Relevant bibliographies by topics / Healthcare

Academic literature on the topic 'Healthcare'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Healthcare"

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Gray, Muir, Jonathon Gray, and Jeremy Howick. "Personalised healthcare and population healthcare." Journal of the Royal Society of Medicine 111, no. 2 (September 18, 2017): 51–56. http://dx.doi.org/10.1177/0141076817732523.

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Selvanambi, Ramani, and Jaisankar N. "Healthcare." International Journal of E-Health and Medical Communications 10, no. 2 (April 2019): 63–85. http://dx.doi.org/10.4018/ijehmc.2019040104.

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Quality analysis of the treatment of cancer has been an objective of e-health services for quite some time. The objective is to predict the stage of breast cancer by using diverse input parameters. Breast cancer is one of the main causes of death in women when compared to other tumors. The classification of breast cancer information can be profitable to anticipate diseases or track the hereditary of tumors. For classification, an artificial neural network (ANN) structure was carried out. In the structure, nine training algorithms are used and the proposed is the Levenberg-Marquardt algorithm. For optimizing the hidden layer and neuron, three optimization techniques are used. In the result, the best approval execution is anticipated and the diverse execution evaluation estimation for three optimization algorithms is researched. The correlation execution diagram for an accuracy of 95%, a sensitivity of 98%, and a specificity of 89% of a social spider optimization (SSO) algorithm are shown.
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&NA;. "Healthcare." Inpharma Weekly &NA;, no. 966 (December 1994): 7. http://dx.doi.org/10.2165/00128413-199409660-00011.

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Franklin, Kathryn, Shannon Engstrand, Jason Thornton, and Jean Anne Connor. "#Healthcare." Dimensions of Critical Care Nursing 41, no. 2 (March 2022): 83–90. http://dx.doi.org/10.1097/dcc.0000000000000514.

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Lorton, Lewis. "Healthcare." Journal of Private Equity 3, no. 2 (May 31, 2000): 38–44. http://dx.doi.org/10.3905/jpe.2000.319958.

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WILKES, KIMBERLY. "Healthcare." Journal of Christian Nursing 23, no. 4 (2006): 38–39. http://dx.doi.org/10.1097/00005217-200611000-00011.

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Bushy, Angeline. "Healthcare." Journal of Ambulatory Care Marketing 4, no. 2 (April 18, 1991): 89–99. http://dx.doi.org/10.1300/j273v04n02_07.

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Ebling, Maria, and Joseph Kannry. "Healthcare." IEEE Pervasive Computing 11, no. 4 (October 2012): 14–17. http://dx.doi.org/10.1109/mprv.2012.71.

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&NA;. "Healthcare." Nursing 44, no. 1 (January 2014): 6. http://dx.doi.org/10.1097/01.nurse.0000438715.43216.e2.

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Micossi, Piero, Maria Carbone, Giovanna Stancanelli, and Antonio Fortino. "HEALTHCARE." Lancet 341, no. 8860 (June 1993): 1566–67. http://dx.doi.org/10.1016/0140-6736(93)90703-j.

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Dissertations / Theses on the topic "Healthcare"

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Ponce, Michael. "Healthcare fraud and non-fraud healthcare crimes: A comparison." CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3233.

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Healthcare fraud is a major problem within the healthcare industry. The study examined medical fraud, its laws, and punishments on federal and state levels. It compared medical fraud to non-fraud crimes done in the healthcare industry. This comparison will be done on a state level. The study attempted to analyze the severity of fraud against non-fraud and that doctors would commit fraud offenses more often than non-fraud offenses.
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Miller, Aretha D. "Associations Between Healthcare Facility Types and Healthcare-Associated Infections." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2035.

