Investigating Evaluation Frameworks for Electronic Health Record: A Literature Review
DOI:
https://doi.org/10.3889/oamjms.2021.3421Keywords:
Electronic medical record, Electronic health record, Evaluation frameworks, Evaluation model, Evaluation theoryAbstract
BACKGROUND: There are various electronic health records (EHRs) evaluation frameworks with multiple dimensions and numerous sets of evaluation measures, while the coverage rate of evaluation measures in a common framework varies in different studies.
AIM: This study provides a literature review of the current EHR evaluation frameworks and a model for measuring the coverage rate of evaluation measures in EHR frameworks.
METHODS: The current study was a comprehensive literature review and a critical appraisal study. The study was conducted in three phases. In Phase 1, a literature review of EHR evaluation frameworks was conducted. In Phase 2, a three-level hierarchical structure was developed, which includes three aspects, 12 dimensions, and 110 evaluation measures. Subsequently, evaluation measures in the identified studies were categorized based on the hierarchical structure. In Phase 3, relative frequency (RF) of evaluation measures in different dimensions and aspects for each of the identified studies were determined and categorized as follows: Appropriate, moderate, and low coverage.
RESULTS: Out of a total of 8276 retrieved articles, 62 studies were considered relevant. The RF range in the second and third level of the hierarchical structure was between 8.6%–91.94% and 0.2%–61%, respectively. “Ease of use” and “system quality” were the most frequent evaluation measure and dimension. Our results indicate that identified studies cover at least one and at most nine evaluation dimensions and current evaluation frameworks focus more on the technology aspect. Almost in all identified studies, evaluation measures related to the technology aspect were covered. However, evaluation measures related to human and organization aspects were covered in 68% and 84% of the identified studies, respectively.
CONCLUSION: In this study, we systematically reviewed all literature presenting any type of EHR evaluation framework and analyzed and discussed their aspects and features. We believe that the findings of this study can help researchers to review and adopt the EHR evaluation frameworks for their own particular field of usage.
Downloads
Metrics
Plum Analytics Artifact Widget Block
References
Nykanen P, Brender J, Talmon J, de Keizer N, Rigby M, BeuscartZephir MC, et al. Guideline for good evaluation practice in health informatics (GEP-HI). Int J Med Inform. 2011;80(12):815-27. https://doi.org/10.1016/j.ijmedinf.2011.08.004 PMid:21920809 DOI: https://doi.org/10.1016/j.ijmedinf.2011.08.004
Sockolow PS, Crawford PR, Lehmann HP. Health services research evaluation principles. Broadening a general framework for evaluating health information technology. Methods Inf Med. 2012;51(2):122-30. https://doi.org/10.3414/me10-01-0066 PMid:22311125 DOI: https://doi.org/10.3414/ME10-01-0066
Lu CH, Hsiao JL, Chen RF. Factors determining nurse acceptance of hospital information systems. Comput Inform Nurs. 2012;30(5):257-64. PMid:22228251 DOI: https://doi.org/10.1097/NCN.0b013e318224b4cf
Chen RF, Hsiao JL. An empirical study of physicians’ acceptance of hospital information systems in Taiwan. Telemed J E Health. 2012;18(2):120-5. PMid:22283362 DOI: https://doi.org/10.1089/tmj.2011.0081
Chen RF, Hsiao JL. An investigation on physicians’ acceptance of hospital information systems: A case study. Int J Med Inform. 2012;81(12):810-20. PMid:22652011 DOI: https://doi.org/10.1016/j.ijmedinf.2012.05.003
Holden RJ, Karsh BT. The technology acceptance model: Its past and its future in health care. J Biomed Inf. 2010;43(1):159- 72. https://doi.org/10.1016/j.jbi.2009.07.002 PMid:19615467 DOI: https://doi.org/10.1016/j.jbi.2009.07.002
Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: A comparison of two theoretical models. Manage Sci. 1989;35(8):982-1003. https://doi.org/10.1287/mnsc.35.8.982 DOI: https://doi.org/10.1287/mnsc.35.8.982
Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS Quart. 2003;27(3):425-78. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540
Garcia-Smith D, Effken JA. Development and initial evaluation of the clinical information systems success model (CISSM). Int J Med Inform. 2013;82(6):539-52. https://doi.org/10.1016/j.ijmedinf.2013.01.011 PMid:23497819 DOI: https://doi.org/10.1016/j.ijmedinf.2013.01.011
Nguyen L, Bellucci E, Nguyen LT. Electronic health records implementation: An evaluation of information system impact and contingency factors. Int J Med Inform. 2014;83(11):779-96. https://doi.org/10.1016/j.ijmedinf.2014.06.011 PMid:25085286 DOI: https://doi.org/10.1016/j.ijmedinf.2014.06.011
DeLone WH, McLean ER. The Delone and McLean model of information systems success. JMIS. 2003;19(4):9-30.
