ABSTRACT

Objective:

To evaluate the capability of hospital records in the Hospital Information System (SIH) to add valuable and complementary information to the Mortality Information System (SIM) in studies on maternal mortality. We calculated and compared the maternal mortality ratio from the SIH and SIM databases, by age group and region, to highlight differences between groups and assess the coverage of maternal deaths using SIH compared with SIM.

Methods:

Obstetric hospitalizations were defined based on three sources (codes ICD-10 in diagnoses; procedures; billing information). Hospital and SIM mortality ratios were calculated by dividing maternal deaths in hospitals affiliated to the Unified Brazilian Health System (SUS) per live births (SINASC) in the same hospitals.

Results:

In 2019, we identified 2,497,957 obstetric admissions, 0.04% (946) with in-hospital mortality as outcome. The presence of three criteria identified 98% of obstetric hospitalizations and 83% of obstetric hospitalizations with death as outcome. The comparison of mortality ratios between SIH (45.5 MMR; 95%CI 42.7 – 48.5) and SIM (49.7 MMR; 95%CI 46.7 – 52.8) was not statistically significant (p-value: 0.053).

Conclusion:

The analysis of SIH was able to provide additional information for the monitoring and surveillance of maternal health in Brazil. Although there are differences between the mortality rates, the SIH, as a complementary information system to the SIM, may be valid in studies on maternal mortality and morbidity.

Keywords:
Maternal mortality; Hospital information systems; Information systems; Surveillance; Death; Brazil

INTRODUCTION

Maternal mortality (MM) reflects the access to and quality of health services in a country, as it is considered preventable in most situations. It is synonymous with neglect of women’s human rights and lack of attention to sexual and reproductive health¹1. World Health Organization. Trends in maternal mortality 2000 to 2017 [Internet]. Geneva: World Health Organization; 2019. [acessado em 28 abr. 2020]. Disponível em: https://apps.who.int/iris/handle/10665/327596
https://apps.who.int/iris/handle/10665/3... ,²2. Reis LGC, Pepe VLE, Caetano R. Maternidade segura no Brasil: o longo percurso para a efetivação de um direito. Physis Rev Saúde Coletiva 2011; 21(3): 1139-60. https://doi.org/10.1590/S0103-73312011000300020
https://doi.org/10.1590/S0103-7331201100... .

The standard calculation of Maternal Mortality Ratio (MMR) in Brazil uses maternal deaths from the Mortality Information System (SIM) as numerator, fed by the Death Certificate (DC) and corrected by an active search for deaths³3. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Análise de Situação em Saúde. Guia de vigilância epidemiológica do óbito materno [Internet]. Brasília: Ministério da Saúde; 2009. [acessado em 21 abr. 2020]. Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/guia_vigilancia_epidem_obito_materno.pdf
http://bvsms.saude.gov.br/bvs/publicacoe... . Surveillance of deaths of women of childbearing age (WCA), mandatory since 2008⁴, seeks to understand possible failures of the health system by not preventing deaths, in the fight against under-reporting, solving possible failures in the registration of deaths classified as erroneously, cases without a DC, and cases not registered in the SIM³3. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Análise de Situação em Saúde. Guia de vigilância epidemiológica do óbito materno [Internet]. Brasília: Ministério da Saúde; 2009. [acessado em 21 abr. 2020]. Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/guia_vigilancia_epidem_obito_materno.pdf
http://bvsms.saude.gov.br/bvs/publicacoe... ,⁵5. Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Ações Programáticas Estratégicas. Manual dos comitês de mortalidade materna. 3a ed. Brasília: Ministério de Saúde; 2009.,⁶6. Szwarcwald CL, Escalante JJC, Rabello Neto DL, Souza Junior PRB, Victora CG. Estimação da razão de mortalidade Materna no Brasil, 2008-2011. Cad Saúde Pública 2014; 30(suppl): S71-S83. https://doi.org/10.1590/0102-311X00125313
https://doi.org/10.1590/0102-311X0012531... .

