21 resultados para medical error
Resumo:
Background. Healthcare providers in pediatrics are faced with parents making medical decisions for their children. Refusal to consent to interventions can have life threatening sequelae, yet healthcare workers are provided little training in handling refusals. The healthcare provider's experience in parental refusal has not been well described, yet is an important first step in addressing this problem. ^ Specific aims. Describe: (1) the decision-making processes made by healthcare providers when parents refuse medical interventions for their children, (2) the source of healthcare workers' skills in handling situations of refusal, and (3) the perspectives of healthcare workers on parental refusals in the inpatient setting. ^ Methods. Nurses, physicians and respiratory therapists (RT) were recruited via e-mail at Texas Children's Hospital (TCH). Interview questions were developed using Social Cognitive Theory constructs and validated. One-on-one in-depth, one hour semi-structured interviews were held at TCH, audio recorded and transcribed. Coding and analysis were done using ATLAS ti. The constant comparative method was applied to describe emergent themes that were reviewed by an independent expert. ^ Results. Interviews have been conducted with nurses (n=6), physicians and practitioners (n=6), social workers (n=3) and RT (n=3) comprising 13 females and 5 males with 3–25 years of experience. Decision-making processes relate to the experience of the caregiver, familiarity with the family, and the acuity of the patient. Healthcare workers' skills were obtained through orientation processes or by trial-and-error. Themes emerged that related to the importance of: (1) Communication, where the initial discussion about a medical procedure should be done with clarity and an understanding of the parents' views; (2) Perceived loss of control by parents, a key factor in their refusal of interventions; and (3) Training, the need for skill development to handle refusals. ^ Conclusions. Effective training involving clarity in communication and a preservation of perceived control by parents is needed to avoid the current trial-and-error experience of healthcare workers in negotiating refusal situations. Such training could lessen the more serious outcomes of parental refusal. ^
Resumo:
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.^
Resumo:
Background. Over 39.9% of the adult population forty or older in the United States has refractive error, little is known about the etiology of this condition and associated risk factors and their entailed mechanism due to the paucity of data regarding the changes of refractive error for the adult population over time.^ Aim. To evaluate risk factors over a long term, 5-year period, in refractive error changes among persons 43 or older by testing the hypothesis that age, gender, systemic diseases, nuclear sclerosis and baseline refractive errors are all significantly associated with refractive errors changes in patients at a Dallas, Texas private optometric office.^ Methods. A retrospective chart review of subjective refraction, eye health, and self-report health history was done on patients at a private optometric office who were 43 or older in 2000 who had eye examinations both in 2000 and 2005. Aphakic and pseudophakic eyes were excluded as well as eyes with best corrected Snellen visual acuity of 20/40 and worse. After exclusions, refraction was obtained on 114 right eyes and 114 left eyes. Spherical equivalent (sum of sphere + ½ cylinder) was used as the measure of refractive error.^ Results. Similar changes in refractive error were observed for the two eyes. The 5-year change in spherical power was in a hyperopic direction for younger age groups and in a myopic direction for older subjects, P<0.0001. The gender-adjusted mean change in refractive error in right eyes of persons aged 43 to 54, 55 to 64, 65 to 74, and 75 or older at baseline was +0.43D, +0.46 D, -0.09 D, and -0.23D, respectively. Refractive change was strongly related to baseline nuclear cataract severity; grades 4 to 5 were associated with a myopic shift (-0.38 D, P< 0.0001). The mean age-adjusted change in refraction was +0.27 D for hyperopic eyes, +0.56 D for emmetropic eyes, and +0.26 D for myopic eyes.^ Conclusions. This report has documented refractive error changes in an older population and confirmed reported trends of a hyperopic shift before age 65 and a myopic shift thereafter associated with the development of nuclear cataract.^
Resumo:
Each year, hospitalized patients experience 1.5 million preventable injuries from medication errors and hospitals incur an additional $3.5 billion in cost (Aspden, Wolcott, Bootman, & Cronenwatt; (2007). It is believed that error reporting is one way to learn about factors contributing to medication errors. And yet, an estimated 50% of medication errors go unreported. This period of medication error pre-reporting, with few exceptions, is underexplored. The literature focuses on error prevention and management, but lacks a description of the period of introspection and inner struggle over whether to report an error and resulting likelihood to report. Reporting makes a nurse vulnerable to reprimand, legal liability, and even threat to licensure. For some nurses this state may invoke a disparity between a person‘s belief about him or herself as a healer and the undeniable fact of the error.^ This study explored the medication error reporting experience. Its purpose was to inform nurses, educators, organizational leaders, and policy-makers about the medication error pre-reporting period, and to contribute to a framework for further investigation. From a better understanding of factors that contribute to or detract from the likelihood of an individual to report an error, interventions can be identified to help the nurse come to a psychologically healthy resolution and help increase reporting of error in order to learn from error and reduce the possibility of future similar error.^ The research question was: "What factors contribute to a nurse's likelihood to report an error?" The specific aims of the study were to: (1) describe participant nurses' perceptions of medication error reporting; (2) describe participant explanations of the emotional, cognitive, and physical reactions to making a medication error; (3) identify pre-reporting conditions that make it less likely for a nurse to report a medication error; and (4) identify pre-reporting conditions that make it more likely for a nurse to report a medication error.^ A qualitative research study was conducted to explore the medication error experience and in particular the pre-reporting period from the perspective of the nurse. A total of 54 registered nurses from a large private free-standing not-for-profit children's hospital in the southwestern United States participated in group interviews. The results describe the experience of the nurse as well as the physical, emotional, and cognitive responses to the realization of the commission of a medication error. The results also reveal factors that make it more and less likely to report a medication error.^ It is clear from this study that upon realization that he or she has made a medication error, a nurse's foremost concern is for the safety of the patient. Fear was also described by each group of nurses. The nurses described a fear of several things including physician reaction, manager reaction, peer reaction, as well as family reaction and possible lack of trust as a result. Another universal response was the description of a struggle with guilt, shame, imperfection, blaming oneself, and questioning one's competence.^
Resumo:
In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^
Resumo:
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.