An official website of the United States government
Patients with multiple chronic conditions and social needs represent a small percentage of the population but have a disproportionate impact on healthcare costs and utilization. Organizations around the United States have created programs, often referred to as complex care interventions, to improve the health and well-being of such patients and reduce avoidable hospital and emergency department use. In this tutorial, we focus on two emerging themes in the field: (1) identifying clinically meaningful subgroups in complex care populations through unsupervised learning methods and (2) describing the key operational features of interventions with an emphasis on staffing needs and the impact on patient outcomes. The material presented in this tutorial draws on the research of the Healthcare Operations Research Laboratory at the University of Massachusetts, Amherst, and its collaborating partners. To illustrate these themes and contextualize the details of complex care delivery, we use a range of patient-level examples, visualizations, descriptive summaries, case studies, and results from the clinical literature.
more »
« less
Environmental impact reduction as a new dimension for quality measurement of healthcare services: The case of magnetic resonance imaging
Purpose The purpose of this paper is to provide a detailed accounting of energy and materials consumed during magnetic resonance imaging (MRI). Design/methodology/approach The first and second stages of ISO standard (ISO 14040:2006 and ISO 14044:2006) were followed to develop life cycle inventory (LCI). The LCI data collection took the form of observations, time studies, real-time metered power consumption, review of imaging department scheduling records and review of technical manuals and literature. Findings The carbon footprint of the entire MRI service on a per-patient basis was measured at 22.4 kg CO 2 eq. The in-hospital energy use (process energy) for performing MRI is 29 kWh per patient for the MRI machine, ancillary devices and light fixtures, while the out-of-hospital energy consumption is approximately 260 percent greater than the process energy, measured at 75 kWh per patient related to fuel for generation and transmission of electricity for the hospital, plus energy to manufacture disposable, consumable and reusable products. The actual MRI and standby energy that produces the MRI images is only about 38 percent of the total life cycle energy. Research limitations/implications The focus on methods and proof-of-concept meant that only one facility and one type of imaging device technology were used to reach the conclusions. Based on the similar studies related to other imaging devices, the provided transparent data can be generalized to other healthcare facilities with few adjustments to utilization ratios, the share of the exam types, and the standby power of the facilities’ imaging devices. Practical implications The transparent detailed life cycle approach allows the data from this study to be used by healthcare administrators to explore the hidden public health impact of the radiology department and to set goals for carbon footprint reductions of healthcare organizations by focusing on alternative imaging modalities. Moreover, the presented approach in quantifying healthcare services’ environmental impact can be replicated to provide measurable data on departmental quality improvement initiatives and to be used in hospitals’ quality management systems. Originality/value No other research has been published on the life cycle assessment of MRI. The share of outside hospital indirect environmental impact of MRI services is a previously undocumented impact of the physician’s order for an internal image.
more »
« less
- Award ID(s):
- 1743682
- PAR ID:
- 10213560
- Date Published:
- Journal Name:
- International Journal of Health Care Quality Assurance
- Volume:
- 31
- Issue:
- 8
- ISSN:
- 0952-6862
- Page Range / eLocation ID:
- 910 to 922
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
We develop a methodology for modeling post-earthquake hospital needs and accessibility, coupling a probabilistic regional casualty risk model with a novel agent-based human behavior model. We use it to study hospital transportation in two socio-economically distinct districts of Lima, Peru, after a hypothetical moment magnitude 8.0 event. Our work provides insights into the infrastructure and socio-economic vulnerability factors that determine timely healthcare access, across various hypothetical behavioral and policy contexts/scenarios. In the baseline scenario that assumes households respond to the emergency independently (i.e. transport only their own members to hospital) but there is coordination among hospitals (i.e. ambulance sharing), car ownership is key for rapid healthcare access. Twenty-four percent of non-life-threatening casualties in the district with 57% car ownership will arrive at hospital in the first 45 min; only 6% of such patients in the more economically deprived district (18% car ownership) will reach hospital in that time. If car-owning neighbors help transporting patients without cars, over 96% of non-life-threatening casualties will reach hospital in the first 45 min in both districts, significantly reducing intra-regional disparities in healthcare access. Arrival times would nearly halve compared to