Keywords
error management and prevention - vulnerable populations - patient safety - patient–provider
communication
Background and Significance
Background and Significance
Diagnostic errors/delays and health care disparities are “twin challenges” in health
care, each worsened by the coronavirus disease 2019 pandemic.[1]
[2]
[3]
[4]
[5]
[6] Individuals at risk of health care disparities may also be at increased risk of
safety events including diagnostic error due to language barrier, reduced self-efficacy,
or biased care.[7]
[8]
[9]
[10]
[11]
[12] Diagnostic errors are generally underreported—a particular hazard for patients identifying
as racial and/or ethnic minorities, those with limited English proficiency or health
literacy, and those who are un- or underinsured.[10]
[13]
Understanding and learning from the experiences of patients/families with diagnostic
error is critical to improve patient safety.[14] Patients and families identify components of diagnostic error that may not otherwise
be recognized by clinicians or health care systems.[14]
[15]
[16] Individuals with limited English proficiency further report unique contributing
factors to diagnostic error.[7] However, feedback about care concerns from patients/families at risk of disparities
is limited.[17]
[18]
[19]
[20] Underreporting of diagnostic errors and lack of patient/family perspectives mean
missed safety events and compromised organizational learning.[10]
[15] These findings increase the urgency to establish systematic ways to broadly engage
patients and families in the diagnostic process (DxP).[13]
Advances in health care technology and policy, such as federally mandated access to
electronic health information in the 2021 Cures Act Final Rule, raise new opportunities
to partner with patients/families in diagnosis. Studies demonstrate that sharing visit
notes can help engage patients/families as diagnostic partners.[21] Patients/families who read notes report better remembering and completing diagnostic
tests and referrals,[22] improved relationships with their providers,[22]
[23] and identification of breakdowns related to the DxP.[15]
[24]
[25] Access to notes also enables patients/families to learn more about their health
conditions, formulate questions without the time pressure or stressors of the clinical
environment, and participate as informed members of the health care team.[26]
Shared electronic health information may also help clinicians understand patients
and improve shared decision-making in diagnosis.[27] Recent studies on patient contributions prior to the visit through the patient portal
or a waiting room iPad show improved communication and visit efficiency.[28]
[29]
[30] In some instances, such contributions were used by clinicians to cogenerate visit
notes.[29]
[30] Incorporating the patient story into the clinic note in this way may be empowering,
especially for patients whose voices are not otherwise adequately heard or for those
who may experience “systemic oppression or disenfranchisement.”[31]
However, access to the patient portal is itself subject to disparities, and interventions
to engage patients/families online may have unintended consequences due to selective
participation.[32]
[33]
[34]
[35] One study comparing the use of a portal-based online previsit survey between patients
in safety net clinics versus patients in nonsafety net clinics demonstrated lower
participation in the former group.[29] Innovations to engage patients in diagnosis therefore require a focus on promoting
equity and principled data collection to examine disparities in use.[16]
[36] To date little is known about how to engage patients and families of diverse races,
ethnicities, or language preferences in the DxP.
We developed an online tool called Our Diagnosis (OurDX) to engage patients and families
in the ambulatory DxP. OurDX was designed with patients and families, using evidence-based
items and common patient-reported diagnostic concerns previously described in the
literature.[7]
[15]
[29]
[37]
Objectives
The objective of the study was to examine differences in sociodemographic factors
(self-reported race, ethnicity, and language preference) on patient and family contributions
to an electronic previsit tool (OurDX) designed to engage patients and families in
the DxP. We hypothesized that OurDX use would vary by race, ethnicity, and language
preference including: (1) identification of patient/family diagnostic concerns (primary
outcome); (2) the number of patient/family contributions; (3) clinician verification
of patient/family diagnostic concerns, and (4) clinician integration of patient/family
contributions into the visit note.
Methods
Study Population
Patients and families with scheduled visits in three participating medical and surgical
subspecialty clinics in a northeast U.S. academic pediatric hospital during May 1,
2021 to December 31, 2021 were invited to complete OurDX as part of a previsit survey
via email. Patient demographics, including legal sex, race, ethnicity, age, preferred
language, and interpreter services preference were extracted from the electronic health
record (EHR). If language preference was missing in the designated administrative
data field, we conducted chart review to identify preferred language.
