Skip to main content
Applied Clinical Informatics logoLink to Applied Clinical Informatics
. 2022 Oct 26;13(5):1015–1023. doi: 10.1055/a-1942-6889

Effect of Notes' Access and Complexity on OpenNotes' Utility

Amro Khasawneh 1,, Ian Kratzke 2, Karthik Adapa 3, Lawrence Marks 3, Lukasz Mazur 3
PMCID: PMC9605819  PMID: 36104159

Abstract

Background  Health care providers are now required to provide their patients access to their consultation and progress notes. Early research of this concept, known as “OpenNotes,” showed promising results in terms of provider acceptability and patient adoption, yet objective evaluations relating to patients' interactions with the notes are limited.

Objectives  To assess the effect of the complexity level of notes and number of accesses (initial read vs. continuous access) on the user's performance, perceived usability, cognitive workload, and satisfaction with the notes.

Methods  We used a 2*2 mixed subjects experimental design with two independent variables: (1) note's complexity at two levels ( simple vs. complex ) and (2) number of accesses to notes at two levels ( initial vs. continuous ). Fifty-three participants were randomly assigned to receive a simple versus complex radiation oncology clinical note and were tested on their performance for understanding the note content after an initial read, and then with continuous access to the note. Performance was quantified by comparing each participant's answers to the ones developed by the research team and assigning a score of 0 to 100 based on participants' understanding of the notes. Usability, cognitive workload, and satisfaction scores of the notes were quantified using validated tools.

Results  Performance for understanding was significantly better in simple versus complex notes with continuous access ( p  = 0.001). Continuous access to the notes was also positively associated with satisfaction scores ( p  = 0.03). The overall perceived usability, cognitive workload, and satisfaction scores were considered low for both simple and complex notes.

Conclusion  Simplifying notes can improve understanding of notes for patients/families. However, perceived usability, cognitive workload, and satisfaction with even the simplified notes were still low. To make notes more useful for patients and their families, there is a need for dramatic improvements to the overall usability and content of the notes.

Keywords: electronic health records, testing, evaluation, notes

Background and Significance

Electronic health records (EHRs) have now been widely adopted in the United States. 1 One potential advantage of EHRs is that patients can readily access their own health data. 2 Indeed, starting in 2021, government regulations require health care providers to provide patients access to all health information in their electronic medical records, including patient consultation and progress notes 3 (often referred to as “OpenNotes”). This requirement followed many studies suggesting that access to notes leads to patients reporting greater control of their care. 4 In addition, studies showed that patients claimed that providing access to consultation and progress notes helped to educate them and increases adherence to medications. 3 4 5

Overall, most studies report that patients wish to continue to have access to their notes, and only a few patients report feeling confused, worried, or offended by the notes. 3 4 6 7 8 9 10 11 For example, in one survey analysis of 96 oncology clinicians and 3,418 patients with a cancer diagnosis, 70% of clinicians and 98% of patients indicated that OpenNotes is a “good idea,” 6 with 44% of the clinicians indicating that patients would be confused by their notes. 6 12 13 In another survey study with 88 patients being seen in radiation oncology, 96% of patients reported that accessing notes improved their understanding of their condition, 94% reported an improved understating of side effects, and 96% felt more confident about their treatment. On the other hand, some patients reported being more worried (11%), getting more confused (6%), and regretted reading the notes (4%). 8

Most of the prior studies report clinicians' and patients' subjective opinions about access to notes with no studies objectively measuring patient understanding of the notes. In addition, there is limited research on how the complexity of these notes and the time spent with the note would affect patients' performance, perceived usability, cognitive workload, and satisfaction with the notes. Thus, the aim of this work was to assess the effect of the complexity level of notes, and the impact of the degree of access to the note, on the user's performance for understanding the note content, perceived usability, cognitive workload, and satisfaction with the notes.

Methods

Participants

This study was completed by healthy volunteers, as surrogates for caregivers. We conducted a pilot analysis with 10 participants to calculate the sample size needed for this study. Our analysis suggested that ≈45 participants would be needed to detect statistical differences between the independent variables at the statistical power of 0.80 and the significance level of 0.05. 14 15 Fifty-three participants completed this study (55% response rate); age range: 19 to 63, mean: 29.5, and standard deviation: 9.4. Table 1 provides a summary of information about participants' demographics. Recruitment was done by sending emails to a variety of list serves at two large academic institution in the United States, and through Research for Me, 16 a platform that provides research participant recruitment services. Participants were compensated with a $10 gift card each upon completion of the study.