There are uncertainties about the MM burden across the world, mainly due to the lack of robust data, precisely in low-income countries where estimates are higher. Over the past few decades, efforts to measure MM have been systematically and globally made. Several initiatives have been undertaken, such as the incorporation of new ways of capturing data on maternal deaths to existing sources, the development of new analytical tools and approaches, and the training of responsible personnel in the countries to correctly interpret data obtained. The choice of one method over another depends on the characteristics of the population being investigated, on data sources and on human and financial resources available to measure deaths. However, studies have shown that these methods have limitations and, whenever possible, the use of official civil records should be extended for a closer determination of maternal deaths and cases of WCA affected by severe obstetric complications⁷7. Mgawadere F, Kana T, van den Broek N. Measuring maternal mortality: a systematic review of methods used to obtain estimates of the maternal mortality ratio (MMR) in low- and middle-income countries. Br Med Bull 2017; 121(1): 121-34. https://doi.org/10.1093/bmb/ldw056
https://doi.org/10.1093/bmb/ldw056... –¹⁰10. Callaghan WM, Mackay AP, Berg CJ. Identification of severe maternal morbidity during delivery hospitalizations, United States, 1991-2003. Am J Obstet Gynecol 2008; 199(2): 133.e1-8. https://doi.org/10.1016/j.ajog.2007.12.020
https://doi.org/10.1016/j.ajog.2007.12.0... .

In this study, we evaluated the use of the Hospital Information System (SIH) as a complementary surveillance tool to the SIM, selecting records of hospital admissions related to pregnancy and the puerperium of WCA. We believe that data from SIH bring additional information to the field. Finally, we calculated the hospital MMR and compared to the MMR calculated using the SIM.

METHODS

Study Design

This is a cross-sectional observational study based on records of hospital admissions of WCA in the SIH, all occurring in 2019, across Brazil. The population sample included women aged 10 to 49 years who had been hospitalized for obstetric causes¹¹11. Cerqueira DRC, Alves PP, Coelho DSC, Reis MVM, Lima AS. Uma análise da base de dados do Sistema de Informação Hospitalar entre 2001 e 2018: dicionário dinâmico, disponibilidade dos dados e aspectos metodológicos para a produção de indicadores sobre violência [Internet]. Rio de Janeiro: IPEA; 2019. [acessado em 01 mai. 2020]. Disponível em: http://www.ipea.gov.br/portal/images/stories/PDFs/livros/livros/191015_Uma_analise_da_base_de_dados_do_sistema_de_informacao.pdf
http://www.ipea.gov.br/portal/images/sto... .

Databases

Open access data were obtained from the Department of Informatics of the Unified Health System (DATASUS), of the Ministry of Health. To compare with the standard calculation, the numerator of the MMR was extracted from the SIM. For the denominator of overall MMR, data were extracted from the Information System on Live Births (SINASC).

Database construction

Admissions of WCA (10–49 years old) were sorted into two groups: admissions for obstetric causes and admissions for other causes.

Maternal Deaths in SIM

We obtained two MMR out of SIM data: 1) overall MMR, which corresponds to the crude MMR as the Ministry of Health (without correction factor); 2) Adapted RMM, with deaths selected from SIM with inclusion criteria similar to those of SIH.

For this, the variable that identifies the health facility (variable “CNES” in SIH and “CODESTAB” in SIM) were used and paired. As the SIH had all obstetric hospitalizations, all values of “CNES” were selected, regardless of the outcome death. Then, we verified which institutions related to obstetric hospitalizations of the SIH were present in the SIM. SIM maternal deaths that did not occur in health facilities listed in the 2019 SIH obstetric admissions were excluded for comparison purposes between both systems. The same criterion for selection of institutions (hospitals and health facilities) was used to select births in the SINASC during 2019, to calculate the number of live births (LB) in hospitals affiliated with SUS, based on obstetric admissions identified in the SIH in the same year by using the variable “CNES” in the SIH and “CODESTAB” in the SINASC.

According to the case selection methodology in both SIH and SIM, there were no missing data.

Statistical Analysis

Categorical variables were compared using the Pearson’s χ² test or the Fisher’s exact test, while continuous variables were described as means (standard deviation) or medians (p25–p75) and compared using the Student’s t test or Wilcoxon-Mann-Whitney’s test, as appropriate. In addition to the nationwide assessment, we also assessed the five macro regions and age categories.

