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1,854 results on '"O'CONNOR, PATRICK J."'

11. Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: Design of a pragmatic trial

Author

Benziger, Catherine P., Suess, Madison, Allen, Clayton I., Freitag, Laura A., Asche, Stephen E., Ekstrom, Heidi L., Essien, Inih J., Muthineni, Abhilash, Thirumalai, Vijayakumar, Vo, Phuong H., Kromrey, Kay A., Ronkainen, Elizabeth A., Saman, Daniel M., O'Connor, Patrick J., and Kharbanda, Elyse O.

Published
2023
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15. Design of a pragmatic clinical trial to improve screening and treatment for opioid use disorder in primary care

Author

Rossom, Rebecca C., Crain, A. Lauren, O'Connor, Patrick J., Wright, Eric, Haller, Irina V., Hooker, Stephanie A., Sperl-Hillen, JoAnn M., Olson, Anthony, Romagnoli, Katrina, Solberg, Leif, Dehmer, Steven P., Haapala, Jacob, Borgert-Spaniol, Caitlin, Tusing, Lorraine, Muegge, Jule, Allen, Clayton, Ekstrom, Heidi, Huntley, Kristen, McCormack, Jennifer, and Bart, Gavin

Published
2023
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19. Development of a Clinical Decision Support System for Pediatric Abdominal Pain in Emergency Department Settings Across Two Health Systems Within the HCSRN

Author

Ekstrom, Heidi L, Kharbanda, Elyse O, Ballard, Dustin W, Vinson, David R, Vazquez-Benitez, Gabriela, Chettipally, Uli K, Dehmer, Steven P, Kunisetty, Gopikrishna, Sharma, Rashmi, Rauchwerger, Adina S, O'Connor, Patrick J, and Kharbanda, Anupam B

Subjects
Health Services and Systems, Health Sciences, Health Services, Emergency Care, Patient Safety, Networking and Information Technology R&D (NITRD), Clinical Research, Pediatric, Digestive Diseases, Good Health and Well Being, Appendicitis, Clinical Decision Support, Pediatric Emergency Medicine, Risk Stratification, Clinical sciences, Health services and systems
Abstract

BackgroundAppendicitis is a common surgical emergency in children, yet diagnosis can be challenging. An electronic health record (EHR) based, clinical decision support (CDS) system called Appy CDS was designed to help guide management of pediatric patients with acute abdominal pain within the Health Care Systems Research Network (HCSRN).ObjectivesTo describe the development and implementation of a clinical decision support tool (Appy CDS) built independently but synergistically at two large HCSRN affiliated health systems using well-established platforms, and to assess the tool's Triage component, aiming to identify pediatric patients at increased risk for appendicitis.ResultsDespite differences by site in design and implementation, such as the use of alerts, incorporating gestalt, and other workflow variations across sites, using simple screening questions and automated exclusions, both systems were able to identify a population with similar appendicitis rates (11.8 percent and 10.6 percent), where use of the full Appy CDS would be indicated.DiscussionThese 2 HCSRN sites designed Appy CDS to capture a population at risk for appendicitis and deliver CDS to that population while remaining locally relevant and adhering to organizational preferences. Despite different approaches to point-of-care CDS, the sites have identified similar cohorts with nearly identical background rates of appendicitis.Next stepsThe full Appy CDS tool, providing personalized risk assessment and tailored recommendations, is undergoing evaluation as part of a pragmatic cluster randomized trial aiming to reduce reliance on advanced diagnostic imaging. The novel approaches to CDS we present could serve as the basis for future ED interventions.

Published
2019

21. Comparison of explanatory and pragmatic design choices in a cluster-randomized hypertension trial: effects on enrollment, participant characteristics, and adherence

Author

Margolis, Karen L., Crain, A. Lauren, Green, Beverly B., O’Connor, Patrick J., Solberg, Leif I., Beran, MarySue, Bergdall, Anna R., Pawloski, Pamala A., Ziegenfuss, Jeanette Y., JaKa, Meghan M., Appana, Deepika, Sharma, Rashmi, Kodet, Amy J., Trower, Nicole K., Rehrauer, Daniel J., McKinney, Zeke, Norton, Christine K., Haugen, Patricia, Anderson, Jeffrey P., Crabtree, Benjamin F., Norman, Sarah K., and Sperl-Hillen, JoAnn M.

