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Morbidity-data sources and measures Farid Najafi MD PhD Kermanshah Health Research Center (KHRC) Kermanshah University of Medical Sciences.

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Presentation on theme: "Morbidity-data sources and measures Farid Najafi MD PhD Kermanshah Health Research Center (KHRC) Kermanshah University of Medical Sciences."— Presentation transcript:

1 Morbidity-data sources and measures Farid Najafi MD PhD Kermanshah Health Research Center (KHRC) Kermanshah University of Medical Sciences

2 Question

3 References

4 What are we measuring? Criteria for diagnosis is the first step (case fefinition) Different case definition leads to different values

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6 Prevalence Prevalence rate is a wrong expression It is a simple proportion or percentage Period prevalence: it requires a smaller survey sample to find enough cases For an accurate estimate. “Did your child have diarrhea during any of the last 7 days?

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9 Incidence Incidence measures how quickly people are developing a disease Population at risk: –Cervical cancer Women vs. men Women after hysterectomy

10 Relationship between incidence and prevalence Direct relationship between incidence and prevalence P=I*D –Hepatitis A vs. Hep C To measure the prevalence we need to conduct a cross-sectional study To measure the incidence we need to conduct a follow-up study

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13 Incidence rate versus cumulative incidence IR is equivalent to the average speed of a car at a particular point in time, e.g. 60 km/hour CI is analogous to the distance travelled by a car during a specified interval of time, e.g. 60 Km in one hour

14 Measuring disease occurrence using routine data Most of our information come from routine data Data are not individual base No causal association between disease and other factors We are usually interested in incidence Difference between crude, age-specific and stadardised incidence and prevalence

15 Raw health data Data can be assessed at two levels 1.Summary data 2.Raw counts of health events More challenge about morbidity data compared to mortality data –Capturing in a less systematic way –Scope of information is enormous –No complete informatin at a local level

16 Disease registeries It covers only small minority of conditions –CHD: first studied in MONICA Project in the early 1980s –Cancer: Most countries, most notably in Scandinavia, have cancer registries that cover the whole country Cancer is an ideal candidate for registration because of its clear-cut diagnosis, based on a single simple record (pathology) –Many infectious diseases

17 Health Surveys There are two major challenges –Representativeness: sample has been chosen to be representative of whole population No inclusion of homeless people Those who disagree to participate (response rate) –Validity; the extent to which a survey actually measures what it set out to measure

18 Validity

19 Health facility data Hospital records: usually based on discharge diagnosis as recorded and coded on the patient’s record with varying degreees on misdiagnosis, mis-recording and mis-coding –Not representing the general population For fatal and serious conditions, hospital records provide useful information Lack of unique patients identifier No information about condition treated by family practioners or n home

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21 Getting access to the data International sources –World Health Organization (http://www.who.int)http://www.who.int –World Bank (http://www.worldbank.org)http://www.worldbank.org –National data sources Ministry of Health

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