Effect of a Pay-for-Performance Program on Renal Outcomes Among Patients With Early-Stage Chronic Kidney Disease in Taiwan

Document Type : Original Article


1 Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan

2 Department of Pharmacy, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan

3 School of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan

4 Division of Nephrology, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan

5 College of Medicine, Chang Gung University, Taoyuan, Taiwan

6 Population Health Research Center, National Taiwan University, Taipei, Taiwan


With the promising outcomes of the pre-ESRD (end-stage renal disease) pay-for-performance (P4P) program, the National Health Insurance Administration (NHIA) of Taiwan launched a P4P program for patients with early chronic kidney disease (CKD) in 2011, targeting CKD patients at stages 1, 2, and 3a. This study aimed to examine the long-term effect of the early-CKD P4P program on CKD progression.
We conducted a matched cohort study using electronic medical records from a large healthcare delivery system in Taiwan. The outcome of interest was CKD progression to estimated glomerular filtration rate (eGFR) 2 between P4P program enrolees and non-enrolees. The difference in the cumulative incidence of CKD progression between the P4P and non-P4P groups was tested using Gray’s test. We adopted a cause-specific (CS) hazard model to estimate the hazard in the P4P group as compared to non-P4P group, adjusting for age, sex, baseline renal function, and comorbidities. A subgroup analysis was further performed in CKD patients with diabetes to evaluate the interactive effects between the early-CKD P4P and diabetes P4P programs.
The incidence per 100 person-months of disease progression was significantly lower in the P4P group than in the non-P4P group (0.44 vs. 0.69, P < .0001), and the CS hazard ratio (CS-HR) for P4P program enrolees compared with non-enrolees was 0.61 (95% CI: 0.58–0.64, P < .0001). The results of the subgroup analysis further revealed an additive effect of the diabetes P4P program on CKD progression; compared to none of both P4P enrolees, the CS-HR for CKD disease progression was 0.60 (95% CI: 0.54–0.67, P < .0001) for patients who were enrolled in both early-CKD P4P and diabetes P4P programs.
The present study results suggest that the early-CKD P4P program is superior to usual care to decelerate CKD progression in patients with early-stage CKD.


