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In the past decade, patient-accessible electronic health record (PAEHR) systems have emerged as an important tool for health management both at the hospital level and individual level. However, little is known about the effects of PAEHR portals on the survivorship of patients with chronic health conditions (eg, cancer).
This study aims to investigate the effects of the use of PAEHR portals on cancer survivors’ health outcomes and to examine the mediation pathways through patient-centered communication (PCC) and health self-efficacy.
Data for this study were derived from the Health Information National Trends Survey (HINTS 5, Cycle 4) collected from February 2020 to June 2020. This study only involved respondents who reported having been diagnosed with cancer (N=626). Descriptive analyses were performed, and the mediation models were tested using Model 6 from the SPSS macro PROCESS. Statistically significant relationships among PAEHR portal use, PCC, health self-efficacy, and physical and psychological health were examined using bootstrapping procedures. In this study, we referred to the regression coefficients generated by min-max normalization as percentage coefficients (
No positive direct associations between PAEHR portal use and cancer survivors’ health outcomes were found. The results supported the indirect relationship between PAEHR portal use and cancer survivors’ psychological health via (1) PCC (
This study offers empirical evidence about the significant role of PAEHR portals in delivering PCC, improving health self-efficacy, and ultimately contributing to cancer survivors’ physical and psychological health.
Cancer is among the leading causes of death worldwide, accounting for about 10 million deaths in 2020 [
The maintenance of long-term cancer treatment plans requires effective patient-provider communication and coordination of cancer survivorship care [
The Chronic Care Model (CCM) provides a framework for understanding the mechanisms through which health care provided via PAEHR portals influences patients’ health outcomes [
Proponents of the eCCM contend that eHealth adoption, referred to in this study as PAEHR portal use, is likely to impact health outcomes through indirect pathways, which comprise proximal outcomes (eg, effective patient-provider communication) of eHealth that then influence health or that contribute to intermediate outcomes (eg, health self-efficacy) that lead to improved distal health outcomes [
Following this line, 2 mediators—PCC and health self-efficacy—were conceptualized as the proximal and intermediate outcomes of PAEHR portal use, respectively. Previous research that examined related variables has provided empirical support. For instance, Madhavan et al [
Hypothesis 1: PAEHR portal use is positively related to cancer survivors’ health outcomes.
Hypothesis 2: PCC mediates the relationship between PAEHR portal use and cancer survivors’ health outcomes.
Hypothesis 3: Health self-efficacy mediates the relationship between PAEHR portal use and cancer survivors’ health outcomes.
Hypothesis 4: PCC and health self-efficacy sequentially mediate the relationship between PAEHR portal use and cancer survivors’ health outcomes.
Pathways between patient-accessible electronic health record portal use and health outcomes.
Data for this study were derived from the Health Information National Trends Survey (HINTS 5, Cycle 4) collected from February 2020 to June 2020. HINTS is administered by the National Cancer Institute in the United States to collect nationally representative data about American adults’ access to health-related information, health behaviors, and health outcomes. The survey design and sampling procedures for HINTS have been explicated extensively in previous research [
This study used secondary data. The HINTS data meet strict ethical standards and have obtained ethics approval. Informed consent has been obtained from all participants, and all methods were carried out in accordance with relevant guidelines and regulations.
PAEHR portal use was measured by asking respondents whether they had accessed patient portals of PAEHR in the past year for certain eHealth activities [
PCC consisted of 7 statements that assessed patients’ perceptions of communication with all doctors, nurses, or other health professionals in the past 12 months [
Health self-efficacy was measured using 1 item to assess one’s ability to take care of his/her health on a 5-point scale from 1 (completely confident) to 5 (not confident at all) [
Physical health was measured by 4 items on comorbidities, drawn from prior research of similar measures [
Psychological health was measured by 4 items derived from previous research [
The control variables included demographics such as age, gender (male=1, female=0), education (less than 8 years=1, postgraduate=7), annual household income (US $0-9999=1, US $200,000 or more=9), and race (non-Hispanic White=1, others=0).
Descriptive statistics of the patient-accessible electronic health record portal use and physical health of the participants (N=626).
