Analysis of statistical data in heath information management

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  • Causes of maternal mortality from 2004 -2007 in ganjuwa
  • Analysis of statistical data in heath information management

    1. 1. Analysis of statistical data inHeath information managementHIMI, JOSBySaleh AhmedSchool of Midwifery, Bauchi.
    2. 2. Analysis of statistical data inHeath information managementIntroduction For proper and effective health planning and decisionmaking in any health institution adequate and reliabledata must be collected and fully analyzed. Well analyzed data will make the decision makers todetect and control emerging and endemic healthproblem, monitor progress towards health goals andpromote equity.
    3. 3. Objectives At the end of this presentation the participants shouldbe able to:-- Define statistics.- Describe types of health statistics in healthinformation management.- Describe various ways of analyzing statistical data inhealth information managemen
    4. 4. - Meeting the eight (8) millennium Development goaltargets can only be achieved by analysis of healthstatistical data such as vital statistics, morbiditystatistics, and health service statistics. Thus analysis ofdata is an indispensable tools in health informationmanagement system globally.
    5. 5. StatisticsDefinition The word statistics is derived from latin – statusmeaning state or condition According to English advanced Dictionary, statistics is the branch of mathematics that deals withanalysis and interpretation of numerical data in termsof sample and population Statistics is a science that is concerned with thecollection, compilation, presentation , analysis andinterpretation of numerical data (Nwabuokei,2001)
    6. 6. - Based on the above definition statistics deals with dataand population(both living e.g. human being and nonliving e.g. measurement of aggregate results)
    7. 7. Branches of statisticsi) Descriptive statisticsii) Inferential statisticsDescriptive statistics –it is type of statistics thatstudies a body of statistical data and no generalizationis made from the results obtained. It involvescollection of data, classification of data, drawing ofhistogram, polygon, charts, percentages, range andother types of statistical graphs, computation ofsample characteristics such as the mean, mode,median , standard deviation etc.
    8. 8. - Descriptive statistics provide precise, standard ways tosummarize, understand and communicate complexinformation. It summarizes the population of data by describingwhat was observed numerically or graphically Numerical –eg, mean, standard deviation. NB, frequency and percentages are useful indescribing categorical data e.g race , sex, age.
    9. 9. - Inferential statistics – it is the branch of statisticsthat studies a group of data in order to use the resultsobtained in making generalization on a larger groupof data. It uses sample results to reach conclusionsabout populations from which the samples have beendrawn from. For instance testing of hypothesis bytaking the form of answering yes or no questions.
    10. 10. - It also performs the followings:- Estimating numerical characteristics ofdata=Estimation Describing association within data =Correlation Modeling(a representative set of data) relationshipswithin the data =Regression, extrapolation,interpolation or other modeling.
    11. 11. Statistical data Data is an information - facts - knowledge Statistical data can be classified based on the nature orthe source. A) based on the source of the datai) primary data- data collected by the investigatorhimself for the purpose of statistical analysisii) secondary data- data collected from existingdata(records )
    12. 12. - Based on the nature of the data i) Qualitative data – data used for describingcharacteristics which can not be defined in numericalterms e.g, colour of hair, colour of theeyes, performance grade- good, average, poor ii) Quantitative data- data that are capable ofnumerical description e.g. weight , height inmeter, scores of students. It consists of measures thattake numerical values for description such as meansand standard deviation. if countable =discrete dataand if measurable express in scale =continuous data eght
    13. 13. Health Statistical Data TypesA) Vital statisticsB) Morbidity statisticsC) Health service statisticsA) Vital statistics – it is the branch of statistics thatdeals with the changes and most basic events ofhuman population e.g, birth, marriage, mortality andillness. Such data are gathered from census andregistration reports.
