Published on in Vol 24 , No 10 (2022) :October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39614, first published .
The Effects of the Use of Patient-Accessible Electronic Health Record Portals on Cancer Survivors’ Health Outcomes: Cross-sectional Survey Study

The Effects of the Use of Patient-Accessible Electronic Health Record Portals on Cancer Survivors’ Health Outcomes: Cross-sectional Survey Study

The Effects of the Use of Patient-Accessible Electronic Health Record Portals on Cancer Survivors’ Health Outcomes: Cross-sectional Survey Study

Original Paper

Department of Communication, Faculty of Social Sciences, University of Macau, Taipa, Macao

Corresponding Author:

Xinshu Zhao, PhD

Department of Communication

Faculty of Social Sciences

University of Macau

Room 2051, Humanities & Social Sciences Building (E21B)

Taipa

Macao

Phone: 853 8822 8837

Email: xszhao@um.edu.mo


Background: 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).

Objective: 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.

Methods: 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 (bp). The 95% bootstrapped CIs were used with 10,000 resamplings.

Results: 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 (bp=0.029; β=.023, 95% CI .009-.054), and (2) PCC and health self-efficacy in sequence (bp=0.006; β=.005, 95% CI .002-.014). Besides, the indirect association between PAEHR portal use and cancer survivors’ physical health (bp=0.006; β=.004, 95% CI .002-.018) via sequential mediators of PCC and health self-efficacy was also statistically acknowledged.

Conclusions: 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.

J Med Internet Res 2022;24(10):e39614

doi:10.2196/39614

Keywords



Cancer is among the leading causes of death worldwide, accounting for about 10 million deaths in 2020 [1]. In 2021, 1.9 million new cancer cases were diagnosed and over 600,000 cancer deaths were estimated in the United States [2]. Due to the growing and aging population as well as increases in early diagnoses and advances in cancer treatments, the number of cancer survivors continues to increase [3]. According to the National Cancer Institute, “An individual is considered a cancer survivor from the time of diagnosis, through the balance of his or her life” [4]. Cancer is viewed as a chronic illness, and cancer survivors face ongoing health challenges that call for unique and long-term survivorship care. This is because physical problems such as functional disability and impairment and psychological disorders due to illness and aggressive treatments might persist throughout cancer survivors’ lifetime [3,5]. As such, delivering high-quality and long-term health care for cancer survivors becomes a major challenge facing public health.

The maintenance of long-term cancer treatment plans requires effective patient-provider communication and coordination of cancer survivorship care [6,7]. Health care information technology has brought about a massive change in cancer care. The transition to patient-accessible electronic health record (PAEHR) systems has changed the way patients and providers engage in health care by facilitating access to patient information (eg, test results) [8], allowing timely and efficient patient-provider communication [9], reducing medical errors [10], educating patients with accessible and affordable health materials [11], and enhancing the privacy and security of patient data [12]. Therefore, researchers generally agree that PAEHR portals have the potential to improve health through evidence-based medicine and effective care coordination [13]. For instance, Wani and Malhotra [14] provided empirical evidence supporting that the assimilation of PAEHRs at a hospital-wide level can help deliver quality care and services, which in turn improve patients’ health outcomes. A systematic review conducted by Kruse et al [13] identified a variety of facilitators of PAEHRs that can improve population health, including the enhancement in productivity/efficiency, the increase in the quality of patient data, and more flexible data management. Nevertheless, the majority of existing studies have inevitably investigated the PAEHR system from perspectives on professionals’ innovation adoption [15] or organizational management [16]. There remains a paucity in the literature on the use of PAEHR portals and health outcomes from patient perspectives. To address this literature gap, our study aims to investigate how PAEHR portal use influences cancer survivors’ health outcomes.

The Chronic Care Model (CCM) provides a framework for understanding the mechanisms through which health care provided via PAEHR portals influences patients’ health outcomes [17]. Six key interdependent components of CCM that are essential for care delivery have been identified: (1) health system support, (2) delivery system design, (3) clinical information systems, (4) community resources, (5) decision support, and (6) self-management support. Researchers suggest that the PAEHR portal may be a prominent tool that incorporates the key elements of CCM and determines the success of care delivery and health management [18]. CCM relies on the use of health information technology for both public and private health care systems to facilitate the provision of longitudinal and patient-centered care, improve patient engagement, and empower patients with self-care skills to manage chronic illness [18,19]. Gee et al [19] proposed a revised CCM—eHealth enhanced CCM (eCCM)—and explicated that the use of eHealth technologies can help improve chronic care (eg, through patient-centered communication [PCC], clinical decision support, information provision, health education). Consequently, experienced PAEHR users have higher health self-efficacy and can achieve improved health outcomes [19].