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Yes | No | Nonvalid | |
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Look up test results | 252 (40.3) | 36 (5.8) | 338 (53.9) |
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Securely message health care provider and staff | 176 (28.1) | 110 (17.6) | 340 (54.3) |
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Download health information to computer or mobile device | 68 (10.9) | 218 (34.8) | 340 (54.3) |
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Diabetes or high blood sugar | 176 (28.1) | 440 (70.3) | 10 (1.6) |
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High blood pressure or hypertension | 374 (59.7) | 244 (39) | 8 (1.3) |
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A heart condition such as heart attack, angina, or congestive heart failure | 91 (14.5) | 527 (84.2) | 8 (1.3) |
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Chronic lung disease, asthma, emphysema, or chronic bronchitis | 132 (21.1) | 486 (77.6) | 8 (1.3) |
Descriptive statistics of patient-centered communication (N=626).
Patient-centered communication | Always, n (%) | Usually, n (%) | Sometimes, n (%) | Never, n (%) | Nonvalid, n (%) |
Give you the chance to ask all the |
393 (62.8) | 142 (22.7) | 39 (6.2) | 3 (0.5) | 49 (7.8) |
Give the attention you needed to your feelings and emotions | 279 (44.6) | 185 (29.6) | 83 (13.3) | 23 (3.7) | 56 (8.9) |
Involve you in decisions about your health care as much as you wanted | 324 (51.8) | 180 (28.8) | 65 (10.4) | 7 (1.1) | 50 (7.9) |
Make sure you understood the things you needed to do to take care of your health | 362 (57.8) | 169 (27) | 43 (6.9) | 3 (0.5) | 49 (7.8) |
Explain things in a way you could understand | 366 (58.5) | 164 (26.2) | 43 (6.9) | 3 (0.5) | 50 (7.9) |
Spend enough time with you | 292 (46.6) | 193 (30.8) | 73 (11.7) | 17 (2.7) | 51 (8.2) |
Help you deal with feelings of uncertainty about your health or health care | 260 (41.5) | 191 (30.5) | 90 (14.4) | 29 (4.6) | 56 (9) |
Descriptive statistics of health self-efficacy (N=626).
Health self-efficacy | Completely confident | Very confident | Somewhat confident | A little confident | Not confident at all | Nonvalid |
How confident are you about your ability to take good care of your health, n (%) | 111 (17.7) | 318 (50.8) | 159 (25.4) | 28 (4.5) | 6 (1) | 4 (0.6) |
Descriptive statistics of psychological health (N=626).
Psychological health | Nearly every day, n (%) | More than half the day, n (%) | Several days, n (%) | Not at all, n (%) | Nonvalid, n (%) |
Little interest or pleasure in doing things | 31 (5) | 53 (8.5) | 123 (19.6) | 404 (64.5) | 15 (2.4) |
Feeling down, depressed, or hopeless | 18 (2.9) | 31 (5) | 122 (19.5) | 436 (69.6) | 19 (3) |
Feeling nervous, anxious, or on edge | 30 (4.8) | 29 (4.6) | 163 (26) | 389 (62.1) | 15 (2.5) |
Not being able to stop or control worrying | 29 (4.6) | 44 (7) | 112 (17.9) | 424 (67.7) | 17 (2.8) |
Data analysis was performed using SPSS version 26 (IBM Corp). First, the MEAN () function was used to compute the mean of multiple-item variables that at least one item has a valid value or single-item variables that have valid values. Otherwise, the cases were considered missing in the following analysis. Besides, as a complementary technique, min-max normalization [
The mean age of the cancer survivors was 67.46 (SD 13.19; range 19-104) years. There were more female respondents (370/626, 59.1%) than male respondents (256/626, 40.9%). The majority of the participants had received some college education (405/626, 64.7%), were non-Hispanic White (428/626, 68.4%), and had annual household income between US $35,000 and US $74,999 (259/626, 41.4%). The detailed demographic information is summarized in
Sample population characteristics (N=626).
Characteristic | Value | ||
Age in years, mean (SD) | 67.46 (13.19) | ||
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Male | 256 (40.9) | |
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Female | 370 (59.1) | |
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Less than 8 years of education | 14 (2.2) | |
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8-11 years of education | 29 (4.6) | |
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12 years of education or completed high school | 132 (21.1) | |
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Post high school training other than college | 46 (7.3) | |
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Some college | 143 (22.8) | |
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College graduate | 145 (23.2) | |
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Postgraduate | 117 (18.7) | |
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0-9999 | 33 (5.3) | |
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10,000-14,999 | 34 (5.4) | |
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15,000-19,999 | 37 (5.9) | |
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20,000-34,999 | 79 (12.6) | |
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35,000-49,999 | 87 (13.9) | |
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50,000-74,999 | 172 (27.5) | |
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75,000-99,999 | 58 (9.3) | |
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100,000-199,999 | 94 (15) | |
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200,000 or more | 32 (5.1) | |
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Non-Hispanic White | 428 (68.4) | |
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Others | 198 (31.6) |
Hypothesis 1 posited that PAEHR portal use is positively related to cancer survivors’ health outcomes.
