Physician responses to insurance benefit restrictions: The case of ophthalmology.

This study examines the impact of social insurance benefit restrictions on physician behaviour, using ophthalmologists as a case study. We examine whether ophthalmologists use their market power to alter their fees and rebates across services to compensate for potential policy-induced income losses. The results show that ophthalmologists substantially reduced their fees and rebates for services directly targeted by the benefit restriction compared to other medical specialists' fees and rebates. There is also some evidence that they increased their fees for services that were not targeted. High-fee charging ophthalmologists exhibited larger fee and rebate responses while the low-fee charging group raise their rebates to match the reference price provided by the policy environment.

Preterm Birth and Total Health Care Use and Costs in the First 5 Years of Life: A Population-based Study.

OBJECTIVES: To investigate the relationship between preterm birth and hospital/out-of-hospital care and costs over the first 5 years of life. STUDY DESIGN: Birth data from a population-based cohort of 631 532 infants born between 2007 and 2013 were linked probabilistically with data on hospitalizations, primary and secondary care, and the use of medications. We analyzed the distribution of health care use and public health care costs for infants who survived at least 5 years, comparing the outcomes of extremely preterm (<28 weeks of gestation), very preterm (28-32 weeks), moderate to late preterm (32-37 weeks), and term infants (at least 37 weeks). A linear regression model was used to investigate the effect of preterm birth on these outcomes, controlling for important confounders including pregnancy and birth complications, neonatal morbidity, survival, and maternal socioeconomic characteristics. RESULTS: Preterm birth has a statistically significant and economically relevant effect on health care use and costs in the first 5 years of life. Compared with a term infant, preterm infants born at 32-36 weeks, 28-32 weeks, and <28 weeks of gestation had, respectively, an average of 7.0 (SE 0.06), 41.6 (0.18), and 68.7 (0.35) more hospital days; 3.1 (0.04), 11.0 (0.13), and 13.2 (0.25) more outpatient specialist physician visits; and 1.2-fold (<0.01), 6.8-fold (0.01), and 10.9-fold (0.02) higher 5-year public health care costs. Preterm infants also had statistically significantly higher levels of general practitioner visits and use of medications. CONCLUSIONS: Higher levels of accessible care are needed for preterm infants across health care settings and over sustained periods. As our understanding of the impact of preterm birth on long-term clinical outcomes continues to improve, clinicians and policymakers should develop an accurate recognition of these needs to enable appropriate resource allocation toward research priorities and early intervention strategies.

Private provider incentives in health care: The case of caesarean births.

Private doctors and hospitals face incentives to intervene in the process of childbirth because they are employed and paid differently from their public counterparts. While private obstetric care has been associated with higher rates of caesarean birth, it is unclear to what extent this is attributable to unobserved selection effects related to clinical need or patient preferences. Using administrative birth data on over 280,000 births in Australia between 2007 and 2012, we implement an instrumental variables framework to account for the endogeneity of choice of care. We also exploit Australia's institutional framework to examine the differences in doctor-level and hospital-level incentives. We find that giving birth in a private hospital leads to a 4 percentage point increase in the probability of having an unplanned caesarean birth. Over our study period, this equates to an additional 3241 caesarean births.

Health care use in response to health shocks: Does socio-economic status matter?

We investigate how utilization of primary care, specialist care, and emergency department (ED) care (and the mix across the three) changes in response to a change in health need. We determine whether any changes in utilization are impacted by socio-economic status. The use of a unique Australian data set that consists of a large survey linked to multiple years of detailed administrative records enables us to better control for individual heterogeneity and allows us to exploit changes in health that are related to the onset of two health shocks: a new diagnosis of diabetes and heart disease. We extend the analysis by also examining changes to patient out-of-pocket costs. We find significant differences in the mix between primary and specialist care use according to income and type of health shock but no evidence of using ED as a substitute for other care. Our results indicate that low- and high-income patients navigate very different pathways for their care following the onset of diabetes and to a lesser extent heart disease. These pathways appear to be chosen on the basis of ability to pay, rather than the most effective or efficient bundle of care delivered through a combination of GP and specialist care.

Birth models of care and intervention rates: The impact of birth centres.

