Hasil Pencarian  ::  Simpan CSV :: Kembali

"There is a current worldwide outbreak of new type of coronovirus (COVID-19) which originated from wuhan in china and has now spread to 199 countries. Governments, business institutions, and consumers are under increased pressure to stop the outbreak spreading to global health emergency."

"Dukungan keluarga dan motivasi dalam perawatan diabetes dapat meningkatkan pemanfaatan pelayanan kesehatan bagi diabetisi tipe 2 dalam upaya mencegah komplikasi diabetes dan meningkatkan kualitas hidup diabetisi. Penelitian ini betujuan untuk mengetahui hubungan karakteristik, dukungan keluarga, dan motivasi diabetisi tipe 2 dengan pemanfaatan pelayanan kesehatan. Penelitian ini menggunakan deskriptif analitik dengan pendekatan Cross-Sectional. Sampel penelitian berjumlah 110 responden yang diambil secara proporsional random sampling. Analisa data dilakukan dengan menggunakan Chi-Square dan regresi logistik berganda. Hasil penelitian menunjukkan ada hubungan dukungan penghargaan keluarga dan motivasi intrinsik dengan pemanfaatan pelayanan kesehatan p value.

---

Family Support and motivation treatment in diabetes patients will improve health services utilization. It aims to prevent diabetes complications and improve the diabetes patients quality of life. This study aimed to investigate the Relationship between patients characteristics, family support and motivation in patients with diabetes type 2 with health services utilization. This study used cross sectional with descriptive analytical approach with 110 respondents Which choosen by proportional random sampling. Analysis result using chi square and multiple logistic regression showed relationship between family reinforcement support and Intrinsic motivation with health services utilization p value."

"Periode neonatal bayi usia 0-28 hari dalam kelangsungan hidup anak merupakan periode yang sangat rentan. Penelitian ini bertujuan untuk mengetahui hubungan antara cakupan pelayanan kesehatan yang terdiri atas kunjungan antenatal care lengkap K4, persalinan di fasilitas kesehatan PF, kunjungan neonatal pertama KN1, kunjungan antenatal care pertama K1, kunjungan neonatal lengkap KN Lengkap, kelas ibu hamil, Program Perencanaan Persalinan dan Pencegahan Komplikasi P4K, dan jumlah puskesmas mampu melaksanakan Pelayanan Obstetri dan Neonatal Emergensi Dasar PONED dengan angka kematian neonatal AKN. Penelitian ini menggunakan desain studi ekologi dengan unit analisis agregat kabupaten/kota se Jawa-Bali tahun 2016. Data yang digunakan adalah data sekunder yang bersumber dari data Laporan Feedback Kesga Kemenkes RI. Hasil univariat menunjukkan AKN Jawa-Bali sebesar 5,98 per 1000 kelahiran hidup. Rata-rata persentase cakupan K1, K4, Pf, KN1, KN lengkap, Kelas Ibu Hamil, dan P4K sudah lebih dari 90, rata-rata persentase Puskesmas mampu PONED 32,72. Hasil bivariat menunjukkan korelasi antara penurunan AKN dengan P4K r=-0,177, p = 0,064. Kesimpulannya, faktor P4K berkorelasi dengan penurunan AKN.

---

Neonatal period infant age 0 28 days in child survival is a very vulnerable period. This study aims to determine the relationship between coverage of health services consisting of complete antenatal care visit K4, delivery at health facility Pf, first neonatal visit KN1, first antenatal care visit K1, complete neonatal visits, maternity education program, birth planning and complication prevention program P4K, and Puskesmas which able to do Basic Essential Neonatus Obstetrics Service PONED with neonatal mortality rate NMR. This study uses ecological study design with aggregate analysis unit of districts cities in Java Bali in 2016. The data used are secondary data sourced from the report of the Directorate of Family Health, Health Ministry, Republic of Indonesia. The univariate result shows Java Bali NMR is 5.98 per 1000 live births. The average percentage of K1, K4, Pf, KN1, complete neonatal visits, maternity education program, and P4K have been more than 90, the average percentage of Puskesmas able to do PONED is 32,72. Bivariate results show the correlation between decreasing of AKN with Program of Birth Planning and Prevention of Complication P4K r 0,177, p 0,064. In conclusion, the P4K factor is correlated with the decrease in AKN."

