Not Just Meaningful Data but Coordinated Data!

2014 ◽  
pp. 19-34 ◽  
Author(s):  
Vahé A. Kazandjian
Keyword(s):  
Cloud Computing ◽  
Information Technologies ◽  
Healthcare Services ◽  
Service Industries ◽  
Data Sources ◽  
Special Focus ◽  
Multiple Data ◽  
Community Evaluation ◽  
Health Systems Performance ◽  
Diverse Data

The era of data collection about health systems' performance is entering the new phase of timely and simultaneous access to diverse data sources in a systematic and coordinated approach. The concepts of harmonization and the measurement of the continuum of care have laid the ground for the pursuit of collecting, organizing, accessing, and sharing treatment and outcomes results. Service industries, faced with the need for access to multiple data sources, have adopted Information Technologies ranging from localized measurement of performance to regional monitoring of services, and finally into global networking via Cloud Computing. This chapter explores the benefits and challenges of Cloud Computing to the amelioration of medical and healthcare services given the idiosyncrasies of medicine and healthcare. A special focus is given to the extent of readiness healthcare systems manifest to measuring their performance, sharing the findings with patients and communities, and the accountability these systems demonstrate for the promises, implicitly or explicitly, they made about quality and safety of care. The implications of these promises in shaping patient expectations leading to patient and community evaluation of the healthcare services is a central theme running through this chapter.

Not Just Meaningful Data but Coordinated Data!

2015 ◽  
pp. 1526-1541
Author(s):  
Vahé A. Kazandjian
Keyword(s):  
Cloud Computing ◽  
Information Technologies ◽  
Healthcare Services ◽  
Service Industries ◽  
Data Sources ◽  
Special Focus ◽  
Multiple Data ◽  
Community Evaluation ◽  
Health Systems Performance ◽  
Diverse Data

The era of data collection about health systems' performance is entering the new phase of timely and simultaneous access to diverse data sources in a systematic and coordinated approach. The concepts of harmonization and the measurement of the continuum of care have laid the ground for the pursuit of collecting, organizing, accessing, and sharing treatment and outcomes results. Service industries, faced with the need for access to multiple data sources, have adopted Information Technologies ranging from localized measurement of performance to regional monitoring of services, and finally into global networking via Cloud Computing. This chapter explores the benefits and challenges of Cloud Computing to the amelioration of medical and healthcare services given the idiosyncrasies of medicine and healthcare. A special focus is given to the extent of readiness healthcare systems manifest to measuring their performance, sharing the findings with patients and communities, and the accountability these systems demonstrate for the promises, implicitly or explicitly, they made about quality and safety of care. The implications of these promises in shaping patient expectations leading to patient and community evaluation of the healthcare services is a central theme running through this chapter.

Incident Command Situation Assessment Utilizing Video Feeds from UAVs

2011 ◽  
pp. 55-71
Author(s):  
John McGuirl ◽  
Nadine Sarter ◽  
David Woods
Keyword(s):  
Disaster Response ◽  
Information Technologies ◽  
Data Sources ◽  
Situation Assessment ◽  
Incident Command ◽  
Data Search ◽  
Image Channel ◽  
Video Feed ◽  
Aerial Vehicle ◽  
Diverse Data

Past experience has shown that introducing new Information Technologies can have unintended and undesirable consequences, such as new forms of errors and a narrowing of data search activities. Eight Incident Commanders (ICs) took part in a simulated disaster response exercise to determine how the availability of real-time image feeds from a UAV impact on situation assessment and decision-making. The exercise simulated the video feed from an unmanned aerial vehicle (UAV) that allows incident command centers to monitor developments at a crisis site. The results showed that information from the video image channel dominated information available from other channels or in other forms. Nearly all of the ICs failed to detect important changes in the situation that were not captured in the imaging channel but that were available via other, more traditional data sources. The dominance of the image feed resulted in ICs narrowing their data search activities and reducing cross-checking across diverse data sources. This study confirms anecdotal reports that users can over-rely on video feeds from UAVs.

