8 resultados para Algebra of Errors

em DigitalCommons@The Texas Medical Center


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One critical step in addressing and resolving the problems associated with human errors is the development of a cognitive taxonomy of such errors. In the case of errors, such a taxonomy may be developed (1) to categorize all types of errors along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to explain why, and even predict when and where, a specific error will occur, and (4) to generate intervention strategies for each type of error. Based on Reason's (1992) definition of human errors and Norman's (1986) cognitive theory of human action, we have developed a preliminary action-based cognitive taxonomy of errors that largely satisfies these four criteria in the domain of medicine. We discuss initial steps for applying this taxonomy to develop an online medical error reporting system that not only categorizes errors but also identifies problems and generates solutions.

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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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BACKGROUND: Most healthcare in the US is delivered in the ambulatory care setting, but the epidemiology of errors and adverse events in ambulatory care is understudied. METHODS: Using the population-based data from the Colorado and Utah Medical Practices Study, we identified adverse events that occurred in an ambulatory care setting and led to hospital admission. Proportions with 95% CIs are reported. RESULTS: We reviewed 14,700-hospital discharge records and found 587 adverse events of which 70 were ambulatory care adverse events (AAEs) and 31 were ambulatory care preventable adverse events (APAEs). When weighted to the general population, there were 2608 AAEs and 1296 (44.3%) APAEs in Colorado and Utah, USA, in 1992. APAEs occurred most commonly in physicians' offices (43.1%, range 46.8-27.8), the emergency department (32.3%, 46.1-18.5) and at home (13.1%, 23.1-3.1). APAEs in day surgery were less common (7.1%, 13.6-0.6) but caused the greatest harm to patients. The types of APAEs were broadly distributed among missed or delayed diagnoses (36%, 50.2-21.8), surgery (24.1%, 36.7-11.5), non-surgical procedures (14.6%, 25.0-4.2), medication (13.1%, 23.1-3.1) and therapeutic events (12.3%, 22.0-2.6). Overall, 10% of the APAEs resulted in serious permanent injury or death. The proportion of APAEs that resulted in death was 31.8% for general internal medicine, 22.5% for family practice and 16.7% for emergency medicine. CONCLUSION: An estimated 75,000 hospitalisations per year are due to preventable adverse events that occur in outpatient settings in the US, resulting in 4839 serious permanent injuries and 2587 deaths.

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Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^

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Medication errors, one of the most frequent types of medical errors, are a common cause of patient harm in hospital systems today. Nurses at the bedside are in a position to encounter many of these errors since they are there at the start of the process (ordering/prescribing) and the end of the process (administration). One of the recommendations from the IOM (Institute of Medicine) report, "To Err is Human," was for organizations to identify and learn from medical errors through event reporting systems. While many organizations have reporting systems in place, research studies report a significant amount of underreporting by nurses. A systematic review of the literature was performed to identify contributing factors related to the reporting and not reporting of medication errors by nurses at the bedside.^ Articles included in the literature review were primary or secondary studies, dated January 1, 2000 – July 2009, related to nursing medication error reporting. All 634 articles were reviewed with an algorithm developed to standardize the review process and help filter out those that did not meet the study criteria. In addition, 142 article bibliographies were reviewed to find additional studies that were not found in the original literature search.^ After reviewing the 634 articles and the additional 108 articles discovered in the bibliography review, 41 articles met the study criteria and were used in the systematic literature review results.^ Fear of punitive reactions to medication errors was a frequent barrier to error reporting. Nurses fear reactions from their leadership, peers, patients and their families, nursing boards, and the media. Anonymous reporting systems and departments/organizations with a strong safety culture in place helped to encourage the reporting of medication errors by nursing staff.^ Many of the studies included in this literature review do not allow results that can be generalized. The majority of them took place in single institutions/organizations with limited sample sizes. Stronger studies with larger sample sizes need to be performed, utilizing data collection methods that have been validated, to determine stronger correlations between safety cultures and nurse error reporting.^

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Errors in the administration of medication represent a significant loss of medical resources and pose life altering or life threatening risks to patients. This paper considered the question, what impact do Computerized Physician Order Entry (CPOE) systems have on medication errors in the hospital inpatient environment? Previous reviews have examined evidence of the impact of CPOE on medication errors, but have come to ambiguous conclusions as to the impact of CPOE and decision support systems (DSS). Forty-three papers were identified. Thirty-one demonstrated a significant reduction in prescribing error rates for all or some drug types; decreases in minor errors were most often reported. Several studies reported increases in the rate of duplicate orders and failures to remove contraindicated drugs, often attributed to inappropriate design or to an inability to operate the system properly. The evidence on the effectiveness of CPOE to reduce errors in medication administration is compelling though it is limited by modest study sample sizes and designs. ^

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Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

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Over the last decade, adverse events and medical errors have become a main focus of interest for the standards of quality and safety in the U.S. healthcare system (Weinstein & Henderson, 2009). Particularly when a medical error occurs, the disclosure of medical errors and its practices have become a focal point of the healthcare process. Patients and family members who have experienced a medical error might be able to provide knowledge and insight on how to improve the disclose process. However, patient and family member are not typically involved in the disclosure process, thus their experiences go unnoticed. ^ The purpose of this research was to explore how best to include patients and family members in the disclosure process regarding a medical error. The research consisted of 28 qualitative interviews from three stakeholder groups: Hospital Administrators, Clinical Service Providers, and Patients and Family Members. They were asked for their ideas and suggestions on how best to include patients and family members in the disclosure process. Framework Analysis was used to analyze this data and find prevalent themes based on the primary research question. A secondary aim was to index categories created based on the interviews that were collected. Data was used from the Texas Disclosure and Compensation Study with Dr. Eric Thomas as the Principal Investigator. Full acknowledgement of access to this data is given to Dr. Thomas. ^ The themes from the research revealed that each stakeholder group was interested and open to including patients and family members in the disclosure process and that the disclosure process should not be a "one-way" avenue. The themes gave many suggestions regarding how to best include patients and family members in the disclosure process of a medical error. Secondary aims revealed several ways to assess the ideas and suggestion given by the stakeholders. Overall, acceptability of getting the perspective of patients and family members was the most common theme. Comparison of each stakeholder group revealed that including patients and family members would be beneficial to improving hospital disclosure practices. ^ Conclusions included a list of recommendations and measureable appropriate strategies that could provide hospital with key stakeholders insights on how to improve their disclosure process. Sharing patients and family members experience with healthcare providers can encourage a shift in culture where patients are valued and active in participating in hospital practices. To my knowledge, this research is the very first of its kind and moves the disclosure process conversation forward in a patient-family member inclusion direction that will assist in improving disclosure practices. Future research should implement and evaluate the success of the various inclusion strategies.^