"Latar belakang: Kemudahan akses pelayanan kesehatan bagi peserta Jaminan Kesehatan Nasional (JKN) merupakan salah satu upaya untuk meningkatkan derajat kesehatan penduduk Indonesia. Kemudahan akses ini terwujud dengan bertambahnya fasilitas kesehatan yang melayani peserta JKN. Indikator kemudahan akses terlihat dari bertambahnya jumlah peserta yang berkunjung ke fasilitas kesehatan baik di tingkat pelayanan rawat jalan maupun rawat inap. Kunjungan peserta JKN per 1.000 penduduk dikenal dengan isitilah rate sebagai salah satu indikator utilisasi pelayanan kesehatan untuk menjaga kesinambungan program JKN. Tujuan: penelitian ini bertujuan menganalisis faktor yang mempengaruhi rate rawat jalan tingkat lanjutan (RJTL) maupun rawat inap inap tingkat lanjutan (RITL) dan pemodelan prediksi rate RJTL dan rate RITL. Data yang digunakan berasal dari database BPJS Kesehatan dan Survei Sosial Ekonomi Nasional (SUSENAS) tahun 2016 – 2019 yang diolah berdasarkan faktor predisposing, faktor enabling, dan faktor need dimana semua data digunakan dalam penelitian atau total sampling. Metode: analisis data panel dinamis yang ditujukan untuk membuat model prediksi rate RJTL dan rate RITL. Hasil: model prediksi yang digunakan pada rate RJTL dan rate RITL adalah estimator First Difference Generalized Method of Moment (FDGMM). Kesimpulan: rate RJTL dipengaruhi oleh variabel nilai tagihan klaim dibayar per kunjungan RJTL; jumlah rumah sakit kelas A, B, C, D; jumlah peserta pria; jumlah peserta berusia > 50 tahun; jumlah peserta dengan jumlah anggota keluarga > 3 orang; jumlah peserta berpengeluaran di bawah garis kemiskinan; jumlah peserta dengan penyakit tidak menular; rasio fragmentasi; rasio rujukan; dan jumlah peserta berpendidikan SMP. Sedangkan, rate RITL dipengaruhi oleh variabel nilai tagihan klaim dibayar per kunjungan RITL; jumlah rumah sakit kelas A, B, C, D; jumlah peserta pria; jumlah peserta berusia > 50 tahun; jumlah peserta dengan jumlah anggota keluarga > 3 orang; rate readmisi; jumlah peserta berpendidikan SMP; dan jumlah peserta berpendidikan Perguruan Tinggi. Saran: hasil penelitian menyarankan agar Pemerintah Daerah turut mendukung pemenuhan sarana prasarana pelayanan kesehatan agar masyarakat dapat menjangkau pelayanan kesehatan dengan mudah, mengelola perencanaan penambahan rumah sakit sesuai kebutuhan; Kementerian Kesehatan dapat memberikan regulasi terkait pemenuhan dan pemerataan fasilitas kesehatan maupun tenaga medis, terutama pada daerah dengan keadaan geografis yang sulit; BPJS Kesehatan dapat menggunakan model prediksi rate RJTL dan rate RITL sebagai alat bantu dalam menilai kebutuhan penambahan kerjasama dengan rumah sakit. Peneliti selanjutnya dapat melakukan penelitian dengan faktor utilisasi yang lebih luas dan lengkap serta melakukan kajian yang lebih mendalam pada satu wilayah tertentu dengan mempertimbangkan pengaruh aspek geografis, seperti jarak antar fasilitas kesehatan, luas wilayah dan kondisi akses ke fasilitas kesehatan.

---

Background: easy access to health services for participants of the National Health Insurance (JKN) is one of the efforts to improve the health status of the Indonesian population. This accessibility is achieved through an increase in health facilities serving JKN participants. The indicator of accessibility can be observed from the rising number of participants visiting health facilities, both at the outpatient and inpatient levels. The rate of visits by JKN participants per 1.000 population is considered an indicator of health service utilization, which contributes to the continuity of the JKN program. Objective: this study aims to analyze the factors that influence the advanced level of outpatient care (RJTL) and inpatient care (RITL) and to model the prediction of RJTL rates and RITL rates. The data used is derived from the BPJS Kesehatan database and the 2016-2019 National Socioeconomic Survey (SUSENAS), which are processed based on predisposing factors, enabling factors, and need factors. All data is utilized in the research, employing total sampling. Method: dynamic panel data analysis is employed to develop prediction models for RJTL rates and RITL rates. Results: the prediction model used for the RJTL rate and RITL rate is the First Difference Generalized Method of Moment (FDGMM) estimator. Conclusion: RJTL rate is influenced by several variables: value of claims bills paid per RJTL visit, number of class A, B, C, and D hospitals, number of male participants, number of participants aged over 50 years, number of participants with more than 3 family members, number of participants with expenditures below the poverty line, number of participants with non-communicable diseases, fragmentation ratio, referral ratio, and number of participants with junior high school education. On the other hand, the RITL rate is affected by value of claim bills paid per RITL visit, number of class A, B, C, and D hospitals, number of male participants, number of participants aged over 50 years, number of participants with more than 3 family members, readmission rate, number of participants with junior high school education, and number of participants with university education. Recommendations: the results of this study suggest that the Regional Government should also support the fulfillment of health service infrastructure so that partisipant can reach health services easily, manage plans for adding hospitals as needed; The Ministry of Health can provide regulations regarding the fulfillment and equity of health facilities and medical personnel, especially in areas with difficult geographical conditions; BPJS Kesehatan can use RJTL rate prediction model and RITL rate as a tool in assessing the need for additional collaboration with hospitals. Future researchers can conduct research with broader and more complete utilization factors and conduct more in-depth studies in a particular area by considering the influence of geographical aspects, such as the distance between health facilities, area size and conditions of access to health facilities."

"Throughout history, humanity has been plagued by a myriad of humanitarian crises that seemingly take the form of perpetual human suffering. Today, approximately 125,000,000 people require humanitarian assistance as the result of famine, war, geopolitical conflict, and natural disasters. A core component of this suffering is afflictions related to human health, where disturbances strain or overwhelm the existing healthcare infrastructure to create the conditions for an increase in morbidities and co-morbidities. One of the more startling elements is the loss of life to preventable medical conditions that were not properly treated or even diagnosed in the field, and is often due to the limited interventional capacity that medical teams and humanitarian practitioners have in these scenarios. These individuals are often hindered by medical equipment deficiencies or devices not meant to function in austere conditions. The development of highly versatile, feasible, and cost-effective medical devices and technologies that can be deployed in the field is essential to enhancing medical care in unconventional settings. In this book we examine the nature of the creative problem-solving paradigm, and dissect the intersection of frugal, disruptive, open, and reverse innovation processes in advancing humanitarian medicine. Specifically, we examine the feasible deployment of these devices and technologies in unconventional environments not only by humanitarian aid and disaster relief agencies, but also by crisis-affected communities themselves. The challenge is complex, but the financial support and technical development of innovative solutions for the delivery of humanitarian aid is a process in which everyone is a stakeholder."