| Title |
Impact of a Population Health Management Intervention on Disparities in Cardiovascular Disease Control
|
|---|---|
| Published in |
Journal of General Internal Medicine, January 2018
|
| DOI | 10.1007/s11606-017-4227-3 |
| Pubmed ID | |
| Authors |
Aisha James, Seth A. Berkowitz, Jeffrey M. Ashburner, Yuchiao Chang, Daniel M. Horn, Sandra M. O’Keefe, Steven J. Atlas |
| Abstract |
Healthcare systems use population health management programs to improve the quality of cardiovascular disease care. Adding a dedicated population health coordinator (PHC) who identifies and reaches out to patients not meeting cardiovascular care goals to these programs may help reduce disparities in cardiovascular care. To determine whether a program that used PHCs decreased racial/ethnic disparities in LDL cholesterol and blood pressure (BP) control. Retrospective difference-in-difference analysis. Twelve thousdand five hundred fifty-five primary care patients with cardiovascular disease (cohort for LDL analysis) and 41,183 with hypertension (cohort for BP analysis). From July 1, 2014-December 31, 2014, 18 practices used an information technology (IT) system to identify patients not meeting LDL and BP goals; 8 practices also received a PHC. We examined whether having the PHC plus IT system, compared with having the IT system alone, decreased racial/ethnic disparities, using difference-in-difference analysis of data collected before and after program implementation. Meeting guideline concordant LDL and BP goals. At baseline, there were racial/ethnic disparities in meeting LDL (p = 0.007) and BP (p = 0.0003) goals. Comparing practices with and without a PHC, and accounting for pre-intervention LDL control, non-Hispanic white patients in PHC practices had improved odds of LDL control (OR 1.20 95% CI 1.09-1.32) compared with those in non-PHC practices. Non-Hispanic black (OR 1.15 95% CI 0.80-1.65) and Hispanic (OR 1.29 95% CI 0.66-2.53) patients saw similar, but non-significant, improvements in LDL control. For BP control, non-Hispanic white patients in PHC practices (versus non-PHC) improved (OR 1.13 95% CI 1.05-1.22). Non-Hispanic black patients (OR 1.17 95% CI 0.94-1.45) saw similar, but non-statistically significant, improvements in BP control, but Hispanic (OR 0.90 95% CI 0.59-1.36) patients did not. Interaction testing confirmed that disparities did not decrease (p = 0.73 for LDL and p = 0.69 for BP). The population health management intervention did not decrease disparities. Further efforts should explicitly target improving both healthcare equity and quality. Clinical Trials #: NCT02812303 ( ClinicalTrials.gov ). |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 14% |
| Student > Bachelor | 7 | 11% |
| Student > Master | 6 | 9% |
| Student > Doctoral Student | 5 | 8% |
| Other | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 22 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 27% |
| Nursing and Health Professions | 7 | 11% |
| Social Sciences | 7 | 11% |
| Psychology | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 27 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 January 2018.
All research outputs
#15,057,216
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#5,588
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Outputs of similar age
#247,931
of 448,754 outputs
Outputs of similar age from Journal of General Internal Medicine
#103
of 146 outputs
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