Article

Patient Use of Electronic Methods to Self-Report Symptoms: An Integrative Literature Review

Sharyn Carrasco

Lene Symes

electronic self-report, patient self-report, patient-reported symptoms, integrative review
ONF 2018, 45(3), 399-416. DOI: 10.1188/18.ONF.399-416

Problem Identification: Clinicians are unaware of most of their patients’ symptoms. Symptoms may be poorly documented and their impact underestimated. Undertreatment of symptoms may lead to increased symptom distress and decreased quality of life. Improving the communication of symptoms to nurses is vital in symptom management and quality-of-life improvement. Electronic patient self-report of symptoms may be beneficial.

Literature Search: An integrative review of the literature was conducted to describe the use of electronic methods for symptom self-report by patients with cancer and to inform best practices.

Data Evaluation: The final sample for this integrative review consisted of 36 studies (32 quantitative and 4 qualitative).

Synthesis: Data analysis was used to summarize the findings of the 36 studies. Patients with cancer found electronic self-report of symptoms to be feasible and the devices usable. Electronic symptom reporting may improve patient–clinician communication, leading to improved physical and psychosocial outcomes.

Implications for Practice: In the studies that included an interactive communication component, oncology nurses were central in receiving, reviewing, and reporting changes to the provider. Patients expressed themselves more when consulting with nurses than with physicians.

Jump to a section

    Patients with cancer experience acute and chronic symptoms caused by their disease and its treatment (Portenoy et al., 1994). However, clinicians are often unaware of patients’ symptoms (Bruera, Sweeney, Calder, Palmer, & Benisch-Tolley, 2001; Butow, Brown, Cogar, Tattersall, & Dunn, 2002; Chang, Hwang, Feueurman, & Kasimis, 2000; Newell, Sanson-Fisher, Girgis, & Bonaventura, 1998) and fail to recognize 50%–80% of these symptoms (Epstein & Street, 2007; Farrell, Beaver, Heaven, & Maguire, 2001; Ryan et al., 2005). Even when symptoms are recognized, they may be underdocumented and undertreated, with their impact underestimated (McIntyre, 2015). Discordance exists between clinicians’ findings during assessment and patients’ reported symptoms (Basch et al., 2006; Petersen, Larsen, Pedersen, Sonne, & Groenvold, 2006), which leads to unmanaged symptoms. Inadequate management of treatment-related toxicities may increase symptom distress and negatively affect quality of life (Cella, 1997; Lee, 2008). Worsening symptoms may lead to emergency department visits and have a negative impact on patient outcomes, including survival (Barbera et al., 2013; Efficace et al., 2012). A vast array of instruments is being used to capture and measure symptoms, as well as to examine the complexity of caring for patients and treating and managing their symptoms (Basch et al., 2007; Berry et al., 2014; Blum et al., 2014; Cella et al., 2014; Fromme, Eilers, Mori, Hsieh, & Beer, 2004).

    Reporting the prevalence, severity, and impact of symptoms is essential in oncology symptom management (White, McMullan, & Doyle, 2009). Reilly et al. (2013) concluded that any clinical study evaluating the impact of treatment on patients should consider including patient self-reporting of symptoms, which is also referred to as patient-reported outcomes.

    The U.S. Food and Drug Administration and the National Cancer Institute have stated that a patient’s own description of symptoms should be considered as the accepted benchmark (Dueck & Sloan, 2007). Increasing interest surrounds the use of electronic methods for patients to self-report their symptoms (Johansen, Henriksen, Berntsen, & Horsch, 2011).

    Since the American Recovery and Reinvestment Act of 2009, which allocated significant funding to the implementation of electronic health records (EHRs), their use has spread widely. The integration of an electronic version of a validated symptom assessment into the EHR can enhance oncology practices and permit real-time patient assessment and management. Evidence supports the idea that the routine collection of patient symptoms, including the provision of timely feedback, enhances patient–clinician communication (Chen, Ou, & Hollis, 2013). The collection of patients’ self-reported symptoms via electronic symptom assessment measures has been shown to be equivalent to paper-and-pencil measures (Gwaltney, Shields, & Shiffman, 2008). However, electronic assessment may offer other benefits. Bennett, Jensen, and Basch (2012) reviewed five electronic assessment systems commonly used in oncology, finding that they support clinical activities, including symptom and toxicity assessment and symptom management. Because of growing interest in the electronic collection of symptoms, the number of studies about patients with cancer reporting their symptoms electronically has also increased. The purpose of this integrative review is to inform best practice by evaluating and synthesizing findings from studies about patients with cancer using an electronic method to self-report their symptoms.

    Methods

    An integrative review (Whittemore & Knafl, 2005) framework was followed. This method allows for the exploration of quantitative, qualitative, and mixed-method designs within one review, and it supports a comprehensive review of research. The sampling frame for this literature review consisted of research articles published in peer-reviewed journals from 2006–2016.

    Search Strategy

    PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed for this review (Moher, Liberati, Tetzlaff, & Altman, 2009) (see Figure 1). The first author of this article conducted a systematic literature search to identify studies in the PubMed, CINAHL®, and EMBASE electronic databases. Bibliographic searching was also performed. The search terms were unique to each database.

    •  PubMed search terms were self reported patient AND neoplasm.

    •  CINAHL search terms were self report AND symptoms AND cancer patients.

    •  EMBASE search terms were self report OR self evaluation AND neoplasm AND patient.

    •  The term electronic was added to the search in titles or abstracts. Filters were adult, past 10 years, and English language.

    Inclusion and Exclusion Criteria

    Eligibility criteria included articles that described studies of adult patients who had access to a telephone or cell phone, were aged 18 years or older, had various types and stages of cancer, and were actively receiving treatment that included chemotherapy. The search was limited to studies reported in English. Literature reviews, articles unrelated to the oncology setting, pediatric studies, studies of cancer survivorship (related to long-term symptoms), and studies that focused only on a specific drug were excluded because their scope was too narrow for the purpose of this literature review.

    The search resulted in 64 articles retrieved from the databases and 9 articles identified by hand search. Of these, 31 articles were duplicates and were removed. An additional three articles were removed after further review of the title and abstract because two articles described a methodologic design and one was a self-report of adherence; all three were determined to be irrelevant. The full text of the remaining 39 articles was reviewed, and another 3 articles were removed because 2 were about methodologic design and 1 concerned cancer survivors who were not actively receiving treatment. The final sample consisted of 36 empirical reports: 32 quantitative and 4 qualitative.

