Annals of Oncology Advance Access published May 19, 2015

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Annals of Oncology 00: 1–13, 2015 doi:10.1093/annonc/mdv181

Patient-reported outcomes in routine cancer clinical practice: a scoping review of use, impact on health outcomes, and implementation factors D. Howell1*, S. Molloy2, K. Wilkinson2, E. Green3, K. Orchard4, K. Wang4 & J. Liberty4 1 Nursing, University Health Network (Princess Margaret Cancer Centre), Toronto; 2Symptom Management, Cancer Care Ontario, Toronto; 3Nursing and Psychosocial Oncology, Cancer Care Ontario, Toronto; 4Evidence Search and Review Service, Cancer Care Ontario, Toronto, Canada

Received 8 August 2014; revised 6 January 2015 and 30 March 2015; accepted 31 March 2015

introduction Cancer patients experience significant physical and psychosocial consequences of cancer and treatment that impacts quality of life (QoL) [1–5]. These consequences may be under-recognized and under-treated in oncology practice, resulting in greater morbidity that is costly to patients and the health system [6–9]. Patient-reported outcome measures (PROMs) are advocated for use in routine cancer clinical practice [10–12] for early detection of distress [13, 14] and as a performance metric for evaluating the quality of care on health outcomes [15, 16]. A PROM is defined as ‘any report coming directly from the patient about a health condition and its treatment’ using a selfreported measure [17]. PROMs focus on physical symptoms, treatment toxicities, or psychosocial problems or global healthrelated quality of life (HRQoL) impacts of a health condition [18]. PROMs that capture the ‘whole-person’ impact of cancer *Correspondence to: Dr Doris Howell, Oncology Nursing Research and Education, University Health Network, 610 University Avenue, Room 15-617, Toronto, ON M5G 2M9 Canada. Tel: +1-416-946-4501; E-mail: [email protected]

and treatments on health outcomes are recommended by patients, clinicians, and decision makers [19]. Globally, cancer organizations have published information about the feasibility and effects of using PROMs in routine clinical practice [20–23]. PROMs are valued for ensuring that the patients’ experience of cancer and treatment is represented in the measurement of health [24] and for capturing the effectiveness of clinical interventions [25]. There is a need to identify the effects of PROMs when used in routine cancer practice and the implementation issues to be addressed to inform health policy for cancer systems [26]. While systematic reviews have focused on the effectiveness of PROMs more generally in healthcare [27, 28] and in specific settings (e.g. palliative care) [29], previous scoping reviews focused on PROMs implementation in routine cancer care were not identified. This review sought to answer the following research questions: (i) which PROMs does the published, English literature show have been implemented for use in routine cancer clinical practice and in what phases of the trajectory; (ii) what are the barriers and enablers influencing clinical uptake of PROMs in routine care; and, (iii) what is the

© The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: [email protected].

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Background: This review focused on the identification of patient-reported outcome measures (PROMs) used in routine cancer clinical practice, the impact on patient, provider, and system outcomes, and the implementation factors influencing uptake. Methods: A scoping review of the published health literature was conducted using empirical databases, namely, Ovid Medline (2003 to September 2013), CINAHL (2003–2013) and PsycINFO (2003–2013). Scoping reviews are systematic literature reviews in a broad topic area that provide relevant and quantified results about the knowledge available on a particular topic and aim to rapidly map and synthesize the evidence to emphasize what is known. Results: From a total of 2447 unique publications, 30 articles that met eligibility criteria were reviewed. PRO use appears to be acceptable to patients, enables earlier detection of symptoms and may improve communication between clinicians and patients. However, the impact of routine PROMs collection on health outcomes is less clear and high-quality research is still warranted. Conclusion: PROMs use in routine cancer clinical practice is growing with improvements on essential care processes shown but a number of implementation barriers must still be addressed. The lack of standardization in PROMs used in cancer organizations may make it difficult to use these data for quality monitoring in the future. Key words: cancer, patient reported-outcomes, implementation barriers, routine practice, review

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impact of the routine use of PROMs on outcomes at the patient, provider, and system levels.

methods We carried out a systematic scoping review of the literature to provide a narrative synthesis of PROMs implementation in cancer clinical practice. Scoping reviews provide quantified results about the knowledge available on a particular topic and include a broad range of evidence. The aim of scoping a review is ‘to map rapidly the key concepts underpinning a research area and the main sources and types of evidence available’ [30]. Scoping reviews differ from systematic reviews as they focus on a broader range of evidence and research questions and seldom is the quality of the evidence appraised [31].

data sources

search terms A combination of keywords for cancer (e.g. neoplasms), cancer, and treatment symptoms (e.g. anxiety, pain, fatigue) with terms for PROMs (e.g. self-report questionnaires, self-assessment, PRO, PROMs, PROMIS, outcomes), implementation/process outcomes (e.g. barriers, impact), and regular or routine practice (e.g. clinical, routine, practice, practice patterns) were combined with Boolean logic (and/or) to identify studies. The search terms were informed by the PROMs-Cancer Core Framework, a person-focused framework for PROMs use in routine cancer care [19]. This framework was adapted from the PROMIS® framework [32] and guided the use of specific search terms for physical, psychosocial, social

selection criteria Articles were included if they: (i) reported on the ‘routine’ use of PROMs; (ii) the PROM was completed by the patient (as opposed to a clinician or caregiver) and resulted in a numeric value to indicate the patient’s state of well-being, symptoms, or ability to function; (iii) included cancer patients or survivors in their study population; and (iv) evaluated outcomes at the patient, clinical practice, or care process or system-level or barriers/enablers to the uptake or use of PROMs. For the purpose of this review, ‘routine’ use was defined as ‘systematic and standardized outcome measure(s) in clinical practice with every patient eligible to complete the PROMs as part of a standardized assessment’ [33]. Articles were also limited to 2003 onwards, English language, and primary quantitative research studies, systematic literature reviews or qualitative studies.

data screening and abstraction Results were imported and screened using a Reference Manager database. Titles and abstracts were separately screened by two reviewers (JL and KW) with a portion of articles doublescreened by both. Any disagreements and uncertainties were discussed with adjustments made to the inclusion and exclusion criteria as per scoping review methods. Full-text articles were retrieved if inclusion criteria were met or if the abstract did not contain sufficient information; full texts were screened in duplicate by two independent reviewers (KW and KO) with disagreements resolved by discussion including a third reviewer (JL). Data were extracted by one reviewer (KO) and assessed by a second reviewer (KW or JL). Extraction was guided by a template developed for this review and approved by all authors and included data on: study design and purpose, population, setting, patient characteristics, PROMs used, outcome(s) assessed, and study results.