For all analyses, values of p<0.05 were considered significant. Database management and statistical analyses were performed using the Stata-15 software (Statacorp, College Station, Texas, USA).

The study was approved by the Research Ethics Committee of the Teaching and Research Institute of Hospital Sírio Libanês (CAAE 34126820.0.0000.5461/opinion number 4.151.968) on July 13, 2020. The Free Informed Consent Form was not required, as the study used secondary data and researchers had no contact with people/patients.

RESULTS

In 2019, 4,236,387 WCA were hospitalized in SUS-affiliated hospitals in the country. Of these, 2,497,957 (59%) had obstetric causes and 946 (0.04%) had maternal death as outcome. As for criteria agreement (1. diagnoses, 2. procedure, 3. billing), 77% of obstetric hospitalizations and 30% of deaths met all three. Considering at least two of the three criteria, 82% of deaths were identified, while 11% were identified exclusively by diagnoses and 5% exclusively by procedures, as shown in Figures 1 and 2.

Of the 40,485 obstetric hospitalizations and 63 maternal deaths identified by criteria 2 and/or 3, but without diagnoses in Chapter XV, important participations of some diagnoses were observed as cause of hospitalization: Z30 (contraception), with 48.7% of hospitalizations and 12.6% of hospitalizations with death as outcome; P95 (fetal death of unspecified cause), with 13.7% of hospitalizations and 55.5% of hospitalizations with death as outcome; and I42 (cardiomyopathies), with 6.8% of hospitalizations and 4.7% of hospitalizations with death as outcome (Table 1 and Table 1 of supplementary material). Among the 63 deaths, 50 were related only to maternal procedure and 11 to procedure and delivery charge (Figure 2). The two remaining deaths were identified only by delivery charge (I50 heart failure and K65 peritonitis), with death of the pregnant woman and the fetus (Table 1 of supplementary material).

Among the 40,485 admissions, 27,971 met criteria 2 and 3 with 11 maternal deaths. From the point of view of delivery charging, 716 cases were discharge of the mother/postpartum woman with the newborn’s death and 3,859 were discharge of the mother/postpartum woman with fetal death. The P95 code was prevalent: 92.6% (663) of the 716 hospitalizations with newborn death and 97.7% (3,771) of the 3,859 hospitalizations with fetal death (Table 2 of supplementary material).

Hospital Maternal Mortality Ratio, Maternal Mortality Ratio from the Adapted Mortality Information System and Maternal Mortality Ratio from the Total Mortality Information System

The total number of maternal deaths in the SIH amounted to 946 and, in the SIM, following the Ministry of Health rules, 1,576 were recorded in 2019, similar to what was disclosed by the MS/DATASUS¹⁴14. Brasil. Ministério da Saúde. DATASUS. Sistema de Informações sobre Mortalidade. Óbitos de mulheres em idade fértil e óbitos maternos [Internet]. 2019 [acessado em 7 dez 2021]. Disponível em: http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sim/cnv/mat10uf.def
http://tabnet.datasus.gov.br/cgi/deftoht... . However, in order to calculate the total SIM MMR, 1,575 maternal deaths were considered, resulting from the exclusion of the death of a 56-year-old woman who did not meet the inclusion criteria based on age.

Figure 3 shows the step-by-step process for identifying the 1,032 deaths in the SIM (1,024 of Chapter XV and eight of the other Chapters—A34, B20-24, D39.2, E23.0, F53, M83.0) occurred during the pregnancy-puerperium cycle (up to 42 days after end of pregnancy) in SUS and affiliated hospitals.

For the calculation of MMR, the number of LB collected at SINASC in 2019 was 2,849,146, occurring in any location, a number used in the calculation of the total SIM MMR. To calculate the hospital MMR and adapted SIM MMR, the denominator was 2,077,630 LB in hospitals affiliated with the SUS.

Table 2 shows that the difference between hospital MMR and SIM MMR adapted for each 100,000 LB was 4.1 more maternal deaths recorded in SIM compared to SIH (p-value 0.053). The MMR increased with age, regardless of the cause of maternal deaths. The 30–39 age group stands out, with a difference in MMR between both databases (absolute difference 12.3, p=0.008), with greater coverage in the SIM. The MMR by region shows a difference between the databases in the Midwest (p-value 0.011) and in the South (p-value 0.002). The number of deaths and births to calculate the MMR is shown in Table 3 of the supplementary material. Figures 1 and 2 of the supplementary material show the MMR by age and region in graphic format.

Finally, the overall SIM MMR calculated in this study was 55.3 per 100,000 LB (1,575/2,849,146 *100,000 LB). It differs from the Ministry of Health¹⁵15. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Análise em Saúde e Vigilância das Doenças não Transmissíveis. Indicadores de cobertura que utilizam a metodologia do busca ativa: razão de mortalidade materna [Internet]. 2021 [acessado em 10 ago 2021]. Disponível em: http://svs.aids.gov.br/dantps/acesso-a-informacao/acoes-e-programas/busca-ativa/indicadores-de-saude/cobertura/
http://svs.aids.gov.br/dantps/acesso-a-i... RMM of 57.9, corrected for the correction factor.

DISCUSSION

In Brazil, where 98.5% of births take place in hospitals¹⁶16. Leal MC, Szwarcwald CL, Almeida PVB, Aquino EML, Barreto ML, Barros F, et al. Saúde reprodutiva, materna, neonatal e infantil nos 30 anos do Sistema Único de Saúde (SUS). Ciênc Saúde Coletiva 2018; 23(6): 1915-28. https://doi.org/10.1590/1413-81232018236.03942018
https://doi.org/10.1590/1413-81232018236... , the availability of a national hospital database can contribute to the study of MM by extrapolating its reimbursement function, bringing data on 2,497,957 obstetric hospitalizations and 946 maternal deaths in 2019.

Understanding MM with the help of the SIH as complementary to the SIM, being able to provide deaths that would not usually be registered, can be an alternative to revert the current situation of difficult reduction of MMR, especially when the temporality of MMR shows stagnation and growth, as in Brazil¹⁷17. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. A mortalidade materna no Brasil: diferenças regionais e desafios para o alcance da meta do Objetivo do Desenvolvimento Sustentável (ODS) em 2030. In: Brasil. Ministério da Saúde. Saúde Brasil 2019: uma análise da situação de saúde com enfoque nas doenças imunopreveníveis e na imunização [Internet]. Brasília: Ministério da Saúde; 2019. p. 71-94. [acessado em 12 ago. 2020]. Disponível em: https://www.google.com/l?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwj8w56u2e_6AhVfBbkGHY57A_4QFnoECA0QAQ&url=https%3A%2F%2Fbvsms.saude.gov.br%2Fbvs%2Fpublicacoes%2Fsaude_brasil_2019_analise_situacao.pdf&usg=AOvVaw2YGgm5qwJaVZHv6katQDNl
https://www.google.com/l?sa=t&rct=j&q=&e... ,¹⁸18. Motta CT, Moreira MR. O Brasil cumprirá o ODS 3.1 da agenda 2030? Uma análise sobre a mortalidade materna, de 1996 a 2018. Ciênc Saúde Coletiva 2021; 26(1): 4397-409. https://doi.org/10.1590/1413-812320212610.10752021
https://doi.org/10.1590/1413-81232021261... and in the United States¹⁹19. Collier ARY, Molina RL. Maternal mortality in the United States: updates on trends, causes, and solutions. Neoreviews 2019; 20(10): e561-e574. https://doi.org/10.1542/neo.20-10-e561
https://doi.org/10.1542/neo.20-10-e561... ,²⁰20. Darney PD, Nakamura-Pereira M, Regan L, Serur F, Thapa K. Maternal mortality in the United States compared with Ethiopia, Nepal, Brazil, and the United Kingdom: contrasts in Reproductive Health Policies. Obstet Gynecol. 2020; 135(6): 1362-6. https://doi.org/10.1097/AOG.0000000000003870
https://doi.org/10.1097/AOG.000000000000... .