    Data Evaluation

    The strength of evidence among the studies varied and consisted of levels II, III, and VI based on the Melnyk levels of evidence (Melnyk & Fineout-Overholt, 2011).

    •  Level II is a well-designed randomized, controlled trial.

    •  Level III is a well-designed nonrandomized, controlled trial or quasiexperimental trial.

    •  Level VI is a single descriptive or qualitative study.

    After the selection of the studies, the identified articles were again checked for inclusion criteria. All studies meeting the inclusion criteria were retained.

    Data Analysis

    The primary data analysis was conducted by the first author as part of the dissertation process and was guided by the method described by Whittemore and Knafl (2005). This method consists of data reduction, display, comparison, conclusion drawing, and verification. The data from the original sources were reviewed thoroughly, and the first author extracted data with consultation and collaboration provided by the second author. The extracted data were coded and then compared; similar data were categorized and grouped.

    Results

    General Characteristics

    The data extracted from the reviewed studies are displayed in a methodologic matrix (see Table 1). The researchers also evaluated different devices and electronic software applications used in the studies. Of the 36 studies, access to the electronic software applications was available to the patients either in the clinic (14 studies) or remotely (16 studies). Six studies allowed remote and clinic access. In addition, as reported by Basch et al. (2007), 76% of patients had computers in their homes, but only 15% self-reported from home.

    Nineteen of the 32 quantitative studies examined in this review were published from 2011–2016. In addition, 19 of these studies were conducted outside of the United States, with 16 of them performed in Europe. The studies looked at the acceptability or feasibility of electronically capturing patients’ self-report of symptoms, as well as the impact on communication between the patient and the healthcare provider and/or the patient’s psychosocial well-being.

    The methodologic matrix of the primary source data was closely examined to identify themes. A critical analysis of the data in the matrix was conducted. Similar themes were categorized and grouped. For accuracy, the themes were verified by returning to the primary source and reconfirming the findings.

    Acceptability, Feasibility, and Usability of Electronic Collection of Symptoms

    Fourteen studies considered the patients’ and/or clinicians’ perspectives. Acceptability and feasibility of electronic assessment of symptoms directly by the patients was the focus of nine studies.

    Symptoms Tracking and Reporting for Patients: Electronic patient self-reporting was shown to be feasible by Basch et al. (2007) and Andikyan et al. (2012) using the Symptoms Tracking and Reporting for Patients (STAR), an online platform that contained five items from the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire–Core 30 (EORTC QLQ-C30) and the patient adaptation of the National Cancer Institute’s Common Terminology Criteria for Adverse Events. STAR also triggered alerts for grade 3 and 4 toxicities. Most of the patients from both studies found STAR to be useful and said they would recommend it to other patients (Andikyan et al., 2012; Basch et al., 2007).

    Electronic Self Report Assessment–Cancer: Studies by Chan et al. (2011) and Wolpin et al. (2008) used the Electronic Self Report Assessment–Cancer (ESRA-C), which is made up of the following four measures: the EORTC QLQ-C30, the 13-item Symptom Distress Scale, the single-item Pain Intensity Numerical Scale, and the 9-item Patient Health Questionnaire–Depression. Moderate to high acceptability was reported for the ESRA-C (Chan et al., 2011; Wolpin et al., 2008). Women reported higher acceptability scores than men (p = 0.026), as did participants aged younger than 60 years compared to those aged older than 60 years (p = 0.048) (Wolpin et al., 2008).

    In two studies, patients’ symptoms were collected via assessments using paper and an electronic device (Abernethy et al., 2008; Blum et al., 2014). In both studies, no significant differences in symptoms were found.

    Wireless tablet computer: The study by Abernethy et al. (2008) reported that patients felt that wireless tablet computers were easy to read (94%) and easy to respond to (98%).

    PALM: In the Blum et al. (2014) study, 49% of the 84 participants preferred the PALM (handheld computer) to the paper-based assessment. Several studies reported high patient acceptability and feasibility regarding the electronic assessment of symptoms (Abernethy et al., 2008; Andikyan et al., 2012; Basch et al., 2007; Blum et al., 2014; Chan et al., 2011; Falchook et al., 2016; Wintner et al., 2015; Wolpin et al., 2008; Wu et al., 2016). Three studies (Head et al., 2009; Mirkovic, Kaufman, & Ruland, 2014; Ruland, Maffei, et al., 2013) considered the usability and usefulness of a device from the patient’s perspective.

    Health Buddy: In the Head et al. (2009) study (N = 75), the telecommunications device Health Buddy was described as an easy-to-use telehealth messaging device. The print on the screen was large and easy to read, and only four buttons were used to register the responses. Compared to standard of care, the patients in the intervention group (n = 42) reported that the device was either easy or very easy to use, with 65% reporting improved satisfaction concerning communication with their healthcare providers.

    Connect and WebChoice: The study by Mirkovic et al. (2014) involved usability testing of a high-fidelity prototype of the Connect mobile application, which was developed to allow patients access to the Internet platform Connect. Seven patients evaluated the look and feel of the application while using it to report their symptoms; overall, patients found that the application was useful and that they would use it again.

    Ruland, Maffei, et al. (2013) examined WebChoice, an interactive health communication application (IHCA) that is tailored to patients’ individual needs and includes various components (e.g., discussion forum, healthcare team messaging, diary). Patient-reported usefulness of WebChoice and its components differed with disease stage. Sixty-four percent of the participants actively used WebChoice (average of 60 times). The discussion forum and messages to the nurse components were used most, with large individual variations. The latter component was most valued by patients. WebChoice is a component of Connect.

    CHOICE: A study by Ruland (2006) evaluated the clinicians’ (65 nurses and 12 physicians) perceived usefulness of a system called Creating better Health Outcomes by Improving Communication about Patients’ Experiences (CHOICE). CHOICE is an assessment tool for patients to report their cancer-specific symptoms; a summary report of these symptoms is then made available to clinicians to review and use for patient care planning. The clinicians highly rated all aspects of CHOICE’s usefulness (e.g., patient involvement, assessment summaries), but the nurses consistently provided higher usefulness ratings than the physicians. The nurses reported feeling as though CHOICE improved care planning and provided them with a better understanding of patients’ views. A strong significant correlation existed between patterns of use and perceived usefulness.

