Appl Clin Inform 2013; 04(01): 1-11
DOI: 10.4338/ACI-2012-10-CR-0041
Case Report
Schattauer GmbH

Developing a Tool to Assess the Quality of Socio-Demographic Data in Community Health Centres

M. Laberge
1   Institute of Health Policy, Management and Evaluation, University of Toronto
,
A. Shachak
1   Institute of Health Policy, Management and Evaluation, University of Toronto
2   Faculty of Information, University of Toronto
› Institutsangaben
Weitere Informationen

Correspondence to:

Maude Laberge
Institute of Health Policy, Management and Evaluation
Faculty of Medicine, University of Toronto
Health Sciences Building, Suite 425
155 College Street
Toronto, ON M5T 3M7

Publikationsverlauf

received: 01. Oktober 2012

accepted: 06. Januar 2012

Publikationsdatum:
19. Dezember 2017 (online)

 

Summary

Objective: The objectives of this study are to 1) create a quality assessment tool for socio-demographic data aligned with the needs of Community Health Centres (CHCs) and based on the data quality framework of the Canadian Institute for Health Information (CIHI), and 2) test the feasibility of the tool in CHCs.

Methods: The tool was developed based on both theoretical and practical knowledge. A review of the literature was performed to identify data quality frameworks and dimensions that could be employed. In addition, informal discussions with Community Health Centres staff members holding various positions were conducted and a team of subject matter experts was established. This approach supported the alignment between the tool (i.e., the indicators developed, the rating scale, and weighting system) and the setting for which it has been designed. The tool was pilot tested in five CHCs across Ontario.

Results: The decision to focus on socio-demographic data was based on findings from the discussions with staff members. The team established nine principles for the development of the tool, including the use of computer software, whenever possible, to query the data and ensure consistency of the measurement. Data quality scores ranged from 45 to 74 on a scale of 0 (lowest quality) to 100 (highest data quality), with one CHC that was not able to run all of the queries. The feedback from staff was positive and supports the feasibility of the tool as an application of the CIHI data quality framework in a local setting.

Conclusion: Pilot test results demonstrate the feasibility of the tool and an applicability of the CIHI framework as a basis for developing tools for data quality assessment in health care organizations.

Citation: Laberge M, Shachak A. Developing a tool to assess the quality of socio-demographic data in community health centres. Appl Clin Inf 2012; 4:1–11

http://dx.doi.org/10.4338/ACI-2012-10-CR-0041


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Conflict of Interest

The authors declare that they have no conflict of interest in the research.

  • References

  • 1 Dick RS, Steen EB. The computer-based patient record: An essential technology for healthcare. Revised Edition, National Academy Press; Washington, DC: 1997
  • 2 Hersh WR. Information retrieval: A health care perspective. Springer; New York: 1996
  • 3 Adams WG, Mann AM, Bauchner H. Use of electronic medical record improves the quality of urban pediatric primary care. Pediatrics 2003; 111: 626-632.
  • 4 Chaudhry B. et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine 2006; 144: 742-752.
  • 5 Blumenthal D. Stimulating the adoption of health information technology. N Engl J Med 2009; 360: 1477-1479.
  • 6 Hogan WR, Wagner MM. Accuracy of data in computer based patient records. J Am Med Inform Assoc 1997; 4: 342-355.
  • 7 Arts DGT, De Keizer NF, Sheffer GJ. Defining and improving data quality in medical registries: A literature review, case study, and generic framework. J Am Med Inform Assoc 2002; 9: 600-611.
  • 8 De Araujp Lima CR. et al. Saúde Pública. Review of data quality dimensions and applied methods in the evaluation of health information systems [Revisão das dimensões de qualidade dos dados e métodos aplicados na avaliação dos sistemas de informação em saúde]. Rio de Janeiro 2009; 25: 2095-2109.
  • 9 Carson CS. Toward a framework for assessing data quality. IMF Working Paper; 2001. 01/25.
  • 10 Strong DM, Lee YW, Wang RY. Data quality in context, communication of the ACM. 1997 40: 5.
  • 11 Wang YW, Strong DM. Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems 1996; 12: 4.
  • 12 Gimbel S. et al. An assessment of routine primary care health information system data quality in Sofala Province, Mozambique. Population Health metrics 2011; 9: 12.
  • 13 Nielsen GL. et al. Analyses of data quality in registries concerning diabetes mellitus –a comparison between a population based hospital discharge and an insulin prescription registry. Journal of Medical Systems 1996; 20.
  • 14 Scobie S, Basnett I, McCartney P. Can general practice data be used for needs assessment and health care planning in an inner-London district?. Journal of Public Health Medicine 1995; 17: 475-483.
  • 15 Armenti KR. et al. Improving the quality of industry and occupation data at a central cancer registry. American Journal of Industrial Medicine 2010; 53: 995-1001.
  • 16 Canadian Institute for Health Information.. The CIHI data quality assessment framework. 2005
  • 17 Kerr AK, Norris T, Stockdale R. The strategic management of data quality in healthcare. Health Informatics Journal 2008; 14: 259-266.
  • 18 Ontario Ministry of Health and Long Term Care. http://www.health.gov.on.ca/english/public/contact/chc/chc_mn.html consulted August 22nd, 2011
  • 19 Thiru K, Hassey A, Sullivan F. Systematic review of scope and quality of electronic patient record data in primary care. BMJ 2003; 326: 1070.
  • 20 Schneider EC. et al. Enhancing performance measurement NCQA’s road map for a health information framework. JAMA 1999; 282: 1184-1190.
  • 21 Hammond WE. et al. Connecting information to improve health. Health Affairs 2010; 2: 284-288.
  • 22 Pringle M, Ward P, Chilvers C. Assessment of the completeness and accuracy of computer medical records in four practices committed to recording data on computer. British Journal of General Practice 1995; 45: 537-541.
  • 23 Nahm ML, Pieper CF, Cunningham MM. Quantifying data quality for clinical trials using electronic data capture. PLoS ONE 2008; 3: e3049.

