Skip to main content

Advertisement

SpringerLink
Log in

Informing management on the future structure of hospital care: an extrapolation of trends in demand and costs in lung diseases

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

Abstract

Objective

The planning of health care management benefits from understanding future trends in demand and costs. In the case of lung diseases in the national German hospital market, we therefore analyze the current structure of care, and forecast future trends in key process indicators.

Methods

We use standardized, patient-level, activity-based costing from a national cost calculation data set of respiratory cases, representing 11.9–14.1 % of all cases in the major diagnostic category “respiratory system” from 2006 to 2012. To forecast hospital admissions, length of stay (LOS), and costs, the best adjusted models out of possible autoregressive integrated moving average models and exponential smoothing models are used.

Results

The number of cases is predicted to increase substantially, from 1.1 million in 2006 to 1.5 million in 2018 (+2.7 % each year). LOS is expected to decrease from 7.9 to 6.1 days, and overall costs to increase from 2.7 to 4.5 billion euros (+4.3 % each year). Except for lung cancer (−2.3 % each year), costs for all respiratory disease areas increase: surgical interventions +9.2 % each year, COPD +3.9 %, bronchitis and asthma +1.7 %, infections +2.0 %, respiratory failure +2.6 %, and other diagnoses +8.5 % each year. The share of costs of surgical interventions in all costs of respiratory cases increases from 17.8 % in 2006 to 30.8 % in 2018.

Conclusions

Overall costs are expected to increase particularly because of an increasing share of expensive surgical interventions and rare diseases, and because of higher intensive care, operating room, and diagnostics and therapy costs.

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

Similar content being viewed by others

References

  1. Halbert, R.J., Natoli, J.L., Gano, A., Badamgarav, E., Buist, A.S., Mannino, D.M.: Global burden of COPD: systematic review and meta-analysis. Eur Respir J 28(3), 523–532 (2006). doi:10.1183/09031936.06.00124605

    Article  CAS  PubMed  Google Scholar 

  2. Buist, A.S., McBurnie, M.A., Vollmer, W.M., Gillespie, S., Burney, P., Mannino, D.M., Menezes, A.M., Sullivan, S.D., Lee, T.A., Weiss, K.B., Jensen, R.L., Marks, G.B., Gulsvik, A., Nizankowska-Mogilnicka, E.: International variation in the prevalence of COPD (the BOLD Study): a population-based prevalence study. Lancet 370(9589), 741–750 (2007). doi:10.1016/s0140-6736(07)61377-4

    Article  PubMed  Google Scholar 

  3. Braman, S.S.: The global burden of asthma. Chest 130(1 Suppl), 4s–12s (2006). doi:10.1378/chest.130.1_suppl.4S

    Article  PubMed  Google Scholar 

  4. Mannino, D.M., Buist, A.S.: Global burden of COPD: risk factors, prevalence, and future trends. Lancet 370(9589), 765–773 (2007). doi:10.1016/s0140-6736(07)61380-4

    Article  PubMed  Google Scholar 

  5. Waatevik, M., Skorge, T.D., Omenaas, E., Bakke, P.S., Gulsvik, A., Johannessen, A.: Increased prevalence of chronic obstructive pulmonary disease in a general population. Respir Med 107(7), 1037–1045 (2013). doi:10.1016/j.rmed.2013.04.008

    Article  PubMed  Google Scholar 

  6. Bahadori, K., Doyle-Waters, M.M., Marra, C., Lynd, L., Alasaly, K., Swiston, J., FitzGerald, J.M.: Economic burden of asthma: a systematic review. BMC Pulm Med 9(1), 24 (2009). doi:10.1186/1471-2466-9-24

    Article  PubMed  PubMed Central  Google Scholar 

  7. D’Souza, A.O., Shah, M., Dhamane, A.D., Dalal, A.A.: Clinical and economic burden of COPD in a Medicaid population. COPD 11(2), 212–220 (2014). doi:10.3109/15412555.2013.836168