OurDX Tool
OurDX was codeveloped by patients, families, clinicians, researchers, and experts
in user-centered-design and diagnostic safety. Through OurDX, patients and families
were invited to contribute visit priorities, recent medical histories, and potential
diagnostic concerns (such as feeling their main concern was not heard or problems
or delays with tests or referrals). The intervention did not rely on patients and
families registering for a patient portal, since OurDX was accessed through email.[38]
[39] Eligible participants were emailed a link to the OurDX survey via a third-party
vendor survey platform (Tonic Health, Murray, Utah, United States) 5 days prior to
their appointment with reminders 3 and 1 day prior to the visit. Completed surveys
were automatically imported into the EHR and available for clinician review within
the EHR's usual visit workflow dashboard. Further details of OurDX development and
implementation are available elsewhere.[37]
[40]
Patient/Family Diagnostic Concerns
We defined patient/family diagnostic concerns as: “A problem or delay reported by
patients/families that could map to any part of the DxP, as outlined in the National
Academy of Medicine conceptual model.”[15] These included problems or concerns related to access to care, inaccurate medical
history, delayed tests or referrals, communication breakdowns, and problems or delays
with diagnosis or next steps. We calculated the frequency of patient/family diagnostic
concerns (primary outcome) from the entire study population.
Chart Review
We conducted chart review, randomly selecting a subset of visits from each participating
clinic. We used chart review to further characterize patients and to determine whether
patient/family OurDX contributions were incorporated into the visit note, as in previously
published methodology.[31] Chart review was completed by a research assistant with support from a pediatrician,
using REDcap. We used the chart review sample for qualitative analyses including the
secondary outcomes (number of patient/family contribution categories, clinician verification
of patient/family concerns, and integration of patient/family contributions into the
visit note).
Coding Process
Two physician–researchers reviewed all patient/family reports in the chart review
sample. We started with a deductive approach, using the Framework for Patient-Reported
DxP-related Breakdowns to code all patient content in OurDX reports, including information
provided in the visit priorities, recent medical history, and diagnostic concerns.[15] We then used an inductive approach to describe and label any new categories emerging
from the data, beyond the framework categories. Using constant comparison and in-depth
discussions to reach consensus, we identified and defined three additional categories,
testing once again for saturation of codes in the data. When no new categories emerged,
we finalized 10 coding categories: access to care, medical history/symptoms, information
on medications related to main concern, recent visits for the same problem, multidisciplinary
information, tests/referrals, explanation (diagnosis) or next steps, care coordination,
communication concern, or other, each supported as important diagnostic information
in the literature.[15]
[31]
[41]
[42] We defined a patient/family contribution as any content that was coded in these
10 categories and provided by the patient/family across all fields in the OurDX tool.
The two physician–researchers also reviewed OurDX reports in detail in the chart review
sample to verify patient/family concerns. We defined a patient/family diagnostic concern
as verified if physician–researcher review of the patient/family information in the
OurDX report and the accompanying chart review and visit note confirmed a probable
diagnostic safety opportunity for clinicians. In other words, the patient/family provided
information that clinicians could respond to at the point of care to improve DxP safety.
Examples include the opportunity to provide specific test results the patient/family
had not received, assist with delayed referrals, or help ensure that patient/family
main concerns were correctly heard and understood, to help prevent potential downstream
diagnostic errors or delays. Throughout the coding process the physicians were blinded
to the patient's sociodemographic information.
To test intercoder reliability, we used 20% of the chart review sample and calculated
the AC1 and kappa statistics. We used AC1 because some categories were used more frequently
than others. However, we also calculated the kappa statistic because it is a more
conservative measure and more commonly used. We considered agreement coefficients
0.61 to 0.8 as good agreement and 0.81 to 1.00 as excellent agreement. Intercoder
reliability testing demonstrated good to excellent agreement: AC1 0.94 (0.89, 0.98)
and kappa 0.84 (0.74, 0.94) for patient contributions and AC1 0.83 (0.76, 0.89); kappa
0.79 (0.72, 0.87) for patient diagnostic concern verification. Based on this agreement,
one physician coded the remainder of reports in the sample.