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Healthcare-Associated Infections (HAIs) continue to be an epidemiological issue burdening patients and public health systems worldwide. The purpose of this study was to determine if specific healthcare facility types (Acute Care Hospitals, Long Term Acute Care Hospitals, and Inpatient Rehabilitation Facilities) were associated with particular categories of HAIs: Ventilator-Associated Pneumonias (VAPs), Central Line-Associated Bloodstream Infections (CLABSIs), and Catheter-Associated Urinary Tract Infections (CAUTIs). The theoretical framework for this study was the environmental determinants of infectious disease framework. A single research question focused on whether an association existed among the specified health care facility types and HAIs. Three independent categorical variables were used, including Acute Care Hospitals, Long Term Acute Care Hospitals, and Inpatient Rehabilitation Facilities, and 3 dependent variables were used, comprising of VAPs, CAUTIs, and CLABSIs. A quantitative design engaged the chi-square test of association, using a 2012 population-level report of archival data collected by the Centers for Disease Control and Prevention's National Healthcare Safety Network. Seven groups of HAIs and facility types were tested, and the results revealed that 6 groups had statistically significant differences. This study may contribute to positive social change by helping to identify whether healthcare facility types are associated with HAIs and to supply evidence to stakeholders to support standardization of best practices across all facility types, thus contributing to the reduction of HAIs in the United States.
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Kilic, Ozgur. "Achieving Electronic Healthcare Record (ehr) Interoperability Across Healthcare Information Systems." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609665/index.pdf.

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Providing an interoperability infrastructure for Electronic Healthcare Records (EHRs) is on the agenda of many national and regional eHealth initiatives. Two important integration profiles have been specified for this purpose: the "
IHE Cross-enterprise Document Sharing (XDS)"
and the "
IHE Cross Community Access (XCA)"
. XDS describes how to share EHRs in a community of healthcare enterprises and XCA describes how EHRs are shared across communities. However, currently no solution addresses some of the important challenges of cross community exchange environments. The first challenge is scalability. If every community joining the network needs to connect to every other community, this solution will not scale. Furthermore, each community may use a different coding vocabulary for the same metadata attribute in which case the target community cannot interpret the query involving such an attribute. Another important challenge is that each community has a different patient identifier domain. Querying for the patient identifiers in another community using patient demographic data may create patient privacy concerns. Yet another challenge in cross community EHR access is the EHR interoperability since the communities may be using different EHR content standards.
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Kim, Beomsoo. "Legislating healthcare quality." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3520.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Economics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Kling, Rakel Nessa. "Promoting the health of healthcare workers : evaluating patient violence in healthcare." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32674.

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Introduction: The high rate of violence in the healthcare sector supports the need for greater prevention efforts. This study had two main objectives: 1) identify risk factors for violence province- wide and 2) investigate the effectiveness of a violence risk assessment system in reducing the risk of violence in an acute care hospital in British Columbia. Methods: Study 1: Data was extracted for a one-year period from the Workplace Health Indicator Tracking and Evaluation (WHITE ™) database for all employee reports of violent incidents for four of the six British Columbia Health Authorities. Risk factors for violence were identified through comparisons of incident rates (number of incidents/100,000 worked hours) by work characteristics, and by regression models. Study 2: Hospital violence incident rates (number of incidents/ 100,000 worked hours)were calculated pre, during and post implementation of the Alert System, a violence risk assessment system, at one acute care hospital. Then, using a retrospective case control study design, multivariable conditional logistic regression was used to model the effect of the Alert System (flag status yes or no) on the risk of a patient violent incident. Results: Study 1: Across health authorities, three groups at particularly high risk for violence were identified: very small healthcare facilities, the care aide occupation, and pediatric departments in acute care hospitals. Study 2: The violent incident rate decreased during the Alert System implementation period, but subsequently returned to pre-implementation levels. In the case-control analyses, patients flagged for violence were associated with an increased rather than decreased risk for violence. Conclusions: Study 1: The specific risk factors that put health care groups at an increased risk of violence should be examined so that targeted prevention or intervention efforts can be implemented. The identification of high-risk groups supports the importance of a province-wide surveillance system. Study 2: Although useful at identifying violent patients, the Alert System does not appear to provide the resources or procedures needed by health care workers to prevent a patient from progressing to a violent incident once flagged. These studies suggest that violence in healthcare should be studied and prevented using a multifaceted approach.
Medicine, Faculty of
Population and Public Health (SPPH), School of
Graduate
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Gabassi, Gianfranco. "Innovation for a Sustainable Healthcare: : How can patients improve their own healthcare?" Thesis, KTH, Industriell produktion, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129269.