Table 1. Demographic information of the participants.

Variable Number %
Gender
 Male 12 23
 Female 41 77
Race
 White/Caucasian 32 60
 Asian 8 15
 African American 4 8
 Hispanic/Latino 4 8
 Multiple 5 9
Prior experience with OpenNotes
 Yes 31 58
 No 22 42

Study Setting

We used a radiation oncology setting since the delivery of radiation therapy is often anxiety-provoking and the notes might thus be particularly reassuring (or worrisome) to patients. For the first independent variable (notes' complexity), an experienced radiation oncology provider wrote two versions of the same patient's note intended to represent “simple” versus “complex” versions (see Supplementary Appendix A [available in the online version] for the notes used in this study). The radiation oncology provider wrote a simple consultation note (the simple level), and then included additional information including more technical terminologies and details to make the notes more complex (the complex level). To quantify the simple versus complex note, two human factors engineering researchers, without any previous medical training, conducted a content analysis (i.e., a qualitative research approach commonly used to categorize qualitative data). 17 18 19 The researchers categorized and scored each sentence in the notes into (1) information known to the patient, (2) technical information, or (3) provider recommendations. Each researcher then coded each sentence in the notes as simple (if they could readily understand it) or complex (if they could not readily understand it). The researchers coded the notes independently and addressed any disagreements by consensus. 18 20 For each of the notes, we calculated a complexity score based on the ratio of simple versus complex sentences. Prior to conducting the study, a few iterations of the notes were generated by the radiation oncology provider to achieve a difference in complexity level that was satisfactory to both researchers and the radiation oncology provider. The difference was considered satisfactory when the complex:simple ratios for the information known to patients and provider recommendation categories (i.e., nontechnical information categories) in the complex note were more than twice as high as those in the simple note (see Table 2 for details and summary results of the content analysis).

Table 2. Content analysis results of the notes.

Code Simple OpenNotes Complex:
simple ratio
Complex OpenNotes Complex:
simple ratio
Information known by patient Total: 48 0.26 Total: 81 0.6
 Number of complex sentences 10 30
 Number of simple sentences 38 51
Technical information Total: 28 6 Total: 64 6.1
 Number of complex sentences 24 55
 Number of simple sentences 4 9
Provider recommendation Total: 17 0.21 Total: 28 0.8
 Number of complex sentences 3 8
 Number of simple sentences 14 10

For the second independent variable (number of accesses to notes): we asked the participants to answer questions about their understanding of the notes twice: once after their initial reading of the note once, and again with continuous access to the notes. This helped us understand if performance was related merely to the participants reading the note once (and not being able to recall information) versus not being able to understand the information even with unlimited access to the note.

Experimental Design

We used a 2*2 mixed subjects experimental design with the two independent variables: (1) note's complexity at two levels ( simple vs. complex ), and (2) the number of accesses to notes at two levels ( initial vs. continuous ). While controlling for prior experience with reading clinical notes, participants were randomly assigned to one of two conditions: simple versus complex notes. Participants were instructed to read the assigned notes as if they were a patient's family member (caregiver). Then, the participants read the notes once (initial) and answered “performance” questions assessing their understanding of the notes without being able to go back and read the notes again. Then, the participants were provided continuous access to the note and were again asked the same series of performance questions. After completing each performance evaluation (initial vs. continuous), participants completed validated questionnaires measuring the perceived usability, cognitive workload, and satisfaction.

Performance

Performance was quantified by comparing each participant's answers to the performance questionnaire (see Supplementary Appendix B , available in the online version) and scored as the percent of “correct answers” (as developed by the research team; thus in a range of 0 to 100%). Therefore, correctly answering the performance questions would reflect higher understanding of the notes. In addition, we conducted a subanalysis on four of the performance questions that were considered clinically critical (physical exam key findings, recommended treatment options, recommended medications, and specialist referral).

