Supplementary private health insurance and health care utilization of people aged 50+

Anikó Bíró

doi:10.1007/s00181-013-0689-2

Empirical Economics

March 2014, Volume 46, Issue 2, pp 501–524 | Cite as

Supplementary private health insurance and health care utilization of people aged 50+

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Anikó BíróEmail author

Article

First Online: 09 March 2013

Received: 10 September 2010

Accepted: 06 December 2012

Abstract

Does supplementary private health insurance (PHI) coverage influence health care utilization in countries where the coverage ratio with public health insurance is high? I estimate this effect using the Survey of Health, Ageing and Retirement in Europe. Handling the potential endogeneity of supplementary insurance coverage and the large fraction of zero observations in the utilization models influences the empirical results. I show that the effect of PHI coverage on inpatient and outpatient care utilization is not trivial even in countries with generous public health funding. The main finding is that supplementary PHI coverage increases dental care utilization, but decreases the visits to general practitioners. Private insurance is estimated to have little and insignificant influence on the utilization of inpatient care and outpatient specialist care. The magnitude of the effect of supplementary PHI on health care utilization varies with the characteristics of the health care systems.

Keywords

Private health insurance Health care utilization SHARE

JEL Classification

C25 C35 G22 I11

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Notes

Acknowledgments

An earlier version of this article was written as part of my Ph.D. thesis at the Central European University. I am grateful for comments and suggestions received at the 5th Nordic Econometric Meeting in Lund, 3rd annual conference of the Hungarian Society of Economics in Budapest, 2nd Health Econometrics Workshop in Rome and from two anonymous referees.

Appendix

Table 6

Sample mean and standard deviation of the variables

	Mean	SD
Age	64.96	10.19
Female	0.55	0.50
Marital status
With spouse	0.68	0.47
With partner	0.04	0.20
Single	0.28	0.45
Has children	0.88	0.32
Income (1,000 EUR)	20.98	74.19
Main residence (1,000 EUR)	102.51	321.00
Education level
Primary	0.35	0.48
Lower secondary	0.18	0.39
Upper secondary	0.31	0.46
Tertiary	0.16	0.37
Living area
Big city	0.14	0.35
Suburbs big city	0.16	0.37
Large town	0.19	0.39
Small town	0.26	0.44
Rural	0.25	0.43
Employment status
Retired	0.50	0.50
Employed, other	0.12	0.33
Unemployed	0.03	0.17
Disabled	0.03	0.17
Homemaker	0.15	0.35
Civil servant	0.04	0.19
Self-employed	0.07	0.26
Public employee	0.07	0.25
Smoking habits
Never	0.53	0.50
Stopped	0.27	0.44
Smoking	0.20	0.40
Last job
Civil servant	0.10	0.29
Public employee	0.17	0.38
Self-employed	0.17	0.37
Supplementary PHI	0.32	0.47
# illness	1.35	1.38
# ADL problems	0.20	0.76
# symptoms	1.45	1.62
Firm size not relevant	0.26	0.44
Firm size 1–5	0.13	0.34
Firm size 6–15	0.14	0.34
Firm size 16–24	0.08	0.26
Firm size 25–199	0.23	0.42
Firm size 200–499	0.07	0.25
Firm size 500–	0.10	0.29
# GP visits	4.89	7.64
# Hosp. nights	1.55	7.13
# Specialist visits	1.57	4.56
Visit dentist	0.54	0.50

Table 7

Percentage of individuals covered by specific types of supplementary PHI

	AU	BE	DK	FR	DE	GR	IT	NL	ES	SE	CH
Medical care with direct access to specialists	2.7	6.4	9.2	70.0	3.8	1.8	1.8	0.0	6.0	1.4	17.8
Medical care with an extended choice of doctors	2.6	0.2	4.9	52.0	3.5	1.3	0.7	0.0	4.3	0.5	18.5
Dental care	1.5	5.7	18.6	75.9	5.6	0.4	0.4	47.0	3.2	0.2	6.4
Larger choice of drugs and/or full drugs expenses	1.6	2.7	13.8	72.1	0.7	0.6	0.4	34.7	0.9	0.4	14.2
Extended choice of hospitals	16.5	0.1	5.3	73.7	4.2	1.5	1.7	0.0	4.3	0.5	38.2
Long-term care	0.8	0.2	0.5	64.1	0.0	0.2	0.0	0.0	0.1	0.1	9.2
Nursing care at home	0.9	0.1	0.8	54.0	0.0	0.3	0.1	0.0	2.3	0.0	8.8
Home help for ADL	0.7	2.7	0.3	25.8	0.0	0.1	0.2	0.0	0.4	0.0	8.3
Full coverage of costs for doctor visits	2.1	0.8	2.0	49.7	0.0	1.0	0.5	0.0	4.1	1.2	1.7
Full coverage of costs for hospital care	6.7	59.5	1.8	12.8	5.3	2.1	1.1	0.0	3.8	0.9	5.0

