# Using Discharge Abstracts to Evaluate a Regional Perinatal Network: Assessment of the Linkage  Procedure of Anonymous Data

Authors: Catherine Quantin; Cyril Ferdynus; Paul Avillach; Béatrice Gouyon; Paul Sagot; Jean-Bernard Gouyon
Journal: International Journal of Telemedicine and Applications
 (2009)

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## Abstract

To assess the Burgundy perinatal network (18 obstetrical units; 18 500 births per year), discharge abstracts and additional data were collected for all mothers and newborns. In accordance with French law, data were rendered anonymous before statistical analysis, and were linked to patients using a specific procedure. This procedure allowed data concerning each mother to be linked to those for her newborn(s). This study showed that all mothers and newborns were included in the regional database; the data for all mothers were linked to those for their infant(s) in all cases. Additional data (gestational age) were obtained for 99.9% of newborns.


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## Body

## 1. Introduction

The Burgundy  perinatal network was created in 1992 to improve the quality of
perinatal care in Burgundy,
a French region with 1 800 000 inhabitants and 18 500 births annually.
This network gradually included the 18 private and public hospitals of Burgundy. The medical
steering committee, made up of medical representatives of each hospital (one
paediatrician and one obstetrician for each) has progressively reorganized
perinatal care in the region. In particular, medical conventions between hospitals
were signed to improve coordination of admissions, transfers of patients, and
the use of technical facilities. Moreover, a half-yearly systematic analysis of
perinatal deaths was initiated.The
impact of actions promoted in the perinatal network has been assessed yearly
since 1998.A
multidisciplinary working group previously chose and precisely defined specific
indicators (25 for each mother and 17 for each newborn) [1, 2]. These indicators
correspond to maternal medical history, psychosocial risk factors, maternal and
neonatal medical data such as hospitalisations during pregnancy, delivery
method, postpartum period, and the different hospitalisations of the newborns. Most
of these items could be obtained from the mandatory discharge abstracts for
each hospitalised patient within the Programme de Médicalisation du Système
d’Information (PMSI). The PMSI collection system was used as it is compulsory
in both public and private hospitals in France. Each hospital provides its
own perinatal data on a voluntary basis. These data are rendered anonymous
before being sent from each hospital to the committee in charge of the
assessment of the perinatal network’s performance (regional audit committee).Optimal
assessment of perinatal care obviously requires effective linkage between
maternal and neonatal data. Indeed, in order to study the mechanisms of
neonatal diseases it is essential to link (1) the abstracts of a mother to
those of her newborn even if they were not cared for in the same hospital and (2)
all discharge abstracts for the same patient (mother and/or newborns), who may
have several discharge abstracts from different hospitals. In our case, this
happens when an antenatal or postnatal transfer from one hospital to another is
decided, according to the written rules for good medical practice in the
perinatal network.This
study intends to assess the performance of the file-linkage process of maternal
and neonatal data used for the evaluation of the Burgundy perinatal network.


## 2. Materials and Methods

### 2.1. Population

All
deliveries and births, whether live  or not, are included in the perinatal
network if the gestational age is at least 22 weeks
and/or if the birth weight is greater than 500 g. For the purpose of this
study, we took into account the population included from 1998, the year data
collection began, to 2001.
In 1998, only nine hospitals participated in the data
collection, whereas in 2001 all of the 18 hospitals involved in the regional
perinatal care network were involved, thus providing data for 100% of the 18 500 annual births.


### 2.2. Data Collection

Discharge
abstracts for all mothers (social and medical data about gestation, childbirth
and the postnatal period) and all newborns (hospitalisations in maternity
hospitals, paediatric wards, neonatal units, and neonatal intensive care units)
collected within the PMSI were provided by each hospital in Burgundy. The collection of discharge
abstracts is mandatory and does not require the agreement of the patient. The
usual data collection system of the PMSI was expanded to include the collection
of birth weight and gestational age. Moreover, six identification items (maiden
names, first names and birth dates of mothers, first names and birth dates of newborns,
zip codes of the main residence of mothers) were recorded for both mothers and newborns
to allow linkage between their discharge abstracts.


