Relevant bibliographies by topics / Quality indicators

Academic literature on the topic 'Quality indicators'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Quality indicators"

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Takahashi, Osamu, and Tsuguya Fukui. "2. Quality Indicators." Nihon Naika Gakkai Zasshi 99, no. 12 (2010): 3035–41. http://dx.doi.org/10.2169/naika.99.3035.

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Decker, Carole. "Quality Indicators." Cardiology in Review 14, no. 6 (November 2006): 308–11. http://dx.doi.org/10.1097/01.crd.0000244461.25429.81.

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Zilberberg, Marya D., and Andrew F. Shorr. "Quality Indicators." Critical Care Medicine 42, no. 8 (August 2014): 1946–47. http://dx.doi.org/10.1097/ccm.0000000000000459.

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Kleinpell, Ruth M. "Quality Indicators." AACN Clinical Issues: Advanced Practice in Acute and Critical Care 16, no. 2 (April 2005): 119–20. http://dx.doi.org/10.1097/00044067-200504000-00001.

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VENTURA, MARLENE R., JANET RIZZO, and SHERRIE LENZ. "Quality Indicators." Nursing Management (Springhouse) 24, no. 1 (January 1993): 46???50. http://dx.doi.org/10.1097/00006247-199301000-00009.

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Prosser-Snelling, Edward, and Edward Morris. "Quality Indicators." Obstetrics, Gynaecology & Reproductive Medicine 27, no. 9 (September 2017): 290–92. http://dx.doi.org/10.1016/j.ogrm.2017.06.008.

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Hjorth-Andersen, Chr. "Quality indicators." European Economic Review 35, no. 8 (December 1991): 1491–505. http://dx.doi.org/10.1016/0014-2921(91)90014-a.

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Flomenbaum, Neal. "Putting Quality Into Quality Indicators." Emergency Medicine 48, no. 4 (April 1, 2016): 148. http://dx.doi.org/10.12788/emed.2016.0025.

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Mahmudov, Yusuf Ganievich, and Bakhtiyor Berdievich Imanov. "Lesson quality indicators." Asian Journal of Multidimensional Research 10, no. 10 (2021): 653–56. http://dx.doi.org/10.5958/2278-4853.2021.00784.9.

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Salzer, Mark S., Carol T. Nixon, L. James A. Schut, Marc S. Karver, and Leonard Bickman. "Validating Quality Indicators." Evaluation Review 21, no. 3 (June 1997): 292–309. http://dx.doi.org/10.1177/0193841x9702100302.

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Dissertations / Theses on the topic "Quality indicators"

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Schuh, Christine. "Performance indicators for indoor air quality." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0016/NQ54809.pdf.

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Yau, Yick-yee Joyce, and 丘奕怡. "Bacterial indicators for beach water quality." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31254445.

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Yau, Yick-yee Joyce. "Bacterial indicators for beach water quality /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21301554.

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Robinson, David Keith. "Developing clinical quality indicators in psychiatric nursing." Thesis, Anglia Ruskin University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259517.

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van, Ree H. J. "Service quality indicators for business support services." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19902/.

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Quality is critical to corporate success as it plays a vital role in improving organisational productivity. It can be defined as ‘the totality of inherent characteristics of a product or service that bear on its ability to increase the demand for that product or service at a fixed price’ and can best be measured by capturing customer perceptions of the performance of those characteristics. Customising the SERVPERF methodology to measure service quality in a business-to-business context and subsequently testing it on both customers and suppliers of cleaning, catering and security services, the research led to a number of important and valuable insights concerning the service quality construct in a business-to-business environment. First, service quality in relation to cleaning, catering and security services consists of nine clear dimensions: reliability, clout, reputation, awareness, competitiveness, collaboration, accessibility, competence and assurance. The nine-dimensional construct identified shows high reliability and good validity in statistical terms. Furthermore, eight of the nine service quality dimensions are strongly or moderately yet significantly related to customer perceived service quality and customer satisfaction - clout being the exception. The same eight dimensions are significantly, but moderately related to purchase intention - suggesting that that there might be other constructs important in making a purchase decision (e.g. the costs of service delivery). Third, relating the nine service quality dimensions to the financial performance of supplier organisations, it was identified that six of the nine dimensions have significant relationships with one or more of the ten financial performance measures investigated - reliability, accessibility and competence being the exceptions. Finally, it was identified that customer organisations have significantly lower perceptions of the service quality they receive than do supplier organisations for competitiveness, collaboration, accessibility and competence. Moreover, customer perceived performance is significantly lower than customer perceived importance for eight of the nine service quality dimensions. For customer organisations, the empirical findings can be used to develop a framework of Service Quality Indicators, which can be used for monitoring and benchmarking service quality perception. For supplier organisations, the findings can be used for resource-allocation decisions pertaining to improve service quality, customer satisfaction and ultimately purchase intentions. It should be noted that the research is exploratory in nature and has only begun to address the many issues that are important in the management of business support services, but the questions addressed - what quality dimensions are important for customer satisfaction and what quality dimensions are important for supplier performance - are arguably among the most important in service quality management.
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Smirl, Julie E. "QUALITY-OF-LIFE INDICATORS IMPACTING OLDER ADULTS." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/dissertations/1044.

