Introduction Results Methods Conclusion Dissemination of HIV, HCV and STD Clinical Evidence to Primary Care Providers – An Analysis of User Profiles and Course Evaluations of a Statewide Online Clinical Education Program Meredith Abrams, MPH; Dongwen Wang, PhD Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ Introduction Results Rapid advances in HIV, HCV, and STD research have generated important clinical evidence. Dissemination of such evidence to primary care clinicians is essential for translating the latest research findings into the daily care of patients. With the wide use of information technology, continuing professional development courses are increasingly offered online. Since 2009, the New York State (NYS) HIV-HCV-STD Clinical Education Initiative (CEI) online training program has developed hundreds of: Multimedia learning modules; Online CME/CNE courses; Interactive case simulation tools; and Other internet-based resources. This study analyzes the profiles of clinicians participating in the CEI online training program and their evaluations of the online CME/CNE courses. Co-Variates Useful and Relevant Easy to Comprehend Knowledgeable Trainer Appropriate Format Knowledge Increase Intention to Use Knowledge Intention to Change Practice Total (4363) 3974 ( 91.08%) 3887 ( 89.09%) 4014 ( 92.00%) 3680 ( 84.35%) 2117 ( 48.52%) 3720 ( 85.26%) 959 ( 21.98%) Course Topic   p=0.0001 p<0.0001 p=0.0002 p=0.0711 HIV – General Medical Management (1401) 1249 ( 89.15%) 1231 ( 87.87%) 1272 ( 90.79%) 1235 ( 88.15%) 638 ( 45.54%) 1173 ( 83.73%) 368 ( 26.27%) HIV – Legal (1481) 1380 ( 93.18%) 1355 ( 91.49%) 1390 ( 93.86%) 1136 ( 76.70%) 818 ( 55.23%) 1284 ( 86.70%) 220 ( 14.85%) STD ( 558) 520 ( 93.19%) 509 ( 91.22%) 521 ( 93.37%) 480 ( 86.02%) 272 ( 48.75%) 491 ( 87.99%) 123 ( 22.04%) Gender p=0.0673 p=0.0275 p=0.0132 p=0.0980 p=0.1563 p=0.1436 p=0.3182 Male (1623) 1499 ( 92.36%) 1473 ( 90.76%) 1519 ( 93.59%) 1398 ( 86.14%) 768 ( 47.32%) 1407 ( 86.69%) 366 ( 22.55%) Female (2723) 2458 ( 90.27%) 2398 ( 88.06%) 2478 ( 91.00%) 2268 ( 83.29%) 1337 ( 49.10%) 2298 ( 84.39%) 589 ( 21.63%) Race p=0.0005 p=0.0004 p=0.0049 Asian ( 500) 476 ( 95.20%) 472 ( 94.40%) 475 ( 95.00%) 440 ( 88.00%) 200 ( 40.00%) 468 ( 93.60%) 141 ( 28.20%) Black or African American (1019) 899 ( 88.22%) 882 ( 86.56%) 898 ( 88.13%) 822 ( 80.67%) 462 ( 45.34%) 845 ( 82.92%) 215 ( 21.10%) White (2340) 2143 ( 91.58%) 2090 ( 89.32%) 2177 ( 93.03%) 2014 ( 86.07%) 1195 ( 51.07%) 1978 ( 84.53%) 502 ( 21.45%) Ethnic Background p=0.0864 p=0.4283 p=0.1181 p=0.1000 Hispanic or Latino ( 838) 776 ( 92.60%) 753 ( 89.86%) 782 ( 93.32%) 667 ( 79.59%) 428 ( 51.07%) 749 ( 89.38%) 140 ( 16.71%) Not Hispanic or Latino (3525) 3198 ( 90.72%) 3134 ( 88.91%) 3232 ( 91.69%) 3013 ( 85.48%) 1689 ( 47.91%) 2971 ( 84.28%) 819 ( 23.23%) Primary Professional Discipline/Occupation Case/Care Manager ( 347) 295 ( 85.01%) 285 ( 82.13%) 302 ( 87.03%) 278 ( 80.12%) 162 ( 46.49%) 282 ( 81.27%) 64 ( 18.44%) Counselor ( 210) 181 ( 86.19%) 180 ( 85.71%) 182 ( 86.67%) 179 ( 85.24%) 92 ( 43.81%) 176 ( 83.81%) 27 ( 12.86%) Nurse ( 572) 501 ( 87.59%) 480 ( 83.92%) 495 ( 86.54%) 274 ( 47.90%) 459 ( 80.24%) 99 ( 17.31%) Nurse Practitioner ( 510) 489 ( 95.88%) 484 ( 94.90%) 490 ( 96.08%) 448 ( 87.84%) 218 ( 42.75%) 486 ( 95.29%) 179 ( 35.10%) Pharmacist ( 229) 205 ( 89.52%) 204 ( 89.08%) 202 ( 88.21%) 198 ( 86.46%) 44 ( 19.21%) 196 ( 85.59%) 57 ( 24.89%) Physician ( 796) 743 ( 93.34%) 734 ( 92.21%) 762 ( 95.73%) 700 ( 87.94%) 399 ( 50.13%) 705 ( 88.57%) 238 ( 29.90%) Social Worker ( 208) 193 ( 92.79%) 188 ( 90.38%) 194 ( 93.27%) 171 ( 82.21%) 115 ( 55.29%) 180 ( 86.54%) 42 ( 20.19%) Employment Setting p=0.0090 p=0.0050 Community Health Center (1050) 981 ( 93.43%) 959 ( 91.33%) 993 ( 94.57%) 875 ( 83.33%) 549 ( 52.29%) 946 ( 90.10%) 258 ( 24.57%) Hospital/Hospital Clinic ( 895) 798 ( 89.16%) 784 ( 87.60%) 808 ( 90.28%) 779 ( 87.04%) 376 ( 42.01%) 764 ( 85.36%) 212 ( 23.69%) Private Practice/Group Practice ( 497) 462 ( 92.96%) 452 ( 90.95%) 463 ( 93.16%) 444 ( 89.34%) 185 ( 37.22%) 433 ( 87.12%) 160 ( 32.19%) State/Local Health Department/Clinic ( 262) 235 ( 89.69%) 237 ( 90.46%) 246 ( 93.89%) 215 ( 82.06%) 115 ( 43.89%) 195 ( 74.43%) 38 ( 14.50%) Methods We compiled CEI online training user profiles and course evaluation data from November 2014 through October 2015. We collected clinicians’ personal and professional background such as demographics, education level, primary professional discipline, practice years, employment setting, employment location, caseload, and clinical services provided. We measured course evaluation through clinicians’ self-reported data on: Usefulness/relevance of information; Ease of comprehension; Knowledge of the trainer; Appropriateness of format; Knowledge level before and after training; Intention to use the learned knowledge; and Plan to change clinical practice. We included in the analysis only those clinicians with complete user profiles and successfully passed at least one online CME/CNE course during the study period. For each parameter of the user profile and seven categories of training topics, we performed univariate analysis with chi-square test to identify the potentially significant factors for positive course evaluations. We then included the statistically significant variables from the univariate analyses into a multivariate logistic regression model for each of the 7 measures. Clinicians evaluations of online courses were very positive: Useful/Relevant: 91.08% Easy Comprehension: 89.09% Knowledgeable Trainer: 92.00% Appropriate Format:84.35% Univariate analyses indicated significant differences within the four evaluation measures (usefulness/relevance, easy comprehension, knowledgeable trainer, and appropriate format) by: (1) training topic (p<0.01) (2) race (p<0.01) (3) education level (p<0.01) (4) discipline (p<0.01) (5) employment setting (p<0.01) (6) HCV and STD caseload (p<0.05) (7) most HIV, HCV, and STD services (p<0.01) We recorded significant differences for knowledge increase by: (3) discipline (p<0.01) (4) practice years (p<0.01) (5) employment setting and location (p<0.01) (6) HIV, STD and HCV caseloads (p<0.01) Assessment of the impact showed that: 48.52% had ≥1 level increase in knowledge 85.26% indicated a plan to utilize the knowledge learned 21.98% clinicians (39.43% of those providing direct patient services) indicated intention to make changes in their practice We recorded significant differences in intention to use knowledge by: (1) race (p<0.01) (2) ethnicity (p<0.01) (3) education level (p<0.01) (4) discipline (p<0.01) (5) practice years (p<0.01) (6) employment setting (p<0.01) (7) HIV, HCV, and STD caseloads (p<0.01) (8) most HIV, HCV, and STD services (p<0.01) We recorded significant differences in intention to change practice by: (1) course topic (p<0.01) (2) race (p<0.01) (3) ethnicity (p<0.01) (4) education level (p<0.01) (5) discipline (p<0.01) (6) practice years (p<0.01) (7) employment setting (p<0.01) (8) HIV, HCV, and STD caseload (p<0.01) (9) most HIV, HCV, and STD services (p<0.01) Conclusion Clinicians had very positive evaluations of the CEI online courses. We have identified potential factors for positive impact to knowledge increase, intention to use knowledge, and plan to change clinical practice. Future development of online CME/CNE courses may need to incorporate these factors for more effective knowledge dissemination. Figure 1: Screenshot of the course evaluation form. Acknowledgements For more information This work is supported by grant #R24HS022057 from the Agency for Healthcare Research and Quality (AHRQ), and by contracts #C023557, #C024882, and #C029086 from NYS Department of Health AIDS Institute. The content is solely the responsibility of the author and does not necessarily represent the official views of the sponsors. Please feel free to contact: Meredith Abrams | Meredith.Abrams@asu.edu Dongwen Wang | Dongwen.Wang@asu.edu