Asch, Steven M.

The quality of health care delivered to adults in the United States

McGlynn, E. A., Asch, S. M., Adams, J., Keesey, J., Hicks, J., DeCristofaro, A., & Kerr, E. A. (2003) · New England Journal of Medicine

Primary Care and Health OutcomesHealthcare Quality and Management

Cited by 5,079

Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations

Chen, J. H., & Asch, S. M. (2017) · New England Journal of Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 1,171

Risk of hepatocellular cancer in patients with non-alcoholic fatty liver disease

Kanwal, F., Kramer, J. R., Mapakshi, S., Natarajan, Y., Chayanupatkul, M., Richardson, P. A., Li, L., Desiderio, R., Thrift, A. P., Asch, S. M., et al. (2018) · Gastroenterology

Liver Disease Diagnosis and TreatmentHepatocellular Carcinoma Treatment and Prognosis

Cited by 795

Development and initial validation of the PEG, a three-item scale assessing pain intensity and interference

Krebs, E. E., Lorenz, K. A., Bair, M. J., Damush, T. M., Wu, J., Sutherland, J. M., Asch, S. M., & Kroenke, K. (2009) · Journal of General Internal Medicine

Pain Management and Opioid UseMusculoskeletal pain and rehabilitation

Cited by 782

The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis

Nuckols, T. K., Smith-Spangler, C., Morton, S. C., Asch, S. M., Patel, V. M., Anderson, L. J., Deichsel, E. L., & Shekelle, P. G. (2014) · Systematic Reviews

Electronic Health Records SystemsPatient Safety and Medication Errors

Cited by 340

Effect of metabolic traits on the risk of cirrhosis and hepatocellular cancer in nonalcoholic fatty liver disease

Kanwal, F., Kramer, J. R., Li, L., Dai, J., Natarajan, Y., Yu, X., Asch, S. M., & El‐Serag, H. B. (2020) · Hepatology

Liver Disease Diagnosis and TreatmentAlcohol Consumption and Health Effects

Cited by 319

Practices to foster physician presence and connection with patients in the clinical encounter

Zulman, D. M., Haverfield, M. C., Shaw, J. G., Brown-Johnson, C. G., Schwartz, R., Tierney, A. A., Zionts, D. L., Safaeinili, N., Fischer, M., Thadaney Israni, S., et al. (2020) · JAMA

Patient-Provider Communication in HealthcareEmpathy and Medical Education

Cited by 287

Effectiveness of Collaborative Care for Depression in Human Immunodeficiency Virus Clinics

Pyne, J. M., Fortney, J. C., Curran, G. M., Tripathi, S., Atkinson, J. H., Kilbourne, A. M., Hagedorn, H. J., Rimland, D., Rodriguez-Barradas, M. C., Monson, T., et al. (2010) · Archives of Internal Medicine

HIV/AIDS Research and InterventionsMental Health Treatment and Access

Cited by 132

Integrated care increases treatment and improves outcomes of patients with chronic hepatitis C virus infection and psychiatric illness or substance abuse

Ho, S. B., Bräu, N., Cheung, R., Liu, L., Sanchez, C., Sklar, M., Phelps, T. E., Marcus, S. G., Wasil, M. M., Tisi, A., et al. (2015) · Clinical Gastroenterology and Hepatology

Hepatitis C virus researchMental Health Treatment and Access

Cited by 118

Human Factors Barriers to the Effective Use of Ten HIV Clinical Reminders

Patterson, E. S., Nguyen, A. D., Halloran, J. P., & Asch, S. M. (2004) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsClinical practice guidelines implementation

Cited by 115

Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets

Chen, J. H., Alagappan, M., Goldstein, M. K., Asch, S. M., & Altman, R. B. (2017) · International Journal of Medical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 101

Measuring persistence of implementation: QUERI Series

Initiative, T. H. Q. E. R., Bowman, C. C., Sobo, E. J., Asch, S. M., & Gifford, A. L. (2008) · Implementation Science

Health Policy Implementation ScienceHealthcare Quality and Management

Cited by 100

Effectiveness of an Artificial Intelligence–Enabled Intervention for Detecting Clinical Deterioration

Gallo, R. J., Shieh, L., Smith, M., Marafino, B. J., Geldsetzer, P., Asch, S. M., Shum, K., Lin, S., Westphal, J., Hong, G., et al. (2024) · JAMA Internal Medicine