    Article  PubMed  Google Scholar 

  8. Andersen, H., Lampela, P., Nevanlinna, A., Saynajakangas, O., Keistinen, T.: High hospital burden in overlap syndrome of asthma and COPD. Clin Respir J 7(4), 342–346 (2013). doi:10.1111/crj.12013

    Article  PubMed  Google Scholar 

  9. Eurostat: Hospital discharges by diagnosis, in-patients, total number (hlth_co_disch1) (2014). http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database. Accessed 9 Nov 2014

  10. Statistisches Bundesamt [The Federal Statistical Office]: Fallpauschalenbezogene Krankenhausstatistik, Fachserie 12 Reihe 6.4 (2013). https://www.destatis.de/DE/Publikationen/Thematisch/Gesundheit/Krankenhaeuser/FallpauschalenKrankenhaus.html. Accessed 9 Nov 2014

  11. European Respiratory Society: European Lung White Book (2013). http://www.erswhitebook.org/chapters/the-burden-of-lung-disease/. Accessed 9 Nov 2014

  12. Ford, E.S.: Hospital discharges, readmissions, and emergency department visits for chronic obstructive pulmonary disease or bronchiectasis among US adults: findings from the Nationwide Inpatient Sample 2001–2012 and Nationwide Emergency Department Sample 2006–2011. Chest (2014). doi:10.1378/chest.14-2146

    Google Scholar 

  13. Lorenzoni, L., Belloni, A., Sassi, F.: Health-care expenditure and health policy in the USA versus other high-spending OECD countries. Lancet 384(9937), 83–92 (2014). doi:10.1016/s0140-6736(14)60571-7

    Article  PubMed  Google Scholar 

  14. Schulz, E., Leidl, R., Konig, H.H.: The impact of ageing on hospital care and long-term care–the example of Germany. Health Policy Amst Neth 67(1), 57–74 (2004)

    Article  Google Scholar 

  15. Strunk, B.C., Ginsburg, P.B., Banker, M.I.: The effect of population aging on future hospital demand. Health Aff Proj Hope 25(3), w141–w149 (2006). doi:10.1377/hlthaff.25.w141

    Article  Google Scholar 

  16. Stark, D., Mould, D., Schweikert, A.: 5 steps to creating a forecast. J Healthc Financ Manag Assoc 62(4), 100–105 (2008)

    Google Scholar 

  17. Institute for the Hospital Remuneration System (InEK): G-DRG Report-Browser (2014). http://www.g-drg.de/cms/Archiv. Accessed 9 Nov 2014

  18. Vogl, M.: Assessing DRG cost accounting with respect to resource allocation and tariff calculation: the case of Germany. Health Econ Rev 2(1), 15 (2012). doi:10.1186/2191-1991-2-15

    Article  PubMed  PubMed Central  Google Scholar 

  19. Vogl, M.: Improving patient-level costing in the English and the German ‘DRG’ system. Health Policy 109(3), 290–300 (2013)

    Article  PubMed  Google Scholar 

  20. Vogl, M.: Hospital financing: calculating inpatient capital costs in Germany with a comparative view on operating costs and the English costing scheme. Health Policy 115(2–3), 141–151 (2014). doi:10.1016/j.healthpol.2014.01.013

    Article  PubMed  Google Scholar 

  21. Kaplan, R.S., Anderson, S.R.: Time-driven activity-based costing: a simpler and more powerful path to higher profits. Harvard Business Press, Boston (2007)

    Google Scholar 

  22. Schreyogg, J., Tiemann, O., Busse, R.: Cost accounting to determine prices: how well do prices reflect costs in the German DRG-system? Health care Manag Sci 9(3), 269–279 (2006)

    Article  PubMed  Google Scholar 

  23. Institut für das Entgeltsystem im Krankenhaus (InEK): Abschlussbericht zur Weiterentwicklung des G-DRG System für das Jahr 2011. http://www.g-drg.de/cms/Archiv (2011). Accessed 19 Mar 2015

  24. Kimberly, J.R., de Pouvourville, G., D’Aunno, T.: The globalization of managerial innovation in health care. Cambridge University Press, Cambridge (2009)