the baseline scenario if the number of available ambulances doubled. If hospitals do not share ambulances, arrival times of non-life-threatening and threatening casualties show a notable reduction in one district (by 56% and 42%, respectively) but a significant increase in the other, more economically deprived district (by 109% and 97%, respectively), compared to the baseline case. The arrival times presented in this study are specific to the studied context, and the appropriate assumptions made. We benchmark the performance of the methodology using patient arrival times from the 2023 Turkey-Syria earthquake, yielding an acceptable outcome (i.e. similar temporal trends in the proportion of hospital arrivals). The findings can be leveraged for planning effective post-earthquake emergency response strategies.more » « less
-
Smart hospital patient rooms incorporate various smart devices to allow digital control of the entertainment --- such as TV and soundbar --- and the environment --- including lights, blinds, and thermostat. This technology can benefit patients by providing a more accessible, engaging, and personalized approach to their care. Many patients arrive at a rehabilitation hospital because they suffered a life-changing event such as a spinal cord injury or stroke. It can be challenging for patients to learn to cope with the changed abilities that are the new norm in their lives. This study explores ways smart patient rooms can support rehabilitation education to prepare patients for life outside the hospital's care. We conducted 20 contextual inquiries and four interviews with rehabilitation educators as they performed education sessions with patients and informal caregivers. Using thematic analysis, our findings offer insights into how smart patient rooms could revolutionize patient education by fostering better engagement with educational content, reducing interruptions during sessions, providing more agile education content management, and customizing therapy elements for each patient's unique needs. Lastly, we discuss design opportunities for future smart patient room implementations for a better educational experience in any healthcare context.more » « less
-
Most life cycle assessment (LCA) of crystalline silicon photovoltaics (c-Si PV) modules are based on public life cycle inventory (LCI) datasets with limited use of actual manufacturing data. We collect and calculate the amount of material used for production of different PV modules installed in the U.S. to analyze the trend in material intensity over and compare the numbers among various tier manufacturers and module reliability. Furthermore, results of LCA models using the public LCI data and the actual manufacturing material (specifically aluminum) data are compared to investigate the impact of material use on the life-cycle impact assessment of c-Si PV modules. Results show a trend of material use decrease over time and indicate a potential connection between material usage and the manufacturer tier – better manufacturers tend to use more materials for modules production which may lead to higher quality performance. Additional work will complete the life cycle assessment, explore more materials, and fill the data gap of PV modules produced by different manufacturer tiers in different years.more » « less
-
Abstract Understanding the thermodynamics associated with ion mixing and separation processes is important in order to meet the rising demands for clean energy and water production. Several electrochemical-based technologies such as capacitive deionization and capacitive mixing (CapMix) are capable of achieving desalination and energy production through ion mixing and separation processes, yet experimental investigations suggest energy conversion occurs with low second law (thermodynamic) efficiency. Here, we explore the maximum attainable efficiency for different CapMix cycles to investigate the impact cycle operation has on energy extraction. All investigated cycles are analogous to well documented heat engine cycles. In order to analyze CapMix cycles, we develop a physics-based model of the electric double layer based on the Gouy-Chapman-Stern theory. Evaluating CapMix cycles for energy generation revealed that cycles where ion mixing occurs at constant concentration and switching occurs at constant charge (a cycle analogous to the Stirling engine) attained the highest overall first law (electrical energy) efficiency (39%). This first law efficiency is nearly 300% greater than the first law efficiency of the Otto, Diesel, Brayton, and Atkinson analog cycles where ion mixing occurs while maintaining a constant number of ions. Additionally, the maximum first law efficiency was 89% with a maximum work output of 0.5 kWh per m3 of solution mixed (V = 1.0V) using this same Stirling cycle. Here the salinity gradient was CH = 600 mM and CL = 1 mM (ΔGmix = 0.56 kWh/m3). The effect of voltage was also examined at CH = 600 mM (seawater) and CL = 20 mM (river water). CapMix cycles operated at lower voltage (V < 1.0V), resulted in the Otto cycle yielding the highest first law efficiency of approximately 25% (compared to under 20% for the Stirling cycle); however, this was at the expense of a reduction (50x) in net electrical energy extracted from the same mixing process (0.01 kWh per m3).more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1108/IJHCQA-10-2016-0153
