Table 1.

Summarized facilitators and barriers.

Authors	Facilitators	Barriers
Kruse CS, et al [8]	Access to information Error reduction Transfer of information Long-run cost savings Clinical and administrative efficiency Project planning Security Time savings Staff retention	Initial cost User perceptions Implementation problems External factors Training Cultural change Future upgrades Necessary maintenance
Cucciniello M, et al [9]	Commitment promotion Role defining System impacts assessments	Change processes
McCullough JM, et al [10]	Availability of clinical data Support from management Competition	Competition
Tang, et al [11]	Availability of RECs	none specified
Abramson EL, et al [12]	Size of hospital (bed size)	Cost Lack of incentive Lack of interoperability Competitiveness Ongoing cost of maintenance
Ben-Zion R et al [13]	Executive management support Alignment with firm strategy Economic competiveness Knowledge management Patient empowerment	Cost-benefit asymmetry Lack of standard protocols for data exchange Uncertainty over implementation cost User resistance Breaches in security Patient privacy
D'Amore JD, et al [14]	Continuity of care document	Omission or misuse of LOINC Excess precision in timestamps Omission or misuse of UCUM in meds Omission or misuse of RxNorm Omission or misuse of dose amount Omission or misuse of allergic reactions Omission or misuse of allergy severity Omission or misuse of dose frequency Omission of result interpretation Omission of result reference range
Jones EB, Furukawa MF [15]	Engage patients and family in their care Improve care coordination Improve population and public health Quality recognition	Health centers with large share of Hispanics and Blacks had lower adoption rates Centers located in rural areas Health center size, income status and region Health centers with larger share of patients whose family incomes were below poverty level had lower rate of EHR adoption
Kruse CS, et al [7]	Size of hospital (bed size) Competiveness Urban locations Users cognitive ability User attitude toward information Workflow impact Communication among users	Patients’ age Rural locations Computer anxiety
Samuel CA [2]	Patients enrolled in Medicare or Medicaid Metropolitan status Increased financial incentives	Health professional shortage areas Minority concentration
Sockolow PS, et al [16]	Increase in productivity Improved clinical notes Reduced time to reimbursement Improved communication among staff	Incomplete medication information Incomplete hospital-stay information
Ancker JS, et al [17]	Monetary incentives Efficiency (fewer providers needed) Efficiency (practice sites) Effectiveness (fewer patients) Practice size	Cost Lack of tech assistance
Audet AM, et al [18]	Size of practice Ability to search for patients by diagnosis Ability to list patients overdue for preventative care Sort patients by specific laboratory results	Cost lack of experience Lack of tech-support infrastructure
Baillie CA, et al [19]	Reduce readmission rates	Existing data may not serve well in a predictive model
Cheung SK, et al [20]	Efficiency Reduction of medical errors Ability to share patient information in public sector Eliminate need to store paper records Eliminate illegibility of practice partners	Patient unfriendliness Limited consultant time Cost concerns Computer use more time consuming Concerns on data migrations from paper to system Insufficient space for computer installation
Georgiou A, et al [21]	Laboratory order forms contained bar codes for easier ordering A unique bar code for patient details Unique bar codes for each test A test order episode barcode	EMR test order problems Handwritten request on an EMR order Order number problem Multiple forms EMR order incorrect Change of test Add-on test No information provided Longer data entry time
Hamid F, Cline TW [5]	EHR satisfaction increased when users understood the benefits Supportive management Training programs	Cost Perceived lack of usefulness and provider autonomy Time consuming
Iqbual U, et al [22]	Perceived usefulness Perceived ease to use Computer self-efficacy Security Intention to use	Clinics with high number of outpatient visits Subjective norm
Kirkendall ES, et al [23]	Communication Job satisfaction Quality and patient data Quality and safety of patient care Employee understanding and support Organizational support The “Rights” of patient care	Transition of data
Middleton B, et al [24]	Monetary incentives Improve effectiveness Improve efficiency	Increased training burden Alert fatigue
Patel V, et al [25]	Financial incentives Size of practice	Lack of interoperability standards
Shen X, et al [26]	Size of practice	Cost Lack of integration with other systems Lack of national guidelines for implementation
Xierali IM, et al [27]	Health maintenance organizations more likely to adopt EHR Those with faculty status more likely to adopt EHR	Medically underserved locations less likely to adopt EHR Geographic health professional shortage areas less likely to adopt EHR International medical graduates less likely to adopt EHR Group practice/solo practice and small practice physicians less likely to adopt EHR
Menachemi N, et al [28]	HMO penetration into market	Competition Low income patients
DesRoches CM, et al [29]	Size of facility Incentives	Cost Size of facility
Decker SL, et al [30]	Size of organization	Age
Hudson JS, et al [31]	Hospital setting Improved outcomes Reduce duplicative tests Integrate levels of care Improve communication Greater readability	Cost
Jamoom E, et al [32]	Age Size of practice Enhanced patient care	none specified
Leu MG, et al [33]	Size of practice	Cost Productivity Customizability (right fit)
Linder JA et al [34]	Better for structured documenters Better for free text documenters	Decrease in quality of care for dictator note takers
Ramaiah M, et al [35]	Workflow can be optimized Access to electronic information e-prescriptions	Workflow often ad-hoc in nature Check-backs of scripts still time consuming Medical literacy of clerks inhibits smooth scheduling Information must still be verified Lack of IT experience of staff Uncertainty of time Uncertainty of cost
Rea S, et al [36]	Secondary use of data Natural language processing	Privacy and security
Ronquillo JG [37]	Genome-associated care Reduce error More efficient care More effective care Control costs	Privacy and security
Wang T, Biederman S [38]	Reduce error Improve quality of care Deliver more effective care	Cost
Soares N, et al [39]	Improve clinician satisfaction Improve clinical efficiency Improve parent satisfaction	Cost Technical assistance Organizational barriers No consensus among peer organizations
Hacker K, et al [40]		Disruption of care Lack of interoperability Disruption of workflow Increased patient-cycle time Breakdown in communication Fragmentation of information Inflexible processes Physician overload