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Methods Inf Med 2011; 50(01): 11-22
DOI: 10.3414/ME09-01-0021
Original Articles

Options for Diabetes Management in Sub-Saharan Africa with an Electronic Medical Record System

G. Kouematchoua Tchuitcheu
1   Department of Medical Informatics, University Medicine, Georg-August-University, Goettingen, Germany
,
O. Rienhoff
1   Department of Medical Informatics, University Medicine, Georg-August-University, Goettingen, Germany
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Summary

Background: An increase of diabetes prevalence of up to 80% is predicted in subSaharan Africa (SSA) by 2025 exceeding the worldwide 55%. Mortality rates of diabetes and HIV/AIDS are similar. Diabetes shares several common factors with HIV/AIDS and multidrug-resistant tuberculosis (MDR-TB). The latter two health problems have been efficiently managed by an open source electronic medical record system (EMRS) in Latin America. Therefore a similar solution for diabetes in SSA could be extremely helpful.

Objectives: The aim was to design and validate a conceptual model for an EMRS to improve diabetes management in SSA making use of the HIV and TB experience.

Methods: A review of the literature addressed diabetes care and management in SSA as well as existing examples of information and communication technology (ICT) use in SSA. Based on a need assessment conducted in SSA a conceptual model based on the traditionally structured healthcare system in SSA was mapped into a three-layer structure. Application modules were derived and a demonstrator programmed based on an open source EMRS. Then the approach was validated by SSA experts.

Results: A conceptual model could be specified and validated which enhances a problem-oriented approach to diabetes management processes. The prototyp EMRS demonstrates options for a patient portal and simulation tools for education of health professional and patients in SSA.

Conclusion: It is possible to find IT solutions for diabetes care in SSA which follow the same efficiency concepts as HIV or TB modules in Latin America. The local efficiency and sustainability of the solution will, however, depend on training and changes in work behavior.

Keywords

Diabetes - computerized medical record - disease management - developing region - Africa



Publication History

Received: 09 March 2009

Accepted: 04 October 2009

Article published online:
18 January 2018

Schattauer GmbH

 