    Analysis

    Berry et al. (2011) and Blum et al. (2014) reported that clinicians found the summary reports generated by the patient self-assessment systems (ESRA-C and E-MOSAIC, or electronic monitoring of symptoms and syndromes associated with advanced cancer, respectively) to be useful. Having a longitudinal and quantitative overview of patients’ symptoms was viewed as being beneficial to clinicians (Blum et al., 2014). Most clinicians noted that the summary report was useful for identifying symptoms and quality-of-life issues, promoting patient–clinician communication, and identifying areas for referral (Berry et al., 2011; Blum et al., 2014).

    Ruland, Maffei, et al. (2013) and Varsi, Gammon, Wibe, and Ruland (2013) looked at patients’ frequency and patterns of use of the components of the WebChoice system. The patients in this study were part of a larger study (Ruland, Andersen, et al., 2013). Ruland, Maffei, et al. (2013) reported that patients with breast cancer logged in to the WebChoice system twice as often as patients with prostate cancer and that they also posted significantly more to the discussion forum. Patients visited the forum more often than they contributed messages to it, and the patients with prostate cancer preferred to send personal messages to the nurses rather than post to the discussion forum. The patients with breast cancer and the patients with prostate cancer sent a similar number of messages to the nurses. In addition, patients who had been diagnosed more than one year prior to entering the study wrote considerably more notes in the diary (which is part of the WebChoice system), sent more messages to the nurses, and visited the assessment section (which allows patients to self-monitor symptoms, problems, and priorities) more often than the patients who had been diagnosed more recently; however, the differences were not statistically significant.

    Varsi et al. (2013) determined that patients appreciated the availability of the Internet-based patient–provider communication services (IPPCs) and the possibility of using such healthcare team messaging as needed, even if they did not actually use it. Their reasons for not using the IPPCs included the following:

    •  Had sufficient access elsewhere

    •  Preferred other types of communication (e.g., telephone, in person)

    •  Hindered in IPPC use (e.g., login problems)

    Despite the variety of devices and symptom assessment tools used in the aforementioned studies, the participating patients and clinicians found electronic self-report of patient symptoms to be acceptable, feasible, and useful. Electronic collection of symptoms allowed for the generation of alerts to clinicians for grade 3 and 4 toxicities. Such alerts and summary reports may have led to increased acceptability, feasibility, and usability of the electronic method of symptom reporting by the patients. The summary reports were viewed as a benefit by clinicians and should be considered when implementing an electronic method of self-reporting symptoms. Understanding that patient use of the system may be dependent on various factors, including cancer type and time from diagnosis, is important.

    Communication

    Thirteen studies considered the effect of electronic patient self-report of symptoms on communication. Of those 13 studies, 6 considered the discussion between the patient and the clinician regarding symptoms, 1 examined the clinician’s documentation of the symptoms, and 6 looked at the management of the self-reported symptoms. The type and capabilities of the electronic methods varied; several web-based patient assessment systems, including automated telephone systems set up to send alerts to the healthcare team, were examined.

    Symptom self-report: In a study by Wagner et al. (2015) (N = 636), Patient-Reported Outcomes Measurement Information System computer adaptive tests (CATs) were completed by most of the patients at home (90%). They were then scored and reported via the Epic MyChart portal, with immediate integration into the EHR system. This real-time integration of patient-reported symptoms into the EHR permitted identification of the need for and implementation of psychosocial and supportive care strategies.

    Symptom discussion: When patients in a study by Heyn, Finset, and Ruland (2013) used CHOICE interactive tailored patient assessment (ITPA) prior to their consultation, they expressed more cues (utterances with an underlying emotional meaning) and concerns (p < 0.01) than did patients in the control group who did not use CHOICE ITPA. In addition, patients reporting to nurses expressed significantly more cues (p < 0.001) than did patients reporting to physicians (Heyn, Ruland, & Finset, 2012). More cues and concerns were expressed by patients early in clinician consultations (Heyn, Finset, & Ruland, 2013). The most frequent cue indicated expression of uncertainty and hope (Grimsbø, Ruland, & Finset, 2012; Heyn et al., 2012).

    The symptom assessment summary report generated was provided to the clinician during the patient’s visit; it prompted significantly more discussion of the patient’s symptoms (Berry et al., 2011; Heyn, Finset, Eide, & Ruland, 2013). Among those in the intervention group, where patients had access to the healthcare messaging component and assessment summary, patients asked more questions, and clinicians provided more information during the visit (Heyn, Finset, Eide, & Ruland, 2013). On the whole, patient–clinician communication improved (Basch, et al., 2007; Berry et al., 2011; Blum et al., 2014; Heyn, Finset, Eide, & Ruland, 2013). These findings are consistent with those in a study by Detmar, Muller, Schornagel, Wever, and Aaronson (2002), who determined that the summary report provided a useful overview of patients’ symptoms and facilitated communication between the patient and the physician. The summary report may have increased clinicians’ acknowledgement of patients’ socio-emotional concerns, as well as clinicians’ overall responsiveness to patients’ cues; however, the summary report did not increase clinicians’ exploration of socio-emotional concerns, even when a prompt was provided (Kennedy Sheldon, Hilaire, & Berry, 2011). Exploration of concerns is necessary for complete assessment of patients’ socio-emotional status (Maguire, Faulkner, Booth, Elliott, & Hillier, 1996). Patients who perceive their providers as acknowledging and exploring their socio-emotional status may have better emotional adjustment and decreased psychological distress compared to patients who do not perceive their providers as responding to these concerns (de Haes & Bensing, 2009).

    Documentation: Patients with breast cancer in the Bock et al. (2012) study (N = 106) reported significantly more symptoms using a secure online questionnaire than were documented in the clinic notes by the clinician (p < 0.001); however, less than 40% of symptoms were managed. Exercise and alcohol consumption were reported 100% of the time in the online questionnaire but were documented in only 28% of the patients’ charts. In 25% of the charts where alcohol consumption was documented, there was significant discordance between patient and clinician reporting.

