Abstract

OBJECTIVE:

to describe near miss maternal morbidity among women living in Paraná State, Brazil, in 2010.

METHODS:

this was a descriptive study using Brazilian National Hospital Information System (SIH/SUS) data on all hospital admissions with primary diagnosis falling under Chapter XV of the International Statistical Classification of Diseases and Related Health Problems 10th Revision and/or with records of obstetric procedures indicative of near misses; three criteria were used to define severe maternal morbidity.

RESULTS:

4,890 admissions owing to near miss were identified, with a rate of 52.9 hospitalizations per 1,000 births, a rate of 69.8/1,000 among women aged 35-39 and a rate of 356.6/1,000 among women aged 44-49; the leading causes of hospitalization were preeclampsia (28.2%), haemorrhage (23.7%) and immune system dysfunction (14.0%).

CONCLUSION:

the results indicate the need to pay greater attention to women aged 35 and over since they had higher rates of near miss.

Keywords:
Maternal Mortality; Morbidity; Pregnancy Complications; Hospital Records; Epidemiology, Descriptive

Introduction

Severe maternal morbidity, also known as near miss, is an event of near death caused by severe complications that occur with a woman during pregnancy, childbirth or puerperium. ¹1. Say L, Souza JP, Pattinson RC; World Health Organization working group on Maternal Mortality and Morbidity classifications. Maternal near miss-towards a standard tool for monitoring quality of maternal health care. Best Pract Res Clin Obstet Gynaecol. 2009 Jun;23(3):287-96. The near miss rate is used as a development indicator in several countries, ²2. Troncon JK, Quadros Netto DL, Rehder PM, Cecatti JG, Surita FG. Mortalidade materna em um centro de referência do sudeste brasileiro. Rev Bras Ginecol Obstet. 2013 set;35(9):388-93. so monitoring may be considered a tool for the prevention of maternal morbidity and mortality, and once those cases are identified, they can be an important alternative and complementary strategy to reduce the occurrence of maternal deaths. ³3. Souza JP, Gülmezoglu AM, Vogel J, Carroli G, Lumbiganon P, Qureshi Z, et al. Moving beyond essential interventions for reduction of maternal mortality (the WHO Multicountry Survey on Maternal and Newborn Health): a cross-sectional study. Lancet. 2013 May;381(9879):1747-55.

Single women, with black skin color, who are less than 20 years old or more than 35, and who have a lower socio-economic status are among the population group that is more vulnerable to the occurrence of complication during pregnancy. ⁴4. Viana RC, Novaes MRCG, Calderon IMP. Mortalidade materna: uma abordagem atualizada. Comun Cienc Saude. 2011; 22 supl 1:S141-S52.

Women mortality due to obstetric causes has declined all over the world, since the decade of 1990s. ⁵5. World Health Organization. Trends in maternal mortality: 1990 to 2008: estimates developed by WHO, UNICEF, UNFPA and The World Bank. Geneva: World Health Organization; 2010. In Brazil, in spite of the 52% reduction in maternal mortality rates, from 120 maternal deaths per 100 thousand live births (LB) in 1990 to 58/100 thousand LB in 2008, the target set by the Millennium Development Goals - 35 deaths per 100 thousand LB for the year of 2015 has not been achieved yet. ⁵5. World Health Organization. Trends in maternal mortality: 1990 to 2008: estimates developed by WHO, UNICEF, UNFPA and The World Bank. Geneva: World Health Organization; 2010. There are variations in the rates among the Brazilian regions, varying from 69.0 in the Northeast and 62.5 in the North, to 47.2 in the Southeast and 44.4 in the South, in 2011. ⁶6. Ministério da Saúde (BR). Secretaria Executiva. Datasus. Informações de Saúde. Epidemiológicas e morbidade [Internet]. Brasília: Ministério da Saúde; 2014. [citado 2015 set 03]. Disponível em: Disponível em: http://www2.datasus.gov.br/DATASUS/index.php?area=0203
http://www2.datasus.gov.br/DATASUS/index... In that same year, Paraná State presented the highest maternal mortality rate among the states of the Southern region of the country (51.7 per 100 thousand LB), whilst Santa Catarina presented 25.2 per 100 thousand LB, and Rio Grande do Sul, 48.7 per 100 thousand LB. ⁶6. Ministério da Saúde (BR). Secretaria Executiva. Datasus. Informações de Saúde. Epidemiológicas e morbidade [Internet]. Brasília: Ministério da Saúde; 2014. [citado 2015 set 03]. Disponível em: Disponível em: http://www2.datasus.gov.br/DATASUS/index.php?area=0203
http://www2.datasus.gov.br/DATASUS/index...

