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Voyce, Stephen

https://orcid.org/0000-0002-2646-2129

Mayo Clinic

Geisinger Health System

Citations 3

Establishing a National Cardiovascular Disease Surveillance System in the United States Using Electronic Health Record Data: Key Strengths and Limitations
Williams, Brent A. , Voyce, Stephen , Sidney, Stephen , Roger, Véronique L. , Plante, Timothy B. , Larson, Sharon , LaMonte, Michael J. , Labarthe, Darwin R. , DeBarmore, Bailey M. , Chang, Alex R. , Chamberlain, Alanna M. , Benziger, Catherine P. , Chamberlain, Alanna M , Benziger, Catherine P , Chang, Alexander R

Journal of the American Heart Association | April 12, 2022 | Volume: 11 | Issue: 8 | Pages: No page available

10.1161/jaha.121.024409 Get It

Cardiovascular disease surveillance involves quantifying the evolving population‐level burden of cardiovascular outcomes and risk factors as a data‐driven initial step followed by the implementation of interventional strategies designed to alleviate this burden in the target population. Despite widespread acknowledgement of its potential value, a national surveillance system dedicated specifically to cardiovascular disease does not currently exist in the United States. Routinely collected health care data such as from electronic health records (EHRs) are a possible means of achieving national surveillance. Accordingly, this article elaborates on some key strengths and limitations of using EHR data for establishing a national cardiovascular disease surveillance system. Key strengths discussed include the: (1) ubiquity of EHRs and consequent ability to create a more “national” surveillance system, (2) existence of a common data infrastructure underlying the health care enterprise with respect to data domains and the nomenclature by which these data are expressed, (3) longitudinal length and detail that define EHR data when individuals repeatedly patronize a health care organization, and (4) breadth of outcomes capable of being surveilled with EHRs. Key limitations discussed include the: (1) incomplete ascertainment of health information related to health care–seeking behavior and the disconnect of health care data generated at separate health care organizations, (2) suspect data quality resulting from the default information‐gathering processes within the clinical enterprise, (3) questionable ability to surveil patients through EHRs in the absence of documented interactions, and (4) the challenge in interpreting temporal trends in health metrics, which can be obscured by changing clinical and administrative processes.
Trends in Atrial Fibrillation Incidence Rates Within an Integrated Health Care Delivery System, 2006 to 2018
Williams, Brent A. , Chamberlain, Alanna M. , Blankenship, James C. , Voyce, Stephen , Chamberlain, Alanna M , Hylek, Elaine M.