    14. 14. - Vital statistics is collected for the purpose ofgenerating birth and mortality rates for the wholepopulation or subgroup. Method of collection is through ongoing recording orregistration of vital event such as birth, adoption,death, marriages, divorces,legal separation etc
    15. 15. - B) Morbidity statistics:-These are data on occurrences ofseverity of sickness in a community. It is collected for the purpose of analysis of ill-health withinhuman population and for provision of detailed analysis ofhealth status and services. Method of collection is through medical services such asmedical institutions from:- a) outpatient clinic, b) special clinics(maternal) c)inpatient services (general hospital, specialist hospital)
    16. 16. - C) Health services statistics – these are data that areobtained from operation of the health services. Two typesof data obtained are i) Resource data ii) institutional records i) Resource data – are data on human and materialresources. Human resource are details of number of varioustypes of health personnel (Doctors, Nurses, Midwives,community health workers etc). Consideration is made ontheir distribution in relation to the population.
    17. 17. - ii) Institutional records – these are recordsgenerated from health facilities. For example recordsof client/patient that attended a health centre incertain period of time.(how many pregnant womenreceived ANC). This serves as a means of providinginformation about the demand for and utilization ofhealth services and about the extent to which targetgroups within the population are being served.
    18. 18. Sources of health statistical data1) Census of the population.2) Registration of births and deaths3) Notification of Diseases(surveillance, epidemiological surveys)4) Medical institutions (hospital, healthcenters, clinical laboratories)
    19. 19. Analysis of statistical dataHealth statistics analysis is based on two measurestools:- rates and ratio. Rate is the frequency (number) of events that occur ina defined period, divided by the average population.
    20. 20. - Denominator data – population at risks Numerator data – events or condition of concern. Constant multiplier is either 100 to make a % or else1,000, 10,000, or 100,000 to make the numerator largerthan 1 for easy discussion Thus rate can be expressed as follows:-.
    21. 21. - -Thus, Health statistical are expressed inrates, i.e number of events that are related topopulation.Rates are expressed in arbitrary totale.g, 1,000, 10,000, 100,000, 1,000,000.Rates is the most important tool formeasuring disease or death. It is used tomeasure events that are related to thepopulation or subgroup in which they occur.
    22. 22. Types of rates Rates are grouped into two that is based on the nature ofpopulation used as follows:- Crude rates Specific rates Crude rates –these are rates that are applied to entirepopulation without reference to any characteristics of theindividuals in it. The rates are calculated with the totalpopulation in an area as the denominator.
    23. 23. - Crude rates is used when for instance i) the frequency of death or disease(numerator) is notknown for the subgroups of population ii) the size of the subgroups(denominator) is notknown iii) the number of person at risk is too small to providea stable estimate.
    24. 24. - Specific rates :- the rates are calculated afterpopulation has been categorized into groups withparticular characteristics e.g age-specific rates or sex-specific rates.
    25. 25. Calculation of vital statistics This calculation is for the purpose of determiningmortality rate. Crude rates-
    26. 26. - Specific rates:-
    27. 27. Calculation of morbidity statistics Morbidity rates are divided into two major types asfollows;1) Incidence rate:- it indicates the rate at which newdisease occurs in a defined, previously disease-freepopulation.NB. period of time can be 1 year period or more
    28. 28. - Prevalence rates:-it measures number of people in apopulation that have a disease at a given time. Prevalence depends on the number of people that havebeen ill in the past and the duration of their illness.
