Constance K. Haan M.D. (Senior Medical Director of System Outcomes and Effectiveness), Mark Adams B.S.H. (Cardiology Data Manager), Ray Cook R.N. (Cardiac Surgery Data Manager)
{"title":"Improving the Quality of Data in Your Database: Lessons from a Cardiovascular Center","authors":"Constance K. Haan M.D. (Senior Medical Director of System Outcomes and Effectiveness), Mark Adams B.S.H. (Cardiology Data Manager), Ray Cook R.N. (Cardiac Surgery Data Manager)","doi":"10.1016/S1549-3741(04)30081-X","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Creating and having a database should not be an end goal but rather a source of valid data and a means for generating information by which to assess process, performance, and outcome quality. The Cardiovascular Center at Shands Jacksonville (Florida) made measurable improvements in the quality of data in national registries and internally available software tools for collection of patient care data.</p></div><div><h3>Methods</h3><p>The process of data flow was mapped from source to report submission to identify input timing and process gaps, data sources, and responsible individuals. Cycles of change in data collection and entry were developed and the improvements were tracked.</p></div><div><h3>Results</h3><p>Data accuracy was improved by involving all caregivers in datasheet completion and assisting them with data-field definitions. Using hospital electronic databases decreased the need for manual retrospective review of medical records for datasheet completion. The number of fields with missing values decreased by 83.6%, and the number of missing values decreased from 31.2% to 1.9%. Data accuracy rose dramatically by real-time data entry at point of care.</p></div><div><h3>Discussion</h3><p>Key components to ensuring data quality for process and outcome improvement are (1) education of the caregiver team, (2) process supervision by a database manager, (3) commitment and explicit support from leadership,(4) increased and improved use of electronic data sources, and (5) data entry at point of care.</p></div>","PeriodicalId":84970,"journal":{"name":"Joint Commission journal on quality and safety","volume":"30 12","pages":"Pages 681-688"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1549-3741(04)30081-X","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Joint Commission journal on quality and safety","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S154937410430081X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Background
Creating and having a database should not be an end goal but rather a source of valid data and a means for generating information by which to assess process, performance, and outcome quality. The Cardiovascular Center at Shands Jacksonville (Florida) made measurable improvements in the quality of data in national registries and internally available software tools for collection of patient care data.
Methods
The process of data flow was mapped from source to report submission to identify input timing and process gaps, data sources, and responsible individuals. Cycles of change in data collection and entry were developed and the improvements were tracked.
Results
Data accuracy was improved by involving all caregivers in datasheet completion and assisting them with data-field definitions. Using hospital electronic databases decreased the need for manual retrospective review of medical records for datasheet completion. The number of fields with missing values decreased by 83.6%, and the number of missing values decreased from 31.2% to 1.9%. Data accuracy rose dramatically by real-time data entry at point of care.
Discussion
Key components to ensuring data quality for process and outcome improvement are (1) education of the caregiver team, (2) process supervision by a database manager, (3) commitment and explicit support from leadership,(4) increased and improved use of electronic data sources, and (5) data entry at point of care.