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Harri Antikainen: Taxi ride sharing and health care accessibility


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Geospatial data in health and welfare research -seminar in Helsinki 23rd October 2018.

Published in: Health & Medicine
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Harri Antikainen: Taxi ride sharing and health care accessibility

  1. 1. Taxi ride sharing and health care accessibility Harri Antikainen Geography Research Unit University of Oulu
  2. 2. University of Oulu In social & health care, taxi transport can be paid for by several authorities ‒ Kela*:  Reimburses costs of traveling to hospital or other health care or rehabilitation sites, excluding a copayment of 25 € per trip  Health Insurance Act (Sairausvakuutuslaki, SVL) ‒ Municipalities:  Transport services for severely disabled persons: Services and Assistance for the Disabled Act (Vammaispalvelulaki, VPL)  Transport services supporting personal mobility for people not capable of using regular public transport, but who are not severely disabled: Social Welfare Act (Sosiaalihuoltolaki, SHL) *) The Social Insurance Institution of Finland2
  3. 3. University of Oulu The use of transport paid for by public funds has been increasing until recent years Tillman, P. & Miettinen, J. (2016). Kelan matkakorvausten kohdentuminen vammaispalvelulain ja sosiaalihuoltolain mukaisiin kuljetuksiin oikeutetuille. Kela, Työpapereita 102. Number of persons entitled to transport / reimbursement, 1995-2014 3
  4. 4. University of Oulu Modes of Kela- reimbursed transportation ‒ Taxi is, by far, the most important means of transportation for Kela- reimbursed trips Number of trips (2015) Reimbursed euros (2015) Data: Kelan korvaamat matkat vuonna 2015, Kelan Tilastokooste4
  5. 5. University of Oulu Reimbursement for travel costs paid by Kela, 1964-2017 Data: ‒ The rise of reimbursement costs ceased after 2012  Copayments for travel expenses raised several times, from 9.25 € in 2012 to 25 € in 2016  Regional dispatch centers arranging shared taxi transport, in operation 2010 → Map adapted from: Kelan korvaamat matkat vuonna 2015, Kelan Tilastokooste5
  6. 6. University of Oulu Regional taxi dispatch centers and taxi ride sharing ‒ In order to reduce costs, regional dispatch centers seek to combine Kela-reimbursed taxi trips whenever possible and reasonable  Trips having the same destination  Maximum of one hour of additional waiting time due to ride sharing allowed  Travel time may increase at most two-fold, or by two hours ‒ In 2015, Kela saved approximately 16 million euros in reimbursement claims due to taxi ride sharing Data: Kelan korvaamat matkat vuonna 2015, Kelan Tilastokooste Saving in reimbursement costs as a result of taxi ride sharing, 2011-2015 6
  7. 7. University of Oulu Our research projects funded by 1) Taxi ride-sharing in Tampere region 2015  Report released in Sep 2018 2) Shareability of taxi transport paid for by public funds (Kela and municipalities)  Currently ongoing research  Oulu / North Ostrobothnia7
  8. 8. University of Oulu Taxi ride sharing in Tampere region ‒ Research questions: 1) How much travel expenses were saved by actual taxi trip sharing in Tampere region? 2) How much more potential there was for ride sharing? ‒ Data:  700.000 Kela-reimbursed taxi trips in Tampere region 2015 (obtained from Kela) → Total taxi costs in this dataset: 36 M€, reimbursement total: 30 M€ ‒ Methods & software:  Shortest path analysis  Graph-based methods (shareability graph, maximum weighted matching of graph)  ArcGIS, Python, NetworkX Kela-reimbursed taxi trips / 100 inhabitants, 2015 Etelä-Pohjanmaa / South Ostrobothnia Pirkanmaa Kanta-Häme Päijät-Häme 8
  9. 9. University of Oulu Actual taxi ride sharing in Tampere region, 2015 ‒ 12% of trips were shared in reality ‒ Highest taxi ride sharing rate was found in South Ostrobothnia ‒ The destination of more than 50% of shared taxi trips was a central hospital ‒ Approximately 3.2 million € were saved in taxi fares due to ride sharing  Calculated as a difference between the cost of shared ride and the sum of costs of taxi trips driven separately  In line with Kela’s own estimate Ride sharing rate of Kela-reimbursed trips by region 9