### 2.3. Anonymity of Information

The Directive 95/46/CE of the European Parliament and
of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data and the Actn°78-17 of 6
January 1978 on Data Processing, Data Files and Individual
Liberties (amended by the Act of 6 August 2004 relating to
the protection of individuals with regard to the processing of
personal data) are the European and French legislations on
data privacy and security. Following these recommendations,
the data were rendered anonymous in each hospital using 3
ANONYMAT software [3–5]. The principle of this  software based on the Standard Hash Algorithm is to
ensure the irreversible transformation of independent fields, which prevents
the identification of an individual. The aim is to obtain a strictly anonymous
code, but always the same one for a given couple of a mother and her newborn(s).
The use of ANONYMAT software has been authorized by the French Department for
Information System Security (SCSSI), and in 1998 the French data protection
commission (Commission Nationale de l'Information
et des Libertés—CNIL) specifically
authorized the management of perinatal data in Burgundy. The collection of the data does
not require the specific consent of the patient, who only has to be informed
that the information contained in discharge abstracts will be used for
epidemiological purposes and not only for budgetary purposes. An information
leaflet explaining the use of the data is given to the patient on admission to
the hospital.In
order to reduce the impact of typing errors, spelling transformation was
introduced into the anonymity process before hash coding. The principle is to
transform the spelling of names according to phonetic rules. Among the
different treatments, SOUNDEX is most widely used. However, in the perinatal
network, a treatment specifically adapted to the particularities of the French
language was used [6].


### 2.4. File Linkage

Once
rendered anonymous, the data were transmitted to the regional audit committee
located in the University Hospital of Dijon (France) and included in a regional
database (cf. Figure1). The first part of the linkage process is to gather all
discharge abstracts concerning the same patient (mother or newborns) from the
same or different hospitals. The second part is devoted to linking the
abstracts of a mother to those of her newborn even if they were not cared for
in the same hospital. In order to respect the confidentiality of medical files,
linkage is carried out on files that are rendered anonymous and not directly on
nominative data. Technically, there is no difference between using original
nominative data or one-way hash-coded data for record linkage, as the
correspondence between these data is almost one-to-one (low collision rate). In
fact, the spelling processing used in the anonymity procedure reduces the
impact of typing errors and increases the efficiency of the linkage. However,
two types of linkage errors are of concern: erroneous links of notifications
(information) from two distinct patients, also called homonym errors, and
failure to link multiple notifications (information) on the same patient, also
called synonym errors.Figure 1
File linkage.These
errors would be reduced if we could use the French Identification Number which
is unique for each individual. However, this number is not recorded by
hospitals, which only use the Social Security Number (SSN), which is not unique
for each individual as it is assigned to each insured person, who may register
his family under the same SSN. Thus, the SSN of a woman may change, for
example, after her marriage. Moreover, communication of the SSN is not allowed
by French legislation except for the transmission of information from
private-sector hospitals to French health-insurance companies.Therefore,
we have developed a record linkage system which is based on the method proposed
by Jaro [7] and takes into account the 6 identification variables.In
this procedure, like in other probabilistic methods [8–15], a weight is
associated with each variable according to the reliability of the information
provided. The weight given to two identical dates of birth is then higher than
that given to two identical zip codes, as date of birth is more discriminating
than zip code. It is then possible to compute the weight corresponding to each
pair of records by summing the positive weights obtained for concordant
variables and negative weights for discordant variables. Two threshold values
can then be computed, from which three sets of possible decisions can be
determined as follows: (1) the pair is matched; (2) no determination is made; (3)
the pair is not matched. In case 2, no determination, other information is
explored.


### 2.5. Reliability of the Linkage Procedure

It
was assumed that a link between a mother and a noncorresponding newborn was impossible
in the case of perfect agreement between two records on the 6 identification
items. Indeed, it is highly unlikely that in the same maternity hospital, two
women having the same zip code, the same maiden name, the same first name, the
same birth date would give birth on the same day to babies with the same first
name. Additionally, the risk for a homonym error was very low (10−48) with the standard hash algorithm [16].In
a perinatal network, it is obvious that every newborn has a mother and vice
versa. When a mother abandons her infant at birth and has the right to remain
anonymous, the maiden name, the first name, and the date of birth of the mother
were filled with
random numbers and thus rendered anonymous in the hospital file before hash
coding, both in the mother’s and in the newborn’s files. As the linkage items for
the mother and her newborn are the same (filled in with the same numbers),
linkage is possible.So,
the fact that no link was found between a newborn and a mother would indicate
either a linkage error or the lack of the mother’s record. Linkage errors were
identified by again using the linkage method on the basis of only five items or
even four. To verify these potential links, each hospital was asked to verify
the identification items of the records corresponding to the given anonymous
numbers. The corrected data were rendered anonymous before being returned from
the hospitals to the regional database.Finally,
the linkage was only performed on the basis of all 6 identification items in
the final database.


