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Chronic diseases are the leading cause of death worldwide. In Canada, more than half of all health care spending is used for managing chronic diseases. Although studies have shown that the use of advanced features of electronic medical record (EMR) systems improves the quality of chronic disease prevention and management (CDPM), a 2012 international survey found that Canadian physicians were the least likely to use 2 or more EMR system functions. Some studies show that maturity vis-à-vis clinicians’ EMR use is an important factor when evaluating the use of advanced features of health information systems. The Clinical Adoption Framework (CAF), a common evaluation framework used to assess the success of EMR adoption, does not incorporate the process of maturing. Nevertheless, the CAF and studies that discuss the barriers to and facilitators of the adoption of EMR systems can be the basis for exploring the use of advanced EMR features.
This study aimed to explore the factors that primary care physicians in Ontario identified as influencing their use of advanced EMR features to support CDPM and to extend the CAF to include primary care physicians’ perceptions of how their use of EMRs for performing clinical tasks has matured.
Guided by the CAF, directed content analysis was used to explore the barriers and facilitating factors encountered by primary care physicians when using EMR features. Participants were primary care physicians in Ontario, Canada, who use EMRs. Data were coded using categories from the CAF.
A total of 9 face-to-face interviews were conducted from January 2017 to July 2017. Dimensions from the CAF emerged from the data, and one new dimension was derived: physicians’ perception of their maturity of EMR use. Primary care physicians identified the following key factors that impacted their use of advanced EMR features: performance of EMR features, information quality of EMR features, training and technical support, user satisfaction, provider’s productivity, personal characteristics and roles, cost benefits of EMR features, EMR systems infrastructure, funding, and government leadership.
The CAF was extended to include physicians’ perceptions of how their use of EMR systems had matured. Most participants agreed that their use of EMR systems for performing clinical tasks had evolved since their adoption of the system and that certain system features facilitated their care for patients with chronic diseases. However, several barriers were identified and should be addressed to further enhance primary care physicians’ use of advanced EMR features to support CDPM.
According to the World Health Organization, by 2020, chronic diseases will account for 73% of all deaths and 60% of the global burden of disease [
Electronic medical records (EMRs) are one of many initiatives available in high-income countries to assist in addressing these risk factors. In a systematic review, approximately 67% of studies showed that EMRs have a positive effect on preventive care, and about 57% of studies found that EMRs contribute to a modest improvement in disease management [
Electronic reminder features for preventive or follow-up care automate reminders for specific tests (eg, vaccinations and blood tests) based on recommended guidelines [
A grounded theory study of EMR usage ranked EMR features from basic to advanced [
Not all physicians use the advanced features of EMR systems to support CDPM. A 2012 study showed that Canadian physicians were the least likely to use at least two EMR functions [
Much of the literature has focused on the factors that contribute to successful EMR adoption. Studies have discussed the need for EMR champions and staff participation to encourage adoption [
In addition, studies have identified the importance of providing adequate education and training to support EMR adoption [
Furthermore, some studies have highlighted the importance of advancing the level of health information system (HIS) use to obtain improved clinical outcomes and have suggested that benefits grow over time as users gain experience, as improvements are made in systems, and as workflows are adjusted to users’ needs [
In this study, the Clinical Adoption Framework (CAF) [
Several frameworks for HIS adoption have been reported in the literature [
The CAF (shown in
This study explored the barriers primary care physicians encounter while using advanced EMR features to facilitate CDPM and the factors facilitating their use of these features. Furthermore, this study extends the CAF to include primary care physicians’ perceptions of how their use of the EMR system had evolved. Thus, the main contribution of this study was looking at the CAF and the maturity of EMR use from the perspective of primary care providers, as they are the ones managing chronic illness.
On the basis of existing evidence about factors influencing EMR adoption, a qualitative directed content analysis was conducted using the CAF. A directed content analysis is typically used when existing theory or prior research about a phenomenon needs further description to validate or extend a theoretical framework or theory [
The study was conducted at primary care clinics located in the Canadian province of Ontario. Although there are various EMR systems available in Ontario, the most common systems used at primary care clinics are PS Suite EMR (produced by Telus Health) [
Drug databases that provide dosing information, administration, and medication allergy alerts.
