Relevant bibliographies by topics / Clinical decisions

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Clinical decisions'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Clinical decisions"

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Kostbade Hughes, Katherine, and Wendy B. Young. "Decision Making Stability of Clinical Decisions." Nurse Educator 17, no. 3 (May 1992): 12–16. http://dx.doi.org/10.1097/00006223-199205000-00010.

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Tavakoli, Manouche, Huw TO Davies, and Richard Thomson. "Aiding clinical decisions with decision analysis." Hospital Medicine 60, no. 6 (June 1999): 444–47. http://dx.doi.org/10.12968/hosp.1999.60.6.1139.

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Metlay, Joshua P., and Katrina A. Armstrong. "Annals Clinical Decision Making: Incorporating Perspective Into Clinical Decisions." Annals of Internal Medicine 172, no. 11 (June 2, 2020): 743–46. http://dx.doi.org/10.7326/m19-3469.

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Drazen, Jeffrey M., Edward W. Campion, Gregory D. Curfman, Pamela W. Miller, Kent R. Anderson, and Stephen Morrissey. "Clinical Decisions." New England Journal of Medicine 356, no. 20 (May 17, 2007): 2093. http://dx.doi.org/10.1056/nejme078065.

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Lowenthal, David T., and Mary M. Conlin. "CLINICAL DECISIONS." Journal of the American Geriatrics Society 43, no. 11 (November 1995): 1303–8. http://dx.doi.org/10.1111/j.1532-5415.1995.tb07410.x.

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Keltch, Brain, Yuan Lin, and Coskun Bayrak. "Advanced decision support for complex clinical decisions." Journal of Biomedical Science and Engineering 03, no. 05 (2010): 509–16. http://dx.doi.org/10.4236/jbise.2010.35071.

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Metlay, Joshua P., and Katrina A. Armstrong. "Annals Clinical Decision Making: Weighing Evidence to Inform Clinical Decisions." Annals of Internal Medicine 172, no. 9 (May 5, 2020): 599–603. http://dx.doi.org/10.7326/m19-1941.

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Ramsey, Rory, and Kingman P. Strohl. "Decisions, decisions, decisions." Sleep and Breathing 9, no. 4 (November 12, 2005): 143–45. http://dx.doi.org/10.1007/s11325-005-0039-5.

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Pope, Kenneth S. "Improving Clinical Decisions." Contemporary Psychology: A Journal of Reviews 36, no. 9 (September 1991): 749–50. http://dx.doi.org/10.1037/030132.

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Kheterpal, Sachin. "Random Clinical Decisions." Anesthesiology 116, no. 1 (January 1, 2012): 3–5. http://dx.doi.org/10.1097/aln.0b013e31823d25de.

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Dissertations / Theses on the topic "Clinical decisions"

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Boren, Shedrick John. "Ignoring Ambiguity: Legitimating Clinical Decisions." Scholarly Repository, 2008. http://scholarlyrepository.miami.edu/oa_dissertations/170.

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As technology advances, health care decisions have become increasingly complex. American hospitals, based on accreditation standards, are required to have a system and process to address ethics, patient rights, and responsibilities. These practices vary widely, and there is very little consistency and few standards across the country. Key court cases have provided minor structure, and the federal government has been silent in the formulation of these structures but not necessarily in this arena. Most often, these accreditation standards related to clinical ethics are managed by Healthcare Ethics Committees (HEC). Bioethics has become a growing field, the level of integration between this discipline and healthcare practice varies widely. Using qualitative methods based on Grounded Theory, this analysis presents six key thematic findings, as well as interpretations to identify current challenges and opportunities to make recommendations for improvement by enhancing clarity and reducing ambiguity.
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Vaithianathan, Rhema. "Economic Incentives and Clinical Decisions." Thesis, University of Auckland, 2000. http://hdl.handle.net/2292/2235.