### 2.6. Data Validation

Before
linkage, the exhaustiveness of both medical items and linkage items was monitored as follows:
(1) exhaustiveness for the 6 linkage items was verified for each discharge
abstract; (2) exhaustiveness for gestational age and birth weight was verified
for each neonatal discharge abstract.After
linkage, the exhaustiveness for the number of mothers and newborns registered
in the regional database was assessed from hand-written notebooks which are
used in each hospital for the registration of births and/or admissions of sick
newborns to units caring for these infants. The law requires these hand-written
notebooks to be completed.Regarding
data quality, computerized procedures have also been developed to reveal
discrepancies between medical data or between dates of exit and admission for
successive hospitalisations. These inconsistencies were validated by a
paediatrician. All erroneous data were then corrected in the nominative files
in each hospital, before being rendered anonymous and sent back to the regional
database. As a consequence, after validation, the number of mothers and
newborns agreed with hand-written notebooks, and the medical or administrative
inconsistencies between discharge abstracts were corrected. We then considered
data after validation as a gold standard for the assessment of the linkage
procedure (on data before validation).


## 2.1. Population

All
deliveries and births, whether live  or not, are included in the perinatal
network if the gestational age is at least 22 weeks
and/or if the birth weight is greater than 500 g. For the purpose of this
study, we took into account the population included from 1998, the year data
collection began, to 2001.
In 1998, only nine hospitals participated in the data
collection, whereas in 2001 all of the 18 hospitals involved in the regional
perinatal care network were involved, thus providing data for 100% of the 18 500 annual births.


## 2.2. Data Collection

Discharge
abstracts for all mothers (social and medical data about gestation, childbirth
and the postnatal period) and all newborns (hospitalisations in maternity
hospitals, paediatric wards, neonatal units, and neonatal intensive care units)
collected within the PMSI were provided by each hospital in Burgundy. The collection of discharge
abstracts is mandatory and does not require the agreement of the patient. The
usual data collection system of the PMSI was expanded to include the collection
of birth weight and gestational age. Moreover, six identification items (maiden
names, first names and birth dates of mothers, first names and birth dates of newborns,
zip codes of the main residence of mothers) were recorded for both mothers and newborns
to allow linkage between their discharge abstracts.


## 2.3. Anonymity of Information

The Directive 95/46/CE of the European Parliament and
of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data and the Actn°78-17 of 6
January 1978 on Data Processing, Data Files and Individual
Liberties (amended by the Act of 6 August 2004 relating to
the protection of individuals with regard to the processing of
personal data) are the European and French legislations on
data privacy and security. Following these recommendations,
the data were rendered anonymous in each hospital using 3
ANONYMAT software [3–5]. The principle of this  software based on the Standard Hash Algorithm is to
ensure the irreversible transformation of independent fields, which prevents
the identification of an individual. The aim is to obtain a strictly anonymous
code, but always the same one for a given couple of a mother and her newborn(s).
The use of ANONYMAT software has been authorized by the French Department for
Information System Security (SCSSI), and in 1998 the French data protection
commission (Commission Nationale de l'Information
et des Libertés—CNIL) specifically
authorized the management of perinatal data in Burgundy. The collection of the data does
not require the specific consent of the patient, who only has to be informed
that the information contained in discharge abstracts will be used for
epidemiological purposes and not only for budgetary purposes. An information
leaflet explaining the use of the data is given to the patient on admission to
the hospital.In
order to reduce the impact of typing errors, spelling transformation was
introduced into the anonymity process before hash coding. The principle is to
transform the spelling of names according to phonetic rules. Among the
different treatments, SOUNDEX is most widely used. However, in the perinatal
network, a treatment specifically adapted to the particularities of the French
language was used [6].


