Skip to main content

Advertisement

SpringerLink
Log in

Are quality-adjusted medical prices declining for chronic disease? Evidence from diabetes care in four health systems

  • Original Paper
  • Published:
The European Journal of Health Economics Aims and scope Submit manuscript

Abstract

Improvements in medical treatment have contributed to rising health spending. Yet there is relatively little evidence on whether the spending increase is “worth it” in the sense of producing better health outcomes of commensurate value—a critical question for understanding productivity in the health sector and, as that sector grows, for deriving an accurate quality-adjusted price index for an entire economy. We analyze individual-level panel data on medical spending and health outcomes for 123,548 patients with type 2 diabetes in four health systems: Japan, The Netherlands, Hong Kong and Taiwan. Using a “cost-of-living” method that measures value based on improved survival, we find a positive net value of diabetes care: the value of improved survival outweighs the added costs of care in each of the four health systems. This finding is robust to accounting for selective survival, end-of-life spending, and a range of values for a life-year or fraction of benefits attributable to medical care. Since the estimates do not include the value from improved quality of life, they are conservative. We, therefore, conclude that the increase in medical spending for management of diabetes is offset by an increase in quality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Hall [16] notes in her excellent review, “in general, the research literature shows adjusting for quality in the measurement of output in the medical sector to be quantitatively important”.

  2. One of our robustness checks also predicts the risk of major diabetes complications, using the Japanese sample and the Japan-specific risk prediction engine developed by Tanaka et al. [34].

  3. See examples and discussion in Baudot et al. [1]; Bertram et al. [2]; Fitria et al. [14]; Stadhouders et al. [31]; Tang et al. [35] (for Taiwan); and Woods et al. [41]. For Hong Kong, see Wong et al. [39, 40].

  4. We are grateful to an anonymous reviewer for suggesting this robustness check.

  5. We are grateful to an anonymous reviewer for suggesting this robustness check.

  6. Indeed, even for the European system included, when the models used for the Dutch analyses were validated in Dutch diabetes populations by independent research groups in different populations than the current dataset, it was found that UKPDS overestimates cardiovascular risk in more recent Dutch populations.

References

  1. Baudot, F.-O., Aguade, A.-S., Barnay, T., Gastaldi-Menager, C., Fagot-Campagna, A.: Impact of type 2 diabetes on health expenditure: estimation based on individual administrative data. Eur. J. Health Econ. (2019). https://doi.org/10.1007/s10198-018-1024-9

    Article  PubMed  PubMed Central  Google Scholar 

  2. Bertram, M.Y., Lauer, J.A., Joncheere, K.D., Edejer, T., Hutubessy, R., Kieny, M.-P., Hill, S.R.: Cost–effectiveness thresholds: pros and cons. Bull. World Health Organ. (2016). https://doi.org/10.2471/BLT.15.164418

    Article  PubMed  PubMed Central  Google Scholar 

  3. Chen, Y., Lee, C.T., Lin, B.J., Chang, Y., Shi, H.: Impact of pay-for-performance on mortality in diabetes patients in Taiwan. Medicine (2016). https://doi.org/10.1097/md.0000000000004197

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cheng, S., Lee, T., Chen, C.: A longitudinal examination of a pay-for-performance program for diabetes care. Med. Care 50(2), 109–116 (2012). https://doi.org/10.1097/mlr.0b013e31822d5d36

    Article  PubMed  Google Scholar 

  5. Chiu, S.Y., et al.: Faecal haemoglobin concentration influences risk prediction of interval cancers resulting from inadequate colonoscopy quality: analysis of the Taiwanese Nationwide Colorectal Cancer Screening Program. Gut. 66(2), 293–300 (2017). https://doi.org/10.1136/gutjnl-2015-310256

    Article  PubMed  Google Scholar 

  6. Chiu, SY.-H., Ying, I.C., Jui-fen, R.L., Sheng-Fong, K., Chih-Hung, C.: Developing predictive model on all-cause mortality risk for type 2 diabetes using hospital-based prospective cohort study. Working paper (2019)

  7. Cutler, D.M., McClellan, M., Newhouse, J.P., Remler, D.: Are medical prices declining? Evidence from heart attack treatments. Q. J. Econ. 113(4), 991–1024 (1998)

    Article  Google Scholar 

  8. Cutler, D.M., Rosen, A.B., Vijan, S.: The value of medical spending in the United States, 1960–2000. N. Engl. J. Med. 355(9), 920–927 (2006)

    Article  CAS  Google Scholar 

  9. Dauda, S., Dunn, A., Hall, A: Are medical care prices still declining? A systematic examination of quality-adjusted price index alternatives for medical care. CRIW/NBER Summer Institute (2019)

