1. 1 The Perinatal Periods of Risk CityMatCH http://www.citymatch.org/

2. 2 PPOR Maps Fetal & Infant Deaths PPOR Maps Fetal & Infant Deaths 500-1499 g 1500+ g Fetal Death Neonatal Post- neonatal Maternal Health/ Prematurity Maternal Care Newborn Care Infant Health Birthweight Age at Death

3. 3 PPOR analytic methods Analytic Preparation http://www.citymatch.org/PPOR/HowTo/Content/AnalyticReadinessWKSHOP.ppt  Acquire access to three required vital records computer files  Prepare vital records files and required data elements  Assess data quality  Assess study sample size

4. 4 PPOR analytic methods Phase I:THE MAPS http://www.citymatch.org/PPOR/HowTo/HowToDo.htm  Define study population  Restrict study population by birthweight and gestational age  Calculate numbers and rates for the feto-infant mortality map  Compare different time periods, subpopulations and geographic areas

5. 5 PPOR analytic methods Phase I, continued: THE GAPS  Select reference population  Calculate excess mortality rates and numbers of deaths  Identify excess mortality gaps

6. 6 PPOR Analytic Methods— Phase 2 Analysis Explains why the excess deaths occurred so that appropriate action can be taken.

7. 7 PPOR is about ACTION Maternal Health/ Prematurity Maternal Care Newborn Care Infant Health Preconception Health Health Behaviors Perinatal Care Prenatal Care High Risk Referral Obstetric Care Perinatal Management Neonatal Care Pediatric Surgery Sleep Position Breast Feeding Injury Prevention

8. 8 Three Phase 2 Directions Community health and health systems assessment Community health and health systems assessment Fetal Infant Mortality Reviews (FIMR) Fetal Infant Mortality Reviews (FIMR) Further epidemiologic study Further epidemiologic study PPOR Analytic Methods —

9. 9 Phase 2 Analysis The third direction is the focus of this presentation: Epidemiologically investigate the reasons for excess mortality Epidemiologically investigate the reasons for excess mortality

10. 10 PPOR Analytic Methods— Steps of Phase 2 Analysis :  Identify causal pathways or biologic mechanisms for excess mortality  Estimate prevalence of risk and preventive factors by type of mechanism  Estimate the impact of the risk and preventive factors.

11. 11 PPOR Phase 2 Analyses Limitations Large number of deaths needed to obtain statistically significant because models are complex and effect sizes are small. Large number of deaths needed to obtain statistically significant because models are complex and effect sizes are small. Unlikely to identify new causes because an observational study using vital records and existing data. Unlikely to identify new causes because an observational study using vital records and existing data. Unlikely to find a single cause for excess mortality because the feto-infant mortality it is a multifactorial problem Unlikely to find a single cause for excess mortality because the feto-infant mortality it is a multifactorial problem

12. 12 How can we most effectively determine the likely causes of excess deaths in our community?

13. 13 PPOR Phase 2 Analyses Strategy Eliminate factors unlikely to be contributing Eliminate factors unlikely to be contributing Find and target factors likely to be contributing Find and target factors likely to be contributing

14. 14 PPOR Phase 2 Analyses Strategy A factor is a likely contributor if: 1.KNOWN cause of death based on scientific literature. 2.MORE PREVALENT among the population with excess deaths Impact analysis helps prioritize among likely contributors

15. 15 Phase 2 Analysis Plan Depends on: Phase 1 Analysis results Phase 1 Analysis results Availability of data Availability of data Community priorities Community priorities

16. 16 Phase 2 Analysis Plan Guidelines Developed for : Infant Health Infant Health Maternal Health/Prematurity Maternal Health/Prematurity Recommendations for : Maternal Care Maternal Care

17. 17 Phase 2 Analyses Preparation The DEATH CERTIFICATE is the source of Age at death Age at death Cause of death Cause of death The BIRTH CERTIFICATE is the source for Maternal characteristics & risk factors Maternal characteristics & risk factors Circumstances of the birth Circumstances of the birth Infant risk factors & conditions Infant risk factors & conditions Geo-coding (mother’s residence) Geo-coding (mother’s residence)

18. 18 Phase 2 Analyses Preparation of data for impact estimation o Use a birth cohort file of live births and fetal deaths with linked deaths. o Convert death cohort files to a single birth cohort file Combine linked o Add fetal deaths for the same year with a variable indicating the outcome.