  • References

  • 1 Levitt N. Diabetes in Africa: Epidemiology, management and healthcare challenges. Heart 2008; 94 (11) 1376-1382.
    CrossrefPubMedGoogle Scholar
  • 2 Kemple A, Hartwick N, Sitaker M, Harmon J, Clark K, Norman J. Exploring the feasibility of combining chronic disease patient registry data to monitor the status of diabetes care. Prev Chronic Dis 2008; 5 (04) 124-137.
    PubMedGoogle Scholar
  • 3 Beran D, Yudkin J. Diabetes care in sub-Saharan Africa. Lancet 2006; 368 9548 1689-1695.
    CrossrefPubMedGoogle Scholar
  • 4 Gimeno S, Ferreira S, Franco L, Hirai A, Matsumura L, Moisés R. Prevalence and 7-year incidence of type II diabetes mellitus in a Japanese-Brazilian population: an alarming public health problem. Diabetologia 2002; 45 (12) 1635-1638.
    CrossrefPubMedGoogle Scholar
  • 5 Venkat Narayan K, Gregg E, Fagot-Campagna A, Engelgau M, Vinicor F. Diabetes – a common, growing, serious, costly, and potentially preventable public health problem. Diabetes Res Clin Pract 2000; 50: 77-84.
    CrossrefPubMedGoogle Scholar
  • 6 Van Vugt M, Schellekens O, Reiss P, Hamers R, Rinke de Wit T. Diabetes and HIV/AIDS in sub Saharan Africa: the need for sustainable healthcare systems. Diabetes Voice 2007; 52 (03) 23-26.
    PubMedGoogle Scholar
  • 7 Sambo B. The diabetes strategy for the WHO African Region: a call to action. Diabetes Voice 2007; 52 (04) 35-37.
    PubMedGoogle Scholar
  • 8 Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004; 27 (05) 1047-1053.
    CrossrefPubMedGoogle Scholar
  • 9 Unwin N, Setel P, Rashid S, Mugusi F, Mbanya J, Kitange H. et al. Noncommunicable diseases in subSaharan Africa: where do they feature in the health research agenda?. Bull World Health Organ 2001; 79 (10) 947-53.
    PubMedGoogle Scholar
  • 10 Kirigia J, Sambo H, Sambo L, Barry S. Economic burden of diabetes mellitus in the WHO African region. BMC Int Health Hum Rights 2009; 9 (01) 6-18.
    CrossrefPubMedGoogle Scholar
  • 11 Njamnshi A, Bella Hiag A, Mbanya J. From research to policy: the development of a national diabetes programme in Cameroon. Diabetes Voice 2006; 51 (03) 18-21.
    PubMedGoogle Scholar
  • 12 Amos A, McCarty D, Zimmet P. The rising global burden of diabetes and its complications: estimates and projections to the year 2010. Diabet Med 1997; 14 (05) 7-84.
    CrossrefPubMedGoogle Scholar
  • 13 Kouematchoua G, Rienhoff O. Sustainable development of medical informatics in Africa: need for a health informatics curriculum. Health Informatics in Africa Conference (HELINA); Bamako 2007
    PubMedGoogle Scholar
  • 14 Haux R. Health information systems – past, present, future. Int J Med Inform 2006; 75 3–4 268-281.
    CrossrefPubMedGoogle Scholar
  • 15 Grant R, Meigs J. The use of computers in population-based diabetes management. JCOM 2002; 9 (07) 390-396.
    PubMedGoogle Scholar
  • 16 Sönksen P, Williams C. Information technology in diabetes care ‘Diabeta’: 23 years of development and use of a computer-based record for diabetes care. Int J Biomed Comput 1996; 42 1–2 67-77.
    CrossrefPubMedGoogle Scholar
  • 17 Ndira S, Rosenberger K, Wetter T. Assessment of data quality of and staff satisfaction with an electronic health record system in a developing country (Uganda): a qualitative and quantitative comparative study. Methods Inf Med 2008; 47 (06) 489-498.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 18 Fraser H, Blaya J, Choi S, Bonilla C, Jazayeri D. Evaluating the impact and costs of deploying an electronic medical record system to support TB treatment in Peru. AMIA Annu Symp Proc; 2006: 264-268.
    PubMedGoogle Scholar
  • 19 Tierney W, Rotich J, Hannan T, Siika A, Biondich P, Mamlin B. et al. The AMPATH medical record system: creating, implementing, and sustaining an electronic medical record system to support HIV/ AIDS care in western Kenya. Stud Health Technol Inform 2007; 129 Pt (01) 372-376.
    PubMedGoogle Scholar
