CAPITULO I: MARCO TEÓRICO DE REFERENCIA SOBRE LAS GENERALIDADES
E. DESARROLLO LABORAL Y PROFESIONAL
6. DESARROLLO PROFESIONAL
Sphere standard
The design and development of health services are guided by the ongoing, coordinated collection, analysis and utilization of relevant public health data.
Purpose/Rationale
Health information is critical to a health system’s functioning.31, 32 A health system
approach to addressing emergencies, therefore, requires significant attention to Health Information Systems (HIS). HIS in emergencies determines priorities and allocates resources accordingly.31 In the emergency phase however, there may not be any HIS. The
priority would be to establish HIS quickly. This section of the chapter on Health Services describes the key tasks in establishing and supporting HIS during an emergency and post- emergency. Before turning to these tasks, it may be helpful to review a definition of HIS in emergencies.
HIS in emergencies is a set of data collection platforms implemented by a coordinated group of humanitarian actors generating information to support strategic decisions, monitor changes, prioritise action and allocate resources, manage programmes, scaling up or down operations, advocate and formulate concerns in relation to an emergency context.’31 (pg. 585)
Essential tasks: emergency phase
Figure 2-30: Tasks to establish and support a health information system
Task 1: Work with the designated HIS coordinating agency to
coordinate and standardise data collection and interpretation
Coordinate with the agency responsible for HIS in the emergency.
The health information system used by all health agencies in an emergency must be standardised. A lead agency, often the ministry of health, will establish the standards for HIS. Assignment of a lead agency is the first step in developing HIS during an emergency.4 typically, one of WHO’s roles in emergencies is providing technical
assistance to the lead agency in the design and function of HIS
Work with the designated HIS coordinating agency to coordinate and standardise data collection and interpretation;
Calculate the crude and under-five mortality rates;
Calculate other key rates of mortality, morbidity and health services utilization; Disaggregate data by age and gender as soon as possible;
Submit recommended standard surveillance data to the designated HIS coordinating agency as scheduled;
Help HIS to detect of infectious disease outbreaks.
Monitor health programmes for vaccination, feeding and reproductive health; Protect data to ensure individuals and populations’ rights and safety; and Triangulate HIS information with other data sources whenever possible.
Health systems and
infrastructure
Use standard case definitions, data collection and reporting forms. These standards should come from the agency given responsibility for coordinating HIS during the emergency.
Figure 2-31: Key steps for lead agency responsible for development of an HIS in an emergency
Assign primary responsibility for HIS coordination to a person or agency; Establish a chain of information transmission and means of communication; Define disease control programme objectives and quantify targets;
Identify essential data categories demography, mortality, morbidity, nutrition and
programme indicators;
Develop and field test case definitions; Design and test simple data collection forms; Train personnel involved in data collection;
Define data compilation, entry and analysis methods; Develop feedback mechanisms e.g. a newsletter; and Evaluate and adapt system periodically.
Task 2: Monitor crude and under-five mortality rates
Crude mortality rates and under-five mortality rates are the key impact indicators for the emergency response effort.27, 32, 5, 10 These rates are thresholds to define a situation as an emergency or not. These rates are also used to monitor and evaluate the relief effort. Different organisations use different thresholds, however. Table 2-8 developed by Checchi and Roberts (2005), shows three different sets of thresholds for defining emergencies using these two rates.