19. 19 Preparation of data for impact estimation Converting 2000 and 2001 Period Files to a 2000 Birth Cohort File Linked File Year Born Year Died Action 200019992000Omit 200020002000Keep 200120002001Keep 200120012001Omit

20. 20 Data Source> Birth/Fetal Certificate Death Cert. IDOutcome Birth- weight Maternal Age Cause of Death Fet01 Fetal Death 79817Infection Fet02 253734 Cong. Anomaly LB01Survive351122 LB02 Infant Death 231425SIDS LB03Survive129321 LB04 63126Infection Preparation of data for impact estimation Portion of birth cohort data file

21. 21 Phase 2 Data Preparation o Other files can be also now be linked to the combined study file o If geocoded according to street address, census tract or zip code (e.g.), GIS analysis including neighborhood and community factors, census, crime, housing, etc.

22. 22 Phase 2 Analyses Preparation OTHER DATA SETS to consider: Hospital discharge system Hospital discharge system PRAMS PRAMS Birth defects surveillance Birth defects surveillance Pregnancy/Pediatric Nutrition Surveillance Pregnancy/Pediatric Nutrition Surveillance Injury surveillance Injury surveillance STD reports STD reports Child abuse reporting systems Child abuse reporting systems Program files (Medicaid, WIC, etc) Program files (Medicaid, WIC, etc) Linked program files Linked program files

23. 23 When linked to birth certificates,other datasets can be used to estimate the impact of risk factors on mortality.

24. 24 INFANT HEALTH PERIOD INFANT HEALTH PERIOD Protocol is on the web at http://www.citymatch.org/PPOR/HowTo/Content/PHAS2IH.doc

25. 25 Phase 2 Analyses-Infant Health Period Identify causal pathways or biologic mechanisms for excess mortality Use Underlying Cause of Death Use Underlying Cause of Death Categorize by CDC’s Postneonatal Mortality Surveillance System Categorize by CDC’s Postneonatal Mortality Surveillance System  birth defects  infections  injuries  perinatal conditions  SIDS  other causes

26. 26 Infant Health SIDS Injury Infection Anomalies Each category has its own set of risk factors Perinatal Phase 2 Analyses-Infant Health Period Identify causal pathways or biologic mechanisms for excess mortality

27. 27 Cause-specific mortality rate (CSMR) the number of deaths in each category the number of deaths in each category number of live births>=1500g Excess Cause-specific mortality rate = Study Pop. CSMR – Ref. Pop. CSMR = Study Pop. CSMR – Ref. Pop. CSMR Phase 2 Analyses-Infant Health Period Identify causal pathways or biologic mechanisms for excess mortality

28. 28 Example City Number of IH Death s IH Death Rate Ref. IH Death Rate Excess CSMR Congenital Anomaly110.1790.160.019 Infection130.2110.140.071 SIDS751.2190.840.379 Perinatal Conditions310.5040.250.254 Other/Undefined160.2600.27-0.010 total IH1462.3721.660.712 Live Births >= 1500g61,540 Phase 2 Analyses-Infant Health Period Identify causal pathways or biologic mechanisms for excess mortality

29. 29 Example City Excess Infant Health Mortality Rate=0.712 per 1000 live births

30. 30 Passive smoke Passive smoke Sleep position Sleep position Breast-feeding Breast-feeding Bedding Bedding Co-sleep Co-sleep Maternal age Maternal age Death scene investigation Death scene investigation Folic acid intake Folic acid intake Alpha-feto protein Alpha-feto protein Alcohol Alcohol Drug abuse Drug abuse Diabetes Diabetes Ultrasound Ultrasound Delivery site Delivery site SIDSAnomalies Phase 2 Analyses-Infant Health Period Estimate prevalence of risk and preventive factors by type of mechanism

31. 31 Medical home Medical home Immunizations Immunizations Breast-feeding Breast-feeding Passive smoke Passive smoke Prenatal care Prenatal care Maternal age Maternal age Infection type Infection type Bedding Bedding Supervision Supervision Environment Environment Injury type Injury type InjuryInfection Phase 2 Analyses-Infant Health Period Estimate prevalence of risk and preventive factors by type of mechanism

