Ali Syed Mustafa, Anjum Naveed, Kamel Boulos Maged N, Ishaq Muhammad, Aamir Javariya, Haider Ghulam Rasool
Monitoring, Evaluation and Learning Unit, Mercy Corps, Pak Palace, Rawal Chowk, Murree Road, Islamabad, Pakistan.
Alexander Graham Bell Center for Digital Health, University of Highlands and Islands, Inverness, Scotland, UK.
BMC Res Notes. 2018 Jan 16;11(1):40. doi: 10.1186/s13104-018-3161-8.
Data quality is core theme of programme's performance assessment and many organizations do not have any data quality improvement strategy, wherein data quality dimensions and data quality assessment framework are important constituents. As there is limited published research about the data quality specifics that are relevant to the context of Pakistan's Tuberculosis control programme, this study aims at identifying the applicable data quality dimensions by using the 'fitness-for-purpose' perspective.
Forty-two respondents pooled a total of 473 years of professional experience, out of which 223 years (47%) were in TB control related programmes. Based on the responses against 11 practical cases, adopted from the routine recording and reporting system of Pakistan's TB control programme (real identities of patient were masked), completeness, accuracy, consistency, vagueness, uniqueness and timeliness are the applicable data quality dimensions relevant to the programme's context, i.e. work settings and field of practice.
Based on a 'fitness-for-purpose' approach to data quality, this study used a test-based approach to measure management's perspective and identified data quality dimensions pertinent to the programme and country specific requirements. Implementation of a data quality improvement strategy and achieving enhanced data quality would greatly help organizations in promoting data use for informed decision making.
数据质量是项目绩效评估的核心主题，许多组织没有任何数据质量改进策略，其中数据质量维度和数据质量评估框架是重要组成部分。由于与巴基斯坦结核病控制项目背景相关的数据质量具体情况的已发表研究有限，本研究旨在从“适用性”角度确定适用的数据质量维度。
42名受访者累计拥有473年的专业经验，其中223年（47%）与结核病控制相关项目有关。根据从巴基斯坦结核病控制项目的常规记录和报告系统采用的11个实际案例（患者真实身份已屏蔽）的回复，完整性、准确性、一致性、模糊性、唯一性和及时性是与该项目背景（即工作环境和实践领域）相关的适用数据质量维度。
基于数据质量的“适用性”方法，本研究采用基于测试的方法来衡量管理层的观点，并确定了与该项目和国家特定要求相关的数据质量维度。实施数据质量改进策略并提高数据质量将极大地帮助组织促进数据用于明智决策。