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In the face of escalating health care expenditure, OECD countries are turning to a variety of cost-containment strategies. This thesis analyses three such mechanisms. In Part I, I consider the use of coinsurance to limit the demand for health care. Because coinsurance reduces the elasticity of demand with respect to the price of health care, consumers facing low coinsurance rates may be charged a higher price by doctors. Such discriminatory pricing enables the doctor to extract surplus created in the insurance market, and therefore reduces the effectiveness of coinsurance. I show that in equilibrium, some consumers remain uninsured. I also show how this problem is solved if the doctor and insurer enter into managed care style arrangements. Such arrangements improve insurer and doctor profitability, and restore complete insurance market coverage. In Part II, I consider the design of fundholding schemes which encourage doctors to restrict expensive treatment to severely ill patients. I show that such schemes may be undermined by a patient-doctor side contract. In the face of such patient-doctor collusion, the fundholding scheme may be made collusion-proof by increasing its "power". I show that the optimal collusion-proof scheme may pay the doctor more than his reservation wage. An alternative solution to patient-doctor collusion is to use a partial fundholding scheme that requires some additional co-payment from the patient. Part III analyses New Zealand's internal market reforms. Introduced in 1993, the reforms involved the separation of funding and provision of health care, and were intended to simulate a competitive market environment, thereby improving the incentives of government owned health care providers to be efficient. On the supply side, I look at the internal restructuring of hospitals into private-sector clones. I argue that this commercialisation failed to take account of informational issues within the hospital. On the demand-side, I examine the suitability of internal markets for eliciting optimal innovation from the hospital sector. Again, I find that a standard argument, namely that increased competition leads to innovation, is questionable in the context of the internal market.
Whole document restricted, but available by request, use the feedback form to request access.
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Whittle, Rosemary Anne. "Decisions, decisions: factors that influence student selection of final year clinical placements." Thesis, University of Canterbury. Education, 2007. http://hdl.handle.net/10092/1057.

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Clinical practice is an essential and integral component of nursing education. The decision-making process involved in student selection of clinical placements is influenced by a range of factors which are internal or external to students. As there was little research that explored these factors and the influence they have on student decisions, I wanted to investigate this further. A mixed-method approach was used, using a questionnaire and focus group interview, to give breadth and depth to the research. This study found that students are particularly influenced by previous positive experiences, or an interest in a particular area of practice. Their personality will also influence their placement decisions. Nurse preceptors and clinical lecturers also provide a key support role to students in the clinical environment.
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Adams, Barbara L. Rhodes Dent. "Making clinical decisions baccalaureate nursing student thought processes /." Normal, Ill. Illinois State University, 2003. http://wwwlib.umi.com/cr/ilstu/fullcit?p3106754.

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Thesis (Ed. D.)--Illinois State University, 2003.
Title from title page screen, viewed October 19, 2005. Dissertation Committee: Dent M. Rhodes (chair), Cathy A. Toll, Eileen T. Borgia, Saundra L. Theis. Includes bibliographical references (leaves 108-116) and abstract. Also available in print.
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Llewelyn, David Evan Huw. "Assessing the validity of diagnostic tests and clinical decisions." Thesis, King's College London (University of London), 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325963.

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Palmer, Barbara Benson 1958. "Clinical decision making about end-of-life decisions of persons over 65: Perceptions of clinicians." Thesis, The University of Arizona, 1992. http://hdl.handle.net/10150/278251.

