899 resultados para Medical lab data


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Statement of the problem and public health significance. Hospitals were designed to be a safe haven and respite from disease and illness. However, a large body of evidence points to preventable errors in hospitals as the eighth leading cause of death among Americans. Twelve percent of Americans, or over 33.8 million people, are hospitalized each year. This population represents a significant portion of at risk citizens exposed to hospital medical errors. Since the number of annual deaths due to hospital medical errors is estimated to exceed 44,000, the magnitude of this tragedy makes it a significant public health problem. ^ Specific aims. The specific aims of this study were threefold. First, this study aimed to analyze the state of the states' mandatory hospital medical error reporting six years after the release of the influential IOM report, "To Err is Human." The second aim was to identify barriers to reporting of medical errors by hospital personnel. The third aim was to identify hospital safety measures implemented to reduce medical errors and enhance patient safety. ^ Methods. A descriptive, longitudinal, retrospective design was used to address the first stated objective. The study data came from the twenty-one states with mandatory hospital reporting programs which report aggregate hospital error data that is accessible to the public by way of states' websites. The data analysis included calculations of expected number of medical errors for each state according to IOM rates. Where possible, a comparison was made between state reported data and the calculated IOM expected number of errors. A literature review was performed to achieve the second study aim, identifying barriers to reporting medical errors. The final aim was accomplished by telephone interviews of principal patient safety/quality officers from five Texas hospitals with more than 700 beds. ^ Results. The state medical error data suggests vast underreporting of hospital medical errors to the states. The telephone interviews suggest that hospitals are working at reducing medical errors and creating safer environments for patients. The literature review suggests the underreporting of medical errors at the state level stems from underreporting of errors at the delivery level. ^

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Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

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National Highway Traffic Safety Administration, Washington, D.C.

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The Australian e-Health Research Centre in collaboration with the Queensland University of Technology's Paediatric Spine Research Group is developing software for visualisation and manipulation of large three-dimensional (3D) medical image data sets. The software allows the extraction of anatomical data from individual patients for use in preoperative planning. State-of-the-art computer technology makes it possible to slice through the image dataset at any angle, or manipulate 3D representations of the data instantly. Although the software was initially developed to support planning for scoliosis surgery, it can be applied to any dataset whether obtained from computed tomography, magnetic resonance imaging or any other imaging modality.

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The application of computer-aided design and manufacturing (CAD/CAM) techniques in the clinic is growing slowly but steadily. The ability to build patient-specific models based on medical imaging data offers major potential. In this work we report on the feasibility of employing laser scanning with CAD/CAM techniques to aid in breast reconstruction. A patient was imaged with laser scanning, an economical and facile method for creating an accurate digital representation of the breasts and surrounding tissues. The obtained model was used to fabricate a customized mould that was employed as an intra-operative aid for the surgeon performing autologous tissue reconstruction of the breast removed due to cancer. Furthermore, a solid breast model was derived from the imaged data and digitally processed for the fabrication of customized scaffolds for breast tissue engineering. To this end, a novel generic algorithm for creating porosity within a solid model was developed, using a finite element model as intermediate.

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In this study on the basis of lab data and available resources in Bangladesh, feasibility study has been carried out for pyrolysis process converting solid tire wastes into pyrolysis oils, solid char and gases. The process considered for detailed analysis was fixed-bed fire-tube heating pyrolysis reactor system. The comparative techno-economic assessment was carried out in US$ for three different sizes plants: medium commercial scale (144 tons/day), small commercial scale (36 tons/day), pilot scale (3.6 tons/day). The assessment showed that medium commercial scale plant was economically feasible, with the lowest unit production cost than small commercial and pilot scale plants for the production of crude pyrolysis oil that could be used as boiler fuel oil and for the production of upgraded liquid-products.

