Home About us Contact
|
Home About us Contact | ||
|
|
||
Health Insurer (health + insurer)
Selected AbstractsThe intention to switch health insurer and actual switching behaviour: are there differences between groups of people?HEALTH EXPECTATIONS, Issue 2 2010Michelle Hendriks PhD Abstract Background, Several western countries have introduced managed competition in their health care system. In the Netherlands, a new health insurance law was introduced in January 2006 making it easier to switch health insurer each year. Objective, The objective was to measure people's intention to switch health insurer and actual switching behaviour. We also examined whether some groups were less inclined to switch health insurer and/or had more difficulty to exert their intention to switch. Design, In October 2006, members of three Dutch panels indicated whether they intended to switch health insurer during that year's open enrolment period. In the beginning of 2007, the same people were asked whether they indeed switched health insurer. Results, Only 1% intended to switch health insurer. Women, older people, lower educated people, people who were insured for a longer period and people who reported a bad or moderate health were less inclined to switch health insurer. The amount of switching was higher among individuals who intended to switch (31%) than among individuals who did not know whether they would switch (7%) and individuals with no intention to switch (2%). Among those who intended to switch health insurer, women and people who reported a good health switched health insurer more often. The years of enrolment were also associated with actual switching behaviour. Discussion and Conclusions, We might have to temper the optimistic expectations on enhanced choice. Future research should determine why people do not switch health insurer when they intend to and which barriers they experience. [source] Impact of Alternative Interventions on Changes in Generic Dispensing RatesHEALTH SERVICES RESEARCH, Issue 5 2006A. James O'Malley Objectives. To evaluate the effectiveness of four alternative interventions (member mailings, advertising campaigns, free generic drug samples to physicians, and physician financial incentives) used by a major health insurer to encourage its members to switch to generic drugs. Methods. Using claim-level data from Blue Cross Blue Shield of Michigan, we evaluated the success of four interventions implemented during 2000,2003 designed to increase the use of generic drugs among its members. Around 13 million claims involving seven important classes of drugs were used to assess the effectiveness of the interventions. For each intervention a control group was developed that most closely resembled the corresponding intervention group. Logistic regression models with interaction effects between the treatment group (intervention versus control) and the status of the intervention (active versus not active) were used to evaluate if the interventions had an effect on the generic dispensing rate (GDR). Because the mail order pharmacy was considered more aggressive at converting prescriptions to generics, separate generic purchasing models were fitted to retail and mail order claims. In secondary analyses separate models were also fitted to claims involving a new condition and claims refilled for preexisting conditions. Results. The interventions did not appear to increase the market penetration of generic drugs for either retail or mail order claims, or for claims involving new or preexisting conditions. In addition, we found that the ratio of copayments for brand name to generic drugs had a large positive effect on the GDR. Conclusions. The interventions did not appear to directly influence the GDR. Financial incentives expressed to consumers through benefit designs have a large influence on their switching to generic drugs and on the less-costly mail-order mode of purchase. [source] Development of a Scale to Measure Patients' Trust in Health InsurersHEALTH SERVICES RESEARCH, Issue 1 2002Article first published online: 18 MAR 200 Objective.,To develop a scale to measure patients' trust in health insurers, including public and private insurers and both indemnity and managed care. A scale was developed based on our conceptual model of insurer trust. The scale was analyzed for its factor structure, internal consistency, construct validity, and other psychometric properties. Data Sources/Study Setting.,The scale was developed and validated on a random national sample (n=410) of subjects with any type of insurance and further validated and used in a regional random sample of members of an HMO in North Carolina (n=1152). Study Design.,Factor analysis was used to uncover the underlying dimensions of the scale. Internal consistency was assessed by Cronbach's alpha. Construct validity was established by Pearson or Spearman correlations and t tests. Data Collection.,Data were collected via telephone interviews. Principal Findings.,The 