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A descriptive study was conducted to explore whether or not there were any differences in perceptions of physicians, acute care nurses, long-term care nurses, and nurse practitioners associated with end-of-life decision making for people over 65 years of age. A convenience sample of 95 health care providers, all of whom were involved in direct patient care was used. Quantitative research techniques were employed for data collection and analysis. Statistically significant differences were found between four individual items on the CDMS and the health care providers. It was found that long-term care nurses believed items associated with pain and suffering, and culture to be more important than either physicians or acute care nurses, where as they found physicians input less important. A statistical significance was also found between the years spent in practice by health care providers and scores on the CDMS.
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Duriseti, Ram S. "Making high quality clinical decisions : influence diagrams in cost-effectiveness analysis /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Gong, Jen J. (Jen Jian). "Improving clinical decisions using correspondences within and across electronic health records." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118087.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 106-112).
Electronic Health Record (EHR) adoption and retrospective analyses of health care data are part of a broader conversation about health care quality and cost in the United States. Machine learning in health care can be used to develop clinical decision-making aids and assess quality of care. This can help improve quality of care while lowering cost. In this thesis, we present three methods of using different kinds of data in health care records to aid clinicians in making care decisions. We focus on the critical care environment, where patient state can rapidly change, and many care decisions need to be made in short periods of time. First, we introduce a method to use correspondences between structured fields from two different EHR systems to a shared space of clinical concepts encoded in an existing domain ontology. We use these correspondences to enable the transfer of machine learning models across different or evolving EHR systems. Second, we introduce a method to learn correspondences between structured health record data and topic distributions of clinical notes written by care team members. Finally, we present a method to characterize care processes by learning correspondences between observations of patient state and actions taken by care team members.
by Jen Jian Gong.
Ph. D.
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AMARAL, Thiago Magalhães. "Optimal control in biological systems as a support for clinical decisions." Universidade Federal de Pernambuco, 2009. https://repositorio.ufpe.br/handle/123456789/6002.

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Made available in DSpace on 2014-06-12T17:43:11Z (GMT). No. of bitstreams: 2 arquivo988_1.pdf: 2441078 bytes, checksum: 571bd2c7f61193398e8587dfeb171c6d (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
O controle ótimo no mundo biológico tem uma vasta aplicação em incontáveis sistemas os quais influenciam enormemente nossas vidas. Objetiva-se a aplicação desta ferramenta em dois sistemas. O primeiro diz respeito ao controle ótimo de dosagem de drogas no tratamento de pacientes infectados pelo vírus HIV . O modelo de Campello de Souza (1999) é usado para estimar a dosagem de drogas onde a função objetivo é minimizada. Esta função representa um balanço entre os benefícios do tratamento e os efeitos colaterais. A técnica de controle ótimo usada é o Princípio do Máximo de Pontryagin, a qual é simulada através do PROPT-TOMLAB - Matlab Optimal Control System Software em uma versão de demonstração. As simulações objetivam a análise de três diferentes pacientes em dois diferentes cenários. Estes cenários têm como objetivo forçar as variáveis de estado a atingirem valores "normais" a fim de estabilizar a carga viral próximo a uma taxa que seja insignificante e elevar o nível de CD4 do paciente. São simulados tratamentos cedos e tardios. As simulações computacionais compararam diferentes cenários para investigar os parâmetros de incerteza da dinâmica entre o vírus HIV e os linfócitos CD4 e CD8. Os resultados mostram que o controle ótimo permite uma melhor administração entre os efeitos positivos da terapia e os efeitos colaterais, ao invés de se usar dosagens constantes de drogas como na atual prática médica. O segundo sistema descreve a aplicação do controle ótimo, também através do Princípio Máximo de Pontryagin, para controlar o nível de glicose em indivíduos diabéticos usando o modelo matemático desenvolvido por Bergman (1971, 1981). Correlacionam-se dados reais da literatura com o modelo teórico para analisar a robustez do modelo. É também estudada a minimização do funcional objetivo para diminuir os efeitos colaterais e consequentemente melhorar o estado de saúde do paciente. Os resultados mostram os benefícios de se utilizar o controle ótimo para regular a taxa de glicose em pacientes diabéticos
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Bell, Emily Rachel. "An exploration of future orientation in adolescents' decisions to continue or terminate a pregnancy." Thesis, University of Hull, 2008. http://hydra.hull.ac.uk/resources/hull:1592.