    Symptom management: An automated telephone system was used in the Cleeland et al. (2011) study in a postoperative setting to enable patients to rate their symptoms twice weekly for four weeks. An email alert was sent to a patient’s clinical team when the symptom reached a predetermined severity threshold, and clinicians responded to 84% of those alerts. Among the alert group, a greater reduction was seen in the number of symptom threshold events, as well as a more rapid decline in these events, compared to the control group.

    In a study by Kearney et al. (2009), a mobile telephone–based advanced symptom management system (ASyMS) allowed patients to remotely report symptoms and supported the management of symptoms in patients receiving chemotherapy. The preliminary findings suggest that the real-time reporting of symptoms facilitates a more accurate reflection of chemotherapy side effects, as well as better monitoring and management of them.

    In a longitudinal study by LeBlanc et al. (2015), the Patient Care Monitor (PCM) was used by patients with advanced lung cancer to self-report their symptoms over time; the authors found that these patients experienced a substantial symptom burden that increased with proximity to death. Concerns related to physical movement or functioning were the most frequently reported moderate to severe issues. Collecting this detailed symptom assessment information and tracking symptoms in real time promoted an individualized supportive care approach.

    Two qualitative studies (Ekstedt, Børøsund, Svenningsen, & Ruland, 2014; Grimsbø, Ruland, & Finset, 2012) and one quantitative study (Grimsbø, Finset, & Ruland, 2011) explored the healthcare team messaging component of WebChoice that allowed direct communication between a patient and the healthcare team. The patients in these three studies were part of a larger trial (Ruland, Andersen, et al., 2013).

    The study by Ekstedt et al. (2014) looked at how the healthcare team messaging component of WebChoice contributed to improving patient safety and continuity of care between treatment cycles. The messages allowed patients to communicate with the healthcare team and alert them to their symptoms and concerns, as well as ensure that quality information was being provided to the patients by confirming the information and sometimes providing further explanation (Ekstedt et al., 2014).

    The study by Grimsbø et al. (2011) reviewed the content of the patients’ electronic messages, and four main themes were identified: living with symptoms and side effects, living with fear of relapse, everyday life concerns, and the healthcare clinicians not meeting their needs for information. Nurses responded to most of the patients’ cues and concerns in the electronic messages, and more than half of their responses provided information and empathy (Grimsbø, Ruland, & Finset, 2012).

    Use of system components, including the electronic messaging component, differed by patient subgroup. For example, many patients with breast cancer used the WebChoice system for health-related information, and a number of patients with prostate cancer used features that helped them talk to their healthcare team. More active communication practices and information-seeking behaviors were observed in patients with a history of long-term illness than in those with a first-time diagnosis (Grimsbø, Engelsrud, Ruland, & Finset, 2012; Ruland, Maffei, et al., 2013). Patients with little social support and high levels of symptom distress and depression used the messaging and symptom self-management support components. Patient communication preferences and patterns are dependent on many factors and should be taken into consideration when identifying electronic methods that allow for patient–patient and patient–clinician communication.

    Psychosocial Impact

    The following studies examined the use of the web-based ESRA-C by patients to report symptoms and quality of life. Berry et al. (2011) found that when clinicians were provided with summary reports of patients’ self-reported cancer symptoms and quality of life, there was a positive impact on patient–clinician communication. In a study by Berry et al. (2014), clinicians were given summary reports for all patients enrolled. The intervention group received education and coaching regarding their symptoms in addition to clinician provision of the summary report and reported lower distress than the patients who did not receive education and coaching. In addition, the intervention group reported lower distress compared to the control group (p = 0.02).

    Basch et al. (2016) reported that health-related quality of life improved by 34% among patients who were reporting their symptoms via tablet and home computer versus an improvement of 18% among patients who were receiving usual care (symptom monitoring at the discretion of the clinician).

    In a study by Hong, Bosco, Bush, and Berry (2013), the ESRA-C was used by patients (N = 627) to report their symptoms at two different time points within a 109-day period. Changes were found in quality of life during patients’ treatment, with more than half of the patients undergoing stem cell transplantation (n = 191) reporting deteriorating quality of life. For the patients undergoing medical or radiation treatment (n = 436), equal proportions perceived improvement (25%) and deterioration (26%) of quality of life.

    Berry, Blonquist, Patel, Halpenny, and McReynolds (2015) conducted a study to evaluate the fully automated ESRA-C. Patients in the intervention group had access to the teaching tips component of ESRA-C. For any symptom or quality-of-life issue that was rated as moderate or severe, the patient would receive teaching tips. Participants who were undergoing radiation treatment were more likely than those who were undergoing medical treatment or transplantation to use the tips. Symptom distress was reduced (p = 0.01) for those who used the teaching tips.

    The intervention group in a study by Ruland et al. (2010) involved the sending of a summary report to clinicians after patients rated and prioritized their self-reported symptoms; the control group did not include provision of this report. In the intervention group, more symptoms were addressed by physicians and nurses, leading to decreased symptom distress over time in 10 of 19 symptom/problem categories versus 2 categories in the control group.

    In a study by Boyes, Newell, Girgis, McElduff, and Sanson-Fisher (2006), a summary report was provided to clinicians after patients completed a computerized survey of their physical symptoms, as well as the 14-item Hospital Anxiety and Depression Scale and a shortened version of the Supportive Care Needs Survey. The intervention group received a report with clinician feedback. The patients in the intervention group who had reported a debilitating physical symptom at their second visit were significantly less likely to report this at their third visit versus control group participants (p = 0.04).

    Patients with access to WebChoice or the healthcare team messaging component reported lower symptom distress over time (p = 0.001), including less depression and anxiety (p = 0.03), compared to the group who did not have access to electronic self-reporting or messaging (Børøsund, Cvancarova, Moore, Ekstedt, & Ruland, 2014). Even in the group with access to only the messaging component, the patients reported lower depression scores than those in the standard care group (Børøsund et al., 2014).

    The study by Ruland, Andersen, et al. (2013) randomized patients to use WebChoice and any of its components, including the messaging component, for one year. The control group received only an information sheet listing publicly available cancer-related Internet sites. Symptom distress was significantly less, as measured by the Memorial Symptom Assessment Scale–Short Form (Børøsund et al., 2014; Ruland, Andersen, et al., 2013). Scores improved in the intervention group compared to the control group for depression, self-efficacy, quality of life, and social support (Ruland, Andersen, et al., 2013).