    Google Scholar 

  25. Busse, R., Geissler, A., Quentin, W., Wiley, M.W.: Diagnosis-related groups in Europe: moving towards transparency, efficiency and quality in hospitals. McGraw-Hill, Open University Press, New York (2011)

    Google Scholar 

  26. Massacci, D.: Predicting the distribution of stock returns: model formulation, statistical evaluation, VaR analysis and economic significance. J Forecast 34(3), 191–208 (2015). doi:10.1002/for.2332

    Article  Google Scholar 

  27. Wohlrabe, K., Buchen, T.: Assessing the macroeconomic forecasting performance of boosting: evidence for the United States, the Euro area and Germany. J Forecast 33(4), 231–242 (2014). doi:10.1002/for.2293

    Article  Google Scholar 

  28. Jones, S.S., Thomas, A., Evans, R.S., Welch, S.J., Haug, P.J., Snow, G.L.: Forecasting daily patient volumes in the emergency department. Acad Emerg Med: Off J Soc Acad Emerg Med 15(2), 159–170 (2008). doi:10.1111/j.1553-2712.2007.00032.x

    Article  Google Scholar 

  29. Hoot, N.R., Epstein, S.K., Allen, T.L., Jones, S.S., Baumlin, K.M., Chawla, N., Lee, A.T., Pines, J.M., Klair, A.K., Gordon, B.D., Flottemesch, T.J., LeBlanc, L.J., Jones, I., Levin, S.R., Zhou, C., Gadd, C.S., Aronsky, D.: Forecasting emergency department crowding: an external, multicenter evaluation. Ann Emerg Med 54(4), 514–522.e519 (2009). doi:10.1016/j.annemergmed.2009.06.006

    Article  PubMed  PubMed Central  Google Scholar 

  30. Boyle, J., Jessup, M., Crilly, J., Green, D., Lind, J., Wallis, M., Miller, P., Fitzgerald, G.: Predicting emergency department admissions. Emerg Med J EMJ 29(5), 358–365 (2012). doi:10.1136/emj.2010.103531

    Article  PubMed  Google Scholar 

  31. Koestler, D.C., Ombao, H., Bender, J.: Ensemble-based methods for forecasting census in hospital units. BMC Med Res Methodol 13, 67 (2013). doi:10.1186/1471-2288-13-67

    Article  PubMed  PubMed Central  Google Scholar 

  32. Limb, M.: Hospitals forecast a rise in emergency admissions, while commissioners forecast a fall. BMJ Clin Res Ed 349, g4699 (2014). doi:10.1136/bmj.g4699

    Google Scholar 

  33. Heidenreich, P.A., Trogdon, J.G., Khavjou, O.A., Butler, J., Dracup, K., Ezekowitz, M.D., Finkelstein, E.A., Hong, Y., Johnston, S.C., Khera, A., Lloyd-Jones, D.M., Nelson, S.A., Nichol, G., Orenstein, D., Wilson, P.W., Woo, Y.J.: Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation 123(8), 933–944 (2011). doi:10.1161/CIR.0b013e31820a55f5

    Article  PubMed  Google Scholar 

  34. Soyiri, I.N., Reidpath, D.D.: Evolving forecasting classifications and applications in health forecasting. Int J Gen Med 5, 381–389 (2012). doi:10.2147/ijgm.s31079

    Article  PubMed  PubMed Central  Google Scholar 

  35. Soyiri, I.N., Reidpath, D.D.: An overview of health forecasting. Environ Health Prev Med 18(1), 1–9 (2013). doi:10.1007/s12199-012-0294-6

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cote, M.J., Tucker, S.L.: Four methodologies to improve healthcare demand forecasting. J Healthc Financ Manag Assoc 55(5), 54–58 (2001)

    CAS  Google Scholar 

  37. Box, G.E.P., Jenkins, G.M., Reinsel, G.C.: Time series analysis: forecasting and control, 4th edn. Wiley, New Jersey (2008)