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 [19]. Rathert et al [20] provide tentative support for the serial mediation effect of PCC and health self-efficacy in the relationship between PAEHR portal use and health outcomes. PCC is about delivering health care that relies upon effective communication and empathy to meet individual patient preferences, needs, and values [21,22]. Health self-efficacy refers to people’s beliefs regarding one’s capabilities to execute the courses of action to improve health [23]. There is a general consensus that the PAEHR is more than a tool that serves for patient data collection and information exchange. It is a “third agent” during patient care encounters that essentially improves PCC [20,24]. For example, patients who used PAEHR portals prior to doctor visits reported that communication with their physicians improved considerably [25]. This is because the patient data in the PAEHR system enables providers to monitor patients’ symptoms and medication adherence [26]. Physicians thus would spend much time and pay more attention to patients during clinical encounters [27]. Meanwhile, patients who used PAEHR portals perceived more PCC, as they felt empowered to ask questions or offer comments regarding their health problems [24,28]. By this token, PAEHR portal use and PCC can facilitate patients’ management of their health and should eventually contribute to health improvement [20,21,29]. Street et al [29] proposed a pathway model of health communication and suggested that, in most cases, PCC affects patient health through a more indirect route via an intermediate outcome of communication, such as health self-efficacy. It is understandable that PCC can increase patients’ health self-efficacy because providers’ clear explanations and expressions of support could increase patient knowledge and shared understanding, motivate patients to follow through with treatment recommendations, and thus improve patients’ confidence in self-care management.

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 [30] found that due to the transportability and interoperability, effective use of PAEHR contributes to improved PCC, which plays a cardinal role in cancer survivors’ health management. Guo et al [31] found that eHealth adoption (eg, seeking web-based health information and using health apps) was significantly associated with improved self-care skills, which further led to more positive self-rated health among Taiwanese patients with chronic diseases [31]. Liu and Yeo [22] conceptualized a framework, suggesting that web-based patient-provider communication via eHealth technologies may improve patients’ quality of life through sequential mediators of patient-centered care and health management skills. Building on prior research, this study aims to examine the relationships among cancer survivors’ PAEHR portal use, PCC, health self-efficacy, and health outcomes. Moreover, the mediation roles of PCC and health self-efficacy were tested. Thus, the following direct and indirect relationships between PAEHR portal use and cancer survivors’ health outcomes (see Figure 1) were proposed:

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.

Figure 1. Pathways between patient-accessible electronic health record portal use and health outcomes. a1, a2, b1, b2, and l1 indicate the pathways and the effects. PAEHR: patient-accessible electronic health record; PCC: patient-centered communication.
View this figure

Study Design and Sample Population

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 [32]. The final sample of HINTS 5, Cycle 4 consisted of 3865 respondents (response rate=36.7%) of the 10,531 participants. This study only involved respondents who reported having been diagnosed with cancer (N=626).

Ethical Considerations

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.

Measures

PAEHR portal use was measured by asking respondents whether they had accessed patient portals of PAEHR in the past year for certain eHealth activities [33]. Three items were included: “Look up test results,” “securely message health care provider and staff,” and “download health information to computer or mobile device.” Responses were dichotomous (no=0, yes=1) and added up to represent PAEHR portal use (mean 1.726, SD 0.575).

PCC consisted of 7 statements that assessed patients’ perceptions of communication with all doctors, nurses, or other health professionals in the past 12 months [21,34]. A 4-point Likert scale (1=always, 4=never) was used. Responses to the 7 statements were reversely coded and averaged to create the index of PCC, and higher values represent high levels of PCC (mean 3.414, SD 0.607; Cronbach α=.93).

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) [23]. Respondents’ answers were reversely scored, and a higher score represented a higher level of health self-efficacy (mean 3.804, SD 0.812).