    Patients’ experiences with WebChoice varied (Grimsbø, Engelsrud, Ruland, & Finset, 2012). Ten patients were interviewed about their interactions with WebChoice; some described WebChoice as feeling either like a trusted friend or a remote stranger, and a range of emotions (including feeling calmed down, upset, or like their normal selves) were reported.

    Discussion

    A variety of electronic devices and software were evaluated in the studies. Applications for tablet computers with touch screens, mobile telephones, personal digital assistants, and the web represent the primary technologies considered. Growing evidence exists to support the idea that routinely collecting patient-reported outcomes electronically is feasible and acceptable to the patient. For instance, a high percentage of patients used the various components of WebChoice, such as the discussion forum, and appreciated the availability of the IPPC, even if they did not use it (Varsi et al., 2013). Such findings are consistent with a Cochrane database review on the effects of IHCAs; users were more knowledgeable than non-users, and they also felt socially supported and may have experienced improved behavioral and clinical outcomes (Murray, Burns, Tai, Lai, & Nazareth, 2005). Clinicians discussing the summary report findings directly with their patients led to increased communication and the early addressing of symptoms and problems (Berry et al., 2011). Real-time review of symptoms by clinicians who provide timely feedback (including interventions to manage symptoms) enhances patient–clinician communication and decreases distress (Boyes et al., 2006).

    Qualitative methods should be considered when the researcher is interested in capturing patients’ experiences. Additional qualitative studies with patients undergoing cancer treatment could enhance understanding concerning different types of electronic self-report of symptoms and their impact on symptom management.

    Limitations

    Challenges existed in identifying and retrieving all relevant research on patient-reported symptoms in oncology. As a result, different terms were used to search individual databases. The search was limited to studies published from 2006–2016 and to English-language articles; gray literature and unpublished studies were excluded. Studies published prior to 2006 may contain important findings. The studies selected for inclusion used different data collection methods, as well as varied in the devices and assessment tools considered and in the sampling methods used. Some of the studies used the same data set, and many studies were single-institution experiences specific to a certain type of cancer diagnosis, which may limit the generalizability of the results.

    Implications for Nursing Practice and Research

    Patient-reported outcomes improve symptom detection and management, enhance quality of care, and promote patient satisfaction (Basch, 2014). Electronic methods are being used by patients to self-report these outcomes, and most patients find electronic methods to be acceptable and feasible for reporting symptoms. Real-time self-reporting via an interactive patient–clinician communication component improved patient–clinician communication and decreased symptom distress. This should be considered when evaluating tools for patients to self-report their symptoms. Other features that increase the usefulness of an electronic method for collecting patient symptoms include the following:

    •  Has mechanisms for real-time self-reporting of symptoms

    •  Generates alerts for selective grade 3 or 4 side effects

    •  Has a patient–clinician communication portal

    •  Has the capability to produce symptom summary reports

    •  Tracks symptoms over time

    •  Has a patient information portal with the capability to access the patient blog

    In addition, oncology nurses were found to be central in receiving, reviewing, and reporting changes to the provider, as well as in responding to patients and providing them with quality information and expressing empathy. They were also significant in care coordination. Patients expressed themselves more when consulting with nurses versus physicians (Heyn, Finset, & Ruland, 2013).

    Finding or developing new ways for nurses to manage patient symptoms is vital to improving patients’ quality of life (National Institute of Nursing Research, 2016). Communication of patient-reported outcomes to nurses is key to symptom management. Electronic methods featuring interactive components that permit patient–clinician communication are becoming important tools for nurses to support patients with cancer. Nurses should consider making available an approach where patients can report their symptoms as they are experienced so assessment and management can occur in real time.

    This literature review uncovered the lack of information that exists regarding patients’ experiences of reporting their symptoms and their preferences related to symptom-reporting method; consequently, this is an area for future research. Understanding the ways in which patients prefer to report their symptoms may influence the likelihood that patients will report those symptoms and report them in a timely manner.

    The 2013 Oncology Nursing Society Research Priorities Survey identified the use of interventions that employ technology to address symptoms, self-management to improve symptom control, and symptom management interventions as top priorities for oncology nurses (LoBiondo-Wood et al., 2014). Studies with larger and more diverse samples are needed to explore the use of various technologies to assess patient-reported symptoms and to improve the understanding behind the use of these technologies for symptom management and self-management. Future studies exploring the electronic capture of symptoms should consider a platform that includes interactive components, allowing for patient–clinician communication and real-time symptom assessment and management. Using qualitative methods to uncover what it means to electronically report symptoms would adequately capture patients’ experiences. This understanding will then need to be incorporated into future research, with the aim of improving symptom reporting and patient interventions, including self-management of symptoms.

    Conclusion

    The studies included in this integrative review employed a variety of symptom assessment measures and electronic methods for patient self-report of symptoms. Electronic assessment of patient-reported symptoms was considered to be acceptable and feasible in most of the studies. In the studies that evaluated the usefulness and usability of electronic or telephonic methods, patients reported that the systems were easy to use, and the clinicians found the information reported by patients to be useful. Considerations should be made based on how usage of the patient communication components of electronic systems varied according to cancer type, disease stage, illness burden, and length of illness. Patients with recurrent or metastatic disease tended to communicate more often and sent more messages to nurses, demonstrating varied needs for patient support. Incorporating patient symptom reporting into clinical practice improves symptom detection and management, enhances quality of care, and improves patient satisfaction.

    Clinicians reported better communication when using the software systems that generated summary reports. EHR integration of patient-reported symptoms may help to improve patient–clinician communication, thanks to real-time delivery of communications and assessment by the healthcare team, including automated triage for supportive care. Using web-based systems with an integrated patient–clinician communication service led to less patient distress because the healthcare team was able to focus on addressing symptoms of concern and then tracking those symptoms over time.

