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• W2888003333 abstract "Lifestyle transitions are making chronic conditions such as chronic kidney disease increasingly common in low- and middle-income countries, including India. According to the 2016 Global Burden of Disease Study, chronic kidney disease was the ninth leading cause of death in India, having risen from 15th rank in 2005 (http://www.healthdata.org/india). In a recent analysis of deaths in 1.1 million Indian households, renal failure was responsible for 2.9% of all deaths among 15–69-year-olds in 2010–2013, an increase of 50% from 2001–2003.1Dare A.J. Fu S.H. Patra J. et al.Renal failure deaths and their risk factors in India 2001–2013: nationally representative estimates from the Million Death Study.Lancet Glob Health. 2017; 5: e89-e95Abstract Full Text Full Text PDF PubMed Scopus (35) Google Scholar Currently, most patients with end-stage kidney disease (ESKD) in India die without receiving appropriate treatment.2Jha V. ESRD burden in South Asia: the challenges we are facing.Clin Nephrol. 2015; 83: 7-10Crossref PubMed Scopus (16) Google Scholar As countries such as India move towards universal health coverage, the health and economic burden imposed by chronic kidney disease—in particular how to take care of patients with ESKD—creates challenges for health systems. Although classified by the World Health Organization as a low priority service on the basis of cost-effectiveness,3World Health Organization. Making fair choices on the path to universal health coverage. Available at http://www.who.int/choice/documents/making_fair_choices/en/. Accessed January 16, 2018.Google Scholar funding of dialysis has generated debates regarding societal willingness to pay for expensive medical care4Treerutkuarkul A. Thailand: health care for all, at a price.Bull World Health Organ. 2010; 88: 84-85Crossref PubMed Google Scholar. The Rajiv Aarogyasri Community Health Insurance Scheme (RACHIS) was introduced in 2007 by the state government of undivided Andhra Pradesh (AP), India to provide free hospital care to poor households.5Shaikh M. Woodward M. Rahimi K. et al.Major surgery in south India: a retrospective audit of hospital claim data from a large community health insurance programme.Lancet. 2015; 385: S23Abstract Full Text Full Text PDF PubMed Google Scholar The poor were defined as those with annual income below 60,000 Indian rupees (INR) (approximately International$ [I$] 3550) in rural areas and below INR 75,000 (I$ 4438) in urban areas. Under the program, a private insurer provided health insurance and was paid in full by the state government. Beneficiaries were able to utilize hospital services through a network of public and private hospitals. Each household received coverage for up to INR 150,000 (I$ 8876) per year, plus an extension of INR 50,000 (I$ 2958) for those needing long-term care. By 2012, RACHIS was claimed to be providing free care for 18.81 million households, constituting 81% of the population of AP.5Shaikh M. Woodward M. Rahimi K. et al.Major surgery in south India: a retrospective audit of hospital claim data from a large community health insurance programme.Lancet. 2015; 385: S23Abstract Full Text Full Text PDF PubMed Google Scholar We studied the use of maintenance HD between mid-2008 and mid-2012 across all 23 districts of undivided AP using RACHIS claims data. In this report, we describe patterns of utilization of dialysis and outcomes for a large population of patients with ESKD. A total of 13,118 beneficiaries (1.4% of all claimants) received HD for ESKD during the study period, with 63.6% seeking care predominantly at private centers. Table 1 summarizes the key findings on patient attributes and utilization patterns. The majority (73.4%) of patients were males, and the gender gap increased with age (Table 2). Approximately half of the patients were between the ages of 40 and 60 years. The mean age at start of HD was slightly lower for females (42.9 vs. 44.4 years; P < 0.001).Table 1Patient characteristics and HD utilization detailsCharacteristicValueNo. of beneficiaries who received HD13,118Annual incidence (per million of the population)49.2 (20.8–77.5)Prevalence (per million of the population)73.7 (09.3–138.0)Males (%)73.4 (72.6–74.1) (n = 9621)Mean age (yr)44.0 (43.8–44.3) Males44.4 (44.2–44.7) Females42.9 (42.5–43.4)No. of days receiving HD Males198 (46–393) Females170 (42–386)No. of HD sessions40 (20–110)Percentage of patients utilizing >60% of HD at private hospitals63.64 (62.80–64.46) (n = 8348)Percentage of patients receiving vascular access procedure42.65 (41.80–43.50) (n = 5595)HD, hemodialysis.Values median and (25th–75th percentile) unless otherwise noted. Open table in a new tab Table 2Age and sex distribution of patients receiving hemodialysisAge (yr)TotalFemalesMalesMale/female ratio0–916 (0.1)6 (0.2)10 (0.1)1.6710–19446 (3.4)163 (4.7)283 (2.9)1.7420–291642 (12.5)456 (13)1186 (12.3)2.6130–392571 (19.6)730 (20.9)1841 (19.1)2.5340–493446 (26.3)906 (25.9)2540 (26.4)2.8150–593055 (23.3)754 (21.6)2301 (23.9)3.06≥601942 (14.8)482 (13.8)1460 (15.2)3.03Total13,118 (100)3497 (100)9621 (100)2.75Numbers in parentheses are percentages. Open table in a new tab HD, hemodialysis. Values median and (25th–75th percentile) unless otherwise noted. Numbers in parentheses are percentages. The number of centers providing HD increased from 50 in 2008–2009 to 89 in 2011–2012 (Supplementary