Relevant bibliographies by topics / Healthcare Data Quality

Contents

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

Academic literature on the topic 'Healthcare Data Quality'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Healthcare Data Quality"

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Charnock, Victoria. "Electronic healthcare records and data quality." Health Information & Libraries Journal 36, no. 1 (2019): 91–95. http://dx.doi.org/10.1111/hir.12249.

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Berndt, D. J., J. W. Fisher, A. R. Hevner, and J. Studnicki. "Healthcare data warehousing and quality assurance." Computer 34, no. 12 (2001): 56–65. http://dx.doi.org/10.1109/2.970578.

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Warwick, William. "A Framework to Assess Healthcare Data Quality." European Journal of Social and Behavioural Sciences 13, no. 2 (2015): 1730–35. http://dx.doi.org/10.15405/ejsbs.156.

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Cadarette, S. M., S. B. Jaglal, L. Raman-Wilms, D. E. Beaton, and J. M. Paterson. "Osteoporosis quality indicators using healthcare utilization data." Osteoporosis International 22, no. 5 (2010): 1335–42. http://dx.doi.org/10.1007/s00198-010-1329-8.

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Deghati, Shirin. "Impact of Data Governance on Data Quality in Healthcare Institutions." American Journal of Data, Information and Knowledge Management 5, no. 1 (2024): 39–48. http://dx.doi.org/10.47672/ajdikm.2351.

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Purpose: The aim of the study was to assess the impact of data governance on data quality in healthcare institutions. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that institutions with robust data governa
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Kerr, Karolyn A., Tony Norris, and Rosemary Stockdale. "The strategic management of data quality in healthcare." Health Informatics Journal 14, no. 4 (2008): 259–66. http://dx.doi.org/10.1177/1460458208096555.

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C., S. Sindhu, and P. Hegde Nagaratna. "A Novel Integrated Framework to Ensure Better Data Quality in Big Data Analytics over Cloud Environment." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (2017): 2798–805. https://doi.org/10.11591/ijece.v7i5.pp2798-2805.

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With advent of Big Data Analytics, the healthcare system is increasingly adopting the analytical services that is ultimately found to generate massive load of highly unstructured data. We reviewed the existing system to find that there are lesser number of solutions towards addressing the problems of data variety, data uncertainty, and data speed. It is important that an errorfree data should arrive in analytics. Existing system offers single-hand solution towards single platform. Therefore, we introduced an integrated framework that has the capability to address all these three problems in on
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Sumaedi, Sik, Medi Yarmen, and I. Gede Mahatma Yuda Bakti. "Healthcare service quality model." International Journal of Productivity and Performance Management 65, no. 8 (2016): 1007–24. http://dx.doi.org/10.1108/ijppm-08-2014-0126.

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Purpose The purpose of this paper is to develop and test a multi-level healthcare service quality (HSQ) model in Jakarta, Indonesia. Design/methodology/approach The research used a quantitative research method. Data were collected via a survey with questionnaire. The respondents are 154 patients of a healthcare institution in Jakarta, Indonesia. Findings The research result shows a multi-level HSQ model. The HSQ model consists of three primary dimensions, namely, healthcare service outcome, healthcare service interaction, and healthcare service environment. Healthcare service outcome has three
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Nandish Shivaprasad. "Metadata Repositories in Healthcare Data Architecture." Journal of Sustainable Solutions 1, no. 4 (2024): 176–86. https://doi.org/10.36676/j.sust.sol.v1.i4.50.

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Meta databases are also very important in managing healthcare information since they provide an effective framework for archiving different varieties of healthcare data. These repositories enhance data sharing and usage, aiming at data correspondence, accuracy, and security of the data in the health sector. Due to rising tendencies of developing complicated health care models, the management of metadata is crucial for enhancing the quality of the health care delivery and maintaining the legal requirements. In this paper, we examine technologies for metadata repositories and potential applicati
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Mehmood, Ali Mohammed, Ali Mohammed Murtuza, and Ali Mohammed Vazeer. "Impact of Artificial Intelligence on the Automation of Digital Health System." International Journal of Software Engineering & Applications (IJSEA) 13, no. 6 (2022): 23–29. https://doi.org/10.5281/zenodo.7417611.