## 2.4. File Linkage

Once
rendered anonymous, the data were transmitted to the regional audit committee
located in the University Hospital of Dijon (France) and included in a regional
database (cf. Figure1). The first part of the linkage process is to gather all
discharge abstracts concerning the same patient (mother or newborns) from the
same or different hospitals. The second part is devoted to linking the
abstracts of a mother to those of her newborn even if they were not cared for
in the same hospital. In order to respect the confidentiality of medical files,
linkage is carried out on files that are rendered anonymous and not directly on
nominative data. Technically, there is no difference between using original
nominative data or one-way hash-coded data for record linkage, as the
correspondence between these data is almost one-to-one (low collision rate). In
fact, the spelling processing used in the anonymity procedure reduces the
impact of typing errors and increases the efficiency of the linkage. However,
two types of linkage errors are of concern: erroneous links of notifications
(information) from two distinct patients, also called homonym errors, and
failure to link multiple notifications (information) on the same patient, also
called synonym errors.Figure 1
File linkage.These
errors would be reduced if we could use the French Identification Number which
is unique for each individual. However, this number is not recorded by
hospitals, which only use the Social Security Number (SSN), which is not unique
for each individual as it is assigned to each insured person, who may register
his family under the same SSN. Thus, the SSN of a woman may change, for
example, after her marriage. Moreover, communication of the SSN is not allowed
by French legislation except for the transmission of information from
private-sector hospitals to French health-insurance companies.Therefore,
we have developed a record linkage system which is based on the method proposed
by Jaro [7] and takes into account the 6 identification variables.In
this procedure, like in other probabilistic methods [8–15], a weight is
associated with each variable according to the reliability of the information
provided. The weight given to two identical dates of birth is then higher than
that given to two identical zip codes, as date of birth is more discriminating
than zip code. It is then possible to compute the weight corresponding to each
pair of records by summing the positive weights obtained for concordant
variables and negative weights for discordant variables. Two threshold values
can then be computed, from which three sets of possible decisions can be
determined as follows: (1) the pair is matched; (2) no determination is made; (3)
the pair is not matched. In case 2, no determination, other information is
explored.


## 2.5. Reliability of the Linkage Procedure

It
was assumed that a link between a mother and a noncorresponding newborn was impossible
in the case of perfect agreement between two records on the 6 identification
items. Indeed, it is highly unlikely that in the same maternity hospital, two
women having the same zip code, the same maiden name, the same first name, the
same birth date would give birth on the same day to babies with the same first
name. Additionally, the risk for a homonym error was very low (10−48) with the standard hash algorithm [16].In
a perinatal network, it is obvious that every newborn has a mother and vice
versa. When a mother abandons her infant at birth and has the right to remain
anonymous, the maiden name, the first name, and the date of birth of the mother
were filled with
random numbers and thus rendered anonymous in the hospital file before hash
coding, both in the mother’s and in the newborn’s files. As the linkage items for
the mother and her newborn are the same (filled in with the same numbers),
linkage is possible.So,
the fact that no link was found between a newborn and a mother would indicate
either a linkage error or the lack of the mother’s record. Linkage errors were
identified by again using the linkage method on the basis of only five items or
even four. To verify these potential links, each hospital was asked to verify
the identification items of the records corresponding to the given anonymous
numbers. The corrected data were rendered anonymous before being returned from
the hospitals to the regional database.Finally,
the linkage was only performed on the basis of all 6 identification items in
the final database.


## 2.6. Data Validation

Before
linkage, the exhaustiveness of both medical items and linkage items was monitored as follows:
(1) exhaustiveness for the 6 linkage items was verified for each discharge
abstract; (2) exhaustiveness for gestational age and birth weight was verified
for each neonatal discharge abstract.After
linkage, the exhaustiveness for the number of mothers and newborns registered
in the regional database was assessed from hand-written notebooks which are
used in each hospital for the registration of births and/or admissions of sick
newborns to units caring for these infants. The law requires these hand-written
notebooks to be completed.Regarding
data quality, computerized procedures have also been developed to reveal
discrepancies between medical data or between dates of exit and admission for
successive hospitalisations. These inconsistencies were validated by a
paediatrician. All erroneous data were then corrected in the nominative files
in each hospital, before being rendered anonymous and sent back to the regional
database. As a consequence, after validation, the number of mothers and
newborns agreed with hand-written notebooks, and the medical or administrative
inconsistencies between discharge abstracts were corrected. We then considered
data after validation as a gold standard for the assessment of the linkage
procedure (on data before validation).