Hypothesis 2 predicted that PCC mediates the relationship between PAEHR portal use and cancer survivors’ health outcomes. As depicted in
Hypothesis 3 predicted that PAEHR portal use might increase cancer survivors’ health outcomes through the mediation of association with health self-efficacy. The mediation effects in the 2 models were statistically unacknowledged. Thus, hypothesis 3 was not supported.
Hypothesis 4 predicted that PAEHR portal use will be related to cancer survivors’ health outcomes through the serial mediation of PCC and health self-efficacy. As shown in
Mediation modelsa.
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SE | 95% CI | ||||||
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PAEHRd→PCCe ( |
0.131 | .125 | .042 | .048 to .214 | .002 | ||||
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PAEHR→Health self-efficacy ( |
0.022 | .021 | .055 | –.078 to .137 | .59 | ||||
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PCC→Health self-efficacy ( |
0.270 | .269 | .052 | .258 to .461 | <.001 | ||||
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PCC→Psychological health ( |
0.217 | .186 | .046 | .127 to .306 | <.001 | ||||
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Health self-efficacy→Psychological health ( |
0.181 | .156 | .034 | .068 to .202 | <.001 | ||||
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PAEHR→Psychological health (direct effect, |
–0.016 | –.013 | .046 | –.108 to .075 | .73 | ||||
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PAEHR→Psychological health (total effect, |
0.023 | .018 | .048 | –.072 to .117 | .64 | ||||
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PAEHR→PCC→ Psychological health (indirect effect, |
0.029 | .023 | .012 | .009 to .054 | N/Af | ||||
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PAEHR→PCC→ Health self-efficacy→Psychological health (indirect effect, |
0.006 | .005 | .003 | .002 to .014 | N/A | ||||
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PAEHR→Health self-efficacy→Psychological health (indirect effect, |
0.004 | <.001 | .008 | –.012 to .020 | N/A | ||||
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PAEHR→PCC ( |
0.131 | .125 | .042 | .048 to .214 | .002 | ||||
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PAEHR→Health self-efficacy ( |
0.022 | .021 | .055 | –.078 to .137 | .59 | ||||
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PCC→Health self-efficacy ( |
0.270 | .269 | .052 | .258 to .461 | <.001 | ||||
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PCC→Physical health ( |
0.013 | .010 | .070 | –.120 to .154 | .81 | ||||
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Health self-efficacy→Physical health ( |
0.168 | .126 | .052 | .066 to .270 | .001 | ||||
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PAEHR→Physical health (direct effect, |
–0.032 | –.023 | .071 | –.183 to .096 | .55 | ||||
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PAEHR→Physical health (total effect, |
–0.021 | –.015 | .071 | –.168 to .112 | .69 | ||||
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PAEHR→PCC→Physical health (indirect effect, |
0.002 | .001 | .011 | –.020 to .024 | N/A | ||||
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PAEHR→PCC→Health self-efficacy→Physical health (indirect effect, |
0.006 | .004 | .004 | .002 to .018 | NA | ||||
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PAEHR→Health self-efficacy→Physical health (indirect effect, |
0.004 | .003 | .010 | –.015 to .026 | N/A |
aa1, a2, b1, b2, and l1 in this table indicate the pathways between patient-accessible electronic health record portal use and health outcomes and the effects.
bRegression coefficient generated by min-max normalization as percentage coefficient.
c
dPAEHR: patient-accessible electronic health record.
ePCC: patient-centered communication.
fN/A: not applicable.
In light of the existing literature on the robust salutary effects of PAEHR portals on patient health, our study examined the effects of PAEHR portal use on cancer survivors’ health outcomes as well as the mediating roles of PCC and health self-efficacy. The results of our study indicated that the significant effect of PAEHR portal use on cancer survivors’ physical and psychological health was indirect through the mediated associations with PCC and health self-efficacy.
