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Data Tools for MCH Professionals: Introduction to Local Data Sources and Analytic Considerations

Data Tools for MCH Professionals: Introduction to Local Data Sources and Analytic Considerations. Michael D. Kogan, PhD Director, Office of Data and Program Development US Dept of Health and Human Services Health Resources and Services Administration Maternal and Child Health Bureau

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Data Tools for MCH Professionals: Introduction to Local Data Sources and Analytic Considerations

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  1. Data Tools for MCH Professionals:Introduction to Local Data Sources and Analytic Considerations Michael D. Kogan, PhD Director, Office of Data and Program Development US Dept of Health and Human Services Health Resources and Services Administration Maternal and Child Health Bureau Laurin Kasehagen Robinson, PhD Senior MCH Epidemiologist CDC Assignee to CityMatCH Adjunct Assistant Professor in Pediatrics University of Nebraska Medical Center

  2. Workshop Overview • Role of local health departments • Importance of local data • Evidence-based public health • Introduction to basic epidemiologic concepts • Introduction to local data sources and overview of the reference guides • What’s available • How to use it • Advantages and limitations of these data sources • Hands-on case studies I and presentations • Break • Hands-on case studies II and presentations • Discussion • What was most useful? • What was missing?

  3. Role of Local Health Departments • Local health departments • play a key role in the provision of public health services to both rural and urban communities • are the closest source for information on and assistance with public health issues and concerns in a community • Serve 3 core functions

  4. Core Function #1 • Assess community problems, needs, and resources, through • Health needs assessments • Data • Surveillance

  5. Core Function #2 • Provide leadership in organizing strategies to address health problems, through • Programs designed to meet community needs

  6. Core Function #3 • Assure that direct services necessary for meeting local public health goals are available to all community residents, through • Community health services, including • Screenings • Education • Prevention • Outreach

  7. Why is local data important? • Essence of the importance of local level data summarized by Shah, Whitman & Silva in “Variations in the Health Conditions of 6 Chicago Community Areas: A Case for Local-Level Data” • “Variations in health measures identified at the local level shed light on the limitations of the existing city data often used in establishing public health policies and monitoring population health. . . . [Such] data are essential in identifying communities most at risk of poor health outcomes, exploring the determinants of such variations in health, and ultimately guiding community health programs and policies.”

  8. Potential Limitations of / for Local Data • Often limited to jurisdictions with populations of at least 100,000 • Why? Issues of small numbers, accuracy and confidentiality • Sometimes limited because of relatively rare events • E.g., maternal mortality, autism, teen pregnancies, unintentional injuries • The data may not be current • Denominators may be based on the 2000 Census • City / County / MSA population may be based on 2000 Census • Data may not be collected at the household or city or county level

  9. Evidence-Based Public Health: Gathering and Using the Best Evidence for Local Data

  10. Evidence-Based Medicine • Health care practices based on review of current best evidence on the effectiveness of a test, drug, surgery or other medical practice • Collect and analyze all of the research studies conducted on a particular intervention • Evidence is then graded • Best evidence based on findings from clinical trials and meta-analysis • Weakest evidence based on case reports

  11. Definition of Evidence-Based Public Health • “EBPH is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of communities and populations in the domain of health protection, disease prevention, health maintenance and improvement.” Jenicek (1997)

  12. Differences between Public Health and Medicine

  13. So what is “best evidence”?

  14. Best Evidence • Makes sense (it’s relevant) • Unbiased • Available • Statistically significant • Significant to public health • Leads to correct decisions

  15. Statistical significance Meaningful to Public Health BOTH GOOD BEST FAIR We have been taught to accept statistical significance. If large samples (as in many cases), we are bound to have statistical significance, even if it is not meaningful. Evidence

  16. Steps of Evidence-Based Public Health • Develop an initial statement of the issue • Search the scientific literature and organize information • Quantify the issue using sources of existing data • Develop and prioritize program options; implement interventions • Evaluate the program or policy

  17. VERY STRONG VERY WEAK Randomized control trials Active surveillance, some clinical studies Routinely collected data, case review programs Review processes, personal anecdotes, gut feelings Different Sources of Evidence in Public Health: The Information Continuum