32. 32 SIDS—major contributor to excess deaths SIDS—major contributor to excess deaths Examine risk factor disparity for SIDS Examine risk factor disparity for SIDS Compare prevalence between study population to reference population Compare prevalence between study population to reference population Denominator is all live births Denominator is all live births Estimate prevalence of risk and preventive factors by type of mechanism

33. 33 Phase 2 Analyses-Infant Health Period Phase 2 Analyses-Infant Health Period OTHER DATA SETS to consider: Hospital discharge system Hospital discharge system PRAMS PRAMS Birth defects surveillance Birth defects surveillance Pregnancy/Pediatric Nutrition Surveillance Pregnancy/Pediatric Nutrition Surveillance Injury surveillance Injury surveillance STD reports STD reports Child abuse reporting systems Child abuse reporting systems Program files (Medicaid, WIC, etc) Program files (Medicaid, WIC, etc) Linked program files Linked program files

34. 34 Phase 2 Analyses-Infant Health Period Example City Prevalence of SIDS Risk Factors Among Live Births Study versus Reference Populations

35. 35 Phase 2 Analyses-Infant Health Period Estimate the impact of the risk and preventive factors Risk Ratio or Relative Risk Probability of disease in the exposed population divided by the probability of disease in the unexposed population Probability of disease in the exposed population divided by the probability of disease in the unexposed population A/(A+B) A/(A+B)RR=C/(C+D) Outcome Yes OutcomeNo Risk Factor YesAB Risk Factor No CD

36. 36 Population Attributable Risk Percent Compares the rate for the whole population to the rate for those WITHOUT the risk factor Compares the rate for the whole population to the rate for those WITHOUT the risk factor Based on the relative risk and the prevalence of the exposure for the whole population. Based on the relative risk and the prevalence of the exposure for the whole population. Has a meaningful interpretation: “Percent of the population that would be prevented from the poor outcome if the risk factor were eliminated from the entire population.” Has a meaningful interpretation: “Percent of the population that would be prevented from the poor outcome if the risk factor were eliminated from the entire population.” Relevant to overall impact and cost. Relevant to overall impact and cost. Phase 2 Analyses-Infant Health Period Estimate the impact of the risk and preventive factors

37. 37 Population Attributable Risk Deb Rosenberg recommends using the formula PAR = P 0 – P 2 Where P 0 is the proportion of the whole population that have the bad outcome P 2 is the proportion of those without the risk factor that have the bad outcome. The difference is interpreted as the proportion of bad outcomes that would be eliminated if no-one in the population had the risk factor. This is the proportion of bad outcomes that can be “attributed” to the factor. Phase 2 Analyses-Infant Health Period Estimate the impact of the risk and preventive factors

38. 38 Population Attributable Risk Percent (PAR%) PAR% = {P (RR-1) /1+P (RR-1)} x 100 Where P = proportion of the population with a particular risk factor, and Where P = proportion of the population with a particular risk factor, and RR = Risk Ratio (can substitute Adjusted Odds Ratio or RR from logistic regression or published literature) RR = Risk Ratio (can substitute Adjusted Odds Ratio or RR from logistic regression or published literature) Phase 2 Analyses-Infant Health Period Estimate the impact of the risk and preventive factors

39. 39 PAR Resources http://www.soph.uab.edu/mch- imrm/stats.htm, LEVIN 1953, Fleiss 1981 p76 Calculator at : http://www.urmc.rochester.edu/cpm/educ ation/mach/PARC.xls http://www.urmc.rochester.edu/cpm/educ ation/mach/PARC.xls

40. 40 Phase 2 Analyses-Infant Health Period PAR% EXAMPLE: EXAMPLE INFANT MORTALITY ATTRIBUTABLE TO TEEN MATERNAL AGE Example: Example: RR=1.998 RR=1.998 PAR%=8.94 PAR%=8.94 Maternal Age Infant Deaths Infants Surviving <=19353082 >=2015927897 If no teen births occurred, 8.94% fewer babies would die in Example. This translates to 17 fewer deaths, or a reduction in IMR from 6.2 to 5.7 per thousand live births.