In 2014, a population-based study conducted in Natal-RN found a near miss rate of 41.1/1,000 LB. ⁷7. Rosendo TMSS, Roncalli AG. Prevalência e fatores associados ao Near Miss Materno: inquérito populacional em uma capital do nordeste Brasileiro. Cienc Saude Coletiva. 2015 abr;20(4):1295-304. Another research, conducted in Recife-PE, on the data of 225 medical records of hospital admissions in an intensive care unit (ICU) from 2007 to 2010, presented a rate of 12.8/1,000 LB. ⁸8. Oliveira LC, Costa AAR. Near miss materno em unidade de terapia intensiva: aspectos clínicos e epidemiológicos. Rev Bras Ter Intensiva. 2015 jul-set;27(3):220-7.

The monitoring and knowledge on the complications that may occur are essential to improve the quality of women's life during pregnancy, childbirth and puerperium, and to reduce maternal morbidity and mortality until it reaches the target established by the Millennium Development Goals. ⁹9. Morse ML, Fonseca SC, Gottgtroy CL, Waldmann CS, Gueller E. Severe maternal morbidity and near miss in a Regional reference hospital. Rev Bras Epidemiol. 2011 Jun;14(2):313-22.

The first studies on severe maternal morbidity or near miss began in the decade of 1990s and, after almost three decades, there is no clear and consensual theoretical and operational definition on this event. ¹⁰10. Nakamura-Pereira M, Silva WM, Dias MAB, Reichenheim ME, Lobato G. Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH/SUS): uma avaliação do seu desempenho para identificação do near miss materno. Cad Saude Publica. 2013 jul;29(7):1333-45.^,1111. Victora CG, Aquino EML, Leal MC, Monteiro CA, Barros FC, Szwarcwald CL. Maternal and child health in Brazil: process and challenges. Lancet. 2011 May;377(9780):1863-76. Some studies point out that the main causes of near miss are the hypertensive emergencies, followed by haemorrhage and sepsis. ⁹9. Morse ML, Fonseca SC, Gottgtroy CL, Waldmann CS, Gueller E. Severe maternal morbidity and near miss in a Regional reference hospital. Rev Bras Epidemiol. 2011 Jun;14(2):313-22.^,1212. Pileggi C, Souza JP, Cecatti JG, Faundes A. Abordagem do near miss neonatal no 2005 WHO Global Survey Brazil. J Pediatr (Rio J). 2010 jan-fev;86(1):21-6.

In a search for a consensus over severe maternal morbidity, the Department of Reproductive Health and Research of the World Health Organization (WHO), in a joint work with other organizations and supported by the Bill & Melinda Gates Foundation, created the Maternal Morbidity Working Group (MMWG), ¹³13. Firoz T, Chou D, von Dadelszen P, Agrawal P, Vanderkruik R, Tunçalp O, et al. Measuring maternal health: focus on maternal morbidity. Bull World Health Organ. 2013 Oct;91(10):794-6. which defined maternal morbidity as 'any health condition attributed to, and/or aggravated by, pregnancy and birth that has a negative impact on the woman's wellbeing'. This definition will be included in the Eleventh Revision of the International Statistical Classification of Diseases and Related Health Problems. ¹³13. Firoz T, Chou D, von Dadelszen P, Agrawal P, Vanderkruik R, Tunçalp O, et al. Measuring maternal health: focus on maternal morbidity. Bull World Health Organ. 2013 Oct;91(10):794-6.