  18. So why isn’t evidence-based decision-making used more often?

  19. How are Decisions Often Made? • Decisions on policies and programs are often made based on: • Personal experience • What we learned in formal training • What we heard at a conference • What a funding agency required / suggested • What others are doing

  20. Evidence and Public Health Decision Making • Good news • Strong evidence on the effect of many policies / programs aimed to improve public health, like immunizations or smoking cessation • Major efforts underway to assess the body of evidence for wide range of public health interventions, like the Cochrane Collaborative or the AMCHP Best Practices program

  21. What Works to Improve the Public’s Health? • Bad news • Many public health professionals are unaware of this evidence • Some who are aware don’t use it • Many existing disease control programs have interventions with insufficient evidence –while others use interventions with strong evidence of effectiveness • Lack of use of effective interventions can adversely affect fulfilling mission and getting public support

  22. Evidence-Based Maternal and Child Health • True or false? • For women who are experiencing problems with their pregnancy, bed rest is effective in preventing preterm labor.

  23. Evidence-Based Maternal and Child Health • FALSE! • Obstetric practices for which there is little evidence of effectiveness in preventing or treating preterm labor include bed rest. (Goldenberg, Obstetrics and Gynecology, 2002)

  24. The True Story of the 3 Local MCH Departments and Governor Wolf’s Office

  25. Once… • …the office of Governor Wolf called up the first local MCH department and wanted to know the preterm birth rate for 2006 and 2007. • The local data staff ran to the computer and quickly calculated the number of preterm births divided by the number of normal gestational age births. • And proudly showed it to the Governor.

  26. “That’s not a rate, that’s a ratio!!!” thundered Governor Wolf (who had a doctorate in epidemiology). • And he huffed and he puffed and he blew away 25% of their funding.

  27. So, the office of Governor Wolf called up the second local MCH department and wanted to know the preterm birth rate for 2006 and 2007. • The local data staff ran to the computer and quickly calculated the number of preterm births divided by the total number of births. • And proudly showed it to the Governor.

  28. “Great,” said the Gov, “is it the same in 2006 and 2007?” • “Oh, we’re not sure of the year” said the second local MCH staff. • “Then it’s not a rate, it’s a proportion!!!” thundered Governor Wolf. • And he huffed and he puffed and he blew away 35.8% of their funding.

  29. And then, Governor Wolf called up the third local MCH department and wanted to know the preterm birth rate for 2006 and 2007. • The local data staff ran to the computer and quickly calculated the number of preterm births divided by the total number of births for each year. • And proudly showed them to the Governor.

  30. “Great,” said the Gov, “is it the same in 2006 and 2007?” • “No, it was 12.8 per 100 live births in 2006, and 10.2 per 100 live births in 2007; a significant decline” said the third local MCH department staff. • “Excellent!!!” cried Governor Wolf.

  31. And he wiped out their funding altogether because of an immediate state budget crisis.

  32. Was Governor Wolf correct? Or, would any of the local health department responses suffice? (or, was the Governor just throwing around his epidemiologic weight)

  33. Why is this a ratio? Why is this a proportion? Why is this a rate? Why does it matter? What are the implications if the wrong measure is used?

  34. Measures of Disease Frequency 92.0% 1.049:1 3,763,758 4,090,007 RATES 6,694 COUNTS PROPORTIONS RATIOS 161.8 per 100,000

  35. Counts Simplest, most frequently performed quantitative measure in epidemiology Refer to the number of cases of disease, injury, events, or other health phenomenon being studied Examples No. of pregnant women who were screened for Hepatitis B during a prenatal care visit No. of women who initiated breastfeeding in the U.S. in 2007 No. of newborns screened for genetic, metabolic, hormonal and/or functional conditions within 24-48 hours of birth

  36. Why isn’t enumeration sufficient? • Can’t / Don’t always detect ALL events • Census • Sample • How would you know whether the counts • Represent events that are big, small, a problem, important? • Represent phenomena common or unique to a population? • Change over time? • Are similar or different between 2 different populations?