Analysis
We used descriptive statistics to compare patient sociodemographics between respondents
and nonrespondents in the participating clinics during the study period. We used chi-squared
analysis to compare the mean number of contributions and clinician verification of
patient/family diagnostic concerns, by race, ethnicity, and language preference. We
used logistic regression to examine potential sociodemographic patient factors associated
with patient/family identification of potential diagnostic concerns and integration
of patient priorities into the clinician's note. For patients with >1 visit during
the study period (<20%), we randomly selected one visit to include in our analyses
using established methodology.[43]
Results
Study Population
Among 18,129 visits during the study period, 7,075 (39.0%) OurDX reports were submitted
by 5,731 patients or parents/proxies (“family”), approximating the response rate of
clinical previsit surveys across all ambulatory clinics in our organization (35%).
Patient characteristics are shown in [Table 1]. Compared with nonparticipating patients, participating patients were more likely
to self-identify as White and English-preferring ([Supplementary Appendixes A] and [B], available in the online version), consistent with the overall sociodemographics
of previsit survey users in our organization. We conducted a total of 324 chart reviews.
Patient characteristics in the chart review sample were similar overall to the whole
patient population and organizational previsit survey respondents.
Table 1
Patient characteristics
|
Patient characteristics
|
All participants (N = 5,731)
|
Chart review participants (N = 320)
|
|
Age, y (mean, SD)
|
7.14 (7.56)
|
7.96 (8.34)
|
|
Gender
|
|
Male
|
3,234 (56.43%)
|
184 (57.50%)
|
|
Female
|
2,497 (43.57%)
|
136 (42.50%)
|
|
Race
|
|
White
|
3,806 (66.41%)
|
202 (63.13%)
|
|
Black
|
262 (4.57%)
|
17 (5.31%)
|
|
Asian
|
223 (3.89%)
|
11 (3.44%)
|
|
Other
|
496 (8.65%)
|
33 (10.31%)
|
|
Unknown
|
944 (16.47%)
|
57 (17.81%)
|
|
Ethnicity
|
|
Hispanic
|
349 (6.09%)
|
25 (7.81%)
|
|
Non-Hispanic
|
4,168 (72.73%)
|
225 (70.31%)
|
|
Unknown
|
1,214 (21.18%)
|
70 (21.88%)
|
|
Preferred language
|
|
English
|
5,518 (96.28%)
|
304 (95.00%)
|
|
Other language
|
213 (3.72%)
|
16 (5.00%)
|
|
Total number of OurDX reports
|
|
|
|
1
|
4,634 (80.86%)
|
316 (98.75%)
|
|
2
|
907 (15.83%)
|
4 (1.25%)
|
|
≥3
|
190 (3.32%)
|
0
|
|
Total number of chronic conditions (mean, SD)
|
N/A
|
1.77 (1.17)
|
|
Total number of medications (mean, SD)
|
N/A
|
0.91 (1.30)
|
Abbreviations: N/A, not applicable; SD, standard deviation.
Note: number of chronic conditions and medications were extracted on chart review
and therefore were not available (n/a) for the entire patient population.
Patient/Family Contributions
Participants made multiple contributions to the DxP, reflected in the visit priorities,
recent medical history, and potential diagnostic concerns, across all 10 categories
including: access problems, medical history, information on medications, interdisciplinary
information, recent visits at other health care centers, problems/delays with tests/referrals,
communication issues, care coordination, explanation/next steps, or other. A comparison
of the mean number of patient/family contribution categories is shown in [Table 2]. Overall, patients and families contributed information in a mean of 2 to 3 categories,
with a range from 1 to 8. We did not observe statistically significant differences
in the mean number of contribution categories by race, ethnicity, or preferred language.