700 600 500 400 300 200 100 0 2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Figure 1. Trend of published articles citing PROMs as a MeSH Term in PubMed from 2003 to 2013. Source: GoPubMed (PubMed Trend Analysis Tool).

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Databases searched included: Ovid Medline (2003 to September 2013), CINAHL (2003–2013) and PsycINFO (2003–2013). As shown in Figure 1, a start date of 2003 was selected for all databases as there was minimal literature relating to PROMs implementation before this time. References from relevant articles were also scanned to identify other publications for inclusion in the review using forward reference searching. Web sources were used to identify PROMs implementation programs internationally, and agencies known to use or report on PROMs for additional publications (Table 1).

health domains, and symptom sub-categories. The search terms and search strategy was initially developed for Medline and adapted for the remaining databases (supplementary Material S1, available at Annals of Oncology online).

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patient and clinical practice outcomes

Table 1. List of search sources Canadian jurisdictions

International jurisdictions

Others

Ontario British Columbia Alberta Saskatchewan Manitoba Quebec Nova Scotia Newfoundland

UK (National Health Service) Australia New Zealand United States European Union (general search)

Agency for Healthcare Research and Quality National Cancer Institute Patient-Centred Outcomes Research Institute (PCORI) Institute for Healthcare Improvement (IHI) International Society for Pharmacoeconomics and Outcomes Research (ISPOR)

results

cancer type and phases PROMs were used across most disease types including less prevalent cancers such as melanoma. Of the five most prevalent cancers, PROMs were tested most often in breast cancer [38–48] and least often in prostate cancer [44, 45]. As shown in Table 2, the most frequently used PROMs was the European Organization for Research and Treatment of Cancer (EORTC-QoL-C30) usually combined with a disease specific module (n = 6) [46, 47, 49–52] and the Hospital Anxiety and Depression Scale (HADS) (n = 4) [39, 46, 47, 51, 52]. Distress screening measures were diverse and included HADS (n = 4), DT (n = 1), SDI (n = 1), or the POMS-17 (n = 1). The Common Terminology Criteria for Adverse Events in a PRO format (PRO-CTCAE) measures (n = 1) and the PROMIS® short forms (n = 1) were seldom used [21, 45]. PROMIS® is a series of short forms, item banks, and computerized adaptive tests to assess PROs in chronic illness and cancer [32]. PROMs were completed mostly during the treatment phase of cancer [39–43, 45–48, 50–56]. The Electronic Self-Report Assessment–Cancer (ESRA-C) and the Supportive Care Needs Survey (SCNS-SHORT) were the only measures used in both pretreatment and treatment phases [39, 52], while five measures were used in both treatment and post-treatment phases [EORTC QLQ-C30; Close Persons Questionnaire (CPQ); Edmonton Symptom Assessment System (ESAS); EuroQol (EQ-5D); and the Social Difficulties Inventory (SDI)] [40–43, 46, 47, 50–53, 57, 58]. The majority of PROMs were used in the United States [20, 41, 44, 45, 48, 49, 53, 54] followed by the United Kingdom [46, 47, 52, 57, 59–62].

patient-level outcomes patient satisfaction. Two randomized, controlled trials (RCTs) evaluated the effect of PROMs on patient satisfaction with clinical consultations [using modified versions of the Patient Satisfaction Questionnaire (PSQ)]. Both studies reported a positive effect on the PSQ but results failed to reach statistical significance [40, 55]. In a systematic review (n = 16 studies) of routine collection of PROMs, 13 studies (81%) reported a positive effect on patient satisfaction [35]. However, a potential ceiling effect was noted due to patients in both groups reporting very high baseline satisfaction scores and the definition of patient satisfaction varied across studies. perceived quality of care. Three prospective feasibility studies conducted at cancer centres in the US used questionnaires (i.e. acceptability surveys) or interviews to evaluate the patients and clinicians perceptions of the effect of PROMs on quality of care [21, 45, 53, 58]. In a feasibility study, health care providers (n = 9) were interviewed before the implementation of a system to routinely collect PROMs; most indicated that such a system would ‘likely improve the quality of patient care’ [54]. However, variations were noted in the percentage of patients who indicated actual quality of care improvement; reported range of 39% to 65% [21, 45, 53]. In a survey of physicians in one study, 65% indicated that quality of care was improved [21]. However, studies were limited by small sample sizes and a lack of comparability in terms of direct outcomes measured. patient outcomes. We identified a total of six studies evaluating the impact of routine use of HRQoL instruments on overall patient well-being [39, 40, 47, 48, 51, 55]. A significant overall effect on HRQoL over time between the intervention and control arms was reported in one RCT controlling for time and performance status [47], whereas four remaining studies (including three RCTs and one sequential cohort) found no significant effect [39, 40, 48, 51]. Mixed findings were found for PROMs use in paediatric oncology consultations, with a significant positive change in HRQoL for children ages 5 to 7 years, but no effect for children aged 0 to 4 or 8 to 18 [55]. Different instruments were used to account for developmental stage and some may be more responsive to change. symptom management. Symptom management may be improved by PROMs use. In a feasibility study, 18 patients and caregivers reported that an electronic system to collect PRO data would likely result in improved patient self-management [58]. Additionally, in a controlled study by Boyes et al. [39] found that when results were generated from a computerized PROM and placed in patients’ files, those reporting debilitating physical doi:10.1093/annonc/mdv181 | 

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As shown in the PRISMA diagram (Figure 2), a total of 3297 records were identified, with 2536 unique publications screened for eligibility following removal of duplicates. A total of 220 full-text articles were retrieved for a second round of screening. We present the findings of 30 independent articles that met the inclusion criteria supplemented with data from four systematic reviews [34–37]. All studies were synthesized to report on the effectiveness of PROMs implementation on patients, provider and system outcomes. We also identified enablers and barriers to routine use of PROMs in cancer clinical practice across studies.