Abdekhoda M, Ahmadi M, Gohari M, Noruzi A. The effects of organizational contextual factors on physicians’ attitude toward adoption of electronic medical records. J Biomed Inf. 2015;53:174-9. https://doi.org/10.1016/j.jbi.2014.10.008 PMid:25445481 DOI: https://doi.org/10.1016/j.jbi.2014.10.008
Currie LM. Evaluation frameworks for nursing informatics. Int J Med Inform. 2005;74(11-12):908-16. PMid:16099711 DOI: https://doi.org/10.1016/j.ijmedinf.2005.07.007
Yusof MM, Papazafeiropoulou A, Paul RJ, Stergioulas LK. Investigating evaluation frameworks for health information systems. Int J Med Inform. 2008;77(6):377-85. https://doi.org/10.1016/j.ijmedinf.2007.08.004 PMid:17904898 DOI: https://doi.org/10.1016/j.ijmedinf.2007.08.004
Ahmadian L, Nejad SS, Khajouei R. Evaluation methods used on health information systems (HISs) in Iran and the effects of HISs on Iranian healthcare: A systematic review. Int J Med Inform. 2015;84(6):444-53. https://doi.org/10.1016/j.ijmedinf.2015.02.002 PMid:25746766 DOI: https://doi.org/10.1016/j.ijmedinf.2015.02.002
Ammenwerth E, de Keizer N. An inventory of evaluation studies of information technology in health care: Trends in evaluation research 1982-2002. Stud Health Technol Inform. 2004;107(2):1289-94. https://doi.org/10.1055/s-0038-1633922 PMid:15361022 DOI: https://doi.org/10.1055/s-0038-1633922
Sadoughi F, Kimiafar K, Ahmadi M, Shakeri MT. Determining of factors influencing the success and failure of hospital information system and their evaluation methods: A systematic review. Iran Red Crescent Med J. 2013;15(12):e11716. https://doi.org/10.5812/ircmj.11716 PMid:24693386 DOI: https://doi.org/10.5812/ircmj.11716
Hayrinen K, Saranto K, Nykanen P. Definition, structure, content, use and impacts of electronic health records: A review of the research literature. Int J Med Inform. 2008;77(5):291-304. https://doi.org/10.1016/j.ijmedinf.2007.09.001 PMid:17951106 DOI: https://doi.org/10.1016/j.ijmedinf.2007.09.001
Oroviogoicoechea C, Watson R. A quantitative analysis of the impact of a computerised information system on nurses’ clinical practice using a realistic evaluation framework. Int J Med Inform. 2009;78(12):839-49. https://doi.org/10.1016/j.ijmedinf.2009.08.008 PMid:19767235 DOI: https://doi.org/10.1016/j.ijmedinf.2009.08.008
Erlirianto LM, Ali AH, Herdiyanti A. The implementation of the human, organization, and technology-fit (HOT-fit) framework to evaluate the electronic medical record (EMR) system in a hospital. Proc Comput Sci. 2015;72:580-7. https://doi.org/10.1016/j.procs.2015.12.166 DOI: https://doi.org/10.1016/j.procs.2015.12.166
Yusof MM, Kuljis J, Papazafeiropoulou A, Stergioulas LK. An evaluation framework for health information systems: Human, organization and technology-fit factors (HOT-fit). Int J Med Inform. 2008;77(6):386-98. https://doi.org/10.1016/j.ijmedinf.2007.08.011 PMid:17964851 DOI: https://doi.org/10.1016/j.ijmedinf.2007.08.011
Tilahun B, Fritz F. Modeling antecedents of electronic medical record system implementation success in low-resource setting hospitals. BMC Med Inform Decis Mak. 2015;15:61. https://doi.org/10.1186/s12911-015-0192-0 DOI: https://doi.org/10.1186/s12911-015-0192-0
Steininger K, Stiglbauer B. EHR acceptance among Austrian resident doctors. Health Policy Technol. 2015;4(2):121-30. https://doi.org/10.1016/j.hlpt.2015.02.003 DOI: https://doi.org/10.1016/j.hlpt.2015.02.003
Hsieh PJ. Physicians’ acceptance of electronic medical records exchange: An extension of the decomposed TPB model with institutional trust and perceived risk. Int J Med Inform. 2015;84(1):1-14. https://doi.org/10.1016/j.ijmedinf.2014.08.008 PMid:25242228 DOI: https://doi.org/10.1016/j.ijmedinf.2014.08.008
