The Use of Databases and Registries to Enhance Colonoscopy Quality

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The use of large databases to enhance quality: The National Healthcare Quality Report example

Large databases result from data collected for administrative purposes, from surveys performed for developing national agendas and other reasons, or from disease or procedure-specific registries. The authors are familiar with the use of these large databases for epidemiologic studies,5 including studies of the burden of gastrointestinal disease.6, 7, 8, 9 The National Healthcare Quality Reports (NHQR) are an example of use of these sources for discovery of quality and of the trends in quality

Challenges in the use of administrative data

The credibility of administrative data, which is usually insurance claims data, for quality reporting and research has long been the subject of debate.13, 14, 15, 16 The term powerful is often used to describe the role of administrative data in studying population-based patterns of health, disease, and medical care.13 This powerful data has potential advantages for research and quality, including the ability to measure large samples of geographically dispersed patients, the ability to assemble

Using administrative data for measurement of individual physician quality of care: the Centers for Medicare and Medicaid Services example

In 2007, the Centers for Medicare and Medicaid Services (CMS) initiated the Physician Quality Reporting Initiative (PQRI).25 In this program, quality measures are suggested by measure development organizations, such as the National Quality Forum or the American Medical Association Physician Consortium for Performance Improvement,26 and adopted for implementation using specialized billing codes, registries, or electronic health record reporting. Of 179 measures in the 2010 PQRI measures set,

Completeness and accuracy of data in clinical registries

Data derived from disease registries or health surveys avoid many of the biases noted with administrative data. Quality of data, however, remains an issue, although the expectations for these data sources are high. Arts and colleagues31 described a framework of procedures for assuring data quality in medical registries (Table 1) that takes into account the 2 methods of data collection, automated extraction from electronic records, and manual abstraction of data from paper or electronic records.

Using electronic health record databases to enhance quality

With the increasing emphasis on documentation of all clinical activities using electronic health records, the question arises whether or not EHRs can be a source for enhancing quality in an automated fashion, without requiring manual review of clinical records. Even where electronic documentation of clinical episodes is the rule, most notes are dictated narrative with few external standards for content, the exceptions being laboratory results, and medication and problem lists when these are

Electronic reporting software for gastrointestinal endoscopy: the Clinical Outcomes Research Initiative experience

The Clinical Outcomes Research Initiative (CORI) experience is an example of how endoscopic reporting software may be used to measure and enhance quality. The CORI reporting software was developed to support outcomes research and is currently used by a national consortium of endoscopists to document endoscopic procedures. Data from each procedure is automatically exported to the National Endoscopic Database after removal of individual identifiers. The CORI reporting software captures the

When Data is Unstructured: Natural Language Processing

Most clinical documentation is at the other end of the documentation spectrum from the CORI model, that is, captured in narrative text. Algorithms for processing this text, resulting in identification of clinical concepts that can then be used for quality measurement and research, are an active area of research. Domains that have been studied include radiology,53 vaccine adverse events,54 and pathology reports.55 Prominent recognition problems, for example, are the negation of concepts (history

Summary

Administrative databases, registries, and clinical databases are designed for different purposes and therefore have different advantages and disadvantages in providing data for enhancing quality. Administrative databases provide the advantages of size, availability, and generalizability, but are subject to constraints inherent in the coding systems used and from data-collection methods optimized for billing. Registries are designed for research and quality reporting, but require significant

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