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As the demographic pictures is changing across the Western world, healthcare costs are growing at unsustainable rates. In order to sustain the healthcare we’re used to in the Western world, new healthcare deliver strategies must be implemented. As the average person grows older, chronic diseases hit more people, requiring costly treatments for a growing part of the population. A successful approach could address the problem of medical adherence, together with increasing awareness among patients through increased involvement. During the last century, the healthcare industry has received vast amounts of technological and medical innovations. However, the interaction between the patient and the doctor has very much remained the same. Is it possible that an increase in patient involvement can lead to improved healthcare outcomes? And further, how would they be able to become more involved? Through a qualitative study involving interviews with experts in the field, ideas were shared on how patient involvement can benefit both the patient and the healthcare, followed by how this involvement can takeplace. Results involved the medical delivery strategy of P4 Medicine, closely related to the concept of Personalized Medicine. These theories advise the patients to take a much more active role in the healthcare. It encourages a shift from the reactive to the proactive healthcare, leading to a new view of the healthcare as a lifelong partner. The conclusion drawn included that patient involvement is an important step towards a much cheaper and effective healthcare. With more data-mining and smarter systems, more people are able to develop services that can improve life for both patients and health professionals.
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Gallagher, Martha S. "The Impact of an International Healthcare Mission on Participating Healthcare Professional Students." University of Toledo / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1083527751.

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Maparzadeh, Milad. "Patients’ perspective of digital healthcare : Social implications during a digital healthcare meeting." Thesis, Högskolan Väst, Avd för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16811.

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The purpose of this study was to gain a deeper understanding of the patient’s perspective regarding social interactions in video healthcare meetings. Social presence theory was used in the context of how video calls can result in vital aspects of social interactions disappearing and how that can affect the outcome of a doctor consultation in contrast to physical meetings. A qualitative method with semi-structured interviews was applied to this study. This study included 7 participants with similar age range from 26-36 years old including both genders. This study resulted in many different views and perspectives whereas some participants found it harder to communicate virtually whereas others did not think that social interactions was not even an important factor. The conclusion that could be made from this study is that virtual healthcare meetings are good depending on which context they are used for. Furthermore, the doctor cannot always get the full picture because the camera creates a psychological distance which makes it harder for the doctor to observe as much as he/she can in a physical setting which can lead to many signals and cues missing out.
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Owen-Smith, Amanda. "Knowing about healthcare rationing." Thesis, University of Bristol, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486124.

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How best to manage the obligation to ration healthcare, and in particular how explicit such priority setting processes should be, is a matter of increasing international interest. Despite this, there exists very limited empirical evidence about the views of clinicians on this issue, and none relating to the views of patients. Qualitative research methods were used to conduct a multi-stage empirical investigation, including an initial study at the community level, followed by two clinical case studies (of morbid obesity and breast cancer treatments) within secondary care. In total, 21 healthcare professionals and 31 patients were interviewed. Purposive and theoretical sampling methods were used and data were analysed using methods of constant comparison. The results revealed that patients had a broad awareness of healthcare rationing, and nearly all said they wanted to know how financial factors affected the provision of their healthcare. However, the data also demonstrated that the experience of explicit rationing could be extremely distressing for patients, particularly when decision-making was viewed as arbitrary or unfair. Clinical professionals reported a strong theoretical commitment to being open about rationing, although in practice this was sometimes over-ridden by ethical or pragmatic concerns, meaning that more implicit approaches were often employed. Patients had a choice whether to accept explicit rationing decisions, protest against them, or pay for private care. However, options were often constrained because of lack of personal resour~es or inadequate access to information. In conclusion, explicit rationing is generally favoured by clinicians and patients, and is amenable to being managed within the shared decision-making model of the doctor-patient relationship. However, clinicians need further training to assist them in appropriate disclosure techniques, and patients need access to adequate information about the basis for rationing decisions, and the possible routes to contest them, to ensure their involvement is meaningful.
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Larsson-Green, Peter. "Kinect’s potential in healthcare." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-109323.

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This project investigates if a Microsoft Kinect has the potential to be used in healthcare as an assisting tool for doctors in their work to diagnose patients or by supporting rehabilitation patients with their exercise training. To test its potential, the accuracy in the skeleton data it produces has been investigated, and two different computer programs making use of the Kinect has been created and evaluated. The results suggest that the Kinect has the potential to be used in some fields in healthcare as long as one takes its strengths and weaknesses into consideration.
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Books on the topic "Healthcare"

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Glowik, Mario, and Slawomir Smyczek, eds. Healthcare. Berlin, München, Boston: DE GRUYTER, 2015. http://dx.doi.org/10.1515/9783110414844.