    About the Author(s)

    Sharyn Carrasco, RN, MSN, is a senior medical science liaison for Array BioPharma in Morrisville, NC, and a graduate student in the College of Nursing at Texas Woman’s University in Houston; and Lene Symes, PhD, RN, is a professor in the College of Nursing at Texas Woman’s University in Houston. Carrasco completed the data collection and provided statistical support. Both authors contributed to the conceptualization and design, provided the analysis, and contributed to the manuscript preparation. No financial relationships to disclose. Carrasco can be reached at scarrasco@twu.edu, with copy to ONFEditor@ons.org. (Submitted October 2017. Accepted January 3, 2018.)

     

    References

    Abernethy, A.P., Herndon, J.E., 2nd, Wheeler, J.L., Patwardhan, M., Shaw, H., Lyerly, H.K., & Weinfurt, K. (2008). Improving health care efficiency and quality using tablet personal computers to collect research-quality, patient-reported data. Health Services Research, 43, 1975–1991.

    Andikyan, V., Rezk, Y., Einstein, M.H., Gualtiere, G., Leitao, M.M., Jr., Sonoda, Y., . . . Chi, D.S. (2012). A prospective study of the feasibility and acceptability of a Web-based, electronic patient-reported outcome system in assessing patient recovery after major gynecologic cancer surgery. Gynecologic Oncology, 127, 273–277.

    Barbera, L., Atzema, C., Sutradhar, R., Seow, H., Howell, D., Husain, A., . . . Dudgeon, D. (2013). Do patient-reported symptoms predict emergency department visits in cancer patients? A population-based analysis. Annals of Emergency Medicine, 61, 427–437. https://doi.org/10.1016/j.annemergmed.2012.10.010

    Basch, E. (2014). The rationale for collecting patient-reported symptoms during routine chemotherapy. American Society of Clinical Oncology Educational Book, 2014, 161–165.

    Basch, E., Iasonos, A., Barz, A., Culkin, A., Kris, M.G., Artz, D., . . . Schrag, D. (2007). Long-term toxicity monitoring via electronic patient-reported outcomes in patients receiving chemotherapy. Journal of Clinical Oncology, 25, 5374–5380. http://doi.org/10.1200/JCO.2007.11.2243

    Basch, E., Iasonos, A., McDonough, T., Barz, A., Culkin, A., Kris, M.G., . . . Schrag, D. (2006). Patient versus clinician symptom reporting using the National Cancer Institute Common Terminology Criteria for Adverse Events: Results of a questionnaire-based study. Lancet Oncology, 7, 903–909.

    Basch, E.M., Deal, A.M., Kris, M.G., Scher, H.I., Hudis, C.A., Sabbatini, P., . . . Schrag, D. (2016). Symptom monitoring with patient-reported outcomes during routine cancer treatment: A randomized controlled trial. Journal of Clinical Oncology, 34, 557–565. https://doi.org/10.1200/JCO.2015.63.0830

    Bennett, A.V., Jensen, R.E., & Basch, E. (2012). Electronic patient-reported outcome systems in oncology clinical practice. CA: A Cancer Journal for Clinicians, 62, 336–347. https://doi.org/10.3322/caac.21150

    Berry, D.L., Blonquist, T.M., Patel, R.A., Halpenny, B., & McReynolds, J. (2015). Exposure to a patient-centered, web-based intervention for managing cancer symptom and quality of life issues: Impact on symptom distress. Journal of Medical Internet Research, 17, e136. https://doi.org/10.2196/jmir.4190

    Berry, D.L., Blumenstein, B.A., Halpenny, B., Wolpin, S., Fann, J.R., Austin-Seymour, M., . . . McCorkle, R. (2011). Enhancing patient–provider communication with the electronic self-report assessment for cancer: A randomized trial. Journal of Clinical Oncology, 29, 1029–1035.

    Berry, D.L., Hong, F., Halpenny, B., Partridge, A.H., Fann, J.R., Wolpin, S., . . . Ford, R. (2014). Electronic self-report assessment for cancer and self-care support: Results of a multicenter randomized trial. Journal of Clinical Oncology, 32, 199–205.

    Blum, D., Koeberle, D., Omlin, A., Walker, J., Von Moos, R., Mingrone, W., . . . Ribi, K. (2014). Feasibility and acceptance of electronic monitoring of symptoms and syndromes using a handheld computer in patients with advanced cancer in daily oncology practice. Supportive Care in Cancer, 22, 2425–2434.

    Bock, M., Moore, D., Hwang, J., Shumay, D., Lawson, L., Hamolsky, D., . . . Melisko, M. (2012). The impact of an electronic health questionnaire on symptom management and behavior reporting for breast cancer survivors. Breast Cancer Research and Treatment, 134, 1327–1335. https://doi.org/10.1007/s10549-012-2150-1

    Børøsund, E., Cvancarova, M., Moore, S.M., Ekstedt, M., & Ruland, C.M. (2014). Comparing effects in regular practice of e-communication and web-based self-management support among breast cancer patients: Preliminary results from a randomized controlled trial. Journal of Medical Internet Research, 16(12), e295.

    Boyes, A., Newell, S., Girgis, A., McElduff, P., & Sanson-Fisher, R. (2006). Does routine assessment and real-time feedback improve cancer patients’ psychosocial well-being? European Journal of Cancer Care, 15, 163–171. https://doi.org/10.1111/j.1365-2354.2005.00633.x

    Bruera, E., Sweeney, C., Calder, K., Palmer, L., & Benisch-Tolley, S. (2001). Patient preferences versus physician perceptions of treatment decisions in cancer care. Journal of Clinical Oncology, 19, 2883–2885. https://doi.org/10.1200/JCO.2001.19.11.2883

    Butow, P.N., Brown, R.F., Cogar, S., Tattersall, M.H., & Dunn, S.M. (2002). Oncologists’ reactions to cancer patients’ verbal cues. Psycho-Oncology, 11, 47–58. https://doi.org/10.1002/pon.556

    Cella, D. (1997). The Functional Assessment of Cancer Therapy-Anemia (FACT-An) Scale: A new tool for the assessment of outcomes in cancer anemia and fatigue. Seminars in Hematology, 34(Suppl. 2), 13–19.

    Cella, D., Choi, S., Garcia, S., Cook, K.F., Rosenbloom, S., Lai, J.-S., . . . Gershon, R. (2014). Setting standards for severity of common symptoms in oncology using the PROMIS item banks and expert judgement. Quality of Life Research, 23, 2651–2661.

