PP149 Assessment Of New Medical Devices With Administrative Databases

Abstract

INTRODUCTION:

Administrative data (for example, hospital discharge databases, HDDs) can be used as a real world source of clinical and economic evidence for assessing new medical devices (MDs), provided that their use can be identified in the data. In absence of updated classification systems for procedures and diagnoses, which allow to identify the use of new technologies in the data, traceability can still be achieved thanks to authorities coding guidelines (that is, indication on how to combine the existing codes for procedures and/or diagnoses when new technologies are used).

In 2009 Italy adopted version 2007 of the International Classification System of Diseases (ICD-9-CM) and version 24 of Diagnosis Related Groups (DRGs), which are still in use. The aim of this work was to investigate the capacity of the classification system currently used in Italy, which is at high risk of obsolescence, to identify innovative MDs.

METHODS:

To achieve our goal, we performed a systematic search of all the national and regional coding guidelines published from 2009 (that is, the year of introduction of the new classification systems) to 2015. We extracted from each document the list of technologies for which the Ministry of Health and/or the Regional Authorities provided with coding indications.

RESULTS:

Our results show that only a few recent technological innovations can be identified in the Italian HDDs. This reduces the possibility for decision makers to measure new technologies outcomes and costs in the real world clinical practice.

CONCLUSIONS:

The traceability of new MDs' can support Heath Technology Assessment (HTA). Indeed, HTA programs should use real world evidence to re-assess MDs 2–3 years after their introduction in clinical practice. The use of routinely collected data, such as HDD, would allow to measure new technologies' “real” effectiveness in “real” world, on “real” patients in “real” hospitals to complement the evidence from Randomized Controlled Trials.