Table S1). This was paralleled by an increase in uptake, as shown by the incidence of new patients accessing HD, from 29.5 per million of the population in 2008 to 69.8 per million of the population in 2012 (Figure 1). Overall, the number of patients who received HD for ESKD increased from 29.5 per million of the population in 2008–2009 to 122.2 per million of the population in 2011–2012. The number of dialysis units for every 100 recipients of ESKD receiving treatment ranged from 0 to 1.89 across districts of AP, with only 6 of 23 districts having more than 1 dialysis unit for 100 residents (Supplementary Table S2). A total of 5595 patients (42.6%) underwent a vascular access procedure: 3928 (29.9%) patients before and 2203 (16.8%) after initiating HD. A total of 488 patients (8.7%) underwent multiple procedures. A total of 15,064 hospitalizations were recorded in this population, 11,991 (79.6%) before starting HD. The majority (56%) of pre-HD hospitalizations were for medical management of chronic renal failure, either for starting dialysis or confirmation of diagnosis. After starting HD, hospitalizations were for the management of HD-related complications or for kidney transplantation. Of all the subjects who started HD, 2.3% received a kidney transplantation, 17.1% were reported as dead, and 63.5% had ceased treatment of their ESKD (i.e., stopped reporting to dialysis centers). After 6 months of HD, 10.2% had died, and 36.2% ceased treatment (Table 3). The median duration that the incident population received HD was 170 days for females and 198 days for males. For patients who did not drop out, the median survival was 1320 and 1372 days for females and males, respectively (Figure 2). The hazard ratio (95% confidence interval) for the risk of death or discontinuation was 0.95 (0.92–0.99) for males compared with females, 1.005 (1.003–1.006) for each year increase in age and 1.07 (1.03–1.12) for those using services at public versus private dialysis centers.Table 3Outcomes by duration of dialysisOutcomeAll cases<90 d3–6 mo7–12 mo≥12 moStill receiving HD2259 (17.3)509 (22.5)318 (14.1)434 (19.2)998 (44.2)Stopped8326 (63.5)3474 (41.7)1334 (16.1)1564 (18.7)1954 (23.5)Died2237 (17.1)988 (44.2)344 (14.9)403 (18.1)502 (22.4)Received kidney transplant296 (2.3)122 (41.2)92 (31.1)49 (16.6)33 (11.1)Total13,118 (100)5093 (38.8)2088 (15.9)2450 (18.7)3487 (26.6)HD, hemodialysis.Numbers in parentheses are percentages. Open table in a new tab HD, hemodialysis. Numbers in parentheses are percentages. The total cost of HD-related care was I$ 63.2 million, accounting for 3.1% of all claim expenses during the study period. A total of I$ 59.9 million was spent on HD and I$ 4.26 million on vascular access procedures. An additional I$ 3.26 million was spent on hospitalizations for other indications in these patients. The mean annual expenditure per patient on HD-related care was I$ 4821 (Supplementary Table S3). In aggregate, HD-related expenditure as a proportion of all RACHIS claims increased 7-fold, from 0.75% in 2008 to 5.2% in 2012 (Figure 3). Supplementary Tables S4 and S5 show details of indications for hospitalization and associated costs. This is the first large-scale study to present population-based data on utilization of HD and outcomes of care for ESKD in India. Our data came from more than 68 million people who were eligible to receive free care, constituting more than 80% of the population in the undivided AP. The year-on-year increase in uptake in treatment suggests that programs such as this are making inroads in addressing the high unmet need for dialysis, albeit at the cost of a significant economic burden on the health system. A notable finding is the poor survival and high drop-out rate, with only 53% patients continuing dialysis for >6 months. Even the dropout and transplant–censored survival was below the global standards. According to the United States Renal Data System Report, the expected remaining lifespan on dialysis is approximately 10.5 years for dialysis patients 40–44 years of age and approximately 5.5 years for those aged 60–64 years.6Saran R. Robinson B. Abbott K.C. et al.US Renal Data System 2016 annual data report: epidemiology of kidney disease in the United States.Am J Kidney Dis. 2017; 69: A7-A8Abstract Full Text Full Text PDF PubMed Scopus (636) Google Scholar A recent systematic review from Africa7Ashuntantang G. Osafo C. Olowu W.A. et al.Outcomes in adults and children with end-stage kidney disease requiring dialysis in sub-Saharan Africa: a systematic review.Lancet Glob Health. 2017; 5: e408-e417Abstract Full Text Full Text PDF PubMed Scopus (97) Google Scholar suggested high mortality and dropouts among patients who received dialysis for ESKD. Overall, only approximately 10% of African adults with incident ESKD continued dialysis for more than 3 months, with patients stopping dialysis after a mean of 6.5 sessions only. Only a minority of patients received financial support for their dialysis, unlike in the present report. The high dropout rates, most of them early in the course of treatment, deserve closer examination. Because we were able to track all unique patients across different dialysis facilities, the likelihood that any patient would be continuing dialysis elsewhere or received a transplant using their own funds either within or outside the jurisdiction of RACHIS is extremely low. Therefore, such dropouts can be safely assumed to have culminated in death. These data are consistent with previous single-center reports from India.8Parameswaran S. Geda S.B. Rathi M. et al.Referral pattern of patients with end-stage renal disease at a public sector hospital and its impact on outcome.Natl Med J India. 