scholarly journals The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset

2018 ◽  
Vol 22 (11) ◽  
pp. 5817-5846 ◽  
Author(s):  
Camila Alvarez-Garreton ◽  
Pablo A. Mendoza ◽  
Juan Pablo Boisier ◽  
Nans Addor ◽  
Mauricio Galleguillos ◽  
...  
Keyword(s):  
Time Series ◽  
Arid Regions ◽  
Snow Water Equivalent ◽  
Potential Evapotranspiration ◽  
Data Sources ◽  
Large Sample ◽  
Daily Streamflow ◽  
Multiple Data ◽  
Diverse Data ◽  
High Elevations

Abstract. We introduce the first catchment dataset for large sample studies in Chile. This dataset includes 516 catchments; it covers particularly wide latitude (17.8 to 55.0∘ S) and elevation (0 to 6993 m a.s.l.) ranges, and it relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of a region where in situ measurements are scarce. For each catchment, the dataset provides boundaries, daily streamflow records and basin-averaged daily time series of precipitation (from one national and three global datasets), maximum, minimum and mean temperatures, potential evapotranspiration (PET; from two datasets), and snow water equivalent. We calculated hydro-climatological indices using these time series, and leveraged diverse data sources to extract topographic, geological and land cover features. Relying on publicly available reservoirs and water rights data for the country, we estimated the degree of anthropic intervention within the catchments. To facilitate the use of this dataset and promote common standards in large sample studies, we computed most catchment attributes introduced by Addor et al. (2017) in their Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset, and added several others. We used the dataset presented here (named CAMELS-CL) to characterise regional variations in hydroclimatic conditions over Chile and to explore how basin behaviour is influenced by catchment attributes and water extractions. Further, CAMELS-CL enabled us to analyse biases and uncertainties in basin-wide precipitation and PET. The characterisation of catchment water balances revealed large discrepancies between precipitation products in arid regions and a systematic precipitation underestimation in headwater mountain catchments (high elevations and steep slopes) over humid regions. We evaluated PET products based on ground data and found a fairly good performance of both products in humid regions (r>0.91) and lower correlation (r<0.76) in hyper-arid regions. Further, the satellite-based PET showed a consistent overestimation of observation-based PET. Finally, we explored local anomalies in catchment response by analysing the relationship between hydrological signatures and an attribute characterising the level of anthropic interventions. We showed that larger anthropic interventions are correlated with lower than normal annual flows, runoff ratios, elasticity of runoff with respect to precipitation, and flashiness of runoff, especially in arid catchments. CAMELS-CL provides unprecedented information on catchments in a region largely underrepresented in large sample studies. This effort is part of an international initiative to create multi-national large sample datasets freely available for the community. CAMELS-CL can be visualised from http://camels.cr2.cl and downloaded from https://doi.pangaea.de/10.1594/PANGAEA.894885.

Developing Innovative Practice in Service Industries

2009 ◽  
pp. 209-220 ◽  
Author(s):  
Elayne W. Coakes ◽  
Peter Smith ◽  
Dee Alwis
Keyword(s):  
Knowledge Sharing ◽  
Service Innovation ◽  
Strong Relationship ◽  
Service Industries ◽  
Service Organizations ◽  
Data Sources ◽  
Market Place ◽  
Organizational Skills ◽  
Multiple Data

This chapter presents the argument that service innovation is promoted by supporting divergent interpretations, enlarging the scope of employee and organizational skills and competencies, making interactions and knowledge sharing between people easy, and by encouraging close ties with customers. The chapter further argues that service organizations that utilize sociotechnical mechanisms for knowledge sharing through the use of a successful community of innovation (which we term a CoInv), and that build into their innovative capacities a strong relationship with their customers and suppliers, are very likely to innovate successfully. The argument is demonstrated through a qualitative case study where data analysis was deductive from multiple data sources. The chapter also demonstrates the power and efficacy of channeling activities through community innovation lenses. We argue that identifying innovation champions and comprehensively supporting them will potentially trigger more successful innovations thus improving service competitiveness in the market place.