Physical health was measured by 4 items on comorbidities, drawn from prior research of similar measures [35]. Respondents were asked whether they had been told by a doctor or another health professional that they had medical conditions such as (1) diabetes or high blood sugar; (2) high blood pressure or hypertension; (3) a heart condition such as heart attack, angina, or congestive heart failure; and (4) chronic lung disease, asthma, emphysema, or chronic bronchitis. Responses to these items were dichotomous (no=0, yes=1). The answers were added up, and a higher value indicated better physical health (mean 2.748, SD 1.082).

Psychological health was measured by 4 items derived from previous research [36]. Sample items included “feeling down, depressed, or hopeless” and “feeling nervous, anxious, or on edge.” The 4 items were measured on a 4-point scale (1=nearly every day to 4=not at all) and averaged to form a composite score representing psychological health (mean 3.502, SD 0.706; Cronbach α=.88). A higher value suggests better psychological health. The descriptive details of the focal variables are shown in Tables 1-4.

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).

Table 1. Descriptive statistics of the patient-accessible electronic health record portal use and physical health of the participants (N=626).

YesNoNonvalid
Patient-accessible electronic health record portal use, n (%)

Look up test results252 (40.3)36 (5.8)338 (53.9)

Securely message health care provider and staff176 (28.1)110 (17.6)340 (54.3)

Download health information to computer or mobile device68 (10.9)218 (34.8)340 (54.3)
Physical health, n (%)

Diabetes or high blood sugar176 (28.1)440 (70.3)10 (1.6)

High blood pressure or hypertension374 (59.7)244 (39)8 (1.3)

A heart condition such as heart attack, angina, or congestive heart failure91 (14.5)527 (84.2)8 (1.3)

Chronic lung disease, asthma, emphysema, or chronic bronchitis132 (21.1)486 (77.6)8 (1.3)
Table 2. Descriptive statistics of patient-centered communication (N=626).
Patient-centered communicationAlways, n (%)Usually, n (%)Sometimes, n (%)Never, n (%)Nonvalid, n (%)
Give you the chance to ask all the health-related questions you had393 (62.8)142 (22.7)39 (6.2)3 (0.5)49 (7.8)
Give the attention you needed to your feelings and emotions279 (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 wanted324 (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 health362 (57.8)169 (27)43 (6.9)3 (0.5)49 (7.8)
Explain things in a way you could understand366 (58.5)164 (26.2)43 (6.9)3 (0.5)50 (7.9)
Spend enough time with you292 (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 care260 (41.5)191 (30.5)90 (14.4)29 (4.6)56 (9)
Table 3. Descriptive statistics of health self-efficacy (N=626).
Health self-efficacyCompletely confidentVery confidentSomewhat confidentA little confidentNot confident at allNonvalid
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)
Table 4. Descriptive statistics of psychological health (N=626).
Psychological healthNearly every day, n (%)More than half the day, n (%)Several days, n (%)Not at all, n (%)Nonvalid, n (%)
Little interest or pleasure in doing things31 (5)53 (8.5)123 (19.6)404 (64.5)15 (2.4)
Feeling down, depressed, or hopeless18 (2.9)31 (5)122 (19.5)436 (69.6)19 (3)
Feeling nervous, anxious, or on edge30 (4.8)29 (4.6)163 (26)389 (62.1)15 (2.5)
Not being able to stop or control worrying29 (4.6)44 (7)112 (17.9)424 (67.7)17 (2.8)

Data Analysis

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 [37] was introduced to compare the estimates of all the paths in the mediation model. Specifically, all research variables were converted into a common measurement scale of 0 to 1. For example, we can subtract 1 from a 5-point rating to adjust the scale to start at 0 and then divide it by 4 to compress the scale. In this study, we referred to the regression coefficients generated by min-max normalization as percentage coefficients (bp) [38,39]. Second, the mean substitution was used for all missing cases. Third, descriptive statistics was analyzed. Fourth, 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. The 95% bootstrapped CIs were used with 10,000 resamplings.


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 Table 5.

