Published on in Vol 20, No 8 (2018): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10458, first published .
Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model

Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model

Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model

Journals

  1. Esdar M, Hüsers J, Weiß J, Rauch J, Hübner U. Diffusion dynamics of electronic health records: A longitudinal observational study comparing data from hospitals in Germany and the United States. International Journal of Medical Informatics 2019;131:103952 View
  2. Kan H, Kharrazi H, Chang H, Bodycombe D, Lemke K, Weiner J, Stiglic G. Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults. PLOS ONE 2019;14(3):e0213258 View
  3. Chen T, Dredze M, Weiner J, Kharrazi H. Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records. Journal of the American Medical Informatics Association 2019;26(8-9):787 View
  4. Hatef E, Rouhizadeh M, Tia I, Lasser E, Hill-Briggs F, Marsteller J, Kharrazi H. Assessing the Availability of Data on Social and Behavioral Determinants in Structured and Unstructured Electronic Health Records: A Retrospective Analysis of a Multilevel Health Care System. JMIR Medical Informatics 2019;7(3):e13802 View
  5. Melnick E, Dyrbye L, Sinsky C, Trockel M, West C, Nedelec L, Tutty M, Shanafelt T. The Association Between Perceived Electronic Health Record Usability and Professional Burnout Among US Physicians. Mayo Clinic Proceedings 2020;95(3):476 View
  6. Brice Y, Joynt Maddox K. Is duration of hospital participation in meaningful use associated with value in Medicare?. JAMIA Open 2019;2(2):238 View
  7. Hatef E, Weiner J, Kharrazi H. A public health perspective on using electronic health records to address social determinants of health: The potential for a national system of local community health records in the United States. International Journal of Medical Informatics 2019;124:86 View
  8. Alexander G, Georgiou A, Siette J, Madsen R, Livingstone A, Westbrook J, Deroche C. Exploring information technology (IT) sophistication in New South Wales residential aged care facilities. Australian Health Review 2020;44(2):288 View
  9. Chen T, Dredze M, Weiner J, Hernandez L, Kimura J, Kharrazi H. Extraction of Geriatric Syndromes From Electronic Health Record Clinical Notes: Assessment of Statistical Natural Language Processing Methods. JMIR Medical Informatics 2019;7(1):e13039 View
  10. Abbasi R, Khajouei R, Mirzaee M. Evaluating the demographic and clinical minimum data sets of Iranian National Electronic Health Record. BMC Health Services Research 2019;19(1) View
  11. Messino P, Kharrazi H, Kim J, Lehmann H. A method for measuring the effect of certified electronic health record technology on childhood immunization status scores among Medicaid managed care network providers. Journal of Biomedical Informatics 2020;110:103567 View
  12. Liang J, Li Y, Zhang Z, Shen D, Xu J, Yu G, Dai S, Ge F, Lei J. Evaluating the Applications of Health Information Technologies in China During the Past 11 Years: Consecutive Survey Data Analysis. JMIR Medical Informatics 2020;8(2):e17006 View
  13. Bery A, Anzaldi L, Boyd C, Leff B, Kharrazi H. Potential value of electronic health records in capturing data on geriatric frailty for population health. Archives of Gerontology and Geriatrics 2020;91:104224 View
  14. Tarabichi Y, Goyden J, Liu R, Lewis S, Sudano J, Kaelber D. A step closer to nationwide electronic health record–based chronic disease surveillance: characterizing asthma prevalence and emergency department utilization from 100 million patient records through a novel multisite collaboration. Journal of the American Medical Informatics Association 2020;27(1):127 View
  15. Park Y, Kim Y, Yi B, Kim S. Clinical Decision Support Functions and Digitalization of Clinical Documents of Electronic Medical Record Systems. Healthcare Informatics Research 2019;25(2):115 View
  16. Kawaguchi H, Koike S, Ohe K. Facility and Regional Factors Associated With the New Adoption of Electronic Medical Records in Japan: Nationwide Longitudinal Observational Study. JMIR Medical Informatics 2019;7(2):e14026 View