  • 20 Fraser H, Allen C, Bailey C, Douglas G, Shin S, Blaya J. Information systems for patient follow-up and chronic management of HIV and tuberculosis: A life-saving technology in resource-poor areas. J Med Internet Res 2007; 9 (04) e29.
    CrossrefPubMedGoogle Scholar
  • 21 Allen C, Jazayeri D, Miranda J, Biondich P, Mamlin B, Wolf B. et al. Experience in implementing the OpenMRS medical record system to support HIV treatment in Rwanda. Stud Health Technol Inform 2007; 129 Pt (01) 382-386.
    PubMedGoogle Scholar
  • 22 Tierney W, Beck E, Gardner R, Musick B, Shields M, Shiyonga N. et al. Viewpoint: a pragmatic approach to constructing a minimum data set for care of patients with HIV in developing countries. J Am Med Inform Assoc 2006; 13 (03) 253-260.
    CrossrefPubMedGoogle Scholar
  • 23 Siika A, Rotich J, Simiyu C, Kigotho E, Smith F, Sidle J. et al. An electronic medical record system for ambulatory care of HIV-infected patients in Kenya. Int J Med Inform 2005; 74 (05) 345-55.
    CrossrefPubMedGoogle Scholar
  • 24 Boyatzis R. Transforming qualitative information: thematic analysis and code development. Thousand Oaks: Sage Pubns; 1998
    Google Scholar
  • 25 Wendt T, Haber A, Brigl B, Winter A. Modeling hospital information systems (part 2): using the 3LGM2 tool for modeling patient record management. Methods Inf Med 2004; 43 (03) 256-267.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 26 Winter A, Brigl B, Wendt T. Modeling hospital information systems (part 1): the revised three-layer graph-based meta model 3LGM2 . Methods Inf Med 2003; 42 (05) 544-551.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 27 Lehmann E, Deutsch T. Insulin dosage adjustment in diabetes. J Biomed Eng 1992; 14 (03) 243-249.
    CrossrefPubMedGoogle Scholar
  • 28 Lehmann E, Deutsch T. A physiological model of glucose-insulin interaction in type 1 diabetes mellitus. J Biomed Eng 1992; 14 (03) 235-42.
    CrossrefPubMedGoogle Scholar
  • 29 Berger M, Rodbard D. Computer simulation of plasma insulin and glucose dynamics after subcutaneous insulin injection. Diabetes Care 1989; 12 (10) 725-736.
    CrossrefPubMedGoogle Scholar
  • 30 Zai A, Grant R, Estey G, Lester W, Andrews C, Yee R. et al. Lessons from implementing a combined work-flow-informatics system for diabetes management. J Am Med Inform Assoc 2008; 15 (04) 524-533.
    CrossrefPubMedGoogle Scholar
  • 31 Wyne K. Information technology for the treatment of diabetes: improving outcomes and controlling costs. J Manag Care Pharm 2008; 14 (02) 12-17.
    PubMedGoogle Scholar
  • 32 Warm E. Diabetes and the chronic care model: a review. Curr Diabetes Rev 2007; 3: 219-225.
    CrossrefPubMedGoogle Scholar
  • 33 Malasanos T, Burlingame J, Youngblade L, Patel B, Muir A. Improved access to subspecialist diabetes care by telemedicine: cost savings and care measures in the first two years of the FITE diabetes project. J Telemed Telecare 2005; 11 (01) 74-76.
    CrossrefPubMedGoogle Scholar
  • 34 Starren J, Hripcsak G, Sengupta S, Abbruscato C, Knudson P, Weinstock R. et al. Columbia University’s informatics for diabetes education and tele-medicine (IDEATel) project technical implementation. J Am Med Inform Assoc 2002; 9 (01) 25-36.
    CrossrefPubMedGoogle Scholar
  • 35 Blanson Henkemans O, Rogers W, Fisk A, Neerincx M, Lindenberg J, van der Mast C. Usability of an adaptive computer assistant that improves self-care and health literacy of older adults. Methods Inf Med 2008; 47 (01) 82-88.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 36 Logan A, McIsaac W, Tisler A, Irvine M, Saunders A, Dunai A. et al. Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. Am J Hypertens 2007; 20 (09) 942-948.
    CrossrefPubMedGoogle Scholar
  • 37 Shea S, Weinstock R, Starren J, Teresi J, Palmas W, Field L. et al. A randomized trial comparing tele-medicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. J Am Med Inform Assoc 2006; 13 (01) 40-51.
    CrossrefPubMedGoogle Scholar
  • 38 Gorman C, Zimmerman B, Smith S, Dinneen S, Knudsen J, Holm D. et al. DEMS – a second generation diabetes electronic management system. Comput Methods Programs Biomed 2000; 62 (02) 127-140.
