Publications (11) View all
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Article: Factors predisposing to claims and compensations for patient injuries following total hip and knee arthroplasty.
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ABSTRACT: Factors associated with malpractice claims are poorly understood. Knowledge of these factors could help to improve patient safety. We investigated whether patient characteristics and hospital volume affect claims and compensations following total hip arthroplasty (THA) and knee arthroplasty (TKA) in a no-fault scheme. A retrospective registry-based study was done on 16,646 THAs and 17,535 TKAs performed in Finland from 1998 through 2003. First, the association between patient characteristics-e.g., age, sex, comorbidity, prosthesis type-and annual hospital volume with filing of a claim was analyzed by logistic regression. Then, multinomial logistic regression was applied to analyze the association between these same factors and receipt of compensation. For THA and TKA, patients over 65 years of age were less likely to file a claim than patients under 65 (OR = 0.57, 95% CI: 0.46-0.72 and OR = 0.65, CI: 0.53-0.80, respectively), while patients with increased comorbidity were more likely to file a claim (OR = 1.17, CI: 1.04-1.31 and OR = 1.14, CI: 1.03-1.26, respectively). Following THA, male sex and cemented prosthesis reduced the odds of a claim (OR = 0.74, CI: 0.60-0.91 and OR = 0.77, CI: 0.60-0.99, respectively) and volume of between 200 and 300 operations increased the odds of a claim (OR = 1.29, CI: 1.01-1.64). Following TKA, a volume of over 300 operations reduced the probability of compensation for certain injury types (RRR = 0.24, CI: 0.08-0.72). Centralization of TKA to hospitals with higher volume may reduce the rate of compensable patient injuries. Furthermore, more attention should be paid to equal opportunities for patients to file a claim and obtain compensation.Acta Orthopaedica 03/2012; 83(2):190-6. · 2.17 Impact Factor -
Article: A methodological approach for register-based evaluation of cost and outcomes in health care.
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ABSTRACT: In health care, measures of performance are needed at producer level for improving the treatment processes and at system level for steering purposes. In addition, measures that enable reliable comparisons of producers with respect to each other should encourage them to develop their treatment processes to attain better positioning in benchmarking. The main innovation of the Performance, Effectiveness, and Costs of Treatment episodes (PERFECT) project is to measure performance using existing linkable information available from registers within well-defined care episodes in a whole population. Finnish health care and related registers are used for constructing the disease-specific databases, with rich content on treatment processes and complete follow-up data. The PERFECT project has developed numerous performance indicators that can be used to evaluate health policy actions as well as to create regional and hospital-level benchmarking data. In PERFECT, the idea is to eliminate individual-level variation from the performance indicators by using individual-level data and proper risk adjustment methods. The focus of our interest is in the variation at the producer or regional level. Our experience shows that the utilization of population-level health care registers with an episode-of-care approach enables a continual system and producer-level performance measurement.Annals of medicine 06/2011; 43 Suppl 1:S4-13. · 3.52 Impact Factor -
Article: Patient and hospital characteristics associated with claims and compensations for patient injuries in coronary artery bypass grafting in Finland.
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ABSTRACT: To analyse the association between individual patients' risk factors and rates of claims and compensations for patient injuries in an insurance scheme in which proof of negligence is not required. And to explore whether either hospital productivity or volume of procedures is related to claims and compensation rates. A two-step sequential logistic regression was applied on data collected from administrative registers. It included 17,834 patients who had undergone coronary artery bypass grafting at public hospitals in Finland between 1998 and 2002. The main outcome measure was the odds of claiming and receiving compensation. Men were less likely to claim compensation (odds ratio [OR] 0.66; 95% confidence interval 0.54-0.81), but among those having claimed were more likely to receive compensation (OR 2.08; 1.15-3.75) than women. Patients with a co-morbidity were more likely to claim (OR 1.29; 1.06-1.57), but among those having claimed were less likely to receive compensation (OR 0.52; 0.31-0.86) than those without a co-morbidity. Advanced age reduced the probability of claiming (OR 0.71; 0.52-0.96). Although high-risk patients file a claim more frequently than low-risk patients, the latter have a higher probability of getting their claims accepted and receiving compensation. This risk pattern is probably a reflection of compensation practices related to patient injuries involving an infection.Journal of Health Services Research & Policy 08/2009; 14(3):150-5. · 1.73 Impact Factor -
Article: Finding the best treatment under heavy censoring and hidden bias
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ABSTRACT: We analyse male "survival duration after hospitalization" following an acute myocardial infarction with a large ("N"=11024) Finnish data set to find the best performing hospital district (and to disseminate its treatment protocol). This is a multiple-treatment problem with 21 treatments (i.e. 21 hospital districts). The task of choosing the best treatment is difficult owing to heavy right censoring (73%), which makes the usual location measures (the mean and median) unidentified; instead, only lower quantiles are identified. There is also a sample selection issue that only those who made it to a hospital alive are observed (54%); this becomes a problem if we wish to know their potential survival duration after hospitalization, if they had survived to a hospital contrary to the fact. The data set is limited in its covariates-only age is available-but includes the distance to the hospital, which plays an interesting role. Given that only age and distance are observed, it is likely that there are unobserved confounders. To account for them, a sensitivity analysis is conducted following pair matching. All estimators employed point to a clear winner and the sensitivity analysis indicates that the finding is fairly robust. Copyright 2007 Royal Statistical Society.Journal of the Royal Statistical Society Series A. 01/2007; 170(1):133-147. -
Article: Health, schooling and lifestyle among young adults in Finland.
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ABSTRACT: This was a longitudinal, general population study based on a Northern Finland 1966 Birth Cohort, using a structural equation approach to estimate the health production function and health input functions for four lifestyle variables (smoking, alcohol consumption, exercise and unhealthy diet) for males and females. In particular, we examined the productive and allocative effects of education on health. We used 15D, a generic measure of health-related quality of life, as a single index score measure but we also estimated models for some of its dimensions. Among the males, the important factors impacting on health were education and all the four lifestyle factors, as well as some exogenous variables at 31 years and variables describing parents' background, and health and behaviour at 14 years. An increase of five years in schooling increased the health score by 0.008, of which about 50% was due to direct effect and 50% due to indirect effects. Among the females, education does not impact on health, but health was affected by the use of alcohol, exercise and diet, but not by smoking. Our results indicate that policy options that increase education among men will increase their health indirectly via healthier lifestyles. However, since the total effect was rather modest and the direct effect insignificant, an increase of schooling is not a cost-effective way to increase health given the present high educational level of Finland. The young adults' and particularly women's internationally high educational status in Finland might be a reason why we find only a modest effect of schooling on health and the non-existence of such effects among women.Health Economics 12/2006; 15(11):1201-16. · 2.12 Impact Factor
