Peer-reviewed publications
  1. Merchant et al. 2018. Impact of a digital health intervention on asthma resource utilization. World Allergy Organization Journal. (Link)
  2. Williams et al. 2018. Short-term impact of PM2.5 on contemporaneous asthma medication use: Behavior and the value of pollution reductions. Proceedings of the National Academy of Sciences. (Link)
  3. Szefler et al. 2018. Quantifying beta agonist utilization: occasions or puffs?. The Journal of Allergy and Clinical Immunology: In Practice. (Link)
  4. Merchant et al. 2018. Digital Health Intervention for Asthma: Patient-Reported Value and Usability. JMIR Mhealth Uhealth.6(6):e133 (Link)
  5. Barrett MA et al. 2018. AIR Louisville: Addressing Asthma With Technology, Crowdsourcing, Cross-Sector Collaboration, And Policy. Health Affairs. Vol. 37, No. 4, pp. 525-534_ (Link)
  6. Van Sickle and Barrett 2018. Transforming Global Public Health Using Connected Medicines. Respiratory Drug Delivery. Volume 1: 61-70. (Link)
  7. Hoch et al. 2018. Feasibility of medication monitoring sensors in high risk asthmatic children. Journal of Asthma. 1-3. (Link)
  8. Magzamen et al. 2018. Association of ambient pollution with inhaler use among patients with COPD: a panel study. Occup Environ Med. 75.5:382-388. (Link)
  9. Barrett et al. 2017. Impact of a mobile health, sensor-driven asthma management platform on asthma symptoms, control and self-management. Annals of Asthma, Allergy and Immunology. 119.5: 415-421. (Link) (PDF)
  10. Sumino et al. 2017. Use of a Remote Inhaler Monitoring Device to Measure Change in Inhaler Use with Chronic Obstructive Pulmonary Disease Exacerbations. In press at J of Aerosol Medicine and Pulmonary Drug Delivery. (Link) (PDF)
  11. Adams et al. 2017. Automated Adherence Feedback for High Risk Children with Asthma: Research Protocol. JMIR. (Link)
  12. Son et al. 2017. Correlated gamma-based hidden Markov model for smart asthma management based on rescue inhaler usage. Statistics in Medicine 36 (10), 1619-1637. (Link)
  13. Su et al. 2017. Feasibility of deploying a mobile health tool to identify the impacts of environmental triggers and built environmental factors on asthma short-acting bronchodilator use. Environmental Health Perspectives. (Link) (PDF)
  14. Merchant et al. 2016. Effectiveness of Population Health Management Using the Propeller Health Asthma Platform: A Randomized Clinical Trial. Journal of Allergy and Clinical Immunology: In Practice. (Link) (PDF)
  15. Fan et al. 2016. Overuse of short-acting beta-agonist bronchodilators in COPD during periods of clinical stability. Respiratory Medicine. (Link) (PDF)
  16. Kim et al. 2016. Using Connected Devices to Monitor Inhaler Use in the Real World. Respiratory Drug Delivery 1: 37-44. (Link) (PDF)
  17. Van Sickle et al. 2013. Monitoring and Improving Compliance and Asthma Control: Mapping Inhaler Use for Feedback to Patients, Physicians and Payers. Respiratory Drug Delivery Europe. (Link) (PDF)
  18. Van Sickle et al. 2013. Remote Monitoring of Inhaled Bronchodilator Use and Weekly Feedback about Asthma Management: An Open-Group, Short-Term Pilot Study of the Impact on Asthma Control. PLoS ONE. (Link) (PDF)
Non peer-reviewed publications
  1. Henderson et al. 2015. Citizen Health Scientists For Chronic Disease: From Disease Management in Isolation to the Power of the Community in Louisville and Beyond. Sustain 33. (PDF)
  2. Van Sickle et al. 2014. Leveraging digital health technology: Five ways to address barriers to inhaled medication adherence. Inhalation. (PDF)
Peer-reviewed abstracts
  1. Anderson et al. 2018. Frequency of improper inhaler technique identified by electronic medication monitor (EMM) actuation timing. Annals of Allergy, Asthma & Immunology. 121.5: S7-S8. (Link)
  2. Hoch et al. 2018. Benefit of smartphone alerts to improve adherence to inhaled asthma controllers. Annals of Allergy, Asthma & Immunology. 121.5: S40. (Link)
  3. Anderson et al. 2018. Asthma control evaluated with electronic medication monitor (EMM)-defined occasions of short-acting beta-agonist inhaler use. Annals of Allergy, Asthma & Immunology. 121.5: S40. (Link)
  4. Hoch et al. 2018. Comparing objective inhaler use among COPD and Asthma populations. European Respiratory Journal. 52: PA2272. (Link)
  5. Anderson et al. 2018. Association Between Objective Short-Acting Beta-Agonist Use and Self-Reported Asthma Control Test Scores Among Adults with Asthma. American Journal of Respiratory and Critical Care Medicine 2018;197:A4834(Link)
  6. Hoch et al. 2018. Using Digital Technology to Identify Adherence Phenotypes May Identify Appropriate Time for Intervention. American Journal of Respiratory and Critical Care Medicine 2018;197:A4855 (Link)
  7. Alshabani et al. 2018. Trends in Long-Acting Bronchodilator Adherence During Electronic Inhaler Monitoring. American Journal of Respiratory and Critical Care Medicine 2018;197:A4558 (Link)
  8. Alshabani et al. 2018. Reduction in COPD Related Healthcare Utilization with Use of Electronic Inhaler Monitoring. American Journal of Respiratory and Critical Care Medicine 2018;197:A4560 (Link)
  9. Carl et al. 2018. Use of Remote Electronic Monitoring Improves Asthma Outcomes Through Improved Adherence. American Journal of Respiratory and Critical Care Medicine 2018;197:A1164 (Link)
  10. Henderson et al. Evaluation of the impact of a digital health platform on perceptions of asthma self-management. Society for Behavioral Medicine Annual Meeting, New Orleans, LA.