The direct association between PAEHR portal use and cancer survivors’ health outcomes is not acknowledged in this study. The findings of our study emphasize the mediation mechanisms through which the PAEHR portal use exerts an influence on cancer survivors’ physical and psychological health, which were in accordance with that reported in previous research that theorizes the process through which PAEHR may impact patient health [
PCC and health self-efficacy were identified as the intrinsic and extrinsic factors of PAEHR, respectively, that help explain how PAEHR portal use influences patients’ health outcomes. The results of our study suggest that PCC can partially mediate the relationship between PAEHR portal use and cancer survivors’ psychological health. The mediation results indicated that the more cancer survivors use the PAEHR portals to stay informed about their health and communicate with health care professionals, the more likely they are to perceive PCC, which in turn results in more positive psychological health. A plausible reason is that the increasing accessibility to health professionals and patient information facilitated by PAEHR systems may enhance patient involvement in their health care decision-making [
The results of our study showed that PCC is positively associated with health self-efficacy, and higher levels of health self-efficacy can enhance cancer survivors’ physical and psychological health. This finding was consistent with prior research, suggesting that PCC may empower patients, help increase their self-care skills, and provide the needed information and support to facilitate patients’ health management [
Our study in comparison with previous work has heuristic value for public health research in several ways. First, the findings of our study offer empirical support for eCCM [
This study also has important practical implications. First, given the important role of electronic means for health management, multifaceted strategies should be implemented to promote the assimilation of PAEHR at both institutional and individual levels. For example, through patient education and support, patients can gain knowledge about PAEHR and be encouraged to integrate PAEHR into their health care in everyday life. Besides, we should also encourage medical professionals to engage in PAEHR systems to provide customized health care services. For example, a medical professional can provide detailed explanations for certain clinical decisions through PAEHR portals, and patients can access and revisit the messages that can facilitate their self-care practices [
Several limitations of this study should be noted. First, owing to the cross-sectional design of HINTS, we know little about the causal inferences of relationships examined in this study. Further research should collect panel data or use experimental research designs to better understand the relationships among PAEHR portal use, PCC, health self-efficacy, and health outcomes. Second, according to CCM and eCCM, there are 6 key components of eHealth technologies for care delivery, such as health system support and delivery system design. However, PAEHR portal use in this study was measured using 3 items, that is, patients’ past experience in PAEHR portal use for checking test results, patient-provider communication, and health information acquisition. We know little about the influence of other aspects of PAEHR portal use. To our knowledge, no study has examined the usability of PAEHR system design and how it impacts patient-provider communication and patients’ health maintenance. Besides, PAEHR portal use was examined as an integrated concept, and we hardly know how different types of PAEHR portal usage may affect patient health differently. Based on this study, future research should take into account the different use dimensions of PAEHR systems or the different types of PAEHR portal usage and compare their different influences. Third, PCC and health self-efficacy were identified as the mediators in the relationship between PAEHR portal use and cancer survivors’ health outcomes. Other potential interveners might be overlooked. Researchers should further extend the model and identify other mediators (eg, knowledge) or moderators (eg, health literacy, digital literacy) that significantly influence PAEHR portal users’ health-related outcomes. Fourth, the research findings of our study might be impacted by sampling bias. For example, more than half of the respondents were aged between 60 years and 80 years (mean 67.46 years) and had at least completed some college education. It is recommended that a more representative sample be analyzed to better understand the full range of cancer survivors’ PAEHR portal use. Moreover, our study focused on cancer survivors, and the results may not be generalizable to other populations. PAEHR portals can likely be helpful and useful for people with other chronic conditions such as diabetes and asthma. Thus, researchers should replicate this work in other populations to obtain more tentative evidence, thereby supporting the positive association between PAEHR portal use and health outcomes.
This study offers empirical evidence on the influence of PAEHR portal use on cancer survivors’ physical and psychological health. Although electronic technologies have been widely applied in health care settings, the adoption rate of PAEHR among patients remains low. This study suggests that PAEHR portal use is vital in delivering longitudinal survivorship care for cancer survivors. In particular, the influence of PAEHR portal use on health outcomes may be indirect through the mediated associations with PCC care and health self-efficacy. Understanding these relationships can help increase the use of PAEHR portals, promote PCC, enhance patients’ health self-efficacy, and eventually improve their physical and psychological health.
Chronic Care Model
eHealth enhanced Chronic Care Model
Health Information National Trends Survey
patient-accessible electronic health record
patient-centered communication
This research was supported in part by grants of the University of Macau, ICI-RTO-0010-2021, CPG20XX-00035-FSS, and SRG20XX-00143-FSS, and a grant of Macau Higher Education Fund (HSS-UMAC-2020-02).
The data sets generated and analyzed during this study are publicly available on [
None declared.