41. 41 MATERNAL HEALTH / PREMATURITY PERIOD Protocol is on the web at http://www.citymatch.org/PPOR/HowTo/Content/PHAS2MH.doc

42. 42 Causes for 500-1,499g are Multifactorial Multifactorial Complex Complex Inconsistent Inconsistent Varies by training Varies by training Phase 2 Analyses-Mat. Health/Prem. Identify causal pathways or biologic mechanisms for excess mortality

43. 43 Kitagawa’s formula algebraically partitions excess mortality into 2 strata portion to birthweight distribution portion to birthweight distribution portion to birthweight specific mortality portion to birthweight specific mortality Phase 2 Analyses-Mat. Health/Prem. Identify causal pathways or biologic mechanisms for excess mortality

44. 44 Kitagawa Phase 2 Analyses-Mat. Health/Prem. Identify causal pathways or biologic mechanisms for excess mortality Maternal Health/ Prematurity Birthweight Distribution Birthweight- Specific Mortality

45. 45 Phase 2 Analyses-Mat. Health/Prem. Identify causal pathways or biologic mechanisms for excess mortality The Kitagawa Formula The Kitagawa Formula Where “P” stands for birthweight distribution (proportion of births in stratum n) And “M” stands for specific mortality (the mortality rate in stratum n) http://www.citymatch.org/PPOR/HowTo/Content/kitgawa_updated_98_00.xls (save the spreadsheet on your own computer)

46. 46 Contribution to Mortality Difference Birth weight Bwt Dist. Mort. Rate Bwt Dist. Mort.Rate 500-7490.4%612.50.2%573.5 750-9990.4%205.50.2%244.3 1000-12490.3%166.70.2%134.6 1250-14990.5%117.00.3%98.0 1500-19991.9%66.91.1%50.4 2000-24994.9%20.13.4%19.9 2500+91.63.694.5%2.7 Total100%10.0100%6.0 Pinellas CountyNational Reference Group

47. 47 Contribution to Mortality Difference Pinellas County vs National Reference Group Birth Weight Birthweight Distribution Mortalit y Rate Combined 500-7491.40.11.5 750-9990.4-0.10.3 1000-12490.10.10.2 1250-14990.20.10.3 1500-19990.40.20.7 2000-24990.30.00.3 2500+-0.10.80.7 Total2.81.24.0

48. 48 Feto-Infant Mortality Contribution to Mortality Pinellas County vs National Reference Group Total Fetal Infant Mortality Maternal Health/ Prematurity Mortality

49. 49 Presenting kitagawa results Kitagawa: Most Common Conclusion “The predominant cause of death for VLBW babies is birthweight distribution: too many babies are born at very low weights. Our community will benefit most by preventing prematurity” “The predominant cause of death for VLBW babies is birthweight distribution: too many babies are born at very low weights. Our community will benefit most by preventing prematurity” “Birthweight-specific mortality nearly matches that of the reference group. Babies born too small are surviving nearly as well as babies in the reference group.” “Birthweight-specific mortality nearly matches that of the reference group. Babies born too small are surviving nearly as well as babies in the reference group.”

50. 50 Presenting kitagawa results Kitagawa: Some cities have up to 40% of excess deaths in the MH/P period of risk due to birthweight specific mortality. “Birthweight-specific mortality in our target group is not as good as it is in the reference group. Babies in that group that are born too small are not surviving as well as can be expected.” “Birthweight-specific mortality in our target group is not as good as it is in the reference group. Babies in that group that are born too small are not surviving as well as can be expected.”

51. 51 Smoking Smoking Prenatal care Prenatal care Race Race Maternal age Maternal age Parity Parity STD/Bacterial Vag. STD/Bacterial Vag. Multiple Preg. Multiple Preg. SES/Education SES/Education Birth Interval Birth Interval Maternal HTN/Diabetes Maternal HTN/Diabetes Gestational age Gestational age Referral system Referral system Perinatal care Perinatal care Mat. complications Mat. complications Neonatal conditions Neonatal conditions Pay source Pay source Birthweight Distribution (VLBW Births) Birthweight- Specific Mortality Phase 2 Analyses-Mat. Health/Prem. Estimate prevalence of risk and preventive factors by type of mechanism

