"How a specific Health Information System (HIS) can help Regional Health Authority (RHA) of Ile de France (IDF) region in perinatal health targets follow-up?"
Crenn Hebert Catherine1, Lebreton Elodie2, Menguy Claudie3
1 APHP, HUPNVS, Hôpital Louis Mourier, Perinat-ARS-IDF, Réseau périnatal 92Nord (France)
2 Perinat-ARS-IDF (France)
3 CHI André-Grégoire, Perinat-ARS-IDF, (France)
Abstract
Background
About 180000 babies were born in 2009 in theIDF region (8 districts, including Paris).The regional health authority (RHA) documented marked territorial health inequalities while preparing its new health plan. Health care facilitiesare not evenly distributed and wide gaps exist in access to care and perinatal mortality between the different districts.
We test the capacity of ahealth information system (HIS)based on validated and routinely available data to monitor the link between inequalities and health outcomes.
Material and Methods
The health information system (HIS) is established by Regional Health Authority, from existing databases, with the involvement of perinatal health professionals since 2006. Some data are available on web-site:
It is based on Hospital discharge summaries (HDS), available for all hospital stays in a maternity unit (mothers and babies, both live and stillborn) and in a neonatal unit (hospitalised newborns). The data obtained with hospital discharge summaries are compared with vital statistics from national civil registration system(INSEE).The perinatal centres are classified in 4 levels according to on-site neonatal care within maternity unit.
Gestational age is available only since April 2009 inHospital discharge summaries. So we still use birthweight to measure preterm birth in 2009.
Geographical analysis by mother placeof residence was carried out. We relate indicators of care and outcome to neighbourhood socioeconomic and supply characteristics using an ecological approach,adapted from the human development index model.
Results
Completeness of the data
The completeness of inclusions, assessed by comparing the number of births with vital statistics from INSEE, was 97,1% of 181557living births by IDF resident mothers in 100 maternity units. (Table 1)
The completeness of the data from hospital discharge summaries was 80% of 2507 stillbirths by comparing withINSEE . (Table 2)
Place of birth
27% of births take place in the 15 level III perinatal centres (maternity with on-site neonatal intensive care - PCIII). The distribution of total births according to perinatal centre level varied among the districts: from 20% of total births in level III in Seine et Marne (district code 77) and Hauts-de-Seine (district code 92) to 36% in Val d’Oise (district code 95) and Yvelines (district code 78) .( Figure 1)
Neonatal intensive care unitsizeand distribution varied from 3 beds (in Seine-et-Marne district) to 21 for 10000 births (in Paris district) among the districts. (Table 3)
Perinatal outcomes
80% (instead of 78% in 2007) of babies born alive weighting less than 1500g, were born in a PCIII. But the gapbetween districts increases: from 66% (in Seine-et-Marne district) to 86% (in Paris district).(Table 4)
Preterm birth rates variedby district from 0,89 (in Paris district) to 1,1% (in Seine-Saint- Denis) for live birth (<1500g). (Table 5)
For live births 1500-2499g rates varied from 5,6% (in Paris district) to 6,3% (in Seine-et-Marne district).(Table 6)
Still-birth rate varied from 1,1% (in Hauts-de-Seine and Yvelines districts) to 1,73%(in Seine-Saint- Denis) in civil registration system (Table 7).
Neonatal mortality in newborn units varied from 0,9% to 1,6% with hospital discharge data.
Social disadvantage
Social disadvantage is measured for each district by education attainment (proportion of population without the baccalaureat)varied from 33% in Paris district to 65% in Seine-Saint- Denis and by employment (rate unemployment varied from 8% in Yvelines to 16% in Seine-Saint- Denis) and manual workers rate (which varied from 7% in Paris to 23% in Seine-Saint- Denis).(Table 8)
We have calculated a score with summarizing the rank of each district (from 1 to 8) for every social disadvantage. The higher score is in Seine-Saint-Denis, and the lowest are in Paris and Yvelines.(Table 9)
Discussion
We have used vital statistics results for each district because completness of Hospital Discharge data in stillbirth rate and accuracy of social informations have to be improved in our perinatal information system.
The less affluent districtsalso have the less access to health facilities and the worst health results.
Conclusion
The Ile-de-France region faces marked inequalities in population characteristics and health outcomes. Implementing routine surveys about health access and inequalities in outcomes on a territorial basis is required for decisions in perinatal policy. This HIS is built from hospital based data with a geographical population analysis. Social disadvantage criteria linked to place of residence may be used when social informationsare missing data.
Keywords: perinatal care, health information system, health services research
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Table 1: Completeness of the data for living birth
HDS 2009 and INSEE 2009 (national vital statistics)
Table 2: Completeness of the data for stillbirths
HDS 2009 estimate stillbirth rate (Pregnancy termination for medical reasons included) by delivery stay
Table 3: Number of intensive carebeds
INSEE 2009
Table 4: Place of birth of less than 1500g newborns
HDS 2009
Table 5: Evolution of Very Preterm birth rate (<1500g)
HDS 2009
Table 6: Evolution of Preterm Birth rate
HDS 2009
Table 7: Stillbirth rates
INSEE 2009
Stillbirth rate* (including pregnancy termination for medical reason)
Table 8: Social disadvantage
INSEE 2007
Table 9 : Social disadvantage ranking and scoring
Figure 1: Distribution of total births in perinatal centres (HDS 2009)
Paris / 75Seine –et-Marne / 77
Yvelines / 78
Essonne / 91
Hauts-de-Seine / 92
Seine-Saint-Denis / 93
Val de Marne / 94
Val d’Oise / 95
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References:
ORS-IDF (2010), Actualisation et « régionalisation » de l’indicateur de développement humain L’indicateur dedéveloppement humain alternatif : IDH-2, Note Rapide , N° 528.
Rey G. (), Rican S, Jougla E.(2011), Measuring social inequalities in mortality by cause of death. Ecological approach based on social a deprivation index,BEH 8-9 / 8 mars 2011.
UNDP, The Human Development Index (HDI). Text available in the web-site:
WHO. CSDH. (2008), Closing the gap in a generation: health equity through action on the
social determinants of health. Final report of the Commission on Social
Determinants of Health, Geneva. Text available in the web-site:
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