CAPACITY SHARING STRATEGY WITH SUSTAINABLE REVENUE-SHARING CONTRACTS

This paper develops a duopoly model to analyse capacity sharing strategy and the optimal revenue-sharing contract under a two-part tariff and examines the effects of capacity sharing, cost, and sharing charges in three scenarios. The paper uses the two-part tariff method and adds a more realistic assumption of incremental marginal costs to improve the research on capacity sharing strategies. The results show that capacity constraints affect the sustainable development of firms. A sustainable revenue-sharing contract can create a win-win situation for both firms and promote capacity sharing. Capacity sharing, cost, and the revenue-sharing rate have different impacts in different scenarios; the optimal revenue-sharing rate and fixed fee can be determined to maximise the profits of firms that share capacity. However, capacity sharing may not improve social welfare.

Performance of the tariff method and physicians in determining stroke as the cause of deaths using verbal autopsy in areas with a limited number of physicians: cases in Indonesia

Background: Physician-certified verbal autopsy (PCVA) is the primary method used to determine the cause of death in Indonesia, although it is very costly and problematic to use in areas where physicians are not widely available with most deaths occur at home. The Tariff method has been piloted to obtain an alternative approach that does not require a physician to determine the cause of death. This validation study presents how the Tariff captures the correctness and distinctiveness of stroke symptoms to the PCVA. Methods: Medical records of 298 adult deaths that occured in four teaching hospitals in the Jakarta from January 1, 2015 to March 2017 were collected prospectively. Verbal Autopsy (VA) was applied using the 2014 WHO instrument diagnosed by a trained physician (PCVA) and by Tariff method. The validity of the VA was assessed by comparing the PCVA diagnoses with the Tariff diagnoses, referring to the best standard. Results. Sensitivity, specificity and positive predictive value (PPV) of VAs using physician’s diagnosis (PCVA) for stroke were 73.9%, 73.5% and 93.4% respectively. The corresponding sensitivity, specificity and positive predictive value (PPV) of VAs diagnosed by the Tariff method were 75%, 61% and 91%. The negative predictive values (NPV) of both techniques were low, 35.6% and 32.6% respectively. Conclusion: The performance of the Tariff method for stroke was almost similar with PCVA, and with a narrower variation, or more consistent than PCVA. Therefore, the Tariff method is a potential alternative to be used on a large scale, because the difficult geographical conditions where physician are not widely available for causes of deaths with distinct signs and symptoms. Keywords: verbal autopsy, sensitivity, specificity, determining cause of death, physician, tariff method Abstrak Latar Belakang: Autopsi verbal yang disertifikasi oleh dokter (PCVA) merupakan metode utama yang digunakan untuk memastikan penyebab kematian di Indonesia. Meskipun sangat mahal dan bermasalah untuk digunakan di daerah di mana dokter tidak banyak tersedia dan sebagian besar kematian terjadi di rumah. Metode Tarif telah diujicobakan untuk mendapatkan pendekatan alternatif yang tidak memerlukan dokter untuk menentukan penyebab kematian. Studi validasi ini menyajikan bagaimana Tarif menangkap kebenaran dan kekhasan gejala stroke dibandingkan dengan PCVA. Metode: Rekam medis dari 298 kematian orang dewasa yang terjadi di empat rumah sakit studi di wilayah Jakarta pada 1 Januari 2015 hingga Maret 2017 dikumpulkan secara prospektif. Autopsi verbal (AV) dilakukan dengan menggunakan instrumen WHO 2014 yang didiagnosis oleh dokter terlatih (PCVA) dan metode Tarif. Validitas AV dinilai dengan membandingkan diagnosis PCVA dengan diagnosis metode Tarif, mengacu pada baku mutu. Hasil. Sensitivitas, spesifisitas dan nilai prediksi positif (PPV) dari AV dengan diagnosis dokter (PCVA) untuk stroke adalah 73,9%, 73,5% dan 93,4%. Sensitivitas, spesifisitas, dan nilai prediksi positif (PPV) yang sesuai dari AV yang didiagnosis dengan metode Tariff adalah 75%, 61% dan 91%. Nilai prediksi negatif (NPV) dari kedua teknik itu rendah, masing-masing 35,6% dan 32,6%. Kesimpulan: Untuk stroke, kinerja metode Tarif hampir sama dengan PCVA, dan dengan variasi yang lebih sempit, atau lebih konsisten dibandingkan PCVA. Oleh karena itu, untuk penyebab kematian dengan tanda dan gejala yang berbeda, metode Tarif merupakan alternatif potensial untuk digunakan dalam skala besar, di Indonesia dimana banyak wilayah dengan geografis sulit dan dokter tidak selalu tersedia. Kata kunci: autopsi verbal, sensitifitas, spesifisitas, penentuan penyebab kematian, dokter, metode tariff

