Understanding maintenance, repair, and replacement of prosthetic limbs using routinely-collected data: a retrospective study over three decades in Cambodia.

Background: Prosthetic limbs deliver major quality of life and socioeconomic benefits for people with amputation, particularly in low-resource settings. The value of administrative data analysis is established for enabling sustainable health care improvement, but there has been limited research into the maintenance, repair, and replacement of prosthetic limbs. Survivorship data are sparse and highly variable, and rarely addresses differences between demographic groups. Methods: We investigated the distribution of time between device delivery, maintenance/repair, and replacement for a Cambodian cohort, considering the influence of a range of service delivery, user demographics, and health characteristics. We conducted Kaplan-Meier survival analysis and used a Cox model to compare repair and replacement likelihood between groups. Results: We explored 14 822 device deliveries to 6986 clients, with a median of three devices per person (interdecile range (IDR) = 1-9), and 22 878 repairs, with a median of one repair/device (IDR = 0-4). The median device survival before repair was 237 days (IDR = 38-854), and replacement was 727 days (IDR = 208-2154). Devices used by children and people in more active occupations were replaced earlier than those used by the population as a whole, upper-limb devices were replaced later than lower-limb devices, and devices were replaced earlier for volume change than for wear and tear. We observed several less intuitive trends. such as different preferences or capacities for device repair vs. replacement between clinics, and earlier device repair and replacement for women than men. Conclusions: Prosthetic limb maintenance, repair, and replacement are influenced both by the device's durability and the user's access to well-resourced physical rehabilitation services. A device that is worn-out and repaired or replaced early may indicate poor quality, or the opposite, i.e. that it fitted well and enabled great mobility. However, such analysis may enable us to identify groups who are less well-served by current devices or rehabilitation models and contribute to cost-effectiveness analysis of current services. Furthermore, the findings represent benchmark data against which engineers could measure new technologies, to ensure that innovation justifies its inherent risk by offering a genuine improvement which balances functionality, cost, and durability.