Considering that women's death during pregnancy, childbirth and puerperium represent only the "tip of the iceberg" of women's health conditions, and that there are few studies on severe maternal morbidity that address all Brazilian regions, the identification of resulting severe complications can be a path to improve the quality of the care given to the health of Brazilian women in their reproductive period. In this sense, the Brazilian National Hospital Information System (SIH/SUS) can be an important source of information in the identification and surveillance of severe maternal morbidity cases. ¹⁴14. Magalhães MC, Bustamante-Teixeira MT. Morbidade materna extremamente grave: uso do Sistema de Informação Hospitalar. Rev Saude Publica. 2012 jun; 46(3):472-8.

The objective of this study was to describe near miss maternal morbidity among women living in Paraná State, Brazil, in 2010.

Methods

This is a descriptive study, on the data of the Hospital Information System of the Brazilian National Health System - SIH/SUS. We considered here the hospital admission records of women aged 10 and 49 years, living in Paraná State, in 2010.

The SIH/SUS is an information system coordinated by the Ministry of Health with the administrative goal of paying for hospitalizations that occur in public or insured hospitals. The system has the Inpatient Hospital Authorization (IHA) as its primary document. This document is filled in with the information of other documents, such as the medical report and the patient's hospital medical record. ¹⁴14. Magalhães MC, Bustamante-Teixeira MT. Morbidade materna extremamente grave: uso do Sistema de Informação Hospitalar. Rev Saude Publica. 2012 jun; 46(3):472-8.^,1515. Ministério da Saúde (BR); Organização Pan-Americana da Saúde; Fundação Oswaldo Cruz. A experiência brasileira em sistemas de informação em saúde: falando sobre os sistemas de informação em saúde no Brasil. Vol. 2. Brasília: Ministério da Saúde; 2009. (Série B. Textos básicos de saúde).

Paraná State, located in the Brazilian Southern region, covers a geographical area of 199,880 km ²2. Troncon JK, Quadros Netto DL, Rehder PM, Cecatti JG, Surita FG. Mortalidade materna em um centro de referência do sudeste brasileiro. Rev Bras Ginecol Obstet. 2013 set;35(9):388-93. and has 339 municipalities. In 2014, Paraná State was the fourth biggest economy of the country, responsible for 6.3% of the national gross domestic product and with a human development index (HDI) of 0.749. ¹⁶16. Instituto Paranaense de Desenvolvimento Econômico e Social. Paraná em números [Internet]. Curitiba: Instituto Paranaense de Desenvolvimento Econômico e Social; 2015 [citado 2015 nov 05]. Disponível em: Disponível em: http://www.ipardes.gov.br/index.php?pg_conteudo=1&cod_conteudo=1 .
http://www.ipardes.gov.br/index.php?pg_c...

The process of building the study's database was conducted, initially, with the selection of all hospital admissions of women living in Paraná that had occurred between January 1 and December 31, 2010. After that, we selected those women aged 10-49 years, with primary or secondary diagnosis falling under Chapter XV - Pregnancy, childbirth and puerperium (codes O00 to O99) - of the International Statistical Classification of Diseases and Related Health Problems - 10th Revision (ICD-10). ¹⁷17. World Health Organization. Classificação estatística internacional de doenças e problemas relacionados à saúde. 10 ed rev. Vol. 2. São Paulo: Centro Colaborador da OMS para a Classificação de Doenças em Português; 2009.