Table 2-8: Mortality thresholds used to define emergency situations5
Agencies Assumed baseline Emergency thresholds Centers for Disease
Control, Médecins Sans Frontièrs, Epicentre, Academia CMR: 0.5 per 10,000 per day
U5MR: 1 per 10,000 per day
CMR ≥1 per 10,000 per day U5MR ≥ 2 per 10,000 per day
UNHCR CMR: 0.5 per 10,000 per day
U5MR: 1 per 10,000 per day
CMR > 1 per 10,000 per day: ‘very serious’
CMR > 2 per 10,000 per day: ‘out of control’
CMR > 5 per 10,000 per day: ‘major catastrophe’
(double for U5MR thresholds) Sphere project Context-specific CMR
(U5MR):
Sub-Saharan Africa: 0.44 (1.14)
Latin America: 0.16 (0.19) South Asia: 0.25 (0.59) Eastern Europe, Former Soviet Union: 0.30 (0.20) Unknown baseline: 0.5 (1.0) Emergency if CMR (U5MR): Sub-Saharan Africa: 0.9 (2.3) Latin America: 0.3 (0.4) South Asia: 0.5 (1.2)
Eastern Europe, Former Soviet Union: 0.6 (0.4)
Health systems and
infrastructure
Figure 2-32: SMART initiative
The U.S. Agency for International Development (USAID) in collaboration with the U.S. Department of State’s Bureau of Population, Refugees and Migration (State/PRM) and the Canadian International Development Agency (CIDA), initiated the Standardised Monitoring of Relief and Transitions (SMART) SMART is an inter- agency initiative that includes most types of humanitarian organisations, donors, international and UN agencies, PVOs and NGOs, universities, research institutes and local partners. There has been a consensus among SMART participants on the use of Crude Mortality Rate (CMR) and Nutritional Status of Under-Five Children as benchmark indicators for humanitarian assistance.
Much of the recent effort in the SMART initiative has focused on developing tools and systems to help standardise methodologies for reliable and valid assessment of mortality and nutritional status plus food security to help ensure the data is used for decision making and reporting. User-friendly manuals and software for application of these tools can be found at the SMART website at http://www.smartindicators.org/index.html
Determine the size of the beneficiary population and the number of children under five. This is a difficult task in emergency situations. Estimates of population size are often over-estimated and sometimes under-estimated.14, 30 A detailed description of commonly
used methods are beyond the scope of this guide. One of the best references for carrying out this task that at time is available for download from the Internet is Telford’s Good Practice Review (1997).30 Other manuals are forthcoming.
Table 2-9: Common sources of information about the size of the beneficiary population
Formal
registration30, 15
E.g., Registration for ration cards, births or for new arrivals
Mapping15 Estimate the area of the camp in square meters, calculate the population density (one person per x m2) at several points within the camp and use these numbers to estimate population size
Estimate under-five population size30
Estimate the number of children under-five by counting all children with a height below a threshold (e.g., < 110 cm) Count of services15 Count the number of services provided to a target population
(e.g., the number of vaccinations given to children under five) and estimate the total population using the target population count as a percentage.
Retrospective mortality surveys31,
5, 15
This can provide the numerator and denominator for both mortality rates. Survey the head of a random sample of households (e.g., thirty cluster survey) about household composition, migration and mortality experiences. This is relatively complex due to sample size calculations and selection of recall periods.
Overflights, aerial photography30
Count the number of households directly or from
photos/images. Combine this information with other estimates about average household size/composition to estimate the total and under-five population.
Health systems and
infrastructure
Figure 2-33: Potential reasons for over- or under-estimation of number of beneficiaries14
The number of beneficiaries are often over-estimated because:
persons in hiding who are not legitimate refugees are not counted, individuals register more than once to increase food rations, out-migrations and deaths are under-reported,
members of the local or host population may attempt to register to access services
provided to refugees.
However, it is important not to compensate by under-estimating. Remember to count individuals:
who settle outside camps in the local population but may be hard to find and count, who are sick or malnourished do not access services that are being used to count
beneficiaries.
Calculate the crude and under-five mortality rates.
A system for recording all deaths is required and another to estimate the total number of the population at risk of dying. Both numbers are needed for the calculation. Retrospective surveys provide the source for the number of deaths and the population at risk of dying. Experienced persons are also needed to calculate the precision of the rates derived from surveys. Please refer to the Epidemiology and Surveillance chapter for details on how to calculate these rates.
Table 2-10: Emergency thresholds used by Sphere2
Task 3: Calculate other rates on mortality, morbidity and health
services utilisation
It is important to calculate proportional and cause-specific morbidity and mortality rates. Data for these indicators is often drawn from information collected at service delivery points such as health facilities, cholera treatment and feeding centres as opposed to
Health systems and
infrastructure
population-based data. This data is sufficient for disease control because the study of trends in rates is still possible.
