41 research outputs found

    Sistem Pembayaran Mixed Method INA-CBGs dan Global Budget di Rumah Sakit: Tahap 1 Uji Coba Mixed Method INA-CBGs-Global Budget di Indonesia

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    AbstrakTidak ada sistem pembayaran pelayanan kesehatan yang sempurna dalam penerapannya termasuk sistem pembayaran DRG (Diagnosis-Related Groups) yang lebih dikenal dengan nama INA-CBGs (Indonesia Case-Based Groups) di Indonesia. Beberapa negara yang mengadopsi DRG telah menerapkan kebijakan pembayaran mixed method DRG-Global Budget dengan variasi implementasinya demi menjaga kesinambungan sistem jaminan kesehatan nasional di negaranya. BPJS Kesehatan menginisiasi studi operasional penerapan sistem pembayaran rumah sakit mixed-method INA-CBGs dan Global Budget mulai tahun 2018. Terdapat tiga tahapan dalam uji coba sistem pembayaran rumah sakit mixed-method INA-CBGs dan Global Budget ini. Tahap pertama adalah Global Budget Tanpa Resiko yang bertujuan untuk menguji metode penghitungan global budget dan mengidentifikasi tantangan yang dihadapi bila kebijakan mixed method INA-CBGs dan Global Budget ini diberlakukan. Studi dilakukan di 5 (lima) kabupaten/kota di 30 rumah sakit (RS). Hasil studi menunjukkan bahwa metodologi penghitungan global budget yang diterapkan cukup akurat untuk memprediksi realisasi klaim di RS. Penghitungan global budget di tingkat kabupaten/kota lebih akurat hasilnya dibandingkan dengan menghitung global budget di tingkat RS karena mengakomodir shifting pasien dari RS yang satu ke RS yang lainnya akibat perubahan kapasitas RS. Perubahan kapasitas RS di tahun berjalan dan adanya pandemi COVID-19 menyebabkan adanya selisih antara penghitungan global budget dan realisasi klaim.AbstractWhen it comes to provider payment system, no one shoe fits all including DRG payment system which in Indonesia are known as INA-CBGs. In some countries that used DRG have mixed it with Global Budget in various mechanisms to maintain the sustainability of the national health insurance system in their countries. BPJS Kesehatan initiated a three-stage pilot study on the implementation of the mixed-method hospital payment system INA-CBGs and Global Budget starting in 2018. The first stage is the Non-Risk stage which aims to test the accuracy of the global budget calculation and prediction and to identify the challenges faced when the mixed-method payment is implemented. The pilot was conducted in 5 districts in 30 hospitals. Initial results show that the calculation and prediction method is accurate to predict the actual hospital claims in the following year. The calculation of the global budget at the district level is more accurate than the hospital level because it accommodates patient transfer from one hospital to another due to changes in hospital capacity. Changes in hospital capacity in the current year and the COVID-19 pandemic requires some adjustments to the budget calculation

    Uniqueness Properties of Solutions to the Benjamin-Ono equation and related models

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    We prove that if u1, u2 are solutions of the Benjamin- Ono equation defined in (x, t) ∈ R × [0, T ] which agree in an open set Ω ⊂ R × [0,T], then u1 ≡ u2. We extend this uniqueness result to a general class of equations of Benjamin-Ono type in both the initial value problem and the initial periodic boundary value problem. This class of 1-dimensional non-local models includes the intermediate long wave equation. Finally, we present a slightly stronger version of our uniqueness results for the Benjamin-Ono equation

    Knowledge, attitudes, and practices related to COVID-19 in Indonesia: A post delta variant wave cross-sectional study

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    IntroductionPublic information and regulations related to the coronavirus disease 2019 (COVID-19) have been widely published and continuously changed. The Indonesian government has responded to the emerging evidence by regularly updating its unprecedented and preventive measures against the transmission of COVID-19 to the public. It is important to understand how the public responded to these updates. This study aimed to investigate the knowledge, attitudes, and practices of Indonesians toward COVID-19 after the emergence of the delta variant wave.MethodsA cross-sectional study was conducted among the adult population of non-healthcare workers in Indonesia through an online questionnaire using the SurveyMonkey platform. A total of 1,859 respondents completed this survey from September to October 2021. The knowledge, attitudes, and practices data were analyzed descriptively to find their frequency and percentage. A multivariate analysis was conducted to confirm the factors affecting the respondents' knowledge, attitudes, and practices with a p-value of <0.05 set as significant.ResultsBeing female, having a higher education level, and having a higher frequency of access to COVID-19 news showed significant impacts on knowledge, attitudes, and practices (p<0.001). Older age stratification influenced the knowledge level (p<0.05) but had no significant effect on people's attitudes and practices toward COVID-19. Respondents' perceived probability of being exposed to COVID-19 (p < 0.05) and their COVID-19 infection frequency (p < 0.001) significantly influenced their knowledge. Household income and respondents' knowledge significantly affected their attitudes toward COVID-19. Furthermore, only their attitudes had a significant impact on the respondents' practices. Perceived severity, perceived susceptibility, and vaccination status did not significantly influence their knowledge, attitudes, and practices (p > 0.05).ConclusionAfter more than a year of the COVID-19 pandemic, Indonesians maintain their high level of knowledge, attitudes, and practices. COVID-19 disinformation must be combatted by strengthening authorized media, empowering communities, and improving governance among institutions during and post-pandemic

    Cerebral small vessel disease genomics and its implications across the lifespan

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    White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

    Computational modeling of solid tumor growth: the avascular stage

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    In this paper, we present a mathematical model for avascular tumor growth and its numerical study in two and three dimensions. For this purpose, we use a multiscale model using PDEs to describe the evolution of the tumor cell densities. In our model, cell cycle regulation depends mainly on micro-environment. The cancer growth of volume induces cells motion and tumor expansion. According to biology, cells grow against a basal membrane which interacts mechanistically with the tumor. We use a level set method to describe this membrane and we compute its influence on cell movement thanks to a Stokes equation. The evolution of oxygen, diffusing from blood vessel to cancer cells and used to estimate hypoxia, is given by a stationary diffusion equation solved with a penalization method. The model has been applied to investigate the therapeutic benefit of anti-invasive agents and constitutes now the basis of a numerical platform for tumor growth simulation

    A viscoelastic model for avascular tumor growth.

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    International audienceA viscoelastic model for avascular tumor growth

    A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents

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    With the aim of inhibiting cancer growth and reducing the risk of metastasis, pharmaceutical companies in the early 1990s developed anti-metastatic agents called inhibitors of metalloproteinases (MMPi). Despite the promising results obtained in pre-clinical studies, results of Phase III trials have been somewhat disappointing for late stage cancer patients. With the aim of mathematically investigating this therapeutic failure, we developed a mechanistically based model which integrates cell cycle regulation and macroscopic tumor dynamics. By simulating the model, we evaluated the efficacy of MMPi therapy. Simulation results predict the lack of efficacy of MMPi in advanced cancer patients. The theoretical model may aid in evaluating the efficacy of anti-metastatic therapies, thus benefiting the design of prospective clinical trials

    Evaluating growth and risk of relapse of intracranial tumors

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    As cancer evolution is challenging to evaluate, there is dire need of novel approaches offering clinicians a better insight on the disease. For instance, having an estimation of the growth of slowly evolving tumors that have to be monitored or of the risk of relapse after treatment may be invaluable for clinicians. In this article, two approaches (statistical learning and mechanistic modelling) are presented that aim at addressing these clinical questions. As we wish to use data available in the clinical routine for solid tumors, medical images will be a major source of insight on the disease
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