The classification proposed by Sousa et al., ¹⁸18. Sousa MH, Cecatti JG, Hardy EE, Serruya SJ. Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance. Reprod Health. 2008;5:6. based on the criteria or markers established by Mantel et al. ¹⁹19. Mantel GD, Buchmann E, Rees H, Pattinson RC. Severe acute maternal morbidity: a pilot study of a definition for a near-miss. Br J Obstet Gynaecol. 1998 Sep;105(9):985-90. and Waterstone et al., ²⁰20. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ. 2001 May;322(7294):1089-93. was used for the selection of hospital admissions due to severe maternal morbidity and was complemented with the existing criteria/markers and procedures in the database of SIH/SUS. The criteria defined by Mantel et al. ¹⁹19. Mantel GD, Buchmann E, Rees H, Pattinson RC. Severe acute maternal morbidity: a pilot study of a definition for a near-miss. Br J Obstet Gynaecol. 1998 Sep;105(9):985-90. include the conditions related to organic dysfunction of the human body organs and systems, in addition to the procedures related to the assistance. The criteria defined by Waterstone et al²⁰20. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ. 2001 May;322(7294):1089-93. include clinical diagnoses of the most frequent pathological conditions, such as severe preeclampsia, severe haemorrhage, severe sepsis and uterine rupture. In turn, Sousa et al. ¹⁸18. Sousa MH, Cecatti JG, Hardy EE, Serruya SJ. Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance. Reprod Health. 2008;5:6. added other diagnoses, such as acute abdomen, the human immunodeficiency virus (HIV) and other conducted procedures - some of which were surgical (Figure 1).

For the selection of hospital admissions by codes of the procedures conducted during the woman's hospitalization period, the table of obstetric procedures in the classification of SUS Management System of the Table of Procedures, Medicines, Orthotics, Prosthetics and Special Materials (SIGTAP) was used, ²¹21. Ministério da Saúde (BR). Portaria nº 321 de 8 de fevereiro de 2007. Institui a tabela de procedimentos, medicamentos, Órteses/Próteses e Materiais especiais - OPM do Sistema Único de Saúde - SUS. Diário Oficial da República Federativa do Brasil, Brasília (DF), 2007 fev 9; Seção 1:42. since it unifies and standardizes the procedure codes of SIH/SUS and the SUS Ambulatory Care Information System (SIA/SUS). For the present study, it was necessary to update some procedures, altered by SIGTAP's new classification criteria, as can be seen in the fourth and fifth columns of Figure 2.

The hospital admissions with procedures for severe haemorrhage (Waterstone et al. criterion ²⁰20. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ. 2001 May;322(7294):1089-93. ) were excluded, since the updated code related to this procedure includes a set of admissions with procedures for the treatment of clinical problems in pregnancy, with no specification of the severity of these problems. If this procedure was considered, any irregularity could be included, even if it was not related to severe maternal morbidity. However, all the hospital admissions that had severe haemorrhage as primary diagnosis were selected.

It is important to highlight that the hospital admissions due to severe maternal morbidity were identified and selected from the group of admissions due to maternal morbidity as the criteria and markers were being applied, with no possibility of duplication.

The severe maternal morbidity rate - near miss - was calculated as the ratio between the number of hospital admissions due to severe maternal morbidity and the number of childbirths, multiplied by 1,000. In the denominator, the number of childbirths identified in the database was considered according to the primary diagnosis recorded on SIH/SUS, and not to the number of live births, since the Information System on Live Births (Sinasc) does not allow distinguishing between births that were and were not funded by the National Health System. For this study, only the hospital admissions funded by SUS were analyzed.

Absolute and relative frequencies of the admissions due to severe maternal morbidity were described according to the most frequent criteria or markers. The age was organized in 5-year intervals, and also in the following age groups, 10-19, 20-34 and 35-49, with the aim of estimating the frequency and rates of severe maternal morbidity, according to the most aggregated age groups.

The study project was approved by the Ethics Committee on Research of the State University of Maringá-PR (UEM): Resolution No. 093/2011.

Results

Out of the total 111,409 hospital admissions with primary diagnosis of pregnancy, childbirth or puerperium, we selected 141 admissions for childbirth mentioning admission to ICU and/or complications and/or death, and other 34,472 admissions due to various reasons. From the admissions with primary diagnosis belonging to other chapters of the ICD-10, 534 with secondary diagnosis of pregnancy, childbirth and puerperium were selected, totalizing 35,147 admissions due to maternal morbidity. From them, 4,890 were selected, of which 4,225 were by primary diagnosis, 216 by admission in ICU, 25 by secondary diagnosis and 424 by obstetric procedures conducted during admission. Figure 2 presents the study's flowchart.

