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Search Results: 1 - 10 of 160099 matches for " Thomas V Perneger "
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The Swiss cheese model of safety incidents: are there holes in the metaphor?
Thomas V Perneger
BMC Health Services Research , 2005, DOI: 10.1186/1472-6963-5-71
Abstract: Survey of a volunteer sample of persons who claimed familiarity with the model, recruited at a conference on quality in health care, and on the internet through quality-related websites. The questionnaire proposed several interpretations of components of the Swiss cheese model: a) slice of cheese, b) hole, c) arrow, d) active error, e) how to make the system safer. Eleven interpretations were compatible with this author's interpretation of the model, 12 were not.Eighty five respondents stated that they were very or quite familiar with the model. They gave on average 15.3 (SD 2.3, range 10 to 21) "correct" answers out of 23 (66.5%) – significantly more than 11.5 "correct" answers that would expected by chance (p < 0.001). Respondents gave on average 2.4 "correct" answers regarding the slice of cheese (out of 4), 2.7 "correct" answers about holes (out of 5), 2.8 "correct" answers about the arrow (out of 4), 3.3 "correct" answers about the active error (out of 5), and 4.1 "correct" answers about improving safety (out of 5).The interpretations of specific features of the Swiss cheese model varied considerably among quality and safety professionals. Reaching consensus about concepts of patient safety requires further work.James Reason proposed the image of "Swiss cheese" to explain the occurrence of system failures, such as medical mishaps [1-5]. According to this metaphor, in a complex system, hazards are prevented from causing human losses by a series of barriers. Each barrier has unintended weaknesses, or holes – hence the similarity with Swiss cheese. These weaknesses are inconstant – i.e., the holes open and close at random. When by chance all holes are aligned, the hazard reaches the patient and causes harm (Figure 1). This model draws attention to the health care system, as opposed to the individual, and to randomness, as opposed to deliberate action, in the occurrence of medical errors.The Swiss cheese model is frequently referred to and widely accepted by patien
Utility of the detection of Plasmodium parasites for the diagnosis of malaria in endemic areas
Thomas V Perneger, Thomas Szeless, André Rougemont
BMC Infectious Diseases , 2006, DOI: 10.1186/1471-2334-6-81
Abstract: We computed the ability of the parasite detection test to identify malaria at various levels of prevalence (0% to 90%), assuming plausible estimates of sensitivity (95% and 85%) and specificity (99% and 95%) for the detection of parasites. In each situation, we computed likelihood ratios of malaria (or absence of malaria) for positive and negative parasite detection tests. Likelihood ratios were classified as clinically useful (≥ 10), intermediate (5–10), or unhelpful (<5).Likelihood ratios of positive tests were strongly related to the prevalence of infection in the general population: a positive test was unhelpful when the prevalence was 20% or more, and useful only when prevalence was 5% or less. The sensitivity and specificity of the test had little influence on these results. Likelihood ratios of negative tests were clinically useful when prevalence was 70% or less, but only for high levels of sensitivity (95%). If sensitivity was low (85%), the negative test was at best of intermediate utility, and was unhelpful if the prevalence of asymptomatic infection exceeded 30%.Identification of Plasmodium parasites supports a diagnosis of malaria only in areas where the prevalence of Plasmodium infection is low. Wherever this prevalence exceeds about 20%, a positive test is clinically unhelpful.In current practice, the diagnosis of malaria in a patient in whom this disease is suspected rests on the identification of Plasmodium parasites in the patient's blood [1]. This diagnostic method is currently recommended by the World Health Organization [2]. Parasite detection tests include the classical methods of the thick or thin blood smear, and various rapid diagnostic tests [3].This approach works well in cases of traveller's malaria, and more generally whenever the patient is unlikely to be an asymptomatic carrier of Plasmodium parasites. However, in populations where malaria is common, many people are infected by Plasmodium parasites without being sick. In such situation
Interpretation of evidence in data by untrained medical students: a scenario-based study
Thomas V Perneger, Delphine S Courvoisier
BMC Medical Research Methodology , 2010, DOI: 10.1186/1471-2288-10-78