11-item scale has good internal consistency (alpha=0.92/0.89) and response variability (range=11,55, M=36.5/37.0, SD=7.8/7.0). Insurer trust is a unidimensional construct and is related to trust in physicians, satisfaction with care and with insurer, having enough choice in selecting health insurer, no prior disputes with health insurer, type of insurer, and desire to remain with insurer. Conclusions.,Trust in health insurers can be validly and reliably measured. Additional studies are required to learn more about what factors affect insurer trust and whether differences and changes in insurer trust affect actual behaviors and other outcomes of interest. [source] The comparative safety of rosuvastatin: a retrospective matched cohort study in over 48,000 initiators of statin therapy,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 7 2006Andrew T. McAfee MD Abstract Purpose The purpose of this study was to compare incidence rates of hospitalization associated with rhabdomyolysis, myopathy, renal, or hepatic dysfunction, and of in-hospital death, between initiators of rosuvastatin and other statins. Methods This was a matched cohort study of statin initiators from the administrative database of a large health insurer in the US, during the first 6 months of rosuvastatin availability with up to 18 months of follow-up. All outcome events were verified by medical record review. Incidence rates, risk ratios, and associated 95% confidence intervals were estimated. Results From an initial pool of 12,217, 11,249 eligible rosuvastatin initiators were matched to 37,282 initiators of other statins. The incidence rate (IR) per 1000 person-years for rhabdomyolysis was 0.10 [0.00, 0.55] for rosuvastatin initiators (n,=,1) and 0.06 [0.01, 0.22] for other statin initiators (n,=,2), for a hazard ratio (HR) of 1.98 [0.18, 21.90]. The IR for myopathy was 0.20 [0.02, 0.71] for rosuvastatin initiators (n,=,2) and 0.00 [0.00, 0.09] for other statin initiators (n,=,0). The IR for renal dysfunction was 1.18 [0.61, 2.06] for rosuvastatin initiators (n,=,12) and 1.26 [0.91, 1.71] for other statin initiators (n,=,42), for a HR of 0.90 [0.47, 1.73]. The IR for hepatic dysfunction was 0.20 (0.02, 0.71) for rosuvastatin initiators (n,=,2) and 0.24 (0.10, 0.47) for other statin initiators (n,=,8), for a HR of 0.87 (0.18, 4.14). Conclusions This study found no difference between rosuvastatin and the other statins in the incidence of hospitalizations associated with renal or hepatic events, or death. The absolute incidence rates of rhabdomyolysis and myopathy were reassuringly low among all statin initiators but remain too small for firm conclusions to be drawn on any difference between the statins. Copyright © 2006 John Wiley & Sons, Ltd. [source] The Impact of Blue Cross Conversions on Accessibility, Affordability, and the Public InterestTHE MILBANK QUARTERLY, Issue 4 2003MARK A. HALL For-profit organization in health care delivery has been a major public policy issue least since at least the 1980s, driven by the growth of for-profit hospital chains and a wave of conversions by nonprofit hospitals. As significant as these events have been, however, they pale in comparison with the potential impact of conversions by Blue Cross and/or Blue Shield plans (which we refer to generically as Blue Cross, abbreviated BC). Because Blue Cross plans are the largest health insurer in almost every state (or substate region where they operate), these conversions could remake the corporate landscape of health care finance. Although BC plans no longer hold the overwhelming market share they enjoyed 50 years ago (when they commanded more than two-thirds of the commercial market; see Blackstone and Fuhr 1998), their share still is considerable. Blue Cross controls at least half the individual market in 33 states and more than a third of the group market in 29 states (Chollet, Kirk, and Chow 2000; McCann 2003). [source] Elasticities of market shares and social health insurance choice in germany: a dynamic panel data approachHEALTH ECONOMICS, Issue 3 2007Marcus Tamm Abstract In 1996, free choice of health insurers was introduced to the German social health insurance system. One objective was to increase efficiency through competition. A crucial precondition for effective competition among health insurers is that consumers search for lower-priced health insurers. We test this hypothesis by estimating the price elasticities of insurers' market shares. We use unique panel data and specify a dynamic panel model to explain changes in market shares. Estimation results suggest that short-run price elasticities are smaller than previously found by other studies. In the long-run, however, estimation results suggest substantial price effects. Copyright © 2006 John Wiley & Sons, Ltd. [source] Development of a Scale to Measure Patients' Trust in Health InsurersHEALTH SERVICES RESEARCH, Issue 1 2002Article first published online: 18 MAR 200 Objective.,To develop a scale to measure patients' trust