BACKGROUND: A large fraction of anti-malaria medicines (and indeed many other medicines classes) used in developing countries are inadequately identified. Framing this problem as one of misidentification rather than the more common framing of criminal misrepresentation leads to new solutions sets not currently being considered. METHOD: That reframing led to consideration and analysis of 4 new problems that informed design of a digital platform technology for delivering a distributed medicine characterization system: 1) problematic interests associated with a focus on preventing counterfeiting, 2) the complexity of the many ways that medicines can deviate from expected identities, 3) the challenge of choosing amongst a diversity of attribute characterization technologies, and 4) the need for a flexible and distributed data aggregation mechanism. RESULTS: Analysis of those new problems confirmed an initial insight that a previously described digital technology for tracking malaria tests results in infrastructure limited regions could be adapted for characterizing pill attributes. Feasibility is illustrated by describing how the platform design can be implemented using open-source software and commodity computational and communication technology readily available and supportable in developing countries. DISCUSSION: A system of this type would allow users to answer several questions. Is this medicine what it is supposed to be? Can it be used to treat locally encountered malaria? What has been the experience of others who have used pills having the same identity? Ubiquitous access to global digital telecommunication infrastructure allows the system to generate data streams from these distributed medicine characterization transactions that can be used to map global patterns of use of specifically identified medicines. This can provide feedback necessary to guide efforts to reduce the burden of malaria.
BACKGROUND: A large fraction of anti-malaria medicines (and indeed many other medicines classes) used in developing countries are inadequately identified. Framing this problem as one of misidentification rather than the more common framing of criminal misrepresentation leads to new solutions sets not currently being considered. METHOD: That reframing led to consideration and analysis of 4 new problems that informed design of a digital platform technology for delivering a distributed medicine characterization system: 1) problematic interests associated with a focus on preventing counterfeiting, 2) the complexity of the many ways that medicines can deviate from expected identities, 3) the challenge of choosing amongst a diversity of attribute characterization technologies, and 4) the need for a flexible and distributed data aggregation mechanism. RESULTS: Analysis of those new problems confirmed an initial insight that a previously described digital technology for tracking malaria tests results in infrastructure limited regions could be adapted for characterizing pill attributes. Feasibility is illustrated by describing how the platform design can be implemented using open-source software and commodity computational and communication technology readily available and supportable in developing countries. DISCUSSION: A system of this type would allow users to answer several questions. Is this medicine what it is supposed to be? Can it be used to treat locally encountered malaria? What has been the experience of others who have used pills having the same identity? Ubiquitous access to global digital telecommunication infrastructure allows the system to generate data streams from these distributed medicine characterization transactions that can be used to map global patterns of use of specifically identified medicines. This can provide feedback necessary to guide efforts to reduce the burden of malaria.
Authors: Paul N Newton; Sue J Lee; Catherine Goodman; Facundo M Fernández; Shunmay Yeung; Souly Phanouvong; Harparkash Kaur; Abdinasir A Amin; Christopher J M Whitty; Gilbert O Kokwaro; Niklas Lindegårdh; Patrick Lukulay; Lisa J White; Nicholas P J Day; Michael D Green; Nicholas J White Journal: PLoS Med Date: 2009-03-24 Impact factor: 11.069