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Purpose – This research has purposes to scrutinize over the role of premium income, expenses claim and underwriting results towards profitability of Indonesia Joint Enterprises Insurance Companies. Design/methodology/approach – The sample used is general insurance company that presents complete financial statements during 2018-2021 and listed by Otoritas Jasa Keuangan through its official website. Purposive sampling used as sampling technique with several samples are 48 data. Panel data regression used as analysis technique which then processed by Eviews-9 application. Findings – Its results showed that only underwriting results which significantly affect on profitability, while the others variables such as premium income had significantly negative affect on profitability so did with the expense claims which turn out had no affect towards profitability. At the level of significance (α = 0.05), it has small effect, while at the significance level of (α = 0.10), the expense claims seem had significant negative affect on profitability of Indonesia general insurance industry. Research limitations/implications – This research has certainly limitations such as the research object used relatively small only the joint general insurance companies which submitted complete financial reports which are listed by Otoritas Jasa Keuangan and followed by the company’s official website. Practical implications – This research indicates that those companies are noticed about an increase in premiums, but on the other hand they have also received many claims, therefore those premiums will be diverted to finance the claims which occur lately, then this certainly would decrease an income or profitability of the insurance company itself. Originality/value – This research also has a different research object and research period compared to previous research, therefore it can be used as a complement the research which have done before.

The health insurance industry has experienced a pronounced six-year cycle of earnings for nearly three decades—three years of profits followed by three years of losses. This profitability cycle triggers a turbulent pricing cycle. After reviewing three schools of thought about the causes of the cycle, in this article we examine new evidence to determine the probable impact on the cycle of a private-public, universal coverage, national health plan. We find no evidence of a cycle in the pricing and use of health care services. Since 1985, the relationship between the overall economy and health insurance trends has weakened. We conclude that the root causes of the cycle are essentially internal to the insurance industry, and, therefore, national health care reform will have little impact on the underwriting cycle.

The purpose of this paper is to describe an approach to gross premium calculations that has been used by the author in an attempt to provide students with a clearer understanding of the nature of the process. The system is designed primarily as a teaching device rather than as a description of the way in which life insurance companies actually calculate gross premiums. Assumptions are made about interest, mortality, lapsation, expenses, cash surrender values, dividends, and profit. Then the gross premium is calculated by solving a linear equation in one unknown.

This chapter contains sections titled: If work is delayed due to two or more competing causes of delay, often referred to as concurrent delays, one of which is the responsibility of the contractor/subcontractor or a neutral event and the other is a result of some fault of the architect, engineer or employer, is there an entitlement to an extension of time and loss and expense? Will a claim for an extension of time and the recovery of loss and expense which does not precisely detail the period of delay and the amount claimed in respect of each claim matter causing delay (i.e. a failure to link cause and effect), sometimes referred to as a global claim, fail? What is meant by a contractor or subcontractor having to ‘use constantly his best endeavours to prevent delay’; does it differ from ‘reasonable endeavours’? What is meant by ‘Time is of the Essence’? Where delays to completion of the works have occurred and disputes arise as to the appropriate extension of time which should be granted, is the employment of a computer‐based critical path analysis essential to establish the true entitlement?

Background: Many economic studies of disease require cost data at the person level to identify diagnosed cases and to capture the type and timing of specific services. One source of cost data is claims and other administrative records associated with health insurance programs and health care providers. Objective: To describe and compare strengths and limitations of various administrative and claims databases. Data and Methods: Data sources included claims and enrollment records from Medicare, Medicaid, and private insurers; Veterans' Health Administration records; state hospital discharge datasets; Healthcare Cost and Utilization Project hospital databases; managed care plan data systems; and provider cost reports. Claims provide information on payments, whereas cost reports yield resource costs incurred to produce services. Administrative data may be significantly augmented by linkage to disease registries and surveys. Results: Administrative data are often available for large, enrolled populations, have detailed information on individual service use, and can be aggregated by service type, episode, and patient. Service use and costs can often be tracked longitudinally. Because they are not collected for research purposes, administrative data can be difficult to access and use. Limitations include generalizability, complexity, coverage and benefit restrictions, and lack of coverage continuity. Linked datasets permit identification of incident cases of disease, and analyses of health care costs by stage at diagnosis, phase of care, comorbidity status, income, and insurance status. Conclusions: Administrative data are an essential source of information for studies of the financial burden of disease. Cost estimates can vary substantially by specific measures (payments, charges, cost to charge ratios) and across data sources.