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Radical changes in the senior citizen population have been triggered by the addition of the baby-boomer generation, which drastically increased the growth of this cohort group. A determination of needs for this diverse group of people is necessary for clinical professionals to employ evidence-based practices in the daily provision of services. Purpose: The focus of this study was to measure quality-of-life indicators by concentrating on the association of chronic illness and mental well-being in predicting long-term relationship satisfaction. A sample of older adults were studied in relationship with health and wellness concerns guided by previous research conducted by the Centers for Disease Control and Prevention (CDC, 2011a), and the World Health Organization (1991). Methods: The population selected for this study was older adults participating in outpatient mental health services. A representative sample of 111 participants was used in the statistical analysis of this project. The utilization of the Revised Dyadic Adjustment Scale (Busby, Crane, Larson, & Christensen, 1995) established relationship satisfaction scores among this varied population. Correlation analysis was used to determine the association between seven variables. The factors of interest were: chronic health, chronic pain, mental health acute or chronic, and scores on mental health screenings routinely used in the outpatient mental health clinics included in this study. These variables were broken down in a hierarchical multiple regression model to find out if any factors predicted overall relationship satisfaction. Results: Hierarchical multiple regression analysis delineated an inverse relationship between mental health status (acute or chronic) and degree of overall relationship satisfaction. Chronic health conditions and pain ratings were positively related, however, did not associate negatively with overall relationship satisfaction as hypothesized. Positive relationships were found among the following variables: anxiety ratings and pain-related impairment, increased reports of anxiety with chronic mental health status, and pain ratings with higher risk for suicide. Low correlation coefficient values found throughout the statistical analysis make these findings tentative. Conclusions: The indications of this study confirmed a negative association between chronic mental illness and overall relationship satisfaction scores. This highlights the importance of addressing long-term psychiatric issues as an integral part of working with older adults. Age-related decline creates a functional need for reliance on others complicating satisfaction in intimate partnerships. Mental health practitioners need to be aware of the struggles found among the growing population of older adults to address their treatment and case management needs. Additional research is necessary to determine the indicators of relationship satisfaction impacting quality-of-life among older adults. Key words: quality-of-life, older adults, generational status, chronic illness, chronic pain, mental health, revised dyadic adjustment scale.
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Baginetas, Konstantinos N. "Agri-environmental sustainability indicators : inter-disciplinary development of soil quality indicators in Nottinghamshire, UK." Thesis, University of Nottingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422761.

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Gill, Peter John. "Developing paediatric quality indicators for UK general practice." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:1837f24f-e501-4e56-906d-6080191f09cb.

