Publications

2016
Kari A Stephens, Nicholas Anderson, Ching-Ping Lin, and Hossein Estiri. 2016. “Implementing partnership-driven clinical federated electronic health record data sharing networks.” International journal of medical informatics, 93, Pp. 26-33.
Hossein Estiri, Terri Lovins, Nader Afzalan, and Kari A Stephens. 2016. “Applying a Participatory Design Approach to Define Objectives and Properties of a “Data Profiling” Tool for Electronic Health Data.” AMIA Summits on Translational Science Proceedings, 2016, Pp. 60. Publisher's Version data_profiling.pdf
2015
Hossein Estiri. 2015. “Differences in Residential Energy Use between US City and Suburban Households.” Regional Studies, Pp. 1–12. Publisher's Version
Kari A Stephens, Sally E Lee, Hossein Estiri, and Hyunggu Jung. 2015. “Examining Researcher Needs and Barriers for using Electronic Health Data for Translational Research.” AMIA Summits on Translational Science Proceedings, 2015, Pp. 168–172. Publisher's VersionAbstract
To achieve the Learning Health Care System, we must harness electronic health data (EHD) by providing effective tools for researchers to access data efficiently. EHD is proliferating and researchers are relying on these data to pioneer discovery. Tools must be user-centric to ensure their utility. To this end, we conducted a qualitative study to assess researcher needs and barriers to using EHD. Researchers expressed the need to be confident about the data and have easy access, a clear process for exploration and access, and adequate resources, while barriers included difficulties in finding datasets, usability of the data, cumbersome processes, and lack of resources. These needs and barriers can inform the design process for innovating tools to increase utility of EHD. Understanding researcher needs is key to building effective user-centered EHD tools to support translational research.
Kari A Stephens, Sally E Lee, Hossein Estiri, and Hyunggu Jung. 2015. “Examining Researcher Needs and Barriers for using Electronic Health Data for Translational Research.” AMIA Summits on Translational Science Proceedings, 2015, Pp. 168.
Hossein Estiri. 2015. “The indirect role of households in shaping US residential energy demand patterns.” Energy Policy, 86, Pp. 585-594.
Hossein Estiri. 2015. “The indirect role of households in shaping US residential energy demand patterns.” Energy Policy, 86, Pp. 585–594.Abstract
About a quarter of US energy demand is for domestic use. Yet an understanding of the processes, determinants, and consequences of household energy demand remains elusive. Conventional energy policy has overwhelmingly focused on improving energy efficiency of the buildings. This research applies a non-linear methodology and an interdisciplinary approach to household energy demand. Using data from the US residential sector (2009 Residential Energy Consumption Survey), this research performs Covariance Structure Analysis to isolate direct and indirect effects of household and housing characteristics on total annual domestic energy use. Outcomes uncover some of households' indirect effects on energy demand, which in this research mainly happen through household effects on building characteristics, highlighting the indirect role of household choices in shaping residential energy demand patterns. To maximize its efficiency in reducing energy demand and GHG emissions, this paper suggests that in addition to investing in energy efficient technologies, energy policy should incorporate indirect effects of household choices on the configuration of their future homes.
Hossein Estiri, Andy Krause, and Mehdi P Heris. 2015. ““Phasic” metropolitan settlers: a phase-based model for the distribution of households in US metropolitan regions.” Urban Geography, 36, 5, Pp. 777-794.
Hossein Estiri, Andy Krause, and Mehdi P. Heris. 2015. ““Phasic” metropolitan settlers: a phase-based model for the distribution of households in US metropolitan regions.” Urban Geography, 36, 5, Pp. 777–794. Publisher's VersionAbstract
In this article, we develop a model for explaining spatial patterns in the distribution of households across metropolitan regions in the United States. First, we use housing consumption and residential mobility theories to construct a hypothetical probability distribution function for the consumption of housing services across three phases of household life span. We then hypothesize a second probability distribution function for the offering of housing services based on the distance from city center(s) at the metropolitan scale. Intersecting the two hypothetical probability functions, we develop a phase-based model for the distribution of households in US metropolitan regions. We argue that phase one households (young adults) are more likely to reside in central city locations, whereas phase two and three households are more likely to select suburban locations, due to their respective housing consumption behaviors. We provide empirical validation of our theoretical model with the data from the 2010 US Cen...