## 3. Results

This
collection started in 1998. The exhaustiveness of data collection and the
linkage rate have improved with time.During
validation after linkage, the number of mothers and newborns registered in the
regional database was assessed from the hand-written notebooks which are used
in each hospital for the registration of births and/or admissions of sick
newborns to units caring for these infants. At the beginning of the collection
in 1998 or 1999, we detected some discrepancies. We thus had to modify the
selection criteria for data collection. From 2000, the consistency between
these numbers was perfect.(1) Exhaustiveness of Discharge Abstracts
In 1998, 9 hospitals were involved in the collection of discharge abstracts.
Abstracts for 84.1% and 99.1% of all eligible mothers were retrieved in the
regional database, respectively, before and after the validation procedure; for
newborns, the percentages were 100% and 98.7%. Overestimation of the
hospitalisation rate in some neonatal files in 1998 was explained by undue
inclusion of hospitalisation beyond the neonatal period.
From
2001 to 2005, 18 hospitals were involved in the collection of discharge
abstracts and the overall exhaustiveness for both mothers and newborns reached
99.9% after the validation procedure. The exhaustiveness of discharge abstracts
was 100% but some mothers may not have been hospitalised if the delivery
occurred at home.(2) Exhaustiveness of the Data in the Discharge Abstracts
In
1998, the six items used for the linkage procedure were recorded in 80% of
discharge abstracts before validation and in 99% after validation. From 2001 to
2005, the exhaustiveness of these items was between 91.9% and 98.5% before and 100% after validation.(3) Linkage Assessment
Before
validation, the percentage of newborns linked to their corresponding mothers on
the basis of the 6 identification items was 71% in 1998, 92.9% in 2001, and
93.4% in 2005.
Different
types of errors were found during the validation procedure after linkage. The
most frequent one corresponded to errors in spelling surnames and first names [6]
leading to phonetic changes that were not subsequently corrected by the
spelling processing included in the ANONYMAT software. The inversion of the
married name, and the maiden name, during data collection was also a source of
linkage failure, and was corrected through the validation procedure. After
validation, 99.98% of newborns were linked to their mothers whatever the year
concerned. Only newborns who were transferred from a hospital of the Burgundy
Region to a hospital of another region were missed (0.2%).
The
results regarding the assessment of the linkage procedure, using validated data
as a gold standard, are presented in Table1, for each year.
Sensitivity
is most often higher than 90% (97.1% in 2006). Of course the figure regarding
the first year is lower. The year 2004 may be considered as an outlier: several
hospitals had to change their software and faced many difficulties in
collecting data. Specificity is nearly always higher than 85%, except in 2006
(77.7%).
The
estimation of the false positive and false negative rates, given in Table1,
also indicates an unexpected higher rate of false positives in 2006 (5.3%). The
analysis of the false positives is presented in Table 2, which provides, in
case of false positives, the percentage of missing data for each identification
item. We can observe that the main reason for false positives appears to be
related to missing data; this was particularly the case in 2006. Among false
positives, 85.11% were due to perfect concordance between the record of the
baby and the record of the mother on the birth dates of the mother and on the
zip codes of the main residence of the mother, while the other items were
nearly all missing.
Of
course, in these cases, agreement between the two records on the 6
identification items cannot be considered perfect. In fact, in case of missing
data on an identification item, the two records are considered discordant on
this item.
For
false negatives, the same analysis is presented in Table3. Here again, missing
data is the main cause. In particular, because of missing data on the maiden
and first names of the mother, the two records were often considered discordant
on these items, which prevented linkage of these records. Hopefully these
errors have been corrected thanks to the validation procedure.Table 1
Assessment of the linkage
procedure: sensitivity, specificity, rates of true positives (TP), true
negatives (TN), false negatives (FN), and false positives (FP), for each year.
YearsRecords no.Sensitivity (%)Specificity (%)TP (%)TN (%)FN (%)FP (%)19981786589.0495.2585.683.5910.550.1819991576997.5397.8289.048.522.250.1920002094197.2497.7786.3510.502.450.7020012507093.0387.4778.9913.205.921.8920022548994.1789.7479.7213.764.941.5720032526493.8286.8478.6414.055.182.1320042597688.2687.3169.1418.919.202.7520052444093.1386.0270.5720.845.203.3920062723897.0977.7473.9718.512.215.30Table 2
Percentages of missing data
for each identification item, among false positives, for each year.
YearsMaiden name (%)Mother’s first name (%)Mother’s date of birth (%)Infant’s first name (%)Infant’s date of birth (%)Zip code (%)199843.7518.7518.7546.8840.6318.75199933.3333.3320.0056.6753.3320.0020003.711.681.8922.4616.721.33200189.8790.080.2197.8997.680.21200278.3079.0529.6897.0196.510.50200384.9484.390.3798.1498.140.37200469.3356.300.1486.4195.380.00200582.4958.828.7074.7679.118.82200675.2171.050.0797.0297.850.14Table 3
Percentages of missing data
for each identification item, among false negatives, for each year.
YearsMaiden name (%)Mother’s first name (%)Mother’s date of birth (%)Infant’s first name (%)Infant’s date of birth (%)Zip code (%)199895.3397.4097.4091.1490.980.32199955.4994.0894.0812.685.632.54200062.6267.9169.2820.9416.0525.24200145.0440.5323.7427.9227.112.63200258.2227.4029.4734.4719.301.03200333.1032.4239.5359.5624.921.91200427.4625.6611.8538.8030.850.63200588.3687.6619.6587.1981.923.07200674.9674.4671.9747.4332.341.00