Birth centres offer a midwifery-led model of care which supports a non-medicalised approach to childbirth. They are often reported as having low rates of birth intervention, however the precise impact is obscured because less disadvantaged mothers with less complex pregnancies, and who prefer and often select little intervention, are more likely to choose a birth centre. In this paper, we use a methodology that purges the impact of these selection effects and provides a causal interpretation of the impact of birth centres on intervention outcomes. Using administrative birth data on over 364,000 births in Australia's most populous state between 2001 and 2012, we implement an instrumental variables framework to address confounding factors influencing choice of birth setting. We find that giving birth in a birth centre results in significantly lower probabilities of intervention, and that critically, this impact has been increasing over time. Our estimates are larger than those in existing studies, reflecting our newer data, diverging intervention rates across birth settings, and our accounting for important selection effects. The results emphasise the greater role of birth centres in delivering on policy priorities which include greater maternal autonomy, lower intervention rates, and lower health system costs.

Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review.

BACKGROUND: Scale heterogeneity, or differences in the error variance of choices, may account for a significant amount of the observed variation in the results of discrete choice experiments (DCEs) when comparing preferences between different groups of respondents. OBJECTIVE: The aim of this study was to identify if, and how, scale heterogeneity has been addressed in healthcare DCEs that compare the preferences of different groups. METHODS: A systematic review identified all healthcare DCEs published between 1990 and February 2016. The full-text of each DCE was then screened to identify studies that compared preferences using data generated from multiple groups. Data were extracted and tabulated on year of publication, samples compared, tests for scale heterogeneity, and analytical methods to account for scale heterogeneity. Narrative analysis was used to describe if, and how, scale heterogeneity was accounted for when preferences were compared. RESULTS: A total of 626 healthcare DCEs were identified. Of these 199 (32%) aimed to compare the preferences of different groups specified at the design stage, while 79 (13%) compared the preferences of groups identified at the analysis stage. Of the 278 included papers, 49 (18%) discussed potential scale issues, 18 (7%) used a formal method of analysis to account for scale between groups, and 2 (1%) accounted for scale differences between preference groups at the analysis stage. Scale heterogeneity was present in 65% (n = 13) of studies that tested for it. Analytical methods to test for scale heterogeneity included coefficient plots (n = 5, 2%), heteroscedastic conditional logit models (n = 6, 2%), Swait and Louviere tests (n = 4, 1%), generalised multinomial logit models (n = 5, 2%), and scale-adjusted latent class analysis (n = 2, 1%). CONCLUSIONS: Scale heterogeneity is a prevalent issue in healthcare DCEs. Despite this, few published DCEs have discussed such issues, and fewer still have used formal methods to identify and account for the impact of scale heterogeneity. The use of formal methods to test for scale heterogeneity should be used, otherwise the results of DCEs potentially risk producing biased and potentially misleading conclusions regarding preferences for aspects of healthcare.

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.

We provide a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a 'way in' for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

Consideration Sets and Their Role in Modelling Doctor Recommendations About Contraceptives.

Decisions about prescribed contraception are typically the result of a consultation between a woman and her doctor. In order to better understand contraceptive choice within this environment, stated preference methods are utilized to ask doctors about what contraceptive options they would discuss with different types of women. The role of doctors is to confine their discussion to a subset of products that best match their patient. This subset of options forms the consideration set from which the ultimate recommendation is made. Given the existence of consideration sets we address the issue of how to model appropriately the ultimate recommendations. The estimated models enable us to characterize doctor recommendations and how they vary with patient attributes and to highlight where recommendations are clear and when they are uncertain. The results also indicate systematic variation in recommendations across different types of doctors, and in particular we observe that some doctors are reluctant to embrace new products and instead recommend those that are more familiar. Such effects are one possible explanation for the relatively low uptake of more cost effective longer acting reversible contraceptives and indicate that further education and training of doctors may be warranted. Copyright © 2015 John Wiley & Sons, Ltd.

Big Data: Will It Improve Patient-Centered Care?

Within a generation, empirical researchers have experienced unprecedented increases in the availability of data. 'Big data' has arrived with considerable hype and a sense that these are dramatic shifts in the research environment that have wide-reaching implications across many disciplines. There is no doubt that the analysis of new and varied sources of data currently available to researchers in health have the potential to better measure, monitor and describe health outcomes of patients and to uncover interesting patterns in how patients respond to treatments and interact with the health system. What is less clear is whether answers are readily available to more nuanced and substantive research questions. Here, the data-rich environment needs to be complemented by considerable research effort developing novel research designs and generating new and improved methods of analysis. Importantly, this will require researchers to be able to combine data from multiple sources and to be pro-active in data collection.

Hips and hearts: the variation in incentive effects of insurance across hospital procedures.

