1. Perinatal Periods of Risk: Using Data and Community Involvement to Prevent Infant Mortality Introduction & Overview

2. INTERNATIONAL EXPERTISE
Dr. Brian McCarthy and colleagues at the
Centers for Disease Control and Prevention
and the World Health Organization knew
that causes of perinatal death are closely related
to both age at death and birth weight. ?
Why not use both pieces of information to learn more about why babies are dying?
The World Health Organization had been working on infant mortality in developing nations, so a group of CityMatCH member cities and CDC people went to them for help. The experts knew that causes of fetal and infant mortality are related to both how old the baby was when he or she died, and how much he weighed at birth. Why not use BOTH pieces of information to learn more?
Phase 1

3. Experts used statistics to combine boxes with similar causes of death and risk factors
Fetal Deaths
Early Neonatal
Late Neonatal
Post- neonatal
Extremely Low Birthweight g
Very Low Birthweight
1,000-1,499 g
The experts used statistics to combine the periods of risk if they had similar causes of death and similar maternal risk factors. If the boxes are that much alike, they don’t need to be analyzed separately. Combining them into blue, pink, yellow and green boxes, simplifies our work, without losing important information. As you can see, we end up with four periods of risk.
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Low Birthweight
1,500-2,499 g 9 10 11 12
Normal Birthweight
2,500 + g 13 14 15 16
Introduction & Overview of PPOR
Phase 1

4. Four Perinatal Periods of Risk named to suggest prevention areas
Fetal Deaths >=24 wks
Post -neonatal
Neonatal
Maternal Health / Prematurity g
The four periods of risk were given labels that suggest the primary preventive direction for the deaths in that group.
[VLBW related deaths can best be prevented by addressing maternal health issues and by preventing and treating prematurity. For HBW related deaths, fetal deaths can best be prevented by providing maternal care, neonatal deaths by providing newborn care, and postneonatal deaths by improving infant health. ]
Notice that the blue box does not include deaths that were less than 500 grams at birth. The experts found that there is inconsistent reporting for the very smallest fetal and infant deaths, not only across the US, but even at the local level, sometimes even between two physicians in the same hospital. It is not possible to make fair comparisons if reporting is inconsistent.
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Maternal Care
Newborn
Care
Infant Health 9 10 11 12
1500+ g 13 14 15 16
Introduction & Overview of PPOR
Phase 1

5. …which means they also had similar SOLUTIONS.
The dividing lines had been chosen so deaths in the same “box” had similar PROBLEMS:
Causes of death
Maternal risk factors
…which means they also had similar SOLUTIONS.
Remember that the dividing lines were chosen so that deaths in the same period of risk had very similar problems. They had both similar causes of death and similar maternal risk factors. The important point is that since deaths within one period of risk had similar problems, they will also have similar solutions.
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6. Each period of risk is associated with
its own set of risk and prevention factors
Preconception Health Health Behaviors
Perinatal Care
etc.
Maternal Health / Prematurity
Prenatal Care
High Risk Referral Obstetric Care
etc.
Maternal Care
Perinatal Management Neonatal Care Pediatric Surgery
etc.
Newborn Care
Infant
Health
Sleep-related Deaths
Injuries
Infections
etc.
Intro to PPOR 6

7. Urban County PPOR “map”
They calculated the rate
for each period of risk the same way,
using the same denominator 97
Maternal Health/ Prematurity
(4.2 ) 48
Maternal Care 44
Newborn Care 47
Infant Health
Urban county went on to do the same calculation in every period of risk, and produced this PPOR “map” .
Of course the period with the most deaths also had the highest rate, because all the rates were calculated with the same denominator.
The advantage of rates is that now we can compare to other populations with a different number of live births and fetal deaths.
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(2.1 )
(1.9 )
(2.0 )
Urban County PPOR “map”
Phase 1