A range of outcomes were assessed for routine implementation of PROMs as follows: (i) patient outcomes i.e. satisfaction, patient perceptions of quality of care, health outcomes, and acceptability; and, (ii) clinical practice outcomes in terms of patient–clinician communication, effect on decision making, symptom monitoring, and length of clinical encounter (Table 3). The statistical evidence for the effectiveness of PROMs in influencing each of these outcomes is shown in Table 4.

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Ovid Medline

CINAHL

PsycINFOL

Grey-Literature

(2003–2013)

(2003–2013)

(2003–2013)

(2003–2013)

2436 titles

365 titles

389 titles

107 titles

3297 Records identified 761 Duplicates removed

2356 Non-duplicates screened

2316 articles excluded after title/abstract screen

220 full text to retrieve 26 full text not available

1 Reference added from review of article reference lists

Screening criteria applied

34 Articles included (30 primary studies/4 review articles

161 articles excluded after full text screen

4 Systematic reviews reviewed separately

Figure 2. PRISMA flow chart.

symptoms before a follow-up oncologist visit were significantly less likely to do so at the next visit compared with patients whose results were not placed in their file (OR = 2.8, P = 0.04). PRO symptom reporting may also increase symptom-related actions taken by clinicians [45]. Seow et al. [45] examined the impact of the routine use of ESAS on the frequency of clinical actions. The results demonstrated that visits where patients reported higher ESAS scores for pain or shortness of breath were significantly associated with higher rates of pain documented in patient charts and of symptom-specific actions in breast and lung cancer patients. Although the association between higher ESAS scores and higher rates of clinical action does not imply causality, it supports the notion that standardized, electronic screening may improve the clinician’s attention to symptom severity.

the future [64]. Three studies evaluated patient acceptability of PROMs [39, 40, 58]. In a controlled study (N = 36), 36 patients evaluated the acceptability of completing the HADS and the SCNS-SHORT on a touch-screen computer [39]. The process took 15–20 min, with results of the questionnaires fed-back to clinicians. The majority of patients (83%) reported willingness to complete the survey each time they visited their oncologist. In another study, 99% of patients believed it would be useful to introduce a touch-screen computerized intervention using the EORTC QLQ-C30 into standard practice at their outpatient clinic [40]. Patients’ acceptability of completing four different PROrelated assessment tools using a computer found that 100% of the 18 patients would recommend the system to providers [58].

provider/clinical practice outcomes acceptability. Acceptability is defined as the action of consenting to or the expression of desire to receive or undertake a measure in

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patient–clinician communication. Communication between patients and clinicians on topics such as emotional functioning,

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Screening criteria applied

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Table 2. PROMs used by cancer phase with studies that used measure in brackets Outcome focus

Cancer phases Pre-treatment

PROMIS measures

Symptom measures (Generic/disease-specific)

ESRA-C (54)

Treatment toxicities Emotional distress/mood

HADS (39)

Social support/difficulties Supportive care needs Quality of life

SCSN-Short (39) FACT-G (20,48)

Treatment

Post-treatment

PROMIS-short forms for anxiety, depression, fatigue, pain impact, physical function, and satisfaction with social roles (45) EPIC-SF (45) ESAS (43, 58, 59) ESRA-C (54) PRO-CTCAE (21) HADS (39, 46, 47, 52) POMS-17 (48)

MDASI (20) ESAS (58, 59) BSI

Population specific (paediatrics; palliative)

FACT-G (20, 48) EQ-5D (58)

PedsQL (55, 60) TAPQOL (55, 60)

PRO-CTCAE, patient-reported outcomes-common terminology criteria for adverse events; SCNS-Short, supportive care needs short; MDASI, MD Anderson Symptom Inventory; MSQ, Mood Symptom Questionnaire; PedsQL, Pediatric Quality Of Life Inventory-Generic Core scale; TAPQOL, Preschool Children Quality Of Life; European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC—QLQ-C30 (core questionnaire) plus Lung Cancer Module (EORTC-LC13) and EORTC-Brain Cancer Module (EORTC QLQ-BN 20); ESAS, Edmonton Symptom Assessment System; UW-QOL, University of Washington Quality of Life; BYI-II, Beck Youth Inventory; BSI, Brief Symptom Inventory; MSQ, Mood and Symptom Questionnaire; CAGE, the Cage Questionnaire for Alcohol Assessment; DT, distress thermometer; PROMIS, Patient-Reported Outcome Measurement Information System; EPIC-SF, Expanded Prostate Cancer Index Composite-Short Form; SDI, Social Difficulties Inventory; CPQ, Close Person Questionnaire; ESRA-C, Electronic Self-Report–Cancer; POMS-17, Profile of Mood States; FLIC, Functional Living Index–Cancer.

HRQoL, and sensitive issues has been shown to increase, especially in cases where clinicians have been provided with patient questionnaire results. Improvement in communication related to emotional, psychosocial, and cognitive functioning was shown in the intervention group in which oncologists received patients’ Pediatric Quality of Life Inventory (PedsQL) and TNO-AZL Preschool children Quality of Life (TAPQOL) scores, compared with the control group, where the oncologist did not receive the results [63]. Similar findings were reported for an intervention group whose computerized EORTC QLQC30 results were sent to their oncologist, compared with those whose results were not [51]. Emotional functioning was discussed more frequently between patients and clinicians in the intervention group (P = 0.015) [51]. HRQoL was discussed significantly more often (P = 0.009) in an intervention group that completed the EORTC QLQ-C30 compared with a control group that did not complete the measure [40]. Takeuchi et al. [46] also found similar results; that patients who complete PROMs (EORTC QLQ-C30, HADS) tend to discuss their symptoms more with their physicians (P = 0.008) compared

with a control group (P = 0.040). An RCT mirrored these results, finding that symptoms assessed using the EORTC QLQ30 were discussed more frequently in the intervention group (P = 0.03), specifically chronic and non-specific symptoms [47] without prolonging the consultation. Chapman et al. [62] reported that use of the Minnesota Satisfaction Questionnaire (MSQ) allowed clinical staff to ask questions about sex more comfortably, noting that having the topic identified by patients through self-report helped staff raise the question in a more natural manner. Two systematic reviews also concluded that PROMs use resulted in a positive effect on patient–clinician communication [35, 36]. early detection and monitoring of symptoms. Four studies evaluated whether PROMs were useful in helping clinicians detect and control patient symptoms [39, 45, 50, 62]. First, Snyder et al. [45] reported that clinicians were most likely to agree that an intervention involving the use of PROMIS®, EPIC, and EORTC QLQ-BR23 helped them to identify areas of concern (58%). Secondly, Erharter et al. [50], in their implementation of