  37. Frequency Measures – Ratio, Proportion, Rate All 3 frequency measures have the same form: numerator denominator x 10n • Characterize part of a distribution • Can be used to compare one part of a distribution to another part of a distribution • Contrast to measures of central tendency that provide single values that summarize entire distributions of data (e.g., mean, median, mode) From “Births: Final Data for 2004” in the National Vital Statistics Reports, vol. 55(1):21, Sept 29, 2006.

  38. What is a ratio? • A fraction in which the numerator is NOT part of the denominator • Numerator and denominator need not be related • Limits -- ∞ to ∞ • Result is often expressed as the “x”:1 • E.g., • male-to-female ratio • no. of controls to no. of cases • no. of LBW births to no. of violent crimes in a neighborhood

  39. How to Calculate a Ratio Ratio = Number or rate of events, items, persons, etc. in one group Number or rate of events, items, persons, etc. in another group Example: Sex ratio – male live births to female live births = 2,118,982 / 2,019,367 = 1.049:1 (or 1,049 male live births per 1,000 female live births)

  40. What is a proportion? Compares a part to the whole The numerator is ALWAYS part of the denominator Type of ratio, “x/y” May be expressed as a decimal, a fraction, or a percentage Limits – 0 to 1 In epidemiology, tells us the fraction of the population that’s affected E.g., proportion of children in a school vaccinated against measles proportion of women in PRAMS who initiated breastfeeding % of women who initiated PNC in the 1st trimester

  41. How to Calculate a Proportion Proportion = Number of persons or events with a particular characteristic Total number of persons or events of which the numerator is a subset Example: Proportion (%) of 2003 live births with birthweights of 2500 grams or greater = 3,763,758 / 4,090,007 = 92.0% From “Infant Mortality Statistics from the 2003 Period Linked Birth/Infant Death Data Set”, NVSR 54(16):1, May 3, 2006.

  42. What is a rate? • A ratio that consists of a numerator and a denominator in which TIME forms a part of the denominator • Measures the frequency with which an event occurs in a defined population over a specified period of time From “Births: Final Data for 2005” in the National Vital Statistics Reports, vol. 56(6):1, December 5, 2007.

  43. Properties and Uses of Rates Useful for putting disease frequency in the perspective of the size of the population Can be used to compare among different groups of persons with potentially different sized populations (i.e., rate is a measure of risk) Limits – 0 to ∞ Can be expressed in any form that is convenient (e.g., per 1000, per 100,000, etc.)

  44. How to Calculate a Rate Rate = No. of persons or events in a given time period No. of persons or events in a reference population (at mid-point of year or time period) Example: 2005 Triplet or higher order multiples birth rate in the United States = 6,694 / 4,138,349 = 161.8 per 100,000 births

  45. Are percentages ratios? Proportions? And/or Rates? • Yes, Ratio – e.g., number of mothers in one group (e.g., 1st trimester) over the number of mothers in another group (e.g., all who had late or no PNC) • Yes, Proportion – e.g., the ratio of mothers in one group who are a subset of the other group • Perhaps, Rate – when percentages are a ratio that consists of a numerator and a denominator in which TIME forms a part of the denominator

  46. Incidence Refers to the occurrence of new cases of disease, injury, attribute or events in a population over a specified period of time Is a proportion, rate Fundamental tool for exploring the etiology and causality of disease because new events provide estimates of risk of developing disease Several types of incidence measures Incidence proportion Attack rates Incidence rate

  47. How to Calculate Incidence Proportion (Risk) Incidence Number of NEW cases of disease, injury, events, or deaths Proportion = during a specified period of time _______________________________________________ Population at start of the specified period of time Example: 2007 Incidence of chickenpox in the United States 519 incident cases of chickenpox in the United States = 519 / 301,139,950 = 1.72 per 1,000,000 population From “Table II. Provisional cases of selected notifiable diseases, United States” in the MMWR, vol. 57(1):26, January 11, 2008.

  48. Uses of Incidence Data Determining the extent of a disease or health problem in a community Helping to determine etiology of disease because an estimate of risk of developing disease can be calculated Identifying changes in disease over time Comparing incidence rates in populations that differ in exposure – permits estimation of effects of exposure to a hypothesized factor of interest

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