Medical Premiums Research Articles

MEDICAL INSURANCE PREMIUM PREDICTION WITH MACHINE LEARNING

A machine learning method for predicting health insurance rates is presented in this article. With healthcare expenditures becoming more complex, it is critical for insurance companies and policyholders to accurately estimate insurance prices. Utilizing a dataset that included medical history, demographic data, and other pertinent variables, a variety of machine learning techniques, such as ensemble methods and regression, were used to create prediction models. R-Squared and mean absolute error were two measures used to assess these models' performance. According to the developed models' results, insurance premiums can be predicted with accuracy, offering useful information for insurance counteragents. This approach has the potential to optimize pricing strategies, enhance risk assessment, and improve decision-making in the healthcare insurance sector. Machine Learning-Based Prediction of Medical Insurance Premiums Make predictions about health insurance companies based on personal traits. A dataset of policyholder attributes (such as age, gender, BMI, number of children, smoking behaviors, and geography) was gathered and preprocessed .Divide the data into sets for testing and training. Create and train a model for an artificial neural network with TensorFlow and Karas. R-squared metrics and mean R-squared error were used to assess the performance of the model. created a high R-Squared predictive model that was accurate. determined the main determinants of insurance rates. Machine learning has shown promise in estimating healthcare costs. This experiment demonstrates how well machine learning predicts medical insurance rates. Insurance companies may offer more individualized insurance plans, expedite the underwriting process, and help customers make well-informed decisions about their healthcare coverage by creating these predictive models. The created model can help policyholders make educated judgments and insurance companies establish proper prices. In the long run, our research helps the insurance industry enhance data-driven techniques, which benefits insurers as well as insured individuals in general.

Medical Insurance Price Prediction Using Machine Learning

The escalating costs and complexities in the healthcare sector underscore the necessity for efficient predictive models to anticipate medical insurance prices. This study explores the application of machine learning techniques for forecasting medical insurance premiums, aiming to provide stakeholders with invaluable insights for pricing strategies and risk management. Using a comprehensive dataset encompassing demographic information, medical history, lifestyle factors, and insurance coverage details, various machine learning algorithms including regression, decision trees, random forests are employed and compared. Feature engineering techniques are applied to enhance model performance and interpretability, ensuring the inclusion of relevant predictors while mitigating overfitting. However, in recent years, the emergence of machine learning techniques has offered promising solutions to enhance medical insurance price prediction. This paper conducts an extensive review of various machine learning approaches utilized for this purpose, covering regression-based methods, time series forecasting techniques, ensemble methods, deep learning strategies, and hybrid models. We delve into the unique strengths, limitations, and practical applications of each technique. Moreover, we address the prevalent challenges associated with employing machine learning in medical insurance price prediction, such as data accessibility, feature selection, model interpretability, scalability, and generalization. Additionally, we look ahead to future research avenues and opportunities aimed at refining the accuracy and utility of machine learning models in predicting insurance prices. Through this comprehensive review, we aim to provide valuable insights for researchers, practitioners, and policymakers, facilitating informed decision-making in healthcare contexts through the utilization of machine learning methodologies.

Optimizing Healthcare Finance: A Predictive Modeling Approach to Medical Insurance Premium

Abstract: This research delves into optimizing healthcare finance through predictive modeling to forecast medical insurance premiums accurately. By harnessing a robust dataset and integrating advanced analytics, this study meticulously constructs models that allow insurance companies to price their policies competitively, ensuring both profitability and fairness. Employing a variety of machine learning algorithms, including linear regression, decision trees, random forests, and gradient boosting, we thoroughly assess the influence of critical factors such as age, BMI, gender, and regional healthcare costs on premium costs. Our analysis not only showcases the precision of predictive modeling in refining insurance pricing strategies and risk management but also illuminates its broader implications for the healthcare insurance sector. By systematically exploring the factors affecting premiums, identifying the most efficacious modeling techniques, and delineating the potential benefits for insurers and policyholders, this paper significantly contributes to the ongoing discourse on leveraging data-driven approaches to enhance the insurance industry's operational efficiency and promote equitable access to healthcare coverage.