Hossein Estiri. 2015. “A structural equation model of energy consumption in the United States: Untangling the complexity of per-capita residential energy use.” Energy Research & Social Science, 6, Pp. 109–120. Publisher's VersionAbstract
Globally, about 20–30% of total energy demand is for residential use. Yet, our understanding of household energy consumption remains obscure. Due to methodological issues, conventional residential energy research has often failed to untangle the complexities of household energy use. In addition, theoretical deficiencies have led to underestimation of the complexities of households' role (vs. buildings' role) in residential energy use processes. This research hypothesizes that households have an indirect effect on energy use – through their housing choice behaviors – that can be untangled from buildings' effect. Using data from the latest Residential Energy Consumption Survey, this paper develops a Structural Equation Model to estimate the direct, indirect, and total effects of household and housing characteristics on per-capita residential energy use in the U.S. Outcomes support the research hypothesis and recommend that, when incorporating the housing choice effect, households' overall effect on energy use is larger than what has been perceived conventionally. Findings of this study provide a new approach to understanding residential energy use by highlighting the role of households and their housing choices in shaping residential energy consumption patterns. Policy makers can incorporate housing policy into energy policy and reduce residential energy consumption more effectively.
Hossein Estiri. 2015. “A structural equation model of energy consumption in the United States: Untangling the complexity of per-capita residential energy use.” Energy Research & Social Science, 6, Pp. 109–120.
Hossein Estiri, Ya-Fen Chan, Laura-Mae Baldwin, Hyunggu Jung, Allison Cole, and Kari A Stephens. 2015. “Visualizing anomalies in electronic health record data: the variability explorer tool.” AMIA Summits on Translational Science Proceedings, 2015, Pp. 56.
Hossein Estiri, Ya-Fen Chan, Laura-Mae Baldwin, Hyunggu Jung, Allison Cole, and Kari A Stephens. 2015. “Visualizing Anomalies in Electronic Health Record Data: The Variability Explorer Tool.” AMIA Summits on Translational Science Proceedings, 2015, Pp. 56–60. Publisher's VersionAbstract
As Electronic Health Record (EHR) systems are becoming more prevalent in the U.S. health care domain, the utility of EHR data in translational research and clinical decision-making gains prominence. Leveraging primay· care-based. multi-clinic EHR data, this paper introduces a web-based visualization tool, the Variability Explorer Tool (VET), to assist researchers with profiling variability among diagnosis codes. VET applies a simple statistical method to approximate probability distribution functions for the prevalence of any given diagnosis codes to visualize between-clinic and across-year variability. In a depression diagnoses use case, VET outputs demonstrated substantial variability in code use. Even though data quality research often characterizes variability as an indicator for data quality, variability can also reflect real characteristics of data, such as practice-level, and patient-level issues. Researchers benefit from recognizing variability in early stages of research to improve their research design and ensure validity and generalizability of research findings.
Hossein Estiri, Ya-Fen Chan, Laura-Mae Baldwin, Hyunggu Jung, Allison Cole, and Kari A Stephens. 2015. “Visualizing Anomalies in Electronic Health Record Data: The Variability Explorer Tool.” AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2015, Pp. 56–60. Publisher's VersionAbstract
As Electronic Health Record (EHR) systems are becoming more prevalent in the U.S. health care domain, the utility of EHR data in translational research and clinical decision-making gains prominence. Leveraging primay· care-based. multi-clinic EHR data, this paper introduces a web-based visualization tool, the Variability Explorer Tool (VET), to assist researchers with profiling variability among diagnosis codes. VET applies a simple statistical method to approximate probability distribution functions for the prevalence of any given diagnosis codes to visualize between-clinic and across-year variability. In a depression diagnoses use case, VET outputs demonstrated substantial variability in code use. Even though data quality research often characterizes variability as an indicator for data quality, variability can also reflect real characteristics of data, such as practice-level, and patient-level issues. Researchers benefit from recognizing variability in early stages of research to improve their research design and ensure validity and generalizability of research findings.