For the calculation of the severe maternal morbidity rate, 92,397 childbirths were accounted in the denominator, being 76,936 of them admitted due to childbirth and 15,461 with the reference of childbirth among the conducted procedures. In 2010, the severe maternal morbidity rate in Paraná State was of 52.9 admissions per 1,000 childbirths. In that year, the highest severe maternal morbidity rates observed occurred in the highest age groups, reaching 356.6 admissions per 1,000 childbirths in women aged 45-49 years, whilst for women aged 20-24 years, this rate was of 41.2; and for those aged 15-19 years, of the rate was of 37.7 admissions per 1,000 births (Figure 3).

The leading causes of severe maternal morbidity were preeclampsia, with 14.9 admissions per 1,000 births, followed by severe haemorrhage (12.5/1,000 births), immune system dysfunction (7.4/1,000 births), severe sepsis (5.5/1,000 births) and eclampsia (5.1/1,000 births). Concerning the main causes of severe maternal morbidity by age group, severe haemorrhage was found in the age group 10-19 years, with 11.1 admissions per 1,000 births, and preeclampsia in the age group 20-34 years (15.9/1,000 births) and 35-49 years (23.4/1,000 births). Considering all the age groups that were analyzed, women aged 35-49 years presented the highest severe maternal morbidity rate: 88.6 admissions per 1,000 births (Table 1).

There was a difference in the identification of severe maternal morbidity cases, depending on the criteria used. Waterstone's criteria allowed identifying more severe maternal morbidity cases - 3,539 admissions - when comparing with Mantel's criteria, which showed 1,265 admissions, and with Sousa's criteria, with 86 admissions. Among the criteria used, in relation to the codes, there was no equality in the evaluated items (Table 1).

Discussion

This study showed that the rate of hospital admissions due to severe maternal morbidity in Paraná State was higher in women aged 35 years and over, and the main causes of hospital admission were preeclampsia, severe haemorrhage and immune system dysfunction.

The severe maternal morbidity rate in Paraná State was higher than the estimates of the rates presented by a systematic review of researches conducted in the period 2004-2010, directed to countries in Africa, Asia and Latin America. ²²22. Tunçalp O, Hindin MJ, Souza JP, Chou D, Say L. The prevalence of maternal near miss: a systematic review. BJOG. 2012 May;119(6):653-61. In the municipality of Juiz de Fora-MG, a research based on SIH/SUS data in 2006-2007 identified 326 women with admissions due to severe maternal morbidity, with a rate of 37.8/1,000 childbirths. ²³23. Magalhães MC, Raymundo CE, Bustamante-Teixeira MT. Morbidade materna extremamente grave a partir de registros de internamento hospitalar no Sistema Único de Saúde: algoritmo para identificação dos casos. Rev Bras Saude Mater Infant. 2013 jan-mar;13(1):17-22.

In this study, the highest rate of admissions due to severe maternal morbidity found among older women corroborates a study conducted in Rio de Janeiro-RJ, in 2009, which showed higher frequency of near miss in the age group of over 30 years (34.8). ⁹9. Morse ML, Fonseca SC, Gottgtroy CL, Waldmann CS, Gueller E. Severe maternal morbidity and near miss in a Regional reference hospital. Rev Bras Epidemiol. 2011 Jun;14(2):313-22.