Abstract: Empirical study of medical students (N = 842), untrained in statistical inference or in the interpretation of diagnostic tests. They were asked to interpret a hypothetical diagnostic test, presented in four versions that differed in the distributions of test scores in diseased and non-diseased populations. Each student received only one version. The intuitive application of the statistical test approach would lead to rejecting the null hypothesis of no disease in version A, and to accepting the null in version B. Application of the likelihood ratio approach led to opposite conclusions - against the disease in A, and in favour of disease in B. Version C tested the importance of the p-value (A: 0.04 versus C: 0.08) and version D the importance of the likelihood ratio (C: 1/4 versus D: 1/8).In version A, 7.5% concluded that the result was in favour of disease (compatible with p value), 43.6% ruled against the disease (compatible with likelihood ratio), and 48.9% were undecided. In version B, 69.0% were in favour of disease (compatible with likelihood ratio), 4.5% against (compatible with p value), and 26.5% undecided. Increasing the p value from 0.04 to 0.08 did not change the results. The change in the likelihood ratio from 1/4 to 1/8 increased the proportion of non-committed responses.Most untrained medical students appear to interpret evidence from data in a manner that is compatible with the use of likelihood ratios.Despite the advent of evidence-based medicine, assessing "evidence" in data is no easy task. Doctors are confronted with evidence in two situations: when interpreting the results of laboratory tests during patient care, and when interpreting statistical tests reported in scientific articles. These situations are similar in many ways. In both situations one wants to infer the true state of things (Does the patient have the disease or not? Is the scientific hypothesis true or false?) from an observed result (a positive or negative diagnostic test, a stati
What doctors think about the impact of managed care tools on quality of care, costs, autonomy, and relations with patients
Marie Deom, Thomas Agoritsas, Patrick A Bovier, Thomas V Perneger
BMC Health Services Research , 2010, DOI: 10.1186/1472-6963-10-331
Abstract: Mail survey of doctors (N = 1546) in Geneva, Switzerland. Respondents were asked to rate the impact of 8 managed care tools on 4 aspects of care on a 5-level scale (1 very negative, 2 rather negative, 3 neutral, 4 rather positive, 5 very positive). For each tool, we obtained a mean score from the 4 separate impacts.Doctors had predominantly negative opinions of the impact of managed care tools: use of guidelines (mean score 3.18), gate-keeping (2.76), managed care networks (2.77), second opinion requirement (2.65), pay for performance (1.90), pay by salary (2.24), selective contracting (1.56), and pre-approval of expensive treatments (1.77). Estimated impacts on cost control were positive or neutral for most tools, but impacts on professional autonomy were predominantly negative. Primary care doctors held more positive opinions than doctors in other specialties, and psychiatrists were in general the most critical. Older doctors had more negative opinions, as well as those in private practice.Doctors perceived most managed care tools to have a positive impact on the control of health care costs but a negative impact on medical practice. Tools that are controlled by the profession were better accepted than those that are imposed by payers."Managed care" is a global term for health care systems that integrate the delivery and financing of health care. Managed care contrasts with liberal medical practice, which allows doctors to make clinical decisions and bill for their services without interference from managers or payers. Traditional forms of managed care include the staff-model health maintenance organization (HMO) and the office-based independent provider association [1,2]. However, many variants exist. Luft notes that "in reality, each HMO is a highly complex combination of economic incentives, bureaucratic structures, and personalities" [3]. Another definition characterizes managed care programs by their use of a variety of interventions, including economic incen
Cost-consciousness among Swiss doctors: a cross-sectional survey
Patrick A Bovier, Diane P Martin, Thomas V Perneger
BMC Health Services Research , 2005, DOI: 10.1186/1472-6963-5-72
Abstract: Doctors (n = 1184) in Geneva, Switzerland, answered questions about their cost-consciousness, practice patterns (medical specialty, public.vs. private sector, number of patients per week, time spent with a new patient), work satisfaction, and stress from uncertainty. General linear models were used to identify independent risk factors of higher cost-consciousness.Most doctors agreed that trying to contain costs was their responsibility ("agree" or "totally agree": 90%) and that they should take a more prominent role in limiting the use of unnecessary tests (92%); most disagreed that doctors are too busy to worry about costs (69%) and that the cost of health care is only important if the patient has to pay for it out-of-pocket (88%). In multivariate analyses, cost-consciousness was higher among doctors in the public sector, those who saw fewer patients per week, who were most tolerant of uncertainty, and who were most satisfied with their work.Thus even in a setting with very high health care expenditures, doctors' stated cost-consciousness appeared to be generally high, even though it was not uniformly distributed among them.Because most health care expenditures are the results of doctors' decisions, whether doctors are cost-conscious is an important matter. Many decisions regarding medical tests and treatments are influenced by factors other than the expected benefit to the patient, including the doctor's demographic characteristics [1,2], training [3-6], work context [7,8], financial incentives [9,10] and information about costs [11-13]. Medical decisions are also influenced by subjective considerations, including risk aversion [14,15], tolerance for uncertainty [16], and concerns about cost and income [17].In this paper, we are interested in cost-consciousness, defined as a concern to contain costs of health care borne by society [18]. Cost-consciousness was the first factor identified from a series of different attitudes hypothesized to influence physicians' res
