Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31181
Service Blueprint for Improving Clinical Guideline Adherence via Mobile Health Technology

Authors: Y. O’Connor, C. Heavin, S. O’ Connor, J. Gallagher, J. Wu, J. O’Donoghue


Background: To improve the delivery of paediatric healthcare in low resource settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (inadequate adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (SL eCCM app) as an exemplar. Results: A service blueprint is developed which illustrates how the SL eCCM app can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users.

Keywords: Adherence, community health workers, mobile clinical decision support systems, CDSS, developing countries, service blueprint

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2253


[1] J. G. Yang, J.S. Yang, J. Kahn, “Mobile health needs and opportunities in developing countries”, Health Affairs, vol. 29, pp. 252-258, 2010.
[2] L. Iwaya, M. Gomes, MA. Simplicio, TC. Carvalho, CK. Dominicini, RR. Sakuragui, MS. Rebelo, MA. Gutierrez, M. Naslund, P. Hakansson, P, “Mobile health in emerging countries: A survey of research initiatives in Brazil. International Journal of Medical Informatics. 82, 283-98. 2013.
[3] T. Tamrat, S. Kachnowski, “Special delivery: An analysis of mHealth in maternal and newborn health programs and their outcomes around the world”, Maternal Child Health Journal, vol. 16, pp. 1092–1101. 2012.
[4] A. Chib, MH. Van Velthoven, J. Car, “mHealth adoption in lowresource environments: A review of the use of mobile healthcare in developing countries”, Journal of Health Communication, vol. 20, no. 1, pp. 4-34. 2015.
[5] WHO. URL:
[6] CJ. Briggs, P. Garner, “Strategies for integrating primary health services in middle- and low-income countries at the point of delivery”, Cochrane Database of Systematic Reviews, vol. 19, no.2, CD003318, 2006.
[7] World Health Organisation Report. The Multi-Country Evaluation of IMCI Effectiveness, Cost and Impact (MCE): Progress Report, May 2001 - April 2002 World Health Organisation. Available at:
[8] AK. Rowe, D. de Savigny, CF. Lanata, CG. Victora, “How can we achieve and maintain high-quality performance of health workers in low-resource settings?”, Lancet, vol. 366, no. 9490,pp. 1026–1035. 2005.
[9] S. Gove, “Integrated management of childhood illness by outpatient health workers: technical basis and overview. The WHO Working Group on Guidelines for Integrated Management of Sick Children”, Bulletin of the World Health Organisation, vol. 75, suppl. 1, pp. 7- 24.1999.
[10] J. Bryce, CG. Victoria, Habicht, JP., RE Black, RW Scherpnier; MCEIMCI Technical Advisors, Programmatic pathways to child survival: results of a multi-country evaluation of Integrated Management of Childhood Illness. Health Policy and Planning, vol. 20, suppl. 1, pp. i5- i17. 2005.
[11] J. Bryce, S. el Arifeen, G. Pariyo, C. Lanaa, D. Gwatkin, J. Habicht, Reducing child mortality: can public health deliver? Lancet, vol. 362, no. 9378, pp. 159-164. 2003.
[12] B. DeRenzi, N. Lesh, T. Parikh, et al., E-IMCI: Improving pediatric health care in low-income countries, In Proc. of the SIGCHI conference on human factors in computing systems, 753-762. 2008.
[13] T. Adam, F. Manzi, JA. Schellenberg, L. Mgalula, D. de Savigny, DB Evans, “Does the Integrated Management of Childhood Illness cost more than routine care? Results from the United Republic of Tanzania,” Bulletin of the World Health Organization, vol.83, no. 5.pp, 369-377.
[14] HM Admed, M. Mitchell, B. Hedt. National implementation of Integrated Management of Childhood Illness (IMCI): Policy constraints and strategies. Health Policy, vol. 96, no.2. pp.128-133. 2010.
[15] M. Mitchell, M. Getchell, M. Nkaka, D. Msellemu J. Van Esch, B. Hedt- Gauthier, “Perceived improvement in integrated management of childhood illness implementation through use of mobile technology: qualitative evidence from a pilot study in Tanzania,” Journal of Health Communication, Vol. 13, sup 1, pp. 118-127. 2012.
[16] C. Gronroos, “Service management: a management focus for service competition,” International Journal of Service Industry Management, vol. 1, no. 1, pp. 6-14, 1990.
[17] E. Gummesson, “Relationship marketing and a new economy: it’s time for de-programming,” Journal of Services Marketing, vol. 16, no. 7, pp. 585-589. 2002.
[18] B. O’Flaherty, S. Woodworth, C, Thornton, Y. O’Connor Y. “An Exploration of Customer-Centric Cloud Service Design”. In: Helfert M, and Donnellan B, ed. Design Science: Perspectives from Europe. Springer International Publishing, vol. 388, pp. 99-111.2013.
[19] I. Sim, P. Gorman, R. Greenes, BR. Haynes, B. Kaplan, H. Lehmann, PC. Tang, “Clinical Decision Support Systems for the Practice of Evidence-based Medicine”, Journal of the American Medical Informatics Association, vol. 8, no. 6, pp. 527-534. 2001.
[20] AX. Garg, N. Adhikari, H. McDonald, et al., “Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. A systematic review,” Journal of the American Medical Association, vol. 293, no. 10, pp. 1223-1238. 2009.
[21] C. McGowan, RG. Neville, IW. Ricketts, FC. Warner, G. Hoskins, GE. Thomas, “Lessons from a randomized controlled trial designed to evaluate computer decision support software to improve the management of asthma,” Medical Informatics and Internet in Medicine, vol. 26, no. 3, pp. 191-201. 2001.
[22] A. Zarabzadeh, J. O’Donoghue, Y. O’Connor, T. O’Kane, S. Woodworth, G. Gallagher, S. O’Connor, “Variations in health care providers’ perceptions: decision making based on patient vital signs,” Journal of Decision Systems, vol. 22, no. 3, pp. 168-189. 2013.
[23] D.L. Hunt, R.B. Haynes, S.E. Hanna, K. Smith, “Effects of Computer- Based Clinical Decision Support Systems on Physician Performance and Patient Outcomes. A Systematic Review,” Journal of the American Medical Association, vol. 280, no.15, pp. 1339-1346. 1998.
[24] SS. Intille, “Ubiquitous computing technology for just-in-time motivation of behavior change”, In Proc. of Medinfo, vol. 11, pp. 1434- 1437. 2004.
[25] GL. Shostack, “How to design a service,” European Journal of Marketing, vol. 16, no. 1, pp. 49-63. 1982.
[26] MJ. Bitner, AL. Ostrom, F. Morgan F. “Service blueprinting: a practical technique for service innovation,” California Management Review, vol. 50, no. 3, pp. 66-94. 2008.