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SDI (52) CPQ (52) SCNS-Short (39) EORTC QLQ-C30 (46, 47, 50, 51, 52, 58) EQ-5D (21, 58) FLIC (48) EORTC QLQ-C30 (51) EORTC QLQ-BN20 (50) EORTC QLQ-LC13 (51) EORTC QLQ-BR23 (45, 47) EORTC QLQ-CR38 (47)

HADS (52) DT (61) MSQ (65) SDI (52) CPQ (52)

Design

Sample/population

PROMs used

Member of medical team given feedback

Patient-level outcomes

Process/system-level outcomes

Abernethy et al. [20]

Feasibility study (descriptive)

Metastatic breast cancer (n = 65) and gastrointestinal cancer (n = 113)

FACT-G, MD Anderson Symptom Inventory, Patient Care Monitor

N/A

Basch et al. [21]

Prospective feasibility study

80 women (gynaecological cancers)

PRO-CTCAE, EQ-5D

Physician

Satisfaction: 75%–88% of patients were satisfied with the use of the system. Facilitated discussions: 74% of patients said it helped them remember symptoms to discuss with doctor. Perceived quality of care: 65% ‘agreed’ that the use of the PROMs system improved their quality of care. None strongly agreed.

Berry et al. [54]

Prospective randomized, controlled trial

660 cancer patients, 56 clinicians Intervention group: n = 295, PROM + feedback Control group: n = 295, PROM, no feedback

ESRA-C (Electronic SelfReport Assessment– Cancer)

Physician and nurses (intervention group only)

N/A

Boyes et al. [39]

Prospective controlled trial

HADS, SCNS-SHORT

Placed in patients file (intervention group only)

Symptom management (physical): Improved (OR = 2.8, P = 0.04). Anxiety and depression: No significant difference (P = 0.09 and 0.20, respectively).

Chapman et al. [62]

Prospective feasibility study (descriptive)

48 patients (n = 25 intervention), 4 clinicians Intervention group: n = 25, PROM + feedback Control group: n = 23, PROM, no feedback 75 patients, 6 staff (nurses, occupational, and physiotherapists)

Clinic flow: No disruption (anecdotal —no data reported). Problem identification/screening: Facilitated (anecdotal—no data reported). Clinical decision making: 7/9 clinicians noted basing clinical decisions on data. Patient–clinician communication: 90% of patients agreed/strongly agreed that the use of the system improved discussions with doctor/nurse; 94% of patients agreed/strongly agreed it made it easier to remember symptoms at the clinic visit. Patient–clinician communication: More likely to discuss symptoms and HRQoL issues if score reached threshold value. Average length of clinic visit: No significant difference (P = 0.352). Promoted appropriate referrals: Perceived by 53.6% of clinicians. Promoted problem identification: Perceived by 64.3% of clinicians. Length of clinic visit: Clinicians anecdotally reported that discussing feedback with patients increased time by 3–5 min.

MSQ (Mood and Symptom Questionnaire)

PROM completed by patient and staff together and discussed at time of completion

N/A

Improved identification of problems: A clinical vignette illustrated how the MSQ helped identify/target distressing issues. Patient–clinician communication: Staff felt more comfortable discussing the item about intimacy; patients often misinterpreted the meaning of this item.

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Table 3. Impact of PROMs on patient and provider/clinical level outcomes

13 clinicians

ESAS, EQ-5D (implemented through HealthHUB)

Sent to physician’s computer (a software called CareHUB)

Engelen et al. [55, 63]

193 child patients Intervention group: n = 94, PROM and feedback Control group: n = 99, PROM, no feedback

PedsQL Generic Core Scale, TAPQOL (Preschool Children Quality of Life) Implemented through QLIC-ON PROfile

Patient response summarized and given to respective oncologist (intervention group only)

110 patients

EORTC QLQ-C30, EORTC QLQ-BN20

Feedback immediately available for physicians in chart form

Erharter et al. Feasibility study [50]

Use in practice: 2/13 Clinicians reported using standardized tools to assess patients in their care. Symptom monitoring: Clinicians stated in interviews that HealthHUB would provide a useful record of patient symptom experience. Satisfaction: Intervention group showed Patient–clinician communication: Significant increase in discussion in positive trend in satisfaction with intervention group for emotional and consultation but no statistically psychosocial functioning, and in time significant difference found. spent on emotional and cognitive Health outcomes: Children in the functioning (P < 0.05). Topics on intervention group aged 5–7 scored emotional functioning and ‘feeling blue’ significantly better for self-esteem, were only raised in the intervention family activities, and psychosocial group summary (P < 0.05). No differences found for children ages 0–4 and 8–18. Problem identification: Significant increase in emotional and cognitive problems identified in intervention group (P < 0.05). Nurses’ awareness of patient HRQL problems was significantly better in intervention group for daily activities, pain, and quality of life (P < 0.05). Effect on referrals: No significant difference in the amount of referrals was found between groups. Average length of visit: No significant difference between groups (P = 0.052). Acceptability: Reported high patient N/A acceptance (data not reported). 22/ 110 patients were unable to complete the PROMs due to illness

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Sequential controlled study

N/A

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Cox et al. [57] Qualitative feasibility study

Design

Patient-level outcomes

PROMs used

Member of medical team given feedback

Hilarius et al. Sequential [40] controlled study

219 patients, 10 nurses Intervention group: n = 111, PROM Control group: n = 108, no PROM

EORTC QLQ-C30

Kallen et al. [58]

Feasibility study

9 patients and their caregivers (i.e. total n = 18), 9 clinicians

Nicklasson et al. [51]

Randomized, controlled trial

171 patients Intervention group: n = 84 PROM + feedback Control group: n = 88 PROM, no feedback

Patients and caregivers only: ESAS and CAGE Clinicians only: MDAS, ECSCP, and CAGE EORTC QLQ-C30, EORTC QLQ-LC13

Feedback given to nurses Satisfaction: Patients responded to in summarized graphs questions on satisfaction with quality (intervention group of care, interpersonal manner, only) communication, and continuity of care. No significant differences were found between the intervention and control group (data not reported). Evaluation of intervention: 89% of patients evaluated the summary profile as accurate. Acceptability: 99% reported it would be useful to introduce the intervention into standard practice at their clinic. Feedback immediately Acceptability: 60% of patients and available to physician caregivers reported a desire to use during visit the system frequently.