ԱՌՈՂՋՈՒԹՅԱՆ ՀԱՄԱՊԱՐՓԱԿ ԱՊԱՀՈՎԱԳՐՈՒԹՅԱՆ ՀԱՄԱԿԱՐԳԻ ԱԶԴԵՑՈՒԹՅՈՒՆՆԵՐԸ ՀՀ ԲՆԱԿՉՈՒԹՅԱՆ ԵԿԱՄՈՒՏՆԵՐԻ ՆԵՐԱՌԱԿԱՆ ԲԱՇԽՄԱՆ ՈՒ ԱՆՀԱՎԱՍԱՐՈՒԹՅԱՆ ՀԱՂԹԱՀԱՐՄԱՆ ՀԱՄԱՏԵՔՍՏՈՒՄ / THE EFFECTS OF THE UNIVERSAL HEALTH INSURANCE SYSTEM IN THE CONTEXT OF INCLUSIVE DISTRIBUTION OF INCOME OF THE RA POPULATION AND OVERCOMING INEQUALITY

The purpose of the article is to discuss the possible social consequences of the implementation of the universal health coverage (UHC) system in the Republic of Armenia from the point of view of ensuring inclusiveness and to evaluate their possible effects on the incomes of different strata of the population. The problems of the research are related to the study of the issues of both quantitative and qualitative assessment of the effects caused by the introduction of UHC and the development of relevant recommendations for reforms in that context. During the research, statistical, inductive and deductive, analytical, simulation analysis methods were used. According to the results of the research, the introduction of UHC in the form proposed by the draft law will significantly increase the tax burden of taxpayers included in the lowest income groups of the population, in some cases even reaching up to the entire income. Within the framework of the research, it was substantiated that the Gini coefficient of income inequality before taxation in the Republic of Armenia is 0.5724, after taxation, taking into account only income tax, 0.5722, with the effects of other regressive components of labor taxation: social and stamp fees, 0.5911. And here, if we take into account the impact of the introduction of the Universal health coverage rate, the Gini coefficient after taxation will be 0.6088, which means that the inequality from the viewpoint of income distribution will be deepened even more with the introduction of this framework of the system. In order to solve the problems, identified within the framework of the research, it is proposed to introduce a progressive scale of mandatory medical insurance premiums, as well as to provide somewhat different mechanisms of state copayments (subsidies) for socially vulnerable and low-income groups of the population.

Machine learning for an explainable cost prediction of medical insurance

Predictive modeling in healthcare continues to be an active actuarial research topic as more insurance companies aim to maximize the potential of Machine Learning (ML) approaches to increase their productivity and efficiency. In this paper, the authors deployed three regression-based ensemble ML models that combine variations of decision trees through Extreme Gradient Boosting (XGBoost), Gradient-boosting Machine (GBM), and Random Forest (RF) methods in predicting medical insurance costs. Explainable Artificial Intelligence (XAi) methods SHapley Additive exPlanations (SHAP) and Individual Conditional Expectation (ICE) plots were deployed to discover and explain the key determinant factors that influence medical insurance premium prices in the dataset. The dataset used comprised 986 records and is publicly available in the KAGGLE repository. The models were evaluated using four performance evaluation metrics, including R-squared (R2), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results show that all models produced impressive outcomes; however, the XGBoost model achieved a better overall performance although it also expanded more computational resources, while the RF model recorded a lesser prediction error and consumed far fewer computing resources than the XGBoost model. Furthermore, we compared the outcome of both XAi methods in identifying the key determinant features that influenced the PremiumPrices for each model and whereas both XAi methods produced similar outcomes, we found that the ICE plots showed in more detail the interactions between each variable than the SHAP analysis which seemed to be more high-level. It is the aim of the authors that the contributions of this study will help policymakers, insurers, and potential medical insurance buyers in their decision-making process for selecting the right policies that meet their specific needs.

Have lower-income groups benefited more from increased government health insurance subsidies? Benefit incidence analysis in Ningxia, China.

China's government subsidies on the demand side-such as subsidizing medical insurance premiums-have accelerated progress towards universal health coverage. We examined whether the increased government subsidies had benefited the population, especially the poor. We conducted two rounds of household surveys and collected the annual claims reports of a rural medical insurance scheme in Ningxia (a relatively underdeveloped region in Western China). We used benefit incidence analysis to evaluate the distribution of benefits for different health services received by individuals with different living standards, as measured by the household wealth index. From 2009 to 2015, the benefit received per capita tripled from 101 to 332 CNY, most (>94%) of which was received for inpatient care. The overall distribution of benefits improved and became pro-poor in 2015 [the concentration index (CI) changed from -0.017 to -0.092], mainly driven by inpatient care. The poorer groups benefited disproportionately more from inpatient care from 2009 to 2015 (the CI changed from -0.013 to -0.093). County and higher-level inpatient care had the greatest improvements towards a pro-poor distribution. The distribution of subsidies for outpatient services significantly favoured the poorer groups in 2009, but less so in 2015 (CI changed from -0.093 to -0.068), and it became less pro-poor in village clinics (CI changed from -0.209 to -0.020). The increased government subsidies for the rural medical insurance scheme mainly contributed to inpatient care and allowed the poor to use more services at county and higher-level hospitals. China's government subsidies on the demand side have contributed to equity in benefit incidence, yet there is a noticeable increasing trend in utilizing services at higher levels of providers. Our findings also indicate that outpatient services need more coverage from rural medical insurance schemes to improve equity.