  1. El Nahas AM, Bello AK. Chronic kidney disease: the global challenge. Lancet. 2005;365(9456):331-340. doi:10.1016/s0140-6736(05)17789-7
  2. Levey AS, Atkins R, Coresh J, et al. Chronic kidney disease as a global public health problem: approaches and initiatives - a position statement from Kidney Disease Improving Global Outcomes. Kidney Int. 2007;72(3):247-259. doi:10.1038/sj.ki.5002343
  3. United States Renal Data System. 2018 USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2018.
  4. Lysaght MJ. Maintenance dialysis population dynamics: current trends and long-term implications. J Am Soc Nephrol. 2002;13 Suppl 1:S37-40.
  5. Liyanage T, Ninomiya T, Jha V, et al. Worldwide access to treatment for end-stage kidney disease: a systematic review. Lancet. 2015;385(9981):1975-1982. doi:10.1016/s0140-6736(14)61601-9
  6. Webster AC, Nagler EV, Morton RL, Masson P. Chronic kidney disease. Lancet. 2017;389(10075):1238-1252. doi:10.1016/s0140-6736(16)32064-5
  7. World Health Organization (WHO). Projections of Mortality and Causes of Death, 2015 and 2030. http://www.who.int/healthinfo/global_burden_disease/projections/en/.  Accessed December 3, 2017.
  8. Nicholson T, Roderick P. International study of health care organization and financing of renal services in England and Wales. Int J Health Care Finance Econ. 2007;7(4):283-299. doi:10.1007/s10754-007-9015-x
  9. Reutens AT, Atkins RC. Chronic kidney disease (CKD): the scope of the global problem. In: El Nahas AM, Levin A, eds. Chronic Kidney Disease: A Practical Guide to Understanding and Management. Oxford: Oxford University Press; 2009:39-76.
  10. Wen CP, Cheng TY, Tsai MK, et al. All-cause mortality attributable to chronic kidney disease: a prospective cohort study based on 462 293 adults in Taiwan. Lancet. 2008;371(9631):2173-2182. doi:10.1016/s0140-6736(08)60952-6
  11. Hwang SJ, Tsai JC, Chen HC. Epidemiology, impact and preventive care of chronic kidney disease in Taiwan. Nephrology (Carlton). 2010;15 Suppl 2:3-9. doi:10.1111/j.1440-1797.2010.01304.x
  12. National Health Insurance Statistical Annual Report 2018. Taiwan: National Health Insurance Administration, Ministry of Health and Welfare; 2019.
  13. Chen YR, Yang Y, Wang SC, et al. Effectiveness of multidisciplinary care for chronic kidney disease in Taiwan: a 3-year prospective cohort study. Nephrol Dial Transplant. 2013;28(3):671-682. doi:10.1093/ndt/gfs469
  14. Lin CM, Yang MC, Hwang SJ, Sung JM. Progression of stages 3b-5 chronic kidney disease--preliminary results of Taiwan national pre-ESRD disease management program in Southern Taiwan. J Formos Med Assoc. 2013;112(12):773-782. doi:10.1016/j.jfma.2013.10.021
  15. Hsieh HM, Lin MY, Chiu YW, et al. Economic evaluation of a pre-ESRD pay-for-performance programme in advanced chronic kidney disease patients. Nephrol Dial Transplant. 2017;32(7):1184-1194. doi:10.1093/ndt/gfw372
  16. Chen PM, Lai TS, Chen PY, et al. Multidisciplinary care program for advanced chronic kidney disease: reduces renal replacement and medical costs. Am J Med. 2015;128(1):68-76. doi:10.1016/j.amjmed.2014.07.042
  17. KDIGO Guidelines.  https://kdigo.org/guidelines/.  AccessedMay 1, 2020.
  18. Fraser SD, Blakeman T. Chronic kidney disease: identification and management in primary care. Pragmat Obs Res. 2016;7:21-32. doi:10.2147/por.s97310
  19. Shao SC, Chan YY, Kao Yang YH, et al. The Chang Gung Research Database-a multi-institutional electronic medical records database for real-world epidemiological studies in Taiwan. Pharmacoepidemiol Drug Saf. 2019;28(5):593-600. doi:10.1002/pds.4713
  20. 2018 Annual Report of Health Services Claims, by Health Care Organizations: National Health Insurance Administration, Ministry of Health and Welfare, Taiwan.
  21. Chen YC, Weng SF, Hsu YJ, Wei CJ, Chiu CH. Continuity of care: evaluating a multidisciplinary care model for people with early CKD via a nationwide population-based longitudinal study. BMJ Open. 2020;10(12):e041149. doi:10.1136/bmjopen-2020-041149
  22. Inker LA, Astor BC, Fox CH, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis. 2014;63(5):713-735. doi:10.1053/j.ajkd.2014.01.416
  23. Levey AS, Coresh J, Greene T, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145(4):247-254. doi:10.7326/0003-4819-145-4-200608150-00004
  24. Levey AS, Coresh J, Greene T, et al. Expressing the Modification of Diet in Renal Disease Study equation for estimating glomerular filtration rate with standardized serum creatinine values. Clin Chem. 2007;53(4):766-772. doi:10.1373/clinchem.2006.077180