Task 4: Disaggregate data by age and gender as soon as possible
From the outset, calculate separate mortality and morbidity rates for children under five.
Even though it is difficult to do divide data by age and gender early on in an emergency, the Sphere standard is to do so while data is being collected because the under-five group is considered at high risk for mortality. Standard mortality and morbidity surveillance forms will typically request that data be disaggregated by under-five, five and older. Refer to the sample morbidity and mortality surveillance forms in the Sphere guidelines. 27 As soon as possible, calculate separate mortality and morbidity rates by gender.
This detects any differences in death and disease by gender and determines if changes in intervention strategies are needed to target those at highest risk. Most standard mortality and morbidity surveillance forms will request data be disaggregated by gender (the Sphere sample forms do).
As the situation permits, further disaggregate mortality and morbidity rates by additional age groups.
Additional disaggregation of mortality and morbidity statistics help identify groups at highest risk and in need of more targeted interventions such as very young children or the elderly. Additional reporting of the following age groups is recommended by Sphere:
< 1 year; 1-4 years; 5-14 years; 15-49 years; 50-59 years; and > 60 years.
Task 5: Confirm data quality before use
Interpret and use the data.
Generally, interpretation and analysis of data or information is weak; in emergencies, it is very weak. Well trained and good scientific people look often look for additional data which may delay important decisions; the situation in the early stages is fluid and changing by the hour. Certain decisions must be made based on vague data and on experience taken from how similar situations have developed in the past. There are also those agencies and organisations that rush to the most convenient place and start operating without considering the available information and need patterns. The balance must be found by coordination and the overall coordination body must be respected. In principle, the first week is marred with inaccuracies and data which can only form patterns. Successively, the quality improves, however. But before using any data, its quality must be judged and potential biases assessed. Problems with data quality and potential biases vary on whether surveillance or surveys are the source of mortality data. It is beyond the scope of this guide to provide a detailed overview of common biases. There are specific guides for just this purpose such as the one by Checchi and Roberts (2005) and are available for download from the Internet.5
Refer to the Epidemiology and Surveillance section of this guide for an in-depth discussion about calculating population size, mortality and other rates in a public health emergency.
Health systems and
infrastructure
Task 6: Submit recommended/standard surveillance data to the
designated HIS coordinating agency per schedule
Use standard reporting forms to submit surveillance data.
Submit data to the lead Health Information Systems (HIS) agency using the standard formats and procedures. The Sphere guidelines provide examples of weekly mortality and morbidity reports that are likely to be very similar to those requested in any emergency.27
Submit standard reports on time.
In most situations, the lead HIS agency will develop a routine mortality and morbidity newsletter (daily, weekly, monthly) with the data included in standard reports. The newsletter will be widely distributed. It is important, therefore, to submit standard reports on time so the epidemiological reports are as informative as possible.
Figure 2-34: The Weekly Morbidity and Mortality Report (WMMR)
Shortly following the Pakistan earthquake of 8 October 2005, the Pakistan ministry of health (MoH) and WHO began publishing The Weekly Morbidity and Mortality Report (WMMR). WMMR is developed from ‘surveillance data that health service providers and NGOs transmit on a weekly basis from health facilities and hospitals in those areas affected by the earthquake. WMMR objectives are to monitor the trend of health conditions over a period of time and provide vital information to all health partners. WMMR is only a snapshot of the health conditions in those facilities where events are registered and data collected and does not necessarily reflect the situation from other health facilities. WMMR is a publication that has been developed for emergencies and previously used in other areas such as the Darfur Crisis.’
Source: http://www.reliefweb.int/rw/RWB.NSF/db900SID/KHII-6Q993G?OpenDocument
Task 7: Help the HIS to detect outbreaks of infectious disease in a
timely manner
Ensure that the local health information collects information required for outbreak detection.
Obtain case definitions and thresholds used by the lead Health Information Systems (HIS) coordinating agency and ensure they are included in the training of facility and community health workers.