Self-Assessed Competency at Working with a Medical Interpreter Is Not Associated with Knowledge of Good Practice
Patricia Hudelson, Thomas Perneger, Véronique Kolly, No?lle Junod Perron
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0038973
Abstract: Background Specific knowledge and skills are needed to work effectively with an interpreter, but most doctors have received limited training. Self-assessed competency may not accurately identify training needs. Purposes The purpose of this study is to explore the association between self-assessed competency at working with an interpreter and the ability to identify elements of good practice, using a written vignette. Methods A mailed questionnaire was sent to 619 doctors and medical students in Geneva, Switzerland. Results 58.6% of respondents considered themselves to be highly competent at working with a professional interpreter, but 22% failed to mention even one element of good practice in response to the vignette, and only 39% could name more than one. There was no association between self-rated competency and number of elements mentioned. Conclusions Training efforts should challenge the assumption that working with an interpreter is intuitive. Evaluation of clinicians' ability to work with an interpreter should not be limited to self-ratings. In the context of large-scale surveys, written vignettes may provide a simple method for identifying knowledge of good practice and topics requiring further training.
Barriers to Participation in a Patient Satisfaction Survey: Who Are We Missing?
Angèle Gayet-Ageron, Thomas Agoritsas, Laura Schiesari, Véronique Kolly, Thomas V. Perneger
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0026852
Abstract: Background A common weakness of patient satisfaction surveys is a suboptimal participation rate. Some patients may be unable to participate, because of language barriers, physical limitations, or mental problems. As the role of these barriers is poorly understood, we aimed to identify patient characteristics that are associated with non-participation in a patient satisfaction survey. Methodology At the University Hospitals of Geneva, Switzerland, a patient satisfaction survey is regularly conducted among all adult patients hospitalized for >24 hours on a one-month period in the departments of internal medicine, geriatrics, surgery, neurosciences, psychiatry, and gynaecology-obstetrics. In order to assess the factors associated with non-participation to the patient satisfaction survey, a case-control study was conducted among patients selected for the 2005 survey. Cases (non respondents, n = 195) and controls (respondents, n = 205) were randomly selected from the satisfaction survey, and information about potential barriers to participation was abstracted in a blinded fashion from the patients' medical and nursing charts. Principal Findings Non-participation in the satisfaction survey was independently associated with the presence of a language barrier (odds ratio [OR] 4.53, 95% confidence interval [CI95%]: 2.14–9.59), substance abuse (OR 3.75, CI95%: 1.97–7.14), cognitive limitations (OR 3.72, CI95%: 1.64–8.42), a psychiatric diagnosis (OR 1.99, CI95%: 1.23–3.23) and a sight deficiency (OR 2.07, CI95%: 0.98–4.36). The odds ratio for non-participation increased gradually with the number of predictors. Conclusions Five barriers to non-participation in a mail survey were identified. Gathering patient feedback through mailed surveys may lead to an under-representation of some patient subgroups.
Regrets Associated with Providing Healthcare: Qualitative Study of Experiences of Hospital-Based Physicians and Nurses
Delphine S. Courvoisier, Thomas Agoritsas, Thomas V. Perneger, Ralph E. Schmidt, Stéphane Cullati
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0023138
Abstract: Background Regret is an unavoidable corollary of clinical practice. Physicians and nurses perform countless clinical decisions and actions, in a context characterised by time pressure, information overload, complexity and uncertainty. Objective To explore feelings associated with regretted clinical decisions or interventions of hospital-based physicians and nurses and to examine how these regrets are coped with. Method Qualitative study of a volunteer sample of 12 physicians and 13 nurses from Swiss University Hospitals using semi-structured interviews and thematic analysis Results All interviewees reported at least one intense regret, which sometimes led to sleep problems, or taking sickness leave. Respondents also reported an accumulation effect of small and large regrets, which sometimes led to quitting one's unit or choosing another specialty. Respondents used diverse ways of coping with regrets, including changing their practices and seeking support from peers and family but also suppression of thoughts related to the situation and ruminations on the situation. Another coping strategy was acceptance of one's limits and of medicine's limits. Physicians reported that they avoided sharing with close colleagues because they felt they could lose their credibility. Conclusions Since regret seems related to both positive and negative consequences, it is important to learn more about regret coping among healthcare providers and to determine whether training in coping strategies could help reduce negative consequences such as sleep problems, absenteeism, or turnover.