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Automating digital systems in healthcare plays a significant role in transforming the quality-of-care services delivered to patients across the board. This role is anticipated to be accomplished by the development and implementation of artificial intelligence in healthcare which has the potential to impact the provision of healthcare services. This paper sought to investigate the impact of adopting and implementing artificial intelligence on the automation of digital health systems within the different levels of healthcare.
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Dissertations / Theses on the topic "Healthcare Data Quality"

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Tiano, Donato. "Learning models on healthcare data with quality indicators." Electronic Thesis or Diss., Lyon 1, 2022. http://www.theses.fr/2022LYO10182.

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Les séries temporelles sont des collections de données obtenues par des mesures dans le temps. Cette données vise à fournir des éléments de réflexion pour l'extraction d'événements et à les représenter dans une configuration compréhensible pour une utilisation ultérieure. L'ensemble du processus de découverte et d'extraction de modèles à partir de l'ensemble de données s'effectue avec plusieurs techniques d'extraction, notamment l'apprentissage automatique, les statistiques et les clusters. Ce domaine est ensuite divisé par le nombre de sources adoptées pour surveiller un phénomène. Les séries
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Echeverri, Ana Lucia Hincapie. "Relationship between Perceived Healthcare Quality and Patient Safety." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/283602.

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The objectives of this study were to examine the association between patient perceived healthcare quality and self-reported medical, medication, and laboratory errors using cross-sectional and cross-national questionnaire data from eleven countries. In this research, quality of care was measured by a multi-faceted construct, which adopted the patient's perspectives. Five separated quality of care scales were assessed: Access to Care, Continuity of care, Communication of Care, Care Coordination, and Provider's Respect for Patients' Preferences. The findings from this investigation support a nu
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Hadziabdic, Emina. "The use of interpreter in healthcare : Perspectives of individuals, healthcare staff and families." Doctoral thesis, Linnéuniversitetet, Institutionen för hälso- och vårdvetenskap, HV, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-14418.

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This thesis focuses on the use of interpreters in Swedish healthcare. The overall aim was to explore how individuals, healthcare professionals and family members experience and perceive the use of interpreters in healthcare. The study design was explorative and descriptive. The thesis included Serbo-Croatian(Bosnian/Croatian/Serbian)speaking individuals(n=17), healthcare professionals(n=24), official documents(n=60)and family members(n=10)of individuals using interpreters in healthcare. Individual interviews, written descriptions, review of official documents in the form of incident reports fr
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Thati, Satish Kumar, and Venkata Praneeth Mareedu. "Determining the Quality of Human Movement using Kinect Data." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13819.

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Health is one of the most important elements in every individual’s life. Even though there is much advancement in science, the quality of healthcare has never been up to the mark. This appears to be true especially in the field of Physiotherapy. Physiotherapy is the analysis of human joints and bodies and providing remedies for any pains or injuries that might have affected the physiology of a body. To give patients a top notch quality health analysis and treatment, either the number of doctors should increase, or there should be an alternative replacement for a doctor. Our Master Thesis is ai
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Leicester, Howard James. "Improving data quality in English healthcare : from case studies to an applied framework." Thesis, City University London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407556.

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Mchunu, Nokubalela Ntombiyethu. "Adequacy of healthcare information systems to support data quality in the public healthcare sector, in the Western Cape, South Africa." Thesis, Cape Peninsula University of Technology, 2012. http://hdl.handle.net/20.500.11838/1387.

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Thesis submitted in fulfilment of the requirements for the degree Master of Technology (MTech) in Information Technology In the Faculty of Informatics and Design, at the Cape Peninsula University of Technology (CPUT), 2013<br>Healthcare services are vital to all human beings, as our daily lives depend on them. In South Africa approximately eighty per cent of the population uses the public healthcare services. In the current healthcare systems data corruption exists which threatens data quality in the systems. The aim of this study was to understand the existing information handling processes a
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Pollard, Olivia L. "A Delphi Study Analysis of Best Practices for Data Quality and Management in Healthcare Information Systems." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/7501.

