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PubMed1997

A risk-assessment model for foot and mouth disease (FMD) virus introduction through deboned beef importation.

We present a risk-assessment model to assess the risk of introduction of foot and mouth disease (FMD) virus associated with deboned beef importation. The model was developed in accordance with the risk-reduction procedures proposed by the European Community for meat importation. The risk reduction procedures include farm-level inspection, ante-mortem inspection, post-mortem inspection, chilling and deboning. The risk assessment was based on the prevalence of FMD-infected cattle in herds as well as the prevalence of infected herds in the exporting country. Computer simulations were carried out to evaluate the probability of FMD virus introduction by importing 100 tons of deboned beef in relation to FMD prevalence, number of cattle selected from each herd, and sample sizes in ante-mortem and post-mortem inspections. The effects of the risk-reduction procedures on the probability of FMD virus introduction were examined.

Animals↗
PubMed2001

Deriving a risk-adjustment model for pressure ulcer development using the Minimum Data Set.

OBJECTIVE: To use the Minimum Data Set (MDS) to derive a risk-adjustment model for pressure ulcer development that may be used in assessing the quality of nursing home care. DESIGN: Perspective observational study using MDS data from 1997. SETTING: A large, for-profit, nursing home chain. PARTICIPANTS: Our unit of analysis was 39,649 observations made on 14,607 nursing home residents who were without a stage 2 or larger pressure ulcer on an index assessment. MEASUREMENTS: Pressure ulcer status was determined at an outcome assessment approximately 90 days after an index assessment. Potential predictors of pressure ulcer development were examined for bivariate associations, contributing to the development of a multivariate logistic regression model. RESULTS: A stage 2 or larger pressure ulcer developed in 2.3% of the observations. Seventeen resident characteristics were found to be associated with pressure ulcer development. These included dependence in mobility and transferring, diabetes mellitus, peripheral vascular disease, urinary incontinence, lower body mass index, and end-stage disease. A risk-adjustment model based on these characteristics was well calibrated and able to discriminate among residents with different levels of risk for ulcer development (model c-statistic = 0.73). CONCLUSION: A clinically credible risk-adjustment model with good performance properties can be developed using the MDS. This model may be useful in profiling nursing homes on their rate of pressure ulcer development.

Aged↗
PubMed2002

Impact of modifying risk adjustment models on rankings of access to care in the VA mental health report card.

OBJECTIVE: Using a measure from the Veterans Administration (VA) mental health report card, the authors examined stability of report card rankings under different risk adjustment models. The study determined the impact of adding one variable to a standard VA risk adjustment model for access to care and examined whether veterans who reside in counties with VA facilities are more likely than veterans who reside in counties without VA facilities to use VA mental health services. METHODS: The authors compared the proportion of service users among veterans residing in counties either with or without VA facilities; the data were risk-adjusted by using demographic and geographic variables. A variable representing the presence or absence of a VA facility in each county was added to the risk adjustment model, and its impact on regional VA report card rankings for access was calculated. RESULTS: Regional rankings for access to mental health services by all veterans changed substantially when the additional variable was introduced into the risk adjustment model. Seven of 22 regions changed by five or more places. Access to mental health services was higher in counties with VA facilities, even after geographic distance to VA and non-VA hospitals was controlled for. CONCLUSIONS: Caution should be exercised when evaluating performance on the basis of report card rankings alone, even after risk adjustment. The results emphasize the importance of attending to observed and adjusted scores, along with standard deviations and standardized scores, rather than to rank order alone and highlight the need to educate report card users in their interpretation and limitations. County boundaries should be taken into consideration when planning VA mental health services.

Evaluation Studies as Topic↗
PubMed1998

The application of a risk-approach model to reduce mortality in infancy.

OBJECTIVES: To examine the utility of a risk-approach model in identifying infants at greater risk of postneonatal mortality (PNM) and to determine whether there is a relationship between PNM and linkage of at-risk infants to primary health care. METHODS: The Sheffield Birth Score instrument was applied to 90,846 newborn infants to determine high-score (HS) and low-score (LS) infant risk groups. Health care visit data were collected on all HS infants who were referred for primary pediatric care. Mortality rates were calculated for both HS and LS infant groups and for HS infants who were linked and not linked to care. RESULTS: The HS infant group was at significantly greater risk of PNM (p < 0.0001). The linked group had a lower PNM rate (p < 0.05), and linked/not-linked group differences were noted for 11 of 20 variables. When these 11 variables and the linked/not-linked variable were entered into a logistic regression analysis, linkage was the only significant variable (p < 0.01) in predicting PNM. CONCLUSIONS: The Sheffield Birth Score differentiated at birth those infants who were at greater risk of PNM. The lower incidence of PNM among linked HS infants suggests a promising argument for early pediatric intervention. Further research to clarify specific factors that influence health care participation decisions is suggested.