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This study explores aspects of the future in adolescents' choices to continue or terminate pregnancy. Future orientation (FO) (e.g. Seginer, 2005) and reasons for pregnancy resolution were investigated using a researcher constructed and administered questionnaire. Three groups were included: termination of pregnancy (ToP) (n = 19), ante natal (AN) (n = 9), and never pregnant (NP) (n = 23). Participants were 13-18 years-old. Statistical and content analyses reveal groups differ in aspects of FO and reasons for pregnancy resolution choice. Future factors are shown to be important in teenagers' pregnancy resolution decisions. The impact of negative discourses about teenage pregnancy and parenting is discussed. Suggestions are made for conducting research that can advance understanding of this complex issue.
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Books on the topic "Clinical decisions"

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K, Parrish Richard, and Anderson Douglas R. 1938-, eds. Clinical decisions in glaucoma. St. Louis, Mo: Mosby, 1993.

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G, Patwardhan Avinash, ed. Scoliosis: Making clinical decisions. St. Louis: Mosby, 1989.

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J, Savino Peter, and Trobe Jonathan D. 1943-, eds. Clinical decisions in neuro-ophthalmology. St. Louis: Mosby, 1985.

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J, Savino Peter, and Trobe Jonathan D. 1943-, eds. Clinical decisions in neuro-ophthalmology. 2nd ed. St. Louis: Mosby Year Book, 1992.

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Assadi, Farahnak. Clinical Decisions in Pediatric Nephrology. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74602-9.

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Clinical decisions in medical retinal disease. St. Louis: Mosby, 1994.

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Jonsen, Albert R. Clinical ethics: A practical approach to ethical decisions in clinical medicine. 6th ed. New York: McGraw Hill, Medical Pub. Division, 2006.

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1941-, Siegler Mark, and Winslade William J, eds. Clinical ethics: A practical approach to ethical decisions in clinical medicine. 3rd ed. New York: McGraw-Hill, Health Professions Division, 1992.

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Jonsen, Albert R. Clinical ethics: A practical approach to ethical decisions in clinical medicine. 7th ed. New York: McGraw-Hill Medical, 2010.

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1941-, Siegler Mark, and Winslade William J, eds. Clinical ethics: A practical approach to ethical decisions in clinical medicine. 7th ed. New York: McGraw-Hill Professional, 2010.

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Book chapters on the topic "Clinical decisions"

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Wheeler, Robert. "Unwise Decisions." In Clinical Law for Clinical Practice, 21–22. First edition. | Boca Raton : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429320583-8.

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Wheeler, Robert. "Making Clinical Legal Decisions." In Clinical Law for Clinical Practice, 141–42. First edition. | Boca Raton : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429320583-61.

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Simpson, Scott A., and Anna K. McDowell. "Share Difficult Decisions." In The Clinical Interview, 173–75. New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429437243-55.

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Fitzgerald, J. D. "Clinical benefits." In Medicines and Risk/Benefit Decisions, 85–90. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3221-0_8.

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Srinathan, Sadeesh K., and Feng Xie. "Clinical Decision Analysis." In Difficult Decisions in Endocrine Surgery, 13–22. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92860-9_2.

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Gore, S. M., A. O. Langlands, D. J. Spiegelhalter, and H. J. Stewart. "Treatment Decisions in Breast Cancer." In Cancer Clinical Trials, 149–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83419-6_18.

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Deal, Cheri, Michele Tony, Hanane Khoury, Gihad Nesrallah, Ahmed A. Al-Jaishi, and Mireille Goetghebeur. "MCDA for the Development of Clinical Practice Guidelines and for the Prioritization Clinical Research Questions." In Multi-Criteria Decision Analysis to Support Healthcare Decisions, 239–73. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47540-0_13.

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Wheeler, Robert. "Can We Rely on Our Advance Decisions?" In Clinical Law for Clinical Practice, 99–101. First edition. | Boca Raton : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429320583-42.

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Swain, Jason E., and Thomas B. Pool. "Culture Media in IVF: Decisions for the Laboratory." In Clinical Embryology, 63–83. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8376-2_5.

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Dollery, C. T. "The risk identified from clinical trials." In Medicines and Risk/Benefit Decisions, 57–65. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3221-0_6.