    Chan, C.W., Tam, W., Cheng, K.K., Chui, Y.Y., So, W.K., Mok, T., . . . Berry, D.L. (2011). Piloting electronic self-report symptom assessment-cancer (ESRA-C) in Hong Kong: A mixed method approach. European Journal of Oncology Nursing, 15, 325–334.

    Chang, V.T., Hwang, S.S., Feueurman, M., & Kasimis, B.S. (2000). Symptom and quality of life survey of medical oncology patients at a veterans affairs medical center: A role for symptom assessment. Cancer, 88, 1175–1183.

    Chen, J., Ou, L., & Hollis, S.J. (2013). A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organizations in an oncologic setting. BMC Health Services Research, 13, 211. https://doi.org/10.1186/1472-6963-13-211

    Cleeland, C.S., Wang, X.S., Shi, Q., Mendoza, T.R., Wright, S.L., Berry, M.D., . . . Vaporciyan, A.A. (2011). Automated symptom alerts reduce postoperative symptom severity after cancer surgery: A randomized controlled clinical trial. Journal of Clinical Oncology, 29, 994–1000. https://doi.org/10.1200/JCO.2010.29.8315

    de Haes, H., & Bensing, J. (2009). Endpoints in communication research, proposing a framework of functions and outcomes. Patient Education and Counseling, 74, 287–294. https://doi.org/10.1016/j.pec.2008.12.006

    Detmar, S.B., Muller, M.J., Schornagel, J.H., Wever, L.D., & Aaronson, N.K. (2002). Health-related quality-of-life assessments and patient-physician communication: A randomized controlled trial. JAMA, 288, 3027–3034.

    Dueck, A.C., & Sloan, J.A. (2007). Meeting on the FDA draft guidance on patient-reported outcomes. Value in Health, 10(Suppl. 2), S64–S65. https://doi.org/10.1111/j.1524-4733.2007.00268.x

    Efficace, F., Cartoni, C., Niscola, P., Tendas, A., Meloni, E., Scaramucci, L., . . . Mandelli, F. (2012). Predicting survival in advanced hematologic malignancies: Do patient-reported symptoms matter? European Journal of Haematology, 89, 410–416. https://doi.org/10.1111/ejh.12004

    Ekstedt, M., Børøsund, E., Svenningsen, I.K., & Ruland, C.M. (2014). Reducing errors through a web-based self-management support system. Studies in Health Technology and Informatics, 201, 328–334.

    Falchook, A.D., Tracton, G., Stravers, L., Fleming, M.E., Snavely, A.C., Noe, J.F., . . . Chera, B.S. (2016). Use of mobile device technology to continuously collect patient-reported symptoms during radiation therapy for head and neck cancer: A prospective feasibility study. Advances in Radiation Oncology, 1, 115–121. https://doi.org/10.1016/j.adro.2016.02.001

    Fromme, E.K., Eilers, K.M., Mori, M., Hsieh, Y.-C., & Beer, T.M. (2004). How accurate is clinician reporting of chemotherapy adverse effects? A comparison with patient-reported symptoms from the Quality-of-Life Questionnaire C30. Journal of Clinical Oncology, 22, 3485–3490. https://doi.org/10.1200/JCO.2004.03.025

    Grimsbø, G.H., Engelsrud, G.H., Ruland, C.M., & Finset, A. (2012). Cancer patients’ experiences of using an interactive health communication application (IHCA). International Journal of Qualitative Studies on Health and Well-Being, 7, 15511. https://doi.org/10.3402/qhw.v7i0.15511

    Grimsbø, G.H., Finset, A., & Ruland, C.M. (2011). Left hanging in the air: Experiences of living with cancer as expressed through e-mail communications with oncology nurses. Cancer Nursing, 34, 107–116. https://doi.org/10.1097/NCC.0b013e3181eff008

    Grimsbø, G.H., Ruland, C.M., & Finset, A. (2012). Cancer patients’ expressions of emotional cues and concerns and oncology nurses’ responses, in an online patient–nurse communication service. Patient Education and Counseling, 88, 36–43. https://doi.org/10.1016/j.pec.2012.01.007

    Gwaltney, C.J., Shields, A.L., & Shiffman, S. (2008). Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: A meta-analytic review. Value in Health, 11, 322–333. https://doi.org/10.1111/j.1524-4733.2007.00231.x

    Head, B.A., Studts, J.L., Bumpous, J.M., Gregg, J.L., Wilson, L., Keeney, C., . . . Pfeifer, M.P. (2009). Development of a telehealth intervention for head and neck cancer patients. Telemedicine and e-Health, 15, 44–52. https://doi.org/10.1089/tmj.2008.0061

    Heyn, L., Finset, A., Eide, H., & Ruland, C.M. (2013). Effects of an interactive tailored patient assessment on patient-clinician communication in cancer care. Psycho-Oncology, 22, 89–96. https://doi.org/10.1002/pon.2064

    Heyn, L., Finset, A., & Ruland, C.M. (2013). Talking about feelings and worries in cancer consultations: The effects of an interactive tailored symptom assessment on source, explicitness, and timing of emotional cues and concerns. Cancer Nursing, 36, E20–E30. https://doi.org/10.1097/NCC.0b013e318254af66

    Heyn, L., Ruland, C.M., & Finset, A. (2012). Effects of an interactive tailored patient assessment tool on eliciting and responding to cancer patients’ cues and concerns in clinical consultations with physicians and nurses. Patient Education and Counseling, 86, 158–165. https://doi.org/10.1016/j.pec.2011.04.024

    Hong, F., Bosco, J.L., Bush, N., & Berry, D.L. (2013). Patient self-appraisal of change and minimal clinically important difference on the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 before and during cancer therapy. BMC Cancer, 13, 165.

    Johansen, M.A., Henriksen, E., Berntsen, G., & Horsch, A. (2011). Electronic symptom reporting by patients: A literature review. Studies in Health Technology and Informatics, 169, 13–17.

    Kearney, N., McCann, L., Norrie, J., Taylor, L., Gray, P., McGee-Lennon, M., . . . Maguire, R. (2009). Evaluation of a mobile phone-based, advanced symptom management system (ASyMS©) in the management of chemotherapy-related toxicity. Supportive Care in Cancer, 17, 437–444.