in health insurers, including public and private insurers and both indemnity and managed care. A scale was developed based on our conceptual model of insurer trust. The scale was analyzed for its factor structure, internal consistency, construct validity, and other psychometric properties. Data Sources/Study Setting.,The scale was developed and validated on a random national sample (n=410) of subjects with any type of insurance and further validated and used in a regional random sample of members of an HMO in North Carolina (n=1152). Study Design.,Factor analysis was used to uncover the underlying dimensions of the scale. Internal consistency was assessed by Cronbach's alpha. Construct validity was established by Pearson or Spearman correlations and t tests. Data Collection.,Data were collected via telephone interviews. Principal Findings.,The 11-item scale has good internal consistency (alpha=0.92/0.89) and response variability (range=11,55, M=36.5/37.0, SD=7.8/7.0). Insurer trust is a unidimensional construct and is related to trust in physicians, satisfaction with care and with insurer, having enough choice in selecting health insurer, no prior disputes with health insurer, type of insurer, and desire to remain with insurer. Conclusions.,Trust in health insurers can be validly and reliably measured. Additional studies are required to learn more about what factors affect insurer trust and whether differences and changes in insurer trust affect actual behaviors and other outcomes of interest. [source] DSM-III and the revolution in the classification of mental illnessJOURNAL OF THE HISTORY OF THE BEHAVIORAL SCIENCES, Issue 3 2005Rick Mayes A revolution occurred within the psychiatric profession in the early 1980s that rapidly transformed the theory and practice of mental health in the United States. In a very short period of time, mental illnesses were transformed from broad, etiologically defined entities that were continuous with normality to symptom-based, categorical diseases. The third edition of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM-III) was responsible for this change. The paradigm shift in mental health diagnosis in the DSM-III was neither a product of growing scientific knowledge nor of increasing medicalization. Instead, its symptom-based diagnoses reflect a growing standardization of psychiatric diagnoses. This standardization was the product of many factors, including: (1) professional politics within the mental health community, (2) increased government involvement in mental health research and policymaking, (3) mounting pressure on psychiatrists from health insurers to demonstrate the effectiveness of their practices, and (4) the necessity of pharmaceutical companies to market their products to treat specific diseases. This article endeavors to explain the origins of DSM-III, the political struggles that generated it, and its long-term consequences for clinical diagnosis and treatment of mental disorders in the United States. © 2005 Wiley Periodicals, Inc. [source] Getting Real Performance Out of Pay-for-PerformanceTHE MILBANK QUARTERLY, Issue 3 2008SEAN NICHOLSON Context: Most private and public health insurers are implementing pay-for-performance (P4P) programs in an effort to improve the quality of medical care. This article offers a paradigm for evaluating how P4P programs should be structured and how effective they are likely to be. Methods: This article assesses the current comprehensiveness of evidence-based medicine by estimating the percentage of outpatient medical spending for eighteen medical processes recommended by the Institute of Medicine. Findings: Three conditions must be in place for outcomes-based P4P programs to improve the quality of care: (1) health insurers must not fully understand what medical processes improve health (i.e., the health production function); (2) providers must know more about the health production function than insurers do; and (3) health insurers must be able to measure a patient's risk-adjusted health. Only two of these conditions currently exist. Payers appear to have incomplete knowledge of the health production function, and providers appear to know more about the health production function than payers do, but accurate methods of adjusting the risk of a patient's health status are still being developed. Conclusions: This article concludes that in three general situations, P4P will have a different impact on quality and costs and so should be structured differently. When information about patients' health and the health production function is incomplete, as is currently the case, P4P payments should be kept small, should be based on outcomes rather than processes, and should target physicians' practices and health systems. As information improves, P4P incentive payments could be increased, and P4P may become more powerful. Ironically, once information becomes complete, P4P can be replaced entirely by "optimal fee-for-service." [source] | ||||||||||