AIMS
Most glucose self-monitoring devices have been developed with high-income countries in mind. We developed a target product profile (TPP) for new glucose self-monitoring technologies for users in low- and middle-income countries (LMICs).
METHODS
A draft TPP including 39 characteristics was developed by an expert group including diabetes specialists, device specialists, and people with diabetes, incorporating findings from qualitative research in LMICs. Each characteristic had minimal and optimal requirements for two use cases, frequent and sporadic use. Characteristics requiring refinement were identified via online survey. Characteristics with agreement level <90% for any requirement were reviewed by the expert group and amended as appropriate.
RESULTS
One characteristic (shelf life) had agreement <75% (both requirements for both use cases). Characteristics with agreement ≥75% and <90% for the frequent use case included infrastructure level, measurement cycle, duration of use before replacement, interchangeability, and calibration (both requirements), and activity log and price per month to end payer (minimal requirement). Intended use (both requirements), accuracy, and price per month to end payer (optimal requirement) had agreement ≥75% and <90% for the sporadic use case.
CONCLUSIONS
This TPP will inform developers on requirements for glucose self-monitoring technologies for LMICs, and support decision-makers in evaluating existing devices.
• Much stronger recommendations are needed to ensure appropriate investment in strengthening and improving the quality of health systems, especially at primary healthcare.
• Governments, the private sector and other actors all need to be involved in finding sustainable solutions to ensure access to medicines and technologies for non-communicable diseases.
• Non-communicable diseases in humanitarian emergencies need to be included in any global guidance on the issue.
• In all contexts allocation of resources needs to optimise access for long-term care and treatment, paired with population-wide prevention efforts in order to guarantee universal health coverage.
Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs).
METHODS
A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate.
RESULT
Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access.
CONCLUSIONS
This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices.