Efektivitas Penerapan Modified Early Obstetric Warning System (MEOWS) untuk Menurunkan Morbiditas pada Ibu Postpartum
DOI:
https://doi.org/10.62354/jurnalmedicare.v4i2.188Keywords:
MEOWS, morbidity, postpartum mothersAbstract
Based on the 2020 Population Census, Indonesia's maternal mortality rate (MMR) reached 189 per 100,000 live births, ranking third highest in ASEAN. The high MMR is closely related to increased maternal morbidity. Early detection is a key strategy to reduce morbidity, one of which is by using the Modified Early Obstetric Warning System (MEOWS). This tool is effective in predicting morbidity risk and the length of postpartum care. This study is a literature review analyzing the effectiveness of MEOWS in reducing postpartum maternal morbidity. Articles were retrieved from electronic databases including PubMed, Sage Journal, Science Direct, and Proquest using the keywords “postpartum,” “modified early obstetric warning system,” and “maternal morbidity.” Out of 665 articles found, 6 were selected based on inclusion and exclusion criteria. The review results showed that MEOWS is effective in predicting postpartum maternal morbidity, with sensitivity reaching up to 99.3% and specificity of 93.5%.
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Cahyani, D. D., Priyanto, H., An, A. D., & Supriyatiningsih. (2024). Sensitivity and Specificity of the Modified Early Obstetric Warning Score (MEOWS) and Maternal Early Warning Criteria (MEWC) for Predicting Maternal Morbidity: A Retrospective Cohort Study in Pregnant Women with COVID-19. Indonesian Journal of Obstetrics and Gynecology. https://doi.org/10.32771/inajog.v12i4.2108
Cole, M. F. (2014). A Modified Early Obstetric Warning System. British Journal of Midwifery, 22(12), 862–868. https://doi.org/10.12968/bjom.2014.22.12.862
Desti Cahyani, D., & Permana, I. (2022). Comparison of Modified Early Obstetric Warning Score (MEOWS) and Maternal Early Warning Criteria (MEWC) as Predictor of Morbidity and Mortality of Pregnant Women With COVID-19 in Bantul Hospital. KESANS : International Journal of Health and Science. https://doi.org/10.54543/kesans.v2i1.117
Gadhavi, D. P., Sharma, D. R., & Jain, D. T. (2024). Evaluation of Modified Early Obstetrics Warning System ( MEOWS ): As a Predictor of Maternal Morbidity. Vidhyayana Ejournal, 9(5), 1–25.
Gangwar, P., Kansal, R., Agarwal, G., Bansal, I., Resident, D. P., Professor, A., … Bansal Associate Professor, I. (2023). A Comparison of Various Obstetric Early Warning Systems to Predict Maternal Morbidity And Mortality. International Journal of Life Sciences, 12(3), 846–854.
Helen M. Ryan, MBBCh BAO, M., Meghan A. Jones, M. Bc., Beth A. Payne, P., Sumedha Sharma, M., Anna M. Hutfield, R., Tang Lee, Ms., … Peter von Dadelszen, MBChB, Dp. (2017). Validating the Performance of the Modified Early Obstetric Warning System Multivariable Model to Predict Maternal Intensive Care Unit Admission.pdf. J Obstet Gynaecol Can, 39(9), 728–733.
Naqvi, R. A., Batool, I., Parveen, S., & Iram, N. (2025). Predicting Maternal Morbidity in Peripartum Period : Validity of Modified Early Obstetric Warning System. Life & Science, 6(1), 65–70. https://doi.org/http://doi.org/10.37185/LnS.1.1.564
Pezdirc, N., Pintaric, T. S., & Lucovnik, M. (2025). Obstetric-Specific Compared to General Early Warning System for Predicting Severe Post Partum Maternal Morbidity. Biomolecules and Biomedicine, 25, 1517–1521. https://doi.org/10.17305/bb.2024.11679
Pristiandaru, D. L. (2024). Angka Kematian Ibu di Indonesia Masih Tinggi. Retrieved January 2, 2025, from https://lestari.kompas.com/read/2024/02/13/140000986/angka-kematian-ibu-di-indonesia-masih-tinggi#google_vignette
Putri, R. A. D., & Hutagaol, I. E. B. (2023). The Use of Maternal Early Obstetric Warning Score (MEOWS) as a Tool to Predict Treatment Needs in the Intensive Care Unit in Severe Preeclampsia Patients. Indonesian Journal of Obstetrics and Gynecology, 11(4), 215–219. https://doi.org/10.32771/inajog.v11i4.1920
Singhal, S., Acharya, N., Madaan, S., Mohammad, S., & Acharya, S. (2022). Use of the Modified Early Obstetric Warning System Chart as a Predictor of Peri-Partum Obstetric Morbidity in a Rural Teaching Institute: a Two-Year Cross-Sectional Study. Journal of Family Medicine and Primary Care. https://doi.org/10.4103/jfmpc.jfmpc_320_22
Sulistianto, S., Siswishanto, R., & Attamimi, A. (2023). Manfaat Maternal Early Obstetric Warning Score (MEOWS) dalam Memprediksi Lama Perawatan pada Pasien Preeklamsia Berat di RSUP Dr. Sardjito. Jurnal Kesehatan Reproduksi. https://doi.org/10.22146/jkr.77590
Supriyanta, B., & Setiawan, B. (2021). Sensitivitas, Spesifisitas, Nilai Prediksi Positif, Nilai Prediksi Negatif dan Akurasi Metode Lateral Flow Immuno Assay (LFIA) dengan Mikroskopis untuk Diagnosis Gonore. Puinovakesmas, 2(2), 40–44. https://doi.org/10.29238/puinova.v2i2.1170
Tuyishime, E., Ingabire, H., Mvukiyehe, J. P., Durieux, M., & Twagirumugabe, T. (2020). Implementing the Risk Identification (RI) and Modified Early Obstetric Warning Signs (MEOWS) tool in District Hospitals in Rwanda: A cross-sectional study. BMC Pregnancy and Childbirth. https://doi.org/10.1186/s12884-020-03187-1
Xu, Y., Zhu, S., Song, H., Lian, X., Zeng, M., He, J., … Xiao, F. (2022). A New Modified Obstetric Early Warning Score for Prognostication of Severe Maternal Morbidity. BMC Pregnancy and Childbirth, 22(1), 1–8. https://doi.org/10.1186/s12884-022-05216-7
Yadav, P., & Sinha, R. (2023). Validating the Performance of Modified Early Obstetrics Warning Score (MEOWS) for Prediction of Obstetrics Morbidity: A Prospective Observational Study in a Tertiary Care Institute in East India. Journal of Obstetrics and Gynecology of India. https://doi.org/10.1007/s13224-023-01855-8
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