Garrick Olson

All Publications

• Development and validation of the Collaborative Health Outcomes Information Registry body map. Pain reports Scherrer, K. H., Ziadni, M. S., Kong, J., Sturgeon, J. A., Salmasi, V., Hong, J., Cramer, E., Chen, A. L., Pacht, T., Olson, G., Darnall, B. D., Kao, M., Mackey, S. 2021; 6 (1): e880

  Abstract

  Introduction: Critical for the diagnosis and treatment of chronic pain is the anatomical distribution of pain. Several body maps allow patients to indicate pain areas on paper; however, each has its limitations.Objectives: To provide a comprehensive body map that can be universally applied across pain conditions, we developed the electronic Collaborative Health Outcomes Information Registry (CHOIR) self-report body map by performing an environmental scan and assessing existing body maps.Methods: After initial validation using a Delphi technique, we compared (1) pain location questionnaire responses of 530 participants with chronic pain with (2) their pain endorsements on the CHOIR body map (CBM) graphic. A subset of participants (n = 278) repeated the survey 1 week later to assess test-retest reliability. Finally, we interviewed a patient cohort from a tertiary pain management clinic (n = 28) to identify reasons for endorsement discordances.Results: The intraclass correlation coefficient between the total number of body areas endorsed on the survey and those from the body map was 0.86 and improved to 0.93 at follow-up. The intraclass correlation coefficient of the 2 body map graphics separated by 1 week was 0.93. Further examination demonstrated high consistency between the questionnaire and CBM graphic (<10% discordance) in most body areas except for the back and shoulders (15-19% discordance). Participants attributed inconsistencies to misinterpretation of body regions and laterality, the latter of which was addressed by modifying the instructions.Conclusions: Our data suggest that the CBM is a valid and reliable instrument for assessing the distribution of pain.

  View details for DOI 10.1097/PR9.0000000000000880

  View details for PubMedID 33490848

• Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. The New England journal of medicine Perez, M. V., Mahaffey, K. W., Hedlin, H., Rumsfeld, J. S., Garcia, A., Ferris, T., Balasubramanian, V., Russo, A. M., Rajmane, A., Cheung, L., Hung, G., Lee, J., Kowey, P., Talati, N., Nag, D., Gummidipundi, S. E., Beatty, A., Hills, M. T., Desai, S., Granger, C. B., Desai, M., Turakhia, M. P., Apple Heart Study Investigators, Perez, M. V., Turakhia, M. P., Lhamo, K., Smith, S., Berdichesky, M., Sharma, B., Mahaffey, K., Parizo, J., Olivier, C., Nguyen, M., Tallapalli, S., Kaur, R., Gardner, R., Hung, G., Mitchell, D., Olson, G., Datta, S., Gerenrot, D., Wang, X., McCoy, P., Satpathy, B., Jacobsen, H., Makovey, D., Martin, A., Perino, A., O'Brien, C., Gupta, A., Toruno, C., Waydo, S., Brouse, C., Dorfman, D., Stein, J., Huang, J., Patel, M., Fleischer, S., Doll, E., O'Reilly, M., Dedoshka, K., Chou, M., Daniel, H., Crowley, M., Martin, C., Kirby, T., Brumand, M., McCrystale, K., Haggerty, M., Newberger, J., Keen, D., Antall, P., Holbrook, K., Braly, A., Noone, G., Leathers, B., Montrose, A., Kosowsky, J., Lewis, D., Finkelmeier, J. R., Bemis, K., Mahaffey, K. W., Desai, M., Talati, N., Nag, D., Rajmane, A., Desai, S., Caldbeck, D., Cheung, L., Granger, C., Rumsfeld, J., Kowey, P. R., Hills, M. T., Russo, A., Rockhold, F., Albert, C., Alonso, A., Wruck, L., Friday, K., Wheeler, M., Brodt, C., Park, S., Rogers, A., Jones, R., Ouyang, D., Chang, L., Yen, A., Dong, J., Mamic, P., Cheng, P., Shah, R., Lorvidhaya, P. 2019; 381 (20): 1909–17

  Abstract

  BACKGROUND: Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.METHODS: Participants without atrial fibrillation (as reported by the participants themselves) used a smartphone (Apple iPhone) app to consent to monitoring. If a smartwatch-based irregular pulse notification algorithm identified possible atrial fibrillation, a telemedicine visit was initiated and an electrocardiography (ECG) patch was mailed to the participant, to be worn for up to 7 days. Surveys were administered 90 days after notification of the irregular pulse and at the end of the study. The main objectives were to estimate the proportion of notified participants with atrial fibrillation shown on an ECG patch and the positive predictive value of irregular pulse intervals with a targeted confidence interval width of 0.10.RESULTS: We recruited 419,297 participants over 8 months. Over a median of 117 days of monitoring, 2161 participants (0.52%) received notifications of irregular pulse. Among the 450 participants who returned ECG patches containing data that could be analyzed - which had been applied, on average, 13 days after notification - atrial fibrillation was present in 34% (97.5% confidence interval [CI], 29 to 39) overall and in 35% (97.5% CI, 27 to 43) of participants 65 years of age or older. Among participants who were notified of an irregular pulse, the positive predictive value was 0.84 (95% CI, 0.76 to 0.92) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular pulse notification and 0.71 (97.5% CI, 0.69 to 0.74) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular tachogram. Of 1376 notified participants who returned a 90-day survey, 57% contacted health care providers outside the study. There were no reports of serious app-related adverse events.CONCLUSIONS: The probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation. This siteless (no on-site visits were required for the participants), pragmatic study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices. (Funded by Apple; Apple Heart Study ClinicalTrials.gov number, NCT03335800.).

  View details for DOI 10.1056/NEJMoa1901183

  View details for PubMedID 31722151