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Institute of Policy Studies (Singapore) and Straits Times Press Pte. Ltd, eds. Healthcare. Singapore: Institute of Policy Studies, 2018.

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Deutsch, Ellen S., Shawna J. Perry, and Harshad G. Gurnaney, eds. Comprehensive Healthcare Simulation: Improving Healthcare Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72973-8.

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Moss, Linda. Art & healthcare: Handbook of healthcare arts. [London]: [Health Building Directorate, DHSS], 1988.

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Yankee Group. Consumer & Technology Division., ed. Consumer healthcare: Marketing healthcare delivery systems. Boston, MA (200 Portland St., Boston, MA 02114): Yankee Group, 1987.

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Pöchhacker, Franz, and Miriam Shlesinger, eds. Healthcare Interpreting. Amsterdam: John Benjamins Publishing Company, 2007. http://dx.doi.org/10.1075/bct.9.

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Bausell, R. Healthcare Evaluation. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2012. http://dx.doi.org/10.4135/9781446261927.

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Bhatia, Surbhi, Ashutosh Kumar Dubey, Rita Chhikara, Poonam Chaudhary, and Abhishek Kumar, eds. Intelligent Healthcare. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67051-1.

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Husain, Mohammad Shahid, Muhamad Hariz Bin Muhamad Adnan, Mohammad Zunnun Khan, Saurabh Shukla, and Fahad U. Khan, eds. Pervasive Healthcare. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-77746-3.

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Chakraborty, Chinmay, and Mohammad R. Khosravi, eds. Intelligent Healthcare. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8150-9.

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Book chapters on the topic "Healthcare"

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Tognetti, Mara. "Healthcare." In Encyclopedia of Quality of Life and Well-Being Research, 2757–59. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3474.

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Lowe, Rodney. "Healthcare." In The Welfare State in Britain since 1945, 174–203. London: Macmillan Education UK, 2005. http://dx.doi.org/10.1007/978-1-137-06368-7_7.

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Assadian, Ojan, Peter Matulat, Katrin Neumann, Antonio Schindler, and Erkki Vilkman. "Healthcare." In Phoniatrics I, 125–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-46780-0_2.

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Tognetti, Mara, and Silvana Greco. "Healthcare." In Encyclopedia of Quality of Life and Well-Being Research, 1–4. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-69909-7_3474-2.

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Wendt, Claus. "Healthcare." In Routledge Handbook of the Welfare State, 407–17. Second edition. | Abingdon, Oxon; New York, NY: Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315207049-36.

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Lafe, Olurinde. "Healthcare." In Abulecentrism, 145–50. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01023-6_8.

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Racine, Jeremy. "Healthcare." In A Practical Guide to Analytics for Governments, 67–98. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119362517.ch4.

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Wilson, Brian, and Kees Van Haperen. "Healthcare." In Soft Systems Thinking, Methodology and the Management of Change, 262–322. London: Macmillan Education UK, 2015. http://dx.doi.org/10.1007/978-1-137-43269-8_22.

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Gibson, Will, and Dirk vom Lehn. "Healthcare." In Institutions, Interaction and Social Theory, 67–87. London: Macmillan Education UK, 2017. http://dx.doi.org/10.1057/978-1-349-93832-2_4.

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Korngold, Alice. "Healthcare." In A Better World, Inc., 107–29. New York: Palgrave Macmillan US, 2014. http://dx.doi.org/10.1007/978-1-137-33712-2_6.

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Conference papers on the topic "Healthcare"

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Verma, Anubha, Harsh Dhand, and Abhijit Shaha. "Healthcare kiosk next generation accessible healthcare solution." In 2008 10th International Conference on e-health Networking, Applications and Services (Healthcom). IEEE, 2008. http://dx.doi.org/10.1109/health.2008.4600135.

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Sandi, Gitarja, Suhono Harso Supangkat, and Ermawati. "Smart Healthcare for Personalized Healthcare: Literature Review." In 2023 10th International Conference on ICT for Smart Society (ICISS). IEEE, 2023. http://dx.doi.org/10.1109/iciss59129.2023.10291631.