The Effects of Consuming Behaviors on Leisure Activities in Silver Market: Derivative Impacts for Related Industries

The prevention of health problems and ideas for successful aging have been major topics in many studies tue to the dramatic increase in the number of individuals age 65 and over worldwide. Despite awareness of the numerous benefits of increasing social and leisure activity levels, the association between the elders’ participation in leisure time physical activity and expenditure categories for understanding the silver market has remained largely unexplored. Therefore, in order to have a valuable information for promoting active lifestyle for the elders and gain a better insight of the effects of their monthly expenses in the current market, this study examined the responses from 1,389 Korean elders selected for 2018 Korean Longitudinal Study of Ageing (KLoSA). This study used SPSS to reveal the general tendencies and mean differences among expenses categories and implemented logistic regression to predict the significant factors influencing participation of leisure activities. The results of descriptive statistics showed that participants spent their money most on living expenses and least on family event, and the elders regularly participated in leisure activities spent more money compared to those who were not participated in leisure activities based on independent t-test. Moreover, the results of this study showed that increasing spending on eating out, medical insurance premium, and the cost of leisure was associated with an increased likelihood of participating leisure activities.

LEVERAGING THE HEALTH INSURANCE RATES MODELLING METHODS TO DEVISE A PREDICTIVE ANALYTICS MODEL TO ENHANCE THE HEALTH CARE FUNDS

The primary focus of this study is the development of predictive models for precise forecasts of medical insurance premiums, which aims to improve healthcare finance. The study creates models that enable insurance companies to price policies competitively while balancing fairness and profitability. A substantial dataset and cutting-edge analytics are used to achieve this. The review inspects the impact of critical factors like age, orientation, BMI, and local medical services costs on premium assessments, utilizing a scope of cutting-edge AI techniques, including slope helping, choice trees, irregular backwoods, and direct relapse. Predictive modelling has the potential to improve insurance pricing and risk management strategies, as shown by our findings. The report additionally highlights the useful ramifications for the medical care protection industry, featuring how information-driven methodologies can elevate impartial admittance to medical care and upgrade functional effectiveness. This research makes a significant contribution to the field of insurance analytics by examining the factors that influence premiums, determining the most efficient modelling methods, and outlining the significant benefits for both insurers and policyholders.

Clinical Characteristics of Elderly Chronic Myeloid Leukemia Patients in Korea; Based on the National Health Information Database

