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Background- Maternal mortality is a preventable cause of death in low‑ and middle‑income economies. The enormous physiological drive and the associated physiological adaptations in pregnancy delay the recognition of early warning signs of sickness.Unrecognized deterioration of clinical status leads to worsening of illness in pregnant women. Early detection of high risk mothers reduces maternal morbidity and mortality. Through global and national programmes aim at reducing the maternal morbidity and mortality the rate in developing countries remains same. One of the important reason for same is inability of screening high risk mothers and early transfer to higher centre.
Objective-Inpresentstudyweaimtostudy and evaluate Maternal Morbidity Score (MMS) app as a new Screening Tool to predict Peripartum Maternal Morbidity.
Methodology - Anobservational study of peripartum women beyond the 28 weeks of gestation. Purposive sampling technique will be used to collect data. Collect the data through using MMS app and also collect data from MEOWS chart .According to scoring system provide the intervention to the peripartum woman. Comparing with the both such as MEOWS and MMS app.
Expected Outcomes - Early identification of abnormal parameter will be significantly help to detect high risk factors in all trimesters and will get immediate management during perinatal period.MMS tool willbeuseful for reducing maternal morbidity.
Conclusion:Early identification of high risk factor will help to reduce maternal morbidity in order to improve the health outcome of antenatal and intranatal period.