on persistently high hospital readmission rates are not well described. Objective: The purpose of this study was to determine the rate and type of MRPs attributed to rehospitalization within 30 days of discharge from a general internal medicine hospitalists’ service at a nonacademic medical center. Methods: A retrospective cohort study was conducted evaluating consecutive patients readmitted within 30-days after discharge to home from an internal medicine hospitalist service. Readmissions attributed to MRPs in physician documentation were systematically classified as indication, effectiveness, adverse drug reaction, or nonadherence problems and evaluated for possible preventability. Descriptive statistics were used to describe the rate and type of MRP. Results: Evaluation of consecutive 30-day readmissions (n = 203) to a nonteaching community hospital identified 50.2% of admissions attributed to MRPs. MRPs (n = 102) were categorized as problems of indication (34.3%), efficacy (19.6%), adverse drug events (18.6%), and nonadherence (27.5%). One third of 30-day readmissions in this cohort were attributed to potentially preventable MRPs. Conclusion: MRPs are frequently implicated in 30-day hospital readmissions in a nonteaching community hospital representing an opportunity for context-specific improvements.

84 Development of a Risk Prediction Model and Comparison with Clinical Severity Scores in Burn Patients

2020 ◽  
Vol 41 (Supplement_1) ◽  
pp. S54-S55
Author(s):  
Dohern Kym
Keyword(s):  
Prediction Model ◽  
Goodness Of Fit ◽  
Scoring Systems ◽  
Clinical Severity ◽  
Brier Score ◽  
P Value ◽  
Burn Patients ◽  
Goodness Of Fit Test ◽  
Prediction Of Mortality ◽  
Severity Scores

Abstract Introduction The purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients. Methods This study included 2009 patients aged more than 18 years who were admitted to the intensive care unit (ICU) within 24 hours after a burn. We divided the patients into two groups; those admitted from January 2007 to December 2013 were included in the derivation group and those admitted from January 2014 to September 2017 were included in the validation group. Shrinkage methods with 10-folds cross-validation were performed to identify variables and limit overfitting of the model. The discrimination was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve. The Brier score, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also calculated. The calibration was analyzed using the Hosmer-Lemeshow goodness-of-fit test (HL test). The clinical usefulness was evaluated using a decision-curve analysis. Results The new prediction model showed good calibration with the HL test (χ2=8.785, p=0.361); the highest AUC and the lowest Brier score were 0.943 and 0.068, respectively. The NRI and IDI were 0.124 (p-value = 0.003) and 0.079 (p-value &lt; 0.001) when compared with FLAMES, respectively. Conclusions This model reflects the current risk factors of mortality among adult burn patients. Furthermore, it was a highly discriminatory and well-calibrated model for the prediction of mortality in this cohort. Applicability of Research to Practice There are many severity scoring systems widely used in the ICU to predict outcomes and characterize the severity of the disease. All of these scoring systems have been developed for the mixed population in the ICU. Their accuracy among subgroups, such as burn patients, is questionable and therefore, burn-specific scoring systems are required for accurate prediction.

scholarly journals Thirty-day medical and surgical readmission following prenatal versus postnatal myelomeningocele repair

2019 ◽  
Vol 47 (4) ◽  
pp. E14 ◽  
Author(s):  
Michael Cools ◽  
Weston Northam ◽  
William Goodnight ◽  
Graham Mulvaney ◽  
Scott Elton ◽  
...  
Keyword(s):  
Hospital Readmission ◽  
Neonatal Intensive Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospital Readmissions ◽  
Lengths Of Stay ◽  
Surgery Patient ◽  
Csf Diversion ◽  
Surgery Rates ◽  
Repair Group

OBJECTIVEHospital readmission is an important quality metric that has not been evaluated in prenatal versus postnatal myelomeningocele (MMC) repair. This study compares hospital readmission outcomes between these two groups as well as their etiologies.METHODSThe medical records of patients who had undergone MMC repair in the period from 2011 to 2017 at a single academic medical center were retrospectively reviewed. Collected clinical data included surgery and defect details, neonatal intensive care unit (NICU) stay, and any readmissions or surgical procedures up to 1 year after surgery. Patient and defect characteristics, readmission outcomes at 30 and 60 days and 1 year after discharge from the NICU, and cerebrospinal fluid (CSF) diversion surgery rates were analyzed with the two-tailed t-test and/or k-sample test on the equality of medians.RESULTSA total of 24 prenatal and 34 postnatal MMC repairs were completed during the study period. Prenatally repaired patients were born more prematurely (p < 0.001) and with lower birth weights (p < 0.001), although the NICU stay was similar between the two groups (p = 0.59). Fewer prenatally repaired patients were readmitted at 30 days (p = 0.005), 90 days (p = 0.004), and 1 year (p = 0.007) than the postnatal repair group. Hydrocephalus was the most common readmission etiology, and 29% of prenatal repair patients required CSF diversion at 1 year versus 81% of the postnatal repair group (p < 0.01). Prenatal patients who required CSF diversion had a higher body weight (p = 0.02) and an older age (p = 0.01) at the time of CSF diversion surgery than the postnatal group.CONCLUSIONSPatients with prenatal MMC repair had fewer hospital readmissions at 30 days, 60 days, and 1 year than the postnatal repair group, despite similar NICU lengths of stay. The prenatal repair group had lower requirements for CSF diversion at 1 year and was older with greater body weights at the time of CSF diversion surgery, compared to those of the postnatal repair group. Future study of hospital quality metrics such as readmissions should be performed to better understand outcomes of these two procedures.

High Prevalence of Visual Midline Shift Syndrome in TBI: A Retrospective Study

2016 ◽  
pp. 176-182
Keyword(s):  
Retrospective Study ◽  
Goodness Of Fit ◽  
Common Finding ◽  
P Value ◽  
Midline Shift ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Group 13 ◽  
History Of ◽  
Chi Square Analysis

Background: Visual Midline Shift Syndrome (VMSS) is a common finding in patients who have suffered traumatic brain injury (TBI) and stroke. Proper identification of VMSS will allow for best patient management since VMSS has previously been shown to be treatable with Yoked Prism lenses. The purpose of this study was to determine the prevalence of VMSS in a group of patients with TBI compared to patients with no report of TBI. Methods: A single-center retrospective study of 60 patients (30 TBI and 30 non-TBI) was conducted by chart review to determine the prevalence and direction of VMSS in each group. The presence of VMSS was determined by Visual Midline Shift Testing where the patient was instructed to follow a moving Wolff Wand fixation target performed at 3 gazes horizontally from both directions to detect any right or left VMSS and then the procedure was repeated vertically to detect any anterior or posterior VMSS. Results: A much higher prevalence of VMSS was found in the TBI group (93%) compared to the non-TBI group (13%). This difference was found to be statistically significant by Chi-Square analysis (p-value of <0.0011). The directions of VMSS in the TBI group, in order of prevalence were right (82%), anterior (64%), posterior (11%), and left (7%). Chi-Square Goodness-of-Fit Test showed the prevalence of right VMSS is statistically different than left VMSS or no right/left VMSS. (p-value < 0.001) and anterior VMSS is statistically different than posterior VMSS or no anterior/posterior VMSS (p-value = 0.002). Conclusion: The prevalence of VMSS is extremely high in patients with TBI. Our study also found a much higher prevalence of right or anterior VMSS. Our data supported VMSS testing to be performed on all patients with a history of TBI.

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