Health Systems in Transition - Hungary - World Health Organization ...

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Health systems in transition Hungary
care providers; the introduction of HTA for the inclusion of new technologies
in the benefit package; the update of clinical guidelines and protocols; the
establishment of the professional supervisory system of the NPHMOS by
means of the National Centre for Healthcare Audit and Inspection in 2005; the
quality indicator initiative of the NHIFA and the introduction of the system
of indicators of the HISA. However, there are still substantial variations in
clinical practice and outcome indicators (Belicza, 2004), and little has been
published on the direct impact of various measures on service provision. he
refurbishment of existing polyclinics under the Regional Operative Programmes,
and the building of new polyclinics under the Social Infrastructure Operative
Programmes of the New Hungary Development Programme, financed by EU
structural funds (2006/6). In the former, day care was optional, while in the
latter it was a compulsory component. Both the introduction of the new payment
system in 1993 and the incentivization of day care (see section 5.4.1) also aimed
at improved care and fewer unnecessary hospitalizations. In addition, the CCS
revealed some interesting areas of potential progress before it was eliminated
in 2008 (see section 7.5 for more information).
A survey carried out at 102 Hungarian hospitals in 2005 found that even
though all participating hospitals reported the utilization of quality management
systems, patient safety activities were not as widely implemented (even if
committed to in theory). The study concludes that separate, additional policies
are called for in order to improve patient safety in Hungary (Makai et al., 2009).
Regarding quality control, the government in power since April 2010 published
a programme entitled The programme of national cooperation (see section 6.2),
which also aims at improving the quality assurance system by strengthening
the mandate of the NPHMOS.
7.4.3 Equity of outcomes
According to a recent study analysing geographical disparities in health status
based on individual mortality data at the micro-regional level, all-cause
mortality differed by 215% between the worst and best micro-regions: 56%
was attributable to the age and gender composition of the population, 8% to the
level of education and economic activity of individual inhabitants and 8% by
the social and economic status of the micro-region. 5 The remaining difference
disappeared when micro-regions were grouped based on level of disadvantage
and development as well as the proportion of Roma population (Kaposvari
& Vitrai, 2008) (see also section 7.3.2 and 5.14).
5 The significance of these factors may be different if the analysis is made on a societal and not on
a micro-regional level.