Incident Command Situation Assessment Utilizing Video Feeds from UAVs

2013 ◽  
pp. 858-874
Author(s):  
John McGuirl ◽  
Nadine Sarter ◽  
David Woods
Keyword(s):  
Disaster Response ◽  
Information Technologies ◽  
Data Sources ◽  
Situation Assessment ◽  
Incident Command ◽  
Data Search ◽  
Image Channel ◽  
Video Feed ◽  
Aerial Vehicle ◽  
Diverse Data

Past experience has shown that introducing new Information Technologies can have unintended and undesirable consequences, such as new forms of errors and a narrowing of data search activities. Eight Incident Commanders (ICs) took part in a simulated disaster response exercise to determine how the availability of real-time image feeds from a UAV impact on situation assessment and decision-making. The exercise simulated the video feed from an unmanned aerial vehicle (UAV) that allows incident command centers to monitor developments at a crisis site. The results showed that information from the video image channel dominated information available from other channels or in other forms. Nearly all of the ICs failed to detect important changes in the situation that were not captured in the imaging channel but that were available via other, more traditional data sources. The dominance of the image feed resulted in ICs narrowing their data search activities and reducing cross-checking across diverse data sources. This study confirms anecdotal reports that users can over-rely on video feeds from UAVs.

Survey of Cloud Computing in Healthcare Sector

2017 ◽  
Vol 7 (7) ◽  
pp. 337
Author(s):  
S. Karthiga Devi ◽  
B. Arputhamary
Keyword(s):  
Cloud Computing ◽  
Healthcare Providers ◽  
High Volume ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
Cloud Infrastructure ◽  
Healthcare Organizations ◽  
Privacy And Security ◽  
Healthcare Data ◽  
Number Of Patients

Today the volume of healthcare data generated increased rapidly because of the number of patients in each hospital increasing.  These data are most important for decision making and delivering the best care for patients. Healthcare providers are now faced with collecting, managing, storing and securing huge amounts of sensitive protected health information. As a result, an increasing number of healthcare organizations are turning to cloud based services. Cloud computing offers a viable, secure alternative to premise based healthcare solutions. The infrastructure of Cloud is characterized by a high volume storage and a high throughput. The privacy and security are the two most important concerns in cloud-based healthcare services. Healthcare organization should have electronic medical records in order to use the cloud infrastructure. This paper surveys the challenges of cloud in healthcare and benefits of cloud techniques in health care industries.

EXPRESS: The Role of Patient Satisfaction in Hospitals’ Medicare Reimbursements

2020 ◽  
pp. 074391562098472
Author(s):  
Lu Liu ◽  
Dinesh K. Gauri ◽  
Rupinder P. Jindal
Keyword(s):  
Patient Satisfaction ◽  
Pain Management ◽  
Hospital Care ◽  
Pay For Performance ◽  
Data Sources ◽  
Satisfaction Survey ◽  
The Us ◽  
Performance System ◽  
Diverse Data

Medicare uses a pay-for-performance program to reimburse hospitals. One of the key input measures in the performance formula is patient satisfaction with their hospital care. Physicians and hospitals, however, have raised concerns especially about questions related to patient satisfaction with pain management during hospitalization. They report feeling pressured to prescribe opioids to alleviate pain and boost satisfaction survey scores for higher reimbursements. This over-prescription of opioids has been cited as a cause of current opioid crisis in the US. Due to these concerns, Medicare stopped using pain management questions as inputs in its payment formula. We collected multi-year data from six diverse data sources, employed propensity score matching to obtain comparable groups, and estimated difference-in-difference models to show that, in fact, pain management was the only measure to improve in response to pay-for-performance system. No other input measure showed significant improvement. Thus, removing pain management from the formula may weaken the effectiveness of HVBP program at improving patient satisfaction, which is one of the key goals of the program. We suggest two divergent paths for Medicare to make the program more effective.

