Integrated k-means clustering with data envelopment analysis of public hospital efficiency

2019 ◽  
Vol 23 (3) ◽  
pp. 325-338 ◽  
Author(s):  
Songul Cinaroglu
2021 ◽  
Vol 10 (04) ◽  
pp. 258-268
Author(s):  
Pantri Widyastuti ◽  
Atik Nurwahyuni

Dalam sistem kesehatan yang berkembang saat ini, efisiensi merupakan hal yang utama. Pengukuran efisiensi bermanfaat untuk pemerintah maupun swasta untuk dapat mengambil keputusan yang berhubungan dengan tinggi rendahnya biaya perawatan di rumah sakit. Penelitian ini bertujuan untuk mengkaji metode Data Envelopment Analysis (DEA) yang digunakan dalam berbagai penelitian dalam pengukuran efisiensi rumah sakit. Desain penelitian yang digunakan adalah dengan sistematic review dengan metode PRISMA tanpa meta analisis. Sumber data didapatkan dari Proquest, Sciencedirect dan Pubmed pada tahun 2019 hingga 2020. Pencarian data dilakukan pada bulan Oktober 2020 dengan kata kunci Hospital Efficiency dan Data Envelopment Analysis. Hasilnya adalah penilaian efisiensi rumah sakit menggunakan metode DEA lebih banyak dilakukan dengan analisa dua tahap menggunakan tobit regression atau truncated regression. Perhitungan index malmquist juga banyak digunakan setelah perhitungan DEA dilakukan untuk melihat efisiensi rumah sakit dalam periode waktu tertentu.


2021 ◽  
Vol 10 (1) ◽  
pp. 1-15
Author(s):  
Nokky Farra Fazria ◽  
Inge Dhamanti

The selection of input and output variables usually pose a problem when carrying out efficiency assessment in hospitals. Data Envelopment Analysis (DEA) is an instrument that is used to calculate the efficiency of a hospital using some inputs and outputs. Therefore, this study aims to identify the most frequently used hospital inputs and outputs from an existing paper,, in order to assist the hospital management staffs in choosing the relevant variables that can represent available inputs, are easily accessible, and need improvement. It was conducted using keywords such as “hospital efficiency” and “DEA for hospital” to search for peer-reviewed journals in the PubMed and Open Knowledge Maps from the year 2014-2020. From, the 586 articles, 54 samples were obtained from the about 5-3504 hospitals which were analyzed from 23 countries. The results showed that, the five most used inputs were the number of beds, medical personnel, non-medical staff,  medical technician staff and operational costs, while the most used outputs were number of inpatients, surgeries, emergency visits, outpatient service, and days of inpatients. These variables are often used for accessing the efficiency of hospitals in the DEA application.


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