Difference between revisions of "DASH Guide:Cardiovascular Disease Co-morbidity"
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Most cardiovascular diseases can be prevented by addressing key behavioral risk factors, including tobacco use, unhealthy eating habits, physical inactivity, obesity, and excessive alcohol consumption. People with cardiovascular disease or those who are at elevated risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidemia or already established disease) can benefit from early detection and management, including counseling, medication, and other treatments. | Most cardiovascular diseases can be prevented by addressing key behavioral risk factors, including tobacco use, unhealthy eating habits, physical inactivity, obesity, and excessive alcohol consumption. People with cardiovascular disease or those who are at elevated risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidemia or already established disease) can benefit from early detection and management, including counseling, medication, and other treatments. | ||
=== Definitions | === Definitions === | ||
* Co-morbidity- The simultaneous presence of two chronic diseases or conditions in an individual. | * Co-morbidity- The simultaneous presence of two chronic diseases or conditions in an individual. | ||
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* Hyperlipidemia- an abnormally high concentration of fats or lipids in the blood. | * Hyperlipidemia- an abnormally high concentration of fats or lipids in the blood. | ||
=== What's Included in the Data | === What's Included in the Data === | ||
==== Publicly Available ==== | ==== Publicly Available ==== | ||
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* Census Tract (2010 boundary) | * Census Tract (2010 boundary) | ||
=== Where to Find the Data | === Where to Find the Data === | ||
* Publicly Available | * Publicly Available | ||
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** [https://data.wprdc.org/dataset/diabetes-hypertension-hyperlipidemia-comorbidity Diabetes + Hypertension +Hyperlipidemia] | ** [https://data.wprdc.org/dataset/diabetes-hypertension-hyperlipidemia-comorbidity Diabetes + Hypertension +Hyperlipidemia] | ||
=== Things to Know | === Things to Know === | ||
All four co-morbidity datasets include information on the total number insured, number of members with a diagnosis, and the number of diagnosed members that have filled medication related to that condition. Separate datasets include each of the four combinations of cardiovascular disease: | All four co-morbidity datasets include information on the total number insured, number of members with a diagnosis, and the number of diagnosed members that have filled medication related to that condition. Separate datasets include each of the four combinations of cardiovascular disease: | ||
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* An individual may be diagnosed with a cardiovascular disease condition, but if they are not a member of a participating managed care organization, they would not be captured in the data. Likewise, an individual could be enrolled in one of the participating managed care organizations, have a cardiovascular disease, be undiagnosed, and therefore not captured in the data. | * An individual may be diagnosed with a cardiovascular disease condition, but if they are not a member of a participating managed care organization, they would not be captured in the data. Likewise, an individual could be enrolled in one of the participating managed care organizations, have a cardiovascular disease, be undiagnosed, and therefore not captured in the data. | ||
* Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days. | * Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days. | ||
== References == |
Latest revision as of 23:01, 21 December 2022
This guide is just part of a larger DASH Data Guide.
These datasets provide de-identified co-morbidity insurance data for diabetes, hypertension, and hyperlipidemia. The data is provided by three managed care organizations in Allegheny County (Gateway Health Plan, Highmark Health, and UPMC) and represents their insured population for the 2015 calendar year.
According to the World Health Organization[1], cardiovascular diseases are the leading global cause of death. In 2012, it has been
estimated that 17.5 million people died from cardiovascular disease, accounting for nearly one third of total deaths on the planet. Of these deaths, an estimated 7.4 million were due to coronary heart disease and 6.7 million were due to stroke. There are also geographic disparities evident in this data, with over three quarters of deaths due to cardiovascular disease occurring in low- and middle-income countries.
Most cardiovascular diseases can be prevented by addressing key behavioral risk factors, including tobacco use, unhealthy eating habits, physical inactivity, obesity, and excessive alcohol consumption. People with cardiovascular disease or those who are at elevated risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidemia or already established disease) can benefit from early detection and management, including counseling, medication, and other treatments.
Definitions
- Co-morbidity- The simultaneous presence of two chronic diseases or conditions in an individual.
- Diabetes - a disease in which the body’s ability to produce or respond to the hormone insulin is impaired, resulting in abnormal metabolism of carbohydrates and elevated levels of glucose in the blood and urine.
- Hypertension- abnormally high blood pressure.
- Hyperlipidemia- an abnormally high concentration of fats or lipids in the blood.
What's Included in the Data
Publicly Available
- Total insured in participating managed care organizations
- Total diagnosed by disease types and gender
- Total receiving medication by disease type and gender
- Census Tract (2010 boundary)
Where to Find the Data
- Publicly Available
Things to Know
All four co-morbidity datasets include information on the total number insured, number of members with a diagnosis, and the number of diagnosed members that have filled medication related to that condition. Separate datasets include each of the four combinations of cardiovascular disease:
- The total number of members referenced in the data dictionary is based on de-identified, merged population data from Gateway Health Plan, Highmark Health, and the University of Pittsburgh Medical Center. These members represent approximately 60% of the county’s insured population. The total estimate of insured people in Allegheny County used to calculate this statistic comes from the U.S. Census Bureau's 2015 American Community Survey.
- The share of insured members of the participating managed care organizations varies from tract to tract. For this reason, the most-appropriate tract level comparison to use is the percent of the insured population from participating managed care organizations with a particular diagnosis.
- An individual may be diagnosed with a cardiovascular disease condition, but if they are not a member of a participating managed care organization, they would not be captured in the data. Likewise, an individual could be enrolled in one of the participating managed care organizations, have a cardiovascular disease, be undiagnosed, and therefore not captured in the data.
- Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time, as data provided were collected for purposes other than surveillance. Limitations of these data include but are not limited to: misclassification, duplicate individuals, exclusion of individuals who did not seek care in past two years and those who are: uninsured, enrolled in plans not represented in the dataset, or were not enrolled in one of the represented plans for at least 90 days.