Figures and tables in Analysing the Effects of Healthcare Payment Policies on Poverty: A Microsimulation Study with Real-World Healthcare Data

Abstract

In Europe, many people experience financial hardship due to healthcare payments, despite (near-)universal healthcare. In Finland and other countries, austerity has further widened the gaps in coverage through increases in patient payments. However, distributional analyses of austerity have solely concentrated on the effects of tax-benefit policies. We present a method for examining how health payment policies and tax-benefit policies affect household income in conjunction to evaluate the total effect of implemented and planned policies. We linked the national tax-benefit microsimulation model, SISU, and its nationally representative 15% sample of households in 2017 (n=826,001) with administrative real-world healthcare data (Finnish Institute for Health and Welfare Care Register for Health Care, HILMO, and Social Insurance Institution of Finland, Kela, National Health Insurance reimbursement registers). As a case study, we analysed the effects on the relative poverty risk and poverty gap during two government terms. We found that between 2011 and 2015, tax-benefit policies contributed to decreasing relative poverty, and health payment changes had no measurable effects. From 2015 to 2019, the poverty risk rate and the average gap increased due to tax-benefit policies, and health payment changes strengthened the effects by 10% to 20%. Health payments and their increases deteriorated the position of older adults; nevertheless, their poverty risk remained close to the population average. Social assistance had an important buffering effect on the under 65-year-old population. Health payment increases thus exacerbated the effects of austerity on the oldest age groups. Furthermore, based on tax-benefit analyses alone, they were relatively well-protected.

This article contains 6 tables.

Tables

Table 1. Payments (user charges and co-payments) for healthcare goods and services financed at least partly from public funds in Finland in 2019, with policy changes and adjustments between 2011 and 2019.

Healthcare good or service		Payment type	Payment in 2019	Legislative changes†	Index / tariff adjust
Public health care services (Act on social and health care client fees & Government Decree)
Public outpatient services	Outpatient doctor	Fixed fee	€20.60 max 3 times or €41.20 / year*	2015(+), 2016(+)	Biennial
	Night/weekend visit	Fixed fee	€28.30 / visit*	2015(+), 2016(+)	Biennial
	Physiotherapy	Fixed fee	€11.40 / visit	2015(+), 2016(+)	Biennial
	Serial treatments	Fixed fee	€11.40 / visit max 45 times/year	2015(+), 2016(+)	Biennial
	Outpatient specialist	Fixed fee	€41.20 / visit*	2015(+), 2016(+)	Biennial
	Ambulatory surgery	Fixed fee	€135.10 / visit*	2015(+), 2016(+)	Biennial
Public inpatient services (excl. long-term)	Short term inpatient care (max 7 days)	Fixed fee	€48.90 or €22.50 /day*	2015(+), 2016(+)	Biennial
	Day patient	Fixed fee	€22.50*	2015(+), 2016(+)	Biennial
	Inpatient rehabilitation	Fixed fee	€16.90*	2015(+), 2016(+)	Biennial
	Outpatient & inpatient services (excl. dental)	Annual ceiling	€683 / year / person incl. children		Biennial
Public dental services	Oral hygienist/ dentist/specialist	Fixed fee	€10.20/€13.10/€18.90*	2016(+)	Biennial
	Procedures, imaging, prosthetics	Based on tariff	€8.40–€222.70*	2016(+)	Biennial
	Material costs	Realised costs
National Health Insurance reimbursement policies (Health Insurance Act & Government Decrees)
Prescription medicines	Annual deductible	Deductible	Max €50 / year*	2016 (+)
	Basic reimbursement	%-based	60% of retail price	2013(+), 2016(-)
	Disease-based special reimbursement (lower)	%-based	35% or retail price	2013(+)
	Disease-based special reimbursement (higher)	Fixed fee	max €4.50 / item / max 3 months' supply	2016(+), 2017(+)
	Reimbursable medicines	Annual ceiling	€572 / year / person	2013(-), 2014(-), 2019(-)	Annual
	Charge after exceeding annual ceiling	Fixed fee	max €2.50 / item / max 3 months' supply	2016(+)
Travel costs	Co-payment/trip	Fixed fee	max €25 or €50/one-way trip	2013(+), 2015(+), 2016(+), 2018(+)
Travel costs	Travel costs	Annual ceiling	€300 / year / person	2013(+), 2015(+), 2016(+)
Private health care services	Doctor fees	Cap	Costs exceeding tariff	2013(0), 2016(+)	2013, 2014, 2015
Private health care services	Examination and treatment	Cap	Costs exceeding tariff	2013(+), 2015(+), 2016(+)	2011, 2013, 2014, 2015
Private dental services	Examination	Cap	Costs exceeding tariff	2013(0), 2015(+), 2016(+)	2013, 2014, 2015
	Dentist fees	Cap	Costs exceeding tariff	2013(0), 2015(+) 2016(+)	2013, 2014, 2015
	Treatment	Cap	Costs exceeding tariff	2013(0), 2015(+) 2016(+)	2013, 2014, 2015

Children under 18 years exempt (for medicines, exemption until the end of the year when the child turns 18).

