Affiliation: University of Texas Southwestern Medical Center
- Measuring clinical information technology in the ICU setting: application in a quality improvement collaborativeRuben Amarasingham
Medicine Services, Parkland Health and Hospital System, Dallas, TX 75235, USA
J Am Med Inform Assoc 14:288-94. 2007....
- Clinical information technology capabilities in four U.S. hospitals: testing a new structural performance measureRuben Amarasingham
Robert Wood Johnson Clinical Scholars Program, Johns Hopkins University School of Medicine, Baltimore, MD 21205 2223, USA
Med Care 44:216-24. 2006..Few tools exist to quantify the performance of a hospital's information system from a user perspective...
- The quest for quality: perspectives from the safety netRon J Anderson
Parkland Health and Hospital System, Dallas, Texas, USA
Front Health Serv Manage 23:15-28. 2007..This article describes Parkland's approach to each component and takes a look at selected processes and outcomes...
- An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record dataRuben Amarasingham
Center for Clinical Innovation, Parkland Health and Hospital System, Dallas, TX 75235, USA
Med Care 48:981-8. 2010..A real-time electronic predictive model that identifies hospitalized heart failure (HF) patients at high risk for readmission or death may be valuable to clinicians and hospitals who care for these patients...
- Hospital characteristics associated with highly automated and usable clinical information systems in Texas, United StatesRuben Amarasingham
Department of Medicine, UT Southwestern Medical Center and Parkland Health and Hospital System, Dallas, USA
BMC Med Inform Decis Mak 8:39. 2008..This environment is not yet well defined. We examined whether specific hospital characteristics are associated with highly automated and usable clinical information systems...
- Clinical information technologies and inpatient outcomes: a multiple hospital studyRuben Amarasingham
Center for Knowledge Translation and Clinical Innovation, Parkland Health and Hospital System, 5201 Harry Hines Blvd, Dallas, TX 75235, USA
Arch Intern Med 169:108-14. 2009..Despite speculation that clinical information technologies will improve clinical and financial outcomes, few studies have examined this relationship in a large number of hospitals...
- A rapid admission protocol to reduce emergency department boarding timesRuben Amarasingham
Center for Clinical Innovation at Parkland Health and Hospital System UT Southwestern Medical Center, Dallas, Texas 75235, USA
Qual Saf Health Care 19:200-4. 2010..A rapid admission protocol was designed at our institution to reduce both EDBT and time to admission orders (EDTAO) for patients admitted to the internal medicine service...
- An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmissionAmit G Singal
Division of Digestive and Liver Diseases, University of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas Department of Internal Medicine, University of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas Department of Clinical Sciences, University of Texas Southwestern, Dallas, Texas Electronic address
Clin Gastroenterol Hepatol 11:1335-1341.e1. 2013..The aim of our study was to construct an automated 30-day readmission risk model for cirrhotic patients using electronic medical record (EMR) data available early during hospitalization...
- Vital Signs Are Still Vital: Instability on Discharge and the Risk of Post-Discharge Adverse OutcomesOanh Kieu Nguyen
Division of General Internal Medicine, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
J Gen Intern Med . 2016..Vital sign instability on discharge could be a clinically objective means of assessing readiness and safety for discharge; however, the association between vital sign instability on discharge and post-hospital outcomes is unclear...
- Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing modelsRuben Amarasingham
Parkland Center for Clinical Innovation, 8435 Stemmons Freeway, Suite 1150, Dallas, TX, 75247, USA
BMC Med Inform Decis Mak 15:39. 2015..The objective of this study was to evaluate the degree to which EMR-based risk models for 30-day readmission or mortality accurately identify high risk patients and to compare these models with published claims-based models...
- Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record dataCarlos A Alvarez
School of Pharmacy Department of Pharmacy Practice, Texas Tech University Health Sciences Center, 5920 Forest Park Rd, Dallas, TX 75235, USA
BMC Med Inform Decis Mak 13:28. 2013....
- Allocating scarce resources in real-time to reduce heart failure readmissions: a prospective, controlled studyRuben Amarasingham
Parkland Center for Clinical Innovation, Dallas, Texas, USA
BMJ Qual Saf 22:998-1005. 2013..To test a multidisciplinary approach to reduce heart failure (HF) readmissions that tailors the intensity of care transition intervention to the risk of the patient using a suite of electronic medical record (EMR)-enabled programmes...
- Use of administrative claims data for identifying patients with cirrhosisMahendra S Nehra
Department of Internal Medicine, UT Southwestern Medical Cente, Dallas, TX 75390 8887, USA
J Clin Gastroenterol 47:e50-4. 2013..Administrative data are used in clinical research, but the validity of ICD-9 codes to identify cirrhotic patients has not been well established...
- Applying data analytics and information exchange to improve care for patientsRuben Amarasingham
Parkland Center for Clinical Innovation, Dallas, Texas, USA
Health Aff (Millwood) 31:2785-6. 2012Parkland Hospital's Ruben Amarasingham built a model to predict patients at high risk for readmission and now leads efforts to extend the benefits of health information to the nation's most vulnerable.
- An electronic medical record-based model to predict 30-day risk of readmission and death among HIV-infected inpatientsAnk E Nijhawan
Department of Medicine, Division of Infectious Diseases, University of Texas Southwestern Medical Center, Center for Clinical Innovation, Parkland Health and Hospital System, Dallas, TX 75235, USA
J Acquir Immune Defic Syndr 61:349-58. 2012..We sought to use data from the Electronic Medical Record (EMR) to create a clinical, robust, multivariable model for predicting readmission risk in hospitalized HIV-infected patients...
- Initial Development of a Computer Algorithm to Identify Patients With Breast and Lung Cancer Having Poor Prognosis in a Safety Net HospitalRamona L Rhodes
Division of Geriatric Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
Am J Hosp Palliat Care 33:678-83. 2016....