Perceived Usability

Perceived usability was quantified using the Systems Usability Scale (SUS). 21 22 23 SUS is a valid, reliable, and most commonly used tool to measure usability of patient-facing interfaces. 24 25 SUS is a 10-item questionnaire, with a five-point rating scale for each item ranging from strongly disagree to strongly agree. The outcome is a 0 [low] to 100 [high] score calculated based on user's rating of the 10 items with higher scores indicating better perceived usability. 26 27

Cognitive Workload

Cognitive workload was quantified using the National Aeronautical and Space Administration's Task Load Index (NASA-TLX), 28 a valid and reliable subjective measure. The NASA-TLX questionnaire evaluates cognitive workload using six dimensions (mental demand, physical demand, temporal demand, frustration, effort, and performance). It provides a global cognitive workload score from 0 [low] to 100 [high].

Satisfaction

Satisfaction was quantified using a slightly modified version of a previously developed survey. 29 Participants rated their satisfaction with the information in the notes, the time required to read the notes, language used in the notes, and the overall design of the notes using a 5-point Likert scale (see Supplementary Appendix C [available in the online version] for the satisfaction survey used in this study). Total satisfaction scores were calculated by averaging scores of items for satisfaction with the information in the notes, the time required to read the notes, language used in the notes, and the overall design.

Results

Data Analysis

IBM SPSS Statistics 28.0.1.0 was used to analyze the data. We conducted multiple mixed-subject ANOVAs (analyses of variance) to determine the effect of the independent variables (simple vs. complex note [between subjects] and initial vs. continuous access to the note [within-subject]) on performance, usability, cognitive workload, and satisfaction. The z-scores from the skewness and kurtosis were used to check for normality of data. Mauchly's test of sphericity was used to test the assumption of sphericity. Least significant difference adjustments were applied to test simple main effects at a statistical significance of p  < 0.05. All simple pairwise comparisons were evaluated at an alpha level of 0.05. We included the demographics variables (e.g., age, education, and previous experience with reading clinical notes) in the analysis as covariates to count for their effect on the dependent variables. However, none of the covariates showed a statistically significant effect. A summary of the findings is provided in Table 3 .

Table 3. Means and SDs for all measures.

Measure Access to notes Simple notes Complex notes
Mean SD Mean SD
Performance Initial 48.65 3.16 44.70 3.22
Continuous 74.88 3.16 53.50 3.22
Usability (SUS) Initial 49.50 4.04 41.71 4.12
Continuous 53.5 4.15 43.21 4.24
Workload (NASA-TLX) Initial 56.30 4.27 57.06 4.93
Continuous 51.78 4.11 55.60 4.75
Satisfaction Initial 2.99 0.21 2.96 0.22
Continuous 3.18 0.24 3.2 0.24

Abbreviations: NASA-TLX, National Aeronautical and Space Administration's Task Load Index; SD, standard deviation; SUS, Systems Usability Scale.

Performance

Participants randomized to the simple notes with continuous access to the notes had better performance when compared to all the other experimental conditions ( F (1, 50) = 11.78, p  = 0.001, η 2  = 0.19; Fig. 1 ). Descriptive statistics are provided in Table 3 . The same result was seen when the analysis was limited to the four clinically critical questions ( F (1, 50) = 6.16, p  = 0.017, η 2  = 0.11; Fig. 2 ).

Fig. 1.

Fig. 1

Effect of access to notes and notes' complexity on performance.

Fig. 2.

Fig. 2

Effect of access to notes and notes' complexity on performance (four items only).

Perceived Usability

There were no significant results associated with perceived usability (SUS scores; p  > 0.05; Table 3 ).

Cognitive Workload

There were no significant results associated with cognitive workload ( p  > 0.05; Table 3 ), including analysis of individual dimensions of the NASA-TLX. Descriptive statistics of the combined data are provided in Fig. 3 and Table 4 . The results are combined since there were no significant differences.

Fig. 3.

Fig. 3

Cognitive workload scores (NASA-TLX) for combined results. NASA-TLX, National Aeronautical and Space Administration's Task Load Index.

Table 4. Means and SDs of cognitive workload scores (NASA-TLX) for combined results.