Acceptance Analysis of PDAM Sleman’s Water Tariff Based on Revenue and Wilingness to Pay Projection

The Regional Water Company (PDAM) of Sleman provides clean water to the community and charges a tariff for each cubic meter of water sold to customers. Minister of Home Affairs Regulation No. 71 of 2016 states that PDAM tariffs requiring a review every four years. Most recently tariffs set by PDAM Sleman was in 2016 therefore it requires a recalculation. Besides that, it is necessary to analyze the tariff acceptance from the service provider and service recipient’s point of view. Calculation tariff method utilized a formula based on the Minister of Home Affairs Regulation No. 71 of 2016. Acceptance analysis conducted by calculating the projection of water sales revenue, the profit to earning assets ratio, and the willingness to pay (WTP) projection of customers. Revenue projections were obtained by multiplying tariffs with the water sold volume. The WTP projection is carried out using the inflation method based on the WTP of PDAM Sleman customers from the 2007’s research. PDAM Sleman tariffs based on calculations resulted low tariffs of IDR3727.48, basic tariffs of IDR4659.36, and full rate of IDR9460.17. Based on the WTP analysis, the tariffs are feasible from the the service recipient’s point of view, which are the PDAM customers, because it is still affordable by customers for their average water consumption. Nevertheless, from the point of view of the service provider, which is PDAM Sleman, the tariffs are not feasible because the profit ratio of 0.31% is still much lower than the fairness profit ratio as 10% amount. Therefore, it is necessary to make tariff adjustments to increase profits. The adjustment strategies such as by determined tariffs only based on consumption blocks without breaking down based on customer group categories and adjusting the range of second and third consumption blocks.

Analysis of Causes of Death Among Brought-in-Dead Cases in a Third-Level Hospital in Lusaka, Republic of Zambia, Using the Tariff Method 2.0 for Verbal Autopsy: A Cross-Sectional Study

Background: Over one third of deaths in Zambian health facilities involve someone who has already died before arrival (i.e., Brough in Dead), and in most BiD cases, the CoD have not been fully analyzed. Therefore, this study was designed to evaluate the function of automated VA based on the Tariff Method 2.0 to identify the CoD among the BiD cases and the usefulness by comparing the data on the death notification form. Methods: The target site was one third-level hospital in the Republic of Zambia’s capital city. All BiD cases who reached the target health facility from January to August 2017 were included. The deceased’s closest relatives were interviewed using a structured VA questionnaire and the data were analyzed using the SmartVA to determine the CoD at the individual and population level. The CoD were compared with description on the death notification forms by using t-test and Cohen’s kappa coefficient. Results: 1378 and 209 cases were included for persons aged 13 years and older (Adult) and those aged 1 month to 13 years old (Child), respectively. The top CoD for Adults were infectious diseases followed by non-communicable diseases and that for Child were infectious diseases, followed by accidents. The proportion of cases with a determined CoD was significantly higher when using the SmartVA (75% for Adult and 67% for Child) than the death notification form (61%). A proportion (42.7% for Adult and 46% for Child) of the CoD-determined cases matched in both sources, with a low concordance rate for Adult (kappa coefficient = 0.1385) and a good for Child(kappa coefficient = 0.635). Conclusions: The CoD of the BiD cases were successfully analyzed using the SmartVA for the first time in Zambia. While there many erroneous descriptions on the death notification form, the SmartVA could determine the CoD among more BiD cases. Since the information on the death notification form is reflected in the national vital statistics, more accurate and complete CoD data are required. In order to strengthen the death registration system with accurate CoD, it will be useful to embed the SmartVA in Zambia’s health information system.