8. “What rates can we expect to see in each Period of Risk?”
PPOR answers this question using a reference group, a real population of mothers that experience best outcomes:
low fetal and infant mortality rates.
The question we really need to ask is “What rates can we EXPECT to see in each period of risk?”
PPOR has a very practical way of answering this question. We use a reference group which is a REAL POPULATION OF MOTHERS that experiences low mortality rates.
We sort the deaths in this real-life group, and calculate the rates in each period of risk the same way we do for our study population. 8

9. The Reference Group is about Justice
The underlying assumption is that if the reference group can have low mortality, our study group should be able to reach that goal.
The reference group is about justice. We make the assumption that IF the reference group population has low mortality, THEN our study population should be able to reach the same goal.
Doesn’t that make sense? Why should our community accept higher mortality rates?
One key part of PPOR is that the community stakeholders group gets to choose the reference group, and they choose it because they believe their own community or study population should be able to reach the same low mortality rates.
[For an internal reference group, a community should attempt to select a population group with better or optimal pregnancy outcomes for the community, a population group that can serve as a model. In general, this group should represent roughly 15% or more of the population. For the U.S., a suggested reference group is infants and fetuses born to non-Hispanic white mothers of 20 or more years of age having 13 or more years of education. This group usually represents more than 15% of the population and has the optimal outcomes in most U.S. cities. Moreover, the mortality rates for this population group are readily available through current vital records system. There are potentially better reference groups that could lead to more specific actions, but frequently quality information may not be available for that population group within the community. Clearly, the community group that is using this approach needs to develop consensus on the reference group. Otherwise, the findings will have little meaning or purpose.]
Community stakeholders choose the reference group. They agree that it is an appropriate standard or goal for their community. 9

10. The difference between rates, or the “gap”, represents “excess mortality” and it means that some of the deaths were preventable.
4.2
2.1
1.9
2.0
Urban County
1.1
0.9
1.5
2.2
Reference Group
Gap
2.0 =
The same calculation is done for the other three periods of risk, and the result is a new PPOR Map of EXCESS MORTALITY. The mortality gap, the difference between the Urban County and the Reference Group, represents excess mortality or preventable deaths.
The pattern of excess mortality is not the same as the pattern of mortality rates in the first PPOR Map. In the excess mortality map on the left the pink and green boxes are very similar, but in the Gap map on the right you can see that the green box is contributing more to Urban County’s preventable deaths than the pink box is. And in Urban County the blue box is contributing the most to both mortality and excess mortality.
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0.6
0.8
1.1

11. and narrowed the scope of their investigation
SUCCESS!
They had eliminated many potential causes
and narrowed the scope of their investigation
Preconception Health Health Behaviors
Perinatal Care
etc.
Maternal Health / Prematurity
Prenatal Care
High Risk Referral Obstetric Care
etc.
Maternal Care
Perinatal Management Neonatal Care Pediatric Surgery
etc.
Newborn Care
One part of their payoff was that REMEMBER THOSE LISTS OF CAUSES AND PREVENTION ACTIVITIES WE SHOWED YOU AT THE BEGINNING? WELL, URBAN COUNTY HAD NOW eliminated two OF THOSE FOUR lists that they might have been investigating.
Urban county could still work on preventing larger stillbirths, but since there is not much excess mortality in the pink box, they would have a difficult time because even the reference population hasn’t reduced their rates in those periods. Urban county could still work on newborn care, yellow box, but since there was not much excess mortality in the yellow box, the doctors and NICUs in Urban County seem to be doing a good job of taking care of newborns – at least as good a job as they’re doing with the reference population. (and by the way, those doctors were much happier about the county’s investigation after they saw those numbers.)
In Contrast, in the blue box , the reference population probably has something going for it that urban county doesn’t have. It might be better preconception health, or healthier behaviors, or earlier or better prenatal care, or recognition and treatment of early labor or many other possibilites
In the green box it might be that the reference population has fewer SUIDS or suffocation deaths, better prevention of accidents, better access to medical homes for treatment of infections … you get the idea.
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Infant
Health
Sleep-related Deaths
Injuries
Infections
etc.
Intro to PPOR 11

