\ud Tanzania Health Insurance Regulatory Framework Review\ud

Make sure that current policy objectives – achieving universal coverage, social health protection, good governance and cost-containment – are reflected in the relevant legislative documents, and provide the requisite legal tools, reflecting the chosen policy options and the institutional consequences of those options. Consider reducing the fragmentation of the health financing legislation which reflects the current fragmentation in health financing and in governance and oversight of the health financing and insurance systems. Develop an explicit policy on competition in health financing to close the current gaps in legislation and to prevent the possibly negative side effects for Tanzania citizens of such competition in the event that the Government of Tanzania (GOT) opts for a competition-based model of health financing. The model ultimately chosen will have consequences not only for health financing practise, but also for the relevant legislation. Consider the establishment of an independent accreditation body for external assessment and gradual improvement of the quality of care of all health services providers, regardless of their sources of financing. Plug the identified gaps in single enactments which can be done without embarking on any big policy changes. The latter can be included in the development of a planned National Health Financing Strategy. During this development process, it will be possible to focus on specific areas of interest and make detailed recommendations. After national adoption of the strategy, new legislation will have to be drawn up.\ud \u

Planting the Seeds for Public Health: How the Farm Bill Can Help Farmers to Produce and Distribute Healthy Foods

Analyzes provisions in the 2008 Farm Bill that impede farmers' production and strategic marketing of fruits and vegetables. Recommends policy changes to remove such barriers, improve consumer access to healthy foods, and help prevent childhood obesity

Managed Care- The First Chapter Comes to a Close

Introduction to the symposium, Managed Care: What\u27s the Prognosis: Managing Care in the Next Century

Insurer Climate Risk Disclosure Survey: 2012 Findings and Recommendations

2012 was the warmest year on record in the Lower 48 states and the second most extreme weather year in U.S. history. This is not a coincidence. Extreme weather -- stronger, more damaging storms, unprecedented drought and heat in some regions and unprecedented rainfall and flooding in others -- are the predictable consequences of rising global temperatures.Eleven extreme weather events each caused at least a billion dollars in losses last year in the United States. A single event, Hurricane Sandy, caused more than $50 billion in economic losses. Insurance companies are on the hook for tens of billions of dollars in claims as a result of Sandy and other severe weather events. And American taxpayers are on the hook for tens of billions of dollars themselves, thanks to losses sustained by the National Flood Insurance Program as well as disaster relief spendingThis raises a fundamental question: Is the insurance industry prepared? Have insurers analyzed and measured their climate-related risk? Are they planning for life in a warmer world? These should be essential questions for insurance regulators in all 50 states to be asking, and some are

The cognitive and affective antecedents to consumer behavior towards on-demand transportation services in Egypt

In the recent few years, smartphones have shaped and assisted in the creation of new business models to formulate and develop some additional dimensions such as shared-economy or shared-mobility. Since transportation is one of the most essential aspects of shared-economy, it is vital to this study to focus and investigate the consumers’ intention to use the new commuting services provided by Transportation Network Companies (TNCs) in Egypt. Consequently, this research aims to examine and understand the cognitive and affective antecedents to consumers’ behavior towards TNCs in Egypt. Therefore, the model of the Unified Theory of Acceptance and Use of Technology (UTAUT2) has been applied to understand and explain the factors that influence the behavioral intention (BI) to use TNCs services. The factors of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV), and Habit (HT) tested through surveying 200 respondents thru online (Google Forms) and offline (Self-Administered Questionnaires) techniques. The results showed that consumers’ intention to use TNCs services in Egypt, was positively affected by the factors of (performance expectancy, social influence, price value, and habit). However, the variables of (effort expectancy, facilitating conditions, and hedonic motivation) showed a negative influence on the intention to use TNCs services in Egypt. Thus, upon the evaluation of the gathered data and discovered findings, the market acceptance and share of TNCs services can be increased if these services considered the factors affecting the consumers\u27 intention that mentioned earlier