Note: Single cases of cholera, measles, yellow fever, dysentery or viral haemorrhagic
fevers can indicate an outbreak. 27 Indications of an outbreak of meningococcal meningitis depend on the population size, time since last outbreak and vaccination status.* An outbreak of malaria is more difficult to define but is suspected when the number of cases is more than expected for a defined population at that time of year. There are other diseases like tetanus, which often occurs after floods, hurricanes and earthquakes. Surprisingly, these patterns are often ignored and despite the International Federation’s warnings in Pakistan and Yojakarta earthquake operations, the governments were still taken by surprise.
* If the population is less than 30,000, five new cases in one week or a doubling of cases over a three-week period indicate an outbreak of meningococcal meningitis. If the population is greater than 30,000 and has a high outbreak risk with no outbreak in more than three years and vaccination coverage is less than 80%, ten cases per 100,000 per week is an indication of an outbreak. Fifteen cases per 100,000 per week indicate an outbreak in a population greater than 30,000 and without a high outbreak risk.
Health systems and
infrastructure
Report suspected outbreaks within twenty-four hour.
Report suspected outbreaks to the designated health authority (often the next level of the health system). The Sphere standard is to report suspected outbreaks within twenty-four hours of detection. This standard implies that health workers have the ability to communicate with health authorities within this time standard if indicated.
Note: Please refer to the section on Communicable Disease Control as well as the
Epidemiology and Surveillance section of this guide for an in-depth discussion about how to investigate and manage disease outbreaks in humanitarian emergencies.
Task 8: Monitor health programmes: vaccination, feeding,
reproductive health
As well as mortality and morbidity data, the health information system should monitor key health programmes. At a minimum, the health information system should monitor vaccination and treatment of malnutrition.32 The health system should also monitor
reproductive health services as soon as feasible.
Monitor vaccination coverage rates.
Measles vaccination rates among children aged six months to fifteen years are calculated when monitoring mass measles immunisation campaigns. These rates may be calculated using administrative estimates (the number of doses divided by the estimated number of children between the ages of six months to fifteen years) or by household surveys. Once a routine immunization system is established, coverage rates for the antigens provided should be calculated (typically coverage among children from twelve to twenty-three months of age).
Monitor the number of patients in intensive or supplementary feeding programmes .
Comparing the number of children enrolled in feeding programmes with the estimated number of mal-nourished children (collected from nutrition surveys) can provide an estimate of feeding programme coverage.
Monitor antenatal care attendance.
The number of women attending antenatal care can help estimate programme coverage. For example, compare the number of women attending antenatal care in the last three months with the expected number of women who are pregnant at any one time (see note below).
Figure 2-35: Regional estimates of pregnancies45
A review of Demographic and Health Surveys conducted between the years 2000 and 2005 can provide regional estimates of the expected number of women who are pregnant at any time. (Note that these estimates may mask considerable variation within country, especially urban/rural differences). The percentages below indicate the average percentage of women 15-49 who were pregnant at the time of the survey across all surveys in the region:
Sub-Saharan Africa—10% (19 countries, range 5.8% to 13.8%); North Africa/West Asia—5% (3 countries, range 4.0 to 6.3%); South and South-East Asia—5% (6 countries, range 4.1 to 7.1%); and Latin America and the Caribbean—5% (6 countries, range 4.2 to 7.6%).
Health systems and
infrastructure
Task 9: Protect the data to ensure rights and safety of
individuals/populations
Limit individual patient information to those directly involved in the patient’s care.
It is difficult to predict the potential misuses of patient information in a given situation. For example, victims of human rights abuses who are treated at a clinic or other service centres might be harmed or threatened, if identified, to prevent abuses from being discovered. The Sphere guideline is not to share patient information with others (those not directly involved in the patient’s care), unless the patient gives permission.27
Store medical records and other data that identifies individuals in a secure, safe place. Medical records need to be stored in a place and manner to prevent unauthorised persons from having access to them. Only record information that identifies a patient when it is needed for their health promotion.
Task 10: Triangulate Health Information Systems (HIS) information
with other data sources when possible
Cross-check the information obtained by HIS with other data sources.
Cross-checking information from different sources increases confidence in the available data when the results are similar. Other potential sources of data complementary to HIS include laboratories, surveys by other organisations and programme reports from other sectors (nutrition, water and sanitation, shelter, etc.). 27