Sockolow PS, Weiner JP, Bowles KH, Lehmann HP. A new instrument for measuring clinician satisfaction with electronic health records. Comput Inform Nurs. 2011;29(10):574-85. https://doi.org/10.1097/ncn.0b013e31821a1568 PMid:21543972 DOI: https://doi.org/10.1097/NCN.0b013e31821a1568
Sockolow PS, Bowles KH, Lehmann HP, Abbott PA, Weiner JP. Community-based, interdisciplinary geriatric care team satisfaction with an electronic health record: A multimethod study. Comput Inform Nurs. 2012;30(6):300-11. https://doi.org/10.1097/ncn.0b013e31823eb561 PMid:22411417 DOI: https://doi.org/10.1097/NCN.0b013e31823eb561
Gagnon MP, Ghandour EK, Talla PK, Simonyan D, Godin G, Labrecque M, et al. Electronic health record acceptance by physicians: Testing an integrated theoretical model. J Biomed Inform. 2014;48:17-27. PMid:24184678 DOI: https://doi.org/10.1016/j.jbi.2013.10.010
Bush RA, Kuelbs C, Ryu J, Jiang W, Chiang G. Structured data entry in the electronic medical record: Perspectives of pediatric specialty physicians and surgeons. J Med Syst. 2017;41(5):75. https://doi.org/10.1007/s10916-017-0716-5 PMid:28324321 DOI: https://doi.org/10.1007/s10916-017-0716-5
Sicotte C, Pare G, Bini KK, Moreault MP, Laverdure G. Virtual organization of hospital medical imaging: A user satisfaction survey. J Digit Imaging. 2010;23(6):689-700. https://doi.org/10.1007/s10278-009-9220-x PMid:19588196 DOI: https://doi.org/10.1007/s10278-009-9220-x
Otieno GO, Hinako T, Motohiro A, Daisuke K, Keiko N. Measuring effectiveness of electronic medical records systems: Towards building a composite index for benchmarking hospitals. Int J Med Inform. 2008;77(10):657-69. https://doi.org/10.1016/j.ijmedinf.2008.01.002 PMid:18313352 DOI: https://doi.org/10.1016/j.ijmedinf.2008.01.002
O’Mahony D, Wright G, Yogeswaran P, Govere F. Knowledge and attitudes of nurses in community health centres about electronic medical records. Curationis. 2014;37(1):1150. https://doi.org/10.4102/curationis.v37i1.1150 PMid:24832678 DOI: https://doi.org/10.4102/curationis.v37i1.1150
Hsiao JL, Chang HC, Chen RF. A study of factors affecting acceptance of hospital information systems: A nursing perspective. J Nurs Res. 2011;19(2):150-60. https://doi.org/10.1097/jnr.0b013e31821cbb25 PMid:21586992 DOI: https://doi.org/10.1097/JNR.0b013e31821cbb25
Gilani MS, Iranmanesh M, Nikbin D, Zailani S. EMR continuance usage intention of healthcare professionals. Inform Health Soc Care. 2017;42(2):153-65. https://doi.org/10.3109/17538157.2016.1160245 PMid:27100821 DOI: https://doi.org/10.3109/17538157.2016.1160245
Nematollahi M, Moosavi A, Lazem M, Aslani N, Kafashi M, Garavand A. Factors affecting in adoption and use of electronic medical record based on unified theory of acceptance and use of technology in Iran. Shiraz E Med J. 2017;18(9):e57582. https://doi.org/10.5812/semj.57582 DOI: https://doi.org/10.5812/semj.57582
Leblanc G, Gagnon MP, Sanderson D. Determinants of primary care nurses’ intention to adopt an electronic health record in their clinical practice. Comput Inform Nurs. 2012;30(9):496-502. https://doi.org/10.1097/nxn.0b013e318257db17 PMid:22592453 DOI: https://doi.org/10.1097/NXN.0b013e318257db17
Kowitlawakul Y, Chan SW, Pulcini J, Wang W. Factors influencing nursing students’ acceptance of electronic health records for nursing education (EHRNE) software program. Nurse Educ Today. 2015;35(1):189-94. https://doi.org/10.1016/j.nedt.2014.05.010 PMid:24947068 DOI: https://doi.org/10.1016/j.nedt.2014.05.010
Takian A, Sheikh A, Barber N. We are bitter, but we are better off: Case study of the implementation of an electronic health record system into a mental health hospital in England. BMC Health Serv Res. 2012;12:484. https://doi.org/10.1186/1472-6963-12-484 PMid:23272770 DOI: https://doi.org/10.1186/1472-6963-12-484