Published
2022
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24. Primary care clinicians’ opinions before and after implementation of cancer screening and prevention clinical decision support in a clinic cluster-randomized control trial: a survey research study

Author

Harry, Melissa L., Chrenka, Ella A., Freitag, Laura A., Saman, Daniel M., Allen, Clayton I., Asche, Stephen E., Truitt, Anjali R., Ekstrom, Heidi L., O’Connor, Patrick J., Sperl-Hillen, Jo Ann M., Ziegenfuss, Jeanette Y., and Elliott, Thomas E.

Published
2022
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25. Development and Validation of a Novel Pediatric Appendicitis Risk Calculator (pARC)

Author

Kharbanda, Anupam B, Vazquez-Benitez, Gabriela, Ballard, Dustin W, Vinson, David R, Chettipally, Uli K, Kene, Mamata V, Dehmer, Steven P, Bachur, Richard G, Dayan, Peter S, Kuppermann, Nathan, O’Connor, Patrick J, and Kharbanda, Elyse O

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Chronic Pain, Pain Research, Patient Safety, Pediatric, Digestive Diseases, Abdominal Pain, Adolescent, Appendicitis, Child, Child, Preschool, Cohort Studies, Diagnosis, Differential, Female, Humans, Male, Nausea, ROC Curve, Reproducibility of Results, Risk Factors, Severity of Illness Index, Vomiting, Medical and Health Sciences, Psychology and Cognitive Sciences, Pediatrics, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

We sought to develop and validate a clinical calculator that can be used to quantify risk for appendicitis on a continuous scale for patients with acute abdominal pain. The pediatric appendicitis risk calculator (pARC) was developed and validated through secondary analyses of 3 distinct cohorts. The derivation sample included visits to 9 pediatric emergency departments between March 2009 and April 2010. The validation sample included visits to a single pediatric emergency department from 2003 to 2004 and 2013 to 2015. Variables evaluated were as follows: age, sex, temperature, nausea and/or vomiting, pain duration, pain location, pain with walking, pain migration, guarding, white blood cell count, and absolute neutrophil count. We used stepwise regression to develop and select the best model. Test performance of the pARC was compared with the Pediatric Appendicitis Score (PAS). The derivation sample included 2423 children, 40% of whom had appendicitis. The validation sample included 1426 children, 35% of whom had appendicitis. The final pARC model included the following variables: sex, age, duration of pain, guarding, pain migration, maximal tenderness in the right-lower quadrant, and absolute neutrophil count. In the validation sample, the pARC exhibited near perfect calibration and a high degree of discrimination (area under the curve: 0.85; 95% confidence interval: 0.83 to 0.87) and outperformed the PAS (area under the curve: 0.77; 95% confidence interval: 0.75 to 0.80). By using the pARC, almost half of patients in the validation cohort could be accurately classified as at 8. In our validation cohort of patients with acute abdominal pain, the pARC accurately quantified risk for appendicitis.

Published
2018

37. Protocol of a patient randomized clinical trial to improve medication adherence in primary care

Author

Sperl-Hillen, JoAnn M., primary, Haapala, Jacob L., additional, Dehmer, Steven P., additional, Chumba, Lilian N., additional, Ekstrom, Heidi L., additional, Truitt, Anjali R., additional, Asche, Stephen E., additional, Werner, Ann M., additional, Rehrauer, Dan J., additional, Pankonin, Melissa A., additional, Pawloski, Pamala A., additional, and O'Connor, Patrick J., additional

Published
2023
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39. Data mining for censored time-to-event data: A Bayesian network model for predicting cardiovascular risk from electronic health record data

Author

Bandyopadhyay, Sunayan, Wolfson, Julian, Vock, David M., Vazquez-Benitez, Gabriela, Adomavicius, Gediminas, Elidrisi, Mohamed, Johnson, Paul E., and O'Connor, Patrick J.