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Healthcare in the US continues to suffer from the poor data quality practices processes that would ensure accuracy of patient health care records and information. A lack of current scholarly research on best practices in data quality and records management has failed to identify potential flaws within the relatively new electronic health records environment that affect not only patient safety but also cost, reimbursements, services, and most importantly, patient safety. The focus of this study was to current best practices using a panel of 25 health care industry data quality experts. The conc
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Schmitt, Jochen, Katrin Arnold, Diana Druschke, et al. "Early comprehensive care of preterm infants - effects on quality of life, childhood development, and healthcare utilization: study protocol for a cohort study linking administrative healthcare data with patient reported primary data." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-214231.

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Background About 9 % of all children in Germany are born preterm. Despite significant improvements of medical care, preterm infants are at a greater risk to develop short and long term health complications. Negative consequences of preterm birth include neurodevelopmental disabilities, behavioral problems or learning disorders. Most data on effects of prematurity are derived from single or multi-center studies and not population-based. Since some of the long term problems of preterm delivery are associated with a disturbed parent-child interaction originating in the neonatal period, several in
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Schmitt, Jochen, Katrin Arnold, Diana Druschke, et al. "Early comprehensive care of preterm infants - effects on quality of life, childhood development, and healthcare utilization: study protocol for a cohort study linking administrative healthcare data with patient reported primary data." BioMed Central, 2016. https://tud.qucosa.de/id/qucosa%3A29977.

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Background About 9 % of all children in Germany are born preterm. Despite significant improvements of medical care, preterm infants are at a greater risk to develop short and long term health complications. Negative consequences of preterm birth include neurodevelopmental disabilities, behavioral problems or learning disorders. Most data on effects of prematurity are derived from single or multi-center studies and not population-based. Since some of the long term problems of preterm delivery are associated with a disturbed parent-child interaction originating in the neonatal period, several in
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Assareh, Hassan. "Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/53342/1/Hassan_Assareh_Thesis.pdf.

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular
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Books on the topic "Healthcare Data Quality"

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R, Mallory Steven, ed. Software quality assurance SOPs for healthcare manufacturers. Interpharm Press, 1997.

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Mallory, Steven R. Software quality assurance SOPs for healthcare manufacturers. 2nd ed. Interpharm Press, 2002.

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Duffy, Vincent G. Advances in human aspects of healthcare. Taylor & Francis, 2012.

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R, Ransom Elizabeth, ed. The healthcare quality book: Vision, strategy, and tools. 2nd ed. Health Administration Press, 2008.

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Simpson, Ned J., and Kenneth A. Kleinberg. Implementation guide to bar coding and auto-ID in healthcare: Improving quality and patient safety. HIMSS, 2009.

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IEEE Dallas Engineering in Medicine and Biology Workshop (2007 University of Texas at Dallas). 2007 IEEE Dallas Engineering in Medicine and Biology Workshop: Emerging technologies for healthcare and quality of life, November 11-12, 2007, the University of Texas at Dallas, Richardson, Texas. Edited by Bhatia Dinesh Kumar 1964-, Rao Shekar, and Hande Abhiman A. IEEE Operations Center, 2007.

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IEEE Dallas Engineering in Medicine and Biology Workshop (2007 University of Texas at Dallas). 2007 IEEE Dallas Engineering in Medicine and Biology Workshop: Emerging technologies for healthcare and quality of life, November 11-12, 2007, the University of Texas at Dallas, Richardson, Texas. Edited by Bhatia Dinesh Kumar 1964-, Rao Shekar, and Hande Abhiman A. IEEE Operations Center, 2007.

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Dallas), IEEE Dallas Engineering in Medicine and Biology Workshop (2007 University of Texas at. 2007 IEEE Dallas Engineering in Medicine and Biology Workshop: Emerging technologies for healthcare and quality of life, November 11-12, 2007, the University of Texas at Dallas, Richardson, Texas. IEEE Operations Center, 2007.