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The overall aim of this thesis is to define a candidate set of quality indicators that are evidence-based, feasible to implement, and have the potential to improve the quality of care provided for children in UK general practice. The indicators were developed using a three-stage process. First, the areas and aspects of care of highest priority for quality indicator development were identified. This was achieved by seeking the views of primary care clinicians and by undertaking a formal analysis of unplanned hospital admissions for ambulatory care sensitive conditions. Then, the evidence-base to underpin indicator development was identified through an overview of Cochrane systematic reviews of interventions relevant to the primary care of children. A search of SIGN and NICE national guidelines was also conducted to inform the evidence-base. Lastly, an expert panel determined the formulation and selection of indicators by applying the RAND appropriateness methodology. This process created a final set of 26 quality indicators in six priority areas: early recognition of potentially serious illness (n=7); child protection and safeguarding (n=4); mental health (n=4); health promotion (n=1); routinely managed conditions (n=6); and general practice management (n=4). The main strength of these indicators is that they reflect a strong professional consensus on their validity and feasibility. The main weakness is that the indicators are underpinned by evidence mainly derived from expert opinion rather than formal research; the requirement for professional consensus means that they do not challenge existing models of care delivery.
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Kwong, Pui-ki. "Surface water quality indicators in China and their implications for sustainability." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36618718.

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STRICKLER, WENDY LORRAINE ALINE. "A DESCRIPTIVE STUDY OF INDICATORS OF EFFECTIVE INTERVENTIONS FOR SUPPORTING STUDENTS." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1085433787.

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Books on the topic "Quality indicators"

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Arizona. Dept. of Environmental Quality. Arizona water quality environmental indicators. [Phoenix, AZ]: The Dept., 1997.

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National Research Council (U.S.). Transportation Research Board., ed. Indicators of quality in maintenance. Washington, D.C: Transportation Research Board, National Research Council, 1989.

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Alberta. Alberta Education. Planning and Policy Secretariat. Educational quality indicators: Annotated bibliography. 2nd ed. Edmonton, Alta: Alberta Education, Planning and Policy Secretariat, 1990.

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Ridzi, Frank, Chantal Stevens, and Lyle Wray, eds. Community Quality-of-Life Indicators. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06940-6.

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Sirgy, M. Joseph. Community Quality-of-Life Indicators. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10208-0.

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Sirgy, M. Joseph, Don Rahtz, and David Swain, eds. Community Quality-of-Life Indicators. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/978-1-4020-4625-4.

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Ridzi, Frank, Chantal Stevens, and Melanie Davern, eds. Community Quality-of-Life Indicators. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48182-7.

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Sirgy, M. Joseph, Don Rahtz, and Dong-Jin Lee. Community Quality-of-Life Indicators. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2202-9.

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Terrell, Charles R. Water quality indicators guide: Surface waters. [Washington, D.C.]: U.S. Dept. of Agriculture, Soil Conservation Service, 1989.

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Association, American Nurses'. Nursing quality indicators: Guide for implementation. Washington, D.C: The Association, 1996.

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Book chapters on the topic "Quality indicators"

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Sarigiannis, Dimosthenis A. "Indoor Air Quality Indicators." In Environmental Indicators, 827–41. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9499-2_46.

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Herrmann, Peter, Laurent J. G. van der Maesen, and Alan Walker. "Social Quality Indicators." In Social Quality, 94–115. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1007/978-0-230-36109-6_5.

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Kingston, J. C., B. F. Cumming, A. J. Uutala, J. P. Smol, K. E. Camburn, D. F. Charles, S. S. Dixit, and R. G. Kreis. "Biological quality control and quality assurance: a case study in paleolimnological biomonitoring." In Ecological Indicators, 1542–44. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-4661-0_65.

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Monakhov, Sergey, Olga Esina, Galina Monakhova, and Vitaly Tatarnikov. "Environmental Quality Assessment: Geoenvironmental Indices." In Environmental Indicators, 461–78. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9499-2_27.

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Haire, Michael S., Narendra N. Panday, Diana K. Domotor, and Dana G. Flora. "Chesapeake Bay Water Quality Indices." In Ecological Indicators, 1115–34. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-4661-0_22.

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van Veldhoven, Robert H. M., and Arthur H. M. van Roermund. "System Quality Indicators." In Robust Sigma Delta Converters, 13–26. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0644-6_2.

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Morse, Stephen. "Land Quality Indicators." In Encyclopedia of Quality of Life and Well-Being Research, 3495–96. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_1596.

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Wiederkehr, Peter, and Seung-Joon Yoon. "Air Quality Indicators." In Urban Air Pollution — European Aspects, 403–18. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-015-9080-8_23.

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Morse, Stephen. "Land Quality Indicators." In Encyclopedia of Quality of Life and Well-Being Research, 1–2. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-69909-7_1596-2.