Both maternal mortality and morbidity result from the difficulty or lack of access to medical services, social, economic and demographic conditions that impact the risk of developing complications during and after pregnancy²¹21. Cecatti JG, Costa ML, Haddad SM, Parpinelli MA, Souza JP, Sousa MH, et al. Network for surveillance of severe maternal morbidity: a powerful national collaboration generating data on maternal health outcomes and care. BJOG 2016; 123(6): 946-53. https://doi.org/10.1111/1471-0528.13614
https://doi.org/10.1111/1471-0528.13614... ,²²22. Pacagnella RC, Nakamura-Pereira M, Gomes-Sponholz F, Aguiar RALP, Guerra GVQL, Diniz CSG, et al. Maternal mortality in Brazil: proposals and strategies for its reduction. Rev Bras Ginecol Obstet 2018; 40(9): 501-6. https://doi.org/10.1055/s-0038-1672181
https://doi.org/10.1055/s-0038-1672181... . Studies on severe maternal morbidity demonstrate how the SIH serves to identify near-death cases of WCA, speeding up recognition, compared to studies based on medical records and interviews²³23. Veras TCS, Mathias TAF. Principais causas de internações hospitalares por transtornos maternos. Rev Esc Enferm USP 2014; 48(3): 401-8. https://doi.org/10.1590/S0080-623420140000300003
https://doi.org/10.1590/S0080-6234201400... ,²⁴24. Herdt MCW, Magajewski FRL, Linzmeyer A, Tomazzoni RR, Domingues NP, Domingues MP. Temporal trend of near miss and its regional variations in Brazil from 2010 to 2018. Rev Bras Ginecol Obstet 2021; 43(2): 97-106. https://doi.org/10.1055/s-0040-1719144
https://doi.org/10.1055/s-0040-1719144... .

We identified 40,485 hospitalizations and 63 deaths that would not be recognized as they did not contain maternal patterns among the hospitalization causes. These findings make up 1.6% of all obstetric admissions (2,497,957) and 6.7% of all admissions with death as outcome (946). With the use of procedure and billing criteria, we found incorrect use of diagnosis codes (Table 1 and Table 1 of supplementary material), with a significant presence of codes Z30, I42 and the pediatric code P95. We suggest that the use of contraception codes (Z30) and fetal death (P95) be reassessed for a possible change of code, accompanied by guidance to the person filling out the Hospital Admission Authorization. As for the code for cardiomyopathies (I42), we suggest a more in-depth study on its use. The use and correct completion of billing variables can help in investigations of fetal and perinatal death by exposing the hospital trajectory of the WCA (Table 1 of supplementary material).

The hospital MMR obtained in this study was 45.5 (95% confidence interval [CI] 42.7–48.5) per 100,000 LB in 2019, which reflects the difficulty of reaching a maximum MMR of 30 by 2030, according to the Sustainable Development Goals (SDG)¹⁷17. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. A mortalidade materna no Brasil: diferenças regionais e desafios para o alcance da meta do Objetivo do Desenvolvimento Sustentável (ODS) em 2030. In: Brasil. Ministério da Saúde. Saúde Brasil 2019: uma análise da situação de saúde com enfoque nas doenças imunopreveníveis e na imunização [Internet]. Brasília: Ministério da Saúde; 2019. p. 71-94. [acessado em 12 ago. 2020]. Disponível em: https://www.google.com/l?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwj8w56u2e_6AhVfBbkGHY57A_4QFnoECA0QAQ&url=https%3A%2F%2Fbvsms.saude.gov.br%2Fbvs%2Fpublicacoes%2Fsaude_brasil_2019_analise_situacao.pdf&usg=AOvVaw2YGgm5qwJaVZHv6katQDNl
https://www.google.com/l?sa=t&rct=j&q=&e... .

