Evaluating the Effectiveness of Maternal, Neonatal, and Child Healthcare in Moroccan Hospitals and SDG 3: Using Two-Stage Data Envelopment Analysis and Tobit Regression DOI
Youssef Er-Rays,

Meriem M’dioud

Evaluation Review, Journal Year: 2024, Volume and Issue: unknown

Published: July 20, 2024

Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly promoting wellbeing. However, maternal, services Moroccan public hospitals face challenges, concerning mortality rates inefficient resource allocation, which hinder optimal outcomes. This study aimed to evaluate operational effectiveness 76 neonatal networks (MNCSN) within hospitals. Using Data Envelopment Analysis (DEA), we assessed technical efficiency (TE) employing both Variable Returns Scale for inputs (VRS-I) outputs (VRS-O) orientation. Additionally, Tobit method (TM) was utilized explore factors influencing inefficiency, with hospital, doctor, paramedical staff considered as inputs, admissions, cesarean interventions, functional capacity, hospitalization days outputs. Our findings revealed that VRS-I exhibited a higher average TE score 0.76 compared VRS-O (0.23). Notably, Casablanca-Anfa MNCSN received highest referrals (30) under VRS-I, followed by Khemisset (24). In contrast, VRS-O, Ben Msick, Rabat, Mediouna each had three peers, 71, 22, 17 references, respectively. Moreover, Malmquist Index indicated 7.7% increase productivity over 9-year period, while decreased 8.7%. Furthermore, doctors bed capacity model 0.01, sections. underscores imperative policymakers strategically prioritize input enhance ensure healthcare

Language: Английский

Evaluating the Effectiveness of Maternal, Neonatal, and Child Healthcare in Moroccan Hospitals and SDG 3: Using Two-Stage Data Envelopment Analysis and Tobit Regression DOI
Youssef Er-Rays,

Meriem M’dioud

Evaluation Review, Journal Year: 2024, Volume and Issue: unknown

Published: July 20, 2024

Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly promoting wellbeing. However, maternal, services Moroccan public hospitals face challenges, concerning mortality rates inefficient resource allocation, which hinder optimal outcomes. This study aimed to evaluate operational effectiveness 76 neonatal networks (MNCSN) within hospitals. Using Data Envelopment Analysis (DEA), we assessed technical efficiency (TE) employing both Variable Returns Scale for inputs (VRS-I) outputs (VRS-O) orientation. Additionally, Tobit method (TM) was utilized explore factors influencing inefficiency, with hospital, doctor, paramedical staff considered as inputs, admissions, cesarean interventions, functional capacity, hospitalization days outputs. Our findings revealed that VRS-I exhibited a higher average TE score 0.76 compared VRS-O (0.23). Notably, Casablanca-Anfa MNCSN received highest referrals (30) under VRS-I, followed by Khemisset (24). In contrast, VRS-O, Ben Msick, Rabat, Mediouna each had three peers, 71, 22, 17 references, respectively. Moreover, Malmquist Index indicated 7.7% increase productivity over 9-year period, while decreased 8.7%. Furthermore, doctors bed capacity model 0.01, sections. underscores imperative policymakers strategically prioritize input enhance ensure healthcare

Language: Английский

Citations

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