JAMA Network Open | August 31, 2020 | Volume: 3 | Issue: 8 | Pages: e2014874

10.1001/jamanetworkopen.2020.14874 Get It

Factors Associated With Large Improvements in Health-Related Quality of Life in Patients With Atrial Fibrillation
Holmes, DaJuanicia N. , Pieper, Karen S. , Ezekowitz, Michael D. , Fonarow, Gregg C. , Gersh, Bernard J. , Kowey, Peter R. , Mahaffey, Kenneth W. , Reiffel, James A. , Singer, Daniel E. , Piccini, Jonathan P. , Mendelson, R. A., NEUTEL, J, Pan, Dengji, Poock, James J., Raffetto, J.D., Greengold, R., Roan, P G, Saba, F., Sackett, Melanie K., Schneider, R., Seymour, Zachary , Shanes, Jeffrey G., Smiley, Nasser, Smith, David H. , Snipes, C., Sotolongo, Rodolfo, Staniloae, Cezar , Stoltz, S., Suresh, D.P. , Tak, Tahir , Tannenbaum, A., Turk, Samir, Vora, Kishor, Randhawa, P., Zebrack, James S., Silva, Eduardo , Riley, Edward T., Weinstein, D., Vasiliauskas, Tomas, Goldbarg, Seth , Yarlagadda, Chakri, Laurion, D., Osunkoya, A., Burns, Richéal , Castor, Tatsiana , Luttman, C., Anton, Stephen D. , McGarvey, Jeremy R., Guthrie, Robert D., Deriso, George T., Flood, Raymond, Fleischer, L H, Fierstein, J.S., Jacobs, George B., Adjei, Nasser, Akyea-Djamson, Ayim, Bacon, Jenny , Bedwell, Noel W., Berger, PB, Berry, Joni I., Bhagwat, Ravi, Boccalandro, Fernando , Capó, Jaïr Dilmé, Kapadia, Sumit, Casanova, Rene, Morriss, J.E., Elsen, J., Farsad, Ramin, Fox, David J. , Frandsen, Brad, Gelernt, M., Hall, Cassandra L. , Hotchkiss, David R. , Ip, J., Jaffrani, Naseem, Kazmierski, John F., Waxman, F., Kneller, G. Larsen, Labroo, Ajay, Jaffe, Bernard M., Lebenthal, Mark, Lillestol, Michael, Leclerc, Kenneth M. , Maccaro, Paul, Mayer, Nolan, Kozłowski, J , Benjamin, Sanford P., Detweiler, Robert, Igic, Petar, Jackson, Tatum, Pappas, Janine, Littlefield, Ryan , Frey, Anna , Vranian, Robert B., Long, W., Grena, Paul, Arouni, Amy , Quinn, John , Blonder, Ronald, Snyder, H., Slabic, S., Cohen, Kenneth D., Walthall, W. W., Snoddy, Brian, Alvarado, Olga Franco, Leach, Corinne L., Rothman, Steven A., Olatidoye, Abiodun G, Almahameed, Soufian , Rosenthal, Shelly, Reiter, William M., Thompson, T., Thew, Stephen, Kobayashi, Junji , Williams, M., Kramer, Joel H. , Latif, Sidrah , Rhee, B., Ruiz-Serrano, D., Stringam, Stanley, Wolok, K., Focil, Augusto, Butman, Samuel, Ingersoll, Henry, Borge, R. P., Al-Saghir, Y., Farris, Neil, Shore, Karen, Gornick, C., Eilat, P., Paliwal, Y., Mitra, Rito , Jingo, Ahmad, Aslam, Asma , Watson, Robert, Voyce, Stephen , Turakhia, Mintu P. , Goytia-Leos, D., Lurie, Miriam, Mallis, G., Strobel, John, Fisher, D M, Atieh, Mutaz I., Drabick, Andrew, Harman, Ece, Ashcraft, B., Krista, M., Videlefsky, A., Zayas, E. Rivera, Tan, A.E., Gersh, Bernard J , Turakhia, Mintu P , Steinberg, Benjamin A. , Allen, Larry A. , Chan, Paul S. , Freeman, James V. , Hylek, Elaine M. , Naccarelli, Gerald V. , Peterson, Eric D. , Mendelson, R., AL-NAHHAS, ADIL M. , Padanilam, B., Pan, D., Raffetto, J., Roan, P., Sackett, M., Seymour, Z., Shoemaker, J. Kevin , Simms, V., Tak, T., Riley, E., Weinstein, D., Hayward, D., Burns, R., Spiller, D., McGarvey, J., Guthrie, R., Flood, R., Aggarwal, R., Jacobs, G., Alfieri, A., Bacon, J., Berger, P., Berry, J., Bloom, S., Kapadia, S., Casanova, R., Christensen, T., Fox, D., Gill, S., Grubb, Søren , Hall, C., Harris, H., Hotchkiss, D., Jones, A., Lee, David S. , Kozlowski, J., Benjamin, S., Detweiler, R., Jackson, T., Littlefield, R., Long, W., Quinn, J., Browne, Kevin D. , Forman, Steven L. , Ebinger, Martin , Williams, David Michael , Stein, R., Kirkland, S., Cohen, K., Walthall, W., Davis, Keith L. , Alvarado, O., Leach, C., Sharma, Anand , Sutter, G., Reiter, W., Kobayashi, J., Kramer, J., Latif, S.A., Adler, Alma J , Butman, Samuel M. , Coats, Paul , Shore, K., Schwartz, M.B., Quinlan, E., Mitra, R., Aslam, A.A., Lurie, M., Atwater, Brett D. , Murray, John M. , Fisher, D., Landes, Reid D. , Harman, E., Zayas, E. Rivera

Circulation: Arrhythmia and Electrophysiology | April 16, 2020 | Volume: 13 | Issue: 5 | Pages: No page available

10.1161/circep.119.007775 Get It

Background: Atrial fibrillation (AF) adversely impacts health-related quality of life (hrQoL). While some patients demonstrate improvements in hrQoL, the factors associated with large improvements in hrQoL are not well described. Methods: We assessed factors associated with a 1-year increase in the Atrial Fibrillation Effect on Quality-of-Life score of 1 SD (≥18 points; 3× clinically important difference), among outpatients in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation I registry. Results: Overall, 28% (181/636) of patients had such a hrQoL improvement. Compared with patients not showing large hrQoL improvement, they were of similar age (median 73 versus 74, P =0.3), equally likely to be female (44% versus 48%, P =0.3), but more likely to have newly diagnosed AF at baseline (18% versus 8%; P =0.0004), prior antiarrhythmic drug use (52% versus 40%, P =0.005), baseline antiarrhythmic drug use (34.8% versus 26.8%, P =0.045), and more likely to undergo AF-related procedures during follow-up (AF ablation: 6.6% versus 2.0%, P =0.003; cardioversion: 12.2% versus 5.9%, P =0.008). In multivariable analysis, a history of alcohol abuse (adjusted OR, 2.41; P =0.01) and increased baseline diastolic blood pressure (adjusted OR, 1.23 per 10-point increase and >65 mm Hg; P =0.04) were associated with large improvements in hrQoL at 1 year, whereas patients with prior stroke/transient ischemic attack, chronic obstructive pulmonary disease, and peripheral arterial disease were less likely to improve ( P <0.05 for each). Conclusions: In this national registry of patients with AF, potentially treatable AF risk factors are associated with large hrQoL improvement, whereas less reversible conditions appeared negatively associated with hrQoL improvement. Understanding which patients are most likely to have large hrQoL improvement may facilitate targeting interventions for high-value care that optimizes patient-reported outcomes in AF. Registration: URL: http://www.clinicaltrials.gov . Unique identifier: NCT01165710.