Yoko Ibuka

Using Game Theory to Examine Incentives in Influenza Vaccination Behavior

The social good often depends on the altruistic behavior of specific individuals. For example, epidemiological studies of influenza indicate that elderly individuals, who face the highest mortality risk, are best protected by vaccination of young individuals, who contribute most to disease transmission. To examine the conditions under which young people would get vaccinated to protect elderly people, we conducted a game-theory experiment that mirrored real-world influenza transmission, with “young” players contributing more than “elderly” players to herd immunity. Participants could spend points to get vaccinated and reduce the risk of influenza. When players were paid according to individual point totals, more elderly than young players got vaccinated, a finding consistent with the Nash equilibrium predicting self-interested behavior. When players were paid according to group point totals, however, more young than elderly players got vaccinated—a finding consistent with the utilitarian equilibrium predicting group-optimal behavior—which resulted in higher point totals than when players were paid for their individual totals. Thus, payout structure affected whether individuals got vaccinated for self-interest or group benefit.

Health-related activities in the American Time Use Survey.

Objectives:The Bureau of Labor Statistics’ American Time Use Survey (ATUS), launched in 2003, offers the first comprehensive look at how individuals spend their time. Health services researchers can use it to study time spent on a variety of health-related activities. We explain the surveys structure and provide an overview of the health-related activities reported by 34,693 respondents in 2003–2004. Methods:For the ATUS, computer-assisted phone interviewers ask respondents age 15 or older to report their activities during the day before the call (their “designated day”), including where they were and who was with them. Activities are assigned 6-digit codes, grouped into 17 major categories. Associated waiting and travel time have separate codes. Certain household types are oversampled to ensure reliable estimates. Results:In 2003–2004, 11.3% of American adults reported spending time (mean, 108 minutes) on activities related to health on their designated day. Some 5.6% reported personal health self-care (86 minutes); 3.4% reported medical and care services (123 minutes); and about 1% each reported activities related to the health of household children, household adults, and nonhousehold adults (78–115 minutes). The prevalence of health-care related activities rose with age. Sports, exercise, and recreation were reported by 17.6% of respondents (114 minutes), with men more likely than women to report these activities. Conclusions:The ATUS, a new publicly available resource, allows researchers to explore factors that influence time devoted to health-related activities, and the relationships among them and other activities, in a nationally representative sample.

Free-Riding Behavior in Vaccination Decisions: An Experimental Study

Individual decision-making regarding vaccination may be affected by the vaccination choices of others. As vaccination produces externalities reducing transmission of a disease, it can provide an incentive for individuals to be free-riders who benefit from the vaccination of others while avoiding the cost of vaccination. This study examined an individuals decision about vaccination in a group setting for a hypothetical disease that is called “influenza” using a computerized experimental game. In the game, interactions with others are allowed. We found that higher observed vaccination rate within the group during the previous round of the game decreased the likelihood of an individuals vaccination acceptance, indicating the existence of free-riding behavior. The free-riding behavior was observed regardless of parameter conditions on the characteristics of the influenza and vaccine. We also found that other predictors of vaccination uptake included an individuals own influenza exposure in previous rounds increasing the likelihood of vaccination acceptance, consistent with existing empirical studies. Influenza prevalence among other group members during the previous round did not have a statistically significant effect on vaccination acceptance in the current round once vaccination rate in the previous round was controlled for.

How Much Time Do Patients Spend on Outpatient Visits?: The American Time Use Survey

AbstractBackground: In Crossing the Quality Chasm, the Institute of Medicine recommended that patient-centered care should not waste patients’ time and should recognize the involvement of family and friends. Studies have documented the time spent by physicians on outpatient visits, but not that spent by patients and their companions. The patient’s perspective provides an important yet overlooked indicator of healthcare effectiveness Objective: To document how much time American patients spend on outpatient visits, for what purposes (travel, waiting, receiving services), and the time required of family members and friends Methods: We used data from the first 4 years (2003–6) of the American Time Use Survey (ATUS), conducted by the US Census Bureau for the Bureau of Labor Statistics, which asks respondents about their activities over a 24-hour period. ATUS is a nationally representative population-based survey that samples days continuously throughout the year. In 2003–6, 60 674 respondents aged ≥15 years were randomly selected from households that completed the Current Population urvey; 1621 reported seeking medical care for themselves on their survey day. We documented the percentage of the population that reported outpatient visits, the percentage who were accompanied to those visits and by whom, and the mean time spent by patients and their companions, by type of activity, and by age and sex Results: After weighting the data to represent the US population, we found that 3.4% of people aged ≥15 years reported traveling, waiting, or receiving services in connection with an outpatient visit on their survey day. The mean time for those who reported the activity was 35 minutes for travel (95% CI 33, 37), 42 minutes of waiting (95% CI 37, 47), and 74 minutes receiving services (95% CI 70, 79). Overall, 39.5% were accompanied, usually by family members. Companions spent a mean of 124 minutes per encounter (95% CI 112, 135). Nearly half of those aged ≥65 years were accompanied, almost always by adults only, suggesting that they may have needed help with transportation, negotiating the healthcare system, or performing cognitive and emotional tasks involved in receiving care Conclusion: Outpatient visits are time intensive for American patients and their families: the equivalent of 207 million 40-hour work-weeks each year. Patients and their families spend substantially more time on outpatient visits than the time with the physician reported by the annual National Ambulatory Medical Care Survey. Further research is needed on the components of outpatient visits that do not directly involve physicians. Efforts to improve care should address waiting times and recognize the involvement of family members. The ATUS could provide periodic benchmarks of patient time use as a supplement to other indicators of patient-centered care in the annual National Healthcare Quality Report

