Data collection and analysis

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Assumptions. You have already had extensive coursework in your public health graduate programYou are starting to get your feet wet in your state assignmentsWhat will be of interest here is information specific to working in state public health agenciesOr, here's some stuff other people might not

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Data collection and analysis

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1. Data collection and analysis CSTE/CDC Epidemiology Fellows Orientation, Atlanta, GA, Sept. 1, 2009 Richard S. Hopkins, MD, MSPH

2. Assumptions You have already had extensive coursework in your public health graduate program You are starting to get your feet wet in your state assignments What will be of interest here is information specific to working in state public health agencies Or, here’s some stuff other people might not have told you

3. Topics to be addressed Data sources Every state is different Death certificates Surveys Working with other agencies Identifying interesting questions Choice of analytic techniques Program evaluation Public health surveillance principles + random comments and tidbits

4. Commonly available data sources Reportable diseases Infectious and non-infectious Electronic laboratory reporting Cancer Birth defects Occupational diseases Population-based surveys BRFSS Don’t forget infectious disease items PRAMS

5. More commonly available sources Hospital discharge data May be maintained by state hospital association Access is often quite restricted Some include data from other clinical settings (FL has records from outpatient surgical clinics, EDs, and radiation therapy centers) Death, birth, and fetal death certificate data Linked infant death-birth files are powerful School-based surveys Youth risk behavior survey Substance use surveys

6. Sidebar: cause of death Who assigns the cause of death? Hint: It’s not the doctor What are those lines on the certificate? Immediate cause of death Due to, or as a consequence of.…. Other conditions present but not contributing to death ICD-9, ICD-10 ICD 10 used in death classification since 1999 ICD-9 CM, now ICD-10 CM ICD9-CM is NOT identical to ICD9 out at the third and fourth digit. Take care!

7. Sidebar (2): cause of death Underlying cause is assigned by an internationally-agreed upon algorithm Used to be done by people called nosologists Now is mostly done by machine Nosologists now make sure there is enough data on certificate to allow classification Any mention, ACME, multiple cause

8. More on cause of death Which of these is the underlying cause? Measles and malnutrition Pneumonia and leukemia Heart disease and diabetes What does it mean to say that deaths are attributable to a particular cause? (e.g. “smoking-attributable deaths”) Excess deaths Population attributable risk percent What is a hurricane-associated death?

9. Some other data sources Public health program service data Patients seen in public health clinics (STD, HIV/AIDS, TB, prenatal, well child, WIC, special needs children, primary care) Usually not population-based Who does NOT come to public health clinics? Some immunization registries are close to population-based Usually readily accessible

10. More data sources School entry (kindergarten) screening results Other school screenings (vision, hearing, height, weight, scoliosis, etc) Special education student records Visits to school health and mental health facilities Driver’s license files (height and weight) Highway crash data files Driver arrest and conviction records Calls to suicide hot lines

11. More data sources ED visits Part of hospital discharge data collection system in some states Syndromic surveillance systems (RODS, ESSENCE etc) Trauma registry Definition of trauma? EMS run reports 911 calls Spinal cord injury registries

12. Data sources of the future Electronic health records Hospitals (admission, lab, pharmacy, radiology records) Outpatient encounter records Electronic laboratory reporting is the leading edge Emerging ‘electronic case detection’ Using combinations of results and observations in EHRs to identify possible cases Candidate cases still have to be evaluated against surveillance case definition Health Information Exchanges and RHIOs Aggregate and exchange EHRs in a community Potentially extremely rich surveillance data source

13. Some things to ask about data sources of interest Timeliness – how old are the data when you can get access? Population coverage – whole state, selected populations? Sensitivity – what fraction of cases you are interested in are in the data set? Positive predictive value – closely related to other aspects of data quality – what fraction of ‘cases’ in the data set are actually ‘cases’? Completeness of key fields in the data set (e.g. race, home address)

14. Surveys Other organizations in your state may be doing surveys with health content University faculty Polling companies Voluntary organizations (heart, lung, cancer, March of Dimes….) Phone surveys are getting harder to do because of caller ID, call blocking, cell phone-only people, etc Reconsider the traditional options: Door to door Mail Internet-based surveys Sampling frame and representativeness Keeping replies anonymous while doing follow-up E-mail reply or web-based

15. Working with partners Consider the different motivations and reward systems of various partners. Academics need grants and publications Some partners have an ax to grind Make the ground rules clear before you start: Who will author report, and who will be first? Who has to approve document before it is released, and who just gets to comment? Who is responsible for which part of the work?

16. Interesting questions If you are working in a small state, urgent public health issues will not come up all that often You won’t make your reputation by working on one of these The trick is to see what is interesting about an apparently routine situation Ask people who are experts about this routine problem what the important unanswered questions are The additional effort is often quite small

17. Choice of analytic techniques You have learned a lot of sophisticated techniques in school Sophisticated is not always better, if you consider the purpose of the analysis To publish a paper? To provide guidance to local action? To persuade administrators and policy-makers? Sometimes the point of doing a careful multivariate analysis is to figure out which univariate or stratified analyses to include in your report.

18. Program evaluation As you look around for projects, you are likely to be asked to help with program evaluations Epidemiologists have real skills and insights to contribute to program evaluations Well-done program evaluation is bigger than epidemiology Epidemiologists can help most with impact or outcome assessment.

19. Program evaluation (2) Formative evaluation: Could a program achieve its goals if carried out as designed? Is staffing and structure appropriate to achieve the goals? Logic model Clear statement of intermediate steps between program activities and desired outcomes With a model, you can identify intermediate effects to measure Some of these effects or end-points are of a kind that epidemiologists can help with You will often be the best person around to help with evaluation data analysis and study design

20. Buy-in to evaluation activities This is the most important reason for failure of evaluations. Phrased as “engage the stakeholders in the design of the evaluation’ What this really means is: If people who are invested in the program don’t get a real chance to influence the shape of the evaluation, they will at best ignore it and at worst undermine and attack it.

21. Surveillance principles (1) 1. Have clear objectives for your surveillance system. Design it to meet those objectives. 2. Collect only the data needed to meet those objectives. More is wasteful, and it rapidly erodes cooperation. 3. Show those providing reports or data how the health department is using these to improve community health status. 4. Value and build on personal relationships as well as laws and rules. 5. Identify and remove barriers to rapid reporting of those events that are put under surveillance.

22. Surveillance principles (2) 6. Provide authoritative consultation to clinicians and laboratorians on clinical and public health issues. Reporting will follow. 7. Have redundant systems for surveillance to minimize damage from gaps or interruptions 8. Routinely and frequently analyze and interpret the surveillance data by person, place, and time. 9. Assure that information from all sources received by all parts of a health department is reviewed and interpreted together 10. Convey your confidence about the value of surveillance, epidemiology, disease control, and public health to those who have data or cases to be reported.

23. A recent analysis in FL

24. Graphing for persuasion

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