52. 52 Maternal Health/ Prematurity Birthweight Distribution Birthweight- Specific Mortality Percent VLBW VLBW Births and Fetal Deaths All Births And Fetal Deaths Mortality Rate OUTCOMEDENOMINATOR Phase 2 Analyses-Mat. Health/Prem. Estimate prevalence of risk and preventive factors by type of mechanism

53. 53 Prematurity—major contributor to excess deaths Prematurity—major contributor to excess deaths Examine risk factor disparity for prematurity Examine risk factor disparity for prematurity Compare prevalence between study population to reference population Compare prevalence between study population to reference population Denominator is all live births Denominator is all live births Phase 2 Analyses-Mat. Health/Prem. Estimate prevalence of risk and preventive factors by type of mechanism

54. 54 Phase 2 Analyses-Mat. Health/Prem. Estimate prevalence of risk and preventive factors OTHER DATA SETS to consider: Hospital discharge system Hospital discharge system PRAMS PRAMS Birth defects surveillance Birth defects surveillance Pregnancy/Pediatric Nutrition Surveillance Pregnancy/Pediatric Nutrition Surveillance Injury surveillance Injury surveillance STD reports STD reports Child abuse reporting systems Child abuse reporting systems Program files (Medicaid, WIC, etc) Program files (Medicaid, WIC, etc) Linked program files Linked program files

55. 55 Should fetal deaths be included in study of VLBW Births? Risk factor information on fetal deaths is more frequently missing. Risk factor information on fetal deaths is more frequently missing. Excluding fetal deaths will have little impact because they make up less than 1% of all births in most communities. Excluding fetal deaths will have little impact because they make up less than 1% of all births in most communities.

56. 56 Example City Prevalence of Prematurity Risk Factors Non-Hispanic White versus Ref. Population

57. 57 Example City Prevalence of Prematurity Risk Factors Non-Hispanic Black versus Ref. Population

58. 58 Plurality PPOR analyses are not restricted to singleton live births. Multiple births contribute to a community’s feto-infant mortality rate and may contribute to an increasing rate or population disparity. These births should be include in Phase 1 Analysis and further studied as part of the Phase 2 Analysis

59. 59 Plurality—bill’s slide Multiple births can contribute to a community’s feto-infant mortality rate, increasing trend or population disparity. Phase 1 Analysis is not restricted to singleton live births. Phase 1 Analysis is not restricted to singleton live births. Plurality studied separately as part of Phase 2 Analyses. Plurality studied separately as part of Phase 2 Analyses.

60. 60 Plurality PPOR analyses are not restricted to singleton live births. Multiple births contribute to a community’s feto-infant mortality rate and may contribute to an increasing rate or population disparity. These births should be include in Phase 1 Analysis and further studied as part of the Phase 2 Analysis

61. 61 Map of Fetal-Infant Mortality Rates by Plurality Baltimore City 1997–99 61.8 (52) 0.0(0)34.4(29) 28.5(24) Total Rate = 124.7 per 1000 Multiple Gestation Excess Deaths = 95 5.4 (151) 3.3(92)1.0(29) 2.2(62) Total Rate = 11.9 per 1000 Singleton

62. 62 Map of Excess Fetal-Infant Deaths Baltimore City, 1997 – 1999 Multiple Gestation to Singleton Pregnancy

63. 63 FIMR Recommendations Multiple Gestation Pregnancy Baltimore City, 1997 – 1999 Increase awareness of the increased risk associated with multiple gestation pregnancy in the community. Increase awareness of the increased risk associated with multiple gestation pregnancy in the community. Improve case management of multiple gestation pregnancy. Improve case management of multiple gestation pregnancy. Educate the provider community Educate the provider community Modify the Prenatal Risk Assessment protocol to include multiple gestation as a risk factor for referral to the Maternal and Infant nursing program. Modify the Prenatal Risk Assessment protocol to include multiple gestation as a risk factor for referral to the Maternal and Infant nursing program.