Main effect of the change on patient’s share of costs: increase (+), decrease (-), neutral (0).

Table 2. Prevalence of healthcare use (% of individuals in the 2017 data), annual mean health payments (€ per user, estimated based on utilisation data), by healthcare type, and prevalence of health payments (% of individuals in the 2017 data) by income quintile.

	Users	Mean payment/ year/user	Individuals with health payments
	Users	Mean payment/ year/user	Total	Lowest income quintile	Highest income quintile
Public health care	62%	€143	47%	51%	40%
Private health care	34%	€287	34%	20%	50%
Public dental care	35%	€81	22%	21%	19%
Private dental care	18%	€300	18%	8%	32%
Prescription medicines	68%	€173	68%	63%	72%
Travel costs	10%	€99	10%	15%	6%

Table 3. Simulated scenarios using the SISU model with and without the health payment (HP) module and varying price indices (consumer price index, CPI, or item-specific price indices, IPI).

Scenario	Tax-benefit policies (SISU)	Social assistance (SISU w/o HP-module)	Health payments (HP- module)	HP price index (HP- module)
#1	Yes	without HP (SISU only)	No	N/A
#2	Yes	without HP (SISU only)	Yes	CPI
#3	Yes	without HP (SISU only)	Yes	IPI
#4	Yes	with HP (SISU & HP module)	Yes	CPI
#5	Yes	with HP (SISU & HP module)	Yes	IPI

Table 4. Simulated annual health payment expenditure (Million €, in real terms) in 2011–2019, and change between 2011–2015 and 2015–2019, by healthcare type.

		2011	2012	2013	2014	2015	2016	2017	2018	2019	Change 2011-2015	Change 2015-2019
Public	Healthcare	373	364	359	378	409	490	487	477	472	10 %	16 %
Public	Dental	127	124	122	128	129	158	157	153	152	2 %	18 %
Private healthcare	IPI	455	455	469	475	482	525	539	547	550	6 %	14 %
Private healthcare	CPI	485	492	502	503	503	540	539	540	536	4 %	7 %
Private dental	IPI	235	235	236	241	265	292	298	301	304	13 %	14 %
Private dental	CPI	254	256	255	256	277	300	298	298	299	9 %	8 %
Medicines	IPI	559	534	579	576	583	650	651	618	588	4 %	1 %
Medicines	CPI	518	518	570	570	571	630	651	649	639	10 %	12 %
Travel costs	IPI	27	27	40	39	44	57	57	55	54	59 %	24 %
Travel costs	CPI	27	26	39	38	43	57	57	54	54	64 %	24 %
Total	IPI	1,777	1,739	1,804	1,836	1,911	2,172	2,188	2,151	2,121	8 %	11 %
Total	CPI	1,783	1,780	1,847	1,874	1,931	2,175	2,188	2,172	2,152	8 %	11 %

Simulations were conducted using 2017 data.

For medicines, private services, and travel costs, the results were simulated using alternative price adjustments: consumer price index (CPI) and item-specific price indices (IPI).

Table 5. Poverty risk rates and gaps in 2011–2019 simulated with tax-benefit and health payment legislations, and decomposition of the effects of health payments on social assistance.

		2011	2012	2013	2014	2015	2016	2017	2018	2019	2011-2015*	2015-2019*
Poverty risk rate (60% of the population median)
All	Rate after tax-benefit legislation, %	15.3	14.2	13.8	13.7	12.8	12.9	13.5	13.6	13.7	-2.5	0.9
	Rate after tax-benefit legislation & health payments, %	15.5	14.4	13.9	13.9	13.0	13.2	13.8	13.9	14.0	-2.6	1.0
	Total effect of health payments & prices incl. SA, ppts	0.2	0.2	0.1	0.2	0.2	0.3	0.3	0.3	0.3	0.0	0.1
	Effect of health payment policies & prices (IPI), ppts	0.4	0.4	0.4	0.4	0.5	0.6	0.6	0.5	0.5	0.0	0.1
	Effect of social assistance (SA), ppts	-0.2	-0.2	-0.3	-0.3	-0.2	-0.2	-0.2	-0.2	-0.2	0.0	0.0
≥65 years	Rate after tax-benefit legislation, %	13.3	12.6	12.1	12.1	11.5	11.8	12.5	12.5	12.8	-1.8	1.3
	Rate after tax-benefit legislation & health payments, %	15.2	14.4	13.9	13.9	13.4	14.1	14.8	14.7	15.0	-1.8	1.6
	Total effect of health payments & prices incl. SA, ppts	1.9	1.8	1.8	1.9	1.9	2.3	2.3	2.2	2.2	0.0	0.3
	Effect of health payment policies & prices (IPI), ppts	1.9	1.8	1.8	1.8	1.9	2.2	2.3	2.2	2.1	0.0	0.2
	Effect of social assistance (SA), ppts	0.1	0.0	0.0	0.1	0.1	0.1	0.1	0.1	0.1	0.0	0.0
Poverty gap (60% of the population median)
All	Gap after tax-benefit legislation, %	15.8	14.9	14.4	14.6	14.6	14.7	15.3	15.3	15.3	-1.2	0.7
	Gap after tax-benefit legislation & health payments, %	15.7	14.8	14.4	14.6	14.6	14.7	15.3	15.3	15.3	-1.2	0.8
	Total effect of health payments & prices incl. SA, ppts	-0.1	-0.1	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1	0.1
	Effect of health payment policies & prices (IPI), ppts	0.4	0.4	0.4	0.4	0.4	0.4	0.5	0.5	0.5	0.0	0.1
	Effect of social assistance (SA), ppts	-0.5	-0.4	-0.4	-0.4	-0.4	-0.4	-0.4	-0.4	-0.4	0.1	-0.1
≥65 years	Gap after tax-benefit legislation, %	10.2	9.8	9.5	9.5	9.4	9.2	9.9	9.8	10.0	-0.8	0.6
	Gap after tax-benefit legislation & health payments, %	11.3	10.9	10.5	10.6	10.5	10.7	11.2	11.1	11.3	-0.8	0.8
	Total effect of health payments & prices incl. SA, ppts	1.1	1.0	1.1	1.1	1.1	1.5	1.3	1.3	1.3	0.0	0.2
	Effect of health payment policies & prices (IPI), ppts	1.1	1.0	1.0	1.1	1.0	1.5	1.3	1.3	1.3	0.0	0.2
	Effect of social assistance (SA), ppts	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