Lambooij MS, Drewes HW, Koster F. Use of electronic medical records and quality of patient data: Different reaction patterns Inform Decis Mak. 2017;17(1):1-11. https://doi.org/10.1186/s12911-017-0412-x DOI: https://doi.org/10.1186/s12911-017-0412-x
Otieno OG, Toyama H, Asonuma M, Kanai-Pak M, Naitoh K. Nurses’ views on the use, quality and user satisfaction with electronic medical records: Questionnaire development. J Adv Nurs. 2007;60(2):209-19. https://doi.org/10.1111/j.1365-2648.2007.04384.x PMid:17877568 DOI: https://doi.org/10.1111/j.1365-2648.2007.04384.x
Hyun S, Johnson SB, Stetson PD, Bakken S. Development and evaluation of nursing user interface screens using multiple methods. J Biomed Inform. 2009;42(6):1004-12. https://doi.org/10.1016/j.jbi.2009.05.005 PMid:19460464 DOI: https://doi.org/10.1016/j.jbi.2009.05.005
Hennington A, Janz B, Amis J, Nichols E. Understanding the multidimensionality of information systems use: A study of nurses’ use of a mandated electronic medical record system. Commun Assoc Inf Syst. 2009;25(1):243-62. https://doi.org/10.17705/1cais.02525 DOI: https://doi.org/10.17705/1CAIS.02525
Devine EB, Patel R, Dixon DR, Sullivan SD. Assessing attitudes toward electronic prescribing adoption in primary care: A survey of prescribers and staff. Inform Prim Care. 2010;18(3):177-87. https://doi.org/10.14236/jhi.v18i3.770 PMid:21396241 DOI: https://doi.org/10.14236/jhi.v18i3.770
Chisolm DJ, Purnell TS, Cohen DM, McAlearney AS. Clinician perceptions of an electronic medical record during the first year of implementaton in emergency services. Pediatr Emerg Care. 2010;26(2):107-10. https://doi.org/10.1097/pec.0b013e3181ce2f99 PMid:20093997 DOI: https://doi.org/10.1097/PEC.0b013e3181ce2f99
Morton ME, Wiedenbeck S. EHR Acceptance Factors in Ambulatory Care: A Survey of Physician Perceptions. United States: Perspectives in Health Information Management/ AHIMA, American Health Information Management Association; 2010. p. 7.
Carayon P, Cartmill R, Blosky MA, Brown R, Hackenberg M, Hoonakker P, et al. ICU nurses’ acceptance of electronic health records. J Am Med Inform Assoc. 2011;18(6):812-9. PMid:21697291 DOI: https://doi.org/10.1136/amiajnl-2010-000018
Holtz B, Krein S. Understanding nurse perceptions of a newly implemented electronic medical record system. J Technol Hum Serv. 2011;29(4):247-62. https://doi.org/10.1080/15228835.201 1.639931
Aggelidis VP, Chatzoglou PD. Hospital information systems: Measuring end user computing satisfaction (EUCS). J Biomed Inform. 2012;45(3):566-79. https://doi.org/10.1016/j.jbi.2012.02.009 PMid:22426283 DOI: https://doi.org/10.1016/j.jbi.2012.02.009
Schnall R, Smith AB, Sikka M, Gordon P, Camhi E, Kanter T, et al. Employing the FITT framework to explore HIV case managers’ perceptions of two electronic clinical data (ECD) summary systems. Int J Med Inform. 2012;81(10):e56-62. https://doi.org/10.1016/j.ijmedinf.2012.07.002 DOI: https://doi.org/10.1016/j.ijmedinf.2012.07.002
Lin C, Lin IC, Roan J. Barriers to physicians’ adoption of healthcare information technology: An empirical study on multiple hospitals. J Med Syst. 2012;36(3):1965-77. https://doi.org/10.1007/s10916-011-9656-7 PMid:21336605 DOI: https://doi.org/10.1007/s10916-011-9656-7
Dale JA, Behkami NA, Olsen GS, Dorr DA. A multi-perspective analysis of lessons learned from building an integrated care coordination information system (ICCIS). AMIA Annu Symp Proc. 2012;2012:129-35. PMid:23304281