  25. Stevens LA, Manzi J, Levey AS, et al. Impact of creatinine calibration on performance of GFR estimating equations in a pooled individual patient database. Am J Kidney Dis. 2007;50(1):21-35. doi:10.1053/j.ajkd.2007.04.004
  26. Wu HY, Fukuma S, Shimizu S, et al. Effects of higher quality of care on initiation of long-term dialysis in patients with CKD and diabetes. Am J Kidney Dis. 2017;70(5):666-674. doi:10.1053/j.ajkd.2017.05.020
  27. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-619. doi:10.1016/0895-4356(92)90133-8
  28. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8
  29. Fukuma S, Shimizu S, Niihata K, et al. Development of quality indicators for care of chronic kidney disease in the primary care setting using electronic health data: a RAND-modified Delphi method. Clin Exp Nephrol. 2017;21(2):247-256. doi:10.1007/s10157-016-1274-8
  30. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(2 Suppl 1):S1-266.
  31. Tsai WC, Wu HY, Peng YS, et al. Risk factors for development and progression of chronic kidney disease: a systematic review and exploratory meta-analysis. Medicine (Baltimore). 2016;95(11):e3013. doi:10.1097/md.0000000000003013
  32. Yang JY, Huang JW, Chen L, et al. Frequency of early predialysis nephrology care and postdialysis cardiovascular events. Am J Kidney Dis. 2017;70(2):164-172. doi:10.1053/j.ajkd.2016.12.018
  33. Bello AK, Levin A, Manns BJ, et al. Effective CKD care in European countries: challenges and opportunities for health policy. Am J Kidney Dis. 2015;65(1):15-25. doi:10.1053/j.ajkd.2014.07.033
  34. Karunaratne K, Stevens P, Irving J, et al. The impact of pay for performance on the control of blood pressure in people with chronic kidney disease stage 3-5. Nephrol Dial Transplant. 2013;28(8):2107-2116. doi:10.1093/ndt/gft093
  35. Hsieh HM, Tsai SL, Shin SJ, Mau LW, Chiu HC. Cost-effectiveness of diabetes pay-for-performance incentive designs. Med Care. 2015;53(2):106-115. doi:10.1097/mlr.0000000000000264
  36. Hsieh HM, Shin SJ, Tsai SL, Chiu HC. Effectiveness of pay-for-performance incentive designs on diabetes care. Med Care. 2016;54(12):1063-1069. doi:10.1097/mlr.0000000000000609
  37. Yen SM, Kung PT, Sheen YJ, Chiu LT, Xu XC, Tsai WC. Factors related to continuing care and interruption of P4P program participation in patients with diabetes. Am J Manag Care. 2016;22(1):e18-30. 
  38. Campbell SM, Reeves D, Kontopantelis E, Sibbald B, Roland M. Effects of pay for performance on the quality of primary care in England. N Engl J Med. 2009;361(4):368-378. doi:10.1056/NEJMsa0807651
  39. Liao PJ, Lin TY, Wang TC, et al. Long-term and interactive effects of pay-for-performance interventions among diabetic nephropathy patients at the early chronic kidney disease stage. Medicine (Baltimore). 2016;95(14):e3282. doi:10.1097/md.0000000000003282
  40. Yang WC, Hwang SJ. Incidence, prevalence and mortality trends of dialysis end-stage renal disease in Taiwan from 1990 to 2001: the impact of national health insurance. Nephrol Dial Transplant. 2008;23(12):3977-3982. doi:10.1093/ndt/gfn406
  41. 2018 Annual Report on Kidney Disease in Taiwan. National Health Research Institutes and Taiwan Society of Nephrology; 2019.
  42. Ogundeji YK, Bland JM, Sheldon TA. The effectiveness of payment for performance in health care: a meta-analysis and exploration of variation in outcomes. Health Policy. 2016;120(10):1141-1150. doi:10.1016/j.healthpol.2016.09.002
  43. Martin B, Jones J, Miller M, Johnson-Koenke R. Health care professionals' perceptions of pay-for-performance in practice: a qualitative metasynthesis. Inquiry. 2020;57:46958020917491. doi:10.1177/0046958020917491
  44. Sawhney S, Marks A, Fluck N, Levin A, Prescott G, Black C. Intermediate and long-term outcomes of survivors of acute kidney injury episodes: a large population-based cohort study. Am J Kidney Dis. 2017;69(1):18-28. doi:10.1053/j.ajkd.2016.05.018
  45. Mendelson A, Kondo K, Damberg C, et al. The effects of pay-for-performance programs on health, health care use, and processes of care: a systematic review. Ann Intern Med. 2017;166(5):341-353. doi:10.7326/m16-1881
Volume 11, Issue 8
August 2022
Pages 1307-1315
  • Receive Date: 17 July 2020
  • Revise Date: 14 January 2021
  • Accept Date: 14 March 2021
  • First Publish Date: 13 April 2021