Hospital Report Manager [
Ontario Laboratories Information System (OLIS) that automatically receives laboratory results from hospitals directly into the patient’s chart [
Electronic fax to electronically receive faxed documents into EMRs.
Eligible participants were primary care physicians located in Ontario who had used EMRs for at least one year. Purposeful sampling was used to represent a range of ages (less than 30 years, 30-40 years, 41-50 years, 51-60 years, 61-70 years, and greater than 71 years), sexes (female and male), and individuals from different cities in Ontario. Face-to-face interviews were conducted.
Data saturation determined the sample size. After 7 interviews, no new ideas were being introduced. Nevertheless, 2 more interviews were conducted to validate that saturation had occurred. A similar study exploring primary care physicians’ experience with EMRs also had a sample size of 9 participants [
OntarioMD assisted in recruiting participants by sharing an advertisement about this study with its peer leaders. Similarly, Ontario academic family practices were contacted to identify participants, resulting in the Ottawa Hospital Family Health Team reaching out to its members. Recruitment emails were also sent to individual family practices.
Data were actively collected between January 2017 and July 2017 by the primary author (RR). In-person interviews were audio recorded. Interviews were approximately 20 min to 60 min and were conducted by using a semistructured interview guide (
Audio recordings of interviews were transcribed verbatim. The directed content approach using the CAF helped determine the initial coding scheme [
The University of Ottawa Research Ethics Board (H01-16-02) granted approval for the study. All participants provided written informed consent before their interview; no personal information was recorded.
Patterns from the data were categorized into themes. In this study, themes refer to barriers and facilitating factors that influenced participants’ use of advanced EMR features. A total of 10 themes emerged from the data: 9 themes directly mapped to the dimensions of the CAF and one new theme was derived from our analysis. The dimensions from the framework that directly mapped to the 9 themes were system quality; information quality; service quality; user satisfaction; net benefits; people; organization; legislation, policy, and governance; and funding and incentives.
Respondents’ characteristics.
Participants | Age range (years) | Sex | Primary care model | Experience using electronic medical records (years) | Information technology lead |
P1 | 51-60 | Male | FHTa | 15 | Yes |
P2 | 61-70 | Female | Independent practice | 3 | No |
P3 | 61-70 | Male | FHT | 10 | Yes |
P4 | 41-50 | Female | FHOb | 7 | Yes |
P5 | 30-40 | Male | FHO | 7 | Yes |
P6 | 51-60 | Male | FHO | 15 | Yes |
P7 | 30-40 | Female | FHT | 4 | No |
P8 | 41-50 | Male | FHO | 4 | No |
P9 | 61-70 | Female | FHO | 9 | No |
aFHT: family health team.
bFHO: family health organization.
Dimensions emerging from the data. EMR: electronic medical record.
The CAF defines the dimension,
Several participants explained that the quick response time for standardized tasks was a system performance factor that facilitated their use of advanced EMR features:
When I receive an abnormal test result I get it right away and I don’t need to wait for the next day.
However, 2 participants mentioned that the drug database feature was not user friendly. Owing to the limitations of this feature, participants used mobile or Web-based drug database applications that were not part of the EMR software as they had an easier interface and quicker response time:
It’s so confusing…but I can write the same thing in my app…it’s just easier to read and it’s quicker.
Participants also described system reliability as a barrier to using advanced EMR features (eg, EMR feature not working).
The dimension
The system is more sophisticated than the last time…it will show me the various dosage forms…that are available.
A few participants were concerned about the completeness and relevance of information provided by the EMR graph feature. These limited their ability to plot and view the trend of a patient’s test results:
It’s a terrible graph…because it’s not temporally organized…so it’s useless as a graph. (P3, age 61-70 years)
The dimension
The CAF cites
According to several participants, certain EMR features (eg, recall system and diabetic flow sheets) were useful and improved their quality of care, for example:
If there’s a drug recall, you can find all the patients who are on that drug and call…them to come in. So it’s amazing what you could do which you couldn’t do on a paper chart.