Rosenbloom et al. [48]

Randomized, controlled trial

213 patients Intervention group 1: n = 73 PROM + feedback Intervention group 2: n = 69, PROM + structured interview completed Control group: Usual care (n = 71)

Clinicians received N/A feedback from patients (intervention group only)

Feedback provided to Satisfaction: No significant difference FLIC (Functional Living nurses in intervention was found between groups on Index–Cancer), FACT-G, group 1 only satisfaction with technical quality, Brief POMS-17 (Brief time spent with doctor, interpersonal Profile of Mood States), aspects, convenience, communication, PSQ-III (Patient financial aspects and general Satisfaction Questionnaire) satisfaction. Health outcomes: No significant difference was found in FACT-G or FLIC scores.

Process/system-level outcomes Patient–clinician communication: HRQL topics discussed significantly more in intervention group (P = 0.009). Furthermore, 100% of nurses reported the intervention facilitated communication, especially with ‘difficult subjects’.

Symptom monitoring: All clinicians reported the system would improve patient monitoring. Patient–clinician communication: Emotional functioning was discussed significantly more often in the intervention group by doctors (P = 0.018) and doctors or patients combined (P = 0.015). Promoted appropriate interventions: Diagnostic and therapeutic interventions directed to emotional and social concerns were statistically high in the intervention group (P = 0.0036). N/A

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Table 3. Continued

Retrospective analysis

648 patients (hospital charts) ESAS

Summary of results attached to chart for oncologist

Snyder et al. [45]

Prospective single-arm study

47 patients (n = 34 breast cancer, n = 13 prostate cancer) and their clinicians

PROMIS-short forms, EORTC QLQ-BR23, EPIC

Clinicians viewed results Completion rate: Patients were more likely to have no missing items when through the electronic PROMIS was completed at home health record and versus the clinic (84% complete versus Patient-Viewpoint 67%). computer program Patterns of use: Patients were more likely to initiate discussion if about body image, hair loss, future perspective, or hormonal function.

Takeuchi et al. [46]

Retrospective analysis of Velikova (2004)

187 patients, 28 clinicians Intervention group 1: n = 94 PROM + feedback Intervention group 2: n = 40 PROM, no feedback Control group: n = 47 no PROM

EORTC QLQ-C30, HADS

N/A Clinicians received feedback before clinical encounter (intervention group 1 only)

Velikova et al. Prospective [47] randomized, controlled trial

187 patients, 28 clinicians Intervention group 1: n = 94 PROM + feedback Intervention group 2: n = 40 PROM, no feedback Control group: n = 47 no PROM

EORTC QLQ-C30, HADS

Wright et al. [52]

183 patients

Promotion of intervention: Analysis revealed that as ESAS scores for pain and increased, the proportion of visits with a pain-related action increased significantly (P < 0.001). Patterns of use: A median number of three potential issues were identified by PROMs, and a median of 1 was discussed. Clinical decision making: 30% of clinicians reported PROM resulted contributed to patient management (details not provided). Identify problems: 38% used PROMs to identify issues to discuss. Patient–clinician communication: Patients in intervention group 1 discussed more symptoms during consultation than those in the intervention group 2 (P = 0.008) and the control group (P = 0.040). However, PROM feedback did not promote questions from clinicians about patients’ symptoms. Patient–clinician communication: More symptoms were discussed in the intervention group 1 group than the control (P = 0.03). Average length of encounters: No difference in length of consultation between groups (P = 0.69). Identify problems: 27% of clinicians reported PROMs helped identify problems for discussion.

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Clinicians received Health outcomes: An improvement in feedback before FACT-G and well-being scores was clinical encounter detected between intervention group 1 (intervention group 1 and control (P = 0.006; P = 0.008, only) respectively), but not intervention group 1 and 2 (P = 0.80). A secondary analysis revealed intervention group 2 had significantly better scores for HRQL, physical and functional wellbeing (P = 0.01) than the control group. SDI (Social Difficulties Feedback given to health N/A Rate of referral: Patients who scores above Inventory), HADS, EORTC professionals the cut-off point had a referral rate of QLQ-C30, CPQ (Close 24.1%, compared with 5% for those Persons Questionnaire) below the cut point score.

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Cross-sectional study

N/A

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Seow et al. [43]

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Table 4. Summary of impact of PROMs on patient and clinical practice outcomes PROMs

=[48] =[48] =[48] +[39] +[39]

Patient health outcomes =[48] =[48] =[48] =[39] =[39] =[40, 51]

+[59] +[22] +[22] +[22] ±[21] ±[21]

Clinical practice outcomes Acceptability Patient–clinician Clinical communication decision making

+[39] +[39] +[40] +[59]

=[55] =[55]

+[46] +[46, 47, 51]

+[51] +[43] +[22] +[22] +[22] +[21] +[21] +[59]

+[55, 60] +[55, 60] +[65]

+/[20, 48] +[51]

+[51]

Symptom monitoring

Length of clinical encounter

+[50] +[22] +[22] +[22] +[21] +[21, 58] +[59] +[55] +[55] +[65] +[57] +[50] +[20]

+[51] +[54] +[61] +[52]

+, signifies a positive finding; =, signifies no statistically significant findings; ±, signifies mixed results.

