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Chronic Disease

Chronic diseases are defined broadly as conditions that last 1 year or more and require ongoing medical attention or limit activities of daily living or both. Chronic diseases such as heart disease, cancer, and diabetes are the leading causes of death and disability in the United States. They are also leading drivers of the nation’s $3.8 trillion in annual health care costs.

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Data Source

About Chronic Diseases (NCCDPHP)

Population Estimates

Population estimates for the years 2016-2019 were obtained from the Texas Demographic Center. As 2020 is a census year, the Texas Demographic Center was unable to provide population estimates for that year. Thus, population estimates for the year 2020 were generated from the U.S. Census Bureau, Population Division and released in June 2021; CC-EST2020-AGESEX-[ST-FIPS]: Annual County and Puerto Rico Municipio Resident Population Estimates by Selected Age Groups and Sex: April 1, 2010 to July 1, 2020. The data include population estimates from file: 7/1/2020 County Characteristics Resident Population Estimates.

Hospitalization Rates

Hospital discharge data and information on primary payment source were analyzed based off data from the Texas Health Care Information Council (THCIC); Texas Hospital Inpatient Discharge Public Use Data File, [Quarter 1 - Quarter 4, 2016-2020]. Texas Department of State Health Services, Center for Health Statistics, Austin, Texas.

'Hospital Inpatient Discharge Rates were suppressed if fewer than 12 hospitalizations were reported, as the rates are unreliable below this threshold. Results do not include individuals positive for HIV or who are identified as drug/alcohol use patients. Counties with exactly 0 reported discharges for a specified condition are denoted. This 0 does not necessarily mean that the county actually had 0 discharges for the condition in question as the data are a snapshot in time, DSHS collects data from all hospitals in Texas not specifically exempted for certain situations such as natural disasters, and lastly the data is subject to errors caused by inability of hospital to communicate data due to form constraints, subjectivity in the assignments of codes, system mapping, and clerical error; 'Exempt hospitals include those located in a county with a population less than 35,000, or those located in a county with a population more than 35,000 and with fewer than 100 licensed hospital beds and not located in an area that is delineated as an urbanized area by the United States Bureau of the Census (Section 108.0025). Exempt hospitals also include hospitals that do not seek insurance payment or government reimbursement (Section 108.009).

Fluctuations in COPD hospital discharge rates during the time period of 2016-2018 are likely multifactorial. The switch in diagnostic coding to International Classification of Diseases (ICD)-10 codes has a likely impact on COPD discharge rates as well as Hurricane Harvey’s effect on hospital reporting status as select facilities were affected by disaster leading to an inability to report discharge data.

In 2020, reduced hospitalization rates were observed across multiple hospitalization indicators. This decrease is most likely due to reduced utilization of hospitals for factors not due primarily to COVID-19.


Asthma deaths were based on International Classification of Diseases (ICD)-10 codes J45-J46. COPD deaths were based on ICD10 codes J40-J44, J47, J67. Diabetes deaths were based on ICD-10 codes E10-E14. Chronic kidney disease deaths were based on ICD-10 codes I12-I13, E10.2, E11.2, E13.2, N18, N03.2, Q61.1-Q61.3, as E08.22 and E09.22 were not available in the VitalPro platform. Heart disease deaths were based on ICD-10 codes I00-I09, I11, I13, I20-I51. Stroke deaths were based on ICD-10 codes I60-I69. Suicide deaths were based on ICD-10 codes X72-74, X60-X71, X75-X84, Y87.0, U03 that describe deaths in which there was indicated use of intentional self-harm causes (suicide) including both "Intentional Self-Harm (Suicide) by Discharge of Firearms" and "Intentional Self-Harm (Suicide) by Other and Unspecified Means and their Sequelae"

County-level data for deaths are not shown due to high suppression rates.


Asthma hospitalization status was based on hospital records listing ICD-10 codes J45-J46 as the principal diagnosis. COPD hospitalization status was based on hospital records listing ICD-10 codes J40-J44, J47, and J67 as the principal diagnosis. Diabetes hospitalization status was based on hospital records listing ICD-10 codes E10-E11, and E13. E12 and E14 were not available in the THCIC dataset and thus were not included in analysis. This may lead to an underestimation of diabetes hospital discharge rates. ICD-10 codes E12 and E14 were able to be included in our mortality analysis. Chronic Kidney Disease hospitalization status was based on hospital records listing ICD-10 codes I12-I13, E08.22, E09.22, E10.22, E11.22, E13.22, N18, N03.2, Q61.1-Q61.3, or Z94.0 as the principal diagnosis. Heart Disease hospitalization status was based on hospital records listing ICD-10 codes I00-I09, I11, I13, or I20-I51 as the principal diagnosis. Stroke hospitalization status was based on hospital records listing ICD-10 codes I60-I69 as the principal diagnosis.


The Texas Behavioral Risk Factor Surveillance System (BRFSS), initiated in 1987, is a federally supported landline and cellular telephone survey that collects data about Texas residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. This surveillance can be used to monitor the Healthy People 2030 Objectives for current smoking, obesity, high blood pressure, exercise and physical activity, flu and pneumonia vaccinations, cholesterol and cancer screenings, seat belt use, as well as other risk factors.

In 2011, BRFSS began including data received from cell phone users and using a new data weighting methodology called raking or iterative proportional fitting. These changes allowed BRFSS to reach segments of the population that were previously inaccessible-those who have a cell phone but not a landline-and produce estimates of risk factors and diseases that are more representative of the population. Therefore, data collected in 2011 and beyond cannot be directly compared to data collected before 2011. In the dashboards above, these years are separated into two dashboards to avoid such comparisons.

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