A novel approach to Data Driven Preventive Maintenance Scheduling of medical instruments

The objective of this endeavor has been to develop a Preventive Maintenance Index (PMI) for each instrument in the clinical engineering inventory to assign a preventive maintenance interval (PM
_Interval
), in what the safety tests most be applied as well as to prioritize the PM procedure. This numerical index has been synthesized based on Risk Level Coefficient (RLC) of the instrument. The equipment inventory has been categorized as per the recommendations of International Electro safety Commission (IEC), Federal Drug Agency (FDA) and Hill into various risk groups as Type C, B, H, Class I, II, III, General, Susceptible, Critical and so on. Relevance factor has been imposed to each aspect analyzed. Static Risk of specific medical equipment is assessed through the factors Physical Risk (PR), Equipment Function (EF), and Hazard Potential (HP).The Hazard Potential of each equipment is extracted from the outcome of a pilot survey conducted at national level, so as the system to be evidence based. The Risk Level Coefficient of equipments are derived by statistically integrating individual relevance coefficients and static risk (SR). A standard audit interval is inadequate; hence PM
_Interval
is designed to be adaptive based on the Interval Adaptation Coefficient (IAC) which in turn points Failure / accident history of the equipment. An attempt to incooperate the PM Due Factor (DF), Age Ratio (AR) and Usability Ratting (UR) also has been made. The proposed `Data Driven Preventive Maintenance Scheduling', is in par and comply with, ISO 14971, IEC 60601 Series and JCAHO regulations.