Real-time prescription surveillance and its application to monitoring seasonal influenza activity in Japan

Background Real-time surveillance is fundamental for effective control of disease outbreaks, but the official sentinel surveillance in Japan collects information related to disease activity only weekly and updates it with a 1-week time lag. Objective To report on a prescription surveillance system using electronic records related to prescription drugs that was started in 2008 in Japan, and to evaluate the surveillance system for monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons. Methods We developed an automatic surveillance system using electronic records of prescription drug purchases collected from 5275 pharmacies through the application service provider’s medical claims service. We then applied the system to monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons. The surveillance system collected information related to drugs and patients directly and automatically from the electronic prescription record system, and estimated the number of influenza cases based on the number of prescriptions of anti-influenza virus medication. Then it shared the information related to influenza activity through the Internet with the public on a daily basis. Results During the 2009–2010 influenza season, the number of influenza patients estimated by the prescription surveillance system between the 28th week of 2009 and the 12th week of 2010 was 9,234,289. In the 2010–2011 influenza season, the number of influenza patients between the 36th week of 2010 and the 12th week of 2011 was 7,153,437. The estimated number of influenza cases was highly correlated with that predicted by the official sentinel surveillance (r = .992, P < .001 for 2009–2010; r = .972, P < .001 for 2010–2011), indicating that the prescription surveillance system produced a good approximation of activity patterns. Conclusions Our prescription surveillance system presents great potential for monitoring influenza activity and for providing early detection of infectious disease outbreaks.

Inventory of data sources for estimating health care costs in the United States.

Objective:To develop an inventory of data sources for estimating health care costs in the United States and provide information to aid researchers in identifying appropriate data sources for their specific research questions. Methods:We identified data sources for estimating health care costs using 3 approaches: (1) a review of the 18 articles included in this supplement, (2) an evaluation of websites of federal government agencies, non profit foundations, and related societies that support health care research or provide health care services, and (3) a systematic review of the recently published literature. Descriptive information was abstracted from each data source, including sponsor, website, lowest level of data aggregation, type of data source, population included, cross-sectional or longitudinal data capture, source of diagnosis information, and cost of obtaining the data source. Details about the cost elements available in each data source were also abstracted. Results:We identified 88 data sources that can be used to estimate health care costs in the United States. Most data sources were sponsored by government agencies, national or nationally representative, and cross-sectional. About 40% were surveys, followed by administrative or linked administrative data, fee or cost schedules, discharges, and other types of data. Diagnosis information was available in most data sources through procedure or diagnosis codes, self-report, registry, or chart review. Cost elements included inpatient hospitalizations (42.0%), physician and other outpatient services (45.5%), outpatient pharmacy or laboratory (28.4%), out-of-pocket (22.7%), patient time and other direct nonmedical costs (35.2%), and wages (13.6%). About half were freely available for downloading or available for a nominal fee, and the cost of obtaining the remaining data sources varied by the scope of the project. Conclusions:Available data sources vary in population included, type of data source, scope, and accessibility, and have different strengths and weaknesses for specific research questions.

