Source: Disability Database Unit, Health Research Board Creator: Disability Database Unit, Health Research Board
The Health Research Board (HRB) is the lead agency supporting and funding health research in Ireland. They also have a core role in maintaining health information systems and conducting research linked to national health priorities. Their aim is to improve peopleís health, build health research capacity, underpin developments in service delivery and make a significant contribution to Irelandís knowledge economy.
The National Intellectual Disability Database (NIDD) was established in 1995 to ensure that information is available to enable the Department of Health and Children, the Health Service Executive (HSE) and the non-statutory agencies in Ireland to provide appropriate services designed to meet the changing needs of people with intellectual disability and their families. The database is intended to provide a comprehensive and accurate information base for decision making in relation to the planning, funding and management of services for people with an intellectual disability.
The database was established on the principle that minimum information with maximum accuracy was preferred; hence, it incorporates only three basic elements of information: demographic details, current service provision and future service requirements. The objective is to obtain this information for every individual known to have an intellectual disability and assessed as being in receipt of, or in need of, an intellectual disability service. Information pertaining to diagnosis is specifically excluded, as the database is not designed as a medical, epidemiological tool. The data held in any individual record represent the information available for that person at a specified point in time only. The record is updated whenever there are changes in the personís circumstances or during the annual review process in the spring of each year.
The information now available from the NIDD provides a much better basis for decision making than was previously the case. Priorities can be set based on an objective evaluation of the needs of people with intellectual disability, and services that are sensitive to these needs can be delivered. The commitment of all services and agencies involved in the maintenance of the database is significant and their continuing commitment and co-operation is crucial in ensuring the ongoing availability of accurate information.
DAY SUPPORT LEVEL CODES
0: NOT APPLICABLE
1: MINIMUM (staff to client ratio is 1 to 10+)
2: LOW (between 1 to 6 and 1 to 9)
3: MODERATE (between 1 to 4 and 1 to 5)
4: HIGH (between 1 to 2 and 1 to 3)
5: INTENSIVE (1 to 1 or above)
RESIDENTIAL SUPPORT LEVEL CODES
A: MINIMUM (no sleep-in)
B: LOW (staff on duty most of the time plus sleep-in)
C: MODERATE (two staff on duty plus sleep-in)
D: HIGH (two staff on duty plus on-duty night staff)
Z: NOT APPLICABLE
Using this data:
Interpret these data cautiously. As a general rule, this website does not include confidence limits in its charts and maps. It aims to provide visual tools that allow you to explore an underling table or dataset. If you find something that you think is important, we strongly urge you to explore it more rigorously – consulting an experienced data analyst if appropriate – before taking any action based on that finding.
1. Statistical precision
Indicator values are prone to statistical error (the difference between an estimated value and the true value). The statistical error associated with an indicator depends on the population subgroup (e.g. the population of a county or LGD) that it refers to. Such differences in levels of statistical error can distort what we see in maps and charts. They can make some relationships involving indicators and attributes appear “real” (practically meaningful or statistically significant) when they are in fact spurious; other relationships that are “real” can be masked. These differences in statistical error can even distort the shape of plots or the colour patterns we see in maps.
Many indicator values estimates are derived from sample surveys, and different sample sizes from different population subgroups will lead to different levels of precision in the indicator values for these subgroups.
Different population subgroups have different population sizes which means that rate estimates for these subgroups will also have different confidence limits.
The true value of a percentage or a rate can influence the level of statistical error of any estimate.
2. Scales and legends
The scales used on chart axes and in can also distort our perceptions:
The range of values allowed on chart axes can accentuate relationships making them appear more “real” than they actually are.
The radial arms of spider plots of scaled data show the position of the value (in a population subgroup) relative to the minimum and maximum values of that indicator. Because these minimum and maximum depend on the indicator, relative positions of different population subgroups on different radial arms are not directly comparable.
The cut-off values used to determine the colours to shade areas of a map are default selections and do not necessarily represent meaningful values of the indicator. Areas with very similar data values can be shown with different shades. You should always note the actual values.