Workload dimension Performance Mental demand Physical demand Temporal demand Frustration Effort Overall workload
Mean 46.70 64.51 9.27 28.04 43.34 55.53 55.20
SD 26.10 22.19 15.00 22.18 29.13 23.63 18.32

Abbreviations: NASA-TLX, National Aeronautical and Space Administration's Task Load Index; SD, standard deviation.

Satisfaction

Participants indicated higher satisfaction when they had continuous access to the notes ( M  = 3.2) than when they did not ( M  = 2.9) with a significant mean difference of 0.24 (95% confidence interval: 0.06–0.36), p  = 0.008 ( F (1, 50) = 0.11, p  = 0.74, η 2  = .002; Table 5 ). The analysis of individual satisfaction items showed no statistically significance. Descriptive statistics of the combined data are provided in Fig. 4 and Table 5 . The results are combined since there were no significant differences.

Table 5. Means and SDs for satisfaction items for combined results.

Satisfaction items Information Time Language Design Overall satisfaction
Mean 3.06 3.60 2.89 2.78 3.09
SD 1.38 1.35 1.41 1.37 1.19

Abbreviation: SD, standard deviation.

Fig. 4.

Fig. 4

Satisfaction scores for combined results.

Discussion

Overall, our results suggest that performance was better with the simple note and with continuous access. Continuous access to the notes was also positively associated with better satisfaction. The overall perceived usability, cognitive workload, and satisfaction scores were low. None of the covariates, including participant's previous experience with reading clinical notes, showed a statistically significant effect. This could be due to the fact that our means to define “experience” is imperfect, and, even if participants had experience with reading clinical notes in other fields, this may not have assisted in their understanding of a radiation oncology note specifically. In the subsections below, we discuss each dependent variable.

Performance

Participants' performance (i.e., understanding) was best with continuous access to simple notes. This is most likely due to the participants being able to go back to the notes and find answers to the performance questions. Results also suggest that participants were not able to recall even the clinically most critical information, which might be somewhat worrisome. 30 Even with continuous access to simple notes, performance was relatively low (overall ≈75% of questions were answered correctly), and no participants answered all questions correctly. Overall, our findings suggest that concerted efforts are needed to further simplify and improve usability of the notes. This might also suggest that, at least for some patients, it might not be practical to expect complete understanding via the note alone, and might potentially limit the ultimate utility of OpenNotes. 31 32 33 34

Perceived Usability

There were no statistical differences in usability between simple and complex notes, nor in the initial vs. continuous access. In all groups, the overall mean of perceived usability scores was relatively very low, i.e., ≈50–54 on the 100-point scale. 35 Thus, simplifying the notes' content in this study was insufficient to show an improvement in perceived usability. In the literature, the average usability score is 68 36 and it is a common practice in the human–computer interaction field to consider any score below this average as unsatisfactory. Thus, usability of notes needs further improvements.

Cognitive Workload

Participants perceived that reading the notes imposes a high cognitive workload, i.e., higher than what is considered “optimal” in the literature, especially for tasks with very low physical demands such as reading. 37 This could be due to the high use of medical jargon in the notes which adds burden onto the user, though the simple note was written explicitly aiming to reduce jargon. Thus, techniques to further reduce cognitive workload during interactions with notes are needed.

Satisfaction

Participants were slightly more satisfied when they had continuous access to the notes. However, satisfaction scores were generally low in both experimental conditions. Ideally, satisfaction scores need to be 4 and above (i.e., satisfied or extremely satisfied). While multiple studies report that patients were highly satisfied to receive access to their notes, 4 8 10 31 38 39 40 41 these conclusions were generally based on a broad subjective question , rather than a formal tool designed to assess satisfaction. Our findings suggest that participants are not satisfied with the content of the notes (information, time to read, language used, and design). Thus, strategies to further improve satisfaction with the notes are needed.

Limitations of Findings

There are a number of limitations that prevent the generalizability of our findings. First, this was a remote study without a moderator present while the participants completed the study. Thus, we asked participants to conduct this study in a setting with limited exposure to distractions and interruptions, though compliance cannot be confirmed. Second, recruitment was done through an online platform. Thus, our sample consisted of those who are familiar and comfortable with using online tools and therefore their perception of reading provider's notes could be different from those who do not use technology frequently. Third, participants were asked to assume they were the caregiver of a patient, but they had no background information about the patient. In the real world, participants would have known the patient to at least some degree, and thus would be more familiar with their medical history. To help with this, we used relatively generic notes and standardized the notes among all participants. Fourth, the comparisons between the initial versus continuous access to the notes are not randomized (as it is not possible to randomize this variable), and the subjects knew the performance for understanding questions at the time when they had continuous access to the notes (since they had just done the assessments after their initial reading of the note). Despite this, performance for understanding was low even in the continuous access setting. Finally, we used only radiation oncology notes, making our findings perhaps most applicable to this particular clinical domain. Findings from this study may or may not be generalizable to other fields.