Table 2
Patient contributions in OurDX by patient sociodemographic factors
|
Patient characteristics
|
N = 314
|
Mean number of contributions
|
Standard deviation
|
p-Value
|
|
Race
|
0.079
|
|
White
|
198
|
3.06
|
1.50
|
|
|
Black/African American
|
17
|
2.41
|
0.87
|
|
|
Other
|
32
|
2.66
|
1.45
|
|
|
Asian
|
11
|
2.09
|
0.83
|
|
|
Unknown
|
56
|
3.00
|
1.62
|
|
|
Ethnicity
|
0.584
|
|
Non-Hispanic
|
220
|
3.00
|
1.49
|
|
|
Hispanic
|
25
|
2.76
|
1.61
|
|
|
Unknown
|
69
|
2.83
|
1.41
|
|
|
Language preference
|
0.385
|
|
English
|
298
|
2.96
|
1.46
|
|
|
Other than English
|
16
|
2.63
|
1.86
|
|
Notes: Contributions were coded from patient reports with actionable information.
Of the 320 participants in the chart review sample, 6 (1.9%) did not have reports
with actionable information, resulting in n = 314.
Patient/Family Diagnostic Concerns
Overall, 10.6% of unique participants identified at least one potential diagnostic
concern, with a total of 609 participants reporting 735 potential diagnostic concerns
during the study. The most common patient diagnostic concerns included problems/delays
with tests or referrals (379/735; 51.6%), problems/delays related to diagnosis or
next steps (257/735; 35.0%), and patients/families feeling their main concern was
not heard (232/735; 31.6%). Factors associated with reporting a potential diagnostic
concern are shown in [Table 3]. Compared with 9.2% of White respondents, 14.0 to 15.3% of respondents self-identifying
as Black, Asian, or “other” race reported a diagnostic concern. Patients self-identifying
as Black or “other” race were significantly more likely to report a potential diagnostic
concern than those self-identifying as white (odds ratio: [OR]: 1.70; 95% confidence
interval [CI]: [1.18, 2.43] and OR: 1.48; 95% CI: [1.08, 2.03], respectively). Similarly,
compared with 10.1% of English-preferring participants, 25.1% of individuals who preferred
a language other than English reported a potential diagnostic concern; (OR: 2.53;
95% CI: [1.78, 3.59]. Notably, reports from participants who preferred a language
other than English were five times as likely to indicate that the main concern had
not been heard, as opposed to reports from English-preferring participants (3.4% English-preferring
vs. 16.9% with another language preference, [Supplementary Appendix C], available in the online version). We did not observe any significant differences
by patient gender or ethnicity.
Table 3
Multiple logistic regression of sociodemographic factors associated with identification
of patient diagnostic concerns (N = 5731)
|
Variable
|
% patients with diagnostic concerns
|
OR
|
95% CI
|
p-Value
|
|
Age, y (mean, SD)
|
7.39 (8.30)
|
1.006
|
0.995
|
1.017
|
0.253
|
|
Gender
|
|
|
|
|
0.208
|
|
Female
|
10.00%
|
0.895
|
0.753
|
1.064
|
|
|
Male (ref)
|
11.11%
|
|
|
|
|
|
Race
|
|
|
|
|
0.006
|
|
White (ref)
|
9.18%
|
|
|
|
|
|
Asian
|
14.03%
|
1.411
|
0.943
|
2.112
|
|
|
Black
|
14.94%
|
1.692
|
1.181
|
2.426
|
|
|
Other
|
15.32%
|
1.478
|
1.078
|
2.028
|
|
|
Unknown
|
11.90%
|
1.258
|
0.920
|
1.719
|
|
|
Ethnicity
|
|
|
|
|
0.935
|
|
Non-Hispanic or Latino (ref)
|
10.14%
|
|
|
|
|
|
Unknown
|
11.29%
|
1.035
|
0.776
|
1.381
|
|
|
Hispanic
|
14.08%
|
0.954
|
0.656
|
1.386
|
|
|
Language preference
|
|
|
|
|
<0.0001
|
|
English (ref)
|
10.07%
|
|
|
|
|
|
Other than English
|
25.12%
|
2.528
|
1.783
|
3.586
|
|
Abbreviations: CI, confidence interval; OR, odds ratio; ref, reference.
Note: Mean and standard deviation of age with at least one patient diagnostic concern
were reported.