  10. 10. University of Oulu Shareability graph analysis ‒ A method for analyzing taxi ride-sharing potential ‒ A shareability graph is a model representing shareability between pairs of trips ‒ In order to construct the graph, each pair of trips needs to be evaluated for shareability ‒ Once constructed, maximal matching can be used to determine the best possible set of pairwise trip combinations  Example on the left: sharing of trips 1 & 5 and 2 & 3 provide the highest possible saving  Limited to pairwise combinations only! Illustration of shareability graph: 10
  11. 11. University of Oulu Results of taxi ride-sharing potential in Tampere region, 2015 – In Tampere region, almost 50% of non- shared trips could have been combined with another non-shared trip (in a 60-minute time window) – Potential for up to 5 million euros of additional savings in taxi fares – Interestingly, inter-regional trip sharing would have increased savings only marginally Potential shareability rate of non-shared taxi trips, in a one-hour time window 11
  12. 12. University of Oulu Lengths of shared trips 12 Trips shared in reality Trips that could have potentially been shared
  13. 13. University of Oulu Our current research project funded by Kela ‒ Taxi trip data obtained from:  Kela: Kela-reimbursed taxi trips in North Ostrobothnia, 2016 (n = ca. 243.000 trips)  City of Oulu: VPL-based trips, 2016 (n = ca. 108.000 trips) ‒ Objectives:  Evaluate the simultaneous use of Kela and VPL transport  To what extent could Kela and VPL trips be shared, in theory?  Develop a GIS-based ride-sharing tool capable of handling more than two trips at a time 13
  14. 14. University of Oulu SVL and VPL transport often used by same people ‒ 53% of VPL clients (n = 934) in Oulu also used taxi transportation reimbursed by Kela (SVL), in 2016  These clients made about a half of all VPL trips in Oulu, and 10% of Kela-reimbursed trips in North Ostrobothnia 14 Numberoftrips
  15. 15. University of Oulu Trip destinations ‒ Destinations of Kela and VPL- based trips are different (as it should be) ‒ Kela (SVL) trip destinations are typically:  University hospital  Regional hospitals  Health care centers  Private health care facilities  Rehabilitation sites ‒ Most common VPL trip destinations:  Shopping centers, supermarkets, etc.  Work, school VPL-based tripsKela-reimbursed trips (SVL) Oulu 15
  16. 16. University of Oulu A (maximal) clique of 4 nodes (trips) A method for identifying potential combinations of more than 2 trips ‒ Computationally difficult due to vast number of possible trip combinations ‒ Clique analysis: given a graph representing pair-wise trip sharing possibilites, identify cliques, i.e. complete subgraphs → A clique can be treated as a possible candidate for ride sharing → The clique-based analysis is not an optimization method, but it can provide an approximation of ride-sharing potential  Implemented in Python using the NetworkX package Shareability graph  A node represents a trip  A link between nodes indicates that the trips are shareable16
  17. 17. University of Oulu Shareability potential between Kela (SVL) and VPL trips in Oulu ‒ Work in progress, only tentative results so far ‒ Apparently a lot of sharing potential between Kela-reimbursed and VPL-based trips ‒ Technically the method is working to a maximum clique size of 5 trips ‒ Further development of the method to include different parameters affecting ride-sharing in the real world 17
  18. 18. University of Oulu Conclusions and thoughts: Taxi transport and ride sharing in social and health care? ‒ Overlap in use of taxi transport services  Kela-reimbursed transport and VPL-based transport often used by same clients  Theoretically a lot of ride-sharing potential due to temporal and spatial overlap ‒ Taxi transport in the future?  More co-operation between different authorities (Kela, municipalities, others)  Shuttle services or dial-a-ride bus services in urban areas instead of taxis?  Fixed departure times for taxis leaving hospitals to make ride-sharing easier?  More extensive use of digital services instead of visits to the hospital?  See: 18