Demographics & Health Conditions

With seven health care systems treating over 10 million patients, PaTH gives researchers the opportunity to work with and learn from larger and more diverse populations than would be available in any single system.

For instance, sites with smaller percentages of young patients, such as Penn State and Temple, can benefit from their partner sites’ higher percent of patients under 18. Meanwhile, the other sites gain Penn State’s high percent of patients who are 65 and older and Utah’s high percent of patients aged 18 to 44.

Likewise, Temple University offers a higher percent of African American patients than its partner sites, while the University of Utah brings a higher percent of Hispanic and Latino patients to studies.

By combining populations, the PaTH Network is able to increase the quantity, quality, and diversity of patient data available to researchers and therefore strengthen their study findings.

Pitt/UPMC PSCoM/HMC TUHS JHU Geisinger OSU UofM PaTH Total
Enrollment
total # of patients in CDM 3,769,209 1,188,031 1,199,151 3,227,975 2,082,953 1,326,701 1,958,971 14,752,991
Age
Percent 17 years or younger 18.23% 21.29% 10.91% 4.06% 15.35% 6.02% 16.84% 15.29%
Percent 18 to 44 years 32.53% 32% 36.86% 31.64% 34.52% 38.22% 34.58% 33.71%
Percent 45 to 64 years 23.86% 22.57% 27.47% 26.53% 23.82% 29.24% 24.25% 25.17%
Percent 65 years or older 25.33% 24.14% 24.76% 27.77% 26.31% 26.52% 24.12% 25.8%
Race/Ethnicity
Percent American Indian/Alaska Native 0.21% 0.17% 0.08% 0.2% 0.15% 0.12% 0.31% 0.19%
Percent Asian 1.56% 1.65% 2.98% 4.65% 1.3% 3.04% 4.52% 2.85%
Percent black or African American 8.23% 5.47% 29.61% 22.62% 5.26% 13.99% 7.52% 12.9%
Percent white 81.62% 68.79% 36.93% 55.41% 90.57% 71.37% 63.47% 69.15%
Percent Asian/Pacific Islander 0.06% 0.07% 0.03% 0.08% 0.5% 0.05% 0.08% 0.12%
Percent unknown 8.33% 20.61% 30.36% 16.98% 2.23% 0.32% 24.11% 13.52%
Percent multiple races 0% 3.24% 0% 0.05% 0% 0.73% 0% 0.34%
Percent hispanic 0.96% 6.65% 13.29% 5.81% 5.23% 2.62% 2.7% 4.46%

Objective: Counts of the number of distinct patients in 2017 with the following codes of interest: Respiratory Conditions, Selected Malignancies, Myocardial Infarction, Stroke, Rheumatoid Arthritis, Ulcerative Colitis, Hypertension, Renal Disease, and Influenza/Pneumonia within PCORnet Clinical Data Research Network.

PCORnet: Characteristics by Condition Cluster Count1 Respiratory Conditions Selected Malignancies Myocardial Infarction Stroke Rheumatoid Arthritis Ulcerative Colitis Hypertension Renal Disease Influenza / Pneumonia Diabetes
N N N N N N N N N N
Overall (N) 122,924 196,521 26,207 46,345 41,496 16,683 931,548 158,161 98,245 386,106
By Age Group2
01-20 406 3,999 39 732 313 988 5,420 1,963 28,013 8,357
21-44 4,931 17,088 1,384 3,162 5,356 5,215 91,903 9,681 15,407 40,858
45-64 49,024 71,603 9,355 15,074 18,188 5,890 375,834 42,126 23,539 159,167
65-74 36,409 59,505 7,216 12,143 10,297 2,792 241,959 42,644 13,847 101,782
75+ 32,154 44,326 8,213 15,234 7,342 1,798 216,432 61,747 17,439 75,942
By Sex2
Female 65,449 81,088 10,539 23,476 31,191 8,999 478,579 76,641 51,666 192,138
Male 57,473 115,430 15,668 22,869 10,305 7,684 452,961 81,517 46,579 193,963
Other/Missing 1 3 0 0 0 0 4 1 0 1
By Race2
American Indian or Alaska Native 174 138 38 54 46 21 1,033 177 122 575
Asian 445 2,583 212 540 383 134 9,394 1,190 1,593 5,277
Black/African American 13,421 19,713 2,895 6,946 4,276 1,103 128,531 25,080 12,934 58,724
Native Hawaiian or Other Pacific Islander 50 75 22 31 29 10 798 91 117 1,922
White 101,062 163,893 21,273 35,287 34,072 14,434 723,761 121,818 75,521 285,849
Other/Missing 7,772 8,640 1,767 3,487 2,690 978 68,031 9,805 7,958 33,759
By Hispanic2
Yes 1,948 3,983 654 1,366 1,160 248 22,379 3,376 3,833 13,733
No 111,344 182,318 23,807 41,884 37,665 15,341 839,647 145,349 87,806 343,895
Other/Missing 9,632 10,220 1,746 3,095 2,671 1,094 69,522 9,436 6,606 28,478

1 Condition cluster counts are based solely on assignment of any of the listed coded diagnoses provided here during 2017. These counts should not be interpreted as epidemiological estimates of the listed conditions, but instead reflect a count of the number of times the listed diagnosis is coded during 2017. Coding procedures may vary from site to site. Duplicate data may exist. The period of time in 2017 during which data were available may vary between Network Partners.
2 Some stratified counts may not equal the total N counts because of low cell count masking.

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