Overall, 2 participants stated that using the EMR feature to assess cardiovascular risk was time consuming and inefficient, thus impacting productivity and preventing them from using this advanced ready-made feature. One participant described the use of the cardiovascular risk feature as challenging, in that it was not fully integrated into their EMR system, necessitating the use of other online tools to calculate risk:
Anything that’s inefficient is dangerous because it creates a barrier for people to do it. It promotes transcription errors. You move the data manually, you’re going to type a key wrong.
The CAF portrays
Participants reported improved workflow efficiency and improved patient efficiency when certain advanced EMR features were used. One participant described how workflow efficiency and patient efficiency were enhanced when they used a customized referral letter template to expedite a specialist referral: “So when I see an abnormal result I can send a referral at that time and its more efficient for me” [P2, age 61-70 years].
Overall, 2 participants suggested that change in productivity was a barrier to their use of advanced EMR features because of the additional cost associated with the EMR system, particularly maintaining, supporting, and upgrading the system to ensure effectiveness and efficiency. Other associated costs included after-sales support from vendors and hiring additional staff to deal with paper documents that were not electronically deposited into the EMR:
Since the EMR, we had to hire one person whose job was just to scan stuff in before the e-fax came.…I’m paying someone a full-time job just to scan, which is out of my pocket, which is created because of this technology.
Furthermore, the quality of provider effectiveness and appropriateness of care were adversely affected when participants could not access patients’ test results from hospitals, in the EMR system. Participants mentioned wasting time searching for unavailable laboratory results instead of using that time for other tasks.
The CAF defines the dimension
The framework uses an individual’s age, gender, experience, and position (eg, being an IT leader) to measure personal characteristics and roles [
I am too far into using EMRs.…I just do what EMR permits.…I really exploit the system.
On the contrary, another participant (P2) with 3 years of experience using an EMR system revealed that they train their patients to remember when to do blood tests rather than use the reminder feature to prompt the physician for patient preventive services. Clearly, the participants’ characteristics and roles impacted their use of advanced EMR features.
The CAF categorizes
Only a few participants stated that the return on value of advanced EMR features was a barrier to the use of these features. One participant said that the electronic fax feature was expensive and not reliable, so their clinic continued to use a paper-based process:
And that’s a problem with the software. They have an Internet faxing version, but they charge a fortune for it…and it has problems with capacity and reliability.
Most participants noted that their inability to directly transfer documents among the EMR system and hospitals and pharmacies was a barrier. The majority of participants reported that they received laboratory results directly into their EMR system from private laboratories. However, most hospital results are faxed, scanned, and added to the patient’s chart, which was another barrier. The OLIS feature facilitates searching for missing laboratory results. However, some participants mentioned that not all hospital laboratory results were available in OLIS. If they were, the amount of paper that clinics received from hospitals would decrease:
If I go to [the patient’s] chart, I will see if their lab results are actually available through the EMR’s access to OLIS….If I can do that, then I don’t need all that printed paper.
Some participants were concerned about the lack of leadership in addressing poor EMR infrastructure, namely, lack of direct links with hospitals and pharmacies. According to one participant:
The fact that we can’t get stuff from hospital…There’s no technical problem. There’s no leadership that puts together the infrastructure and secures it to do it the way it’s supposed to be done. That’s all we’re missing, leadership…the government can fix two things. One, they could tell the people who supply the software whom they certify, that they have to provide turnkey end-to-end service. And number two, the government actually can help create the connectivity between us and the pharmacies, us and the hospitals.
Furthermore, 2 participants were concerned about the security and privacy of patient charts because of legislation allowing the Ontario government to access patient data.
A total of 2 other participants noted that they did not receive enough government funding to cover all the EMR system expenses. As one participant said:
[The program] didn’t cover everything but it was great, but then they stopped that…then this ongoing and maintaining, it’s all out of our pockets.
Participants were directly asked how their use of EMRs for performing clinical tasks had evolved since adoption. The CAF does not have a category to account for the different maturity stages of the user, so a new category was developed. The CAF describes factors that impact the success of EMR adoption at a moment in time, whereas the new theme describes how these factors evolve over time.