Humans↗
PubMed1995

MBS: a model for risk benefit analysis of breast cancer screening.

Breast cancer screening programmes employing mammography are being implemented in various European countries. Different screening protocols are used in demonstration projects and nationwide programmes. To evaluate and improve protocols, a computer model for the evaluation of breast cancer screening has been developed. The availability of such a model can be of great importance in obtaining a better insight into the influence of various parameters. The Monte Carlo computer model is based on random selection from distributions of relevant parameters including tumour onset, tumour growth rate, lifetime expectancy, tumour detection size for screening and spontaneous observation. The radiation risk is calculated for various screening protocols employing multiplicative and additive risk models combined with lifetime expectancy, number of females screened and absorbed dose per screening session. The benefit is calculated on the basis of the reduction in tumour size at detection due to screening compared with spontaneous observation and the survival as a function of tumour diameter. Data from the Swedish two-county study are used to validate the model in terms of prevalence, interval tumour rates and interval tumour diameter distributions. Except for the spontaneous tumour diameter distribution, the model can describe the Swedish two-county study. Specific information is presented on the distributions of relevant parameters.

Adult↗
PubMed2006

Combining the cost of reducing uncertainty with the selection of risk assessment models for remediation decision of site contamination.

The decision as to whether a contaminated site poses a threat to human health and should be cleaned up relies increasingly upon the use of risk assessment models. However, the more sophisticated risk assessment models become, the greater the concern with the uncertainty in, and thus the credibility of, risk assessment. In particular, when there are several equally plausible models, decision makers are confused by model uncertainty and perplexed as to which model should be chosen for making decisions objectively. When the correctness of different models is not easily judged after objective analysis has been conducted, the cost incurred during the processes of risk assessment has to be considered in order to make an efficient decision. In order to support an efficient and objective remediation decision, this study develops a methodology to cost the least required reduction of uncertainty and to use the cost measure in the selection of candidate models. The focus is on identifying the efforts involved in reducing the input uncertainty to the point at which the uncertainty would not hinder the decision in each equally plausible model. First, this methodology combines a nested Monte Carlo simulation, rank correlation coefficients, and explicit decision criteria to identify key uncertain inputs that would influence the decision in order to reduce input uncertainty. This methodology then calculates the cost of required reduction of input uncertainty in each model by convergence ratio, which measures the needed convergence level of each key input's spread. Finally, the most appropriate model can be selected based on the convergence ratio and cost. A case of a contaminated site is used to demonstrate the methodology.

Decision Making↗
PubMed1992

The inappropriateness of psycho-social models of risk behaviour for understanding HIV-related risk practices among Glasgow male prostitutes.

Much the most common models of HIV-related risk behaviour are those psychosocial models derived from studies of health behaviour and tested on large interview samples of American gay men. These models were not appropriate for understanding risk behaviour among 32 Glasgow male prostitutes. Whereas psycho-social models conceive of risk behaviour as volitional and individualistic, ethnographic data indicate that the male prostitutes' risk practices were constrained and emergent from the immediate circumstances of the sexual encounter. Unsafe sex was associated with client control. Safer sex was associated with countervailing prostitute strategies of influence. These data confirm the utility of self-empowerment approaches to health education.

Contraceptive Devices, Male↗
PubMed2001

Comparing alternative risk-adjustment models.

The use of mental health indicators to compare provider performance requires that comparisons be fair. Fair provider comparisons mean that scores are risk adjusted for client characteristics that influence scores and that are beyond provider control. Data for the study are collected from 336 outpatients receiving publicly funded mental health services in Washington State. The study compares alternative specifications of multiple regression-based risk-adjustment models to argue that the particular form of the model will lead to different conclusions about comparative treatment agency performance. In order to evaluate performance fairly it is necessary to not only incorporate risk adjustment, but also identify the most correct form that the risk-adjustment model should take. Future research is needed to specify; test, and validate the mental health risk-adjustment models best suited to particular treatment populations and performance indicators.

Adult↗
PubMed2006

Cost of caring for Medicare beneficiaries with Parkinson's disease: impact of the CMS-HCC risk-adjustment model.

Previous studies have demonstrated that Medicare risk-adjusted capitation models do not adequately compensate programs serving primarily disabled or frail populations. Using the Medicare Current Beneficiary Survey, we demonstrate that the Centers for Medicare and Medicaid Services-Hierarchical Condition Categories (CMS-HCC) model calculates Medicare capitation payments for Parkinson's patients more accurately than for the general population. The discrepancies between the predicted and actual expenditures estimated at various disability levels were smaller for Parkinson's patients than for other beneficiaries. If the CMS-HCC payment model were to apply to programs that draw a significant percentage of their participants from the Parkinson's disease community, these programs likely would be compensated fairly.