Conclusion

While participants randomized to the simple notes with continues access to the notes performed better than the participants randomized to the complex notes, their understanding, perceived usability, cognitive workload, and satisfaction with the notes were still low. While patients and their families have a strong interest in accessing their clinical notes, and the majority of patients expect meaningful benefits from reading the notes, our results suggest that to make the notes useful there is a need for dramatic improvements to the usability and content of the notes. Doing so might facilitate the use of clinical notes to also serve as a means to provide instructions and resources for patients (and families).

Clinical Reference Statement

This study suggests that the current way of writing clinical notes does not meet patient's need. The current version of the clinical notes is associated with low performance (understanding of the notes), usability, workload, and satisfaction. Thus, this could potentially lead patient to misinterpret the information in the notes and make poor decisions regarding their health. In order to improve patient engagement and decision making by providing patients access to their clinical notes, the usability and content of the notes must be improved to better address patients' needs.

Multiple choice questions

  1. When patients read clinical notes, which of the following has an impact on performance (understanding the content of the notes)?

    1. Notes' complexity (simple vs. complex)

    2. Access to notes (initial vs. continuous)

    3. Both notes' complexity and access to notes

    4. None

    Correct Answer: The correct answer is option c . Participants' performance (i.e., understanding) was best with continuous access and simple notes.

  2. When patients read clinical notes, which of the following has an impact on their cognitive workload?

    1. Notes' complexity (simple vs. complex)

    2. Access to notes (initial vs. continuous)

    3. Both notes' complexity and access to notes

    4. None

    Correct Answer: The correct answer is option d. None of these variables have significant effect on patients' cognitive workload. All participants reported high cognitive workload no matter which condition they were in.

Conflict of Interest None declared.

Protection of Human and Animal Subjects

Participation was voluntary and does not pose undue risk. All human participants read and signed the informed consent form and all needed information was given to them when deciding whether to participate in the study. This was a remote unmoderated study and was fully implemented in Qualtrics. 42 The study protocol was reviewed and approved by the University of North Carolina at Chapel Hill Institutional Review Board (IRB) under reference ID: 338124.

Supplementary Material

10-1055-a-1942-6889-s202205ra0156.pdf (77.9KB, pdf)