When we compared maternal deaths from SIM adapted MMR (n=1,032), 92% were also found in the SIH (n=946), with the limitation of assessing aggregated data and not necessarily being the same women in both databases. Our findings comparing the regions were interesting, given that sometimes the MMR was higher in the SIM, sometimes in the SIH. Regions where the SIM adapted MMR was greater than that estimated by the SIH could suggest that the investigation of maternal deaths has been carried out more effectively, increasing deaths in the SIM after review. This is what we assume to have happened in the South and Midwest MMR. According to a study¹⁷17. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. A mortalidade materna no Brasil: diferenças regionais e desafios para o alcance da meta do Objetivo do Desenvolvimento Sustentável (ODS) em 2030. In: Brasil. Ministério da Saúde. Saúde Brasil 2019: uma análise da situação de saúde com enfoque nas doenças imunopreveníveis e na imunização [Internet]. Brasília: Ministério da Saúde; 2019. p. 71-94. [acessado em 12 ago. 2020]. Disponível em: https://www.google.com/l?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwj8w56u2e_6AhVfBbkGHY57A_4QFnoECA0QAQ&url=https%3A%2F%2Fbvsms.saude.gov.br%2Fbvs%2Fpublicacoes%2Fsaude_brasil_2019_analise_situacao.pdf&usg=AOvVaw2YGgm5qwJaVZHv6katQDNl
https://www.google.com/l?sa=t&rct=j&q=&e... , the regions with the highest percentages of deaths of WCA investigated in 2017 were the South, followed by the Midwest and Southeast. The opposite occurred in the Northeast, where we found more deaths in the SIH than in the adapted SIM. Although it is an uncertain estimate (absolute difference 3.9, 95%CI -3.8−11.7 per 100,000 LB), this finding can be explored in other years and, upon confirmation, be investigated.

Another possible explanation for the difference could be related to hospitals with mixed obstetric beds, with part of the beds linked to SUS and part of beds being supplementary/private. As one of the selection criteria for comparable maternal deaths of SIM and SIH came from the hospitals where all obstetric admissions of the SIH occurred, there may have been a selection of maternal deaths in the SIM in a health establishment common to both bases, but in beds not affiliated with SUS and, therefore, not present in the SIH database.

Exposing the known increased risk of MM with advancing age, the hospital MMR of the age group of 40–49 years was three times greater than the overall MMR of the SIH and four times greater than the age group of 10–19 years, showing that the MMR of women over 40 years old still remains high, even though the literature points to significant reductions in the MMR of women aged 40–49 years in Brazil from 1996 to 2018^18,25.

We reinforce the importance of training in proper filling out of the Hospital Admission Authorization, normally carried out by an administrative professional who is not trained to extract data from medical records, aiming at billing and reimbursement by the SUS, often making the diagnosis and procedure compatible to avoid reimbursement glosses²⁷27. Bittencourt SA, Bastos Camacho LA, Leal MC. O Sistema de Informação Hospitalar e sua aplicação na saúde coletiva. Cad Saúde Pública 2006; 22(1): 19-30. https://doi.org/10.1590/s0102-311x2006000100003
https://doi.org/10.1590/s0102-311x200600... ,²⁸28. Bittencourt SA, Camacho LAB, Leal MC. A qualidade da informação sobre o parto no Sistema de Informações Hospitalares no Município do Rio de Janeiro, Brasil, 1999 a 2001. Cad Saúde Pública 2008; 24(6): 1344-54. https://doi.org/10.1590/S0102-311X2008000600015
https://doi.org/10.1590/S0102-311X200800... .

The unit of analysis being the Hospital Admission Authorization is a limitation. Without access to nominal data, possible records of rehospitalization of the same patient were not recognized, which we assume occurs mainly in postpartum hospitalizations. Another limitation is the possible risk of information bias inherent in the use of secondary data.

One limitation of this study was the failure to stratify the calculation of the SIH and SIM MMR by race/color, given their relevance in exposing maternal health racial inequalities. The inherent complexity of the topic includes missing data that are unlikely to be distributed completely by chance²⁹29. Gebregziabher M, Zhao Y, Axon N, Gilbert GE, Echols C, Egede LE. Lessons learned in dealing with missing race data: an empirical investigation. J Biomet Biostat 2012; 3(3): 138. https://doi.org/10.4172/2155-6180.1000138
https://doi.org/10.4172/2155-6180.100013... .

Traditionally, the measurement of maternal deaths in health databases uses the ICD-10 codes. This study identified a larger contingent of hospitalizations and deaths with the inclusion of variables procedures performed and delivery charges from the SIH. Although there are differences between hospital MMR and adapted SIM MMR, the use of the SIH as a complementary information system can be valid in research on maternal mortality and morbidity.

References

Publication Dates

History