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All Journal Jurnal Kesehatan Masyarakat (JKM) CENDEKIA UTAMA Proceeding of International Conference Health, Science And Technology (ICOHETECH)
Siti Musyarofah
STIKES Kendal
Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Public Health

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STUDI KUALITIATIF DETERMINAN BALITA STUNTING DI KELURAHAN BANDENGAN KECAMATAN KOTA KENDAL Siti Musyarofah
JKM (Jurnal Kesehatan Masyarakat) Cendekia Utama Vol 10, No 1 (2022): JKM (Jurnal Kesehatan Masyarakat) Cendekia Utama
Publisher : STIKES Cendekia Utama Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31596/jkm.v10i1.1026

Abstract

Stunting adalah kondisi tinggi badan seseorang yang kurang dari normal berdasarkan usia dan jenis kelamin. Determinan stunting meliputi faktor genetik, status ekonomi, jarak kelahiran, riwayat BBLR, anemia pada ibu, hygiene dan sanitasi lingkungan. Kasus gizi buruk dan stunting di wilayah Pantai Utara (Pantura) Barat, Jawa Tengah masih tinggi. Kejadian stunting di Kelurahan Bandengan cukup tinggi. Tujuan penelitian yaitu untuk mengetahui deskripsi determinan stunting di Kelurahan Bandengan. Desain penelitian adalah observasional dengan  pendekatan cross sectional dan dilakukan dengan metode kualitatif, dengan teknik pengumpulan data dilakukan melalui pengamatan dan wawancara mendalam. Informan dipilih secara purposive sampling.  Hasil penelitian menunjukkan bahwa determinan stunting meliputi faktor ekonomi, kesehatan ibu saat hamil, ASI tidak eksklusif, pemberian MP ASI (keterlambatan/terlalu dini), picky eater,  ayah perokok, dan lingkungan. Determinan Stunting lebih dari satu faktor (multifaktor). Faktor ekonomi merupakan faktor awal dari determinan stunting.
Disparities in hospital cost and INA-CBGs tariff with unit cost analysis of inpatient services Warsi Maryati; Muhammad Faiz Othman; Siti Musyarofah; Puguh Ika Listyorini; Fhahrul Dwi Aryanti; Miftakhul Jannah
Proceeding of International Conference on Science, Health, And Technology 2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.723 KB) | DOI: 10.47701/icohetech.v1i1.1097

Abstract

The National Health Insurance Program, a form of health insurance that has been implemented since 2014, which uses the Indonesian Case Based Groups (INA-CBGs) system. The implementation of this system ensures that patients get good service and hospitals get standard tariff. The intended tariff is in the form of a package which includes all components of hospital costs. This study aims to determine the relationship between the unit cost of all health service cost components and the INA-CBGs tariff and how the gap is. The research sample was taken from the INA-CBGs claim document in the second quarter of 2020 as many as 4,833. Data were analyzed using linear regression to find a relationship between hospital health service costs and the INA-CBGs tariff. Hospital service costs are calculated based on unit cost analysis. The average unit cost of laboratory was IDR 853,500 (7.91%), radiology IDR 366,198 (3.39%), treatment IDR 2,031,850 (18.82%), Examination IDR 4,205,745 (38.95%), Consumables IDR 345,092 (3.17%), and Drugs IDR 3,022,694 (27.76%). The results of the analysis showed Laboratory (b = 1.639; 95% CI = 1.177 to 2.100; p <0.001), Treatment (b = 0.915; 95% CI = 0.852 to 0.978; p <0.001), Examination and Accommodation (b = 1.211; 95% CI = 1.138 to 1.285; p <0.001), and Drug (b = 0.015; 95% CI = 0.007 to 0.024; p <0.001) had a significant relationship with the INA-CBGs tariff. Other variables such as Radiology (b = -0.141; 95% CI = -0.629 to 0.347; p <0.001) and Consumable Costs (b = -0.343; 95% CI = -696 to 0.009; p <0.001) had no significant relationship with INA-CBGs Tariff. However, all cost components have a significant effect (p <0.001) of 42.7% on the INA-CBG tariff with a strong influence category (R = 0.654). Hospitals must be wiser in managing finances with the INA-CBGs pattern, because the tariff may look small because there are some treatment that are not cost effective or there are still unnecessary treatment for patients taking a large portion of the cost of the package.
Co-Authors Fhahrul Dwi Aryanti Maryati, Warsi Miftakhul Jannah Muhammad Faiz Othman Puguh Ika Listyorini