the EORTC QLQ-C30 and EORTC QLQ-BN20, reported that clinicians found monitoring HRQoL contributed to ‘better detection of symptoms’, particularly for loss of bladder control. Thirdly, Chapman et al. [62] found that the MSQ helped clinicians identify and target the problems that were causing the most distress to their patients. Finally, a systematic review by Chen et al. [65] found 11 studies reporting a strong or modest effect on the increased monitoring of symptoms from implementation of PROMs, and 15 studies reported a strong or moderate positive effect on detection of unrecognized symptoms [based on The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system] [66]. clinical decision making. Six studies assessed whether clinicians used questionnaire results to help guide clinical decision making [21, 45, 51, 53, 54, 58, 60, 63]. Three studies suggest use of PROMs may support clinical decision making [21, 51, 60]. PROMs use may also facilitate the identification of need for patient referral [54], with an increase in rate of referrals to psychosocial care shown [51, 60]. For example, Nicklasson et al. [51] found that providers who were given EORTC QLQ-C30 results were more likely to refer those expressing emotional and social concerns to diagnostic or therapeutic interventions compared with providers who did not receive those results (P = 0.036). Similarly, Lynch et al. [60] found high staff adherence to use of the distress thermometer,

 | Howell et al.

with all patients who reported scores above the threshold score for distress (score >4) referred to the clinical psychologist. Additionally, physicians who received pain scores from PROMs provided analgesic prescriptions that were significantly different, and were more likely to make changes to regular prescriptions with patients for whom they had received PROMs data [36]. A number of qualitative studies have also characterized the use of PROMs for clinical decision making. Clinicians have reported using PROMs to confirm their knowledge of patients’ problems, provide an overall assessment of the patient, identify issues to discuss, and contribute to patient management [45, 53, 58]. In particular, Basch et al. [53] reported that clinicians are more likely to discuss a symptom if it is flagged by an automated system at visits and does not increase the duration of the visit. Although these self-reports seem to indicate that PROMs are useful in supporting clinical decision making, no difference in actual patient management activities between intervention and control groups was found in an RCT when recorded clinical encounters were analysed [47]. This included both the number of medical actions (i.e. decisions on cancer treatment, symptomatic/ supportive treatment, investigations, or referrals) and nonmedical actions (i.e. advice on lifestyle, coping, and reassurance). Kallen et al. [58] reported that most clinicians provide positive feedback for electronic PROMs (ESAS) and suggest that the integration of PROMs into routine clinical practice would improve use of patient assessments in decision making, identification of

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FLIC PSQ-III Brief POMS -17 SCNS-SHORT HADS EORTC QLQ-C30 ESAS PROMIS-Short Forms EPIC EORTC QLQ-BR23 PRO-CTCAE EQ-5D ECS-CP PedsQL TAPQOL MSQ UW-QOL EORTC QLQ-BN20 FACT-G EORTC QLQ-LC13 ESRA-C DT SDI

Patient outcomes Patient Perceived satisfaction quality of care

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causal relationships between care events and outcomes, monitoring of patients, and operational efficiencies. However, Hughes et al. [67] described relatively negative feedback from nurses regarding the use of PROMs due to time constraints and perceived ‘uncontrolled symptoms’.

when they feel well) [41, 45, 53]. Enablers to patient use may include more disease-specific questions and simplifying scales (e.g. scale with verbal descriptors) [42].

length of clinical encounter. Several studies did not find a significant impact of PROMs implementation on the length of the clinical encounter [47, 53–55]. Velikova et al. [47] found that when aggregate results of PROMs were shared with physicians before the clinical encounter, discussions of chronic non-specific conditions were more frequent (P = 0.03) but the length of the encounter was not significantly different between groups. Similarly, Engelen et al. [55], found no significant differences between groups in terms of average length of clinical encounter, despite increased emotional and psychosocial discussions in the intervention group when HRQoL results were shared with clinicians before consultation. Berry et al. [54] also revealed parallel results with the ESRA-C: there were no significant differences in average length of clinic visit between the intervention group (for which clinicians were informed of ESRA-C results before the clinic visit) and the control, despite the increase in discussion of symptoms and QoL issues during the visit. In terms of the actual duration of PROMs completion, Erharter et al. [50] measured the average total time required for 110 patients to complete the EORTC QLQ C-30 and the companion brain module-BN20 administered on a tablet personal computer. QoL was evaluated 521 times in total, averaging 4.74 times per patient. The time it took at first assessment was ∼10 min, including explanation and completion time. Using this measure, total time for completion decreased over the course of the study; at the fifth assessment, the average duration was 3.7 min [50].

The body of literature on the use of PROMs in routine cancer clinical care has increased substantially in the last decade likely due to use of electronic systems for data collection [16, 71]. In spite of our scoping review being limited to select empirical databases and the published English literature, we did identify some trends in the use of PROMs for routine clinical practice. First, the EORTC QLQ30 was the most commonly used PROM likely due to its comprehensiveness in measuring the impact of cancer across multiple domains of functioning ( physical, role, cognitive, emotional, social) but also for its ability to capture disease-specific effects using modules. A second trend was the use of PROMs as a manoeuvre for screening for emotional distress, unmet supportive care needs, or social difficulties. This is likely due to the emphasis on screening for distress as a standard of care in the United States and globally [14]. Furthermore, a wide variety of PROMs were used with little standardization across studies or health care organizations and the same measures were applied regardless of treatment modality or cancer phase. Similar to other reviews, we found that PROMs implementation improves communication about symptoms and QoL. However, in a recent systematic review of trials of PROMs implementation in oncology practice, only small effects for symptom reduction were shown and the effects on QoL, supportive care needs, and psychological symptoms were equivocal [72]. In most studies, it was unclear how PROMs data were used in devising or evaluating treatment plans. Studies suggest that more attention needs to be paid to these processes of care and to better training of clinicians in use of PROMs data in both the interpretation of change in PROMs scores and for intervention selection [12, 73]. The use of evidence-based knowledge translation strategies may be useful to facilitate an effective response to PROMs by clinicians and their integration in routine practice [74]. None of the studies addressed the role of patient symptom self-management or included training of patients in the use of PROMs data for evaluating effectiveness of self-management strategies. The psychometric quality of PROMs in regards to their responsiveness to change was also not addressed in most of the studies. This may make it difficult for clinicians in the interpretation of meaningful change and may be a barrier to their use [33, 75]. Moreover, most studies focused on the implementation of HRQoL measures in routine care with little consideration of the other care processes that would need to be addressed for a change in HRQoL to be shown empirically [73]. The relationship between clinical communication and health outcomes i.e. HRQoL is complex and the targeting of interventions to more proximal outcomes such as symptom reduction may be critical to achieving an overall effect on HRQoL [73, 76, 77]. A number of implementation issues to use of PROMs data by clinicians will need to be considered: (i) limiting data collection so as to minimize patient burden and completion time to within ∼30 min, (ii) collecting PRO data at baseline and selected followup times while minimizing the number of assessments, (iii) considering whether measurement equivalence has been established