  10. Diabetes Prevention Program Research Group: Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N. Engl. J. Med. 346(6), 393–403 (2002)

    Article  Google Scholar 

  11. Dunn, A., Grosse, S.D., Zuvekas, S.H.: Adjusting health expenditures for inflation: a review of measures for health services research in the United States. Health Serv. Res. 53(1), 175–196 (2018)

    Article  Google Scholar 

  12. Eggleston, K.N., Shah, N.D., Smith, S.A., Wagie, A.E., Williams, A.R., Grossman, J.H., Newhouse, J.P.: The net value of health care for patients with type 2 diabetes, 1997–2005. Ann. Intern. Med. 151(6), 386–393 (2009)

    Article  Google Scholar 

  13. Eggleston, K.N., Shah, N.D., Smith, S.A., Berndt, E.R., Newhouse, J.P.: Quality adjustment for health care spending on chronic disease: evidence from diabetes treatment, 1999–2009. Am. Econ. Rev. Pap. Proc. 101(3), 206–211 (2011)

    Article  Google Scholar 

  14. Fitria, N., Asselt, A.D.I.V., Postma, M.J.: Cost-effectiveness of controlling gestational diabetes mellitus: a systematic review. Eur. J. Health Econ. 20(3), 407–417 (2018). https://doi.org/10.1007/s10198-018-1006-y

    Article  PubMed  PubMed Central  Google Scholar 

  15. GBD 2016 Lifetime Risk of Stroke Collaborators: Global, regional, and country-specific lifetime risks of stroke, 1990 and 2016. N. Engl. J. Med. 379(25), 2429–2437 (2018)

    Article  Google Scholar 

  16. Hall, Anne E.: Adjusting the measurement of the output of the medical sector for quality: a review of the literature. Med. Care Res. Rev. 74(6), 639–667 (2017)

    Article  Google Scholar 

  17. Hashimoto, C., K. Eggleston. Healthy aging and economic research on the net value of non-communicable disease management in Japan. Chapter 3 in healthy aging in Asia (K. Eggleston, editor), Stanford FSI Shorenstein Asia–Pacific Research Center publication series, Brookings Institution Press, forthcoming (2019)

  18. Hsieh, H., Gu, S., Shin, S., Kao, H., Lin, Y., Chiu, H.: Cost-effectiveness of a diabetes pay-for-performance program in diabetes patients with multiple chronic conditions. Plos One (2015). https://doi.org/10.1371/journal.pone.0133163

    Article  PubMed  PubMed Central  Google Scholar 

  19. Iizuka, T., Nishiyama, K., Chen, B., Eggleston, K. Is Preventive Care Worth the Cost? Evidence from Mandatory Checkups in Japan. NBER Working Paper No. 23413 (2017)

  20. International Diabetes Federation (2017) IDF Diabetes Atlas 2017. International Diabetes Federation (IDF), Brussels, Belgium. Available at https://diabetesatlas.org/resources/2017-atlas.html. Accessed 17 July 2019

  21. Lakdawalla, D., Shafrin, J., Lucarelli, C., Nicholson, S., Khan, Z.M., Philipson, T.J.: Quality-adjusted cost of care: a meaningful way to measure growth in innovation cost versus the value of health gains. Health Aff. 34(4), 555–561 (2015)

    Article  Google Scholar 

  22. Lu, J-f. R., Ying, I.C., Karen, E., Chih-Hung, C., Brian, C. Assessing a Taiwan pay-for-performance program for the care of diabetes patients from the net value perspective, working paper, April 2019 (2019)

  23. Manning, W.G., Mullahy, J.: Estimating log models: to transform or not to transform? J. Health Econ. 20(4), 461–494 (2001)

    Article  CAS  Google Scholar 

  24. Moran, A.E., Odden, M.C., Thanataveerat, A., Tzong, K.Y., Rasmussen, P.W., Guzman, D., Williams, L., Bibbins-Domingo, K., Coxson, P.G., Goldman, L.: Cost-effectiveness of hypertension therapy according to 2014 guidelines. N. Engl. J. Med. 372(5), 447–455 (2015). https://doi.org/10.1056/NEJMsa1406751

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. National Research Council (US) Panel to Advance a Research Program on the Design of National Health Accounts. (2010). Accounting for health and health care: approaches to measuring the sources and costs of their improvement. National Academies Press (US), Washington (DC). Available from: https://www.ncbi.nlm.nih.gov/books/NBK53346/, https://doi.org/10.17226/12938. Accessed 17 July 2019

