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Franklin Gaylis, Edward Cohen, Renee Calabrese, Hilary Prime, Paul Dato, Christopher J Kane
OBJECTIVE: To measure past active surveillance (AS) adoption rates, institute the best practice, and measure the AS adoption rates following implementation. We report our findings over a 3-year period. METHODS: Patient prostate needle biopsy and treatment data from the period August 2011 to August 2014 were retrieved from an integrated electronic medical records (Allscripts) and stored in a Microsoft Access database for analysis. Structured data were queried using the automated software program WizMD and unstructured data were abstracted by manual review...
July 2016: Urology
A Rogers, J Ravenell, M Donat, A Sexias, C Ogedegbe, S I McFarlane, G Jean-Louis
INTRODUCTION: Identification of risk factors for obstructive sleep apnea (OSA) is important to enable comprehensive intervention to reduce OSA-related cardiovascular disease (CVD). The metabolic syndrome outcome study (MetSO) provides a unique opportunity to address these factors. This study investigated risk of OSA among blacks with metabolic syndrome. METHODS: The present study utilized data from MetSO, an NIH-funded cohort study of blacks with metabolic syndrome...
2015: Journal of Obesity and Overweight
Priyadarshini P Ravindran, Wenzhao Zang, Swetha Renukunta, Rick Mansour, Srinivas Denduluri
BACKGROUND: Weight gain as an adverse effect of monotherapy of antidepressant has been well-studied. The effects of augmentation therapy involving multiple antidepressants, on weight changes needs to be adequately addressed. OBJECTIVE: To study the co-medication effects of bupropion in combination with six individual antidepressants on body mass index (BMI) using EMR based data analysis. METHODS: Allscripts data warehouse was used to identify patients on monotherapy of five selective serotonin reuptake inhibitor (SSRI) drugs, escitalopram, sertraline, citalopram, paroxetine, fluoxetine, one selective norepinephrine reuptake inhibitor (SNRI) duloxetine and the aminoketone, bupropion for at least 180 days...
June 2015: Therapeutic Advances in Psychopharmacology
Li An, Priyadarshini P Ravindran, Swetha Renukunta, Srinivas Denduluri
Electronic Medical Records (EMRs) are wealthy storehouses of patient information, to which data mining techniques can be prudently applied to reveal clinically significant patterns. Detecting patterns in drug-drug interactions, leading to adverse drug reactions is a powerful application of EMR data mining. Adverse effects of drug treatments can be investigated by mining clinical laboratory tests data which are reliable indicators of abnormal physiological functions. We report here the co-medication effects of pravastatin (HMG-CoA reductase inhibitor) and paroxetine (selective serotonin reuptake inhibitor (SSRI) anti-depressant) on significant clinical parameters, identified through a data mining analysis conducted on the Allscripts data warehouse...
November 2013: Journal of Clinical Pharmacology
Gabriel Perna
No abstract text is available yet for this article.
June 2013: Healthcare Informatics: the Business Magazine for Information and Communication Systems
A Wright, A McCoy, S Henkin, M Flaherty, D Sittig
BACKGROUND: In a prior study, we developed methods for automatically identifying associations between medications and problems using association rule mining on a large clinical data warehouse and validated these methods at a single site which used a self-developed electronic health record. OBJECTIVE: To demonstrate the generalizability of these methods by validating them at an external site. METHODS: We received data on medications and problems for 263,597 patients from the University of Texas Health Science Center at Houston Faculty Practice, an ambulatory practice that uses the Allscripts Enterprise commercial electronic health record product...
2013: Applied Clinical Informatics
Joseph Conn
No abstract text is available yet for this article.
December 24, 2012: Modern Healthcare
Katherine C Michelis, Bassel Hassouna, Mina Owlia, Linda Kelahan, Heather A Young, Brian G Choi
BACKGROUND: Although recent federal mandate provides incentives for physicians to use electronic prescribing (e-prescribing), clinical end points to support its use are lacking. HYPOTHESIS: E-prescribing should improve low-density lipoprotein (LDL) goal attainment. METHODS: In this retrospective cohort study, we queried the electronic medical records (Allscripts Electronic Health Record [EHR]) of a multispecialty outpatient academic medical practice to identify patient encounters during which consecutive lipid panels were drawn in 2007 (n = 2218)...
April 2011: Clinical Cardiology
Joseph Conn
No abstract text is available yet for this article.
June 14, 2010: Modern Healthcare
Gary Baldwin
No abstract text is available yet for this article.
February 2009: Health Data Management
Dara L Grieger, Stephen H Cohen, David A Krusch
BACKGROUND: Adoption rates for electronic health records (EHRs) have been slow, despite growing enthusiasm. Cost is a frequently cited obstacle to implementing an EHR. The body of literature citing a positive return on investment is largely anecdotal and infrequently published in peer-reviewed journals. STUDY DESIGN: Five ambulatory offices, with a total of 28 providers, within the University of Rochester Medical Center, participated in a pilot project using an EHR to document the return on investment...
July 2007: Journal of the American College of Surgeons
Charles H McKown
No abstract text is available yet for this article.
March 2007: West Virginia Medical Journal
Joseph Conn
No abstract text is available yet for this article.
January 30, 2006: Modern Healthcare
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