This document summarizes a model for predicting market shares of competing care providers for the elderly in Flanders over a 10-year period from 2010 to 2020. The model divides elderly care needs into 4 tiers based on level of dependency. It considers various care providers that compete within and between the tiers, including home care, assisted living facilities, retirement homes, and e-care platforms. The model mechanisms include patient flows between tiers and competition within tiers. Simulation results indicate trends in how competition may evolve and the impact of limited capacity on waiting lists. Conclusions discuss using the model to forecast market shares and further techno-economic analysis of e-care platforms.

1. Modeling Market Shares of Competing (e)Care Providers J. Van Ooteghem , T. Tesch, S. Verbrugge, A. Ackaert, D. Colle, M. Pickavet, P. Demeester eHealth2009, Istanbul September 24th 2009

2. IBBT TranseCare project Transparant ICT platforms for eCare Project duration 2007 - 2010 Project website http://projects.ibbt.be/TranseCare

3. CONCEPTUAL FRAMEWORK AND MODEL MECHANISMS Modeling Market Shares of Competing (e)Care Providers

4. Competing (e)Care model

5. Tier 3 Characteristics Elderly requiring near constant (medical) attention Competing care providers Retirement Homes (RH) Multi-residence housing facilities intended for highest-level dependency elderly WaitingList (WL) High-dependent elderly not able to receive adequate care at the time of need, due to capacity limitations

6. Tier 2 Characteristics Elderly requiring extended external attention Staying in their private homes is therefore impossible Competing care providers Service Flats (SF) Assisted living facilities for elderly already needing a certain level of continued care Retirement Homes (RH) WaitingList (WL)

7. Tier 1 Characteristics Elderly requiring (some) external attention and care They can stay in their own homes Competing care providers HomeCare (HC) On-demand supportive care provided in the patient's home by professionals HomeCare augmented with eCarePlatform (HC+eCP) Professional homecare facilitated by an eCarePlatform

8. Tier 0 Characteristics Elderly still living in their private homes No need for (professional) homecare Competing care providers SelfSustained (SS) Independent living eCarePlatform (eCP) Own initiative for subscribing to an eCarePlatform

9. Model mechanisms Vertically Inflow (Tier 0) Outflow (Death) Churn between services Horizontally Increased level of care Tier 0 Tier 1

10. SIMULATION RESULTS Modeling Market Shares of Competing (e)Care Providers

11. Case study Flemish situation 10 year period: 2010 – 2020 Data Obtained from public sources Model refined and assessed by professionals Goal To indicate the trend in how competition between care providers in the sector will evolve

12. Capacity Capacity is limited for service flats and retirement homes Uptake of eCarePlatform services has a positive effect on the length of the waiting list

13. Market shares of competing care providers Tier 3 Tier 1 Tier 2 Tier 0

14. CONCLUSIONS FUTURE WORK Modeling Market Shares of Competing (e)Care Providers

15. Conclusions Conceptual framework Allows forecasting evolution of market shares of competing care providers Market mechanisms Based on the dependency level of the elderly Competition within tiers (churn) Capacity Tier 3 capacity always needs to be guaranteed Waiting list problem situated in Tier 2 Market shares eCarePlatform will gain market share as soon as efficiency and added value has been proved.

16. Future work Techno-economic analysis of eCare platform business cases Input from the presented model eCare value network models Quantitative cost/benefit model Multi-actor analysis

17. CTTE 2010 Ghent, Belgium June 16-18, 2010 Conference of Telecommunication, Media and Internet Techno-Economics Call for papers: user and service adoption pricing strategies for new services value network analysis and competition opportunities regulatory impacts on industry structure and competition OPEX and CAPEX models for network and service providers direct and indirect revenue modeling comparison of novel versus classic investment decision techniques sensitivity studies, risk analysis and real options multi-actor analysis game theoretic analysis http://www.ctte-conference.org/

18. Thank you for your attention Questions ? Jan Van Ooteghem [email_address] www.ibcn.intec.ugent.be/te INTEC Broadband Communication Networks (IBCN) Department of Information Technology (INTEC) Ghent University - IBBT