Correspondence to:

Maude Laberge
Institute of Health Policy, Management and Evaluation
Faculty of Medicine, University of Toronto
Health Sciences Building, Suite 425
155 College Street
Toronto, ON M5T 3M7

  • References

  • 1 Dick RS, Steen EB. The computer-based patient record: An essential technology for healthcare. Revised Edition, National Academy Press; Washington, DC: 1997
  • 2 Hersh WR. Information retrieval: A health care perspective. Springer; New York: 1996
  • 3 Adams WG, Mann AM, Bauchner H. Use of electronic medical record improves the quality of urban pediatric primary care. Pediatrics 2003; 111: 626-632.
  • 4 Chaudhry B. et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine 2006; 144: 742-752.
  • 5 Blumenthal D. Stimulating the adoption of health information technology. N Engl J Med 2009; 360: 1477-1479.
  • 6 Hogan WR, Wagner MM. Accuracy of data in computer based patient records. J Am Med Inform Assoc 1997; 4: 342-355.
  • 7 Arts DGT, De Keizer NF, Sheffer GJ. Defining and improving data quality in medical registries: A literature review, case study, and generic framework. J Am Med Inform Assoc 2002; 9: 600-611.
  • 8 De Araujp Lima CR. et al. Saúde Pública. Review of data quality dimensions and applied methods in the evaluation of health information systems [Revisão das dimensões de qualidade dos dados e métodos aplicados na avaliação dos sistemas de informação em saúde]. Rio de Janeiro 2009; 25: 2095-2109.
  • 9 Carson CS. Toward a framework for assessing data quality. IMF Working Paper; 2001. 01/25.
  • 10 Strong DM, Lee YW, Wang RY. Data quality in context, communication of the ACM. 1997 40: 5.
  • 11 Wang YW, Strong DM. Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems 1996; 12: 4.
  • 12 Gimbel S. et al. An assessment of routine primary care health information system data quality in Sofala Province, Mozambique. Population Health metrics 2011; 9: 12.
  • 13 Nielsen GL. et al. Analyses of data quality in registries concerning diabetes mellitus –a comparison between a population based hospital discharge and an insulin prescription registry. Journal of Medical Systems 1996; 20.
  • 14 Scobie S, Basnett I, McCartney P. Can general practice data be used for needs assessment and health care planning in an inner-London district?. Journal of Public Health Medicine 1995; 17: 475-483.
  • 15 Armenti KR. et al. Improving the quality of industry and occupation data at a central cancer registry. American Journal of Industrial Medicine 2010; 53: 995-1001.
  • 16 Canadian Institute for Health Information.. The CIHI data quality assessment framework. 2005
  • 17 Kerr AK, Norris T, Stockdale R. The strategic management of data quality in healthcare. Health Informatics Journal 2008; 14: 259-266.
  • 18 Ontario Ministry of Health and Long Term Care. http://www.health.gov.on.ca/english/public/contact/chc/chc_mn.html consulted August 22nd, 2011
  • 19 Thiru K, Hassey A, Sullivan F. Systematic review of scope and quality of electronic patient record data in primary care. BMJ 2003; 326: 1070.
  • 20 Schneider EC. et al. Enhancing performance measurement NCQA’s road map for a health information framework. JAMA 1999; 282: 1184-1190.
  • 21 Hammond WE. et al. Connecting information to improve health. Health Affairs 2010; 2: 284-288.
  • 22 Pringle M, Ward P, Chilvers C. Assessment of the completeness and accuracy of computer medical records in four practices committed to recording data on computer. British Journal of General Practice 1995; 45: 537-541.
  • 23 Nahm ML, Pieper CF, Cunningham MM. Quantifying data quality for clinical trials using electronic data capture. PLoS ONE 2008; 3: e3049.