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Conference papers on the topic "Clinical decisions"

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Motorin, Sergey S., Nikolay V. Golishev, and Anna A. Afanasyeva. "Clinical decisions support information system." In 2008 9th International Scientific-Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE). IEEE, 2008. http://dx.doi.org/10.1109/apeie.2008.4897066.

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Mclachlan, Scott, Evangelia Kyrimi, Bridget J. Daley, Kudakwashe Dube, Max Marsden, Sarah Finer, Graham A. Hitman, and Norman E. Fenton. "Incorporating Clinical Decisions into Standardised Caremaps." In 2020 IEEE International Conference on Healthcare Informatics (ICHI). IEEE, 2020. http://dx.doi.org/10.1109/ichi48887.2020.9374381.

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Sui, Yanan, and Joel W. Burdick. "Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/389.

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We consider sequential decision making under uncertainty, the optimization over large decision space with noisy comparative feedback. This problem can be formulated as a K-armed Dueling Bandits problem where K is the total number of decisions. When K is very large, existing dueling bandits algorithms suffer huge cumulative regret before converging on the optimal arm. This paper studies the dueling bandits problem with a large number of dependent arms. Our problem is motivated by a clinical decision making process in large decision space. We propose an efficient algorithm CorrDuel for the problem which makes decisions to simultaneously deliver effective therapy and explore the decision space. Many sequential decision making problems with large and structured decision space could be facilitated by our algorithm. After evaluated the fast convergence of CorrDuel in analysis and simulation experiments, we applied it on a live clinical trial of therapeutic spinal cord stimulation. It is the first applied algorithm towards spinal cord injury treatments and experimental results show the effectiveness and efficiency of our algorithm.
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CHEN, JONATHAN H., MARY K. GOLDSTEIN, STEVEN M. ASCH, and RUSS B. ALTMAN. "DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2015. http://dx.doi.org/10.1142/9789814749411_0019.

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Canovas-Segura, Bernardo, Francesca Zerbato, Barbara Oliboni, Carlo Combi, Manuel Campos, Antonio Morales, Jose M. Juarez, Roque Marin, and Francisco Palacios. "A Process-Oriented Approach for Supporting Clinical Decisions for Infection Management." In 2017 IEEE International Conference on Healthcare Informatics (ICHI). IEEE, 2017. http://dx.doi.org/10.1109/ichi.2017.73.

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Marukhina, Olga V., Olga G. Berestneva, and Nina P. Stepanenko. "CLINICAL DECISIONS SUPPORT SYSTEM FOR CHOOSING THE TREATMENT COURSE CHILDREN WITH ENDOCRINOPATHIES." In International Conference ICT, Society, and Human Beings 2019. IADIS Press, 2019. http://dx.doi.org/10.33965/ict2019_201908l006.

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Ponciano-Silva, Marcelo, Juliana P. Souza, Pedro H. Bugatti, Marcos V. N. Bedo, Daniel S. Kaster, Rosana T. V. Braga, Angela D. Bellucci, Paulo M. Azevedo-Marques, Caetano Traina, and Agma J. M. Traina. "Does a CBIR system really impact decisions of physicians in a clinical environment?" In 2013 IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2013. http://dx.doi.org/10.1109/cbms.2013.6627762.

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Dakua, S. P., N. V. Navkar, J. Abi-Nahed, D. Groen, M. O. Bernabeu, M. A. R. Saghir, H. Kamel, A. Al-Ansari, and P. V. Coveney. "Towards a computational system to support clinical treatment decisions for diagnosed cerebral aneurysms." In 2014 Middle East Conference on Biomedical Engineering (MECBME). IEEE, 2014. http://dx.doi.org/10.1109/mecbme.2014.6783259.

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Carr, J., D. Collingridge, T. Allen, C. Vines, R. Srivastava, J. Rubin, and N. C. Dean. "Small Hospitals, Big Decisions: Rural Clinicians' Response to Electronic Clinical Decision Support for the Treatment of Community Acquired Pneumonia." In American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a2149.