In general, acceptability of the routine collection and use of PROMs has been high among patients [39–41, 50, 58] and clinicians [20]. However, a number of barriers are identified including time constraints (e.g. concern that there may not be enough time to address issues that arise from PROMs) [36, 44, 59, 67, 68]; a lack of training on the use and interpretation of PROM data [34, 68]; and ‘value’ add of using PROMs [49, 62]; liability issues regarding what to do in cases where patients electronically report on PROMs between visits [53]; and the perception that PROMs may be ‘intrusive’ in the clinical setting [59]. Enablers to clinician use may include integration with clinical practice guidelines [69]; automatic ‘flagging’ of clinically important scores [70]; incorporating the service-user perspective into development [61]; and providing longitudinal interpretation of what signifies a clinically important difference in PROMs data [35, 65]. At a patient level, factors may include length and complexity of the scale [34, 42, 70], availability of translated and culturally meaningful versions [34, 53, 70], ensuring that the PROM addresses issues relevant to patients and cancer type, stage, and phase of the cancer journey [34–36, 44, 53, 65], patient comfort level with technology [53, 57], including prior experience using the internet (for electronic administration of PROMs) [53]; and the degree of disability (i.e. some patients may be too ill to report symptoms, while others may not see the value of doing so

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enablers and barriers to successful implementation

discussion

review when using different modes of patient-reported data collection (e.g. web, telephone, tablet, or paper), (iv) collecting data via electronic technologies whenever possible, and (v) employing methods to minimize missing data including educating site personnel, patients and clinicians, and real-time monitoring of adherence [12, 33]. Other key areas of focus for research were also identified, specifically best practices for integrating these tools in clinical practice; and education to meet the training needs of clinicians, service managers, board members, and others on how to interpret scores and raise awareness of the limitations of their use in terms of performance measurement [12, 68, 70–72]. This is an area of research that needs considerable attention and researchers will be wise to work collaboratively with knowledge translation experts in the design of PROMs implementation studies to facilitate the practice behaviour changes that may be required to achieve an effect on health outcomes.

Funding support to complete the review was received from Cancer Care Ontario, Toronto, Ontario, Canada. A grant number does not apply.

disclosure The authors have declared no conflicts of interest.

references 1. Globocan, International Associate of Research in Cancer, Fact Sheets, 2012. http:// globocan.iarc.fr/Pages/fact_sheets_cancer.aspx (15 January 2012, date last accessed). 2. Henry DH, Viswanathan HN, Elkin EP et al. Symptoms and treatment burden associated with cancer treatment: results from a cross-sectional national survey in the U.S. Support Cancer Care 2008; 16: 791–801. 3. Kangas M, Henry JL, Bryant RA. The course of psychological disorders in the 1st year after cancer diagnosis. J Consult Clin Psychol 2005; 73: 763–768. 4. Fossa SD, Vassilopoulou-Sellin R, Dahl AA. Long term physical sequelae after adult-onset cancer. J Cancer Surviv 2008; 2(1): 3–11. 5. Stein KD, Syrjala KL, Andrykowski MA. Physical and psychological long-term and late effects of cancer. Cancer 2008; 112(11 Suppl): 2577–2592. 6. Carlson LE, Angen M, Cullum J et al. High levels of untreated distress and fatigue in cancer patients. Br J Cancer 2004; 90(12): 2297–2304. 7. Sanson-Fisher R, Girgis A, Boyes A et al. The unmet supportive care needs of patients with cancer. Supportive Care Review Group. Cancer 2000; 88(1): 226–237. 8. Laugsand EA, Sprangers MA, Bjordal K et al. Health care providers underestimate symptom intensities of cancer patients: a multicenter European study. Health Qual Life Outcomes 2010; 8: 104. 9. Cancer Care for the Whole Person: Meeting Psychosocial Health Needs. Washington, DC: Institute of Medicine, National Academies Press 2007. 10. McGrail K, Bryan S, Davis J. Let’s all go to the PROM: the case for routine-patient reported outcome measurement in Canadian health care. Healthc Pap 2011; 11 (4): 8–18. 11. Devlin NJ, Appleby J, Buxton M et al. Getting the most out of PROMs: putting health outcome at the heart of the NHS decision-making, London: Health Economics, 2010. 12. Snyder CF, Aaronson NK. Use of patient-reported outcomes in clinical practice. Lancet 2009; 374(9687): 369–370.

 | Howell et al.