12. There are three helpful steps in Phase 2 Analysis
Identify the most important probable causes or mechanisms for excess mortality
Examine risk factors for those causes, by comparing the study and reference populations
Phase 2 uses this three-step strategy to help prioritize among the potential risk factors .
1 Identify the most important probable causes or mechanisms for excess mortality
2Examine risk factors for those causes, by comparing the study and reference populations
3 Estimate potential impact of risk factors
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Estimate potential impact of risk factors
Intro to PPOR 12

13. Phase 2 Analysis Example for the Infant Health Period of Risk
There are many common causes of death in the Infant Health Period of Risk
SIDS/SUID
Suffocation
Drowning
Car accidents
Assault
Infections
Congenital anomalies
etc.
What are some of the causes of death in this period of risk? If a baby is not born very low birth weight, and has already made it through the first month, what can cause his death at that point?
These are common causes – but the first task in Phase 2 is to try to figure out which of these is causing the most EXCESS mortality in Urban County. That’s a little different from which is the most common cause of death. A cause may be very common, but if that cause is common in the reference group too, it won’t be causing our EXCESS deaths. And it won’t be a good place to focus our initial efforts because if the best-case group hasn’t been able to overcome whatever it is, it will not be “low hanging fruit” for our stakeholders to tacke.
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Step 1 is to find out which of these are causing excess mortality in our community.
Intro to PPOR 13

14. Step 1. The dozens of ICD-10 codes were grouped,
and mortality rates calculated for each group
in both the study and reference populations.
Urban County grouped the remaining causes of death into five more categories: congenital anomalies, ill-defined (which were heart and breathing related), infections, injuries, and perinatal conditions. Then they calculated a mortality rate for each cause group
Here we can see that the Sleep-related grouping accounts for most of the difference between the study and reference populations.
[using as a denominator the babies born at over 1,500 grams and surviving at least 28 days .]

15. Phase 2 Analysis Example for the Infant Health Period of Risk
There are many common causes of death in the Infant Health Period of Risk
SIDS/SUID
Suffocation
Drowning
Car accidents
Assault
Infections
Congenital anomalies
etc.
What are some of the causes of death in this period of risk? If a baby is not born very low birth weight, and has already made it through the first month, what can cause his death at that point?
These are common causes – but the first task in Phase 2 is to try to figure out which of these is causing the most EXCESS mortality in Urban County. That’s a little different from which is the most common cause of death. A cause may be very common, but if that cause is common in the reference group too, it won’t be causing our EXCESS deaths. And it won’t be a good place to focus our initial efforts because if the best-case group hasn’t been able to overcome whatever it is, it will not be “low hanging fruit” for our stakeholders to tacke.
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They had eliminated causes that were not large contributors to their excess infant mortality, and further narrowed the scope of their investigation.
Intro to PPOR 15

16. Step 2: In Urban County, how common are the
known risk factors for sleep related deaths?
Compare study and reference groups if possible.
Sleep position
Maternal smoking
Passive smoke
Bedding
Co-sleeping
Crib availability and use
Parental substance abuse
Death scene investigation
This is a list of known risk factors for SUIDS and sleep-related deaths. For almost two decades there have been campaigns to teach care givers not to put babies to sleep on their stomach. Maternal smoking, and smoking near the baby has also been linked to SUIDS. The CDC now advises people to put babies to sleep on their backs, in a crib with no blankets or pillows or anything else. Many infant deaths have been attributed to sleeping with an adult or sibling. Having access to a crib may be an important risk factor, and parents use of drugs has been linked to some deaths. How death scenes are investigated can influence how they are recorded, and the resulting rate.
For each risk factor, Urban County stakeholders tried to find data on their study population. Vital records data provided some of the answers. Other sources that vary from city to city might include PRAMS, YRBS, BRFSS surveys, Healthy Start data, Medicaid and private insurance data, hospital data, child death review systems, and FIMR can also be helpful. 16