The separate identification of effects due to incentives, selection and preference heterogeneity in insurance markets is the topic of much debate. In this paper, we investigate the presence and variation in moral hazard across health care procedures. The key motivating hypothesis is the expectation of larger causal effects in the case of more discretionary procedures. The empirical approach relies on an extremely rich and extensive dataset constructed by linking survey data to administrative data for hospital medical records. Using this approach we are able to provide credible evidence of large moral hazard effects but for elective surgeries only.

Well-being losses due to care-giving.

This paper estimates the impact of informal caregiving on self-reported well-being. It uses a sample of 23,285 respondents of the first eleven waves of the Household, Income and Labour Dynamics in Australia (HILDA). We apply a relatively new analytical method that enables us to estimate fixed effects ordered logit to analyse subjective well-being. The econometric estimates show that providing informal care has a negative effect on subjective well-being. The empirical evidence of our paper could be helpful to inform policy makers to better understand the impact of caregiving and design the appropriate long term care policies and support services.

Preference heterogeneity and selection in private health insurance: the case of Australia.

A basic prediction of theoretical models of insurance is that if consumers have private information about their risk of suffering a loss there will be a positive correlation between risk and the level of insurance coverage. We test this prediction in the context of the market for private health insurance in Australia. Despite a universal public system that provides comprehensive coverage for inpatient and outpatient care, roughly half of the adult population also carries private health insurance, the main benefit of which is more timely access to elective hospital treatment. Like several studies on different types of insurance in other countries, we find no support for the positive correlation hypothesis. Because strict underwriting regulations create strong information asymmetries, this result suggests the importance of multi-dimensional private information. Additional analyses suggest that the advantageous selection observed in this market is driven by the effect of risk aversion, the ability to make complex financial decisions and income.

Explaining health care expenditure variation: large-sample evidence using linked survey and health administrative data.

Explaining individual, regional, and provider variation in health care spending is of enormous value to policymakers but is often hampered by the lack of individual level detail in universal public health systems because budgeted spending is often not attributable to specific individuals. Even rarer is self-reported survey information that helps explain this variation in large samples. In this paper, we link a cross-sectional survey of 267 188 Australians age 45 and over to a panel dataset of annual healthcare costs calculated from several years of hospital, medical and pharmaceutical records. We use this data to distinguish between cost variations due to health shocks and those that are intrinsic (fixed) to an individual over three years. We find that high fixed expenditures are positively associated with age, especially older males, poor health, obesity, smoking, cancer, stroke and heart conditions. Being foreign born, speaking a foreign language at home and low income are more strongly associated with higher time-varying expenditures, suggesting greater exposure to adverse health shocks.

The effect of adverse information and positive promotion on women's preferences for prescribed contraceptive products.

Recent rapid growth in the range of contraceptive products has given women more choice, but also adds complexity to the resultant decision of which product to choose. This paper uses a discrete choice experiment (DCE) to investigate the effect of adverse information and positive promotion on women's stated preferences for prescribed contraceptive products. In November 2007, 527 Australian women aged 18-49 years were recruited from an online panel. Each was randomly allocated to one of three information conditions. The control group only received basic information on contraceptive products. One treatment group also received adverse information on the risks of the combined oral pill. The other group received basic information and promotional material on the vaginal ring, newly introduced into Australia and on the transdermal patch, which is unavailable in Australia. Respondents completed 32 choice sets with 3 product options where each option was described by a product label: either combined pill, minipill, injection, implant, hormonal IUD, hormonal vaginal ring, hormonal transdermal patch or copper IUD; and by the attributes: effect on acne, effect on weight, frequency of administration, contraceptive effectiveness, doctor's recommendation, effect on periods and cost. Women's choices were analysed using a generalized multinomial logit model (G-MNL) and model estimates were used to predict product shares for each information condition. The predictions indicated that adverse information did not affect women's preferences for products relative to only receiving basic information. The promotional material increased women's preferences for the transdermal patch. Women in all groups had a low preference for the vaginal ring which was not improved by promotion. The findings highlight the need for researchers to pay attention to setting the context when conducting DCEs as this can significantly affect results.

What's good and bad about contraceptive products?: a best-worst attribute experiment comparing the values of women consumers and GPs.