ObjectivesAging involves progressive impairments in the functional reserve of multiple organs, which might also affect drug metabolism and pharmacokinetics. Elderly might experience more drug adverse events than younger patients. Thus, we evaluated clinical characteristics and tyrosine kinase inhibitor (TKI) prescription pattern in Korean elderly chronic myeloid leukemia (CML) patients, using National Health Information Database “NHID”.MethodsThis study included patients 70 and older who were diagnosed with Philadelphia chromosome positive CML (ICD code C92.1) from 2005 to 2013 and prescribed TKIs (which included imatinib, dasatinib, nilotinib and radotinib which were covered by the National Health Insurance Service (NHIS), currently). We excluded following cases; ①TKI was prescribed just once ② TKI was started with a higher dose than the recommended for chronic phase (imatinib, 400mg QD; dasatinib, 100mg QD; nilotinib, 300mg BID; radotinib 300mg BID). ③ interferon was treated prior to TKI ④ TKI dosage data was missing. We extracted age, sex, medical insurance premium (which is imposed by proportionate to income), prescribed medication list, and date of death from NHID. Medication possession ratio (MPR) was used for adherence. Each patients' laboratory result, disease phase (chronic phase, accelerate phase, or blastic crisis), or the reasons for TKI change or dose reduction were not available.Overall survival (OS) was calculated by Kaplan-Meier methods. Additionally, Univariate and multivariate analysis were done with Cox proportional hazard regression, with following variables using SAS; sex (male vs female), age (70 ≤age<75, 75≤age<80, age≥80) medical insurance premium (high vs low), frontline TKI (imatinib vs other TKIs), and MPR (≥0.9 vs <0.9).ResultA total of 385 patients were followed up median 52 (1-133) months until the end of 2016. The patients consisted of 54% male (n=208), median age of 75 (70-95), and 64 patients (16.6%) who were diagnosed after the age of 80. About 85% of the patients experienced imatinib. Dasatinib was prescribed to 107 patients (27.8%), nilotinib to 71 (18.4%), and radotinib to 16 (4.2%). Frontline TKI was maintained in 279 (72.5%) patients, and the others were treated with more than one TKI; 2TKIs, n=80 (20.8%); 3TKIs, n=22 (5.7%); 4TKIs n=4 (1%). Imatinib was selected as frontline TKI in 318 patients (81.8%). Median MPR to TKI was 0.89 (0.00-1.84), and 51% of patients' MPR was less than 0.9. Patients were treated median 42 (0-146) months, and 186 (48.3%) were expired during the follow up period.Among 327 patients, 42 (12.8%) started with reduced dose of imatinib, and 285 (87.2%) started with imatinib 400mg QD. After median 2 (0-118) months, full dose imatinib reduced to mean 263mg±63 in 165 patients. Only 111 patients (34%) maintained imatinib. Dasatinib 100 mg was initiated in 89.9% (n=94) of 107 patients. Thirty patients (28%) did not change dasatinib dose. Others, reduced dose to mean 57±13mg after median 3 (0-33) months. Patients who were taking nilotinib or radotinib, full dose without dose reduction, were 31 (43%) and 7 (43%) respectively. Nilotinib was reduced to mean 325±62 after median 2(0-29) months, and radotinib to mean 357±162mg after median 4 (0-43) months.The estimated OS at 5-year was 60.3% and 10-year was 24.6%. For both univariate and multivariate analysis, age and MPR associated OS significantly; Patients aged 80 and older and from 75 to 80 showed poor OS than those aged from 70 to 75 through adjusted HR 2.67[95% CI.I, 1.81-3.93] (p<0.0001) and 1.81[95% C.I., 1.29-2.53] (p=0.0006), respectively. Patients with high MPR (≥0.9) survived longer than those with low MPR (<0.9), and its adjusted HR was 2.34 [95% C.I. 1.70-3.23] (p<0.0001).ConclusionBased on NHID, 10-50% of TKIs were initiated with reduced dose in age 70 and older CML patients. Full dose was maintained only 28-43% of prescribed TKIs. Despite of this, the outcome was favorable showing that because the estimated OS at 5-year was 60.3%. Age and adherence to TKI were associated with OS in elderly CML patients. DisclosuresNo relevant conflicts of interest to declare.

Adherence to Tyrosine Kinase Inhibitor Affects Overall Survival in Adult Korean Chronic Myeloid Leukemia Patients; Based on the National Health Information Database

ObjectivesWe evaluated clinical characteristics including adherence and its effects on overall survival (OS) in Korean patients diagnosed with chronic myeloid leukemia (CML) using National Health Information Database “NHID”.MethodsThis study included patients 15 and older who were diagnosed with Philadelphia chromosome positive CML (ICD code C921) from 2005 to 2013 and prescribed with tyrosine kinase inhibitors (TKIs). TKIs included imatinib, dasatinib, nilotinib and radotinib which were covered by the National Health Insurance Service (NHIS) currently.Patients who were received interferon, prescribed TKI only once, or prescribed TKI 6 months after diagnosis were excluded. We extracted age, sex, medical institution, medical insurance premium (which is imposed by proportionate to income), medication list, date of hematopoietic stem cell transplantation (HSCT), and date of death from NHID. Each patients' laboratory result or disease phase (chronic phase, accelerate phase, or blastic crisis) were not available. Medication possession ratio (MPR) was used for adherence. Overall Survival (OS) was calculated by Kaplan-Meier methods. As well as, univariate and multivariate analysis were done with Cox proportional hazard regression using SAS with following variables: Sex, age (≤50 years vs 50> years), income (high (upper 50%), low (lower 50%)), frontline TKI (imatinib vs others), and adherence (high (MPR ≥0.90), low (MPR<0.9)).ResultsA total of 3146 were followed up with a median of 69 (1-147) months until the end of 2016. Male was 60.2% (n=1899). Median age was 50 (16-92). More patients (n=1991, 62.9%) payed higher insurance premium. Imatinib was most frequently prescribed TKI (n=2764, 87.4%), then dasatinib (n=904, 28.6%), nilotinib (n=760, 24.0%), and radotinib (n=145, 4.6%) followed in orders. About two-thirds (n=2055, 65%) maintained frontline TKI until the end of follow up. Imatinib was selected as frontline TKI in 86.2% (n=3310), and 13.8% of patients chose newer generation TKIs. After TKI treatment, 7.7% of the patients received cytotoxic chemotherapy, and 19 patients underwent HSCT. Median MPR was 0.975 (0.003-2.035). A total 62% of patients (n=1966) showed high adherence. Male (p=0.036), young age (p<0.0001), high income (p=0.0002), using newer generation TKIs in the frontline (p<0.0001), and longer TKI treatment duration (p<0.0001) were associated with better adherence. Patients with low MPR performed chemotherapy (p<0.0001) or HSCT(p<0.0001) and expired (p<0.001) more than those with high MPR. Estimated OS at 5-year and 10-year were 84.7% and 75.3%, respectively. In univariate analysis, patients older than 50-years (HR 2.11 [95% C.I. 1.81-2.47] (Figure 1A) and low MPR (HR 6.34[95% CI 5.22-7.70] (Figure 1B) showed poor OS. In multivariate analysis, male, age >50, low MPR patients associated with poor OS showing HR 1.29 [95% C.I., 1.09-1.52], 2.98 [95% C.I., 2.49-3.58], and 6.13 [95% C.I., 5.04-7.45], respectively.ConclusionBased on NHID, estimated OS of 3146 Korean CML patients at 10-year was 75.3%, and female, age ≤50, and high MPR associated with better OS. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