Integration of statistical and administrative agricultural data from Namibia

2021 ◽  
pp. 1-22
Author(s):  
Emily Berg ◽  
Johgho Im ◽  
Zhengyuan Zhu ◽  
Colin Lewis-Beck ◽  
Jie Li
Keyword(s):  
Measurement Error ◽  
Data Collection ◽  
Administrative Data ◽  
Statistical Data ◽  
Data Sources ◽  
Extension Programs ◽  
Multiple Data ◽  
Administrative Agencies ◽  
Crop Area ◽  
Using Data

Statistical and administrative agencies often collect information on related parameters. Discrepancies between estimates from distinct data sources can arise due to differences in definitions, reference periods, and data collection protocols. Integrating statistical data with administrative data is appealing for saving data collection costs, reducing respondent burden, and improving the coherence of estimates produced by statistical and administrative agencies. Model based techniques, such as small area estimation and measurement error models, for combining multiple data sources have benefits of transparency, reproducibility, and the ability to provide an estimated uncertainty. Issues associated with integrating statistical data with administrative data are discussed in the context of data from Namibia. The national statistical agency in Namibia produces estimates of crop area using data from probability samples. Simultaneously, the Namibia Ministry of Agriculture, Water, and Forestry obtains crop area estimates through extension programs. We illustrate the use of a structural measurement error model for the purpose of synthesizing the administrative and survey data to form a unified estimate of crop area. Limitations on the available data preclude us from conducting a genuine, thorough application. Nonetheless, our illustration of methodology holds potential use for a general practitioner.

scholarly journals Adopt, adapt, or abandon technology-supported person-centred care initiatives: healthcare providers’ beliefs matter

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kari Dyb ◽  
Gro Rosvold Berntsen ◽  
Lisbeth Kvam
Keyword(s):  
Information Technologies ◽  
Scale Up ◽  
Healthcare Providers ◽  
Healthcare Services ◽  
Analytical Framework ◽  
Development Project ◽  
Technology Support ◽  
Care Needs ◽  
Term Care

Abstract Background Technology support and person-centred care are the new mantra for healthcare programmes in Western societies. While few argue with the overarching philosophy of person-centred care or the potential of information technologies, there is less agreement on how to make them a reality in everyday clinical practice. In this paper, we investigate how individual healthcare providers at four innovation arenas in Scandinavia experienced the implementation of technology-supported person-centred care for people with long-term care needs by using the new analytical framework nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability (NASSS) of health and care technologies. We also discuss the usability and sensitivity of the NASSS framework for those seeking to plan, implement, and evaluate technology-supported healthcare programmes. This study is part of an interdisciplinary research and development project called Patients and Professionals in Partnership (2016–2020). It originates at one of ten work packages in this project. Method The main data consist of ethnographic field observations at the four innovation arenas and 29 interviews with involved healthcare providers. To ensure continuous updates and status on work in the four innovation arenas, we have also participated in a total of six annual network meetings arranged by the project. Results While the NASSS framework is very useful for identifying and communicating challenges with the adoption and spread of technology-supported person-centred care initiatives, we found it less sensitive towards capturing the dedication, enthusiasm, and passion for care transformation that we found among the healthcare providers in our study. When it comes to technology-supported person-centred care, the point of no return has passed for the involved healthcare providers. To them, it is already a definite part of the future of healthcare services. How to overcome barriers and obstacles is pragmatically approached. Conclusion Increased knowledge about healthcare providers and their visions as potential assets for care transformation might be critical for those seeking to plan, implement, and evaluate technology-supported healthcare programmes.

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