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IEEE Dallas Engineering in Medicine and Biology Workshop (2007 University of Texas at Dallas). 2007 IEEE Dallas Engineering in Medicine and Biology Workshop: Emerging technologies for healthcare and quality of life, November 11-12, 2007, the University of Texas at Dallas, Richardson, Texas. Edited by Bhatia Dinesh Kumar 1964-, Rao Shekar, and Hande Abhiman A. IEEE Operations Center, 2007.

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1957-, Swift Elaine K., and Institute of Medicine (U.S.), eds. Guidance for the national healthcare disparities report. The National Academies Press, 2002.

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Book chapters on the topic "Healthcare Data Quality"

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Mans, Ronny S., Wil M. P. van der Aalst, and Rob J. B. Vanwersch. "Data Quality Issues." In Process Mining in Healthcare. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16071-9_6.

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Cabitza, Federico, and Carlo Batini. "Information Quality in Healthcare." In Data-Centric Systems and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24106-7_13.

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Martin, Niels. "Data Quality in Process Mining." In Interactive Process Mining in Healthcare. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53993-1_5.

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McCann, Lloyd, and John Robson. "Data in Healthcare and Quality Improvement." In Textbook of Medical Administration and Leadership. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5211-3_6.

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Macias, Charles G., and Kathleen E. Carberry. "Data Analytics for the Improvement of Healthcare Quality." In Medical Quality Management. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48080-6_6.

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Schroeder, Lisa L. "Using Data to Drive Change." In Patient Safety and Quality Improvement in Healthcare. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55829-1_8.

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Schulz, Stefan, Robert Stegwee, and Catherine Chronaki. "Standards in Healthcare Data." In Fundamentals of Clinical Data Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99713-1_3.

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AbstractClinical data interoperability requires shared specifications of meaning. This is the rationale for clinical data standards. Up until now, the adoption of such standards has been varied, although they are increasingly advocated in an area where proprietary specifications prevail, and semantic resources are geared to specific purposes and limited by boundaries of languages and jurisdictions. This chapter highlights the need of data standards in the context of the difficult and heterogeneous field of clinical data and the way how they are addressed by terminologies, ontologies and inform
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Berlage, Thomas, Carsten Claussen, Sandra Geisler, Carlos A. Velasco, and Stefan Decker. "Medical Data Spaces in Healthcare Data Ecosystems." In Designing Data Spaces. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93975-5_18.

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AbstractExchange of sensitive medical data between healthcare providers and researchers requires a particularly high level of trust and security. Involving patients and citizen into this process increases transparency and may improve the outcome of preventive, diagnostic, and therapeutic measures. We propose to build the structure of a healthcare ecosystem on the basis of “apps” that not only hold (and exchange) health data but support user interaction and healthcare process management. Emphasis on process support may also be used to improve data quality, which is an important prerequisite for
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Dungey, Sheena, Natalia Beloff, Rachael Williams, Tim Williams, Shivani Puri, and A. Rosemary Tate. "Characterisation of Data Quality in Electronic Healthcare Records." In Health Monitoring and Personalized Feedback using Multimedia Data. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17963-6_7.

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Monsen, Karen A. "Exploratory Data Analysis." In Intervention Effectiveness Research: Quality Improvement and Program Evaluation in Healthcare. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-54111-7_8.

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Conference papers on the topic "Healthcare Data Quality"

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Marteau, Benoit L., Andrew Hornback, Yishan Zhong, et al. "Improving A Large Healthcare System Research Data Warehouse Using OHDSI's Data Quality Dashboard." In 2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 2024. https://doi.org/10.1109/bhi62660.2024.10913573.

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Joshi, Kireet, Jianming Yong, Xiaohui Tao, and Yahua Zhang. "Big Data in Healthcare has Improved the Care Quality! A Reality or Myth?" In 2024 Twelfth International Conference on Advanced Cloud and Big Data (CBD). IEEE, 2024. https://doi.org/10.1109/cbd65573.2024.00066.

