Background The public hospital network in Morocco plays a crucial role in providing healthcare services. However, this network faces challenges in terms of technical efficiency in healthcare management. Objectives This study aimed to assess the technical efficiency of the public hospital network in Morocco. Methods This article compares the efficiency of 77 public hospital networks from 2017 to 2020. Data were collected from the Directorate of Planning and Financial Resources (DPFR) of the Health Ministry Marocco. The Data Envelopment Analysis (DEA) method was employed, using three inputs (Hospital, Physician and Paramedical) and four outputs (Functional capacity, Hospitalization days and Admission). Additionally, the Malmquist index (MI) is utilized to analyse the factors of production, and peer modelling is incorporated to address hospital inefficiency. Results The average technical efficiency of public hospital networks under the CRS hypothesis from 2017 to 2020 is 0.697 (71% of DMUs have a score lower than 1), indicating that these networks need to minimize their inputs by approximately 30.3%. The Malmquist index reveals a decline in productivity gain from 2017/2018 (score of 0.980) followed by improvement in 2018/2019 (score of 1.163). In terms of peer modelling, 72.7% of the DMUs should emulate the most effective DMUs beginning in 2020, whereas the lowest score was observed in 2019. Conclusion These findings highlight the need for the public hospital network in Morocco to enhance the effective and efficient utilization of inputs, such as the number of hospitals and medical and paramedical staff, to produce the same outputs, including the number of surgical procedures, hospitalization days, admissions, and functional capacity.

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