## 4. Discussion

### 4.1. Discussion of the Results

Optimal
assessment of perinatal care needs a linkage procedure between successive files
for the same patient and between files for the mothers and their corresponding newborn(s).
The latter linkage was found to be essential in the assessment of the postnatal
consequences of antenatal risk factors and maternal diseases. For instance, in
1999, one maternity hospital showed significantly higher rates of both
Caesarean section and neonatal hospitalisation compared with regional and
national rates. The linkage procedure revealed that the excess in neonatal
hospitalisations was related to an excess in the use of caesarean section in a
population of mothers similar to that admitted to other maternity hospitals in Burgundy. This study was
performed after adjustment for gestational age and maternal diseases. This
discrepancy was particularly noticeable for full-term infants. This finding was
a strong argument for reorganising perinatal care leading to a significant
decrease in the use of Caesarean section in this hospital.The
fact that each mother corresponded to a newborn and vice versa was particularly
helpful in testing the linkage procedure. Indeed, this study demonstrated that
coupling the direct linkage of anonymous data files with the validation
procedure that takes into account the potential links revealed by the
statistical procedure generated very satisfactory results on a regional scale.This
linkage method could also be used to link the siblings (having the same
mother). The linkage of(1)
full brothers or sisters  by sorting the dates of birth of all the individuals with
the same parents,(2)
half brothers and sisters  by sorting the dates of birth of all the individuals
with the same father or the same mother,
would require the implementation of a new identifier, such as the family-based
identifier (also including the names and date of birth of the father) [17, 18].The
assessment method used in Burgundy relied on the PMSI system. The main advantages of using the PMSI information
system were that this data collection system is mandatory in all French
hospitals and that the classification used in this program (i.e., the
International Disease classification—10th revision) contained most of the items
necessary for an audit of the perinatal network. Moreover, the number of
additional items included was limited. Although PMSI was not designed for the
assessment of care networks, using this information system made it unnecessary
to set up another data collection system in each participating hospital and
thus avoided duplication of work.However,
the collection of additional data and the need to extract items from PMSI required
extension of the existing software in each hospital. Moreover, these changes involved
several companies that were more or less interested in modifying their
software. These changes have thus been implemented slowly over a 3-year period.Overall,
the collection and analysis of perinatal data had a substantial cost. Each
hospital spent 1000 euros for changes in the PMSI software. Moreover, health
professionals and a computer engineer were needed for validation procedures,
management of the regional database, statistical analyses, transmitting
regional data to the medical steering committee, drafting reports, and helping
the hospitals to improve item recording.Our
results showed that satisfactory collection of the linkage items was more
difficult to obtain than was the collection of medical items. This is easily
explained by the fact that physicians are less motivated to collect
administrative data. Therefore, the validation procedure for the identification
items was made a cornerstone in the quality process.The
results regarding the assessment of the linkage procedure revealed that
sensitivity and specificity are quite high (resp., higher than 90% and 85%).
The decrease in sensitivity in 2004 is related to software changes in several
hospitals. The decrease in specificity in 2006, as well as the overall false
positive rate among the whole period, seemed to be the consequence of missing
data. These observations led us to propose harmonization of the procedures
(software and rules for collecting data) in all hospitals. This initiative,
called the EXTRANAT project, is described in the next section.