With regard to the criteria of Mantel et al. ¹⁹19. Mantel GD, Buchmann E, Rees H, Pattinson RC. Severe acute maternal morbidity: a pilot study of a definition for a near-miss. Br J Obstet Gynaecol. 1998 Sep;105(9):985-90. and Waterstone et al., ²⁰20. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ. 2001 May;322(7294):1089-93. the most frequent causes of admissions that indicate severe maternal morbidity were preeclampsia (28.2%), followed by severe haemorrhage (23.7%) and immune system dysfunction (14.0%). In Sousa et al.'s study, ¹⁸18. Sousa MH, Cecatti JG, Hardy EE, Serruya SJ. Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance. Reprod Health. 2008;5:6. conducted with 2002 SIH/SUS data, when including all Brazilian capitals with Waterstone and Mantel's criteria, in addition to adding three more criteria (acute abdomen, HIV disease and surgical procedures), the results were different, with a higher incidence of immune system dysfunction comparing to severe haemorrhage. ¹⁸18. Sousa MH, Cecatti JG, Hardy EE, Serruya SJ. Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance. Reprod Health. 2008;5:6. In 2014, a population based survey was conducted in Natal-RN and identified, as markers for severe maternal morbidity, admission in ICU (19.1/1,000 births), eclampsia (13.5/1,000 births), blood transfusion (11.3/1,000 births) and hysterectomy (2.3/1,000 births). ⁷7. Rosendo TMSS, Roncalli AG. Prevalência e fatores associados ao Near Miss Materno: inquérito populacional em uma capital do nordeste Brasileiro. Cienc Saude Coletiva. 2015 abr;20(4):1295-304.

In a systematic review on the prevalence of severe maternal morbidity, 33 studies were found. They were conducted in the period 1999-2010, pointing the emergency hysterectomy as a criterion for near miss diagnosis. The same review showed that countries with low and medium income, most of them located in Asia and Africa, have higher severe maternal morbidity rates, ²²22. Tunçalp O, Hindin MJ, Souza JP, Chou D, Say L. The prevalence of maternal near miss: a systematic review. BJOG. 2012 May;119(6):653-61. corroborating the data from the World Health Organization: according to the institution, about 536 thousand women die every year due to complications during pregnancy, and 99% of these deaths occur in low and medium income countries. ²⁴24. World Health Organization. World Health Statistics: 2009. Geneva: World Health Organization; 2009.

From the detailed analysis of each criterion adopted in the diagnoses for severe maternal morbidity, using the total amount of each criterion, we can notice that the criteria of organic dysfunction (dysfunctions of the many systems of the human body [Mantel]) are more restrict in identifying near miss cases: they showed only 26% of the cases of this study. The criteria of clinical conditions (Waterstone) identified 72% of the cases.

This inequality in the severe maternal morbidity rates pointed out in the literature through the use of different criteria brings up the discussion on the possibility to adopt a single and standardized classification, capable of providing, as routine procedures, the surveillance and analysis of these conditions by hospitals' health care teams that assist women during pregnancy, childbirth and puerperium.

WHO, in an attempt to standardize these criteria, formulated a classification based on three principles of severe maternal morbidity: clinical markers; laboratory markers; and management markers. ²⁵25. Pattinson R, Say L, Souza JP, Broek N, Rooney C; WHO Working Group on Maternal Mortality and Morbidity Classifications. WHO maternal death and near-miss classifications. Bull World Health Organ. 2009 Oct;87(10):734. However, a study, conducted in 2009, used this classification for the selection of severe maternal morbidity cases in a public hospital of Niterói-RJ, and concluded that, in addition to these principles, it would also be necessary to use the criteria proposed by Mantel et al. ¹⁹19. Mantel GD, Buchmann E, Rees H, Pattinson RC. Severe acute maternal morbidity: a pilot study of a definition for a near-miss. Br J Obstet Gynaecol. 1998 Sep;105(9):985-90. and by Waterstone et al. ²⁰20. Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ. 2001 May;322(7294):1089-93. for identifying the cases, since they are based on different approaches, with different characteristics. ⁹9. Morse ML, Fonseca SC, Gottgtroy CL, Waldmann CS, Gueller E. Severe maternal morbidity and near miss in a Regional reference hospital. Rev Bras Epidemiol. 2011 Jun;14(2):313-22. The classification adopted by WHO allows the identification of more severe cases, with higher risk of death. On the other hand, Waterstone's criteria broaden the cases detection.

