Methodological proposal for the redistribution of deaths due to garbage codes in mortality estimates for Noncommunicable Chronic Diseases

Abstract

Objective: To propose a method for improving mortality estimates from noncommunicable diseases (NCD), including the redistribution of garbage codes in Brazilian municipalities. Methods: Brazilian Mortality Information System (MIS) was used as a data source to estimate age standardized mortality rates, before and after correction, for NCD (cardiovascular, chronic respiratory, diabetes, and neoplasms). The treatment for the correction of data addressed missing data, under-registration, and redistribution of garbage codes (GCs). Three-year periods 2010–2012 and 2015–2017, and the Bayesian method were used to estimate mortality rates, reducing the effect of fluctuation caused by small numbers at the municipal level. Results: GCs redistribution step showed greater weight in corrections, about 40% in 2000 and roughly 20% as from 2007, with stabilization starting in this year. Throughout the historical series, the quality of information on causes of death has improved in Brazil, with heterogeneous results being observed among municipalities. Conclusion: Methodological studies that propose correction and improvement of the MIS are essential for monitoring mortality rates due to NCD at regional levels. The methodological proposal applied, for the first time in real data from Brazilian municipalities, is challenging and deserves further improvements. Improving the quality of the data is essential in order to build more accurate estimates based on the raw data from the SIM.

Premature mortality due to non-communicable diseases in Brazilian municipalities estimated for the three-year periods of 2010 to 2012 and 2015 to 2017

“…This study consisted of a technical-scientific effort to estimate rates of premature mortality due to NCDs in small areas, with the application of a methodology to improve the quality of SIM data, and to analyze them in a spatiotemporal perspective. The treatment of GCs represents a methodological innovation, although it is highlighted that the redistribution applied here, suggested by Teixeira et al 24 , should also be validated in the future.…”

“…More detailed information on the methods used to treat SIM data, the list of codes of defined causes of death investigated in this study and the list of GC can be accessed in another publication 24 .…”

Estimates in small geographic areas: a necessary step towards reducing health inequalities

“…The SIS and its corrections were widely used in this supplement, supporting local managers and researchers in understanding the importance of these adjustments. The SIM was used with corrections for underreporting, redistribution of Garbage Codes and ill-defined causes, application of Baysean methods, among others 11,12 .…”