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Akther, Sayma. "Visualization Driven AI Ensuring Quality in Wearable Time-Series Sensor Data for Healthcare." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00295.

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Domova, Veronika, and Shiva Sander-Tavallaey. "Visualization for Quality Healthcare: Patient Flow Exploration." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006351.

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Hickey, David, Rita Connor, Pauline McCormack, Peter Kearney, Roosa Rosti, and Rob Brennan. "The Data Quality Index: Improving Data Quality in Irish Healthcare Records." In 23rd International Conference on Enterprise Information Systems. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010441906250636.

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Huser, Vojtech, Michael G. Kahn, Jeffrey S. Brown, and Ramkiran Gouripeddi. "Methods for examining data quality in healthcare integrated data repositories." In Pacific Symposium on Biocomputing 2018. WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813235533_0059.

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Dantanarayana, GGT, Tony Sahama, and GN Wikramanayake. "Quality of information for quality of life: Healthcare big data analytics." In 2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer). IEEE, 2015. http://dx.doi.org/10.1109/icter.2015.7377714.

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Kumar, Vivek, Simone Balloccu, Zixiu Wu, et al. "Data Augmentation for Reliability and Fairness in Counselling Quality Classification." In Scarce Data in Artificial Intelligence for Healthcare. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011531400003523.

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Fox, Frank, Vishal R. Aggarwal, Helen Whelton, and Owen Johnson. "A Data Quality Framework for Process Mining of Electronic Health Record Data." In 2018 IEEE International Conference on Healthcare Informatics (ICHI). IEEE, 2018. http://dx.doi.org/10.1109/ichi.2018.00009.

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Jea, David, Rahul Balani, Ju-Lan Hsu, Dae-Ki Cho, Mario Gerla, and Mani B. Srivastava. "Diagnostic quality driven physiological data collection for personal healthcare." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4649798.

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Reports on the topic "Healthcare Data Quality"

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Shey Wiysonge, Charles. Does public disclosure of performance data improve quality of healthcare? SUPPORT, 2016. http://dx.doi.org/10.30846/1608082.

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Information about the performance of health plans (health insurance or subscription-based medical care), hospitals, and healthcare professionals is increasingly available in the public domain. However, the effects of such public disclosure of performance data are unclear.
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Bossuroy, Thomas, Clara Delavallade, and Vincent Pons. Biometric Tracking, Healthcare Provision, and Data Quality: Experimental Evidence from Tuberculosis Control. National Bureau of Economic Research, 2019. http://dx.doi.org/10.3386/w26388.

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Smeaton, John, and Lorna Christie. AI and healthcare. Parliamentary Office of Science and Technology, 2021. http://dx.doi.org/10.58248/pn637.

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There are various applications of Artificial Intelligence (AI) in healthcare, such as helping clinicians to make decisions, monitoring patient health, and automating routine administrative tasks. This POSTnote gives an overview of these uses, and their potential impacts on the cost and quality of healthcare, and on the workforce. It summarises the challenges to wider adoption of AI in healthcare, including those relating to safety, privacy, data-sharing, trust, accountability and health inequalities. It also outlines some of the regulations relevant to AI, and how these may change. As healthca
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Holmer, Haley K., Suchitra Iyer, Celia Fiordalisi, et al. Supplementing Systematic Review Findings With Healthcare System Data: Pilot Projects From the Agency for Healthcare Research and Quality Evidence-based Practice Center Program. Agency for Healthcare Research and Quality (AHRQ), 2025. https://doi.org/10.23970/ahrqepcwhitepapersupplementing.

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Objectives. The Agency for Healthcare Research and Quality (AHRQ), through the Evidence-based Practice Center (EPC) Program, aims to provide health system decision makers with the highest-quality evidence to inform clinical decisions. However, limitations in the literature may lead to inconclusive findings in EPC systematic reviews (SRs). The EPC Program conducted pilot projects to understand the feasibility, benefits, and challenges of utilizing health system data to augment SR findings to support confidence in healthcare decision making based on real-world experiences. Study Design and Setti
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Hoy, Aislinn, Frank Moriarty, and Anne Nolan. The healthcare costs of poor air quality in Ireland: A review of potential data sources and methods. ESRI, 2025. https://doi.org/10.26504/sustat130.

