PREVNEXTSUBMITMenuResourcesGlossaryTranscriptClear and return to MenuSearch ResultsFilterSlide TextTranscriptSearch in:Check to includeSearch...TermsDefinitionFINISHfinishdefinitionresourcessearchpauseplayreplaysubmitnextpreviousvolumeSkip Navigation. Hit enter to return to the slide.SUBMIT ALLsubmit allQuestion ListMore infoSend an emailCloseBioExit<html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Welcome to Part 3 of Module 1. This part will cover some common terms used with data and information. </textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>We have talked about data and information in relationship to the public health functions. Before we proceed further, let’s get clear on terminology. Such terms as data, measurement, information, and evidence are frequently used interchangeably in everyday conversation. The terms may have slightly different meanings, depending on whether used, for example, in the sectors of health, business, or law. These terms will be used throughout the course, so take a moment to really understand their definitions. Don’t get confused by the many different definitions and meanings of these words. </textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Earlier we spoke about data as individual facts, statistics, measurements, or a combination thereof. Data can a mean single element, or it can mean many pieces of data. Data is often a number, but it can also be a word, a picture, a video, or even a sound. A weight measurement or a telephone number are examples of data about a person. A description like “adult” or “adolescent”, or a blood test result like “positive” or “negative” are also examples of data about a person. </textformat><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>When humans bring meaning and context to data, then it becomes information. Think of data as raw. It hasn’t been shaped, or processed, or interpreted. It doesn’t make sense on its own.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Let’s talk about some examples of data. Blood pressure represents one type of patient data. At the vitals station in a clinic, it’s not uncommon to find a discarded slip of paper with the words “BP 110/70”. If the slip of paper doesn’t have the patient’s name, then the numbers on that slip of paper have very limited usefulness. </textformat><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>For this piece of data to be useful, additional context and related facts, such as the patient’s name, are necessary.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Another example is a CD4 cell count of a person living with HIV. A patient’s CD4 count is periodically measured to assess health status. The CD4 count is an indicator of the health of a person’s immune system. The CD4 count is a blood test that is done at baseline and yearly after a person starts ART. The number of CD4 cells counted is another type of patient data. Again, for the data to be useful, it must be associated with a person and a date.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>For the purposes of this course, we are interested in that data that is objectively measured. We are less concerned about opinion, conjecture, feelings or assumptions. We are more interested on the data that depends upon verifiable and repeatable measurement. To get data on blood pressure, it’s necessary to measure blood pressure in a standard manner using a blood pressure cuff. A nurse can’t determine a person’s blood pressure simply by looking at the patient’s physical appearance. Data relies on objective measurement.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Information is data that has been processed or interpreted so that it has meaning. Bringing together different pieces of data can help in turning data into information. Once data becomes information, it becomes useful for informing decisions. Later in this course we’ll cover skills for analysing data. When we analyse data to find patterns and meaning, we turn it from raw data into information. </textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>For example, when multiple CD4 count observations are recorded in a patient chart, these data can form information. The trends in the CD4 count for this patient are analysed and the doctor or nurse uses this information to make conclusions about the effect of ART. The CD4 count pattern across many different patients may be analysed against changes in their health. </textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Here’s another example. 8 614 pregnant patients participated in HIV testing as part of the PMTCT programme on their first ANC visit. Of this number, 2 114 of those tested were found to be HIV positive. If we consider these two facts in relation to each other, expressing the second fact as a percentage of the first fact is a process of analysis that gives us a useful piece of information about the level of HIV positivity among pregnant women. A facility manager like Sister Sinah, who we met earlier, can then bring interpretation and meaning to this information, seeking to understand if the level is high or low, improving or getting worse. This can then inform Sister Sinah’s decisions on how to manage PMTCT services.</textformat><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'></textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>A third example is the primary health care (PHC) headcount. Looking at this data alongside other data, such as staffing counts, and comparing both sets of data to an expected standard or target makes these pieces of data information. Both types of data are part of the model for Workforce Indicators of Staffing Need (or WISN), and the information from WISN can be used for assessment and decision-making about where to allocate staffing.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Sometimes having a single piece of data on its own can provide information leading to a decision. Let’s think about a clinical example. Imagine a patient who has a blood glucose of 28 mmol/l. When considered against a clinical standard, this observed measurement of glucose level--this single piece of data -- is high. Clearly this piece of data, together with clinical guidelines for management of hyperglycaemia or diabetes, should lead to rapid decision-making about how to manage the patient’s health condition.</textformat><textformat leading='7' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'></textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>A piece of data or fact, however accurate and credible, isn’t information if it can’t inform a decision. For example, let’s go back to the fact that 8 614 pregnant women completed HIV testing during their first visit for antenatal care during 2015 in Mzansi Clinic. This single piece of data may not be very useful alone! What if there are an additional 100 pregnant women with unknown HIV status who did not participate in HIV testing during their first ANC visit? Is this number high or low, favourable or unfavourable? Now we have a comparison to analyse and assess how well we’re reaching the goal of universal testing for HIV in antenatal settings, and we can make decisions on this basis. This is information!