64. 64 Relative risk Population attributable risk Logistic regression for adjusted odds ratios Phase 2 Analyses-Mat. Health/Prem. Estimate the impact of the risk and preventive factors

65. 65 Impact of Risk Factors for Orange County 1999 ComparisonAdjusted Odds- Ratio 95% Confidence Interval White Hispanics vs. Non-Whites Hispanics 1.1050.896-1.362 Black Non-Hispanic vs. White Non-Hispanics 1.6671.364-2.038 Odds Ratio adjusting for: Age, Marital Status, Number of Pre-natal visits, weight gain, mother’s education, mother’s tobacco use and mother’s alcohol use. Phase 2 Analyses-Mat. Health/Prem. Estimate the impact of the risk and preventive factors

66. 66 LNP Healthy Start – Pop. Attributable Risk for VLBW FactorPARRR (95% CI) Previous Preterm Delivery 16.0%136.9(59.0-341.7) Pregnancy Related Hypertension 11.8%4.8(3.1-7.3) Inadequate PNC and Eclampsia or Hypertension (Chronic or pregnancy induced) 8.3%3.7(1.6-7.6) Chronic Hypertension 6.7%3.3(1.5-6.5) Med Risk Factors and Inadequate PNC 3.3%2.5(1.5-4.0) High Parity 1.7%1.8(1.3-2.5) Smoking0.4%1.2(.79-1.7) Inadequate PNC 0%1.0(.7-1.4) PAR results help focus discussions on specific interventions for reduction of VLBW in Lower North HS area

67. 67 PPOR Phase II Analysis Useful Epidemiological Tools KitagawaKitagawa Relative RiskRelative Risk Odds RatioOdds Ratio Population Attributable RiskPopulation Attributable Risk Logistic RegressionLogistic Regression Poisson RegressionPoisson Regression Multi-level ModelingMulti-level Modeling

68. 68 MATERNAL CARE PERIOD

69. 69 Phase 2 Analyses-Maternal Care Period The epidemiology of fetal deaths is less known The epidemiology of fetal deaths is less known Fetal Deaths have more missing information Fetal Deaths have more missing information Causal pathways such as chromosomal abnormalities, severe congenital anomalies, and placental vascular abnormalities not captured on vital records Causal pathways such as chromosomal abnormalities, severe congenital anomalies, and placental vascular abnormalities not captured on vital records

70. 70 Phase 2 Analyses-Maternal Care Period Risk Factors that are more reliably collected on fetal death certificates include Birthweight and Gestational age Birthweight and Gestational age Maternal age and race Maternal age and race Parity and previous fetal loss Parity and previous fetal loss Smoking Smoking Education/socioeconomic Education/socioeconomic Inter-pregnancy interval Inter-pregnancy interval Multiple gestation Multiple gestation

71. 71 Phase 2 Analyses-Maternal Care Period Risk Factors from other data sources BMI BMI Weight gained during pregnancy adjusted for BMI Weight gained during pregnancy adjusted for BMI Diabetes Diabetes Hypertension Hypertension RH disease RH disease FIMR can be used to examine larger fetal deaths

72. 72 USE OF FIMR

73. 73 Integrating PPOR & FIMR PPOR and FIMR have complementary strengths. PPOR and FIMR use similar community- oriented processes. An existing FIMR Community Action Team might include the community stakeholders that the PPOR approach requires, and vice-versa.

74. 74 Integrating PPOR & FIMR FIMR data can help in Phase 2 of PPOR Analysis, as a way to better understand the reasons for excess deaths. PPOR can help an existing FIMR team by providing a context or framework for their case reviews and community action teams. PPOR can help a community focus their FIMR reviews on cases that will most benefit the community.

75. 75 Integrating FIMR & PPOR the Magnolia Project in Jacksonville, FL Annual update of contributing factors using PPOR framework Annual update of contributing factors using PPOR framework Case selection to gain info on PPOR areas of concern Case selection to gain info on PPOR areas of concern 2000-YTD 2003 case reviews: maternal health, black outcomes, target area (n=99) 2000-YTD 2003 case reviews: maternal health, black outcomes, target area (n=99)