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Background: Effective self-management of diabetes is essential for the reduction of diabetes-related complications, as global rates of diabetes escalate. Methods: Randomised controlled trial. Adults with type 2 diabetes (n = 120), with HbA1c greater than or equal to 7.5 %, were randomly allocated (4 × 4 block randomised block design) to receive an automated, interactive telephone-delivered management intervention or usual routine care. Baseline sociodemographic, behavioural and medical history data were collected by self-administered questionnaires and biological data were obtained during hospital appointments. Health-related quality of life (HRQL) was measured using the SF-36. Results: The mean age of participants was 57.4 (SD 8.3), 63 % of whom were male. There were no differences in demographic, socioeconomic and behavioural variables between the study arms at baseline. Over the six-month period from baseline, participants receiving the Australian TLC (Telephone-Linked Care) Diabetes program showed a 0.8 % decrease in geometric mean HbA1c from 8.7 % to 7.9 %, compared with a 0.2 % HbA1c reduction (8.9 % to 8.7 %) in the usual care arm (p = 0.002). There was also a significant improvement in mental HRQL, with a mean increase of 1.9 in the intervention arm, while the usual care arm decreased by 0.8 (p = 0.007). No significant improvements in physical HRQL were observed. Conclusions: These analyses indicate the efficacy of the Australian TLC Diabetes program with clinically significant post-intervention improvements in both glycaemic control and mental HRQL. These observed improvements, if supported and maintained by an ongoing program such as this, could significantly reduce diabetes-related complications in the longer term. Given the accessibility and feasibility of this kind of program, it has strong potential for providing effective, ongoing support to many individuals with diabetes in the future.

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Cartilage defects heal imperfectly and osteoarthritic changes develop frequently as a result. Although the existence of specific behaviours of chondrocytes derived from various depth-related zones in vitro has been known for over 20 years, only a relatively small body of in vitro studies has been performed with zonal chondrocytes and current clinical treatment strategies do not reflect these native depth-dependent (zonal) differences. This is surprising since mimicking the zonal organization of articular cartilage in neo-tissue by the use of zonal chondrocyte subpopulations could enhance the functionality of the graft. Although some research groups including our own have made considerable progress in tailoring culture conditions using specific growth factors and biomechanical loading protocols, we conclude that an optimal regime has not yet been determined. Other unmet challenges include the lack of specific zonal cell sorting protocols and limited amounts of cells harvested per zone. As a result, the engineering of functional tissue has not yet been realized and no long-term in vivo studies using zonal chondrocytes have been described. This paper critically reviews the research performed to date and outlines our view of the potential future significance of zonal chondrocyte populations in regenerative approaches for the treatment of cartilage defects. Secondly, we briefly discuss the capabilities of additive manufacturing technologies that can not only create patient-specific grafts directly from medical imaging data sets but could also more accurately reproduce the complex 3D zonal extracellular matrix architecture using techniques such as hydrogel-based cell printing.

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We propose a new approach for quantifying regions of interest (ROIs) in medical image data. Rotationally invariant shape descriptors (ISDs) were applied to 3D brain regions extracted from MRI scans of 5 Parkinson's patients and 10 control subjects. We concentrated on the thalamus and the caudate nucleus since prior studies have suggested they are affected in Parkinson's disease (PD). In the caudate, both the ISD and volumetric analyses found significant differences between control and PD subjects. The ISD analysis however revealed additional differences between the left and right caudate nuclei in both control and PD subjects. In the thalamus, the volumetric analysis showed significant differences between PD and control subjects, while ISD analysis found significant differences between the left and right thalami in control subjects but not in PD patients, implying disease-induced shape changes. These results suggest that employing ISDs for ROI characterization both complements and extends traditional volumetric analyses. © 2006 IEEE.

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BACKGROUND: Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study's protocol. METHODS/DESIGN: MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff. DISCUSSION: This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness. TRIAL REGISTRATION: NCT01956773.