  26. Quan, J., Li, T.K., Pang, H., Choi, C.H., Siu, S.C., Tang, S.Y., Wat, N.M., Woo, J., Johnston, J.M., Leung, G.M.: Diabetes incidence and prevalence in Hong Kong, China during 2006–2014. Diabet. Med. 34(7), 902–908 (2017). https://doi.org/10.1111/dme.13284

    Article  CAS  PubMed  Google Scholar 

  27. Quan, J., Pang, D., Li, T.K., Choi, C.H., Siu, S.C., Tang, S.Y., Wat, N.M., Woo, J., Lau, Z.Y., Tan, K.B., Leung, G.M.: Risk prediction scores for mortality, cerebrovascular, and heart disease among Chinese people with type 2 diabetes. J. Clin. Endocrinol. Metab. 104(12), 5823–5830 (2019). https://doi.org/10.1210/jc.2019-00731

    Article  PubMed  Google Scholar 

  28. Rodríguez-Sánchez, B., Feenstra, T.L., Bilo, H.J.G., Alessie, R.J.M.: Costs of people with diabetes in relation to average glucose control: an empirical approach controlling for year of onset cohorts. Eur. J. Health Econ. 20(7), 989–1000 (2019). https://doi.org/10.1007/s10198-019-01072-z

    Article  PubMed  Google Scholar 

  29. Rodríguez-Sánchez, B., Talitha, F., Henk, B., Jeroen, S. The net value of Dutch primary care management of patients with type 2 diabetes, focusing on the elderly. Presentation at EuHEA July 2018 (2018)

  30. Sakamoto, H., Rahman, M., Nomura, S., et al. Japan Health Systems Review. In: Asia Pacific Observatory on Health Systems and Policies, vol. 8(1) (2018).  http://www.searo.who.int/entity/asia_pacific_observatory/publications/hits/hit_japan/en/. Accessed 17 July 2019

  31. Stadhouders, N., Koolman, X., Dijk, C., Jeurissen, P., Adang, E.: The marginal benefits of healthcare spending in the Netherlands: estimating cost-effectiveness thresholds using a translog production function. Health Econ. 28(11), 1331–1344 (2019). https://doi.org/10.1002/hec.3946

    Article  PubMed  PubMed Central  Google Scholar 

  32. Taiwan Health Promotion Administration, 2016. https://www.hpa.gov.tw/Pages/Detail.aspx?nodeid=1090&pid=6426. Accessed on 14 Apr 2019

  33. Taiwan National Health Insurance Administration, 2018. https://www.nhi.gov.tw/Content_List.aspx?n=806314145D8E1187&topn=CDA985A80C0DE710. Accessed on 14 Apr 2019

  34. Tanaka, S., Sachiko, T., Satoshi, I., for the Japan Diabetes Complications Study Group and the Japanese Elderly Diabetes Intervention Trial Group, et al.: Predicting Macro- and microvascular complications in type 2 diabetes. Diabetes Care. 36(5), 1193–1199 (2013)

    Article  Google Scholar 

  35. Tang, C.-H., Cheng, W.F., Jiang, J.-H., You, S.L., Huang, L.-W., Hsieh, J.-Y., Lee, C.: Cost-effectiveness analysis of human papillomavirus vaccination in adolescent girls in Taiwan. Asian Pac. J. Cancer Prev. 20(5), 1377–1387 (2019). https://doi.org/10.31557/apjcp.2019.20.5.1377

    Article  PubMed  PubMed Central  Google Scholar 

  36. Van den Berg, M., Heijink, R., Zwakhals, L., Verkleij, H., Westert, G.: Health care performance in the Netherlands: easy access, varying quality, rising costs. Eurohealth 16(4), 27 (2011)

    Google Scholar 

  37. Van Der Heijden, A.A., Ortegon, M.M., Niessen, L.W., Nijpels, G., Dekker, J.M.: Prediction of coronary heart disease risk in a general, pre-diabetic, and diabetic population during 10 years of follow-up: accuracy of the Framingham, SCORE, and UKPDS risk functions: The Hoorn Study. Diabetes Care 32(11), 2094–2098 (2009)

    Article  Google Scholar 

  38. Wamble, D., Ciarametaro, M., Houghton, K., Ajmera, M., Dubois, R.W.: What’s been the bang for the buck? Cost-effectiveness of health care spending across selected conditions in the US. Health Aff. 38(1), 68–75 (2019)

    Article  Google Scholar 

  39. Wong, I.O., Kuntz, K.M., Cowling, B.J., Lam, C.L., Leung, G.M.: Cost effectiveness of mammography screening for Chinese women. Cancer 110(4), 885–895 (2007). https://doi.org/10.1002/cncr.22848

    Article  PubMed  Google Scholar 

  40. Wong, Carlos K.H., Lang, Brian H.H., Guo, Vivian Y.W., Lam, Cindy L.K.: Possible impact of incremental cost-effectiveness ratio (ICER) on decision making for cancer screening in Hong Kong: a systematic review. Appl. Health Econ. Health Pol. 14(6), 647–657 (2016). https://doi.org/10.1007/s40258-016-0266-x.)