### 4.2. Perspectives for the Development of the Perinatal Network

The Burgundy perinatal
network was created in 1992 because of the high perinatal morbidity and
mortality in France (7th highest
among OCDE countries) notably in Burgundy (14th
highest in France).Since 1995, it has included the following.(i)
A hierarchal interestablishment
network of all of the maternity clinics (1 type III maternity clinic, 2 type II
maternity clinics, 8 type I maternity clinics, and 4 local perinatal care
centers). The missions of each establishment and the criteria and procedures
for the transfer of the mother (before or after delivery) and the newborn have
been defined.(ii)
A common paper-based record document.(iii)
An original and exhaustive evaluation system,
based on the PMSI, for all of the 18 000 annual pregnancies, with anonymization of data in each
establishment after discharge, and linkage between the mother and her infant.Thanks to the
combination of these three elements and to the perseverance of those involved
in perinatal care and the Burgundy DIM, since 1999, our region has climbed to
be among the top three in France
with regard to low maternal and perinatal mortality and morbidity.However,
though retrospective analysis of records on perinatal mortality showed a
considerable improvement in the quality of intra- and interhospital care
between 1996 and 2003 (in-utero transfers for extremely premature births,
high-risk patients, antenatal corticotherapy, pediatric care at the maternity
clinic), it also revealed a significant deterioration in preclinic conditions, showing
the need to set up an “extranet” tool for all of those involved in perinatal
care (GPs, specialists, midwives), whether they are based in public hospitals,
in private practice or in Mother and Child Care Centres (Protection Maternelle
et Infantile).This is the
rationale behind the “Extranat Bourgogne”
project, a computer system to facilitate(i)
the communication (between professionals),(ii)
the training and the evaluation of
professional practices (discussions about protocols),(iii)
the implementation of shared interactive
computerized medical records, with the medical and organizational references of
the network.Thanks to Extranat,
it will be possible to have real-time communication, and regular meetings in the
form of videoconferences (telemedicine) to study problem cases. The telemedicine
system is already up and running and Extranat is currently being set up.The aim of
this project is to fulfill the three missions of the perinatal network as follows:(i)
improvement of the quality of care by enabling the health-care professional to input
initial medical data (no longer final data at discharge from the
establishment). This is a criterion in the improvement in information
collection and in the sharing of medical data with complementary specialists
(specialists in women’s health, specialists in neonatal health for infants that
may be transferred to other medical departments or other establishments),(ii)
evaluation of professional practices,
which requires identification and anonymization of the professionals concerned,(iii)
evaluation of the medical and organizational
aspects of the Burgundy perinatal network
(anonymized database with mother-child linkage), already operational and presented
in this article.It is
therefore essential for the new Extranat system to use the same patient
identification and anonymization system (mothers, newborns, fathers) as the perinatal
network, so as to(i)
provide access (limited and
controlled) to medical data for professionals who are treating the mother or newborn
(data identified at the physician’s practice and/or the medical establishment),(ii)
respect the anonymization
requirements for data for the patients (as requested by the CNIL), and for the
professionals, in the regional data base.


## 4.1. Discussion of the Results

Optimal
assessment of perinatal care needs a linkage procedure between successive files
for the same patient and between files for the mothers and their corresponding newborn(s).
The latter linkage was found to be essential in the assessment of the postnatal
consequences of antenatal risk factors and maternal diseases. For instance, in
1999, one maternity hospital showed significantly higher rates of both
Caesarean section and neonatal hospitalisation compared with regional and
national rates. The linkage procedure revealed that the excess in neonatal
hospitalisations was related to an excess in the use of caesarean section in a
population of mothers similar to that admitted to other maternity hospitals in Burgundy. This study was
performed after adjustment for gestational age and maternal diseases. This
discrepancy was particularly noticeable for full-term infants. This finding was
a strong argument for reorganising perinatal care leading to a significant
decrease in the use of Caesarean section in this hospital.The
fact that each mother corresponded to a newborn and vice versa was particularly
helpful in testing the linkage procedure. Indeed, this study demonstrated that
coupling the direct linkage of anonymous data files with the validation
procedure that takes into account the potential links revealed by the
statistical procedure generated very satisfactory results on a regional scale.This
linkage method could also be used to link the siblings (having the same
mother). The linkage of(1)
full brothers or sisters  by sorting the dates of birth of all the individuals with
the same parents,(2)
half brothers and sisters  by sorting the dates of birth of all the individuals
with the same father or the same mother,
would require the implementation of a new identifier, such as the family-based
identifier (also including the names and date of birth of the father) [17, 18].The
assessment method used in Burgundy relied on the PMSI system. The main advantages of using the PMSI information
system were that this data collection system is mandatory in all French
hospitals and that the classification used in this program (i.e., the
International Disease classification—10th revision) contained most of the items
necessary for an audit of the perinatal network. Moreover, the number of
additional items included was limited. Although PMSI was not designed for the
assessment of care networks, using this information system made it unnecessary
to set up another data collection system in each participating hospital and
thus avoided duplication of work.However,
the collection of additional data and the need to extract items from PMSI required
extension of the existing software in each hospital. Moreover, these changes involved
several companies that were more or less interested in modifying their
software. These changes have thus been implemented slowly over a 3-year period.Overall,
the collection and analysis of perinatal data had a substantial cost. Each
hospital spent 1000 euros for changes in the PMSI software. Moreover, health
professionals and a computer engineer were needed for validation procedures,
management of the regional database, statistical analyses, transmitting
regional data to the medical steering committee, drafting reports, and helping
the hospitals to improve item recording.Our
results showed that satisfactory collection of the linkage items was more
difficult to obtain than was the collection of medical items. This is easily
explained by the fact that physicians are less motivated to collect
administrative data. Therefore, the validation procedure for the identification
items was made a cornerstone in the quality process.The
results regarding the assessment of the linkage procedure revealed that
sensitivity and specificity are quite high (resp., higher than 90% and 85%).
The decrease in sensitivity in 2004 is related to software changes in several
hospitals. The decrease in specificity in 2006, as well as the overall false
positive rate among the whole period, seemed to be the consequence of missing
data. These observations led us to propose harmonization of the procedures
(software and rules for collecting data) in all hospitals. This initiative,
called the EXTRANAT project, is described in the next section.