  11. Ramirez E et al. 2018. Public/Private Partnerships for Public Health: Lessons from the Santa Monica Wellbeing Project and AIR Louisville. Society for Behavioral Medicine Annual Meeting, New Orleans, LA.
  12. Anderson et al. 2018. Real-Life Patterns of Short-Acting Beta-Agonist Use in Persistent Asthmatics Vary by Age, Time of Day, and Season. Journal of Allergy and Clinical Immunology. Volume 141, Issue 2, Supplement, February 2018, Page AB61. (Link)
  13. Kaye et al. 2018. Real-Life Patterns of Asthma Controller Use Vary by Age, Time of Day and Season.
    JJournal of Allergy and Clinical Immunology. Volume 141, Issue 2, Supplement, February 2018, Page AB61 (Link)
  14. Su et al. 2017. Leveraging wireless inhaler sensors to estimate the impact of rising temperatures and pollutant levels on asthma symptoms. American Public Health Association Annual Meeting, Atlanta, GA.(Link)
  15. Pepper et al. 2017. Evaluating asthma short-acting beta agonist use and outdoor air pollution: a geospatial-temporal analysis leveraging digital health technology. American Public Health Association Annual Meeting, Atlanta, GA. (Link)
  16. Hoch et al. 2017. Assessing the utility of asthma medication monitoring sensors in a group of high risk asthmatic children. European Respiratory Society Annual Meeting, Milan, Italy.
  17. Merchant et al. 2017. Impact of A Digital Health Intervention On Asthma Healthcare Utilization. European Respiratory Society Annual Meeting, Milan, Italy.
  18. Chen et al. Feasibility and clinical impact of deploying a digital health intervention in a Medicare population with COPD. European Respiratory Society Annual Meeting, Milan, Italy.
  19. Szefler et al. 2017. Daily pattern of ß2 -agonists: Understanding real-life use of rescue medication in asthma. European Respiratory Society Annual Meeting, Milan, Italy.
  20. Chen et al. 2017. Feasibility and clinical impact of deploying a digital health intervention on a Medicare population with asthma or COPD. American Journal of Respiratory and Critical Care Medicine 2017;195:A1722 (Link)
  21. Merchant et al. 2017. Digital health intervention for asthma: patient perception of usability and value for self-management. American Journal of Respiratory and Critical Care Medicine 2017;195:A3326 (Link)
  22. Merchant RK, Inamdar R, Tuffli M, Barrett M, Hogg C, Van Sickle D. 2017. Interim Results Of The Impact Of A Digital Health Intervention On Asthma Healthcare Utilization. Journal of Allergy and Clinical Immunology: 139: 2. (Link)
  23. Hoch et al. 2017. A Feasibility Study of Daily Monitoring of Controller and Rescue Medication Use in a Pediatric Patient Population at High Risk of an Asthma Exacerbation. American Journal of Respiratory and Critical Care Medicine 2017;195:A2198. (Link)
  24. Chen et al. 2017. Feasibility and clinical impact of deploying a digital health intervention on a Medicare population with asthma or COPD. American Journal of Respiratory and Critical Care Medicine 2017; 195:A1722. (Link)
  25. Merchant et al. 2017. Interim results of the impact of a digital health intervention on asthma healthcare utilization. American Journal of Respiratory and Critical Care Medicine 2017; 195:
  26. Merchant RK, Inamdar R, Henderson K, Barrett M, Van Sickle D. 2016. Patient reported value and usability of a digital health intervention for asthma. Journal of Medical Internet Research. iproc 2016;2(1):e36 DOI: 10.2196/iproc.6242 (Link)
  27. Su, et al. 2016. Application of wireless inhaler sensors to enhance asthma surveillance and inform municipal interventions. American Public Health Association Annual Meeting. Denver, CO. (Link)
  28. Van Sickle D, Humblet O, Barrett M, Henderson K, and Hogg C. 2016. Randomized, controlled study of the impact of a mobile health tool on asthma SABA use, control and adherence. European Respiratory Journal:48: PA1018. (Link)