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Air pollution is a major risk factor for disease and premature mortality worldwide. In Ireland, fine particulate matter (PM2.5), which originates largely from burning solid fuel for heating, and nitrogen dioxide (NO2), derived from road transport, in particular from diesel engines, are the main contributing sources of poor air quality. In addition to the mortality and morbidity burden, air pollution also imposes a significant economic burden, in terms of healthcare costs, lost productivity, impact on agricultural crops and damage to buildings and infrastructure. In this report, we scope out th
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Hartley, David M., Hanieh Razzaghi, Charles Bailey, et al. How Accurate Are PCORnet® Data for Measures of Children's Healthcare Quality? — A PCORnet® Study. Patient-Centered Outcomes Research Institute (PCORI), 2021. http://dx.doi.org/10.25302/09.2021.hsd.160435160.

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Echevin, Damien, Bernard Fortin, and Aristide Houndetoungan. Healthcare Quality by Specialists under a Mixed Compensation System: an Empirical Analysis. CIRANO, 2023. http://dx.doi.org/10.54932/cttw3290.

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We analyze the effects of a mixed compensation (MC) scheme for specialists on the quality of their healthcare services. To do so, we exploit a major reform that was implemented in Quebec (Canada) in 1999. The government introduced a payment mechanism combining a fixed per diem with a reduced fee per clinical service. Using panel patient-doctor data covering the period 1996-2016 and including 320,441 patients, we estimate a multi-state multi-spell hazard model with correlated heterogeneity, analogous to a difference-in-differences approach. We compute three output-based quality indicators from
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Tipton, Kelley, Brian F. Leas, Emilia Flores, et al. Impact of Healthcare Algorithms on Racial and Ethnic Disparities in Health and Healthcare. Agency for Healthcare Research and Quality (AHRQ), 2023. http://dx.doi.org/10.23970/ahrqepccer268.

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Objectives. To examine the evidence on whether and how healthcare algorithms (including algorithm-informed decision tools) exacerbate, perpetuate, or reduce racial and ethnic disparities in access to healthcare, quality of care, and health outcomes, and examine strategies that mitigate racial and ethnic bias in the development and use of algorithms. Data sources. We searched published and grey literature for relevant studies published between January 2011 and February 2023. Based on expert guidance, we determined that earlier articles are unlikely to reflect current algorithms. We also hand-se
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McDonagh, Marian S., Roger Chou, Jesse Wagner, et al. Living Systematic Reviews: Practical Considerations for the Agency for Healthcare Research and Quality Evidence-based Practice Center Program. Agency for Healthcare Research and Quality (AHRQ), 2022. http://dx.doi.org/10.23970/ahrqepcwhitepaperlsr.

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Living systematic reviews are a relatively new approach to keeping the evidence in systematic reviews current by frequent surveillance and updating. The Agency for Healthcare Research and Quality’s Evidence-based Practice Center Program recently commissioned a systematic review of plant-based treatments for chronic pain management. This white paper describes the team’s experience in implementing the protocol that was developed a priori, and reflects on the challenges faced and lessons learned in the process of developing and maintaining a living systematic review. Challenges related to scoping
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Savedoff, William D., Laura Goyeneche, Luis Alberto Soler, et al. Disruption and Rebound: Healthcare and Telemedicine in Colombia during the COVID-19 Pandemic for Chronic Care Patients. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004865.

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The COVID-19 pandemic led to declines in in-person consultations and substantial increases in telemedicine use in many countries. This paper investigates whether this pattern occurred in Colombia using data for people with particular health conditions prior to the pandemic (rheumatoid arthritis, hemophilia, chronic kidney disease, HIV, and cancer). The study shows that healthcare utilization by people in Colombia with these conditions dropped significantly during the first months of the pandemic relative to the average of the previous two years. However, by the end of 2020, the rate of healthc
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