Cancer screening in a middle-aged general population: factors associated with practices and attitudes
Stéphane Cullati, Agathe I Charvet-Bérard, Thomas V Perneger
BMC Public Health , 2009, DOI: 10.1186/1471-2458-9-118
Abstract: Mailed survey of 30–60 year old residents of Geneva, Switzerland, that included questions about screening for five cancers (breast, cervix uteri, prostate, colon, skin) in the past 3 years, attitudes toward screening, health care use, preventive behaviours and socio-demographic characteristics. Cancer screening practice was dichotomised as having done at least one screening test in the past 3 years versus none.The survey response rate was 49.3% (2301/4670). More women than men had had at least one cancer screening test in the past 3 years (83.2% vs 34.5%, p < 0.001). A majority of women had had a cervical smear (76.6%) and a mammography (age 30–49: 35.0%; age 50 and older: 90.3%); and 55.1% of men 50–60 years old had been screened for prostate cancer. Other factors associated with screening included older age, higher income, a doctor visit in the past 6 months, reporting a greater number of preventive behaviours and a positive attitude toward screening. Factors linked with positive attitudes included female gender, higher level of education, gainful employment, higher income, a doctor visit in the past 6 months and a personal history of cancer.Attitudes play an important role in cancer screening practices among middle-aged adults in the general population, independent of demographic variables (age and sex) that determine in part screening recommendations. Negative attitudes were the most frequent among men and the most socio-economically disadvantaged. The moderate participation rate raises the possibility of selection bias.Routine cancer screening has become more frequent in developed societies in the past decades [1-5]. However, disparities within populations remain. Screening is more common among people who are older (an effect partially influenced by screening age recommendations), more educated, white, more affluent, those who do not live alone, and those with a personal and/or family history of cancer [2-4,6-9].Such differences may relate to problems with acce
What differences are detected by superiority trials or ruled out by noninferiority trials? A cross-sectional study on a random sample of two-hundred two-arms parallel group randomized clinical trials
Angèle Gayet-Ageron, Thomas Agoritsas, Christophe Combescure, Krisztina Bagamery, Delphine S Courvoisier, Thomas V Perneger
BMC Medical Research Methodology , 2010, DOI: 10.1186/1471-2288-10-93
Abstract: Cross-sectional study based on a random sample of two hundred two-arm, parallel group superiority (100) and noninferiority (100) randomized clinical trials published between 2004 and 2009 in 27 leading medical journals. The main outcome measure was the smallest difference in favor of the new treatment to be detected (superiority trials) or largest unfavorable difference to be ruled out (noninferiority trials) used for sample size computation, expressed as standardized difference in proportions, or standardized difference in means. Student t test and analysis of variance were used.The differences to be detected or ruled out varied considerably from one study to the next; e.g., for superiority trials, the standardized difference in means ranged from 0.007 to 0.87, and the standardized difference in proportions from 0.04 to 1.56. On average, superiority trials were designed to detect larger differences than noninferiority trials (standardized difference in proportions: mean 0.37 versus 0.27, P = 0.001; standardized difference in means: 0.56 versus 0.40, P = 0.006). Standardized differences were lower for mortality than for other outcomes, and lower in cardiovascular trials than in other research areas.Superiority trials are designed to detect larger differences than noninferiority trials are designed to rule out. The variability between studies is considerable and is partly explained by the type of outcome and the medical context. A more explicit and rational approach to choosing the difference to be detected or to be ruled out in clinical trials may be desirable.A key step in planning a randomized clinical trial is the determination of the smallest difference in the primary outcome that should be detected between the study arms. This difference determines the sample size to be used in the study together with the type I error, power and variance of the primary outcome. In principle, this determination should be made a priori by the researchers [1] based on scientific a
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