Clinician Verification of Patient Diagnostic Concerns
Across patient population groups, the majority (61.5–84.6%) had diagnostic concerns
that were confirmed on physician–researcher review ([Table 4]). We did not observe any significant differences in the proportion of confirmed
patient diagnostic concerns when compared by patient sociodemographic characteristics,
although the total number of patient-reported diagnostic concerns were very small
in some subgroups.
Table 4
Clinician verification of patient diagnostic concerns in chart review sample
|
Patient characteristic
|
N = 213
|
Clinician-verified patient diagnostic concern, n (%)
|
p-Value
|
|
Race
|
0.9057
|
|
White
|
129
|
91 (70.54%)
|
|
|
Black/African American
|
13
|
8 (61.54%)
|
|
|
Other
|
24
|
16 (66.67%)
|
|
|
Asian
|
8
|
6 (75.00%)
|
|
|
Unknown
|
39
|
29 (74.36%)
|
|
|
Ethnicity
|
0.96
|
|
Non-Hispanic
|
146
|
102 (69.86%)
|
|
|
Hispanic
|
17
|
12 (70.59%)
|
|
|
Unknown
|
50
|
36 (72.00%)
|
|
|
Language preference
|
0.2472
|
|
English
|
200
|
139 (69.50%)
|
|
|
Another language
|
13
|
11 (84.62%)
|
|
Integration of Patient/Family Priorities into the Visit Note
In total, 294 (90.7%) OurDX reports in the 324 chart reviews provided visit priorities.
Among these, 191(65.0%) of clinician notes included all patient/family documented
priorities. In addition, 97 (33.0%) included some patient/family priorities. We did
not observe any differences in the likelihood of clinicians including all patient/family
priorities in the note by patient race, ethnicity, or preferred language ([Table 5]).
Table 5
Multiple logistic regression of patient/family priorities included in clinician note
by sociodemographic characteristics (n = 320)
|
Variable
|
% of patients with all priorities included in note
|
OR
|
95% CI
|
p-Value
|
|
Age, y
|
7.64 (8.58)
|
0.987
|
0.959
|
1.016
|
0.365
|
|
Gender
|
|
|
|
|
0.109
|
|
Female
|
58.87%
|
0.663
|
0.400
|
1.097
|
|
|
Male (ref)
|
70.06%
|
|
|
|
|
|
Race
|
|
|
|
|
0.585
|
|
White (ref)
|
64.74%
|
|
|
|
|
|
Black/African American
|
83.33%
|
2.483
|
0.52
|
11.852
|
|
|
Other
|
71.43%
|
1.021
|
0.385
|
2.075
|
|
|
Asian
|
50.00%
|
0.598
|
0.143
|
2.498
|
|
|
Unknown
|
62.26%
|
0.645
|
0.250
|
1.661
|
|
|
Ethnicity
|
|
|
|
|
0.219
|
|
Hispanic
|
84.21%
|
2.876
|
0.697
|
11.871
|
|
|
Unknown
|
67.79%
|
1.643
|
0.671
|
4.027
|
|
|
Non-Hispanic (ref)
|
62.80%
|
|
|
|
|
|
Language preference
|
|
|
|
|
0.753
|
|
Other than English
|
77.78%
|
1.329
|
0.225
|
7.835
|
|
|
English (ref)
|
64.89%
|
|
|
|
|
Abbreviations: CI, confidence interval; OR, odds ratio; ref, reference.
Discussion
Our study of over 5,700 patients and families attending 7,075 ambulatory visits with
medical and surgical subspecialists demonstrates that OurDX can serve as a structured
tool to invite contributions to the DxP from patients/families of varying backgrounds.
Although responses were more common among individuals identifying as White or English-preferring,
when patients/families at greater risk of health care disparities did participate,
they provided important contributions and were more likely to report potential diagnostic
concerns than their counterparts. Although clinicians may be skeptical about the clinical
relevance or interpretability of diagnostic concerns reported by some patients at
risk of health disparities—such as those with limited English proficiency—the majority
were confirmed on clinician review and we observed no differences in the likelihood
of clinician verification by patient sociodemographics, although the small numbers
in some subgroups require further study.