    Article  Google Scholar 

  41. Woods, B., Revill, P., Sculpher, M., Claxton, K.: Country-level cost-effectiveness thresholds: initial estimates and the need for further research. Value Health 19(8), 929–935 (2016). https://doi.org/10.1016/j.jval.2016.02.017

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to the individuals and data providers for allowing access to the individual-level data and to our comparative health system team coauthors for the individual system-level analyses and their ability to undertake this comparative study. Karen Eggleston gratefully acknowledges support from a Stanford FSI Shorenstein Asia-Pacific Research Center faculty research award; for the Japan study, Toshiaki Iizuka, Brian Chen and Karen Eggleston gratefully acknowledge funding from the Abe Fellowship Program, JSPS Bilateral Open Partnership Joint Research Projects, and a Shorenstein APARC faculty research award; for the Netherlands study, Beatriz Rodriguez-Sanchez, Talitha Feenstra, and Jeroen N. Struijs gratefully acknowledge Professor H. Bilo for allowing access to the ZODIAC data, and Chantal van Tilburg and Mirte van Galen from VEKTIS for providing hospitality to work on the linked dataset; for the Hong Kong study, Jianchao Quan, Janet Tin Kei Lam, and Gabriel Leung gratefully acknowledge funding from Research Grants Council of the Hong Kong SAR, China (Project no. HKU 27112518) and thank the Hospital Authority for providing data; and for the Taiwan study, Jui-fen Rachel Lu, Ying Isabel Chen, Chih-Hung Chen, Brian Chen and Karen Eggleston gratefully acknowledge Chang Gung Memorial Hospital for providing the patient-level data for analyses and grant funding support from the Taiwan Ministry of Science and Technology (MOST 100-2632-H-182-001-MY2, 104-2918-I-182-002).

Author information

Authors and Affiliations

  1. Stanford University and NBER, Stanford, USA

    Karen Eggleston

  2. University of South Carolina, Columbia, USA

    Brian K. Chen

  3. Chang Gung Memorial Hospital, Keelung, Taiwan

    Chih-Hung Chen

  4. National Taiwan University, Taipei, Taiwan

    Ying Isabel Chen

  5. National Institute for Public Health and Environment and University of Groningen, Groningen, The Netherlands

    Talitha Feenstra

  6. University of Tokyo, Tokyo, Japan

    Toshiaki Iizuka

  7. University of Hong Kong, Patrick Manson Building, 7 Sassoon Road, Hong Kong SAR, China

    Janet Tin Kei Lam, Gabriel M. Leung & Jianchao Quan

  8. Chang Gung University, Taoyuan, Taiwan

    Jui-fen Rachel Lu

  9. Faculty of Law and Social Sciences, University of Castilla la Mancha, Toledo, Spain

    Beatriz Rodriguez-Sanchez

  10. National Institute for Public Health and Environment and Leiden University Medical Center, Campus The Hague, The Hague, The Netherlands

    Jeroen N. Struijs

  11. Harvard University and NBER, Cambridge, USA

    Joseph P. Newhouse

Authors
  1. Karen Eggleston
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brian K. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chih-Hung Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ying Isabel Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Talitha Feenstra
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Toshiaki Iizuka
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Janet Tin Kei Lam
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Gabriel M. Leung
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jui-fen Rachel Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Beatriz Rodriguez-Sanchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jeroen N. Struijs
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Jianchao Quan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Joseph P. Newhouse
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianchao Quan.

Ethics declarations

Conflict of interest

The authors have nothing to disclose.

Ethical review

The analysis for Japan was reviewed and approved by the Stanford University Institutional Review Board (IRB). For the Netherlands, since this research concerned analysis on secondary and fully anonymous data, no METC approval was required according to Dutch law. The analysis plan was reviewed and approved by both data sources, for VEKTIS by all Dutch health care insurers and for Zodiac by the Zodiac board. The Hong Kong analyses were approved by the seven Hong Kong Hospital Authority cluster IRBs. The analysis for Taiwan was approved by the Chang Gung Memorial Hospital IRB.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 530 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Eggleston, K., Chen, B.K., Chen, CH. et al. Are quality-adjusted medical prices declining for chronic disease? Evidence from diabetes care in four health systems. Eur J Health Econ 21, 689–702 (2020). https://doi.org/10.1007/s10198-020-01164-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-020-01164-1

Keywords

JEL Classification

Search

Navigation