Empirical Evidence on the Use of Credit Scoring for Predicting Insurance Losses with Psycho-social and Biochemical Explanations

An important development in personal lines of insurance in the United States is the use of credit history data for insurance risk classification to predict losses. This research presents the results of collaboration with industry conducted by a university at the request of its state legislature. The purpose was to see the viability and validity of the use of credit scoring to predict insurance losses given its controversial nature and criticism as redundant of other predictive variables currently used. Working with industry and government, this study analyzed more than 175,000 policyholders’ information for the relationship between credit score and claims. Credit scores were significantly related to incurred losses, evidencing both statistical and practical significance. We investigate whether the revealed relationship between credit score and incurred losses was explainable by overlap with existing underwriting variables or whether the credit score adds new information about losses not contained in existing underwriting variables. The results show that credit scores contain significant information not already incorporated into other traditional rating variables (e.g., age, sex, driving history). We discuss how sensation seeking and self-control theory provide a partial explanation of why credit scoring works (the psycho-social perspective). This article also presents an overview of biological and chemical correlates of risk taking that helps explain why knowing risk-taking behavior in one realm (e.g., risky financial behavior and poor credit history) transits to predicting risk-taking behavior in other realms (e.g., automobile insurance incurred losses). Additional research is needed to advance new nontraditional loss prediction variables from social media consumer information to using information provided by technological advances. The evolving and dynamic nature of the insurance marketplace makes it imperative that professionals continue to evolve predictive variables and for academics to assist with understanding the whys of the relationships through theory development.IC2 Institut

Technology Assisted Choice in Medicare Part D Plan Selection

In 2006, the Centers for Medicare and Medicaid Services (CMS) implemented a new benefit for Medicare enrollees that was under schedule Part D of Medicare. This new benefit, known as Medicare Part D, covered prescription medications for enrollees in the Medicare programs. Medicare beneficiaries had to enroll in this new benefit to access this coverage. A new website, the Medicare Part D Plan Finder, was developed as part of this rollout to allow Medicare beneficiaries the opportunity to view available plan in their area and enroll in those plans. Several years after the original enrollment, several studies were conducted to examine the effectiveness of plan selection. The reviews looked at the financial costs and benefits of the current plans against the available plans for an enrollee. The switching rates for enrollees was not very active. This made the initial choice of plan more important, as once an enrollee signed up for a plan, there was a high level of “stickiness” to stay with that plan even as health circumstances might have changed, available plans might have changed, drug formularies could have been modified or current coverages and benefits were altered. These studies found that enrollees were paying more than they needed to pay because of this lack of switching behavior. Some of these behaviors were attributed to the way that plan information was 7 presented on the Medicare Plan Finder website, which saw the information as confusing, voluminous, and in some circumstances, incorrect. In 2019 a new version of the Medicare Part D Plan finder website was implemented. The new site incorporated feedback from enrollees, policy makers and health insurance experts. The intent was to create a tool that would allow consumers to better review and analyze information to assist them in making plan choices for Medicare Part D. This study used a discrete choice experiment to review and examine how individuals use the new site and if the information presented is helpful in determining the optimal plan choice for a hypothetical patient profile. Participants used a defined set of medications, pharmacy options and beneficiary location to establish a set of available plans. The Plan Finder tool was then used by the participants to select the optimal plan. A post experiment survey also collected information on the decision-making process, information used, the efficacy of the site, and the confidence in the decision. In the experiment, only 35% of the participants made an optimal Medicare Part D Plan choice. There were four groups with different levels of supporting information, as well as online and in-person support. The group that performed the best in determining the optimal plan choice was provided with high levels of information and instruction, but low levels of in-person or inline task support. 50% of this group correctly made the optimal plan choice. Individuals who were 65 or older, which is the target population for Medicare Part D plans, only had a 21% successful selection rate. An individual’s decision-making confidence was a predictor of successful plan selection and low decision making confidence was also predictive of incorrect optimal plan choice