Table 8

Supplementary PHI coverage and health care utilization—sample means

	Supplementary PHI coverage	Hospital stay	Visit GP	Visit specialist	Visit dentist	# Hospital nights\(^\mathrm{a}\) (if hosp. > 0)	# GP visits\(^\mathrm{a}\) (if GP > 0)	# Specialist visits\(^\mathrm{a}\) (if spec. > 0)
AT	0.23	0.19	0.85	0.37	0.51	11.57	5.51	3.58
BE	0.76	0.14	0.92	0.48	0.49	9.35	6.17	3.77
DK	0.36	0.12	0.81	0.18	0.76	8.58	4.01	3.78
FR	0.84	0.15	0.93	0.46	0.44	8.92	5.75	3.63
DE	0.14	0.16	0.92	0.54	0.75	12.35	5.54	4.29
GR	0.05	0.08	0.76	0.27	0.37	8.22	5.43	4.63
IT	0.06	0.12	0.83	0.41	0.33	9.76	7.70	4.02
NL	0.72	0.11	0.80	0.40	0.57	7.50	3.71	4.18
ES	0.09	0.11	0.88	0.42	0.26	9.13	7.72	4.40
SE	0.09	0.11	0.75	0.28	0.78	6.66	2.70	3.07
CH	0.33	0.12	0.83	0.30	0.68	8.93	4.13	3.86

\(^\mathrm{a}\) Hospital nights or doctoral visits above 50 are excluded

Table 9

Estimated coefficients of the probit model of supplementary private health insurance coverage

	PHI
Age	\(-0.009^{***}\)
Female	0.077\(^{***}\)
Marital status
With partner	0.074
Single	\(-0.118^{***}\)
Log income	0.093\(^{**}\)
Log income: DE	0.153\(^{**}\)
Log income: SE	0.061
Log income: NL	\(-0.121^{*}\)
Log income: ES	0.046
Log income: IT	0.106
Log income: FR	\(-0.087\)
Log income: DK	0.098
Log income: GR	0.010
Log income: CH	\(-0.106\)
Log income: BE	\(-0.010\)
Log home	0.010
Log home: DE	0.020\(^{**}\)
Log home: SE	\(-0.003\)
Log home: NL	\(-0.005\)
Log home: ES	0.001
Log home: IT	\(-0.014\)
Log home: FR	0.004
Log home: DK	0.011
Log home: GR	\(-0.028^{**}\)
Log home: CH	\(-0.001\)
Log home: BE	\(-0.002\)
Education level
Lower secondary	0.136\(^{***}\)
Upper secondary	0.360\(^{***}\)
Tertiary	0.485\(^{***}\)
Firm size 1–5	0.183\(^{***}\)
Firm size 6–15	0.164\(^{***} \)
Firm size 16–24	0.077
Firm size 25–199	0.170\(^{***}\)
Firm size 200–499	0.146\(^{***}\)
Firm size 500–	0.268\(^{***} \)
Country: DE	\(-2.045^{***}\)
Country: SE	\(-1.201\)
Country: NL	2.626\(^{***}\)
Country: ES	\(-0.819\)
Country: IT	\(-1.513^{*}\)
Country: FR	2.674\(^{***}\)
Country: DK	\(-0.747\)
Country: GR	\(-0.644\)
Country: CH	1.431\(^{**}\)
Country: BE	1.667\(^{***}\)
Constant	\(-1.554^{***}\)
Observations	23,503