Table 5. Sample population characteristics (N=626).
CharacteristicValue
Age in years, mean (SD)67.46 (13.19)
Gender, n (%)

Male256 (40.9)

Female370 (59.1)
Education, n (%)

Less than 8 years of education14 (2.2)

8-11 years of education29 (4.6)

12 years of education or completed high school132 (21.1)

Post high school training other than college46 (7.3)

Some college143 (22.8)

College graduate145 (23.2)

Postgraduate117 (18.7)
Annual income (USD), n (%)

0-999933 (5.3)

10,000-14,99934 (5.4)

15,000-19,99937 (5.9)

20,000-34,99979 (12.6)

35,000-49,99987 (13.9)

50,000-74,999172 (27.5)

75,000-99,99958 (9.3)

100,000-199,99994 (15)

200,000 or more32 (5.1)
Race, n (%)

Non-Hispanic White428 (68.4)

Others198 (31.6)

Hypothesis 1 posited that PAEHR portal use is positively related to cancer survivors’ health outcomes. Table 6 shows that there was no significant direct association between PAEHR portal use and cancer survivors’ health outcomes, irrespective of the physical or psychological health. Thus, hypothesis 1 was not supported.

Hypothesis 2 predicted that PCC mediates the relationship between PAEHR portal use and cancer survivors’ health outcomes. As depicted in Table 6, PAEHR portal use was significantly and positively associated with PCC (bp=0.131; β=.125, 95% CI .048-.214; P=.002) in the 2 models. Meanwhile, PCC was positively associated with cancer survivors’ psychological health (bp=0.270; β=.269, 95% CI .258-.461; P<.001). No significant relationship between PCC and cancer survivors’ physical health was acknowledged. The results indicated that PCC indeed mediated the relation between PAEHR portal use and cancer survivors’ psychological health (bp=0.029; β=.023, 95% CI .009-.054), whereas the counterpart effect failed to pass the statistical threshold (95% CI contained zero) for physical health. Hypothesis 2 was partially supported.

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 Table 6, the indirect relationship between PAEHR portal use and cancer survivors’ physical health (bp=0.006; β=.004, 95% CI .002-.018) and between PAEHR portal use and psychological health (bp=0.006; β=.005, 95% CI .002-.014) via sequential mediators of PCC and health self-efficacy were statistically acknowledged, thereby supporting hypothesis 4.

Table 6. Mediation modelsa.

bpbβSE95% CIP valuec
Dependent variable: Psychological health (Model 1)

PAEHRd→PCCe (a1 path)0.131.125.042.048 to .214.002

PAEHR→Health self-efficacy (a2 path)0.022.021.055–.078 to .137.59

PCC→Health self-efficacy (l1 path)0.270.269.052.258 to .461<.001

PCC→Psychological health (b1 path)0.217.186.046.127 to .306<.001

Health self-efficacy→Psychological health (b2 path)0.181.156.034.068 to .202<.001

PAEHR→Psychological health (direct effect, d path)–0.016–.013.046–.108 to .075.73

PAEHR→Psychological health (total effect, c path)0.023.018.048–.072 to .117.64

PAEHR→PCC→ Psychological health (indirect effect, a1xb1)0.029.023.012.009 to .054N/Af

PAEHR→PCC→ Health self-efficacy→Psychological health (indirect effect, a1xb2xl1)0.006.005.003.002 to .014N/A

PAEHR→Health self-efficacy→Psychological health (indirect effect, a2xb2)0.004<.001.008–.012 to .020N/A
Dependent variable: Physical health (Model 2)

PAEHR→PCC (a1 path)0.131.125.042.048 to .214.002

PAEHR→Health self-efficacy (a2 path)0.022.021.055–.078 to .137.59

PCC→Health self-efficacy (l1 path)0.270.269.052.258 to .461<.001

PCC→Physical health (b1 path)0.013.010.070–.120 to .154.81

Health self-efficacy→Physical health (b2 path)0.168.126.052.066 to .270.001

PAEHR→Physical health (direct effect, d path)–0.032–.023.071–.183 to .096.55

PAEHR→Physical health (total effect, c path)–0.021–.015.071–.168 to .112.69

PAEHR→PCC→Physical health (indirect effect, a1b1)0.002.001.011–.020 to .024N/A

PAEHR→PCC→Health self-efficacy→Physical health (indirect effect, a1b2l1)0.006.004.004.002 to .018NA

PAEHR→Health self-efficacy→Physical health (indirect effect, a2b2)0.004.003.010–.015 to .026N/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.

cP values are not computed for bootstrapped indirect effects.

dPAEHR: patient-accessible electronic health record.

ePCC: patient-centered communication.

fN/A: not applicable.