Analysis of Causes of Death Among Brought-in-Dead Cases in a Third-Level Hospital in Lusaka, Republic of Zambia, Using the Tariff Method 2.0 for Verbal Autopsy: A Cross-Sectional Study

Background: Over one third of deaths in Zambian health facilities involve someone who has already died before arrival (i.e., Brough in Dead[横堀1] ), and in most BiD cases, the CoD have not been fully analyzed. Therefore, this study was designed to evaluate the function of automated VA based on the Tariff Method 2.0 to identify the CoD among the BiD cases and the usefulness by comparing the data on the death notification form. Methods: The target site was one third-level hospital in the Republic of Zambia’s capital city. All BiD cases who reached the target health facility [横堀2] from January to August 2017 were included. The deceased’s closest relatives were interviewed using a structured VA questionnaire and the data were analyzed using the SmartVA to determine the CoD at the individual and population level. The CoD were compared with description on the death notification forms by using t-test and Cohen’s kappa coefficient. Results: [横堀3] 1378 and 209 cases were included for persons aged 13 years and older (Adult) and those aged 1 month to 13 years old (Child), respectively. The top CoD for Adults were infectious diseases followed by non-communicable diseases and that for Child were infectious diseases, followed by accidents. The proportion of cases with a determined CoD was significantly higher when using the SmartVA (75% for Adult and 67% for Child) than the death notification form (61%). A proportion (42.7% for Adult and 46% for Child) of the CoD-determined cases matched in both sources, with a low concordance rate for Adult (kappa coefficient = 0.1385) and a good for Child(kappa coefficient = 0.635). Conclusions: The CoD of the BiD cases were successfully analyzed using the SmartVA for the first time in Zambia. While there many erroneous descriptions on the death notification form, the SmartVA could determine the CoD among more BiD cases. Since the information on the death notification form is reflected in the national vital statistics, more accurate and complete CoD data are required. In order to strengthen the death registration system with accurate CoD, it will be useful to embed the SmartVA in Zambia’s health information system.

Development of a set of limits for the main performance indicators of energy-generating companies

Restrictive conditions established on average throughout the organization, which each energy-generating company should strive to carry out, have been proposed and analyzed. In order to ensure a sustainable level of financial stability, the calculation of the use of debt coverage and debt service limits is predicated. Fulfillment of the established limits should be taken into account in the formation of investment programs, which the energy-generating company intends to implement, which should imply the corresponding energy-generating company certain preferences, for example, a reduced interest rate on loans, which in turn increases the efficiency of the investment project of the organization and leads to more economic efficiency of the tariff method RAB-regulation.

Analysis of Causes of Death Among Brought-in-Dead Cases in a Third-Level Hospital in Lusaka, Republic of Zambia, Using the Tariff Method 2.0 for Verbal Autopsy: A Cross-Sectional Study

Background Over one third of deaths in Zambian health facilities involve someone who has already died before arrival (i.e., brought in dead [BiD]), and in most BiD cases, the causes of death (CoD) have not been fully analyzed. Therefore, this study aimed to analyze the CoD of BiD cases using the Tariff Method 2.0 for automated verbal autopsy (VA), which is called SmartVA.Methods The target site was one third-level hospital in the Republic of Zambia’s capital city. All BiD cases aged 13 years and older at this facility from January to August 2017 were included. The deceased’s closest relatives were interviewed using a structured VA questionnaire (Population Health Metrics Research Consortium Shortened Questionnaire) and the data were analyzed using the SmartVA to determine the CoD at the individual and population level. The CoDs were compared with description on the death notification forms by using t-test and Cohen’s kappa coefficient.Results Approximately 1500 cases were included (average age = 47.2 years, 61.8% males). The top CoD were infectious diseases, including acquired immunodeficiency syndrome, tuberculosis, and malaria, followed by non-communicable diseases, such as stroke, cardiovascular diseases, and diabetes mellitus (DM). The comparison with the CoD distribution among hospital deaths showed that the trends were similar except for DM, which was greater among hospital deaths, and malaria and accident, which were less frequent in the main CoD. The proportion of cases with a determined CoD was significantly higher when using the SmartVA (75%) than the death notification form (61%). A proportion (42.7%) of the CoD-determined cases matched in both sources, with a low concordance rate (kappa coefficient = 0.1385).Conclusions The CoD of the BiD cases were successfully analyzed using the SmartVA for the first time in Zambia. While there many erroneous descriptions on the death notification form, the SmartVA could determine the CoD among more BiD cases. Since the information on the death notification form is reflected in the national vital statistics, more accurate and complete CoD data are required. In order to strengthen the death registration system with accurate CoD, it will be useful to embed the SmartVA in Zambia’s health information system.