  17. Fischer S, Rudin R, Shi Y, Shekelle P, Amill-Rosario A, Scanlon D, Damberg C. Trends in the use of computerized physician order entry by health-system affiliated ambulatory clinics in the United States, 2014–2016. BMC Health Services Research 2020;20(1) View
  18. Savinkina A, Sapiano M, Berger J, Basavaraju S. Is surgical volume still the most accurate indicator of blood usage in the United States?. Transfusion 2019;59(3):1125 View
  19. Hannan E, Barrett S, Samadashvili Z, Schmaltz S. Retooling of Paper-based Outcome Measures to Electronic Format. Medical Care 2019;57(5):377 View
  20. Ma X, Jung C, Chang H, Richards T, Kharrazi H. Assessing the Population-Level Correlation of Medication Regimen Complexity and Adherence Indices Using Electronic Health Records and Insurance Claims. Journal of Managed Care & Specialty Pharmacy 2020;26(7):860 View
  21. Kanakubo T, Kharrazi H. Comparing the Trends of Electronic Health Record Adoption Among Hospitals of the United States and Japan. Journal of Medical Systems 2019;43(7) View
  22. Ke C, Stukel T, Luk A, Shah B, Jha P, Lau E, Ma R, So W, Kong A, Chow E, Chan J. Development and validation of algorithms to classify type 1 and 2 diabetes according to age at diagnosis using electronic health records. BMC Medical Research Methodology 2020;20(1) View
  23. Krasuska M, Williams R, Sheikh A, Franklin B, Heeney C, Lane W, Mozaffar H, Mason K, Eason S, Hinder S, Dunscombe R, Potts H, Cresswell K. Technological Capabilities to Assess Digital Excellence in Hospitals in High Performing Health Care Systems: International eDelphi Exercise. Journal of Medical Internet Research 2020;22(8):e17022 View
  24. Schenk E, Marks N, Hoffman K, Goss L. Four Years Later. JONA: The Journal of Nursing Administration 2021;51(1):43 View
  25. Flynn A, Fortier C, Maehlen H, Pierzinski V, Runnebaum R, Sullivan M, Wagner J, Stevenson J. A strategic approach to improving pharmacy enterprise automation: Development and initial application of the Autonomous Pharmacy Framework. American Journal of Health-System Pharmacy 2021;78(7):636 View
  26. Kharrazi H, Ma X, Chang H, Richards T, Jung C. Comparing the Predictive Effects of Patient Medication Adherence Indices in Electronic Health Record and Claims-Based Risk Stratification Models. Population Health Management 2021 View
  27. Esdar M, Liebe J, Thye J, Babitsch B, Hübner U. The Effect of Health Care Organizations’ Innovation Capabilities on the Quality of Health Information Technology: Development of an Empirical Model (Preprint). JMIR Medical Informatics 2020 View
  28. Liang J, Li Y, Zhang Z, Shen D, Xu J, Zheng X, Wang T, Tang B, Lei J, Zhang J. Adoption of Electronic Health Records (EHRs) in China During the Past 10 Years: Consecutive Survey Data Analysis and Comparison of Sino-American Challenges and Experiences. Journal of Medical Internet Research 2021;23(2):e24813 View
  29. Fitzgerald M, Kaufman M, Massey S, Fridinger S, Prelack M, Ellis C, Ortiz‐Gonzalez X, Fried L, DiGiovine M, Melamed S, Malcolm M, Banwell B, Stephenson D, Witzman S, Gonzalez A, Dlugos D, Kessler S, Goldberg E, Abend N, Helbig I, Fung F, Lewin N, Patel A, Rosen A, Smidt S, Vithayathil J, Tencer J, Bergqvist C, McKee J, O'Connor‐Prange E, Anto M, Cristancho A, Marsh E, Chadehumbe M, Tefft S, Hagopian. S. Assessing seizure burden in pediatric epilepsy using an electronic medical record–based tool through a common data element approach. Epilepsia 2021;62(7):1617 View
  30. Tarabichi Y, Frees A, Honeywell S, Huang C, Naidech A, Moore J, Kaelber D. The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform. ACI Open 2021;05(01):e36 View

Books/Policy Documents

  1. Kharrazi H, Gamache R, Weiner J. Public Health Informatics and Information Systems. View
  2. Guillod P, Sabouri A. Personalized Medicine in Anesthesia, Pain and Perioperative Medicine. View
  3. Ulapane N, Wickramasinghe N. Optimizing Health Monitoring Systems With Wireless Technology. View