    CrossrefPubMedGoogle Scholar
  • 39 Larizza C, Bellazzi R, Stefanelli M, Ferrari P, De Cata P, Gazzaruso C. et al. The M2DM Projectthe experience of two Italian clinical sites with clinical evaluation of a multi-access service for the management of diabetes mellitus patients. Methods Inf Med 2006; 45 (01) 79-84.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 40 Achtmeyer C, Payne T, Anawalt B. Computer order entry system decreased use of sliding scale insulin regimens. Methods Inf Med 2002; 41 (04) 277-281.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 41 Kildegaard J, Randlov J, Poulsen J, Hejlesen O. A study of trained clinicians’ blood glucose predictions based on diaries of people with type 1 diabetes. Methods Inf Med 2007; 46 (05) 553-557.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 42 Biermann E, Rihl J, Schenker M, Standl E. Semi-automatic generation of medical tele-expert opinion for primary care physician. Methods Inf Med 2003; 42 (03) 212-219.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 43 Williams J. Measuring the completeness and currency of codified clinical information. Methods Inf Med 2003; 42 (04) 482-488.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 44 Bu D, Pan E, Walker J, Adler-Milstein J, Kendrick D, Hook J. et al. Benefits of information technology-enabled diabetes management. Diabetes Care 2007; 30 (05) 1137-1142.
    CrossrefPubMedGoogle Scholar
  • 45 Bødker K, Granlien M. Computer support for shared care of diabetes: findings from a Danish case. Stud Health Technol Inform 2008; 136: 389-394.
    PubMedGoogle Scholar
  • 46 Garg S. Glucose monitoring: an important tool for improving glucose control and reducing hypoglycemia. Diabetes Technol Ther 2008; 10 (01) 1-4.
    CrossrefPubMedGoogle Scholar
  • 47 American Diabetes Association.. Standards of medical care in diabetes – 2008. Diabetes care 2008; 31 (01) 12-54.
    CrossrefPubMedGoogle Scholar
  • 48 Mamlin B, Biondich P, Wolf B, Fraser H, Jazayeri D, Allen C. et al. Cooking up an open source EMR for developing countries: OpenMRS – a recipe for successful collaboration. AMIA Annu Symp Proc; 2006: 529-533.
    PubMedGoogle Scholar
  • 49 Blaya J, Shin S, Yagui M, Yale G, Suarez C, Asencios L. et al. A web-based laboratory information system to improve quality of care of tuberculosis patients in Peru: functional requirements, implementation and usage statistics. BMC Med Inform Decis Mak 2007; 7 (01) 33-44.
    CrossrefPubMedGoogle Scholar
  • 50 Sobngwi E, Mauvis-Javis F, Vexiau P, Mbanya J, Gantier J. Diabetes in Africa. Part 1: epidemiology and clinical specificities. Diabetes Metab 2001; 27: 628-634.
    PubMedGoogle Scholar
  • 51 Levitt N, Ohwovoriole E, Komla T, Twahir A, Ramaiya K, Mbanya J. Type 2 diabetes clinical practice guidelines for sub-Saharan Africa. Brussel: International Diabetes Federation Africa Region 2006
    PubMedGoogle Scholar
  • 52 Lehmann E, Chatu S, Hashmy S. Retrospective pilot feedback survey of 200 users of the AIDA version 4 educational diabetes program. 17 – Quantitative survey data. Diabetes Technol Ther 2006; 8 (03) 419-432.
    CrossrefPubMedGoogle Scholar
  • 53 Tatti P, Lehmann E. Utility of the AIDA diabetes simulator as an interactive educational teaching tool for general practitioners (primary care physicians). Diabetes Technol Ther 2001; 3 (01) 133-140.
    CrossrefPubMedGoogle Scholar
  • 54 Lehmann E. Research use of the AIDA www.2aida.org diabetes software simulation program: a review – part 2. Generating simulated blood glucose data for prototype validation. Diabetes Technol Ther 2003; 5 (04) 641-651.
    CrossrefPubMedGoogle Scholar
  • 55 Lehmann E. Research use of the AIDA www.2aida.org diabetes software simulation program: a review – part 1. Decision support testing and neural network training. Diabetes Technol Ther 2003; 5 (03) 425-438.
    CrossrefPubMedGoogle Scholar
  • 56 Murray P. The IMIA strategic plan-towards IMIA 2015. Yearb Med Inform; 2008: 7-15.
    PubMedGoogle Scholar