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The purpose of this paper is to use results from a comprehensive analysis of a physician‐prescribing model to draw guidelines on how to promote a new drug in the presence of competing older drugs, in a chronic therapeutic state.

The authors use an extensive database from SDI Health, LLC, and a second data set from IMS Health. They calibrate their model using logarithmic regression methodology. The dependent variable in the model is number of new prescriptions and the explanatory variables are physician and patient characteristics, and marketing variables.

The authors' estimates imply that heavy prescribers are likely to be specialists, be in solo practice, have more experience, receive more sales rep traffic, have more HMO affiliations, have a higher proportion of patients in HMOs, write more prescriptions across all therapeutic categories, see a higher number of patients, receive more free samples from the sales reps, have more rep intensity in their offices, and allow longer visits by sales reps.

This model has novel implications for drug manufacturers on the effect of time‐in‐the‐market. Accordingly, new drug makers are well‐advised to wait until a drug gets established in the community for it to be prescribed more heavily by specialists and target physicians in solo practice and newer physicians to speed up the adoption process. Furthermore, for newer drugs traditional forms of detailing via a live sales rep are not as effective as for older more established drugs – the new‐drug manufacturer can try other means such as e‐detailing, social media, direct‐to‐consumer advertising, and word‐of‐mouth/mouse to initiate market share.

This paper focuses on Medicare risk contracting in the USA. The issue of the current method of reimbursement versus Medicare risk contracting is explored. Risk sharing and payment mechanisms are described and analyzed. The strengths and weaknesses (score‐ card) of Medicare beneficiaries entering HMOs are reviewed. Finally, the issue of selection bias in Medicare HMOs is discussed regarding future implementation strategy.

Asthma is a chronic inflammatory airways disease characterized by acute exacerbations interspaced by symptom‐free periods. Its management imposes a substantial burden on healthcare services, as well as personal suffering and significant financial tolls. The aim of this paper is to demonstrate links between routinely used computerized databases and to establish an automatic mechanism for monitoring asthma patients.

The study population was all adult subscribers to a major health maintenance organization (HMO) in Southern Israel (230,000 adults, age 20‐65 years). Relevant data for this retrospective analysis (2000 to 2004) were extracted from several computerized databases routinely used in the service: pharmacy; administrative; and each person's personal computerized medical file in the primary care clinic.

Based on data from 72 regional primary care clinics, during the study period, 11,054 adults were treated simultaneously by β₂ agonists and steroids – assumed to be asthmatics. In contrast, asthma diagnosis was recorded in only 4,061 personal files. The intersection between two databases yielded 2,569 persons recorded in both. These findings attest to the feasibility of developing computerized automatic surveillance systems for monitoring asthma patients with certain algorithms to assure service quality.

Data extracted from the various databases were unequal quality, a factor that imposed data management difficulties.

Similar surveillance systems can be developed relatively easily by using comparable algorithms for monitoring different chronic diseases or introducing management indices to secure quality of services.

The paper focuses on developing an automatic asthma monitoring model, using information from routinely used computerized HMO DBs.

Despite continuing debate about costs and benefits, managed care became an integral part of the health care sector during the 1990s. In this paper, we examine the organizational and practice variation in the managed care industry at two points in the 1990s using a national census of organizations operating in those years. We use a definition of managed care that captures the increased diversity within the industry while still distinguishing it from traditional indemnity, fee-for-service care. We draw on institutional theory to begin to formulate a framework for understanding why certain organizational forms and practices emerged when and where they did.

One of the fundamental tasks in optimal insurance design is mitigating the moral hazard effects inherent in insurance mechanisms. Empirically, relatively little is known about how individual-level time preferences affect selection of insurance options. We use several waves of the Health and Retirement Survey to explore the relationship between revealed time preferences at the individual level and the selection of insurance options for both the under-age-65 population and the Medicare-eligible population. Our results suggest that time preferences are not likely to be fixed across the life cycle, and that they appear to be important predictors of health insurance decisions.

Depression is a major public health problem. The distress and functional and social disability it causes are costly to individuals and families, the health care system, and society. The majority of depressed patients are treated by primary care clinicians. Understanding is limited about the factors that affect the pathway to outpatient care for depression in HMO settings. This study describes, among members of a large U.S. health maintenance organization (HMO), the predictors of outcomes that represent progress on the pathway to care for depression, focusing in particular on the relative contribution of depressive symptom levels, gender, age, and other medical and nonmedical factors. The study population is an age/sex stratified sample of HMO members aged 25+ (N=7,844). Data sources include member survey questionnaires, medical charts, and automated utilization databases. Data were collected during a baseline year prior to the members' survey response date (1990–1992) and a follow-up year after that date. The study outcomes measured during the followup year were; study subjects' use of primary medical care; chart notations by a primary care clinician of depression diagnoses, antidepressant prescriptions, and referrals to specialty mental health care; and use of specialty mental health care. Predictor variables included age, gender, level of depressive symptoms, social role functioning, mental health care history, general health status, baseline health care utilization, sociodemographic characteristics, and relation to a personal primary care clinician (and the specialty of that clinician).

Provides a review and analysis of Medicare health maintenance organizations in the USA. The Porter model of industry structure is used. Discusses the issues of suppliers, buyers, market entry and substitutes. Indicates there is currently no intense rivalry among Medicare risk‐based HMOs. However, the Porter model reveals crucial information regarding the forces which drive industry competition. Trends in the field of managed care and Medicare financing continue to be a real challenge regarding future research.

This study tests the effects of incomplete institutionalization in outpatient healthcare delivery settings on the quality and quantity of services provided after controlling for technical and agency factors. One dimension of quality (provider-patient contact time) and one dimension of quantity (number of services provided) were examined using the National Ambulatory Medical Care Survey for the year 2000. Regression models capture 27.8% and 36.4% of the variance in these respective dimensions (p<.001). The results reaffirm that uncertainty breeds variation and that ownership differences matter. From a management perspective, the regression model associated with provider-contact time has added utility in that a priori knowledge of certain variables might be used as decision support for provider (and service) scheduling.

This article examines the dialectics of wrongful life and wrongful birth claims in Israel from 1986 until 2012. In May 2012 Israeli Supreme Court declared that while wrongful birth claims were still permitted, wrongful life claims were no longer accepted in a court of law. The article examines the conditions that allowed for and supported the expansion of wrongful life/birth claims until 2012. The article identifies two parallel dynamics of expansion: a broadening of the scope of negligent conduct and a view of milder forms of disabilities as damage that merits compensation. The article further suggests four explanations for such doctrinal evolution, two of which emanate from doctrinal ambiguities and the other two are rooted in social factors that have shaped the meaning of disability as a tragedy and state of inferiority. While recent developments seem promising, the article concludes with a word of caution. Such changes may reproduce past injustices mainly because the compensation mechanism has remained an individual-torts based one, which may run counter to the broader struggle for social change for disabled people.

This volume of Advances in Management Accounting (AIMA) begins with a paper by Evans, Leone, and Nagarajan on non-financial performance measures, or quality-based incentives, in particular, in the healthcare industry. This study examines the economic consequences of non-financial measures of performance in contracts between Health Maintenance Organizations (HMOs) and primary care physicians (PCPs). The authors examine how quality provisions in HMO–PCP contracts affect utilization (patient length of stay in the hospital), patient satisfaction, and HMO costs. In the second paper, Shields and Shields review the research on revenue drivers by reference to five revenue-driver models in the accounting literature. The revenue drivers identified by quantitative empirical research are located in a revenue-driver model based on their levels of analysis (customer, product, organization, and industry) and other characteristics of a revenue driver–revenue relation.