  29. Smith et al. 2016. Improving the burden of respiratory disease through data-driven innovation: the AIR Louisville program in Jefferson County, Kentucky. Am J Respir Crit Care Med 193;2016:A1750 (Link), (PDF)
  30. Su et al. 2016. Identifying Environmental Drivers of Asthma Hotspots using Real-Time Inhaler Sensors. Annual Conference of the National Association of Chronic Disease Directors and Centers for Disease Control and Prevention. (conference link, abstract to be posted)
  31. Su et al. 2016. Identification of asthma short-acting bronchodilator use in space and time using mobile health tools. Association of American Geographers Annual Conference. (Link)
  32. Van Sickle et al. 2016. Impact of a Mobile Health and Sensor-Driven Asthma Management Pilot Study on Symptoms, Control, and Self-Management. Journal of Allergy and Clinical Immunology: 137, Issue 2, Supplement, Page AB9 (Link)
  33. Van Sickle et al. 2015. Impact of a mobile health pilot study on asthma rescue inhaler use, control and self-management. Eur Respir J 46 (suppl 59). (Link)
  34. Sumino et al. 2015. Use Of A Remote Inhaler Monitor Device To Measure Change In Inhaler Use With COPD Exacerbations. ATS. (Link)
  35. Van Sickle et al. 2015. Recent Advances in Digital Health Tools for Asthma and COPD Management in Underserved Populations. American Thoracic Society Meeting, Denver, CO.
  36. Barrett et al. 2015. Identifying environmental drivers of asthma hotspots in Louisville, Kentucky, using sensors to capture spatially-explicit, real-time data on inhaler use: AIR Louisville program. American Public Health Association Annual Meeting. Chicago, IL. (Link)
  37. Merchant et al. 2014. Interim Results From A Randomized, Controlled Trial Of Remote Monitoring Of Inhaled Bronchodilator Use On Asthma Control, Symptoms And Management. American Journal of Respiratory and Critical Care Medicine: A1386-A1386 (Link)
  38. Smith et al. 2014. Technology-driven asthma data program to inform regional policy: The municipal perspective. American Public Health Association Annual Meeting. New Orleans, LA. (Link)
  39. Van Sickle, et al. 2014. Impact of a technology-driven asthma program on symptoms, control and self-management: The clinical perspective. American Public Health Association Annual Meeting. New Orleans, LA. (Link)
  40. Barrett et al. 2014. Exploring drivers of asthma in Louisville with spatially-explicit, real-time data: The environmental perspective. American Public Health Association Annual Meeting. New Orleans, LA. (Link)
  41. Nesbitt, L. 2014. Technology-driven asthma data can support surveillance efforts: The public health perspective. American Public Health Association Annual Meeting. New Orleans, LA. (Link)
  42. Merchant R, et al. 2013. Interim Results From a Randomized, Controlled Trial of Remote Monitoring of Inhaled Bronchodilator Use on Asthma Control and Management. CHEST Journal 144.4_MeetingAbstracts (2013): 71A-71A. (Link)
  43. Van Sickle et al. 2013. Louisville asthma data initiative – a municipal digital health program to improve self-management and public health surveillance of asthma. (Link)
  44. Van Sickle and Morrison. 2011. Weekly Feedback Summarizing Use Of Remotely Monitored Rescue Medication Improves Asthma Control C51. Asthma Epidemiology, A4755-A4755 (Link)
  45. Van Sickle et al. 2011. Understanding Socioeconomic and Racial Differences in Adult Lung Function. American Journal of Respiratory and Critical Care Medicine, Vol. 184, No. 5 (2011), pp. 521-527. (Link)
  46. Van Sickle et al. 2010. Online Feedback About Remotely Monitored Inhaled Bronchodilators Improves Composite Measures Of Asthma Control. B47. Asthma Epidemiology: Clinical and pharmacological determinants of asthma outcomes. A3127-A3127 (Link)
  47. Van Sickle. 2009. Development of a Networked Asthma Inhaler To Improve Clinical Management and Public Health Surveillance. Evaluating disease control and quality of life in asthma and COPD, A4065 (Link)