    Book  Google Scholar 

  38. Gardner, E.S.: Exponential smoothing: the state of the art. J Forecast 4(1), 1–28 (1985)

    Article  Google Scholar 

  39. Hyndman, R.J., Athanasopoulos, G.: Forecasting: principles and practice (2013). https://www.otexts.org/book/fpp. Accessed 19 Nov 2014

  40. Billah, B., King, M.L., Snyder, R.D., Koehler, A.B.: Exponential smoothing model selection for forecasting. Int J Forecast 22(2), 239–247 (2006)

    Article  Google Scholar 

  41. Gardner, E.S., Dannenbring, D.G.: Forecasting with exponential smoothing: some guidelines for model selection. Decis Sci 11(2), 370–383 (1980)

    Article  Google Scholar 

  42. Statistisches Bundesamt [The Federal Statistical Office]: Verbraucherpreisindizes [consumer price index] (2014). https://www.destatis.de/DE/ZahlenFakten/GesamtwirtschaftUmwelt/Preise/Verbraucherpreisindizes/Verbraucherpreisindizes.html. Accessed 19 Nov 2014

  43. Samet, J.M., Avila-Tang, E., Boffetta, P., Hannan, L.M., Olivo-Marston, S., Thun, M.J., Rudin, C.M.: Lung cancer in never smokers: clinical epidemiology and environmental risk factors. Clin Cancer Res Off J Am Assoc Cancer Res 15(18), 5626–5645 (2009). doi:10.1158/1078-0432.ccr-09-0376

    Article  Google Scholar 

  44. Lamprecht, B., McBurnie, M.A., Vollmer, W.M., Gudmundsson, G., Welte, T., Nizankowska-Mogilnicka, E., Studnicka, M., Bateman, E., Anto, J.M., Burney, P., Mannino, D.M., Buist, S.A.: COPD in never smokers: results from the population-based burden of obstructive lung disease study. Chest 139(4), 752–763 (2011). doi:10.1378/chest.10-1253

    Article  PubMed  PubMed Central  Google Scholar 

  45. Deutsche Gesellschaft für Gesundheitsökonomie: Perspectives of reforming hospital financing in Germany [in German]. Gesundheitsökonomie und Qualitätsmanagement 19(6), 248–249 (2014)

    Article  Google Scholar 

  46. Appleby, J.: Do we have too many hospitals? BMJ Clin Res Ed. 348, (2014). doi:10.1136/bmj.g1374

  47. Pokhrel, S., Evers, S., Leidl, R., Trapero-Bertran, M., Kalo, Z., Vries, H., Crossfield, A., Andrews, F., Rutter, A., Coyle, K., Lester-George, A., West, R., Owen, L., Jones, T., Vogl, M., Radu-Loghin, C., Voko, Z., Huic, M., Coyle, D.: EQUIPT: protocol of a comparative effectiveness research study evaluating cross-context transferability of economic evidence on tobacco control. BMJ open 4(11), e006945 (2014). doi:10.1136/bmjopen-2014-006945

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Conflict of interest

The authors declare that they have no conflicts of interest.

Author information

Authors and Affiliations

  1. Helmholtz Zentrum München, German Research Center for Environmental Health, Member of the German Center for Lung Research (DZL), Institute of Health Economics and Health Care Management (IGM), PO Box 1129, 85758, Neuherberg, Munich, Germany

    Matthias Vogl & Reiner Leidl

  2. Ludwig-Maximilians-Universität München, Munich School of Management, Institute of Health Economics and Health Care Management and Munich Centre of Health Sciences, Munich, Germany

    Matthias Vogl & Reiner Leidl

Authors
  1. Matthias Vogl
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reiner Leidl
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthias Vogl.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vogl, M., Leidl, R. Informing management on the future structure of hospital care: an extrapolation of trends in demand and costs in lung diseases. Eur J Health Econ 17, 505–517 (2016). https://doi.org/10.1007/s10198-015-0699-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-015-0699-4

Keywords

JEL Classification

Search

Navigation