How Much Time Do Adults Spend on Health-related Self-care? Results from the American Time Use Survey

Background: The amount of time individuals spend on health-related self-care is not known. Objective: The aim of this study was to describe how much time American adults reported spending on health-related self-care (eg, taking insulin, dressing a wound). Methods: We analyzed data from the first 5 years, 2003 to 2007, of the population-based American Time Use Survey. Of 64,310 respondents 25 years of age and older, 4267 reported 7022 episodes of health-related self-care on their survey day. We used descriptive statistics, weighted to represent US adults, to describe self-reported time and logit regressions to analyze the odds of engaging in self-care as a function of age, sex, race, and other characteristics. Because health status was collected only in 2006 to 2007, analyses were conducted separately for 2003 to 2007 and 2006 to 2007. Results: Of Americans 25 years of age and older, 6.6% engaged in health-related self-care each day. Among those reporting self-care, mean time reported was 90 minutes (median, 15 minutes); 20.6% reported 2 hours or more. Regressions for 2006 to 2007 show that people aged 75 or older were 3.9 times as likely (95% CI, 2.7–5.8) to report self-care as persons aged 25 to 44. Compared with persons in excellent health, those in fair health were 2.0 times as likely (95% CI, 1.4–2.8) and those in poor health were 3.7 times as likely (95% CI, 2.5–5.6) to report engaging in self-care. Nonworking disabled persons reported self-care 4 times (95% CI, 3.1–5.3) as often as employed persons. Sex, race/ethnicity, presence of children, and body mass index were also significant. Conclusions: Time spent on health-related self-care is disproportionately distributed across the population, with a larger amount of time reported by those in poor health (3.6 hours/week) and the nonworking disabled (3.2 hours/week). To provide patient-centered care and to promote optimal decisions about health-related time management when making recommendations for additional self-care tasks, clinicians need to talk to patients about how much time they are already spending on self-care.

Social contacts, vaccination decisions and influenza in Japan

Background Contact patterns and vaccination decisions are fundamental to transmission dynamics of infectious diseases. We report on age-specific contact patterns in Japan and their effect on influenza vaccination behaviour. Methods Japanese adults (N=3146) were surveyed in Spring 2011 to assess the number of their social contacts within a 24 h period, defined as face-to-face conversations within 2 m, and gain insight into their influenza-related behaviour. We analysed the duration and location of contacts according to age. Additionally, we analysed the probability of vaccination and influenza infection in relation to the number of contacts controlling for individuals characteristics. Results The mean and median reported numbers of daily contacts were 15.3 and 12.0, respectively. School-aged children and young adults reported the greatest number of daily contacts, and individuals had the most contacts with those in the same age group. The age-specific contact patterns were different between men and women, and differed between weekdays and weekends. Children had fewer contacts between the same age groups during weekends than during weekdays, due to reduced contacts at school. The probability of vaccination increased with the number of contacts, controlling for age and household size. Influenza infection among unvaccinated individuals was higher than for those vaccinated, and increased with the number of contacts. Conclusions Contact patterns in Japan are age and gender specific. These contact patterns, as well as their interplay with vaccination decisions and infection risks, can help inform the parameterisation of mathematical models of disease transmission and the design of public health policies, to control disease transmission.

Who got vaccinated against H1N1 pandemic influenza? – A longitudinal study in four US cities

The recent H1N1 pandemic influenza stimulated numerous studies into the attitudes and intentions about the H1N1 vaccine. However, no study has investigated prospective predictors of vaccination behaviour. We conducted a two-wave longitudinal study among residents in four US cities during the course of the H1N1 outbreak, using Internet surveys to assess demographic, cognitive and emotional predictors of H1N1 vaccination behaviour. Surveys were conducted at two time points, before (Time 1) and after (Time 2) the H1N1 vaccine was widely available to the public. Results show that Time 2 vaccination rates, but not Time 1 vaccination intentions, tracked H1N1 prevalence across the four cities. Receipt of seasonal influenza vaccine in the previous year, worry, compliance with recommended interventions, household size and education assessed at Time 1 were significant prospective predictors of vaccination behaviour. Perception of the H1N1 vaccine, social influence and prioritised vaccine recipient status assessed at Time 2 also predicted vaccination behaviour. Critically, worry about H1N1 mediated the effects of both objective risk (prevalence at the city level) and perceived risk on vaccination behaviour. These results suggest that H1N1 vaccination behaviour appropriately reflected objective risk across regions, and worry acted as the mechanism by which vaccination behaviour followed objective risk.

The Stabilization of an Open Economy with Capital Controls: An Analysis Using Malaysian Data

The purpose of this paper is to analyze the effectiveness of capital controls and fixed exchange rates in improving economic welfare. We apply Malaysian data to our theoretical model and derive the following results for the period of our estimation. High exchange rate volatility negatively affects Malaysian net exports and real GDP. By stabilizing the exchange rate and recovering monetary policy autonomy, capital controls and fixed exchange rates can lead to lower values of loss functions. This beneficial effect is stronger, the more open the Malaysian economy.