Structuring and coding in health care records: a qualitative analysis using diabetes as a case study

Ann R R Robertson, Bernard Fernando, Zoe Morrison, Dipak Kalra, Aziz Sheikh

Abstract


Background   Globally, diabetes mellitus presents a substantial burden to individuals and healthcare systems. Structuring and/or coding of medical records underpin attempts to improve information sharing and searching, potentially bringing clinical and secondary uses benefits.

Aims and objectives   We investigated if, how and why records for adults with diabetes were structured and/or coded, and explored stakeholders’ perceptions of current practice.

Methods   We carried out a qualitative, theoretically-informed case study of documenting healthcare information for diabetes patients in family practice and hospital settings, using semi-structured interviews, observations, systems demonstrations and documentary data.

Results   We conducted 22 interviews and four on-site observations, and reviewed 25 documents. For secondary uses – research, audit, public health and service planning – the benefits of highly structured and coded diabetes data were clearly articulated. Reported clinical benefits in terms of managing and monitoring diabetes, and perhaps encouraging patient self-management, were modest. We observed marked differences in levels of record structuring and/or coding between settings, and found little evidence that these data were being exploited to improve information sharing between them.

Conclusions   Using high levels of data structuring and coding in medical records for diabetes patients has potential to be exploited more fully, and lessons might be learned from successful developments elsewhere in the UK.


Keywords


diabetes mellitus; medical records; clinical coding; qualitative research

Full Text:

PDF HTML

References


The Lancet editorial. The diabetes pandemic. The Lancet 2011 (July);378:99.

Royal College of General Practitioners & NHS Diabetes. Coding, classification and diagnosis of diabetes report. 2011 (March). Available at: http://www.sccgformulary.co.uk/Coding%20Classification%20and%20Diagnosis%20of%20Diabetes%20Report.pdf.

Department of Health. Six years on: delivering the Diabetes National Service Framework. 2010(Feb). Available at: http://webarchive.nationalarchives.gov.uk/20130107105354/http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/@ps/documents/digitalasset/dh_112511.pdf.

Department of Health. Management of adult diabetes services in the NHS 2012 (May). Available at: http://www.nao.org.uk/wp-content/uploads/2012/05/121321.pdf.

Department of Health. Your health, your way – your NHS guide to long-term conditions and self care. Available at: http://www.nhs.uk/Planners/Yourhealth/Pages/Yourhealth.aspx. [last accessed 03/03/2014].

Department of Health. Health and Social Care Bill. 2011. Available at: http://www.publications.parliament.uk/pa/cm201011/cmbills/132/11132.pdf.

Morrison Z, Fernando B, Kalra D, Cresswell K and Sheikh A. National evaluation of the benefits and risks of greater structuring and coding of the electronic health record: exploratory qualitative study. JAMIA. doi:10.1136/amiajnl- 2013-001666. Available at: http://jamia.bmj.com/content/early/2013/11/01/amiajnl-2013-001666.full..

Morrison Z, Fernando B, Kalra D, Cresswell K, Robertson A and Sheikh A. The collection and utilisation of patient ethnicity data in general practices and hospitals in the United Kingdom: a qualitative case study. Informatics in Primary Care 2014;21(3):118–31. PMid:25207615.

Stake RE. Case studies. Denzin NK and Lincoln YS. (Eds). Handbook of Qualitative Research. London: Sage Publications, 1994, pp. 236–47.

UK Clinical Research Network. Information available at: http://www.ukcrc.org/research-infrastructure/clinical-researchnetworks/uk-clinical-research-network-ukcrn. [last accessed 09/11/2013].

Patton MQ. Qualitative Evaluation and Research Methods, 2nd edition. London: Sage Publications, 1990.

Braun V and Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology 2006;3(2):77–101. Available at: http://dx.doi.org/10.1191/1478088706qp063oa..

12NVivo8. QSR International. Information available at: http://www.qsrinternational.com/products_previous-products_nvivo8.aspx. [last accessed 09/12/2013].

Corbin J and Strauss A (Eds.). Strategies for qualitative data analysis. Basics of Qualitative Research. Techniques and Procedures for Developing Grounded Theory, 3rd edition. London: Sage Publications, 2008.

Coiera E. Four rules for the reinvention of health care. British Medical Journal 2004;328:1197–9. Available at: http://dx.doi.org/10.1136/bmj.328.7449.1197. PMid:15142933; PMCid:PMC411109.

Silverman D. Doing Qualitative Research: A Practical Handbook, 1st edition. London: Sage Publications, 2000.

The Scottish Care Information – Diabetes Collaboration (SCI-DC). Information available at: http://www.sci-diabetes.scot.nhs.uk [last accessed 09/12/2013].

Farmer A and Fox R. Diagnosis, classification and treatment of diabetes. British Medical Journal 2011;342. Available at: http://dx.doi.org/10.1136/bmj.d3319.

Stone MA, Camosso-Stenfinovic J, Wilkinson J, de Lusignan S, Hattersley AT and Khunti K. Incorrect and incomplete coding and classification of diabetes: a systematic review. Diabetic Medicine 2010;27(5):491–7. Available at: http://dx.doi.org/10.1111/j.1464-5491.2009.02920.x. PMid:20536944.

Manuel DG, Rosella LC and Stukel TA. Importance of accurately identifying chronic disease in studies using electronic health records. British Medical Journal 2010;341:c4226. Available at: http://dx.doi.org/10.1136/bmj.c4226. PMid:20724404.

Gray J, Orr D and Majeed A. Use of read codes in diabetes management in a South London primary care group: implications for establishing disease registers. British Medical Journal 2003;326:1130. Available at: http://dx.doi.org/10.1136/bmj.326.7399.1130. PMid:12763987; PMCid:PMC156011.

de Lusignan S, Sadek N, Mulnier H, Tahir A, Russell-Jones D and Khunti K. Miscoding, misclassification and misdiagnosis of diabetes in primary care. Diabetic Medicine 2011 (Aug) 26. Available at: http://dx.doi.org/10.1111/j.1464-5491.2011.03419.x.

de Lusignan S, Khunti K, Belsey J, Hattersley A, van Vlymen J and Gallagher H. A method of identifying and correcting miscoding, misclassification and misdiagnosis in diabetes: a pilot and validation study of routinely collected data. Diabetic Medicine 2010 (Feb);27(2):203–9. Available at: http://dx.doi.org/10.1111/j.1464-5491.2009.02917.x. PMid:20546265.

Cebul RD, Love TE, Jain AK and Hebert CJ. Electronic health records and quality of diabetes care. The New England Journal of Medicine 2011;365(9):825–33. Available at: http://dx.doi.org/10.1056/NEJMsa1102519. PMid:21879900.

Kupersmith J, Francis J, Kerr E, Krein S, Pogach L, Kolodner et al. Advancing evidence-based care for diabetes: lessons from the Veterans Health Administration. Health Affairs 2007; http://dx.doi.org/10.1377/hlthaff.26.2w156.




DOI: http://dx.doi.org/10.14236/jhi.v22i2.90

Refbacks

  • There are currently no refbacks.


This is an open access journal, which means that all content is freely available without charge to the user or their institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal starting from Volume 21 without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open accessFor permission regarding papers published in previous volumes, please contact us.

Privacy statement: The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Online ISSN 2058-4563 - Print ISSN 2058-4555. Published by BCS, The Chartered Institute for IT