76. 76 Integrating PPOR & FIMR the Magnolia Project in Jacksonville, FL, 1995-1999 MATERNAL HEALTH (n=28) 85%–Preterm labor or premature rupture of membranes 85%–Preterm labor or premature rupture of membranes 46%–Sexually transmitted diseases 46%–Sexually transmitted diseases 36%–Maternal age less than 21 years or more than 35 years 36%–Maternal age less than 21 years or more than 35 years 36%–No, late or inconsistent prenatal care 36%–No, late or inconsistent prenatal care 32%–Infant infection 32%–Infant infection 29%–Pre-existing medical condition 29%–Pre-existing medical condition 29%–Substance use (alcohol, tobacco or drugs) 29%–Substance use (alcohol, tobacco or drugs) 25%–Maternal obesity 25%–Maternal obesity 25%–History of previous adverse pregnancy outcome 25%–History of previous adverse pregnancy outcome 21%–Family planning issues 21%–Family planning issues MATERNAL CARE (n= 15) 67%–Sexually transmitted diseases 67%–Sexually transmitted diseases 47%–Lack of patient education 47%–Lack of patient education 33%–Maternal obesity 33%–Maternal obesity 33%–No, late or inconsistent prenatal care 33%–No, late or inconsistent prenatal care 33%–Substance use (alcohol, tobacco or drugs) 33%–Substance use (alcohol, tobacco or drugs)

77. 77 NEWBORN CARE (n=29) 55%–Pre-existing infant medical condition 55%–Pre-existing infant medical condition 45%–No, late or inconsistent prenatal care 45%–No, late or inconsistent prenatal care 34%–Maternal age less than 21 years or more than 35 years 34%–Maternal age less than 21 years or more than 35 years 31%–No Healthy Start screening completed 31%–No Healthy Start screening completed 28%–History of previous adverse pregnancy outcome 28%–History of previous adverse pregnancy outcome 21%–Family planning issues 21%–Family planning issues 21%–Lack of support systems 21%–Lack of support systems 21%–Preterm labor or premature rupture of membranes 21%–Preterm labor or premature rupture of membranes 21%–Sexually transmitted diseases 21%–Sexually transmitted diseases 21%–Substance use (alcohol, tobacco or drugs) 21%–Substance use (alcohol, tobacco or drugs) INFANT HEALTH (n=44) 52%–Sexually transmitted diseases 52%–Sexually transmitted diseases 48%–No, late or inconsistent prenatal care 48%–No, late or inconsistent prenatal care 41%–Need for SIDS education 41%–Need for SIDS education 36%–Maternal age less than 21 years or more than 35 years 36%–Maternal age less than 21 years or more than 35 years 25%–Pre-existing infant medical condition 25%–Pre-existing infant medical condition 25%–Maternal obesity 25%–Maternal obesity 23%–Lack of preventive and medical follow up 23%–Lack of preventive and medical follow up Integrating PPOR & FIMR the Magnolia Project in Jacksonville, FL, 1995-1999

78. 78 Role of FIMR the Magnolia Project in Jacksonville, FL Aggregate info on contributing factors can help identify specific needs, risks Aggregate info on contributing factors can help identify specific needs, risks FIMR info can be used to formulate, tailor interventions FIMR info can be used to formulate, tailor interventions FIMR findings can be used to monitor impact of new interventions FIMR findings can be used to monitor impact of new interventions PPOR questions can guide case selection process PPOR questions can guide case selection process

79. 79 USE OF GIS

80. 80 PPOR rates by Neighborhood Philadelphia, PA (red=higher than city rate Philadelphia, PA ) Maternal Health/ Prematurity Maternal Care Newborn Care Infant Health Total All Philadelphia 5.13.01.52.712.3 South5.21.61.72.110.6 Southwest4.63.71.63.613.5 West6.83.01.82.814.4 Lower North 9.53.52.23.518.7 Upper North 6.64.01.84.116.5 Bridesburg/ Kensington/ Richmond 4.33.81.72.612.4 Olney/oak Lane 4.22.70.73.911.5 Lower NE 3.52.41.31.3 8.5 8.5 Upper NE 3.23.81.40.7 9.1 9.1

81. 81 Very Low Birth Weight Births 1998-2000 Density Analysis Philadelphia, PA

82. 82 The Magnolia Project Project area: Project area: Five zip codes in NW Jacksonville Account for more than half of the Black infant mortality in the city Five zip codes in NW Jacksonville Account for more than half of the Black infant mortality in the city About 25,000 women age 15-44 years old live in the project area About 25,000 women age 15-44 years old live in the project area 85% African-American 85% African-American

83. 83