BACKGROUND: In the past decade, the range of contraceptives available has increased dramatically. There are limited data on the factors that determine women's choices on contraceptive alternatives or what factors providers consider most important when recommending contraceptive products to women. OBJECTIVES: Our objectives were to compare women's (consumers') preferences and GPs' (providers') views in relation to existing and new contraceptive methods, and particularly to examine what factors increase the acceptability of different contraceptive products. METHODS: A best-worst attribute stated-choice experiment was completed online. Participants (Australian women of reproductive age and Australian GPs) completed questions on 16 contraceptive profiles. 200 women of reproductive age were recruited through a commercial panel. GPs from all states of Australia were randomly sampled and approached by phone; 162 GPs agreed to participate. Participants chose the best and worst attribute levels of hypothetical but realistic prescribed contraceptive products. Best and worst choices were modelled using multinomial logit and product features were ranked from best to worst according to the size of model coefficients. RESULTS: The most attractive feature of the contraceptive products for both GPs and women consumers were an administration frequency of longer than 1 year and light or no bleeding. Women indicated that the hormonal vaginal ring was the least attractive mode of administration. CONCLUSIONS: Women and GPs agree that longer-acting methods with less bleeding are important features in preferred methods of contraception; however, women are also attracted to products involving less invasive modes of administration. While the vaginal ring may fill the niche in Australia for a relatively non-invasive, moderately long-acting and effective contraceptive, the results of this study indicate that GPs will need to promote the benefits of the vaginal ring to overcome negative perceptions about this method among women who may benefit from using it.

Preferences for new and existing contraceptive products.

New contraceptive methods provide greater choice in terms of effectiveness, management of side-effects, convenience and frequency of administration and flexibility, but make the decisions about contraception more complex. There are limited data on the factors that determine women's choices among these alternatives, to inform providers about the factors which are most important to women, or to predict uptake of new products. This paper reports on a choice experiment designed to elicit women's preferences in relation to prescribed contraception and to forecast the impact of the introduction of two new products into the Australian market. A generalised multinomial logit model is estimated and used in the simulation exercise. The model forecasts that the hormonal patch would be well received among women, achieving a greater market share than current non-pill products, but the vaginal ring would have limited appeal.

Decisions about Pap tests: what influences women and providers?

Despite the success internationally of cervical screening programs debate continues about optimal program design. This includes increasing participation rates among under-screened women, reducing unnecessary early re-screening, improving accuracy of and confidence in screening tests, and determining the cost-effectiveness of program parameters, such as type of screening test, screening interval and target group. For all these issues, information about consumer and provider preferences and insight into the potential impact of any change to program design on consumer and provider behaviour are essential inputs into evidence-based health policy decision making. This paper reports the results of discrete choice experiments to investigate women's choices and providers' recommendations in relation to cervical screening in Australia. Separate experiments were conducted with women and general practitioners, with attributes selected to allow for investigation of how women and general practitioners differ in their preferences for attributes of screening programs. Our results indicate a considerable commonality in preferences but the alignment was not complete. Women put relatively more weight on cost, chance of a false positive and if the recommended screening interval were changed to one year.

Optimal recall length in survey design.

Self-reported data collected via surveys are a key input into a wide range of research conducted by economists. It is well known that such data are subject to measurement error that arises when respondents are asked to recall past utilisation. Survey designers must determine the length of the recall period and face a trade-off as increasing the recall period provides more information, but increases the likelihood of recall error. A statistical framework is used to explore this trade-off. Finally we illustrate how optimal recall periods can be estimated using hospital use data from Sweden's Survey of Living Conditions.

Using discrete choice experiments to investigate subject preferences for preventive asthma medication.

BACKGROUND AND OBJECTIVE: Long-term adherence to inhaled corticosteroids is poor despite the crucial role of preventer medications in achieving good asthma outcomes. This study was undertaken to explore patient preferences in relation to their current inhaled corticosteroid medication, a hypothetical preventer or no medication. METHODS: A discrete choice experiment was conducted in 57 adults with mild-moderate asthma and airway hyper-responsiveness, who were using inhaled corticosteroid

Why worry about awareness in choice problems? Econometric analysis of screening for cervical cancer.

The decision to undertake a screening test is conditional upon awareness of screening. From an econometric perspective there is a potential selection problem, if no distinction is made between aware and unaware non-screeners. This paper explores this problem through analysis of the determinants of cervical screening in Australia. Cervical cancer is one of the most preventable and curable forms of cancer. Since 1991 there has been a concerted effort in Australia to recommend and encourage women to have Pap smears every two years. The success of this program can be partly gauged by exploring the determinants of screening for cervical cancer. Using unit record data from the 1995 National Health Survey, an econometric model is developed for whether women have ever screened or not. A proportion of women in the sample contend that they have never heard of a Pap test. The analysis characterizes this group of women and accounts for their presence in the modelling. The paper demonstrates failing to model awareness can result in inconsistent parameter estimates even when the degree of censoring in the sample is relatively small.