High Time to Discuss Future-Oriented Telemedicine.

High Time to Discuss Future-Oriented Telemedicine.

Asphyxie périnatale et infirmité motrice d’origine cérébrale (II – Implications médico-légales et prévention)

Obstetric litigation is a growing problem in developed countries and its escalating cost together with increasing medical insurance premiums is a major concern for maternity service providers, leading to obstetric practice cessation by many practitioners. Fifty-four to 74 % of claims are based on cardiotocographic (CTG) abnormalities and their interpretation followed by inappropriate or delayed reactions. A critical analysis is performed about the nine criteria identified by the American College of Obstetricians and Gynecologists and the American Academy of Pediatrics in their task force on Neonatal Encephalopathy and Cerebral Palsy: four essential criteria defining neonatal asphyxia and five other suggesting an acute intrapartum event sufficient to cause cerebral palsy in term newborns. The importance of placental histologic examination is emphasized in order to confirm sudden catastrophic events occurring before or during labor or to detect occult thrombotic processes affecting the fetal circulation, patterns of decreased placenta reserve and adaptative responses to chronic hypoxia. It may also exclude intrapartum hypoxia by revealing some histologic patterns typical of acute chorioamnionitis and fetal inflammatory response or compatible with metabolic diseases. Magnetic resonance imaging (MRI) of the infant's damaged brain is very contributive to elucidate the mechanism and timing of asphyxia in conjunction with the clinical picture, by locating cerebral injuries predominantly in white or grey matter. Intrapartum asphyxia is sometimes preventable by delivering weak fetuses by cesarean sections before birth, by avoiding some “sentinel” events, and essentially by responding appropriately to CTG anomalies and performing an efficient neonatal resuscitation. During litigation procedures, it is necessary to have access to a readable CTG, a well-documented partogram, a complete analysis of umbilical cord gases, a placental pathology and an extensive clinical work-up of the newborn infant including cerebral MRI. Malpractice litigation in obstetric care can be reduced by permanent CTG education, respect of national CTG guidelines, use of adjuncts such as fetal blood sampling for pH or lactates, regular review of adverse events in Clinical Risk Management (CRM) groups and periodic audits about low arterial cord pH in newborns, admission to neonatal unit, the need for assisted ventilation and the decision-to-delivery interval for emergency operative deliveries. Considering the fast occurrence of fetal cerebral hypoxic injuries, and thus despite an adequate management, many intrapartum asphyxias will not be preventable. Conversely, well-documented hypoxic-ischemic brain insults during the antenatal period do not automatically exclude intrapartum suboptimal obstetric care.

