Results 291 to 300 of about 11,695,622 (343)
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Nursing Management, 2010
The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
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The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
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2000
Several different kinds of problems arise when parish records are used. First, the data include only the Christian population, and the population development of the Christians might be quite different from the other part of the society. During the 1930s the proportion of the Christian population of the whole population was already about 40 per cent in ...
Harri Siiskonen, Veijo Notkola
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Several different kinds of problems arise when parish records are used. First, the data include only the Christian population, and the population development of the Christians might be quite different from the other part of the society. During the 1930s the proportion of the Christian population of the whole population was already about 40 per cent in ...
Harri Siiskonen, Veijo Notkola
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Dynamic data maintenance for quality data, quality research
International Journal of Information Management, 2012Abstract Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generate ideas and clear-cut solutions to be implemented by transportation professionals and ...
Dilruba Ozmen-Ertekin, Kaan Ozbay
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Communications of the ACM, 2002 How good is a company's data quality? Answering this question requires usable data quality metrics. Currently, most data quality measures are developed on an ad hoc basis to solve specific problems [6, 8], and fundamental principles necessary for developing usable metrics in practice are lacking.
Leo L. Pipino +2 more
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2019
We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Oliveira, Alexandra +4 more
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We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Oliveira, Alexandra +4 more
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Structured data quality reports to improve EHR data quality
International Journal of Medical Informatics, 2015To examine whether a structured data quality report (SDQR) and feedback sessions with practice principals and managers improve the quality of routinely collected data in EHRs.The intervention was conducted in four general practices participating in the Fairfield neighborhood electronic Practice Based Research Network (ePBRN).
Jane Taggart, Siaw-Teng Liaw, Hairong Yu
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2009
Publisher Summary Data quality ensures the accuracy and timeliness of data and it is much easier to ensure data quality before data get into a database than after they are stored. To be useful, the data in a database must be accurate, timely, and available when needed.
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Publisher Summary Data quality ensures the accuracy and timeliness of data and it is much easier to ensure data quality before data get into a database than after they are stored. To be useful, the data in a database must be accurate, timely, and available when needed.
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2001
Publisher Summary This chapter focuses on the practical process of aligning business user data quality expectations that can be measured and then correlated to the identified business impacts. Various ways to help classify data quality expectations with ways to measure conformance to these expectations are elaborated in the chapter.
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Publisher Summary This chapter focuses on the practical process of aligning business user data quality expectations that can be measured and then correlated to the identified business impacts. Various ways to help classify data quality expectations with ways to measure conformance to these expectations are elaborated in the chapter.
openaire +2 more sources