Bouamrane MM, Mair FS. A study of general practitioners’ perspectives on electronic medical records systems in NHSScotland. BMC Med Inform Decis Mak. 2013;13:58. https://doi.org/10.1186/1472-6947-13-58 PMid:23688255 DOI: https://doi.org/10.1186/1472-6947-13-58
Messeri P, Khan S, Millery M, Campbell A, Merrill J, Shih S, et al. An information systems model of the determinants of electronic health record use. Appl Clin Inform. 2013;4(2):185-200. https://doi.org/10.4338/aci-2013-01-ra-0005 PMid:23874357 DOI: https://doi.org/10.4338/ACI-2013-01-RA-0005
Hsu SC, Liu CF, Weng RH, Chen CJ. Factors influencing nurses’ intentions toward the use of mobile electronic medical records. Comput Inform Nurs. 2013;31(3):124-32. https://doi.org/10.1097/nxn.0b013e318270100b PMid:23114391 DOI: https://doi.org/10.1097/NXN.0b013e318270100b
Michel-Verkerke MB, Hoogeboom AM. Evaluation of the USE IT-questionnaire for the evaluation of the adoption of electronic patient records by healthcare professionals. Methods Inf Med. 2013;52(3):189-98. https://doi.org/10.3414/me12-01-0041 PMid:23591761 DOI: https://doi.org/10.3414/ME12-01-0041
Mei YY, Marquard J, Jacelon C, DeFeo AL. Designing and evaluating an electronic patient falls reporting system: Perspectives for the implementation of health information technology in long-term residential care facilities. Int J Med Inform. 2013;82(11):e294-306. https://doi.org/10.1016/j.ijmedinf.2011.03.008 PMid:21482183 DOI: https://doi.org/10.1016/j.ijmedinf.2011.03.008
Gardner CL, Pearce PF. Customization of electronic medical record templates to improve end-user satisfaction. Comput Inform Nurs. 2013;31(3):115-21. https://doi.org/10.1097/nxn.0b013e3182771814 PMid:23321480 DOI: https://doi.org/10.1097/NXN.0b013e3182771814
Gu Y, Day K. Propensity of people with long-term conditions to use personal health records. Stud Health Technol Inform. 2013;188:46-51. PMid:23823287
Kuo KM, Liu CF, Ma CC. An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC Med Inform Decis Mak. 2013;13(1):88. https://doi.org/10.1186/1472-6947-13-88 PMid:23938040 DOI: https://doi.org/10.1186/1472-6947-13-88
Tavakoli N, Jahanbakhsh M, Shahin A, Mokhtari H, Rafiei M. Electronic medical record in central polyclinic of isfahan oil industry: A case study based on technology acceptance model. Acta Inform Med. 2013;21(1):23-5. https://doi.org/10.5455/aim.2012.21.23-25 PMid:23572857 DOI: https://doi.org/10.5455/aim.2012.21.23-25
Kirkendall ES, Goldenhar LM, Simon JL, Wheeler DS, Andrew Spooner S. Transitioning from a computerized provider order entry and paper documentation system to an electronic health record: Expectations and experiences of hospital staff. Int J Med Inform. 2013;82(11):1037-45. https://doi.org/10.1016/j.ijmedinf.2013.08.005 PMid:24041453 DOI: https://doi.org/10.1016/j.ijmedinf.2013.08.005
Iqbal U, Ho CH, Li YC, Nguyen PA, Jian WS, Wen HC. The relationship between usage intention and adoption of electronic health records at primary care clinics. Comput Methods Programs Biomed. 2013;112(3):731-7. https://doi.org/10.1016/j.cmpb.2013.09.001 PMid:24091088 DOI: https://doi.org/10.1016/j.cmpb.2013.09.001
Bossen C, Jensen LG, Udsen FW. Evaluation of a comprehensive EHR based on the DeLone and McLean model for IS success: Approach, results, and success factors. Int J Med Inform. 2013;82(10):940-53. https://doi.org/10.1016/j.ijmedinf.2013.05.010 PMid:23827768 DOI: https://doi.org/10.1016/j.ijmedinf.2013.05.010
Ho CH, Wene HC, Chu CM, Wu YS, Wang JL. Importance-satisfaction analysis for primary care physicians’ perspective on EHRs in Taiwan. Int J Environ Res Public Health. 2014;11(6):6037-51. PMid:24914640 DOI: https://doi.org/10.3390/ijerph110606037
Hysong SJ, Spitzmuller C, Espadas D, Sittig DF, Singh H. Electronic alerts and clinician turnover: The influence of user acceptance. Am J Manag Care. 2014;20(17):SP520-30. PMid:25811826