## 4.2. Perspectives for the Development of the Perinatal Network

The Burgundy perinatal
network was created in 1992 because of the high perinatal morbidity and
mortality in France (7th highest
among OCDE countries) notably in Burgundy (14th
highest in France).Since 1995, it has included the following.(i)
A hierarchal interestablishment
network of all of the maternity clinics (1 type III maternity clinic, 2 type II
maternity clinics, 8 type I maternity clinics, and 4 local perinatal care
centers). The missions of each establishment and the criteria and procedures
for the transfer of the mother (before or after delivery) and the newborn have
been defined.(ii)
A common paper-based record document.(iii)
An original and exhaustive evaluation system,
based on the PMSI, for all of the 18 000 annual pregnancies, with anonymization of data in each
establishment after discharge, and linkage between the mother and her infant.Thanks to the
combination of these three elements and to the perseverance of those involved
in perinatal care and the Burgundy DIM, since 1999, our region has climbed to
be among the top three in France
with regard to low maternal and perinatal mortality and morbidity.However,
though retrospective analysis of records on perinatal mortality showed a
considerable improvement in the quality of intra- and interhospital care
between 1996 and 2003 (in-utero transfers for extremely premature births,
high-risk patients, antenatal corticotherapy, pediatric care at the maternity
clinic), it also revealed a significant deterioration in preclinic conditions, showing
the need to set up an “extranet” tool for all of those involved in perinatal
care (GPs, specialists, midwives), whether they are based in public hospitals,
in private practice or in Mother and Child Care Centres (Protection Maternelle
et Infantile).This is the
rationale behind the “Extranat Bourgogne”
project, a computer system to facilitate(i)
the communication (between professionals),(ii)
the training and the evaluation of
professional practices (discussions about protocols),(iii)
the implementation of shared interactive
computerized medical records, with the medical and organizational references of
the network.Thanks to Extranat,
it will be possible to have real-time communication, and regular meetings in the
form of videoconferences (telemedicine) to study problem cases. The telemedicine
system is already up and running and Extranat is currently being set up.The aim of
this project is to fulfill the three missions of the perinatal network as follows:(i)
improvement of the quality of care by enabling the health-care professional to input
initial medical data (no longer final data at discharge from the
establishment). This is a criterion in the improvement in information
collection and in the sharing of medical data with complementary specialists
(specialists in women’s health, specialists in neonatal health for infants that
may be transferred to other medical departments or other establishments),(ii)
evaluation of professional practices,
which requires identification and anonymization of the professionals concerned,(iii)
evaluation of the medical and organizational
aspects of the Burgundy perinatal network
(anonymized database with mother-child linkage), already operational and presented
in this article.It is
therefore essential for the new Extranat system to use the same patient
identification and anonymization system (mothers, newborns, fathers) as the perinatal
network, so as to(i)
provide access (limited and
controlled) to medical data for professionals who are treating the mother or newborn
(data identified at the physician’s practice and/or the medical establishment),(ii)
respect the anonymization
requirements for data for the patients (as requested by the CNIL), and for the
professionals, in the regional data base.


## 5. Conclusion

It is possible to set up a continuous and exhaustive recording system for linked
perinatal data to assess the quality of care on a regional scale. A pre-existing
database like PMSI may be valuable, but may have to be extended if necessary.
The linkage of anonymous files may greatly enhance the accuracy of the
assessment procedure. These principles of assessment of a perinatal network
could be extended to other medical domains.



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*Source: 181842-2008-12-23.xml*