2014
Hossein Estiri. 2014. “Building and household X-factors and energy consumption at the residential sector.” Energy Economics, 43, Pp. 178–184. Publisher's VersionAbstract
Energy use in residential buildings is one of the major sources of greenhouse gas emission production from cities. Using microdata from the 2009 Residential Energy Consumption Survey (RECS), this study applies structural equation modeling to analyze the direct, indirect, and total impacts of household and building characteristics on residential energy consumption. Results demonstrate that the direct impact of household characteristics on residential energy consumption is significantly smaller than the corresponding impact from the buildings. However, accounting for the indirect impact of household characteristics on energy consumption, through choice of the housing unit characteristics, the total impact of households on energy consumption is just slightly smaller than that of buildings. Outcomes of this paper call for smart policies to incorporate housing choice processes in managing residential energy consumption.
Hossein Estiri. 2014. “Building and household X-factors and energy consumption at the residential sector.” Energy Economics, 43, Pp. 178–184. Publisher's Version
Hossein Estiri. 2014. “Building and household X-factors and energy consumption at the residential sector: a structural equation analysis of the effects of household and building characteristics on the annual energy consumption of US residential buildings.” Energy Economics, 43, Pp. 178-184.
Hossein Estiri. 2014. “The Impacts of Household Behaviors and Housing Choice on Residential Energy Consumption”.
Hossein Estiri. 2014. “The impacts of household behaviors and housing choice on residential energy consumption.” ProQuest Dissertations and Theses. Publisher's VersionAbstract
Despite efforts made in the past decade to curb excessive energy consumption and the corresponding greenhouse gas (GHG) emissions, both energy consumption and GHG emissions are expected to increase in coming years. Not only does such increasing trends epitomize the escalating, enduring human contribution to global warming, it verifies that our current policies are not working, at least not as well as expected or hoped. Globally, approximately a quarter of our total energy consumption is in the home, almost as much as in any other sector. Yet an understanding of the processes, determinants, and consequences of household energy consumption remains elusive. Conventional research on residential energy consumption has often applied linear methodologies and overwhelmingly focused on physical attributes of the housing stocks and systems. This approach, therefore, has failed: 1) to provide a coherent perspective of energy consumption processes, and 2) to account for the role of household behaviors. Accordingly, conventional energy policy has been left without the essential understanding of the phenomenon that would allow it to take effective action. To rectify issues with conventional research and policy, this research applies a non-linear and interdisciplinary approach to household energy consumption as an outcome of housing consumption and choice behaviors. Using data from the latest Residential Energy Consumption Survey, I use a set of Structural Equation Models to estimate the direct, indirect, and total effects of household and housing characteristics on energy use. Outcomes demonstrate that household characteristics have an indirect effect on energy consumption by influencing housing unit attributes, the housing choice effect on energy consumption. That is, a household's choice of housing unit has a permanent effect on the household's energy consumption, as an outcome, up until they relocate. Results of this study show that, accounting for the housing choice effects, the overall effect of household characteristics on energy consumption is almost twice as important as anticipated by conventional research. This study's findings highlight the role of housing choice and consumption behaviors in shaping residential energy consumption patterns. Energy consumption is expected to increase due to inevitable sociodemographic and economic changes. In addition to investing in improved building efficiencies and technologies, smart energy policies aimed at reducing energy consumption should promote more sustainable housing consumption behaviors and provide better housing choices.
Hossein Estiri, Andy Krause, and Mehdi P. Heris. 2014. “Lifecycle, Housing Consumption, and Spatial Distribution of Households across Metropolitan Regions: Evidence from Five U.S. Metropolitan Statistical Areas.” In Population Association of America. Publisher's Version

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