Subjects
Statistics - Machine Learning, Statistics - Applications
Abstract

Models for predicting the risk of cardiovascular events based on individual patient characteristics are important tools for managing patient care. Most current and commonly used risk prediction models have been built from carefully selected epidemiological cohorts. However, the homogeneity and limited size of such cohorts restricts the predictive power and generalizability of these risk models to other populations. Electronic health data (EHD) from large health care systems provide access to data on large, heterogeneous, and contemporaneous patient populations. The unique features and challenges of EHD, including missing risk factor information, non-linear relationships between risk factors and cardiovascular event outcomes, and differing effects from different patient subgroups, demand novel machine learning approaches to risk model development. In this paper, we present a machine learning approach based on Bayesian networks trained on EHD to predict the probability of having a cardiovascular event within five years. In such data, event status may be unknown for some individuals as the event time is right-censored due to disenrollment and incomplete follow-up. Since many traditional data mining methods are not well-suited for such data, we describe how to modify both modelling and assessment techniques to account for censored observation times. We show that our approach can lead to better predictive performance than the Cox proportional hazards model (i.e., a regression-based approach commonly used for censored, time-to-event data) or a Bayesian network with {\em{ad hoc}} approaches to right-censoring. Our techniques are motivated by and illustrated on data from a large U.S. Midwestern health care system., Comment: 31 pages (including references), 6 figures

Published
2014

42. The Professional Development Needs of Academic Teachers Adding Career-Technical Education Licenses

Author

O'Connor, Patrick J.

Abstract

This study reports the results on the needs of an emerging population of Career-Technical Education (CTE) teachers in Ohio. The purposes of the study were to determine the needs of the teachers and the effectiveness of the teacher education program they completed to add the CTE license. Twenty six academic teachers added a CTE license through a modified licensure program at Kent State University over a two year period from 2008-2010. The primary goal of the licensure program was to support the academic teachers in the transition from the academic to the CTE environment. Six data collection sources were used to determine the effectiveness of the program. A profile of the academic teacher was also identified. The results indicate that the academic teachers were successful and satisfied as they made the transition. The teachers also felt least competent in specific CTE competencies such as collaborating with employer/job sites, working with advisory boards and planning work-based learning instructional activities. Suggestions to assist the teachers were provided.

Published
2012

44. Comparative Effectiveness of Adaptive Treatment Strategies

Author

Neugebauer, Romain S., Schmittdiel, Julie A., O’Connor, Patrick J., van der Laan, Mark J., Bickel, Peter, Series Editor, Diggle, Peter, Series Editor, Fienberg, Stephen E., Series Editor, Gather, Ursula, Series Editor, Zeger, Scott, Series Editor, van der Laan, Mark J., and Rose, Sherri

Published
2018
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45. How School Counselors Make a World of Difference

Author

O'Connor, Patrick J.

Abstract

School counselors play a key role in promoting students' academic achievement, social and emotional development, and college and career readiness. The author reviews the research on counselors' work in these areas and discusses how schools can ensure that their counselors are better able to succeed in supporting students.

Published
2018
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48. The development and initial feasibility testing of D-HOMES: a behavioral activation-based intervention for diabetes medication adherence and psychological wellness among people experiencing homelessness

Author

Vickery, Katherine Diaz, primary, Ford, Becky R., additional, Gelberg, Lillian, additional, Bonilla, Zobeida, additional, Strother, Ella, additional, Gust, Susan, additional, Adair, Edward, additional, Montori, Victor M., additional, Linzer, Mark, additional, Evans, Michael D., additional, Connett, John, additional, Heisler, Michele, additional, O'Connor, Patrick J., additional, and Busch, Andrew M., additional

Published
2023
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