Our findings underscore that the ability of patients/families to identify DxPs at
risk may depend on how the question is asked. Despite known underreporting of error
among patient populations potentially at risk of health disparities,[10]
[20] eliciting process measures like whether patients felt heard or experienced specific
problems or delays related to the DxP actually yielded higher reporting of diagnostic concerns from patients and families self-identifying as Black
or other race and among patients and families preferring a language other than English
compared with their counterparts, respectively. This may be explained at least in
part by patients who may not understand the term “error”; may not be sure about whether
their experience constitutes an error; or may harbor greater concerns for reporting
an error, due to fear of retaliation or other ill-effects on the patient–clinician
relationship.[7]
[15]
[17]
[44]
[45] A tool that empowers patients/families by routinely eliciting their DxP concerns
in basic terms (i.e., “did you feel heard?”) and in the comfort and safety of their
own home may help overcome some of these barriers, although additional support to
participate is needed.
Because patient/family reported diagnostic concerns in OurDX reports were available
to the clinician at the time of the visit, these reports present a unique opportunity
to act upon potential diagnostic safety opportunities at the point of care, thus helping
to prevent downstream diagnostic errors. Recognizing and addressing patient concerns
such as not feeling heard and problems or delays in tests, referrals, diagnosis, or
next steps are critical to improve diagnostic safety[7]
[14]
[15] and may be particularly vital for patients and families from historically marginalized
communities, who may be at greater risk for diagnostic error.[11] For example, our findings indicate that reports from patients/families who prefer
a language other than English were more than five times as likely to indicate that
the patient/family's main concern was not heard. Identification of such patient/family
diagnostic concerns may prompt clinicians to listen more intently, check for understanding,
ensure the use of interpreters when needed, or use “teach back” principles to ensure
greater alignment between patients/families and clinicians,[46]
[47]
[48]
[49] behaviors that were not measured in this study but that may particularly benefit
individuals at risk of diagnostic error. Eliciting information before the visit might
also help ameliorate potential implicit bias on the part of the provider, although
further research is needed.[50] Finally, systematically asking patient/family priorities and concerns through OurDX
before the visit may help tackle disparities by better aligning patient–clinician
agendas and shared understanding. Taken together, these factors suggest that OurDX
may help clinicians identify and address at least some equity gaps in diagnostic safety.
We did not find significant differences in clinician integration of patient/family
priorities into the visit note by patient sociodemographic characteristics, although
larger studies are needed. This is an important issue because cultural differences,
language barrier, implicit bias, or miscomprehension may otherwise result in misalignment
between patients/families and clinicians regarding the significance of patient symptoms
or concerns.[36] Such misalignments between patients and clinicians have been associated with diagnostic
delay and diagnostic blindspots.[16]
[51] Documenting priorities and histories in patient or family member's own words may
also help to improve the accuracy of notes.[52] This may be of particular benefit to patients at risk of healthcare disparities
since inaccurate records were an important contributing factor cited by patients with
limited English language health literacy or disadvantaged socioeconomic position who
reported a diagnostic error in a U.S. population-based survey.[7]
Finally, recent data demonstrate that negative descriptors are more commonly found
in the EHRs of patients self-identifying as a racial minority and may exacerbate health
care disparities.[53]
[54]
[55] Stigmatizing language can be transmitted in the EHR, affecting the attitudes and
practices of other clinicians.[56]
[57] Sharing and cogenerating notes with patients and families may help raise awareness
about more neutral and respectful EHR language. Further research is needed to test
whether incorporating patient and family priorities and histories in notes may help
mitigate this disparity.
Strengths and Limitations
Strengths and Limitations
Although the study included over 7,000 patient/family reports, the overall sample
size for marginalized populations was small. In addition, the response rate in our
study was limited, although it exceeded the response rate typical of online surveys.[58]
[59] Like many studies focusing on health disparities related to health information technology
use, it was inherently limited by nonresponse bias, although patients/families self-identifying
a race other than White or a language preference other than English showed a >25%
response rate, exceeding many email surveys.[60] Similar to prior studies using digital surveys, overall response rates to OurDX
were the highest among patients and families who self-identified as White or English-preferring,
highlighting ongoing challenges in addressing the barriers and inequities in accessing
digital tools and digital health literacy, and missed opportunities to learn from
patients, especially those who use interpreters.[61]
[62]
[63]
[64]
[65]
[66] While we tested the intervention at three different medical and surgical subspecialty
clinics, the study involved one site, limiting generalizability.
