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The European Journal of Health Economics
Published in: The European Journal of Health Economics 4/2020

Open Access 01-06-2020 | Original Paper

Low risk, high reward? Repeated competitive biddings with multiple winners in health care

Authors: Visa Pitkänen, Signe Jauhiainen, Ismo Linnosmaa

Published in: The European Journal of Health Economics | Issue 4/2020

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Abstract

We study physiotherapy providers’ prices in repeated competitive biddings where multiple providers are accepted in geographical districts. Historically, only very few districts have rejected any providers. We show that this practice increased prices and analyze the effects the risk of rejection has on prices. Our data are derived from three subsequent competitive biddings. The results show that rejecting at least one provider decreased prices by more than 5% in the next procurement round. The results also indicate that providers have learned to calculate their optimal bids, which has also increased prices. Further, we perform counterfactual policy analysis of a capacity-rule of acceptance. The analysis shows that implementing a systematic acceptance rule results in a trade-off between direct cost savings and service continuity at patients’ usual providers.
Appendix
Available only for authorised users
Footnotes
1
This behavior is similar to tacit collusion in repeated auctions [20].
 
2
Some patients may have received physiotherapy organized by their municipality before Kela accepts their rehabilitation plan or after they turn 66 years and are not entitled to the service organized by Kela.
 
3
If patients have a referral from the doctor, they are entitled to a small reimbursement paid by Kela from the National Health Insurance.
 
4
Other large physiotherapy purchasers such as municipalities also use repeated competitive biddings, and there may be spillover effects in the procurements between the different markets because many providers are present in the different markets. However, we do not have data on other procurements and the focus is therefore in the markets organized by Kela.
 
5
Exceptions are South Ostrobothnia and Päijät-Häme districts that implemented a fixed price pilot in the 2011–2014 contract period.
 
6
Unfortunately, data on prices prior to 2003 was not available.
 
7
In 2006, the quality–price scoring rule was quality/price, in 2010 quality was weighted 60% and price 40%, whereas in 2014 quality and price were both weighted 50%.
 
8
The quality–price score tables have been available from the districts also later on.
 
9
Unfortunately we do not have data about bids that did not meet the minimum requirements.
 
10
The 2003 data is based on a list of providers’ accepted prices in November 2006.
 
11
We use a distance of 0.5 kilometres when patient and provider were located in the same postcode. The smallest distance between two independent postcodes in our data is 0.93 kilometres. Unfortunately, we did not have access to data on actual travel times between postcodes.
 
12
We acknowledge that the physiotherapy market has many not-for-profit providers.
 
13
The quality–price score was calculated simply as quality/price in 2006. We have transformed this into a similar quality–price measure as in 2010 and 2014 using weights of 50% for both quality and price. This does not change the original order of the providers in the districts’ score tables and makes the results comparable in the different competitive biddings.
 
14
Figure 3 (in the Appendix) illustrates the intuition: The highest ranked provider received 45 quality points and offered a price of 58 euros. The provider receives the quality–price scoring table after the procedure and notices that many providers with the same or lower quality points offered a higher price and received a contract. Thus, it is likely that this provider will bid a higher price in the next round compared to a provider with lower rank.
 
15
Altogether the data includes 2023 different providers, 36% of which participated in all of the four procurements.
 
16
All of the districts did not include capacity in their quality–price score tables in 2006.
 
17
In the 2018 competitive bidding, Kela used a capacity-rule based on number of patients in 2017 added by 10 percent, but accepting at least three providers in each municipality to ensure short travel distances.
 
18
For example the district of Helsinki was responsible for organizing the service for 985 patients in 2014. The district received bids from 72 providers with a total capacity of 3471 in the 2014 competitive bidding for the contract period 2015–2018. The district accepted all 72 providers into the pool. Using the 10 percent capacity-based rule we create a counterfactual pool where the first providers in the quality–price list are accepted until the required capacity of 1084 is reached. In this example, the first 23 providers are accepted in the counterfactual pool and the remaining 49 providers in the list are not included.
 
19
We performed a similar analysis for the 2010–2014 contract period. The results are similar to the 2015–2018 period, but potential direct fiscal savings would have been lower because the overall price-level of the bids was lower. The results are available from the authors.
 
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Metadata
Title
Low risk, high reward? Repeated competitive biddings with multiple winners in health care
Authors
Visa Pitkänen
Signe Jauhiainen
Ismo Linnosmaa
Publication date
01-06-2020
Publisher
Springer Berlin Heidelberg
Published in
The European Journal of Health Economics / Issue 4/2020
Print ISSN: 1618-7598
Electronic ISSN: 1618-7601
DOI
https://doi.org/10.1007/s10198-019-01143-1

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