Waiting times in the ambulatory sector - the case of chronically Ill patients

International Journal for Equity in Health

Thomas Kopetsch¹  Leonie Sundmacher² 

[1] National Association of Statutory Health Insurance Physicians, Herbert-Lewin-Platz 2, 10623, Berlin;Health Services Management Department, Munich School of Management, Ludwig Maximilians University, Schackstraße 4, 80539, Munich

关键词: Consultations;    Ambulatory sector;    Waiting times;   

Others  :  811375
DOI  :  10.1186/1475-9276-12-77

 received in 2013-05-13, accepted in 2013-08-25,  发布年份 2013

【 摘 要 】

Aims

First, the influence of determinants on the waiting times of chronically ill patients in the ambulatory sector is investigated. The determinants are subdivided into four groups: (1) need, (2) socio-economic factors, (3) health system and (4) patient time pressures. Next, the influence of waiting times on the annual number of consultations is examined to assess whether the existing variation in waiting times influences the frequency of medical examinations. The waiting times of chronically ill patients are analysed since regular ambulatory care for this patient group could both improve treatment outcomes and lower costs.

Data sources

Individual data from the 2010 Representative Survey conducted by the National Association of Statutory Health Insurance Physicians (KBV) together with regional data from the Federal Office of Construction and Regional Planning.

Study design

This is a retrospective observational study. The dependent variables are waiting times in the ambulatory sector and the number of consultations of General Practitioners (GPs) and specialist physicians in the year 2010. The explanatory variables of interest are ‘need’ and ‘health system’ in the first model and ‘length of waiting times’ in the second. Negative binomial models with random effects are used to estimate the incidence rate ratios of increased waiting times and number of consultations. Subsequently, the models are stratified by urban and rural areas.

Results

In the pooled regression the factor ‘privately insured’ shortens the waiting time for treatment by a specialist by approximately 28% (about 3 days) in comparison with members of the statutory health insurance system. The category of insurance has no influence on the number of consultations of GPs. In addition, the regression results stratified by urban and rural areas show that in urban areas the factor ‘privately insured’ reduces the waiting time for specialists by approximately 35% (about 3.3 days) while in rural areas there is no evidence of statistical influence. In neither of the models, however, does the waiting time have a documentable effect on the number of consultations in the ambulatory sector.

Conclusions

In our random sample, characteristics of the health care system have an influence on the waiting time for specialists, but the waiting time has no documentable effect on the number of consultations in the ambulatory sector. In the present analysis this applies to consultations of both GPs and specialists. Nevertheless, it does not rule out the possibility that the length of waiting times might influence the treatment outcomes of certain patient populations.

【 授权许可】

   
2013 Sundmacher and Kopetsch; licensee BioMed Central Ltd.

【 参考文献 】

• [1]Zok K: Warten auf einen Arzttermin. WIdO-monitor 2007, 4(1):1-7.
• [2]The National Association of Statutory Health Insurance Funds. Zahlen und Grafiken; http://www.gkv-spitzenverband.de/presse/zahlen_und_grafiken/zahlen_und_grafiken.jsp webcite
• [3]Social Code, Book V: Gesetzliche Krankenversicherung. 2001, 70:1. SGB V
• [4]Lüngen M, Stollenwerk B, Messner P, Lauterbach KW, Gerber A: Waiting times for elective treatments according to insurance status; a randomised empirical study in Germany. International Journal of Equity in Health 2008, 7:1. doi:10.1186/1475-9276-7-1. http://www.equityhealthj.com/content/7/1/1 webcite BioMed Central Full Text
• [5]Schellhorn M: Vergleich der Wartezeiten von gesetzlich und privat Versicherten in der ambulanten ärztlichen Versorgung. In Gesundheitsmonitor 2007. Gesundheitsversorgung und Gestaltungsoptionen aus der Perspektive von Bevölkerung und Ärzten. Edited by Böcken J, Braun B, Amhof R. Gütersloh: Verlag Bertelsmann Stiftung; 2007:95-113.
• [6]Roll K, Stargardt T, Schreyögg J: Effect of type of insurance and income on waiting time for outpatient care. The Geneva Papers on Risk and Insurance 2012, 37:609-632. in print
• [7]Prentice JC, Pizer SD: Delayed access to health care and mortality. Health Serv Res 2007, 42(2):644-662.
• [8]Prentice JC, Pizer SD: Waiting times and hospitalizations for ambulatory care sensitive conditions. Health Serv Outcomes Res Meth 2008, 8:1-18.
• [9]Prentice JC, Graeme Fincke B, Miller DR, Pizer SD: Primary care and health outcomes among older patients with diabetes. Health Service Research 2012, 47(1 Pt 1):46-67. doi:10.1111/j.1475-6773.2011.01307
• [10]Ozegowski S, Sundmacher L: Ensuring access to health care - Germany reforms supply structures to tackle inequalities. Health Policy 2012, 106(2):105-109.
• [11]National Association of Statutory Health Insurance Physicians (KBV): Versichertenbefragung der Kassenärztlichen Bundesvereinigung. 2010. http://www.kbv.de/publikationen/versichertenbefragung2010.html webcite
• [12]Wellstood K, Wilson K, Eyles J: “Reasonable Access” to primary care: assessing the role of individual and system characteristics. Health Place 2006, 12(2):121-130.
• [13]Siciliani L, Verzulli R: Waiting times and socioeconomic status among elderly Europeans: evidence from share. Health Econ 2009, 18(11):1295-1306.
• [14]Federal Statistical Office: Jeder Vierte in Deutschland hat Abitur. https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/zdw/2012/PD12_007_p002.html webcite
• [15]Ofman JJ, Badamgarav E, Henning JM, Knight K, Gano AD, Levan RK, Gur-Arie S, Richards MS, Hasselblad V, Weingarten SR: Does disease management improve clinical and economic outcomes in patients with chronic diseases? A systematic review. Am J Med 2004, 117(3):182-192.
• [16]Neugebauer R, Ng S: Differential Recall as a source of bias in epidemiologic research. J Clin Epidemiol 1990, 43(12):1337-1341.