Despite the lack of an operational classification of severe maternal morbidity events, the method used in this study showed that is possible to detect cases by analyzing the information from SIH/SUS.

The SIH/SUS can be used as a tool to analyze hospital morbidity. The system represents an important option for the planning of preventive measures. ¹²12. Pileggi C, Souza JP, Cecatti JG, Faundes A. Abordagem do near miss neonatal no 2005 WHO Global Survey Brazil. J Pediatr (Rio J). 2010 jan-fev;86(1):21-6. Identifying admissions of women with obstetric complications is essential for planning the care during pregnancy, childbirth and puerperium. This identification brings information so that health professionals may avoid death or severe complications in women. ²⁶26. Magalhães MC, Raymundo CE, Bustamante-Teixeira MT. Morbidade materna extremamente grave a partir de registros de internamento hospitalar no Sistema Único de Saúde algoritmo para identificação dos casos. Rev Bras Saude Mater Infant. 2013 jan-mar;13(1):17-22.

The use of this method can be a way to study severe maternal morbidity cases in Brazil, its regions and municipalities, considering that the admissions supported by SUS are still a majority in the country, which will allow an evaluation of the care provided by the Brazilian Public Health.

The use of secondary data has increased in Brazilian studies. They generate epidemiological information on the populations' health as a whole, in addition to the possibility of revealing the profile of obstetric complications and death of women in reproductive age. ²⁷27. Coeli CM. Sistema de informação em saúde e uso de dados secundários na pesquisa e avaliação em saúde. Cad Saude Colet. 2010;18(3):335-36.

In 2008, a study conducted in the municipality of Rio de Janeiro-RJ sought to identify cases of severe maternal morbidity by comparing data resulting from the revision of hospital admissions with those available at SIH/SUS database. The authors did not recommend the use of SIH/SUS as a source for identifying severe maternal morbidity and the possible prevention of these complications. ¹⁰10. Nakamura-Pereira M, Silva WM, Dias MAB, Reichenheim ME, Lobato G. Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH/SUS): uma avaliação do seu desempenho para identificação do near miss materno. Cad Saude Publica. 2013 jul;29(7):1333-45. However, another study, which was conducted in Paraná State in 2010, and thus, using most recent records of SIH/SUS, found that the system can be a valuable tool for identifying obstetric complications. ²⁸28. Veras TCS, Mathias TAF. Principais causas de internações hospitalares por transtornos maternos. Rev Esc Enferm USP. 2014;48(3):401-8. It is important to highlight that few countries have well-structured hospital admission information systems, and Brazil is one of them. ²⁹29. Haddad SM, Cecatti JG, Parpinelli MA, Souza JP, Costa ML, Sousa MH, et al. From planning to practice: building the national network for the surveillance of severe maternal morbidity. BMC Public Health. 2011 May;11:283.

However, there are some limits imposed in working with secondary data, in which information generated by the system depends on the (i) quality and coverage of the data filled in hospital medical records and the (ii) qualification of professionals that encode the diagnoses of hospital admissions. These conditions are added to the fact that SIH/SUS main objective is to transfer financial resources to hospitals, reason why we could not use the haemorrhage criterion as secondary diagnosis in this study, due to the changes promoted in the procedures' codes, which began to include all hospital admissions with procedures per treatment of clinical irregularities of pregnancy, with no specification of the severity of these diseases.

Regardless of these limitations, studies on severe maternal morbidity that use SIH/SUS can be a promising path for the surveillance of these complications, since the results that were found in this study are similar to other studies on this topic.

The severe maternal morbidity events - near miss - are not rare in the country's health clinics and hospitals. For health services, this study presents SIH/SUS as a tool for identifying these cases, with the objective of improving the quality of assistance and, consequently, the reduction of maternal mortality. The results presented also show the need to pay particular attention to women aged 35 years and over, which are exactly the group who presented the highest rates of severe maternal morbidity.

References

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