The administrative costs of providing health insurance in the US are very high, but their determinants are poorly understood. We advance the nascent literature in this field by developing new measures of billing complexity for physician care across insurers and over time, and by estimating them using a large sample of detailed insurance \"remittance data\" for the period 2013-15. We found dramatic variation across different types of insurance. Fee-for-service Medicaid is the most challenging type of insurer to bill, with a claim denial rate that is 17.8 percentage points higher than that for fee-for-service Medicare. The denial rate for Medicaid managed care was 6 percentage points higher than that for fee-for-service Medicare, while the rate for private insurance appeared similar to that of Medicare Advantage. Based on conservative assumptions, we estimated that the health care sector deals with $11 billion in challenged revenue annually, but this number could be as high as $54 billion. These costs have significant implications for analyses of health insurance reforms.

Background: To improve access to outpatient services and provide financial support in outpatient expenses for the insured, China has been establishing its scheme of decreasing the out-of-pocket expenses for outpatient care in recent years. There are 156 million diabetes patients in China which almost accounts for a quarter of diabetes population worldwide. Outpatient services plays an important role in diabetes treatment. The study aims to clarify the effects of decreasing the out-of-pocket expenses for outpatient care on health-seeking behaviors, health outcomes and medical expenses of people with diabetes. Methods: This study constructed a two-way fixed effect model, utilized 5,996 diabetes patients’ medical visits records from 2019 to 2021, to ascertain the influence of decreasing the out-of-pocket expenses for outpatient care on diabetes patients. The dependent variables were diabetes patients’ health-seeking behaviors, health outcomes, medical expenses and expenditure of the basic medical insurance funds for them; the core explanatory variable was the out-of-pocket expenses for outpatient care expressed by the annual outpatient reimbursement ratio. Results: With each increase of 1% in the annual outpatient reimbursement ratio: (1) for health-seeking behaviors, a diabetes patient’s annual number of outpatient visits and annual number of medical visits increased by 0.021 and 0.014, while the annual number of hospitalizations decreased by 0.006; (2) for health outcomes, a diabetes patient’s annual length of hospital stays and average length of a hospital stay decreased by 1.2% and 1.1% respectively, and the number of diabetes complications and Diabetes Complications Severity Index (DCSI) score both decreased by 0.001; (3) for medical expenses, a diabetes patient’s annual outpatient expenses, annual inpatient expenses, annual medical expenses and annual out-of-pocket expenses decreased by 2.2%, 4.6%, 2.6% and 4.0%; (4) for expenditure of the basic medical insurance funds for a diabetes patient, the annual expenditure on outpatient services increased by 1.1%, and on inpatient services decreased by 4.4%, but on healthcare services didn’t change. Conclusion: Decreasing the out-of-pocket expenses for outpatient care appropriately among people with diabetes could make patients have a more rational health-seeking behaviors, a better health status and a more reasonable medical expenses while the expenditure of the basic medical insurance funds is stable totally.

This commentary explores the current state, challenges, and potential of artificial intelligence (AI) in health care revenue cycle management, emphasizing collaboration, data standardization, and targeted implementation to enhance adoption.

Hurricane Betsy, which hit Louisiana September 9, 1965, was one of the most intense, deadly, and costly storms ever to make landfall in the United States: it killed 76 people in Louisiana and caused$1.5 billion in damage—equal to nearly $ 10 billion in 2010 dollars. In 1965, no flood insurance was available, so victims had to rely on friends and family, charities, or federal relief. After that catastrophe, the U.S. government established a new program in 1968—the National Flood Insurance Program (NFIP)—to make flood insurance widely available. Now, after more than 40 years of operation, the NFIP is today one of the longest standing government-run disaster insurance programs in the world. In this paper, I present an overview of the 40 years of operation of the National Flood Insurance Program, starting with how and why it was created and how it has evolved to now cover$1.23 trillion in assets. I analyze the financial balance of the NFIP between 1969 and 2008. Excluding the 2005 hurricane season (which included Hurricane Katrina) as an outlier, policyholders have paid nearly $ 11 billion more in premiums than they have received in claim reimbursements over that period. However, the program has spent an average of 40 percent of all collected premiums on administrative expenses, more than three quarters of which were paid to private insurance intermediaries who sell and manage flood insurance policies on behalf of the federal government but do not bear any risk. I present challenges the NFIP faces today and propose ways those challenges might be overcome through innovative modifications.