978 resultados para Medical errors
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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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Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.
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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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This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^
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Acknowledgements The iHARP database was funded by unrestricted grants from Mundipharma International Ltd and Research in Real-Life Ltd; these analyses were funded by an unrestricted grant from Teva Pharmaceuticals. Mundipharma and Teva played no role in study conduct or analysis and did not modify or approve the manuscript. The authors wish to direct a special appreciation to all the participants of the iHARP group who contributed data to this study and to Mundipharma, sponsors of the iHARP group. In addition, we thank Julie von Ziegenweidt for assistance with data extraction and Anna Gilchrist and Valerie L. Ashton, PhD, for editorial assistance. Elizabeth V. Hillyer, DVM, provided editorial and writing support, funded by Research in Real-Life, Ltd.
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Purpose: To analyze and define the possible errors that may be introduced in keratoconus classification when the keratometric corneal power is used in such classification. Materials and methods: Retrospective study including a total of 44 keratoconus eyes. A comprehensive ophthalmologic examination was performed in all cases, which included a corneal analysis with the Pentacam system (Oculus). Classical keratometric corneal power (Pk), Gaussian corneal power (Pc Gauss), True Net Power (TNP) (Gaussian power neglecting the corneal thickness effect), and an adjusted keratometric corneal power (Pkadj) (keratometric power considering a variable keratometric index) were calculated. All cases included in the study were classified according to five different classification systems: Alió-Shabayek, Amsler-Krumeich, Rabinowitz-McDonnell, collaborative longitudinal evaluation of keratoconus (CLEK), and McMahon. Results: When Pk and Pkadj were compared, differences in the type of grading of keratoconus cases was found in 13.6% of eyes when the Alió-Shabayek or the Amsler-Krumeich systems were used. Likewise, grading differences were observed in 22.7% of eyes with the Rabinowitz-McDonnell and McMahon classification systems and in 31.8% of eyes with the CLEK classification system. All reclassified cases using Pkadj were done in a less severe stage, indicating that the use of Pk may lead to the classification of a cornea as keratoconus, being normal. In general, the results obtained using Pkadj, Pc Gauss or the TNP were equivalent. Differences between Pkadj and Pc Gauss were within ± 0.7D. Conclusion: The use of classical keratometric corneal power may lead to incorrect grading of the severity of keratoconus, with a trend to a more severe grading.
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Evidence suggests that inactivity during a hospital stay is associated with poor health outcomes in older medical inpatients. We aimed to estimate the associations of average daily step-count (walking) in hospital with physical performance and length of stay in this population. Medical in-patients aged ⩾65 years, premorbidly mobile, with an anticipated length of stay ⩾3 d, were recruited. Measurements included average daily step-count, continuously recorded until discharge, or for a maximum of 7 d (Stepwatch Activity Monitor); co-morbidity (CIRS-G); frailty (SHARE F-I); and baseline and end-of-study physical performance (short physical performance battery). Linear regression models were used to estimate associations between step-count and end-of-study physical performance or length of stay. Length of stay was log transformed in the first model, and step-count was log transformed in both models. Similar models were used to adjust for potential confounders. Data from 154 patients (mean 77 years, SD 7.4) were analysed. The unadjusted models estimated for each unit increase in the natural log of stepcount, the natural log of length of stay decreased by 0.18 (95% CI −0.27 to −0.09). After adjustment of potential confounders, while the strength of the inverse association was attenuated, it remained significant (βlog(steps) = −0.15, 95%CI −0.26 to −0.03). The back-transformed result suggested that a 50% increase in step-count was associated with a 6% shorter length of stay. There was no apparent association between step-count and end-of-study physical performance once baseline physical performance was adjusted for. The results indicate that step-count is independently associated with hospital length of stay, and merits further investigation.
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Objectives: To measure the step-count accuracy of an ankle-worn accelerometer, a thigh-worn accelerometer and one pedometer in older and frail inpatients. Design: Cross-sectional design study. Setting: Research room within a hospital. Participants: Convenience sample of inpatients aged ≥65 years, able to walk 20 metres unassisted, with or without a walking-aid. Intervention: Patients completed a 40-minute programme of predetermined tasks while wearing the three motion sensors simultaneously. Video-recording of the procedure provided the criterion measurement of step-count. Main Outcome Measures: Mean percentage (%) errors were calculated for all tasks, slow versus fast walkers, independent versus walking-aid-users, and over shorter versus longer distances. The Intra-class Correlation was calculated and accuracy was visually displayed by Bland-Altman plots. Results: Thirty-two patients (78.1 ±7.8 years) completed the study. Fifteen were female and 17 used walking-aids. Their median speed was 0.46 m/sec (interquartile range, IQR 0.36-0.66). The ankle-worn accelerometer overestimated steps (median 1% error, IQR -3 to 13). The other motion sensors underestimated steps (40% error (IQR -51 to -35) and 38% (IQR -93 to -27), respectively). The ankle-worn accelerometer proved more accurate over longer distances (3% error, IQR 0 to 9), than shorter distances (10%, IQR -23 to 9). Conclusions: The ankle-worn accelerometer gave the most accurate step-count measurement and was most accurate over longer distances. Neither of the other motion sensors had acceptable margins of error.
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The paper explores the attitudes of medical physicians towards adverse incident reporting in health care, with particular focus on the inhibiting factors or barriers to participation. It is recognised that there are major barriers to medical reporting, such as the ‘culture of blame’. There are, however, few detailed qualitative accounts of medical culture as it relates to incident reporting. Drawing on a 2-year qualitative case study in the UK, this paper presents data gathered from 28 semi-structured interviews with specialist physicians. The findings suggest that blame certainly inhibits medical reporting, but other cultural issues were also significant. It was commonly accepted by doctors that errors are an ‘inevitable’ and potentially unmanageable feature of medical work and incident reporting was therefore ‘pointless’. It was also found that reporting was discouraged by an anti-bureaucratic sentiment and rejection of excessive administrative duties. Doctors were also apprehensive about the increased potential for managers and non-physicians to engage in the regulation of medical quality through the use of incident data. The paper argues that the promotion of incident reporting must engage with more than the ubiquitous ‘culture of blame’ and instead address the ‘culture of medicine’, especially as it relates to the collegial and professional control of quality.
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The issue of health professionals facing criminal charges of manslaughter or criminal negligence causing death or grievous bodily harm as a result of alleged negligence in their professional practice was thrown into stark relief by the recent acquittal of four physicians accused of mismanaging Canada’s blood system in the early 1980s. Stories like these, as well as international reports detailing an increase in the numbers of physicians being charged with (and in some cases convicted of) serious criminal offences as the result of alleged negligence in their professional practice, have resulted in some anxiety about the apparent increase in the incidence of such charges and their appropriateness in the healthcare context. Whilst research has focused on the incidence, nature and appropriateness of criminal charges against health professionals, particularly physicians, for alleged negligence in their professional practice in the United Kingdom, the United States, Japan, and New Zealand, the Canadian context has yet to be examined. This article examines the Canadian context and how the criminal law is used to regulate the negligent acts or omissions of a health care professional in the course of their professional practice. It also assesses the appropriateness of such use. It is important at this point to state that the analysis in this article does not focus on those, fortunately few, cases where a health professional has intentionally killed his or her patients but rather when patients’ deaths or grievous injuries were allegedly as a result of that health professional’s negligent acts or omissions when providing health services to that patient.