Morbidade materna extremamente grave a partir dos registros de internação hospitalar do sistema único de saúde: Algoritmo para identificação dos casos

Abstract

Objectives: to identify codes for constant procedures in the Brazilian National Health System's Hospital Information System (SIH-SUS) deemed to be cases of Extremely Severe Maternal Morbidity (MMEG) and to develop an algorithm to manage/prepare an AIH database, with a view to identifying cases of MMEG in this database. Methods: the data used were from the SIH-SUS supplied by the Juiz de Fora Health Secretary and refer to admissions to SUS hospitals between 2006 and 2007. The study covered all admissions where the principal diagnosis involved all of Chapter XV of CID10 - complications of pregnancy, miscarriage, delivery and puerperium and/or admissions to hospital involving obstetric procedures. For identification of SIH-SUS procedures deemed to be MMEG, the criteria proposed by the WHO were used. The algorithm was developed using Microsoft Access. Results: 326 cases of MMEG were found among the 8620 women selected, constituting a rate of 37.8/1000 women. The most frequent procedures were transfusion of blood products, "a longer stay" and severe pre-eclampsia/eclampsia, with a prevalence of 15.7/1000, 9.5/1000 and 8.2/1000, respectively. Conclusions: the algorithm used may optimize the use of the SIH-SUS for identifying cases of MMEG and generating information for maternal morbidity and mortality surveillance services and the evaluation of obstetric care.