Healthcare Insights: Evaluating the Access to the Italian Healthcare System

The Italian health system is organised on a regional basis and services are provided by both public and private operators, affecting the planning of services, access to services by citizens and their health rights. The creation of an observatory monitoring the methods and times of access to healthcare services has been pursued. The preliminary phase of the project is presented, which will lead to the comparison of the data obtained from 2019, with an eye on the Covid-19 pandemic impact.

Pinocchio testing in the forensic analysis of waiting lists: using public waiting list data from Finland and Spain for testing Newcomb-Benford's Law

OBJECTIVE

Newcomb-Benford's Law (NBL) proposes a regular distribution for first digits, second digits and digit combinations applicable to many different naturally occurring sources of data. Testing deviations from NBL is used in many datasets as a screening tool for identifying data trustworthiness problems. This study aims to compare public available waiting lists (WL) data from Finland and Spain for testing NBL as an instrument to flag up potential manipulation in WLs.

DESIGN

Analysis of the frequency of Finnish and Spanish WLs first digits to determine if their distribution is similar to the pattern documented by NBL. Deviations from the expected first digit frequency were analysed using Pearson's χ², mean absolute deviation and Kuiper tests.

SETTING/PARTICIPANTS

Publicly available WL data from Finland and Spain, two countries with universal health insurance and National Health Systems but characterised by different levels of transparency and good governance standards.

MAIN OUTCOME MEASURES

Adjustment of the observed distribution of the numbers reported in Finnish and Spanish WL data to the expected distribution according to NBL.

RESULTS

WL data reported by the Finnish health system fits first digit NBL according to all statistical tests used (p=0.6519 in χ² test). For Spanish data, this hypothesis was rejected in all tests (p<0.0001 in χ² test).

CONCLUSIONS

Testing deviations from NBL distribution can be a useful tool to identify problems with WL data trustworthiness and signalling the need for further testing.