Principal Findings

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 [20]. Rathert et al’s [20] and Street et al’s [29] pathway models provide the needed theoretical foundation for this study, supporting that several steps must occur for health improvement to be influenced by cancer survivors’ PAEHR portal use. First, PAEHR portals serve as a tool that facilitates patient-provider communication. Physicians should incorporate PAEHR systems to provide PCC that supports patients in making informed health care decisions that are consistent with their needs, values, and preferences. Unless PCC is improved, PAEHR portal use will not increase patients’ health self-efficacy and improve their health outcomes. Although previous research has identified the association between PAEHR and patient health, we investigated the mediating mechanisms (the process) through which PAEHR impacts 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 [40]. Through PAEHR portals, cancer survivors are likely to be informed about their health status, be well educated with adequate health information, and have convenient access to health care professionals for medical guidance [41]. As a result, patients feel more engaged in PCC, which helps better understand their health and motivate them to stay positive and improve their psychological health [42-44]. However, PCC has no mediation effect between PAEHR portal use and cancer survivors’ physical health. This might be because the research sample of this study consisted of 626 cancer survivors with an average age >60 years, and they were likely to have inferior health status. PCC could not improve physical health unless patients were equipped with the necessary health skills. This assumption was supported by the sequential mediation effect of PCC and health self-efficacy between PAEHR portal use and cancer survivors’ health outcomes.

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 [45,46]. Furthermore, improved health self-efficacy can help people take care of their physical and psychological health, and this finding was congruent with previous findings [47-49]. Our results provide empirical evidence of the indirect effect of PAEHR portal use on cancer survivors’ health outcomes through PCC and health self-efficacy.

Comparison With Prior Work

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 [19] and Rathert et al’s [20] pathway model in understanding the process through which PAEHR impacts patient health. Second, this study extends the current literature by investigating the usability of eHealth technologies in delivering longitudinal survivorship care for patients with chronic diseases as well as examining the mediation roles of PCC and health self-efficacy. Our findings stressed PCC as the salient intrinsic factor of PAEHR that helps improve patients’ health self-efficacy and prompts them into action to maintain their health. The mediation effects provide a more nuanced understanding of the mechanisms underlying the association between PAEHR portal use and patients’ health outcomes. This model was established in several hypotheses by which the assumptions have been shown tenable. This study thus helps consolidate past research on the relationships between PAEHR portal use and patients’ physical and psychological health.

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 [50]. Second, considering the significant role of PAEHR portals, we should continue to develop information technology infrastructure to improve the accessibility of high-quality and long-term survivorship care. For example, patients who live remotely with low-speed internet and people who have poor internet skills may not benefit from the convenience and great efficiency brought by the internet for medical consultations [47]. Thus, information and communication technology companies should expand high-speed internet provisions to the other regions and deliver benefits to more people and communities. In addition, we should provide continuous support to help individuals overcome the barriers encountered in using PAEHR portals for health management [51]. Third, strict policies for web-based health service regulation should be implemented to protect patients’ information and to ensure a safe PAEHR environment. In parallel with the governmental measures, it is equally important to educate patients about their rights to access health data and responsibilities for personal information security. Fourth, considering the effect of PCC, it is important to help patients more actively participate in health consultations as well as provide training to physicians in delivering empathetic, mindful, informative, and patient-centered care.

Limitations and Directions for Future Research

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.

Conclusion

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.

Acknowledgments

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).

Data Availability

The data sets generated and analyzed during this study are publicly available on [52]. All data and materials comply with field standards.

Conflicts of Interest

None declared.