Schwarz C, Schwarz A. To adopt or not to adopt: A perceptionbased model of the EMR technology adoption decision utilizing the technology-organization-environment framework. J Organ End User Comput. 2014;26(4):57-79. https://doi.org/10.4018/joeuc.2014100104 DOI: https://doi.org/10.4018/joeuc.2014100104
Liu CF, Cheng TJ. Exploring critical factors influencing physicians’ acceptance of mobile electronic medical records based on the dual-factor model: A validation in Taiwan. BMC Med Inform Decis Mak. 2015;15:4. https://doi.org/10.1186/s12911-014-0125-3 PMid:25889506 DOI: https://doi.org/10.1186/s12911-014-0125-3
Kralj D, Kern J, Tonkovic S, Koncar M. Development of the quality assessment model of EHR software in family medicine practices: Research based on user satisfaction. J Innov Health Inform. 2015;22(3):340-58. https://doi.org/10.14236/jhi.v22i3.158 PMid:26577425 DOI: https://doi.org/10.14236/jhi.v22i3.158
Wang JY, Ho HY, Chen JD, Chai S, Tai CJ, Chen YF. Attitudes toward inter-hospital electronic patient record exchange: Discrepancies among physicians, medical record staff, and patients. BMC Health Serv Res. 2015;15:264. https://doi.org/10.1186/s12913-015-0896-y DOI: https://doi.org/10.1186/s12913-015-0896-y
Sintonen S, Mäkelä K, Miettinen R. User acceptance of electronic health records: A post-implementation study. Int J Healthc Technol Manage. 2015;15(2):162-75. https://doi.org/10.1504/ijhtm.2015.074556 DOI: https://doi.org/10.1504/IJHTM.2015.074556
Gan Q. Is the adoption of electronic health record system contagious? Health Policy Technol. 2015;4(2):107-12. https://doi.org/10.1016/j.hlpt.2015.02.009 DOI: https://doi.org/10.1016/j.hlpt.2015.02.009
Salleh MI, Zakaria N, Abdullah R. The influence of system quality characteristics on health care providers’ performance: Empirical evidence from Malaysia. J Infect Public Health. 2016;9(6):698- 707. https://doi.org/10.1016/j.jiph.2016.09.002 PMid:27659115 DOI: https://doi.org/10.1016/j.jiph.2016.09.002
Kim S, Lee KH, Hwang H, Yoo S. Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Med Inform Decis Mak. 2016;16(1):12. https://doi.org/10.1186/s12911-016-0249-8 PMid:26831123 DOI: https://doi.org/10.1186/s12911-016-0249-8
Shaw NT. CHEATS: A generic information communication technology (ICT) evaluation framework. Comput Biol Med. 2002;32(3):209-20. PMid:11922936 DOI: https://doi.org/10.1016/S0010-4825(02)00016-1
Alharthi H, Youssef A, Radwan S, Al-Muallim S, Zainab AT. Physician satisfaction with electronic medical records in a major Saudi government hospital. J Taibah Univ Med Sci. 2014;9(3):213-8. https://doi.org/10.1016/j.jtumed.2014.01.004 DOI: https://doi.org/10.1016/j.jtumed.2014.01.004
Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Proc. 1991;50(2):179-211. https://doi.org/10.1016/0749-5978(91)90020-t DOI: https://doi.org/10.1016/0749-5978(91)90020-T
Angst CM, Agarwal R, Sambamurthy V, Kelley K. Social contagion and information technology diffusion: The adoption of electronic medical records in US hospitals. Manage Sci. 2010;56(8):1219-41. https://doi.org/10.1287/mnsc.1100.1183 DOI: https://doi.org/10.1287/mnsc.1100.1183
Michel-Verkerke MB, Stegwee RA, Spil TA. The six P’s of the next step in electronic patient records in the Netherlands. Health Policy Technol. 2015;4(2):137-43. https://doi.org/10.1016/j.hlpt.2015.02.011 DOI: https://doi.org/10.1016/j.hlpt.2015.02.011
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2021 Zahra Ebnehoseini, Hamed Tabesh, Majid Jangi Jangi, Kolsoum Deldar , Sayyed Mostafa Mostafavi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
http://creativecommons.org/licenses/by-nc/4.0