Supplementary Material

Supplementary Material

References

  • 1.HealthIT.gov Office-based physician electronic health record adoptionAccessed May 18, 2021 at:https://dashboard.healthit.gov/quickstats/pages/physician-ehr-adoption-trends.php
  • 2.Roehrs A, da Costa C A, Righi R D, de Oliveira K SF. Personal health records: a systematic literature review. J Med Internet Res. 2017;19(01):e13. doi: 10.2196/jmir.5876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Delbanco T, Walker J, Darer J D. Open notes: doctors and patients signing on. Ann Intern Med. 2010;153(02):121–125. doi: 10.7326/0003-4819-153-2-201007200-00008. [DOI] [PubMed] [Google Scholar]
  • 4.Kayastha N, Pollak K I, LeBlanc T W.Open notes: a qualitative study of oncology patients' experiences reading their cancer care notes J Clin Oncol 201735(31, suppl):33–33. [DOI] [PubMed] [Google Scholar]
  • 5.Murugan A, Gooding H, Greenbaum J. Lessons learned from OpenNotes learning mode and subsequent implementation across a pediatric health system. Appl Clin Inform. 2022;13(01):113–122. doi: 10.1055/s-0041-1741483. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Salmi L, Dong Z J, Yuh B, Walker J, DesRoches C M. Open notes in oncology: patient versus oncology clinician views. Cancer Cell. 2020;38(06):767–768. doi: 10.1016/j.ccell.2020.09.016. [DOI] [PubMed] [Google Scholar]
  • 7.Shaverdian N, Wang X, Hegde J V. The patient's perspective on breast radiotherapy: initial fears and expectations versus reality. Cancer. 2018;124(08):1673–1681. doi: 10.1002/cncr.31159. [DOI] [PubMed] [Google Scholar]
  • 8.Shaverdian N, Chang E M, Chu F-I. Impact of open access to physician notes on radiation oncology patients: results from an exploratory survey. Pract Radiat Oncol. 2019;9(02):102–107. doi: 10.1016/j.prro.2018.10.004. [DOI] [PubMed] [Google Scholar]
  • 9.Turer R W, DesRoches C M, Salmi L, Helmer T, Rosenbloom S T. Patient perceptions of receiving COVID-19 test results via an online patient portal: an open results survey. Appl Clin Inform. 2021;12(04):954–959. doi: 10.1055/s-0041-1736221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Sarabu C, Lee T, Hogan A, Pageler N. The value of OpenNotes for pediatric patients, their families and impact on the patient-physician relationship. Appl Clin Inform. 2021;12(01):76–81. doi: 10.1055/s-0040-1721781. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Ponathil A P, Khasawneh A, Byrne K, Madathil K C. Factors affecting the choice of a dental care provider by older adults based on online consumer reviews. IISE Trans Healthc Syst Eng. 2021;11(01):51–69. [Google Scholar]
  • 12.Blease C, Salmi L, DesRoches C M. Open notes in cancer care: coming soon to patients. Lancet Oncol. 2020;21(09):1136–1138. doi: 10.1016/S1470-2045(20)30423-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.NIH Cancer patients say clinical notes access valuable - National Cancer InstituteAccessed May 18, 2021 at:https://www.cancer.gov/news-events/cancer-currents-blog/2020/open-clinical-notes-access-by-cancer-patients
  • 14.Cohen J.The effect sizeIn: Statistical Power Analysis for the Behavioral Sciences.Mahwah: NJLawrence Erlbaum Associates; 19888–13.
  • 15.Khasawneh A, Chalil Madathil K, Dixon E, Wisniewski P, Zinzow H, Roth R. An investigation on the portrayal of blue whale challenge on youtube and twitter. Proc Hum Factors Ergon Soc Annu Meet. 2019;63(01):887–888. [Google Scholar]
  • 16.Research for Me - HomeAccessed May 10, 2022 athttps://researchforme.unc.edu/index.php/en/
  • 17.Harwood T G, Garry T. An overview of content analysis. Marketing Rev. 2003;3(04):479–498. [Google Scholar]
  • 18.Richards K AR, Hemphill M A. A practical guide to collaborative qualitative data analysis. J Teach Phys Educ. 2018;37(02):225–231. [Google Scholar]
  • 19.Khasawneh A, Chalil Madathil K, Dixon E, Wiśniewski P, Zinzow H, Roth R. Examining the self-harm and suicide contagion effects of the blue whale challenge on YouTube and Twitter: qualitative study. JMIR Ment Health. 2020;7(06):e15973. doi: 10.2196/15973. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Khasawneh A, Madathil K C, Zinzow H. An investigation of the portrayal of social media challenges on youtube and twitter. Trans Soc Comput. 2021;4(01):1–23. [Google Scholar]
  • 21.Peres S C, Pham T, Phillips R. Validation of the system usability scale (SUS) Proc Hum Factors Ergon Soc Annu Meet. 2013;57(01):192–196. [Google Scholar]
  • 22.Wilson M K, Khasawneh A, Ponathil A. A preliminary study investigating patients' perceptions of research consenting methods. Proc Hum Factors Ergon Soc Annu Meet. 2019;63(01):1931–1935. [Google Scholar]