  1. Cancer. World Health Organization.   URL: https://www.who.int/news-room/fact-sheets/detail/cancer [accessed 2021-06-30]
  2. Cancer facts and figures. American Cancer Society.   URL: https:/​/www.​cancer.org/​content/​dam/​cancer-org/​research/​cancer-facts-and-statistics/​annual-cancer-facts-and-figures/​2021/​cancer-facts-and-figures-2021.​pdf [accessed 2021-07-08]
  3. Naughton M, Weaver K. Physical and mental health among cancer survivors: considerations for long-term care and quality of life. N C Med J 2014;75(4):283-286 [FREE Full text] [CrossRef] [Medline]
  4. Denlinger C, Ligibel J, Are M, Baker KS, Demark-Wahnefried W, Friedman DL, National Comprehensive Cancer Network. Survivorship: sleep disorders, version 1.2014. J Natl Compr Canc Netw 2014 May;12(5):630-642 [FREE Full text] [CrossRef] [Medline]
  5. Keating N, Nørredam M, Landrum M, Huskamp H, Meara E. Physical and mental health status of older long-term cancer survivors. J Am Geriatr Soc 2005 Dec;53(12):2145-2152. [CrossRef] [Medline]
  6. Epstein RM, Street RL. Patient-centered communication in cancer care: promoting healing and reducing suffering. National Cancer Institute.   URL: https://cancercontrol.cancer.gov/brp/docs/pcc_monograph.pdf [accessed 2021-07-08]
  7. Gorin S, Haggstrom D, Han P, Fairfield K, Krebs P, Clauser S. Cancer Care Coordination: a Systematic Review and Meta-Analysis of Over 30 Years of Empirical Studies. Ann Behav Med 2017 Aug;51(4):532-546. [CrossRef] [Medline]
  8. Singh H, Fox S, Petersen N, Shethia A, Street R. Older patients' enthusiasm to use electronic mail to communicate with their physicians: cross-sectional survey. J Med Internet Res 2009 Jun 16;11(2):e18 [FREE Full text] [CrossRef] [Medline]
  9. Patel M, Smith A, Leo H, Hao W, Zheng K. Improving Patient-Provider Communication and Therapeutic Practice Through Better Integration of Electronic Health Records in the Exam Room: A Pilot Study. Health Educ Behav 2019 Jun;46(3):484-493 [FREE Full text] [CrossRef] [Medline]
  10. Abramson E, Barrón Y, Quaresimo J, Kaushal R. Electronic Prescribing Within an Electronic Health Record Reduces Ambulatory Prescribing Errors. The Joint Commission Journal on Quality and Patient Safety 2011 Oct;37(10):470-478 [FREE Full text] [CrossRef]
  11. Detmer D, Bloomrosen M, Raymond B, Tang P. Integrated personal health records: transformative tools for consumer-centric care. BMC Med Inform Decis Mak 2008 Oct 06;8:45 [FREE Full text] [CrossRef] [Medline]
  12. Fernández-Alemán JL, Señor IC, Lozoya P, Toval A. Security and privacy in electronic health records: a systematic literature review. J Biomed Inform 2013 Jun;46(3):541-562 [FREE Full text] [CrossRef] [Medline]
  13. Kruse C, Stein A, Thomas H, Kaur H. The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature. J Med Syst 2018 Sep 29;42(11):214 [FREE Full text] [CrossRef] [Medline]
  14. Wani D, Malhotra M. Does the meaningful use of electronic health records improve patient outcomes? Journal of Operations Management 2018 Jun 22;60(1):1-18 [FREE Full text] [CrossRef]
  15. Hossain A, Quaresma R, Rahman H. Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: An empirical study. International Journal of Information Management 2019 Feb;44:76-87 [FREE Full text] [CrossRef]
  16. Barrett A. Electronic Health Record (EHR) Organizational Change: Explaining Resistance Through Profession, Organizational Experience, and EHR Communication Quality. Health Commun 2018 Apr;33(4):496-506. [CrossRef] [Medline]
  17. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract 1998;1(1):2-4. [Medline]
  18. Siminerio L. The role of technology and the chronic care model. J Diabetes Sci Technol 2010 Mar 01;4(2):470-475 [FREE Full text] [CrossRef] [Medline]
  19. Gee P, Greenwood D, Paterniti D, Ward D, Miller L. The eHealth Enhanced Chronic Care Model: a theory derivation approach. J Med Internet Res 2015 Apr 01;17(4):e86 [FREE Full text] [CrossRef] [Medline]