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Cavoski, Sava, Vladimir Vujovic, Vuk Devrnja, Boris Ferenc, and Filip Lukic. "Digital Transformation in Healthcare Healthcare on Demand." In 2022 21st International Symposium INFOTEH-JAHORINA (INFOTEH). IEEE, 2022. http://dx.doi.org/10.1109/infoteh53737.2022.9751335.

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Little, Linda, and Pam Briggs. "Pervasive healthcare." In the 2nd International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1579114.1579185.

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Adenuga, Kayode I., Rahmat O. Adenuga, Abdallah Ziraba, and Penn E. Mbuh. "Healthcare Augmentation." In ICSIE '19: 2019 8th International Conference on Software and Information Engineering. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3328833.3328840.

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Zhu, Haining, and John M. Carroll. "Healthcare Opportunities." In CSCW '18: Computer Supported Cooperative Work and Social Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3272973.3274042.

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Jha, Niraj K. "Smart Healthcare." In GLSVLSI '23: Great Lakes Symposium on VLSI 2023. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3583781.3592463.

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Jones, Jim, and Jeffrey Jones. "Optimizing Healthcare." In 2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM). IEEE, 2021. http://dx.doi.org/10.1109/healthcom49281.2021.9399021.

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Bentsen, Patrick, Jesper Hedeager Nielsen, Jorgen Nybo, Christen Ring, and Stefan Wagner. "Continuous Healthcare." In 4th International ICST Conference on Pervasive Computing Technologies for Healthcare. IEEE, 2010. http://dx.doi.org/10.4108/icst.pervasivehealth2010.8900.

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De Michele, Roberta, and Marco Furini. "IoT Healthcare." In GoodTechs '19: EAI International Conference on Smart Objects and Technologies for Social Good. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3342428.3342693.

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Reports on the topic "Healthcare"

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Chandra, Amitabh, Amy Finkelstein, Adam Sacarny, and Chad Syverson. Healthcare Exceptionalism? Productivity and Allocation in the U.S. Healthcare Sector. Cambridge, MA: National Bureau of Economic Research, July 2013. http://dx.doi.org/10.3386/w19200.

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Chandra, Amitabh, Amy Finkelstein, Adam Sacarny, and Chad Syverson. Healthcare Exceptionalism? Performance and Allocation in the U.S. Healthcare Sector. Cambridge, MA: National Bureau of Economic Research, October 2015. http://dx.doi.org/10.3386/w21603.

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Herrera, Cristian, and Andy Oxman. Does integration of primary healthcare services improve healthcare delivery and outcomes? SUPPORT, 2017. http://dx.doi.org/10.30846/170411.

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Primary healthcare in many low- and middle-income countries is organised through vertical programmes for specific health problems such as tuberculosis control or childhood immunisation. Vertical programmes can help deliver particular technologies or services, but may lead to service duplication and fragmentation. To address such problems, the World Health Organization and other organizations promote integration, where inputs, delivery, management and organization of particular service functions are brought together. Integration may involve adding a service to an existing vertical programme or full integration of services within routine healthcare delivery.
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Herrera, Cristian, Andy Oxman, and Shaun Treweek. Does integration of primary healthcare services improve healthcare delivery and outcomes? SUPPORT, 2017. http://dx.doi.org/10.30846/1704112.

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Primary healthcare in many low- and middle-income countries is organised through vertical programmes for specific health problems such as tuberculosis control or childhood immunisation. Vertical programmes can help deliver particular technologies or services, but may lead to service duplication and fragmentation. To address such problems, the World Health Organization and other organizations promote integration, where inputs, delivery, management and organization of particular service functions are brought together. Integration may involve adding a service to an existing vertical programme or full integration of services within routine healthcare delivery.
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Boward, Rene L., Brenda S. Farrell, Matthew S. Feely, Lynn M. Fulling, and Marvin K. Harvey. 2001 Industry Studies: Healthcare. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada426216.

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Greenberg, Paul E., Andree-Anne Fournier, Tammy Sisitsky, Crystal T. Pike, Ronald C. Kessler, Benjamin I. Goldstein, Howard G. Birnbaum, et al. Focus on Healthcare Economics. Physicians Postgraduate Press, Inc, February 2015. http://dx.doi.org/10.4088/pp.15013foc0.

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Bock, Conrad, Lisa Carnahan, Steven Fenves, Michael Gruninger, Vipul Kashyap, Bettijoyce Lide, James Nell, Ravi Raman, and Ram D. Sriram. Healthcare strategic focus area :. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7263.