    29. 29. presentation of data. Health information management can only be achievedwhen data collected are explicitly stored in meaningfulforms which can be understood by stakeholder andpolicy makers Data are presented in the following methods The text method The semi-text method The tabular method-Diagrammatic and graphic method(use ofgraphs, charts and diagrams)
    30. 30. The text method This is the simplest method of presentation of data inform of written report E.g the number of health personnel in AbubakarTafawa Balewa teaching Hospital as at 2009,is 1,000.out of which 600 were male and 400 were females. Its shortcomings- it can’t give effective and clearinterpretation of statistical data and there ispossibilities of omission and repetition,
    31. 31. The semi-text method At times called the partial-tabular method. Itcombines the text and tabular forms of datapresentation. It facilitates easy comparison because figures arepresented separately from the text. Eg. number of patients admitted in Specialist Hospitalfor the period of 2005 – 2007 2,000 in 2005, 2,500 in 2006, 3,000 in 2007
    32. 32. Tabular method This involves the systematic arrangement of facts andfigures in series of boxes made up of rows andcolumns. According to Nwabuokei (2001) the Components ofstatistical tables are; The title The caption or box head(column labeling) The stub (row labeling) The source and or footnotes(abbreviation or symbolnot universally known)
    33. 33. Types of tables Simple table- it consists of merely a list of items. itprovides statistical data in one or two column Table 1: Enrollment into SON,Monze in 2009 Source –SON MonzeLGA No of Candidates enrolledMuzabuka 14Choma 28Chukuni 35
    34. 34. - Complex table:-it shows division of total into twoor more. It is useful in making comparisons Table II Sex distribution of students enrolled Source :-SON MonzeLGA No Male female withdrawMuzabuka14 5 9 3Choma 28 10 18 4ChukuniTotal357715302047613
    35. 35. Frequency distribution tables This is the most commonly used in presentation ofhealth statistic in public health. The process ofdrawing of the table is a follows First , the data –ie the raw data are arranged based ontheir magnitude-ascending or descending order. Thisis known as the array of data Eg , 3,2,8,6,8,3,10,8,10,2,3,5,8,5,8 }raw data 2,2,3,3,3,5,5,5,6,8,8,8,8,8,8,10,10 }array of data.
    36. 36. - Table III: Anatomy test scores over 10score tally frequency2356810IIIIIIIIIIIIIII233152total 16
    37. 37. Graphic representation This is the display of data in the forms of graphs, geometricfeatures or pictures. The purpose is to provide a simple, visual aid that thereader will readily appreciate the important features of thedata The common examples are- A) Bar chart- it contains bars of which the length isproportional to the frequency of events and eachrepresenting each items in the group. It is of 3 typessimple,compound &component. It is useful inrepresenting discrete variable(data).Below are theexamples bar charts.
    38. 38. Causes of maternal deaths inGashakaCauses No ofdeathspercentageEclampsia 15 21.4%infection 25 35.7%Post partumhemorrhage30 42.9%Total 70 100%
    39. 39. Causes of maternal deaths inSabon Kaura village0.00%5.00%10.00%15.00%20.00%25.00%30.00%35.00%40.00%45.00%50.00%Eclampsia Infection PostpartumhaemorrhageSeries1
    40. 40. Causes of maternal deaths from2004 – 2007 in Ganjuwa LGA0% 20% 40% 60%2004200520062007eclampsiainfectionpost partum haemorrge
    41. 41. Histogram It is a special type of Bar chart used for displayingnumerical variables Variables of interest are shown on one axis as acontinuous scale split into class. The bars are joined to each other and their areasrepresenting frequency of events. For instance the age and sex distribution of populationmay be displayed in the form histogram to producepopulation pyramid
    42. 42. Pie chart It consists of a circle divided into sector which area ofeach sector is proportional to the value of eachvariable. It is used for presenting data of proportion orpercentage of whole. In order to present information using pie chart, thefollowing should be done, 1) calculate the size of each sector based on themagnitude in degree from 360 circle. 2) Draw the circle
    43. 43. Major causes of sudden deaths.15%25%8%52%hypertensionheart attackdiabetes
    44. 44. - There are other various methods of data analysis thatare not dealt with.
    45. 45. Conclusion. The objective of health information management is togenerate information that decision makers andmanagers can use to support health programs. Thiscan be achieved by proper record system and wellestablished institution for registration of vital eventssuch as births, deaths etc. it therefore theresponsibility of all healthworkers, epidemiologists, and statisticians to ensurethat data are collected, analyzed interpreted andcommunicated for optimum health services deliveryto all citizens of Nigeria
    46. 46. - Thank you.

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