Healthcare Technology and Patient MonitoringMachine Learning in Healthcare

Cited by 58

Finding order in heterogeneity: types of quality-improvement intervention publications

Rubenstein, L. V., Hempel, S., Farmer, M. M., Asch, S. M., Yano, E. M., Dougherty, D., & Shekelle, P. W. (2008) · Quality and Safety in Health Care

Health Policy Implementation ScienceHealthcare Quality and Management

Cited by 52

AI and biosecurity: The need for governance

Bloomfield, D., Pannu, J., Zhu, A. W., Ng, M. Y., Lewis, A., Bendavid, E., Asch, S. M., Hernandez-Boussard, T., Cicero, A., & Inglesby, T. (2024) · Science

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 50

Partnered Research in Healthcare Delivery Redesign for High-Need, High-Cost Patients: Development and Feasibility of an Intensive Management Patient-Aligned Care Team (ImPACT)

Zulman, D. M., Ezeji-Okoye, S. C., Shaw, J. G., Hummel, D. L., Holloway, K. S., Smither, S. F., Breland, J. Y., Chardos, J. F., Kirsh, S., Kahn, J. S., et al. (2014) · Journal of General Internal Medicine

Chronic Disease Management StrategiesHealthcare Policy and Management

Cited by 35

Patient and provider perspectives on the development of personalized medicine: a mixed-methods approach

Puryear, L., Downs, N., Nevedal, A., Lewis, E. T., Ormond, K. E., Bregendahl, M., Suarez, C. J., David, S. P., Charlap, S., Chu, I., et al. (2018) · Journal of Community Genetics

Genomics and Rare DiseasesPatient-Provider Communication in Healthcare

Cited by 31

Physician- and Patient-Elicited Barriers and Facilitators to Implementation of a Machine Learning–Based Screening Tool for Peripheral Arterial Disease: Preimplementation Study With Physician and Patient Stakeholders

Ho, V., Brown Johnson, C., Ghanzouri, I., Amal, S., Asch, S., & Ross, E. (2023) · JMIR Cardio

Health Policy Implementation ScienceArtificial Intelligence in Healthcare and Education

Cited by 28

Cost of rapid HIV testing at 45 U.S. hospitals

Pinkerton, S. D., Bogart, L. M., Howerton, D., Snyder, S., Becker, K., & Asch, S. M. (2010) · AIDS Patient Care and STDs

HIV/AIDS Research and InterventionsHealth Systems, Economic Evaluations, Quality of Life

Cited by 26

The hepatitis C self‐management programme: a randomized controlled trial

Groessl, E. J., Weingart, K. R., Stepnowsky, C. J., Gifford, A. L., Asch, S. M., & Ho, S. B. (2011) · Journal of Viral Hepatitis

Hepatitis C virus researchDiabetes Management and Education

Cited by 25

Enhancing Organizational Change and Improvement Prospects: Lessons from an HIV Testing Intervention for Veterans

Sobo, E. J., Bowman, C., Aarons, G. A., Asch, S., & Gifford, A. L. (2008) · Human Organization

Health Policy Implementation ScienceOrganizational Change and Leadership

Cited by 20

Development of the Hepatitis C Self-Management Program

Groessl, E. J., Weingart, K. R., Gifford, A. L., Asch, S. M., & Ho, S. B. (2011) · Patient Education and Counseling

Hepatitis C virus researchMedication Adherence and Compliance

Cited by 14

Predictive Validity of a Quality Measure for Intensive Substance use Disorder Treatment

Schmidt, E. M., Gupta, S., Bowe, T., Ellerbe, L. S., Phelps, T. E., Finney, J. W., Asch, S. M., Humphreys, K., Trafton, J., Vanneman, M., et al. (2017) · Substance Abuse

Substance Abuse Treatment and OutcomesOpioid Use Disorder Treatment

Cited by 12

Improving postsurgical fall detection for older Americans using LLM-driven analysis of clinical narratives

Pillai, M., Blumke, T. L., Studnia, J., Wang, Y., Veigulis, Z. P., Ware, A. D., Hoover, P. J., Carroll, I. R., Humphreys, K., Osborne, T. F., et al. (2024) · medRxiv

Machine Learning in HealthcareBalance, Gait, and Falls Prevention

Cited by 4