2011; 24: 208-213PubMed Google Scholar Finally, it is possible that some patients with acute kidney injury were miscoded as having ESKD but recovered kidney function sufficiently to discontinue dialysis. Given that treatment through this program was provided without charge, factors other than the cost of dialysis itself likely contributed to early discontinuation, especially in the rural populations. They could include out-of-pocket expenses for travel to dialysis units; management of associated conditions (anemia, abnormalities of bone and mineral metabolism, blood pressure, and nutrition) and comorbidities, the costs of which were not covered by the scheme; loss of income; and caregiver burden. RACHIS covered only one set of laboratory tests per month. Previous studies have shown that the catastrophic cost burden associated with long-term dialysis treatment is a major contributor to cessation of treatment and inequity in access to care.9Ramachandran R. Jha V. Kidney transplantation is associated with catastrophic out of pocket expenditure in India.PLoS One. 2013; 8: e67812Crossref PubMed Scopus (76) Google Scholar The annual spend per patient was low in comparison with that reported from other countries (US$ 89,900 in the United States, AU$ 65,000 in Australia, US$ 12,100 in Thailand, and US$ 9112 in Brazil). One consequence of the low spend may be the poor patient survival observed in this study. The reimbursement rates were decided by the government without any formal costing analysis to determine a model that will provide an essential level of quality. Given limited resources available, maintaining a low-cost model of care while meeting a minimum acceptable level of service quality is critical for enabling a basic level of access. Our analysis suggests that the current model of insurance coverage does not adequately address all the barriers to long-term care that lead to optimum survival. Overcoming these barriers is likely to increase the cost of care, hence understanding the gains from such investment in terms of enhanced patient survival and productivity is important. The data also suggest residual inequities in the care of females with ESKD. Although men outnumber women among the dialysis population in almost all geographic regions, the overrepresentation of men (3:1) in this study was striking, suggesting that social determinants are influencing the disparities. It is possible that a larger proportion of women in this population either are not diagnosed or do not present for treatment. Even those females who entered the HD program were more likely to cease treatment than males, perhaps because, in these cases, households are less willing to bear the out-of-pocket costs of ongoing medications. State-funded dialysis programs for patients with ESKD are being increasingly adopted as part of universal health care provision in low- and middle-income countries.4Treerutkuarkul A. Thailand: health care for all, at a price.Bull World Health Organ. 2010; 88: 84-85Crossref PubMed Google Scholar The findings presented here are of significance, because the recently announced National Dialysis Program in India envisages provision of free dialysis to the poor using a public–private partnership model akin to the one evaluated in this study. However, the suboptimal outcomes suggest the need to make dialysis more accessible through participative approaches. Community-focused models of dialysis delivery, such as peritoneal dialysis and satellite dialysis units, need to be developed. The financing model, especially in terms of the ancillary costs, and oversight in terms of overall quality of care need evaluation to ensure that dialysis programs can deliver acceptable outcomes. Other urgent needs include development of a program of care that includes early detection and prevention of kidney disease, better care of those with pre-dialysis chronic kidney disease, and expansion of the transplant program. Finally, success of ongoing efforts to develop low-cost but robust and sustainable dialysis delivery systems (https://www.ellenmedical.com/) could be particularly relevant for emerging economies. Our study has several strengths: it covered a large beneficiary population that is unlikely to have gone outside of the network for expensive treatment, such as dialysis. For the same reason, we were able to establish the outcomes with a high degree of confidence. We were able to perform a comprehensive cost calculation that included not only the cost of dialysis treatment but also ancillary services. The weaknesses were related to the nature of the data. The source of information was claims data, without any link to medical records. Hence, we were unable to get information on comorbidities, causes of death, medication use, dialysis quality, and complications. We were also unable to determine the characteristics of patients who discontinued dialysis—whether these people had been referred late, had to travel long distances, belonged to very poor rural communities, or had inadequate family support. Because participants were recruited in hospitals, we were unable to account for patients who might have developed