  20. Rathert C, Mittler J, Banerjee S, McDaniel J. Patient-centered communication in the era of electronic health records: What does the evidence say? Patient Educ Couns 2017 Jan;100(1):50-64. [CrossRef] [Medline]
  21. Liu P, Jiang S. Patient-Centered Communication Mediates the Relationship between Health Information Acquisition and Patient Trust in Physicians: A Five-Year Comparison in China. Health Commun 2021 Feb;36(2):207-216. [CrossRef] [Medline]
  22. Liu P, Yeo T. How Online Patient-Provider Communication Impacts Quality of Life: Examining the Role of Patient-Centered Care and Health Competence. Health Commun 2021 Aug 02:1-6. [CrossRef] [Medline]
  23. Zou W. How Do Patient-Centered Communication, Emotional Well-Being, Confidence in Health Information-Seeking, and Future Time Perspective Influence Health Self-Efficacy? American Journal of Health Education 2021 Apr 08;52(3):137-144 [FREE Full text] [CrossRef]
  24. Pearce C, Kumarapeli P, de Lusignan S. "Effects of exam room EHR use on doctor-patient communication: a systematic literature review" - triadic and other key terms may have identified additional literature. Inform Prim Care 2013;21(1):40-42 [FREE Full text] [CrossRef] [Medline]
  25. Wald J, Businger A, Gandhi T, Grant R, Poon E, Schnipper J, et al. Implementing practice-linked pre-visit electronic journals in primary care: patient and physician use and satisfaction. J Am Med Inform Assoc 2010;17(5):502-506 [FREE Full text] [CrossRef] [Medline]
  26. Young H, Nesbitt T. Increasing the Capacity of Primary Care Through Enabling Technology. J Gen Intern Med 2017 Apr;32(4):398-403 [FREE Full text] [CrossRef] [Medline]
  27. Bose-Brill S, Feeney M, Prater L, Miles L, Corbett A, Koesters S. Validation of a Novel Electronic Health Record Patient Portal Advance Care Planning Delivery System. J Med Internet Res 2018 Jun 26;20(6):e208 [FREE Full text] [CrossRef] [Medline]
  28. McGrath J, Arar N, Pugh J. The influence of electronic medical record usage on nonverbal communication in the medical interview. Health Informatics J 2007 Jun;13(2):105-118 [FREE Full text] [CrossRef] [Medline]
  29. Street RJ, Makoul G, Arora N, Epstein R. How does communication heal? Pathways linking clinician-patient communication to health outcomes. Patient Educ Couns 2009 Mar;74(3):295-301. [CrossRef] [Medline]
  30. Madhavan S, Sanders AE, Chou WS, Shuster A, Boone KW, Dente MA, et al. Pediatric palliative care and eHealth opportunities for patient-centered care. Am J Prev Med 2011 May;40(5 Suppl 2):S208-S216 [FREE Full text] [CrossRef] [Medline]
  31. Guo S, Hsing H, Lin J, Lee C. Relationships Between Mobile eHealth Literacy, Diabetes Self-care, and Glycemic Outcomes in Taiwanese Patients With Type 2 Diabetes: Cross-sectional Study. JMIR Mhealth Uhealth 2021 Feb 05;9(2):e18404 [FREE Full text] [CrossRef] [Medline]
  32. Park C, Cho D, Moore P. How does education lead to healthier behaviours? Testing the mediational roles of perceived control, health literacy and social support. Psychol Health 2018 Nov;33(11):1416-1429. [CrossRef] [Medline]
  33. Hong Y, Jiang S, Liu P. Use of Patient Portals of Electronic Health Records Remains Low From 2014 to 2018: Results From a National Survey and Policy Implications. Am J Health Promot 2020 Jul;34(6):677-680. [CrossRef] [Medline]
  34. Blanch-Hartigan D, Chawla N, Moser R, Finney Rutten LJ, Hesse B, Arora N. Trends in cancer survivors' experience of patient-centered communication: results from the Health Information National Trends Survey (HINTS). J Cancer Surviv 2016 Dec;10(6):1067-1077. [CrossRef] [Medline]
  35. Greenberg A, Falisi A, Finney Rutten LJ, Chou WYS, Patel V, Moser RP, et al. Access to Electronic Personal Health Records Among Patients With Multiple Chronic Conditions: A Secondary Data Analysis. J Med Internet Res 2017 Jun 02;19(6):e188 [FREE Full text] [CrossRef] [Medline]
  36. Ellis E, Orom H, Giovino G, Kiviniemi M. Relations between negative affect and health behaviors by race/ethnicity: Differential effects for symptoms of depression and anxiety. Health Psychol 2015 Sep;34(9):966-969. [CrossRef] [Medline]
