Background: Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED.

Background & Aims-Colorectal cancer (CRC) risk estimates based on family history typically include only close relatives. We report familial relative risk in probands with various combinations, or constellations, of affected relatives, extending to third-degree.

Hospitals that operate at or over capacity may experience heightened rates of patient safety events and might consider re-engineering the structures of care to respond better during periods of high stress.

The goal of this study was to determine the accuracy and the impact of 5 different claims-based pneumonia definitions. Three International Classification of Diseases, Version 9, (ICD-9), and 2 diagnosis-related group (DRG)-based case identification algorithms were compared against an independent, clinical pneumonia reference standard. Among 10748 patients, 272 (2.5%) had pneumonia verified by the reference standard. The sensitivity of claims-based algorithms ranged from 47.8% to 66.2%. The positive predictive values ranged from 72.6% to 80.8%. Patient-related variables were not significantly different from the reference standard among the 3 ICD-9-based algorithms. DRG-based algorithms had significantly lower hospital admission rates (57% and 65% vs 73.2%), lower 30-day mortality (5.0% and 5.8% vs 10.7%), shorter length of stay (3.9 and 4.1 days vs 5.6 days), and lower costs (USD $4543 and USD $5159 vs USD $8585). Claims-based identification algorithms for defining pneumonia in administrative databases are imprecise. ICD-9-based algorithms did not influence patient variables in our population. Identifying pneumonia patients with DRG codes is significantly less precise.

No abstract

The Strategic Health IT Advanced Research Projects (SHARP) Program, established by the Office of the National Coordinator for Health Information Technology in 2010 supports research findings that remove barriers for increased adoption of health IT. The improvements envisioned by the SHARP Area 4 Consortium (SHARPn) will enable the use of the electronic health record (EHR) for secondary purposes, such as care process and outcomes improvement, biomedical research and epidemiologic monitoring of the nation’s health. One of the primary informatics problem areas in this endeavor is the standardization of disparate health data from the nation’s many health care organizations and providers. The SHARPn team is developing open source services and components to support the ubiquitous exchange, sharing and reuse or ‘liquidity’ of operational clinical data stored in electronic health records. One year into the design and development of the SHARPn framework, we demonstrated end to end data flow and a prototype SHARPn platform, using thousands of patient electronic records sourced from two large healthcare organizations: Mayo Clinic and Intermountain Healthcare. The platform was deployed to (1) receive source EHR data in several formats, (2) generate structured data from EHR narrative text, and (3) normalize the EHR data using common detailed clinical models and Consolidated Health Informatics standard terminologies, which were (4) accessed by a phenotyping service using normalized data specifications. The architecture of this prototype SHARPn platform is presented. The EHR data throughput demonstration showed success in normalizing native EHR data, both structured and narrative, from two independent organizations and EHR systems. Based on the demonstration, observed challenges for standardization of EHR data for interoperable secondary use are discussed.

GUIDElINE GlossaryADl -activities of daily living, AF -atrial fibrillation; BMibody mass index; Bp -blood pressure; CAS -carotid angioplasty and stenting; CeA -carotid endarterectomy; Ci -confidence interval; CSF -cerebrospinal fluid; CT -computed tomography; Cv -cardiovascular; DSA -digital subtraction angiography; DvT -deep-vein thrombosis; DWi -diffusion-weighted imaging; eCG -electrocardiography; eMS -emergency medical services; eSr -erythrocyte sedimentation rate; GCp -good clinical practice; HDl -high-density lipoprotein; Hiv -human immunodeficiency virus; inr -international normalised ratio; lDl -low-density lipoprotein; MCA -middle cerebral artery; MrA -magnetic resonance angiography; Mri -magnetic resonance imaging; mrS -modified rankin score; MDT -multi-disciplinary team; nASCeT -north American Symptomatic Carotid endarterectomy Trial; nG -nasogastric; niHSS -national institutes of Health Stroke Scale; ninDS -national institute of neurological Disorders and Stroke; nnT -numbers needed to treat; OSA -obstructive sleep apnoea; Or -odds ratio; OT -occupational therapy; pe -pulmonary embolism; peG -percutaneous enteral gastrostomy; pFO -patent foramen ovale; rCT -randomised controlled trial; rr -relative risk; SASpi -Southern African Stroke prevention initiative study; SASS -South African Stroke Society; SSris -selective serotonin reuptake Recommendations. ideally, all patients with acute stroke should be managed in a dedicated stroke unit. There is ample evidence that protocol-driven multidisciplinary stroke unit care within a hospital improves recovery from stroke. Treatment in a stroke unit has been shown to reduce mortality as well as reduce the likelihood of dependency after stroke. An effective stroke service requires the establishment of a seamless network consisting of acute stroke units, post-acute care and rehabilitation, and further care in the community. primary preventive measures reduce stroke incidence and should be universally available and actively promoted at all levels of health care in South Africa. Successful care of a stroke patient begins with recognition by the public and health professionals that stroke should be considered an emergency. Avoiding delay should be the major aim of the prehospital phase of acute stroke care. Acute stroke or transient ischaemic attack (TiA) should be treated as a medical emergency and evaluated with minimum delay. General supportive treatment is emphasised and is directed at maintaining homeostasis and the treatment of complications. intravenous thrombolytic therapy with recombinant tissue plasminogen activator (tpA) is an accepted therapy for acute ischaemic stroke within 4.5 hours of onset of symptoms, but can only be administered at centres with specific resources. Awareness and treatment of the neurological and systemic complications of acute stroke are an integral part of management. patients with suspected TiA and minor stroke with early spontaneous recovery should be evaluated as soon as possible after an event.Brain imaging is recommended, and ...

In this study, we evaluate the performance of a Natural Language Processing (NLP) application designed to extract medical problems from narrative text clinical documents. The documents come from a patient's electronic medical record and medical problems are proposed for inclusion in the patient's electronic problem list. This application has been developed to help maintain the problem list and make it more accurate, complete, and up-to-date. The NLP part of this system-analyzed in this study-uses the UMLS MetaMap Transfer (MMTx) application and a negation detection algorithm called NegEx to extract 80 different medical problems selected for their frequency of use in our institution. When using MMTx with its default data set, we measured a recall of 0.74 and a precision of 0.756. A custom data subset for MMTx was created, making it faster and significantly improving the recall to 0.896 with a non-significant reduction in precision.