</textformat><textformat leading='0' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'></textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>To summarize, how do we tell the difference between data and information? Data is a raw piece of information that can’t stand on its own. Information is the meaning and interpretation we bring to the data, by considering one piece of data in context or in relationship to other pieces of data.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>When information is accumulated in support of a particular claim, decision, procedure, action, or set of actions, we call this evidence. Scientific evidence refers to anything used to support a hypothesis or theory. In health, we may look for evidence that a particular segment of the population suffers a heavier burden of illness than another segment of the population, or evidence that a new course of treatment results in better health outcomes than an older course of treatment. We may use indicator data as part of evidence. </textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>Information and evidence, when brought together and confirmed with time and experience, can form knowledge. The Greek philosopher Plato defined knowledge as being justified, true, and believed. Knowledge arises through accumulation of evidence and experience. As health practitioners, we build our own, adding to the collective body of knowledge, thanks to the data we observe, the information we draw from the data, and the learning experiences that we gain over time. Click on the box to read an every-day example.</textformat></html><html><textformat leading='2' tabstops='[0, 48, 96, 144]' blockindent='0' indent='0'>We just learned various terms, including data, information, evidence, and knowledge. In the next part, we’ll look at the data cycle and the patient pathway.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>A total amount; thought of as a whole, all together.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>To gather together information from different sources in order to study it carefully.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Individual facts, statistics, measurements, or a collective of the same. Data can refer to any characteristic, event or other descriptor. It is usually used to calculate, analyse or plan something.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>The pathway in the life of data, which involves the following steps:</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>1. Collection and storage</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>2. Processing </textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>3. Reporting</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>4. Analysis, interpretation, and use</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>The goal of descriptive analysis is to describe what is happening in a sample or target population. An example of descriptive analysis could be the average number of patients seen at a clinic per month, how this number may vary over the course of the year, and the patterns by sex and age group. It does not attempt to explain why the number may increase or decrease, or why a particular pattern by age and sex exists.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Epidemiology means "the study of what is upon the people". It is the study of what health problems exist in the population, how health problems change over time, what factors affect health, and how diseases and illnesses can be controlled. </textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>To judge the value/condition of someone/something in a careful and thoughtful way.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Involves a systematic, objective analysis of a project’s outcome and impact in relation to its objectives:</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Are the activities enabling the program to meet its objectives?</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Have the expected outcomes been achieved?</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Is the project having the desired impact?</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Is it successful?</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Is it needed?</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Should it continue?</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>The goal of explanatory analysis is to explore relationships and/or identify causes. Explanatory analysis may involve testing a hypothesis or experiment. For example, when testing a new outreach strategy to increase HIV testing uptake among adolescents, an explanatory analysis would compare the trend in HIV testing in this target group before and after implementation of the new outreach strategy to find out if the strategy worked, and why or why not.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>A measure used to quantify, characterize, or assess a given situation. Indicators are often standardized and expressed as an event (numerator) over a population (denominator) for a given period of time. Tracking indicators helps us to observe relative changes over time.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Knowledge about someone or something; facts or details about a subject. Data becomes information when it can be used to make decisions.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>When information and evidence are brought together and confirmed with time and experience.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>To watch, observe, listen to, or check something for a special purpose over a period of time.</textformat></html><html><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Process of routinely gathering information on key aspects of a program and utilizing this information in management and decision-making.</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>Monitoring involves:</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Recording what a program has done – activities and outputs</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Comparing actual outputs with planned outputs</textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'></textformat><textformat leading='0' tabstops='[0, 48, 96]' blockindent='0' indent='0'>• Making adjustments if the difference between the plan and what is actually achieved is too great</textformat></html>