Aged↗
PubMed1991

Biologic basis for a risk assessment model for cleft palate.

A biologic model for palatogenesis is presented, intended as a basis for risk assessment. It comprises a sequence of developmental stages: growth and migration of neural crest cells, downward growth of palatal buds, elevation of palatal shelves, and differentiation of the epithelium followed by shelf fusion. Several events representing these stages and amenable to mathematical translation may be measurable in the form of biomarkers such as DNA and protein synthesis, phospholipid metabolism, and signal transducing systems. Interrupting components of the model will result in cleft palate. Teratogens with known mechanisms of action are compared with the model. The quantitative risk of cleft palate is conceived as a sequence of mathematical probabilities that any stage of the model runs an abnormal course. Stage-specific probabilities are determined by a chemical's potency and dose, and by duration of exposure and gestational age. Species or strain sensitivity may be expressed as quantitative differences in model parameters. Although the model is designed for cleft palate, the risk model may also estimate a multiple response risk to the same exposures.

Animals↗
PubMed2006

Recalibration of risk prediction models in a large multicenter cohort of admissions to adult, general critical care units in the United Kingdom.

OBJECTIVE: To assess the performance of published risk prediction models in common use in adult critical care in the United Kingdom and to recalibrate these models in a large representative database of critical care admissions. DESIGN: Prospective cohort study. SETTING: A total of 163 adult general critical care units in England, Wales, and Northern Ireland, during the period of December 1995 to August 2003. PATIENTS: A total of 231,930 admissions, of which 141,106 met inclusion criteria and had sufficient data recorded for all risk prediction models. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The published versions of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE II UK, APACHE III, Simplified Acute Physiology Score (SAPS) II, and Mortality Probability Models (MPM) II were evaluated for discrimination and calibration by means of a combination of appropriate statistical measures recommended by an expert steering committee. All models showed good discrimination (the c index varied from 0.803 to 0.832) but imperfect calibration. Recalibration of the models, which was performed by both the Cox method and re-estimating coefficients, led to improved discrimination and calibration, although all models still showed significant departures from perfect calibration. CONCLUSIONS: Risk prediction models developed in another country require validation and recalibration before being used to provide risk-adjusted outcomes within a new country setting. Periodic reassessment is beneficial to ensure calibration is maintained.

APACHE↗
PubMed1992

Polycystic ovary syndrome and risk for myocardial infarction. Evaluated from a risk factor model based on a prospective population study of women.

In order to estimate whether women with polycystic ovary syndrome (PCOS) have an increased risk of developing myocardial infarction, a risk factor model was applied on 33 women with PCOS and 132 age matched referents. The risk factor model was established from independent risk factors for myocardial infarction in a prospective population study of 1462 women in Göteborg, Sweden. The independent risk factors were age, manifest hypertension, manifest diabetes mellitus, central obesity measured as increased waist to hip circumference ratio and serum triglyceride concentration. A considerably increased risk (relative risk of 7.4) of developing myocardial infarction was observed for women with PCOS compared to age-matched referents. Since the risk factors include variables correlated to obesity, the results indicate that advice on dietary restriction is an important part of the treatment once the diagnosis is established.

Adult↗
PubMed2024

The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup.

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup. We define a metric called "expected PRS" (ePRS), the expected value of a PRS based on one's global or local admixture patterns. We further define the "residual PRS" (rPRS), measuring the deviation of the PRS from the ePRS. Simulation studies confirm that it suffices to adjust for ePRS to obtain nearly unbiased estimates of the PRS-outcome association without further adjusting for PCs. Using the TOPMed dataset, the estimated effect size of the rPRS adjusting for the ePRS is similar to the estimated effect of the PRS adjusting for genetic PCs. Similarly, we applied the ePRS framework to six cardiovascular-related traits in the All of Us dataset, and the results are consistent with those from the TOPMed analysis. The ePRS framework can protect from population stratification in association analysis and provide an equitable strategy to quantify genetic risk across diverse populations.

Journal Article↗
PubMed2006

Screening level risk assessment model for chemical fate and effects in the environment.

A screening level risk assessment model is developed and described to assess and prioritize chemicals by estimating environmental fate and transport, bioaccumulation, and exposure to humans and wildlife for a unit emission rate. The most sensitive risk endpoint is identified and a critical emission rate is then calculated as a result of that endpoint being reached. Finally, this estimated critical emission rate is compared with the estimated actual emission rate as a risk assessment factor. This "back-tracking" process avoids the use of highly uncertain emission rate data as model input. The application of the model is demonstrated in detail for three diverse chemicals and in less detail for a group of 70 chemicals drawn from the Canadian Domestic Substances List. The simple Level II and the more complex Level III fate calculations are used to "bin" substances into categories of similar probable risk. The essential role of the model is to synthesize information on chemical and environmental properties within a consistent mass balance framework to yield an overall estimate of screening level risk with respect to the defined endpoint. The approach may be useful to identify and prioritize those chemicals of commerce that are of greatest potential concern and require more comprehensive modeling and monitoring evaluations in actual regional environments and food webs.