  37. Jayalakshmi T, Santhakumaran A. Statistical Normalization and Back Propagationfor Classification. IJCTE 2011:89-93 [FREE Full text] [CrossRef]
  38. Zhao X, Zhang X. Emerging methodological issues in quantitative communication research. New Trends Commun Stud. II 2014:953-978 [FREE Full text]
  39. Hayes A. Introduction to Mediation, Moderation, and Conditional Process Analysis, First Edition: A Regression-Based Approach. eBook: The Guilford Press; 2022.
  40. Roter D, Larson S, Sands D, Ford D, Houston T. Can e-mail messages between patients and physicians be patient-centered? Health Commun 2008;23(1):80-86. [CrossRef] [Medline]
  41. Zanaboni P, Kummervold P, Sørensen T, Johansen M. Patient Use and Experience With Online Access to Electronic Health Records in Norway: Results From an Online Survey. J Med Internet Res 2020 Feb 07;22(2):e16144 [FREE Full text] [CrossRef] [Medline]
  42. Calfas K, Sallis J, Zabinski M, Wilfley DE, Rupp J, Prochaska JJ, et al. Preliminary evaluation of a multicomponent program for nutrition and physical activity change in primary care: PACE+ for adults. Prev Med 2002 Feb;34(2):153-161. [CrossRef] [Medline]
  43. Lee Y, Lin J. Do patient autonomy preferences matter? Linking patient-centered care to patient-physician relationships and health outcomes. Soc Sci Med 2010 Nov;71(10):1811-1818. [CrossRef] [Medline]
  44. Rathert C, Wyrwich M, Boren S. Patient-centered care and outcomes: a systematic review of the literature. Med Care Res Rev 2013 Aug;70(4):351-379. [CrossRef] [Medline]
  45. Finney Rutten LJ, Hesse B, St Sauver JL, Wilson P, Chawla N, Hartigan DB, et al. Health Self-Efficacy Among Populations with Multiple Chronic Conditions: the Value of Patient-Centered Communication. Adv Ther 2016 Aug;33(8):1440-1451 [FREE Full text] [CrossRef] [Medline]
  46. Saha S, Beach M. The impact of patient-centered communication on patients' decision making and evaluations of physicians: a randomized study using video vignettes. Patient Educ Couns 2011 Sep;84(3):386-392 [FREE Full text] [CrossRef] [Medline]
  47. Bachmann J, Goggins K, Nwosu S, Schildcrout J, Kripalani S, Wallston K. Perceived health competence predicts health behavior and health-related quality of life in patients with cardiovascular disease. Patient Educ Couns 2016 Dec;99(12):2071-2079 [FREE Full text] [CrossRef] [Medline]
  48. Silva WD, Campos J, Marôco J. Impact of inherent aspects of body image, eating behavior and perceived health competence on quality of life of university students. PLoS One 2018;13(6):e0199480 [FREE Full text] [CrossRef] [Medline]
  49. Kujala S, Hörhammer I, Väyrynen A, Holmroos M, Nättiaho-Rönnholm M, Hägglund M, et al. Patients' Experiences of Web-Based Access to Electronic Health Records in Finland: Cross-sectional Survey. J Med Internet Res 2022 Jun 06;24(6):e37438 [FREE Full text] [CrossRef] [Medline]
  50. Xie L, Zhang S, Xin M, Zhu M, Lu W, Mo P. Electronic health literacy and health-related outcomes among older adults: A systematic review. Prev Med 2022 Apr;157:106997. [CrossRef] [Medline]
  51. Vollbrecht H, Arora V, Otero S, Carey K, Meltzer D, Press V. Evaluating the Need to Address Digital Literacy Among Hospitalized Patients: Cross-Sectional Observational Study. J Med Internet Res 2020 Jun 04;22(6):e17519 [FREE Full text] [CrossRef] [Medline]
  52. Health information national trends survey (HINTS). National Cancer Institute.   URL: https://hints.cancer.gov [accessed 2022-10-19]


CCM: Chronic Care Model
eCCM: eHealth enhanced Chronic Care Model
HINTS: Health Information National Trends Survey
PAEHR: patient-accessible electronic health record
PCC: patient-centered communication


Edited by T Leung; submitted 17.05.22; peer-reviewed by R Yang, J Hagström; comments to author 13.08.22; revised version received 04.09.22; accepted 24.09.22; published 24.10.22

Copyright

©Piper Liping Liu, Xinshu Zhao, Jizhou Francis Ye. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.10.2022.

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