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Etzkowitz, Henry, and Richard N. Spivack. Information infrastructure for healthcare:. Gaithersburg, MD: National Institute of Standards and Technology, 1999. http://dx.doi.org/10.6028/nist.ir.6404.

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Cohen, Deborah J., Annette M. Totten, Robert L. Phillips, Jr., Yalda Jabbarpour, Anuradha Jetty, Jennifer DeVoe, Miranda Pappas, Jordan Byers, and Erica Hart. Measuring Primary Healthcare Spending. Agency for Healthcare Research and Quality (AHRQ), May 2024. http://dx.doi.org/10.23970/ahrqepctb44.

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Background. Policy leaders and researchers have identified a range of primary care spending conceptualizations, developed frameworks and methods for measuring primary care spending, and documented the pros and cons of different approaches. However, these efforts have not been comprehensive, particularly as the number of estimates has grown. We continue this work by identifying the definitions, data sources, and approaches used to estimate primary care spending in the United States. Our objective was to identify where there is and is not consensus across methods, and how initial steps toward a standardized approach to estimating primary care spending might be achieved. We approached this comparison from a societal economic perspective. Methods. Searches were conducted in Ovid MEDLINE® and Cochrane CENTRAL databases (inception to May 2, 2023), and were supplemented by manual reviews of reference lists, Scopus searches of key articles, gray literature searches of State and organization websites, and responses to a Federal Register Notice, as well as recommendations from Key Informants. Websites of States and organizations that produced reports were reviewed in November 2023 to identify updates. Publicly available estimates and reports of methods were supplemented by discussions with experts who have supported States’ estimates. Findings. We identified 67 primary care spending estimates for 2010 to 2021: 42 of these were produced by 11 State Governments for their State, 2 were published by the Veterans Health Administration, and 23 were published by researchers or other organizations, which include foundations and policy organizations. Forty-four estimates reported on primary care spending for a single State, one estimate reported spending for the New England States, and 22 reported national spending. To date, 13 State Governments have developed and/or are implementing measurements of primary care spending. When State Governments measure primary care spending, they produce regular, often yearly, estimates. States have produced one to eight estimates, demonstrating some States have more experience with this task than others. Primary care spending estimates in our sample ranged from 3.1 to 10.3 percent. These estimates started with definitions of primary care, which are often labeled narrow or broad. Estimates may use these same labels to mean different things. Narrow definitions of primary care usually include fewer providers, locations, or service types, while broad definitions include more. State, regional, or national estimates are either reported as two estimates, one using a narrow and one using a broad definition of primary care, or as a single estimate labeled neither narrow nor broad. Variations in what providers, services, and locations are included in definitions of primary care are significant and likely contribute to variation in primary care spending estimates. However, it is difficult to distinguish differences in definitions and measurement from differences in actual primary care spending. Conclusions. While there are some core similarities in how primary care spending is measured across State, regional, and national estimates, there are more differences. While there may be rationale behind some of these variations, this variation limits comparisons and what could be understood about the impact of policies. Furthermore, lack of clear, detailed reporting of methods can obscure precisely how and why estimates differ. Research is needed that quantifies the impact different decisions and measurement methods have on spending estimates. To assure the validity and reliability of estimates of primary care spending, and facilitate comparisons and links to health outcomes, Federal, State, and policy leaders need to: (1) collaborate to create a primary care clinician database that can function as a public utility for States to allow for more precise identification of primary care clinics and clinicians, and reduce reliance on Current Procedural Terminology/Healthcare Common Procedure Coding System codes; (2) develop a template for transparent reporting of methods used to estimate primary care spending; (3) foster collaboration among Federal agencies and State leaders to develop a consensus definition of primary care and process for estimating primary care spending, with consideration of methods that are easy to understand and transparent; and (4) support the development and ongoing maintenance of State All-Payer Claims Databases, expand to include nonclaims payments, and supply Medicare and Medicaid estimates for every State.
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Smith, Samantha, Brendan Walsh, Maev-Ann Wren, Steve Barron, Edgar Morgenroth, James Eighan, and Seán Lyons. Geographic profile of healthcare needs and non-acute healthcare supply in Ireland. Economic and Social Research Institute, July 2019. http://dx.doi.org/10.26504/rs90.

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