Caso 1- Saúde e Diabete

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12/11/2018 Knowing the who, informs the what | SAS
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Knowing the who, informs the
what
Accurate diabetes data helps New Zealand provide
appropriate and timely care
Diabetes is a condition in which the pancreas fails to make enough insulin or the body is
insensitive to the insulin present, resulting in an overabundance of glucose in the blood.
Patient care for the condition is extremely important as diabetes often causes additional
complications, including significant morbidity, mortality and high health care costs.
New Zealand's Ministry of Health found it difficult to accurately estimate the number of
cases in the country since there was no consistent data collection across all general
practices and hospitals. With the help of SAS' data analysis capabilities, the ministry
created a register to accurately predict the prevalence of the condition and help design
effective public health policies to support quality clinical improvements.
Tracking the population of diabetics
GPs should know already how many [diabetic patients] they have - the VDR
is also able to help them predict who may be at risk so they can be
prepared.
Dr. Paul Drury 
Clinical Director of the Diabetes Auckland
Center and Medical Director of NZSSD 
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The Ministry of Health, in collaboration with experts from the New Zealand Society for
the Study of Diabetes (NZSSD), established a Virtual Diabetes Register (VDR) that
combines and filters various sources of health information to more accurately determine
how many people are diagnosed with the condition, as well as predicting who is likely to
develop it in the future.
Dr. Paul Drury, Clinical Director of the Diabetes Auckland Center and Medical Director of
NZSSD; Dr. Sandy Dawson, Chief Clinical Advisor; and Emmanuel Jo, Principal
Technical Specialist at Health Workforce New Zealand, Ministry of Health, have all been
instrumental in the establishing the VDR.
"Previously, we would use national surveys to measure diabetes in the community;
however, this proved to be slow, costly and have a high error rate," Jo says. "Now, the
quality of data within the VDR is offering the accuracy and immediacy we need."
Six major databases were used to establish the VDR: hospital admissions coded for
diabetes; outpatient attendances for diabetes and diabetes retinal screening;
prescriptions of specific antidiabetic therapies; laboratory orders for HbA1c, which is a
measure of diabetes management; and primary health (general practitioner)
enrollments.
Using SAS software, an analytical model was created and modified to improve
sensitivity and specificity, and then validated against primary care registers.
"Primary data was linked by the National Health Index number, which was available
from six databases at the ministry," Jo says.
He adds one challenge came from linking the six data sources and integrating them with
a patient's health number to work out if they needed to make contact with their local
health center – a process he says took years to refine.
But Drury says the initial results were impressive. "The initial estimation before the VDR
was refined showed that 210,679 people, or 4.88 percent, had diabetes in New Zealand
as of Dec. 31, 2009. This compares with the country's population of 4,315,355. The
VDR yielded a final estimate of 189,256 people, or 4.39 percent, with diabetes."
He adds that diabetes prevalence also showed a clear difference between
European/other versus non European/other ethnicity. "Indian and Pacific people have the
highest diabetes prevalence rate," Drury says. "This means we can focus health policies
on this group.
"The beauty of the VDR is in combining many data sources and merging the database
with other sources of data to look at the implication of diabetes in particular cohorts,"
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Drury says.
"SAS' analytical capabilities have been the key tool in developing the VDR to be very
accurate and robust, revealing a true representation of the diabetes population," Jo
says.
More effective health policy planning
In addition to more accurately predicting the number of people with diabetes, the VDR is
used for planning health services and policies.
"We have 20 different District Health Boards (DHB), and the data can show them how
many diabetic people are in their area," Drury says. "GPs should know already how
many they have, but the VDR is also able to help them predict who may be at risk so
they can be prepared. By knowing the populations where diabetes is more prevalent,
more resources can be directed at them to provide clinical quality improvements."
Privacy in health is always an important factor, but Drury says access to the data in the
VDR is regulated. "We have built the VDR to ensure there is privacy around patient
information. Each DHB from this year can access this and see its data. GPs themselves
don't have open access to the register – it only goes to those directly involved in that
individual person's health care."
100 million rows of data with SAS
The VDR relies on SAS for its analytical data management. "SAS is the only tool that is
able to deal with the amount of number crunching that we require," Jo says. "Some of
the data sets we use are very large with more than 1 million rows of data per month.
Sometimes we need to go back 10 years, so we're looking at working with over 100
million rows of data. SAS is the best tool to enable this."
In the future, the VDR will continue to have more criteria added to it to monitor changes.
"The criteria from five years ago will become less accurate as medical science changes,
so our systems with SAS are built to be able to respond easily to these changes," Drury
says.
Jo adds that it is very easy to change the analytical models in the SAS solution. "It is a
well structured system with robust coding," he says.
Both Jo and Drury are extremely pleased with the support from SAS in setting up the
VDR and the positive effects it has had on managing diabetes in the country.
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The results illustrated in this article are specific to the particular situations, business models, data input, and computing
environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all
statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on
individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve
similar results. The only warranties for SAS products and services are those that are set forth in the express warranty
statements in the written agreement for such products and services. Nothing herein should be construed as constituting an
additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or
project success summarization following a successful implementation of SAS software. Brand and product names are
trademarks of their respective companies.
"The VDR is invaluable for monitoring national prevalence and supporting clinical quality
improvements," Drury says. "It is also readily applicable to other areas and future
projects to investigate the correlation between the two areas or among many other
factors." 
Challenge
Getting accurate information surrounding the number of people in New Zealand with
diabetes.
Solution
Benefits
 SAS Analytics®
 SAS BI Server®
 SAS Enterprise Guide® ®
 Linked six data sources and integrated those sources with patient's heath number.
 Identified cohorts with increasedprevalence rate.
 Can predict who may be at risk to ensure appropriate resources are available.
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