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Walker, Alan, and Laurent van der Maesen. "Social Quality and Quality of Life." In Social Indicators Research Series, 13–31. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2903-5_2.

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Conference papers on the topic "Quality indicators"

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Papadakis, Mike, Thierry Titcheu Chekam, and Yves Le Traon. "Mutant Quality Indicators." In 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). IEEE, 2018. http://dx.doi.org/10.1109/icstw.2018.00025.

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Ortiz Mayoral, Herminia, Reyes Calzado López, Rosario Melchor Iñiguez, Nuria Abad Santamaría, Maria Teresa Río Ramírez, Ismael Ali García, Bárbara Steen, Mercedes Izquierdo Patrón, and Beatriz Morales Chacón. "Quality indicators in pleural pathology." In ERS International Congress 2018 abstracts. European Respiratory Society, 2018. http://dx.doi.org/10.1183/13993003.congress-2018.pa3165.

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Mangas, C., E. Santana, J. Cubiella, A. Suárez, I. Portillo, A. Seoane, M. Ponce, et al. "FULFILMENT OF COLONOSCOPY QUALITY INDICATORS." In ESGE Days 2018 accepted abstracts. Georg Thieme Verlag KG, 2018. http://dx.doi.org/10.1055/s-0038-1637363.

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Ivanets, O. B., I. V. Morozova, and Yu M. Tereshchenko. "Approach to Assessing Quality Indicators." In 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL). IEEE, 2019. http://dx.doi.org/10.1109/caol46282.2019.9019564.

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Tuomikoski, Markus, Sami Ihme, Arttu Huttunen, Marko Korkalainen, and Samuli Yrjana. "Indoor air quality sensing indicators." In 2016 6th Electronic System-Integration Technology Conference (ESTC). IEEE, 2016. http://dx.doi.org/10.1109/estc.2016.7764711.

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Wimalasena, NN, A. Chang-Richards, KIK Wang, and K. Dirks. "Housing quality indicators: A systematic review." In 10th World Construction Symposium. Building Economics and Management Research Unit (BEMRU), University of Moratuwa, 2022. http://dx.doi.org/10.31705/wcs.2022.43.

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A wealth of studies has demonstrated the significance of adequate or quality housing on occupant’s productivity, performance, comfort and health. However, insufficient data on the conditions of existing housing stocks and a lack of consensus measures of housing quality hinder housing developments from achieving residential needs. Due to the lack of quality indicators, the quality of housing is not often assessed. Therefore, this paper presents a systematic review using the PRISMA protocol to provide an overview of the housing quality indicators that can be employed to evaluate housing quality. The review consisted of 62 studies investigating 66 housing quality indicators. Each fall into one of eight categories, namely 1) dwelling unit architectural design characteristics and features; 2) user comfort; 3) housing site location and neighbourhood; 4) building services; 5) construction quality and stability; 6) economic aspect; 7) building maintenance; or 8) sustainability. The results show that investigating housing quality indicators is a growing research field where adequate ventilation was the most critical indicator of a quality home. Since the identified indicators are essential determinants of a quality house, architects and engineers can integrate these features at the design and construction stages in upgrading the conditions of dwellings while satisfying occupant’s comfort and quality of life. Further, governments can develop housing quality standards or regulations using these indicators to improve the quality of new housing constructions.
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Berlanga, Rafael, Indira Lanza-Cruz, and Maria Jose Aramburu. "Quality Indicators for Social Business Intelligence." In 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS). IEEE, 2019. http://dx.doi.org/10.1109/snams.2019.8931862.

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Rydberg-Cox, Jeffrey A., Anne Mahoney, and Gregory R. Crane. "Document quality indicators and corpus editions." In the first ACM/IEEE-CS joint conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/379437.379757.

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Chen, Yen-Liang, Jacky Huang, Rita Lee, Chen-Ming Wang, Chih-Ming Ke, and Tsai-Sheng Gau. "Quality indicators of image-based overlay." In SPIE Advanced Lithography, edited by Alexander Starikov. SPIE, 2012. http://dx.doi.org/10.1117/12.917995.

