Data Sources: I use the Healthcare Cost and Utilization Project’s Nationwide Inpatient Sample (NIS) from 2000 to 2011. The NIS is a 20% sample of all inpatient claims. The Manhattan Institute supplied data on the availability of health savings accounts in each state. State PTR implementation dates were gathered by Hans Christensen, Eric Floyd, and Mark Maffett of University of Chicago’s Booth School of Business by contacting the health department, hospital association, or website controller in each state.
Study Design: The NIS data was collapsed by procedure, hospital, and year providing averages for the dependent variable, Cost, and a host of covariates. Cost is a product of Total Charges within the NIS and the hospital’s Cost to Charge ratio. A new binary variable, PTR, was defined as ‘0’ if the year was strictly less than the disclosure website’s implementation date, ‘1’ for afterwards, and missing for the year of implementation. Then, using multivariate OLS regression with fixed effect modeling, the change in cost from before to after the year of implementation is estimated.
Principal Findings: The analysis estimates the effect of PTR to decrease the average cost per procedure by 7%. Specifications identify within state, within hospital, and within procedure variation, and reports that 78% of the cost decrease is due to within-hospital, within-procedure price discounts. An additional model includes the interaction of PTR with the prevalence of health savings accounts (hereafter, HSAs) and procedure electivity. The results show that PTR lowers costs by an additional 3 percent with each additional 10 percentage point increase in the availability of HSAs. In contrast, the cost reductions from PTR were much smaller for procedures more frequently coded as elective.
Conclusions: The study concludes price transparency regulations can lead to a decrease in a procedure’s costs on average, primarily through price discounts and slightly through lower cost procedures, but not due to patients moving to cheaper hospitals. This implies that hospitals are taking initiative and lowering prices as the competition’s prices become publically available suggesting that hospitals – not patients – are the biggest users of price transparency websites. Hospitals are also finding some ways to provide cheaper alternatives to more expensive procedures. State regulators should evaluate if a better metric other than charge prices, such as expected out-of-pocket payments, would evoke greater patient participation. Furthermore, states with higher prevalence of HSAs experience greater effects of PTR as expected since patients with HSAs have greater incentives to lower their costs. Patients should expect a shift towards plans that offer these types of savings accounts since they’ve shown to have a reduction of health costs on average per procedure in states with higher prevalence of HSAs.
Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.
Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.
Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.
Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.
Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables.
Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983–2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (− 95%) to an increase of 339 deaths per year (+ 359%).
Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.
Preventing heat-associated morbidity and mortality is a public health priority in Maricopa County, Arizona (United States). The objective of this project was to evaluate Maricopa County cooling centers and gain insight into their capacity to provide relief for the public during extreme heat events. During the summer of 2014, 53 cooling centers were evaluated to assess facility and visitor characteristics. Maricopa County staff collected data by directly observing daily operations and by surveying managers and visitors. The cooling centers in Maricopa County were often housed within community, senior, or religious centers, which offered various services for at least 1500 individuals daily. Many visitors were unemployed and/or homeless. Many learned about a cooling center by word of mouth or by having seen the cooling center’s location. The cooling centers provide a valuable service and reach some of the region’s most vulnerable populations. This project is among the first to systematically evaluate cooling centers from a public health perspective and provides helpful insight to community leaders who are implementing or improving their own network of cooling centers.
This study aims to examine the relationship between urban densification and pedestrian thermal comfort at different times of the year, and to understand how this can impact patterns of activity in downtown areas. The focus of the research is on plazas in the urban core of downtown Tempe, given their importance to the pedestrian landscape. With that in mind, the research question for the study is: how does the microclimate of a densifying urban core affect thermal comfort in plazas at different times of the year? Based on the data, I argue that plazas in downtown Tempe are not maximally predisposed to pedestrian thermal comfort in the summer or the fall. Thus, the proposed intervention to improve thermal comfort in downtown Tempe’s plazas is the implementation of decision support tools focused on education, community engagement, and thoughtful building designs for heat safety.