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This study explored the experiences of informal carers who were aged 65 years and over. It has been estimated that 15 per cent of those aged 65 or over provide some form of informal care in England. Despite a growing literature on the involvement of older people in research, there is a paucity of literature on the involvement of older carers. In this study, older carers were identified via a General Practice (GP) register in one urban medical practice. Data was collected through a series of focus groups, which were transcribed and analysed using
thematic analysis. Every carer aged 55 or over and registered with the medical practice was invited to take part in the study. Four female carers and one male carer took part in the study (age range 65-83). Themes that emerged during data analysis included, 1) managing things in an emergency, 2) feeling valued because they took part in the research and 3) the day-to-day reality of living with social exclusion. GP registers provide a valuable tool for identifying older
carers who may otherwise be difficult to engage in research. However, persuading GPs to engage with qualitative research may be a challenge.

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Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.

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Objective To investigate the incidence of falls and explore fall prevention practices at acute care hospitals in Singapore.

Design A retrospective audit to collect baseline data on (1) incidence of falls (patient fall rates and fall injury rates) and (2) fall prevention practices, was conducted in five acute care hospitals in Singapore from December 2004 to March 2005.

Study participants Medical record data (n = 6000) of patients admitted into the medical, surgical and geriatric units in the five hospitals.

Outcome measures Fall incidence was obtained from the hospital's fall databases and incident reports for the period of June 2003 to May 2004. In total, 6000 medical records from five hospitals were randomly selected, retrieved and reviewed to determine whether falls, fall assessments and interventions were being initiated and documented.

Results The number of fallers for all hospitals was 825. Analysis showed that patient fall rates ranged from 0.68 to 1.44 per 1000 patient days, and the proportion of falls associated with injury ranged from 27.4% to 71.7%. The use of a fall risk assessment tool by nurses was recorded in 77% of all the nursing records.

Conclusion This study has laid the foundation for further research for fall prevention in Singapore by describing current fall rates, fall-associated injury rates and the status of fall prevention practices in acute care settings. The results will be used to inform the development of a tailored multifaceted strategy to facilitate the implementation of Fall Prevention Clinical Practice Guidelines to reduce the burden of falls and fall injuries in hospitals in Singapore.

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Background: The increased prevalence of obesity in pregnant women in Australia and other developed countries is a significant public health concern. Obese women are at increased risk of serious perinatal complications and guidelines recommend weight gain restriction and additional care. There is limited evidence to support the effectiveness of dietary and physical activity lifestyle interventions in preventing adverse perinatal outcomes and new strategies need to be evaluated. The primary aim of this project is to evaluate the effect of continuity of midwifery care on restricting gestational weight gain in obese women to the recommended range. The secondary aims of the study are to assess the impact of continuity of midwifery care on: women’s experience of pregnancy care; women’s satisfaction with care and a range of psychological factors.
Methods/Design: A two arm randomised controlled trial (RCT) will be conducted with primigravid women recruited from maternity services in Victoria, Australia. Participants will be primigravid women, with a BMI≥30 who are less than 17 weeks gestation. Women allocated to the intervention arm will be cared for in a midwifery continuity of care model and receive an informational leaflet on managing weight gain in pregnancy. Women allocated to the control group will receive routine care in addition to the same informational leaflet. Weight gain during pregnancy, standards of care, medical and obstetric information will be extracted from medical records. Data collected at recruitment (self administered survey) and at 36 weeks by postal survey will include sociodemographic information and the use of validated scales to measure secondary outcomes.
Discussion: Continuity of midwifery care models are well aligned with current Victorian, Australian and many international government policies on maternity care. Increasingly, midwifery continuity models of care are being introduced in low risk maternity care, and information on their application in high risk populations is required. There is an identified need to trial alternative antenatal interventions to reduce perinatal risk factors for women who are obese and the findings from this project may have application in other maternity services. In addition this study will inform a larger trial that will focus on birth and postnatal outcomes.

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We propose in this paper a novel sparse subspace clustering method that regularizes sparse subspace representation by exploiting the structural sharing between tasks and data points via group sparse coding. We derive simple, provably convergent, and computationally efficient algorithms for solving the proposed group formulations. We demonstrate the advantage of the framework on three challenging benchmark datasets ranging from medical record data to image and text clustering and show that they consistently outperforms rival methods.