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Rao, Hrishikesh, Kedar Phatak, and Elie Khoury. "Improving Speaker Recognition with Quality Indicators." In 2021 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2021. http://dx.doi.org/10.1109/slt48900.2021.9383627.

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Reports on the topic "Quality indicators"

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Kleerup, Eric C., and David H. Solomon. Quality Indicators for Quality of Care During Hospitalization for Vulnerable Elder Persons. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada427482.

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Lanjouw, Jean, and Mark Schankerman. The Quality of Ideas: Measuring Innovation with Multiple Indicators. Cambridge, MA: National Bureau of Economic Research, September 1999. http://dx.doi.org/10.3386/w7345.

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Westfall, James A. FIA national assessment of data quality for forest health indicators. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2009. http://dx.doi.org/10.2737/nrs-gtr-53.

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Sanz, E., P. Alonso, B. Haidar, H. Ghaemi, and L. García. Key performance indicators (KPIs). Scipedia, 2021. http://dx.doi.org/10.23967/prodphd.2021.9.002.

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The project “Social network tools and procedures for developing entrepreneurial skills in PhD programmes” (prodPhD) aims to implement innovative social network-based methodologies for teaching and learning entrepreneurship in PhD programmes. The multidisciplinary teaching and learning methodologies to be developed will enable entrepreneurship education to be introduced into any PhD programme, providing students with the knowledge, skills, and motivation to engage in entrepreneurial activities. However, the use of the output of the project will depend on the nature and profile of the research or scientific field. In this context, key performance indicators (KPIs) form the base on which the quality and scope of the methodologies developed in the project will be quantified and benchmarked. The project’s final product will be an online tool that higher education students can use to learn entrepreneurship from a social network perspective. Performance measurement is one of the first steps of any project and involves the choice and use of indicators to measure the effectiveness and success of the project’s methods and results. All the KPIs have been selected according to criteria of relevance, measurability, reliability, and adequacy, and they cover the process, dissemination methods, and overall quality of the project. In this document, each KPI is defined together with the units and instruments for measuring it. In the case of qualitative KPIs, five-level Likert scales are defined to improve indicator measurability and reliability. The KPIs for prodPhD are divided into three main dimensions, depending on the stage of the project they evaluate. The three main dimensions are performance and development (which are highly related to the project’s process), dissemination and impact (which are more closely correlated with the project’s output), and overall project quality. Different sources (i.e., European projects and papers) have been drawn upon to define a set of 51 KPIs classified into six categories, according to the project phase they aim to evaluate. An Excel tool has been developed that collects all the KPIs analysed in the production of this document. This tool is shared in the Scipedia repository.
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Wenger, Neil S., and Roy Young. Quality Indicators of Continuity and Coordination of Care for Vulnerable Elder Persons. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada427411.

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Warren, Charlotte, James Kimani, Jackline Kivunaga, Brian Mdawida, Charity Ndwiga, Katharine McCarthy, and Ann Blanc. Validating indicators of the quality of maternal health care: Final report, Kenya. Population Council, 2014. http://dx.doi.org/10.31899/rh10.1008.

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Berdichevsky, Karla, Claudia Diaz, Katharine McCarthy, and Ann Blanc. Validating indicators of the quality of maternal health care: Final report, Mexico. Population Council, 2014. http://dx.doi.org/10.31899/rh10.1009.

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Tumlinson, Katherine. Measuring quality of care: A review of previously used methodologies and indicators. Population Council, 2016. http://dx.doi.org/10.31899/rh8.1048.

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Tumlinson, Katherine. Fact sheet—Measuring quality of care: A review of methodologies and indicators. Population Council, 2016. http://dx.doi.org/10.31899/rh8.1049.

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Roux, Anne M., Jessica E. Rast, K. A. Anderson, and Paul T. Shattuck. National Autism Indicators Report: Vocational Rehab. A.J. Drexel Autism Institute, May 2016. http://dx.doi.org/10.17918/nairvocrehab2016.

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Employment is about more than simply earning a paycheck - it influences quality of life, independence, and wellness. Historically, employment outcomes for adults with autism are poor. The U.S. Vocational Rehabilitation system (VR) is designed to provide support to states for implementation of services to assist people with disabilities to prepare for, find, and keep employment. VR data allow us to examine some outcomes for those with autism compared to their peers.
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