    Kennedy Sheldon, L., Hilaire, D., & Berry, D.L. (2011). Provider verbal responses to patient distress cues during ambulatory oncology visits. Oncology Nursing Forum, 38, 369–375. https://doi.org/10.1188/11.ONF.369-375

    LeBlanc, T.W., Nickolich, M., Rushing, C.N., Samsa, G.P., Locke, S.C., & Abernethy, A.P. (2015). What bothers lung cancer patients the most? A prospective, longitudinal electronic patient-reported outcomes study in advanced non-small cell lung cancer. Supportive Care in Cancer, 23, 3455–3463.

    Lee, J. (2008). Exploring chemotherapy-induced nausea and vomiting: The symptoms, interventions, and relationship to functional status (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses Global. (UMI No. 3311334)

    LoBiondo-Wood, G., Brown, C.G., Knobf, M.T., Lyon, D., Mallory, G., Mitchell, S.A., . . . Fellman, B. (2014). Priorities for oncology nursing research: The 2013 national survey. Oncology Nursing Forum, 41, 67–76. https://doi.org/10.1188/14.ONF.67-76

    Maguire, P., Faulkner, A., Booth, K., Elliott, C., & Hillier, V. (1996). Helping cancer patients disclose their concerns. European Journal of Cancer, 32A, 78–81.

    McIntyre, P. (2015, March 1). Side effects of targeted treatments: Clinicians’ perceptions, patients’ realities. Cancerworld. Retrieved from https://bit.ly/2Hz0JpA

    Melnyk, B.M., & Fineout-Overholt, E. (2011). Evidence-based practice in nursing and healthcare: A guide to best practice (2nd ed.). Philadelphia, PA: Lippincott Williams and Wilkins.

    Mirkovic, J., Kaufman, D.R., & Ruland, C.M. (2014). Supporting cancer patients in illness management: Usability evaluation of a mobile app. JMIR mHealth and uHealth, 2(3), e33. https://doi.org/10.2196/mhealth.3359

    Moher, D., Liberati, A., Tetzlaff, J., & Altman, D.G. (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA statement. PLOS Medicine, 6(7), e1000097.

    Murray, E., Burns, J., Tai, S.S., Lai, R., & Nazareth, I. (2005). Interactive health communication applications for people with chronic disease. Cochrane Database of Systematic Reviews, 4, CD004274.

    National Institute of Nursing Research. (2016). The NINR strategic plan: Advancing science, improving lives. A vision for nursing science. Retrieved from https://bit.ly/2vlMVdi

    Newell, S., Sanson-Fisher, R.W., Girgis, A., & Bonaventura, A. (1998). How well do medical oncologists’ perceptions reflect their patients’ reported physical and psychosocial problems? Data from a survey of five oncologists. Cancer, 83, 1640–1651.

    Petersen, M.A., Larsen, H., Pedersen, L., Sonne, N., & Groenvold, M. (2006). Assessing health-related quality of life in palliative care: Comparing patient and physician assessments. European Journal of Cancer, 42, 1159–1166.

    Reilly, C.M., Bruner, D.W., Mitchell, S.A., Minasian, L.M., Basch, E., Dueck, A.C., . . . Reeve, B.B. (2013). A literature synthesis of symptom prevalence and severity in persons receiving active cancer treatment. Supportive Care in Cancer, 21, 1525–1550. https://doi.org/10.1007/s00520-012-1688-0

    Ruland, C.M. (2006). Clinicians’ perceived usefulness of a support system for patient-centered cancer care. Studies in Health Technology and Informatics, 124, 624–630.

    Ruland, C.M., Andersen, T., Jeneson, A., Moore, S., Grimsbø, G.H., Børøsund, E., & Ellison, M.C. (2013). Effects of an internet support system to assist cancer patients in reducing symptom distress: A randomized controlled trial. Cancer Nursing, 36, 6–17.

    Ruland, C.M., Maffei, R.M., Børøsund, E., Krahn, A., Andersen, T., & Grimsbø, G.H. (2013). Evaluation of different features of an eHealth application for personalized illness management support: Cancer patients’ use and appraisal of usefulness. International Journal of Medical Informatics, 82, 593–603. https://doi.org/10.1016/j.ijmedinf.2013.02.007

    Varsi, C., Gammon, D., Wibe, T., & Ruland, C.M. (2013). Patients’ reported reasons for non-use of an internet-based patient–provider communication service: Qualitative interview study. Journal of Medical Internet Research, 15(11), e246. https://doi.org/10.2196/jmir.2683

    Wagner, L.I., Schink, J., Bass, M., Patel, S., Diaz, M.V., Rothrock, N., . . . Cella, D. (2015). Bringing PROMIS to practice: Brief and precise symptom screening in ambulatory cancer care. Cancer, 121, 927–934. https://doi.org/10.1002/cncr.29104

    White, C., McMullan, D., & Doyle, J. (2009). “Now that you mention it, doctor . . .”: Symptom reporting and the need for systematic questioning in a specialist palliative care unit. Journal of Palliative Medicine, 12, 447–450. https://doi.org/10.1089/jpm.2008.0272

    Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. Journal of Advanced Nursing, 52, 546–553. https://doi.org/10.1111/j.1365-2648.2005.03621.x

    Wintner, L.M., Giesinger, J.M., Zabernigg, A., Rumpold, G., Sztankay, M., Oberguggenberger, A.S., . . . Holzner, B. (2015). Evaluation of electronic patient-reported outcome assessment with cancer patients in the hospital and at home. BMC Medical Informatics and Decision Making, 15, 110.

    Wolpin, S., Berry, D., Austin-Seymour, M., Bush, N., Fann, J.R., Halpenny, B., . . . McCorkle, R. (2008). Acceptability of an electronic self-report assessment program for patients with cancer. Computers, Informatics, Nursing, 26, 332–338.

    Wu, A.W., White, S.M., Blackford, A.L., Wolff, A.C., Carducci, M.A., Herman, J.M., & Snyder, C.F. (2016). Improving an electronic system for measuring PROs in routine oncology practice. Journal of Cancer Survivorship, 10, 573–582. https://doi.org/10.1007/s11764-015-0503-6