All simulations were conducted using the 2017 data. Prices for medicines, private services, and travel costs were adjusted using IPI.

Change in percentage points.

Table 6. Simulated poverty risk rate in 2011–2019 after tax-benefit legislation and health payments, and the effect of health payments, by population subgroup.

		2011	2012	2013	2014	2015	2016	2017	2018	2019	2011-2015‡	2015-2019‡
Poverty risk rate (60% of population median)*
<18 yrs	Rate after tax-benefit legislation & health payments, %	14.4	12.9	12.2	12.3	11.5	11.6	12.0	12.2	12.3	-3.0	0.8
<18 yrs	Total effect of health payments, ppts	-0.5	-0.6	-0.6	-0.6	-0.6	-0.6	-0.6	-0.6	-0.6	0.0	0.0
18-64 yrs at work†	Rate after tax-benefit legislation & health payments, %	4.2	3.8	3.6	3.6	3.0	3.0	3.1	3.2	3.2	-1.2	0.2
18-64 yrs at work†	Total effect of health payments, ppts	-0.1	-0.1	-0.2	-0.2	-0.1	-0.1	-0.1	-0.1	-0.1	0.0	0.0
18-64 yrs not at work†	Rate after tax-benefit legislation & health payments, %	40.2	37.9	36.7	36.6	34.5	34.7	36.5	36.5	36.7	-5.7	2.2
18-64 yrs not at work†	Total effect of health payments, ppts	0.0	-0.1	-0.3	-0.3	-0.2	-0.1	-0.1	-0.1	0.0	-0.1	0.1
Poverty risk rate (50% of population median)
All	Rate after tax-benefit legislation & health payments, %	7.4	6.5	6.1	6.2	5.8	5.9	6.4	6.4	6.5	-1.6	0.7
All	Total effect of health payments, ppts	0.1	0.0	0.0	0.0	0.1	0.1	0.2	0.1	0.1	0.0	0.0
≥65 yrs	Rate after tax-benefit legislation & health payments, %	4.8	4.3	3.9	4.0	3.8	4.2	4.7	4.6	4.7	-1.0	0.9
≥65 yrs	Total effect of health payments, ppts	1.1	1.0	0.9	1.0	1.0	1.2	1.4	1.3	1.3	-0.1	0.3
<18 yrs	Rate after tax-benefit legislation & health payments, %	6.1	5.1	4.7	4.8	4.5	4.6	4.9	5.0	5.0	-1.6	0.5
<18 yrs	Total effect of health payments, ppts	-0.3	-0.4	-0.3	-0.3	-0.3	-0.3	-0.3	-0.3	-0.3	0.1	0.0
18-64 yrs at work†	Rate after tax-benefit legislation & health payments, %	1.7	1.4	1.4	1.4	1.2	1.2	1.3	1.3	1.3	-0.5	0.1
18-64 yrs at work†	Total effect of health payments, ppts	-0.1	-0.1	-0.1	-0.1	-0.1	-0.1	-0.1	-0.1	-0.1	0.0	0.0
18-64 yrs not at work†	Rate after tax-benefit legislation & health payments, %	23.3	20.7	19.5	19.8	18.6	18.8	20.5	20.6	20.7	-4.6	2.0
18-64 yrs not at work†	Total effect of health payments, ppts	-0.3	-0.3	-0.4	-0.3	-0.2	-0.2	-0.2	-0.2	-0.2	0.1	0.0

All simulations were conducted using the 2017 data. Prices for medicines, private services, and travel costs were adjusted using IPI.

Poverty risk rate 60% of population median for all and ≥65-year-olds, see Table 5.

At work/not at work = with and without labour market attachment in the long term (one year).

Change in percentage points.