\(^{*}, ^{**}, ^{***}\) Significant at the 10, 5, 1 % level, respectively

References

Bago d’Uva T, Jones AM (2009) Health care utilisation in Europe: new evidence from the ECHP. J Health Econ 28:265–279CrossRefGoogle Scholar
Cameron AC, Trivedi PK (2005) Microeconometrics: methods and applications. Cambridge University Press, New YorkGoogle Scholar
Cameron AC, Trivedi K (2009) Microeconometrics using Stata. Stata Press, College Station, TXGoogle Scholar
Cappellari L, Jenkins SP (2006) Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation. Stata J 6(2):156–189Google Scholar
Deb P, Trivedi PK (1997) Demand for medical care by the elderly: a finite mixture approach. J Appl Econom 12:313–336CrossRefGoogle Scholar
Deb P, Manning W, Norton E (2010) Sample programs for ASHE June 2010 at Cornell University IthacaGoogle Scholar
Dow MH, Norton EC (2003) Choosing between and interpreting the Heckit and two-part models for corner solutions. Health Serv Outcomes Res Methodol 4:5–18CrossRefGoogle Scholar
Gibbons RD, Wilcox-Gok V (1998) Health service utilization and insurance coverage: a multivariate probit analysis. J Am Stat Assoc 93(441):63–72CrossRefGoogle Scholar
Greene WH (2003) Econometric analysis, 5th edn. Prentice Hall, Upper Saddle River, NJGoogle Scholar
Grossman M (1972) On the concept of health capital and the demand for health. J Polit Econ 80:223–255CrossRefGoogle Scholar
Holly A et al. (2005) Out-of-Pocket Payments for Health Care Expenditures. In: Börsch-Supan A et al. (eds) Health, aging and retirement in Europe - first results from the survey on health, aging and retirement in Europe. MEA, Mannheim , pp 126–132Google Scholar
Hullegie P, Klein TJ (2010) The effect of private health insurance on medical care utilization and self-assessed health in Germany. Health Econ 19(9):1048–1062CrossRefGoogle Scholar
Hunt-McCool J, Kiker BF, Ng YC (1994) Estimates of the demand for medical care under different functional forms. J Appl Econom 9(2):201–218CrossRefGoogle Scholar
Jones AM (2000) Handbook of health economics. In: Culyer AJ, Newhouse JP (eds) Health econometrics, vol 1, chap 6. Elsevier, Amsterdam, pp 265–344Google Scholar
Jones AM, Koolman X, van Doorslaer E (2006) The impact of having supplementary private health insurance on the use of specialists. Ann Écon Stat 83(84):251–275Google Scholar
Manning WG et al (1987) Health insurance and the demand for medical care: evidence from a randomized experiment. Am Econ Rev 77(3):251–277Google Scholar
Mossialos E, Thomson S (2004) Voluntary health insurance in the European Union. WHO, European Observatory on Health Systems and PoliciesGoogle Scholar
Norton EC, Dow WH, Do YK (2008) Specification tests for the sample selection and two-part models. Health Serv Outcomes Res Methodol 8:201–208CrossRefGoogle Scholar
OECD (2004) Private Health Insurance in OECD Countries. The OECD Health ProjectGoogle Scholar
Paccagnella O, Rebba V, Weber G (2012) Voluntary private health care insurance among the over fifties in Europe: a comparative analysis of SHARE data. Health Econ. doi: 10.1002/hec.2800
Pohlmeier W, Ulrich V (1995) An econometric model of the two-part decisionmaking process in the demand for health care. J Hum Resour 30(2):339–361CrossRefGoogle Scholar
Rodríguez M, Stoyanova A (2004) The effect of private insurance access on the choice of GP/specialist and public/private provider in Spain. Health Econ 13(7):689–703CrossRefGoogle Scholar
Terza JV (1998) Estimating count data models with endogenous switching: sample selection and endogenous treatment effects. J Econom 84:129–154CrossRefGoogle Scholar
Terza JV, Basu A, Rathouz PJ (2008) Two-stage residual inclusion estimation: addressing endogeneity in health econometric modeling. J Health Econ 27:531–543CrossRefGoogle Scholar
Thomson S, Foubister T, Mossialos E (2009) Financing health care in the European Union. WHO, European Observatory on Health Systems and PoliciesGoogle Scholar
Werblow A, Felder S, Zweifel P (2007) Population ageing and health care expenditure: a school of ’red herrings’? Health Econ 16:1109–1126CrossRefGoogle Scholar
Zimmerman Murphy M (1987) The importance of sample selection bias in the estimation of medical care equations. East Econ J 13:19–29Google Scholar

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Anikó Bíró
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1.School of EconomicsThe University of EdinburghEdinburghUK

Supplementary private health insurance and health care utilization of people aged 50+

Abstract

Keywords

JEL Classification

Notes

Acknowledgments

References

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