ESKD but did not access HD at all. In conclusion, removal of out-of-pocket of cost leads to increase in uptake of HD, confirming a previously high unmet need. The high mortality and dropout rates suggest that insurance coverage does not address all inequities in access and the barriers to maintaining long-term care. Prospective studies are needed to identify reasons for dialysis discontinuation and death; and to identify factors that will promote patients to continue dialysis and improve quality of life and rehabilitation status. Such factors may need to be specifically tailored for women. In projecting the future financing needs for dialysis treatment within the context of universal health coverage, the study illustrates that meeting the previously high levels of unmet need will be a significant driver of cost, and the imperative will be on expanding coverage and promoting survival while maintaining a low-cost model of dialysis care. We obtained data on all enrollees in RACHIS between 2008 and 2012. Unique identifiers for patients and households were used to reconstruct patient-level records of hospitalizations, procedures, and costs. Data on the number of beneficiaries were collated from RACHIS annual reports. Patient age, sex, social class, and place of residence were obtained from the claim records. This study included all patients having at least 1 claim for the billing code of Maintenance HD for chronic renal failure during the study period (coded as M6.5 under the RACHIS billing system). This billing code entitled the dialysis center to receive a reimbursement of INR 10,000 (I$ 590) for a package of 10 HD sessions and a single renal biochemistry panel. Because many hospitals submit claims late, claims submitted until March 2013 were obtained, and cut-off dates for follow-up were backdated to the end of the study period in 2012. We identified unique individuals from these claims to build a database of patients receiving HD. Claims received from all centers were examined to account for any interfacility transfers. The number of days receiving HD was computed as the difference between the dates of the first and the last claims, both days included. Patients utilizing more than 60% of the services at private facilities were assigned to the private group; otherwise they were classified as public patients. We also identified claims received for dialysis vascular access–related procedures (billing codes: S7.11.13, S7.11.14, and S9.1.2) and other hospitalization events. Hospitalizations with a discharge date before start of HD were identified as pre-HD and others as concurrent hospitalizations. The key parameters were clinical outcome (defined below) and costs of care. Patients were considered to be still receiving HD if the end date of the last claim received was beyond the study cut-off and the patient had not received a renal transplant nor was reported to be dead. Death while receiving HD was recorded if the last claim mentioned a date of death. Patients were classified as having stopped HD if the last claim received was before the study cut-off date and the patient neither received a renal transplant nor was reported dead. Finally, we scrutinized all claims for renal transplant surgery to identify whether the patient receiving HD had received a renal transplant. For calculating costs, claims submitted for each patient were collated separately into those for HD, vascular access related, and other hospitalizations. Claims for HD and vascular access–related hospitalizations were combined to calculate costs. Currency exchange from INR to I$ was done on the basis of purchasing power parities in given years (https://data.oecd.org/conversion/purchasing-power-parities-ppp.htm). Data are presented as mean (SD) or median (interquartile interval). The annual incidence and prevalence were expressed per million of the population, with population estimates derived from census data. Between-group comparisons were done by χ2 tests for categorical variables and Student t tests for continuous variables. Two types of survival analyses were done using an adjusted Cox model: one in which patients who ceased dialysis or received a transplant were censored, and the other for a composite of death and dialysis cessation. VJ serves on Steering Committee for a trial funded by GlaxoSmithKline and serves on an advisory board and/or has spoken at scientific meetings for Biocon, Baxter, Janssen, Medtronic, and NephroPlus. He has a policy of all honoraria being paid to his employer. All the other authors declared no competing interests. Download .docx (.01 MB) Help with docx files Table S1Number of dialysis centers in Andhra Pradesh from 2008 to 2012. Download .docx (.01 MB) Help with docx files Table S2The number of dialysis centers and residents on hemodialysis in all districts of Andhra Pradesh. Download .docx (.01 MB) Help with docx files Table S3Treatment costs in relation to outcomes amongst patients on hemodialysis. Download .docx (.02 MB) Help with docx files Table S4Cost of care for hospitalization prior to start of hemodialysis. Download .docx (.02 MB) Help with docx files Table S5Cost of care for hospitalization after start of hemodialysis." @default.
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• W2888003333 title "Utilization, costs, and outcomes for patients receiving publicly funded hemodialysis in India" @default.
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