Overall, 2 participants stated that their use of EMRs for performing clinical tasks had not evolved effectively since adoption. They noted flaws such as technical errors with the laboratory requisition feature; poor feature design for prescribing medication doses; and excessive scanner use because of the inability to electronically transfer documents among the EMR and some hospitals and pharmacies, which was needed to support continuity of care over time. Such flaws limited these participants from using the system to its maximum capacity. As one participant explained:
There’s way too much paper handling. Why is a person sitting at a scanner all day long? Why are we still waiting?
However, most participants agreed that their use of the EMR system to perform clinical tasks had improved since its adoption. Several participants revealed the importance of using certain advanced EMR features (eg, electronic fax and Hospital Report Manager) to facilitate patient care delivery and reduce paper work. As one participant said:
We get features that now allow us to run almost a paperless office that did not exist when we first started
As such, the use of advanced features to facilitate patient care delivery and reduce paper work demonstrates that these physicians’ use of the EMR system is maturing as they are able to incorporate advanced EMR features into their workflow.
Furthermore, using the electronic fax and Hospital Report Manager is considered advanced EMR use as physicians have incorporated these features into their clinical process as a way to facilitate CDPM. These features allow physicians to electronically access patient’s results and limit the need to scan paper documents into the EMR, thereby reducing the wait time of physicians accessing patient’s results. Thus, these features can improve patient care by decreasing the wait time during an appointment as the physician searches for the patient’s results or the possibility of human error when scanning paper documents into the EMR, such as support staff mismatching scanned results to a patient’s chart.
Theme 10 shows the need to have a temporal dimension to EMR evaluation to see what types of emerging issues will arise over time. The CAF looks at a more generic set of adoption factors, whereas theme 10 highlights the need to identify specific factors that facilitate EMR use that will emerge over time.
This study explores primary care physicians’ use of EMR systems to support CDPM. Most participants highlighted factors that facilitated their use of advanced EMR features. However, participants continue to experience barriers.
Most participants mentioned that system quality and information quality factors, such as quick response time for standardized tasks (eg, receiving blood test results), and the feature’s provision of complete and relevant information facilitated their use of advanced EMR features. However, participants reported unreliability as a barrier (eg, EMR feature not working), and a few participants also found the drug database feature to be non–user friendly.
Studies have recommended involving users in system design to address such technical factors [
Several participants noted that insufficient technical support and inadequate user training on the part of the vendor was a barrier. In addition, lack of on-site technical support from the vendor created additional costs such as hiring staff to address technical issues. A program such as QIDSS [
User satisfaction emerged from the data in terms of participants’ perceived usefulness of an EMR feature as well as its perceived impact on both productivity and quality of care. Although several participants noted that EMR features (eg, recall system and diabetic flow sheets) supported their quality of patient care, for others, certain EMR features (eg, data entry and cardiovascular risk feature) were inefficient and time consuming, thus a barrier to their productivity.
A systematic review recommended discussing the usefulness of a given EMR feature, demonstrating its ease of use, and having fellow physicians demonstrate the feature [
According to our findings, participants who were IT leaders and had more EMR experience were more likely than others to exploit the EMR system. These findings are consistent with the diffusion of innovations theory, which describes how characteristics of potential adopters (eg, expertise and perception of innovation) influence the success of innovation adoption [
Lack of leadership in addressing poor interoperability among EMR systems and hospitals and pharmacies is an important macrolevel factor discussed by a few participants. A grounded theory study conducted in Ontario also noted the lack of connectivity among clinical EMRs and hospital laboratories [
Legislation and funding also emerged as issues in the data. Some participants were uneasy regarding the security and privacy of patient charts because of legislation that allows the Ontario government to access patient data. Other studies have also shown that concerns about privacy and security of patient data are a barrier to EMR use because of the potential legal problems [
In addition, participants who were not part of an FHT practice felt that government funding was not sufficient to cover EMR expenses. These findings confirm those of other studies in which barriers related to insufficient funding influenced the adoption and use of EMRs [
Most participants thought that their use of EMR systems had improved since adoption with the support of advanced EMR features (eg, electronic fax and Hospital Report Manager). Studies that assessed clinicians’ use of EMR systems found that longer EMR use led to improved outcomes (eg, greater expertise and improved patient care) [
Key factors such as reliability, functionality, and user-friendliness of the EMR feature; technical support and user training; user satisfaction; productivity; return on value; and infrastructure could be assessed as part of the mature use of an EMR system either quantitatively using surveys or qualitatively through interviews. One possible method would be ranking the progress of each key factor for each advanced feature and the progress of mature use of these advance features. For example, for the advanced feature OLIS, its reliability, functionality, and user-friendliness could be ranked using a Likert scale that ranges from 0 to 5, where 0 indicates that the user strongly disagrees that OLIS is reliable, functional, and user friendly. Similarly, the progress of mature use can be assessed using a 5-point Likert scale, where 0 shows that the user strongly disagrees that the feature is fully integrated within their clinical workflow (eg, feature is not being used) and 5 implies that the user strongly agrees that the feature is fully integrated within their clinical workflow (eg, feature is used to access patient’s current and past test results to enable treatment decisions and, if applicable, results are shared with the patient at the point of care). A longitudinal analysis of a clinic would need to be done to measure the progress of these key factors over time and the progress of mature use of these advanced EMR features. Thus, the maturity of EMR use dimension extends the CAF by incorporating postadoption factors perceived by physicians to influence their use of advanced features and the effects of these factors over time to reflect the different maturity stages of the user.