Animals↗
PubMed1993

[Health diagnosis and health counseling. Traditional risk factors are not in the foreground!].

This article reviews the bio-psycho-social factors of health stabilization and health rehabilitation. It is our aim to improve psychology's and general medicine's cooperation in these fields of research and practice. We, therefore, firstly concentrate on the psychosocial factors which improve health diagnosing and health education; we illustrate health education by selectively reviewing illness-related health trainings. Secondly, we discuss health counseling. Again, we concentrate on the improvement of general practitioner's health counseling. On the one hand, this improvement seems possible on the basis of individual bio-psycho-social risk models. Individual bio-psycho-social risk models, on the other hand, only can serve as a basis for individual-centered interventions, but not for population-centered interventions. After reporting various case histories from different doctor-patient-interactions, we demonstrate the application of bio-psycho-social risk models in the individual case. These applications in the general practitioner's office promise to be useful. Nevertheless, general medicine as well as psychology seem to have only minor interest in intensifying their cooperation.

Aged↗
PubMed2005

Use of diagnosis-based risk adjustment models to predict individual health care expenditure under the National Health Insurance system in Taiwan.

BACKGROUND AND PURPOSE: Diagnostic information has been extensively studied and employed in the prediction of risk adjusted capitation payments in some countries. Nevertheless, few studies have been dedicated to the development of diagnosis-based risk adjusters in Taiwan. The purposes of this study were to develop outpatient diagnosis-based risk adjusters for a model of Taiwan's National Health Insurance (NHI) system and to evaluate the predictability of the risk adjustment models generated utilizing these adjusters. METHODS: Using a 2% random sample of 371,620 NHI enrollees, 5 risk adjustment models--i.e., demographic, inpatient diagnostic information outpatient diagnostic information, full diagnostic information, and prior utilization models--were evaluated with respect to predictive R2 and predictive ratios. While inpatient diagnosis-based risk adjusters were borrowed from previous research, outpatient diagnosis-based risk adjusters, referred to as Taiwan Ambulatory Spending Groups (TASGs), were developed based on 1996 claims data. RESULTS: The values of predictive R2 for the 5 risk adjustment models showed that the inclusion of outpatient diagnostic information considerably improved the predictability of the risk adjustment models for Taiwan's NHI system. Moreover, the predictive ratios revealed that the full diagnostic information model would reimburse different risk subgroups more fairly than the demographic, inpatient diagnostic information, and outpatient diagnostic information models and also outperform the prior utilization model with respect to disease risk groups. CONCLUSIONS: The risk adjustment model including the TASG risk adjusters can significantly improve predictability and can be employed to assess the NHI's current and proposed reform measures.

Capitation Fee↗
PubMedDate not supplied

Do clinicians follow a risk-sensitive model of capacity-determination? An experimental video survey.

The authors asked whether clinicians use a risk-sensitive model for decisional-capacity determinations; that is, whether a higher degree of capacity was required in higher-risk situations. The respondents were randomly assigned to view a videotaped "capacity" interview of a medication-randomized clinical trial scenario (N=52) or a neurosurgical clinical trial scenario (N=47). A significant scenario effect was mediated by the respondents' perception of scenario-specific risk. Respondents showed considerable disagreement within each scenario that was not explained by clinician-specific factors. Thus, clinicians, in fact, use the normative risk-sensitive model for capacity, but there remains considerable unexplained variability in their judgments.

Aptitude↗
PubMed1987

Cancer risk-assessment models: anticipated contributions from biochemical epidemiology.

Uncertainties in quantitative assessment of cancer risk limit the scientific role of this activity in the policy and regulatory debate on cancer control. Risk-assessment strategies and models are highly dependent on the nature and quality of the data available. However, accumulating laboratory and epidemiologic studies that are shedding new light on mechanisms of carcinogenesis have not yet been integrated into current risk-assessment models. Future developments in risk assessment may, therefore, be anticipated by considering the type of epidemiologic data that may soon be generated. Three important areas of epidemiologic and biochemical research should reduce some of the uncertainty in quantitative risk assessment by making it possible to: identify stages of the disease process through precursor lesions, biochemical markers, and to determine at which stage the carcinogen acts; identify subpopulations that are at enhanced or reduced susceptibility to carcinogenic influences; and obtain additional and refined indices of dose. Much of this research is being called "biochemical epidemiology." Strategies for incorporating these newly generated data into regulatory decisions vary from developing new mechanistically based mathematical models to applying existing models to biologically distinct subpopulations.

Carcinogens↗