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AbuKhousa, Eman, and Piers Campbell. "Predictive data mining to support clinical decisions: An overview of heart disease prediction systems." In 2012 International Conference on Innovations in Information Technology (IIT). IEEE, 2012. http://dx.doi.org/10.1109/innovations.2012.6207745.

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Reports on the topic "Clinical decisions"

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Manski, Charles. Improving Clinical Guidelines and Decisions under Uncertainty. Cambridge, MA: National Bureau of Economic Research, October 2017. http://dx.doi.org/10.3386/w23915.

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Johnson, Erin, M. Marit Rehavi, David Chan, and Daniela Carusi. A Doctor Will See You Now: Physician-Patient Relationships and Clinical Decisions. Cambridge, MA: National Bureau of Economic Research, September 2016. http://dx.doi.org/10.3386/w22666.

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Biesecker, Barbara, Melissa Raspa, Douglas Rupert, Rebecca Moultrie, Robert Furberg, and Lauren A. McCormack. Making Clinical Trials More Patient-Centered Using Digital Interactive E-Consent Tools. RTI Press, October 2019. http://dx.doi.org/10.3768/rtipress.2019.op.0063.1910.

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Research participants are required to give their consent to participate in clinical trials and nonexempt government-funded studies. The goal is to facilitate participant understanding of the intent of the research, its voluntary nature, and the potential benefits and harms. Ideally, participants make an informed choice whether to participate; one that is based on having sufficient relevant knowledge and that is consistent with their values and preferences. Achieving this objective can be challenging, and as such, many scholars have declared the consent process flawed or “broken.” Moreover, clinical trials are complex studies, and compelling evidence suggests that current consent processes are inadequate in achieving informed choice. E-consent offers a dynamic, engaging consent delivery mode that can effectively support making informed decisions about whether to participate in a trial.
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Millington, Kerry. COVID-19 Health Evidence Summary No.113. Institute of Development Studies (IDS), February 2021. http://dx.doi.org/10.19088/k4d.2021.023.

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This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Infection Prevention and Control; Therapeutics; Vaccines; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs and Online learning & events.
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Millington, Kerry, and Samantha Reddin. COVID-19 Health Evidence Summary No.108. Institute of Development Studies (IDS), January 2021. http://dx.doi.org/10.19088/k4d.2021.007.

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This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Testing; Therapeutics; Vaccines; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events
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6

Millington, Kerry. COVID-19 Health Evidence Summary No.115. Institute of Development Studies (IDS), March 2021. http://dx.doi.org/10.19088/k4d.2021.030.

Full text
Abstract:
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Infection Prevention and Control; Therapeutics; Vaccines; Indirect impact of COVID-19; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events.
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7

Millington, Kerry. COVID-19 Health Evidence Summary No.116. Institute of Development Studies (IDS), March 2021. http://dx.doi.org/10.19088/k4d.2021.035.

Full text
Abstract:
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Therapeutics; Vaccines; Indirect impact of COVID-19; Health systems; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs and Online learning & events.
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8

Piotrowski, Helen. COVID-19 Health Evidence Summary No.121. Institute of Development Studies (IDS), April 2021. http://dx.doi.org/10.19088/k4d.2021.065.

Full text
Abstract:
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Therapeutics; Vaccines; Leadership and governance; Health systems; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events.
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9

Piotrowski, Helen. COVID-19 Health Evidence Summary No.122. Institute of Development Studies (IDS), May 2021. http://dx.doi.org/10.19088/k4d.2021.075.

Full text
Abstract:
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Vaccines; Indirect impact of COVID-19; Social Science; Leadership and governance; Health systems; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs and Online learning & events.
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10

Millington, Kerry, and Samantha Reddin. COVID-19 Health Evidence Summary No.110. Institute of Development Studies (IDS), February 2021. http://dx.doi.org/10.19088/k4d.2021.013.

Full text
Abstract:
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Therapeutics; Vaccines; Indirect impact of COVID-19; Social Science; Leadership and governance; Comments, Editorials, Opinions, Blogs, News; Guidelines, Statements & Tools; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events
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