An application of this extended CAF would be to evaluate the progress of advanced EMR feature use among primary care physicians. Another would be for physicians to identify potential factors within their practice that influence their use of advanced EMR features in reaching maturity and to make recommendations for improvements.
Furthermore, the extended CAF could be used by key stakeholders, such as Canada Health Infoway and OntarioMD, to assess the progress of advanced EMR feature use to inform future policies designed to sustain the momentum of advanced EMR feature use.
One limitation of our study is the composition of the participant sample. OntarioMD assisted with recruiting participants by reaching out only to its peer leaders. Peer leaders are typically super users who could be biased favorably toward EMRs. Another limitation is that no participants were located in a rural setting. This group might report other barriers or motives. Researcher bias because of using directed content analysis is another limitation, as researchers are likely to find evidence supportive of their theory. Finally, participants might have answered questions a certain way to please the researcher [
In addition, as the type of EMR software investigated was dependent on the software used by participants, the study only involved 3 types of EMR software: PS Suite, IndiviCare, and Nightingale On Demand. This may have prevented us from observing other advanced EMR features available in other EMR software. Moreover, the EMR software we investigated were all OntarioMD certified, which provided additional benefits (eg, access to Hospital Report Manager, OLIS, and EMR funding eligibility). Other factors might have emerged had we investigated non–OntarioMD-certified EMR systems.
A key strength of this study is that physicians were interviewed in person, providing a deeper understanding of their responses and allowing them to demonstrate certain EMR features. This, in turn, allowed us to observe the barriers and facilitating factors experienced by participants. In addition, the credibility of this study was enhanced by coauthors auditing the results and 2 team members independently analyzing transcripts.
In this study, 9 primary care physicians in Ontario discussed barriers and facilitating factors that influenced their use of advanced EMR features. This study also extended the CAF through the emergence of a new dimension regarding the maturity of users’ EMR use. The extended CAF can be used to support key stakeholders in tracking the use of advanced EMR features, which would support future policies. A future research direction could be the development tools (eg, survey or interview guide) to formally evaluate the extended CAF. Overall, our findings show that although primary care physicians’ use of EMR systems has improved, barriers remain and need to be addressed to further enhance the physicians’ use of advanced EMR features to facilitate CDPM.
Electronic medical record maturity model.
Clinical adoption framework.
Interview guide.
Clinical Adoption Framework
chronic disease prevention and management
electronic medical record
family health organization
family health team
health information system
information technology
Ontario Laboratories Information System
quality improvement decision support specialist
The authors thank all participating family physicians and patients for their cooperation. The authors also thank OntarioMD for its support in recruiting participants.
RR, the primary investigator, conceived, led, and coordinated the development and writing of the manuscript; RR and SY independently analyzed the transcripts; SY participated throughout the development and writing of the manuscript; RR, SY, and CK audited the data analysis findings; and SY, CK, and JM reviewed and made substantial contributions to the manuscript, contributing intellectual content and feedback on the drafts of the paper. All authors read and approved the final paper.
None declared.