Who should pay for assisted reproductive techniques? Answers from patients, professionals and the general public in Germany

Financing ART is variously regulated in the different countries of Europe. In Germany, coverage of assisted reproduction by statutory health insurances was restricted to 50% in 2004. We conducted a national survey among patients, professionals (physicians and other academics in IVF centres, psychosocial counsellors, medical ethicists, social lawyers, health politicians) and the general public in Germany regarding their opinions on financing ART. Standard questionnaire techniques (paper and pencil interviewing, computer-aided web interviewing, computer-aided telephone interviewing) were used. The vast majority of all groups supported public coverage of ART. Co-payments by patients were considered appropriate by about one-third of the patients, two-third of the physicians and three quarters of all other groups. According to the respondents, the amount of co-payment should cover 15-25% of the costs, considerably less than what patients actually have to pay (50%). Support for public coverage was strongly correlated with the views (i) of infertility as a disease, (ii) that there is a need for assisted reproduction for infertile couples and (iii) that every human should have the opportunity to have children. The respondents had varying opinions on whether to increase medical insurance premiums in order to cover ART. Reducing services in other areas of health care in favour of reproductive medicine was supported only by the group of reproductive physicians. Financial incentives for oocyte sharing were rejected by most groups as was a money-back guarantee for unsuccessful treatments. Experts and the general public in Germany accept moderate co-payments for ART. No clear pattern of opinion emerged regarding the question of how public co-funding should be financed.

Medical Insurance Coverage and Health Production Efficiency

ABSTRACT Conventional economic theory predicts that medical insurance coverage causes an inefficient production of health because of ex ante and ex post moral hazard effects. However, no research has empirically examined the magnitude of the inefficiency. This study empirically examines the impact of medical insurance on the technical efficiency of health production at the metropolitan level. The underlying health production function allows for preventive care, curative care, and behavioral factors. Data envelopment analysis determines relative technical efficiency. The multiple regression results indicate that insurance coverage generates inefficiency but the efficiency loss appears to be relatively small on the extensive margin. INTRODUCTION Among various issues, high medical care costs dominate much of the political debates taking place during the recent presidential election. Given that medical costs now comprise 16 percent of gross domestic product, the attention seems to be well deserved. However, many health economists and policymakers are not entirely convinced that the medical spending represents an economic burden on society. For example, Cutler and McClellan (2001) show that the aggregate benefits of just two major medical technologies outweighed all medical care costs during the last two decades. While medical care may pay for itself on average, conventional theory suggests that medical insurance may generate inefficiencies at the margin because of both ex ante and ex post moral hazard effects (Ehrlich and Becker, 1972; Breyer and Zweifel, 1997). Ex ante moral hazard refers to the effect of insurance on preventive actions taken before states of sickness occur, such as healthy lifestyles, preventive care, or early detection of diseases. In contrast, ex post moral hazard captures the size of the financial loss or cost of treatment because of insurance coverage and may show up in terms of longer hospitals stays and additional visits to health-care providers. If preventive and curative services are substitutes in the production of health, the theory generally views medical insurance as lowering the out-of-pocket price of curative inputs relative to the price of preventive inputs and thereby distorting the choice of inputs. Prevention declines, the probability of sickness rises, and an increased consumption of medical care occurs. The medical costs of maintaining a given level of health increase as a result. For example, Newhouse (1993) finds that households in low coinsurance health plans received more medical care yet possessed virtually the same level of health as those households in high coinsurance plans, ceteris paribus. Because of nine limiting conditions, however, some researchers note that medical insurance may not have a major impact on the efficiency of health production (Crew, 1969; Schlesinger and Venezian, 1986; Pauly and Held, 1990; Kenkel, 2000; Nyman, 2003; Dave and Kaestner, forthcoming). First, health-care providers may possess market power. The resulting restriction of output negates the typical ex post moral hazard effect of medical insurance towards overconsumption. Second, the ex ante moral hazard effect may be small because medical insurance does not completely cover the utility loss associated with sickness (pain and suffering). Third, preventive inputs may remain attractive because the choice of health inputs actually involves completely preventing versus incompletely curing illness. The attractiveness of preventive inputs, however, is limited by the fact that prevention can never reduce the probability of illness to zero. Fourth, medical insurance premiums may be risk-rated. While that might be true for individual medical insurance plans, it is not true for the employer-sponsored and public medical insurance plans that cover most people in the United States. Fifth, health insurers such as managed care organizations (MCOs) may invest directly in prevention to reduce the probability of a loss. …