17. Step 2: Since more mothers in Urban County smoked, this could be contributing to the gap.
In the first step of Phase 2 Urban County had found that the most important causes of their EXCESS mortality were sleep-related . Their second step was to find out how common the risk factors for sleep related deaths were.
Maternal smoking information is available from birth certificates and in some surveys. Smoking is generally under-reported but if it’s under-reported by the same amount for both groups it still gives us an idea of the disparity. Here it looks like Urban County moms were more likely to be smokers than reference group moms, so smoking COULD have contributed to their excess mortality.
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18. Step 2: Over 70% of Urban County babies were put to sleep on their backs, which is as good as the best states. Prone sleep position is less likely to be contributing to the gap.
PRAMS (the Pregnancy Risk Assessment Monitoring System) is a CDC survey of new moms. It normally gives only state data. This state provided some county-level PRAMS data on the percent of babies that were put to sleep on their backs.
It looks as though babies in Urban County were almost as likely to be sleeping on their backs as the babies in the BEST states. This means tummy-sleeping was less likely to be contributing to Urban County’s SUIDS gap.
But, notice that we don’t have PRAMS data for the national reference group that Urban County used. Those green bars are overall state rates of back-sleeping. It is possible that the reference group would have a higher rate. When we don’t have exactly what we want, we use the closest substitute, but we have to understand its limitations.

19. Step 2: Other important information
Child abuse investigators on the team reported that couches, blankets, and parental drug use had been factors in several “SIDS” death cases.
A survey of local obstetricians revealed that
Most doctors did not discuss safe sleep with expectant mothers
Most were not aware of available smoking cessation services
Child abuse investigators who were contracted to investigate infant deaths for the police were members of the stakeholders group. They reported that couches, blankets, and parental drug use had been factors in several infant death cases that were called SIDS deaths.
A lot of time was spent doing a survey of local obstetricians to see what guidance they were offering their prenatal care patients.
Most doctors did not discuss safe sleep with expectant mothers
Most were not aware of available smoking cessation services

20. Step 2: Guided by PPOR findings, the Fetal Infant Mortality Review team focused on Sleep-related deaths for six months.
The FIMR Case Review Team reported that the physical and mental health of mothers was a factor in many of these deaths, including
chronic stressful conditions
lack of social support
Urban County stakeholders had access to other kinds of information too. They worked closely with their county’s FIMR Community Action Team which modified their usual FIMR process and had their case review team review ONLY SUIDs and sleep related deaths for six months, to see if they could learn about factors that are not reported on any survey or on death certificates. They found that the mothers of most these babies had both physical and mental health problems, including extremely stressful lives and lack of social support.

21. The stakeholders weighed the evidence and sought more information as needed.
The stakeholders weighed all this evidence, and the more they found out, the more questions they had, and the data committee kept investigating. I am sure you are thinking of good questions and potential data issues even as I am speaking, and I hope you will type them in for the moderator, because questions help us do our job better.
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Phase 2 investigations can continue
as questions arise and more data becomes available

22. SUCCESS in Outcomes PPOR 1993-2009 Urban County
Fetal-Infant Rate=10.7
The decrease in mortality rates can’t
necessarily all be attributed to PPOR
Fetal-Infant Rate=10.3
4.0
2.3
1.4
2.9
Fetal-Infant Rate=8.8
4.1
2.5
1.8
1.9
Fetal-Infant Rate=8.2
3.5
After a decade of this work, the overall Fetal and infant mortality rate in Urban County had decreased, and looking at the boxes, this was mostly because the GREEN BOX rate had gone down. While it is impossible to prove that this was because of PPOR, the community stakeholders group is not planning to stop doing PPOR any time soon.
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1.9
1.4
2.0
3.9
2.0
1.0
1.3 22 22