To mitigate known challenges in patient portal registration among patients and families
facing health disparities, we sent a survey link directly via email, bypassing the
need for a patient portal account and alleviating a potential barrier to survey access.[39]
[67] The survey was written in English, and response rates could be improved with translation
to other languages, and EHR tools that better support patients whose primary language
is not English.[68] Additional factors driving participation that were raised during our study and others
include broader support for speaking up—especially among patients vulnerable to health
disparities, provider encouragement to participate, and reassurance that providers
read patient/family contributions.[17]
[20]
[45]
[69] Patients who prefer a language other than English may already be at a disadvantage
in reviewing notes and may not be able to thus identify and speak up about note inaccuracies.
Our study did not examine socioeconomic factors or other social determinants of health
that may also affect participation. Far more sweeping changes in structural racism,
social justice, health literacy, and information technology are needed to achieve
“Techquity,” “the strategic development and deployment of technology in health care
and health to achieve health equity.”[62] Interventions like OurDX are a humble step and must be further developed in concert
with these broader policy efforts and community participants. Larger studies with
greater diversity are needed to build upon these exploratory findings as well as qualitative
studies that may provide additional rich context to the interpretation of these findings
and future tool refinement.
Conclusion
Emerging research suggests underreporting of medical errors among patient populations
at risk of healthcare disparities. In this exploratory study, use of OurDX—an online
tool to engage patients and families in the DxP—resulted in significantly greater
identification of patient-reported DxP concerns among patients and families from racial
minorities or those who preferred a language other than English, compared with their
respective counterparts. For example OurDX reports among participants preferring a
language other than English were more than 5 times as likely to indicate that the
patient/family's main concern was not heard. Because patient contributions through
OurDX are available at the time of the visit, clinicians may have a greater opportunity
to identify and act on patient/family concerns at the point of care before they may
lead to diagnostic errors. We did not observe differences in the number of DxP contributions,
the proportion of patient/family-reported diagnostic concerns verified on clinician
review, or the likelihood of integrating patient/family contributions into clinician
visit note by clinicians by race, ethnicity, or language preference among those who
used the tool. Greater solicitation and integration of priorities, perspectives, and
concerns of patients at risk of healthcare disparities into the medical record may
help engage more diverse patients in the DxP and ultimately improve diagnostic safety,
but further research with broader patient populations and more in-depth qualitative
studies are needed to address disparity gaps.
Clinical Relevance Statement
Clinical Relevance Statement
Patients and families historically at higher risk of healthcare disparities were more
likely to report diagnostic concerns through an online diagnostic safety tool as compared
with their counterparts, providing an opportunity to engage broader patient populations
in safety, improve under-reporting of concerns, and potentially prevent diagnostic
errors and safety disparities at the point of care, if implemented alongside broader
organizational equity efforts.
Multiple-Choice Questions
Multiple-Choice Questions
-
ALL of the following patient-reported diagnostic concerns were most commonly reported
by patients and families, EXCEPT:
-
Problems or delays with tests or referrals
-
Problems or delays related to diagnosis or next steps
-
Not feeling their main concern was heard by clinicians
-
Delay in medication refill requests
Correct Answer: The correct answer is option d. The most commonly reported patient diagnostic concerns
included problems/delays with tests or referrals, problems/delays related to diagnosis
or next steps, and patients feeling their main concern was not heard.
-
As compared with English-preferring participants, how much more likely were participants
preferring a language other than English to report not feeling heard?
-
1.5 times more likely
-
5 times more likely
-
2.5 times more likely
-
6 times more likely
Correct Answer: The correct answer is option b. 16.9% of individuals who preferred a language other
than English reported not feeling heard as compared with 3.4% of English-preferring
participants.