Hedonic Damages – One More Time: A Symposium

On January 5, 2008, the National Association of Forensic Economics (NAFE) sponsored its third symposium on “hedonic damages,” this time entitled “Hedonic Damages – One More Time.” The first symposium on hedonic damages was presented at the December 1989 Allied Social Sciences meetings in Atlanta, Georgia with the title “Hedonic Damages and the Value of Life.” Papers from that session by W. Kip Viscusi, Ted R. Miller, Stan V. Smith, and William T. Dickens were published in Volume 3, No. 3 of this journal (1990). The second symposium on hedonic damages was presented at the January 2000 Allied Social Sciences meetings in Boston, Massachusetts with the title “Hedonic Damages Ten Years Later.” Papers from that session by W. Kip Viscusi, J. Paul Leigh and Jorge A. Garcia, Ted R. Miller, Stan V. Smith and Thomas R. Ireland, along with an introduction by Peter Marks and Thomas R. Ireland were published in Volume 13, No. 2 of this journal (2000). W. Kip Viscusi and Ted R. Miller returned as presenters for a third time at the January, 2008 symposium, along with Brian McDonald and John O. Ward. Thomas Ireland acted as the organizer of the 2008 symposium and Peter Marks served as its chair. The term “hedonic damages” first entered general public consciousness on December 12, 1988 with a front page story in the Wall Street Journal by Paul M Barrett on “The Price of Pleasure,” featuring Stan V. Smith and his successful presentation of hedonic damages testimony in the case of Sherrod v. Berry (1985, 1987, and 1988). Two federal judges in Illinois had commented favorably about Smith’s testimony in the original opinion and one of the appeals decisions before the case was reversed on other grounds in 1988. The NAFE symposium in December of 1989 was designed to explore this interesting new development in the field of forensic economics. As of the 2000 symposium hedonic damages testimony had enjoyed several successes in individual states, but had been rejected by the courts in a number of reported decisions, particularly at the federal level. The threat of Daubert and Frye standards for admission of expert testimony being applied negatively to hedonic damage testimony had become one of the central features in the debate over this concept. As of 2008 hedonic damages testimony had become much more specialized. Because hedonic damages testimony had been rejected in a number of legal decisions, fewer and fewer forensic economists were involved, but Stan Smith, Robert Johnson, Brian McDonald, as well as several other economic experts

Market Behaviour of Commercial Medical Insurance in China

Rationale: Commercial health insurance has emerged as an alternative solution to the problem of Chinese healthcare today. However, very little is known about the size of this market as well as its actuarial features. Objective: The study offers a quantitative accounting of commercial health business and identifies factors affecting the behaviour of health insurers in China given the national strategies to extend the population coverage of the medical insurance. Methodology: With the assistance of the insurance regulator, a survey of commercial insurers was conducted. A set of key indicators including premium income and loss ratios by product types was collected. Interviews and focus-groups of commercial insurers were organized to enrich our understanding behind the quantitative figures. Results: Total medical insurance premiums collected by commercial insurers were estimated to be USD1.5-1.8 million. Reimbursement plans constituted only 20% of the individual health insurance market while it is a mainstay in the group market (90%). Average claims per case and premiums per enrollee varied across different insurers. Without proper integration with social health plans organized by local governments, commercial plan does not seem to be commercially attractive, hindering the willingness of the industry to invest in the operational infrastructure. Conclusion: Public-private partnership is a global trend in healthcare reform today. Commercial insurers could offer a quick and quality solution to address the health financing problem in China. Only through removal of some obstacles in the business and regulatory environment can the private sector resources can be mobilized.

The Influence of the Current Medicolegal Climate on New South Wales Anaesthetic Practice

A survey was posted to all New South Wales and Provisional Fellows of the Australian and New Zealand College of Anaesthetists to assess the influence of the current medicolegal climate on their anaesthetic practice. Information collected included demographics, opinions regarding the current medico-legal climate, medical defence organizations, and the implications for anaesthetic practice. The response rate was 78% (640/820). Nearly all (95.3%) were concerned about the current medical indemnity crisis and 80.5% felt concerned about the financial security of medical insurers. Of all these respondents 23.6% had personal experience of litigation and 73.6% expected to have a claim made against them during their career: Respondents spent an average of 8.3% of their gross annual income on medical insurance premiums and 47.2% are concerned about the viability of their practice given the rising costs of medical insurance. Obstetric anaesthesia was the most common area of practice to be ceased due to medicolegal concerns. In the next two years, 20.2% of obstetric anaesthetists who responded intend to cease practice. In the past two years, 3.1% of respondents retired due to their litigation concerns, while 12.8% (average age 56.7y) are intending to retire in the next two years for the same reasons. Changes to the conduct of the preoperative consultation were common. Other changes to practice included more thorough documentation of complications (50.8%) and a strong reluctance to perform neuraxial blocks (54%). This survey suggests that anaesthetists are concerned about the current medicolegal climate and as a result, some are retiring earlier and giving up high-risk areas of practice.

