Assessment of Expenditure and Budget Impact Analysis of Post-kidney Transplant Care at Kenyatta National Hospital

Abstract

Background In Kenya, the Ministry of Health reported that 4 million Kenyans have chronic kidney disease with a significant proportion of this population progressing to kidney failure. In the event that kidneys fail, renal replacement therapy by dialysis or transplantation is the only means of survival. Renal transplantation therapy (RTT) is a cost-effective therapy compared to hemodialysis or peritoneal dialysis in patients with end-stage renal disease (ESRD) despite being associated with a huge economic burden. The major factor limiting transplantation rates is availability of donor kidneys. Currently in Kenya, the NHIF benefit package only caters for dialysis and kidney transplantation omitting post-kidney transplant care. This signifies a gap service provision and policy which has devastating financial consequences on KTRs. Consequently, many healthcare providers in Kenya have lamented about this cost and resultant impact of non-adherence. It is possible that this cost can be comfortably borne by the NHIF. Objective The main objective of this study was to determine the expenditure and budget impact of post kidney transplant care from a provider perspective. Methods This was a mixed methods study comprising of a retrospective cohort study and a predictive Markov model. The study was done from the perspective of the healthcare provider (KNH). Patients who had undergone a kidney transplant and receiving care at the renal unit from 2010 to 2019 were identified. One hundred and fourteen files were identified after simple random sampling with replacement. Files of patients were selected using simple random sampling technique with replacement. This was carried out using a coin. The files that satisfied the inclusion criteria were gathered and a coin was tossed. Whichever file coincided with the head was included. The process was repeated until the calculated sample size was attained. A pre-tested data abstraction tool was used to collect socio-demographic and resources used in the management post-kidney transplant patient while an interview guide was used to collect cost data. vi For each patient file, the principal investigator identified resources consumed in each year using the data abstraction form and estimated the quantities by counting the number of tablets/ tests used in each year to determine the total resources consumed. This process was repeated for a period of five years’ post-transplant. Data was entered into an Excel based database and descriptive analysis was done using STATA version 10. A micro ingredient approach was used to cost all the resources used to manage kidney transplant recipients (KTRs). Resources used were identified and quantified and the unit cost were obtained from the procurement and billing departments. These were used to compute the total expenditure incurred by each patient per year. The expenditure data were converted to US dollars at the prevailing rate of 1 dollar to Ksh 102.9. The contribution of each cost category was computed. One-way sensitivity analysis was done to identify the cost categories whose uncertainty in value had the most impact on the total expenditure incurred and the findings presented in the form of a tornado charts. Budget impact analysis was done to determine the impact of including the care after transplant into the Kenyatta National Hospital and National Hospital Insurance Fund budgets. To predict the costs associated managing post kidney transplant patients, time varying discrete states markov modelling was done. A kidney transplant recipient (KTR) could exist in 3 possible states. The three states were survival with a viable kidney; hemodialysis following graft rejection; and death. Markov modeling was done and the transition probabilities for the three states were calculated using Heemod package version 0.14.2 in R. The cycle length was one month. A diagrammatic representation of the model is shown in Figure 4.13. We constructed a Markov model that was used to estimate the number of patients that would need post-kidney transplant services in five years. It was conducted from the perspective of Kenyatta National Hospital. The R code that was used to compute the costs associated with each health state is presented in Appendix five and the actual costs are presented in Appendix six. Results The three main categories whose expenditure contributed significantly to the total cost of post - kidney transplant care were immunesuppressants, laboratory investigations and services. We demonstrated that expenditure was highest in the first year post-kidney transplantation; a cost of Ksh 32,882 per patient per month (PPPM) followed by year three at Ksh 25,639 (PPPM)and the trend decreased gradually from year one to year five. vii In addition, in the years following kidney transplant, the annual medicine and hospital budget increased by Ksh 369,568,640 and Ksh 3,824,569,720 respectively over a five-year period. Results from the budget impact analysis of KTRs in Kenya showed that expenditure for NHIF Outpatient budget will increase from Ksh 175,729,217 million in year one to Ksh 275,508,106 million in year five which is an increment of Ksh 99,778,889 million shillings. Discussion The results demonstrate that the first year post-kidney transplant is associated with the greatest expenditure of approximately Ksh 32,882 per patient per month. This amount is more than twice Kenya’s monthly minimum wage of Ksh 13,572. Immunosuppressive medicines in particular were a major contributor to the yearly total expenditure signifying their important role in post-transplant care. In the budget impact analysis for all the kidney transplant recipients in Kenya, we have demonstrated that the incremental expenditure change over a five-year period for NHIF outpatient budget was Ksh 1,132,459,571 representing a 23% change from their baseline expenditure (2020). We propose that post-kidney transplant care be incorporated into the NHIF benefit package since this amount is reasonable considering the important role of post-transplant care, to ease access and the financial burden associated with out of pocket expenditure. Conclusion The main expenditure drivers after kidney transplantation were immunosuppressants, laboratory investigations and services offered to KTRs. The first year post-kidney transplant is associated with the greatest expenditure of approximately Ksh 32,882 per patient per month. This amount is 2.4 times Kenya’s monthly minimum wage of Ksh 13,572. Immunosuppressive medicines and laboratory investigations in particular were a major contributor to the yearly total expenditure signifying their important role in post-transplant care. We recommend that these expenditures to be covered by NHIF.