  • 23.Khasawneh A, Rogers H, Bertrand J, Madathil K C, Gramopadhye A. Human adaptation to latency in teleoperated multi-robot human-agent search and rescue teams. Autom Construct. 2019;99:265–277. [Google Scholar]
  • 24.Gomes K M, Ratwani R M. Evaluating improvements and shortcomings in clinician satisfaction with electronic health record usability. JAMA Netw Open. 2019;2(12):e1916651. doi: 10.1001/jamanetworkopen.2019.16651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Cole A C, Adapa K, Khasawneh A, Richardson D R, Mazur L. Codesign approaches involving older adults in the development of electronic healthcare tools: a systematic review. BMJ Open. 2022;12(07):e058390. doi: 10.1136/bmjopen-2021-058390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Lewis J R, Sauro J. Item benchmarks for the system usability scale. Journal of Usability Studies. 2018;13(03):158–167. [Google Scholar]
  • 27.Sauro J, Lewis J R. Amsterdam: Elsevier; 2004. Quantifying the User Experience: Practical Statistics for User Research. [Google Scholar]
  • 28.Hart S G. Nasa-Task Load Index (NASA-TLX); 20 years later. Proc Hum Factors Ergon Soc Annu Meet. 2006;50(09):904–908. [Google Scholar]
  • 29.Hamad J, Fox A, Kammire M S, Hollis A N, Khairat S. Evaluating the experiences of new and existing teledermatology patients during the COVID-19 pandemic: cross-sectional survey study. JMIR Dermatol. 2021;4(01):e25999. doi: 10.2196/25999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Cowan N. What are the differences between long-term, short-term, and working memory? Prog Brain Res. 2008;169:323–338. doi: 10.1016/S0079-6123(07)00020-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Mishra V K, Hoyt R E, Wolver S E, Yoshihashi A, Banas C. Qualitative and quantitative analysis of patients' perceptions of the patient portal experience with OpenNotes. Appl Clin Inform. 2019;10(01):10–18. doi: 10.1055/s-0038-1676588. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Fossa A J, Bell S K, DesRoches C. OpenNotes and shared decision making: a growing practice in clinical transparency and how it can support patient-centered care. J Am Med Inform Assoc. 2018;25(09):1153–1159. doi: 10.1093/jamia/ocy083. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Leveille S G, Walker J, Ralston J D, Ross S E, Elmore J G, Delbanco T. Evaluating the impact of patients' online access to doctors' visit notes: designing and executing the OpenNotes project. BMC Med Inform Decis Mak. 2012;12:32. doi: 10.1186/1472-6947-12-32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Bialostozky M, Huang J S, Kuelbs C L. Are you in or are you out? provider note sharing in pediatrics. Appl Clin Inform. 2020;11(01):166–171. doi: 10.1055/s-0040-1701679. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Adobe XD Ideas The System Usability Scale & How it's Used in UXAccessed February 7, 2022 at:https://xd.adobe.com/ideas/process/user-testing/sus-system-usability-scale-ux/
  • 36.Usability.gov System Usability Scale (SUS)Accessed February 8, 2022 at:https://www.usability.gov/how-to-and-tools/methods/system-usability-scale.html
  • 37.Prabaswari A D, Basumerda C, Utomo B W. The mental workload analysis of staff in study program of private educational organization. IOP Conf Ser: Mater Sci Eng. 2019;528:12018. [Google Scholar]
  • 38.Walker J, Leveille S, Bell S. Opennotes after 7 years: patient experiences with ongoing access to their clinicians' outpatient visit notes. J Med Internet Res. 2019;21(05):e13876. doi: 10.2196/13876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Panattoni L, Stone A, Chung S, Tai-Seale M. Patients report better satisfaction with part-time primary care physicians, despite less continuity of care and access. J Gen Intern Med. 2015;30(03):327–333. doi: 10.1007/s11606-014-3104-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Alpert J M, Morris B B, Thomson M D, Matin K, Geyer C E, Brown R F. OpenNotes in oncology: oncologists' perceptions and a baseline of the content and style of their clinician notes. Transl Behav Med. 2019;9(02):347–356. doi: 10.1093/tbm/iby029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Joseph A, Chalil Madathil K, Jafarifiroozabadi R. Communication and teamwork during telemedicine-enabled stroke care in an ambulance. Hum Factors. 2022;64(01):21–41. doi: 10.1177/0018720821995687. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Qualtrics XM The leading experience management softwareAccessed November 2, 2021 at:https://www.qualtrics.com/

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

10-1055-a-1942-6889-s202205ra0156.pdf (77.9KB, pdf)

Supplementary Material

Supplementary Material


Articles from Applied Clinical Informatics are provided here courtesy of Thieme Medical Publishers

RESOURCES