Tax credits, insurance, and the use of medical care

Abstract. The personal income tax systems in Canada, the United States, and elsewhere permit deductions or tax credits for out‐of‐pocket health care expenditures and private medical insurance premiums. Little is known about the effects of such tax measures on individual behaviour, in contrast to the extensive research on the tax exemption for employer‐provided health insurance. In this paper, we exploit variation in the after‐tax cost of health expenditures under the tax law to estimate the tax price elasticity of demand for prescription drugs, health insurance, and other eligible expenditures. We find evidence of moderate to large tax price elasticities, compared with traditional point‐of‐service price elasticity estimates – despite the apparent differences in the way tax subsidies are experienced by consumers. In contrast, we find no evidence the tax subsidy affects demand for health insurance on the intensive margin, which we show is consistent with the theory of optimal self‐insurance. We discuss the implications of our results for recent proposals to reform public and private health insurance systems. JEL classification: I1, H2

Medical malpractice crisis: Florida's recent experience.

As summarized in several previous Circulation Mini-Reviews1–3 and elsewhere,4 the United States is experiencing a growing deficit in cardiovascular physicians that is made worse as cardiovascular diseases become more prevalent. Important contributors to this deficit in the cardiovascular workforce and other specialty workforces are the high and rising costs of malpractice premiums in the majority of our states.5 As cardiovascular specialists in Florida (cardiothoracic surgery and cardiology), we are at the center of this crisis. In the present review, we will examine the problem along with recent activities related to this crisis in Florida and discuss their implications. The American Medical Association stated in June 2002, that the majority (>40) of our states had major problems in that members of high-risk specialties were leaving or considering leaving their practices. Then–AMA President, Richard F. Corlin, MD, stated, “doctors are disappearing from American communities on a regular basis because of skyrocketing medical liability insurance premiums and an out-of-control legal system. As insurance becomes unaffordable or unavailable, and the legal system produces multi-million dollar jury awards on a regular basis, physicians are forced to limit services, leave practices, or relocate—all of which seriously impede patient access to high quality health care.” Florida (along with Georgia, Mississippi, Nevada, New Jersey, New York, Ohio, Oregon, Pennsylvania, Texas, Washington, and West Virginia) was among the 12 states considered to be at crisis level. According to the Department of Insurance in Florida, in 1975, total indemnity payments for professional liability cases were $10 271 090. By 2001, this had increased 3074% to a total indemnity payout of $326 052 228. A survey of comparative 2002 malpractice insurance premiums revealed that an invasive cardiologist in Los Angeles paid $16 148 for $1 000 000 coverage, whereas the same specialist in Miami paid $106 497, highest …

Managed mental health care: a home grown product.

Public non-profit mental health services the Mentally Ill (NAMI) found that 70% of businesses agreed with the concept of parhave been the last entities in health care to be affected by the managed care revoluity. Thirty-two percent of businesses surveyed have already made changes in order tion. Managed care companies have been greatly concerned that services to the to comply, and another 43% said they were in the process of complying. Only mentally ill involve unpredictable costs. This fear is driven, in part, by the preva2% thus far have sought a waiver, and only 1% in the survey intend to drop their menlence of severe and persistent mental illness, along with legislation in most states tal health coverage. Maryland has reported to the National that entitles severely mentally ill persons, through Medicaid entitlements, to receive Institute of Mental Health (1998) that the total medical premium has decreased by as much mental health service as is deemed medically necessary. Concomi0.2% following compliance with the parity law. After Minnesota had been under partantly, data are beginning to show that fears about unpredictable costs are unity for 1 year, Blue Cross/Blue Shield reduced the premium for small businesses founded in states that have begun to introduce mental health parity. The Mental from 6 to 5%. North Carolina implemented parity in 1992, and has seen a decrease in Health Parity Act of 1996 requires annual and lifetime benefits for mental illness that mental health payments, as a percentage of total health payments, from 6.4 to 3.4% (a are on a par with those offered by employers. Employers are exempt if they have 50 47% reduction). Clearly, these results have been achieved through careful manageor fewer employees and/or if the benefit raises health premiums more than 1%. ment of mental health resources. In spite of these successes, the public A survey by the National Alliance for mental health system has been slow to change. Supported by mental health tax dollars in most large urban centers, nonWalter Smitson, Ph.D., is President and CEO of profit mental health and substance abuse Central Clinic, Cincinnati, and is Professor in agencies have long guarded their individthe Department of Psychiatry, University of Cinual turfs, and have effectively resisted efcinnati College of Medicine. forts to enter the domain of painful Address for correspondence: Walter S. Smitson, Ph.D., Central Clinic, 3259 Elland Ave., change. Instead, many agency executives Cincinnati, OH 45229-2801. and their boards have often developed