13. Mitchell AJ. Pooled results from 38 analyses of the accuracy of distress thermometer and other ultra-short methods of detecting cancer-related mood disorders. J Clin Oncol 2007; 25: 4670–4681. 14. Fashoyin-Aje LA, Martinez KA, Dy SM. New patient-centered care standards from the commission on cancer: opportunities and challenges. J Support Oncol 2012; 10(3): 107–111. 15. Health Outcomes of Care: An Idea Whose Time Has Come. Canadian Institute for Health Information, 2012; 1–52. https://secure.cihi.ca/free_products/HealthOutcomes 2012_EN.pdf (5 September 2013, date last accessed). 16. Darzi A. Our NHS Our Future: High Quality Care for All. NHS Next Stage Review. Department of Health, Publication and Policy Guidance, National Health Service, UK, 2008. 17. FDA U.S. Food and Drug Administration (FDA). Patient-reported outcome measures: use in medical product development to support labeling claims, 2006. www.fda.gov/cber/gdlns/problbl.html (August 2009, date last accessed). 18. Lipscomb J, Gotay CC, Snyder C. Patient-reported outcomes in cancer: a review of recent research and policy initiatives. CA Cancer J Clin 2007; 57: 278–300. 19. Howell D, Fitch M, Bakker D et al. Core domains for a person-focused outcome measurement system in cancer (PROMS-Cancer Core) for routine care: a scoping review and Canadian Delphi Consensus. Value Health 2013; 16(1): 76–87. 20. Abernethy AP, Zafar SY, Uronis H et al. Validation of the Patient Care Monitor (Version 2.0): a review of system assessment instrument for cancer patients. J Pain Symptom Manage 2010; 40: 545–558. 21. Basch E, Artz D, Iasonos A et al. Evaluation of an online platform for cancer patient self-reporting of chemotherapy toxicities. J Am Med Inform Assoc 2007; 14: 264–268. 22. Snyder CF, Jensen R, Courtin SO et al. PatientViewpoint: a website for patientreported outcomes assessment. Qual Life Res 2009; 18: 793–800. 23. Gilbert JE, Howell D, King S et al. Quality improvement in cancer symptom assessment and control: the Provincial Palliative Care Integration Project (PPCIP). J Pain Symptom Manage 2012; 43(4): 663–678. 24. Klag MJ, MacKenzie EJ, Carswell CI, Bridges JFP. Foreword: the role of the patient in promoting patient-centered outcomes research. Patient 2008; 1(1): 1–3. 25. Osaba D. Translating the science of patient-reported outcomes assessment into clinical practice. JNCI Monogr 2007; 37: 5–11. 26. Howell D, Liu G. Can routine collection of patient reported outcome data actually improve person-centered health? Healthcare Papers 2012; 11(4): 42–47. 27. Marshall S, Haywood K, Fitzpatrick R. Impact of patient-reported outcome measures on routine practice: a structured review. J Eval Clin Pract 2006; 12(5): 559–568. 28. Valderas JM, Kotzeva A, Espallargues M et al. The impact of measuring patientreported outcomes in clinical practice: a systematic review of the literature. Qual Life Res 2008; 17(2): 179–193. 29. Antunes B, Harding R, Higginson IJ. Implementing patient-reported outcome measures in palliative care clinical practice: a systematic review of facilitators and barriers. Palliat Med 2014; 28(2): 158–175. 30. Mays N, Roberts E, Popay J. Synthesizing research evidence. In Fulup N, Allend P, Clarke A, Black N (eds), Studying the Organisation and Delivery of Health Services: Research Methods. London: Routledge 2001; 188–220. 31. Petticrew M, Roberts H. Systematic reviews in the social sciences. Oxford: Wiley Blackwell 2006. 32. Cella D, Yount S, Rothrock N et al. The Patient Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap Cooperative group during its first two years. Med Care 2007; 45(5): S3–11. 33. Duncan EA, Murray J. The barriers and facilitators to routine outcome measurement by allied health professionals in practice: a systematic review. BMC Health Serv Res 2012; 12(96): 47–55. 34. Alsaleh K. Routine administration of standardized questionnaires that assess aspects of patients’ quality of life in medical oncology clinics: a systematic review. [Review]. J Egypt Natl Canc Inst 2013; 25(2): 63–70. 35. Chen J, Ou L, Hollis SJ. A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. [Review]. BMC Health Serv Res 2013; 13: 211. 36. Luckett T, Butow PN, King MT. Improving patient outcomes through the routine use of patient-reported data in cancer clinics: future directions. Psychooncology 2009; 18(11): 1129–1138.

Downloaded from http://annonc.oxfordjournals.org/ by guest on October 28, 2015

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Annals of Oncology

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58. Kallen MA, Yang D, Haas N. A technical solution to improving palliative and hospice care. Support Care Cancer 2012; 20(1): 167–174. 59. Kanatas AN, Mehanna HM, Lowe D, Rogers SN. A second national survey of health-related quality of life questionnaires in head and neck oncology. Ann R Coll Surg Engl 2009; 91(5): 420–425. 60. Lynch J, Goodhart F, Saunders Y, O’Connor SJ. Screening for psychological distress in patients with lung cancer: results of a clinical audit evaluating the use of the patient distress thermometer. Support Care Cancer 2010; 19(2): 193–202. 61. Bausewein C, Simon ST, Benalia H et al. Implementing patient reported outcome measures (PROMs) in palliative care–users’ cry for help. Health Qual Life Outcomes 2011; 9: 27. 62. Chapman E, Whale J, Landy A et al. Clinical evaluation of the Mood and Symptom Questionnaire (MSQ) in a day therapy unit in a palliative support centre in the United Kingdom. Palliat Support Care 2008; 6(1): 51–59. 63. Engelen V, van Zwieten M, Koopman H et al. The influence of patient reported outcomes on the discussion of psychosocial issues in children with cancer. Pediatr Blood Cancer 2012; 59(1): 161–166. 64. Santana MJ, Feeny D, Weinkauff J et al. The use of patient-reported outcomes becomes standard practice in the routine clinical care of lung-heart transplant patients. Patient Relat Outcome Meas 2010; I: 93–105. 65. Chen J. The impact of routine collection of Patient Reported Outcome Measures on patients, providers and health organizations in an oncologic setting: a rapid review. Sax Institute, 2011; 1–76. https://www.saxinstitute.org.au/wp-content/ uploads/06_PROMS-Report.pdf (20 June 2014, date last accessed). 66. Guyatt G, Oxman AD, Akl EA et al. GRADE guidelines: introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol 2011; 64: 383–394. 67. Hughes R, Aspinal F, Addington-Hall JM et al. It just didn’t work: the realities of quality assessment in the English health care context. Int J Nurs Stud 2004; 41 (7): 705–712. 68. Daveson BA, Simon ST, Benalia H et al. Are we heading in the same direction? European and African doctors’ and nurses’ views and experiences regarding outcome measurement in palliative care. Palliat Med 2012; 26(3): 242–249. 69. DuBenske LL, Gustafson DH, Shaw BR, Cleary JF. Web-based cancer communication and decision making systems: connecting patients, caregivers, and clinicians for improved health outcomes. Med Decis Making 2010; 30(6): 732–744. 70. Basch E, Abernethy AP. Supporting clinical practice decisions with real-time patient-reported outcomes. J Clin Oncol 2011; 29(8): 954–956. 71. Jensen RE, Snyder C, Abernethy AP et al. Review of electronic patient-reported outcomes systems used in cancer clinical care. J Oncol Pract 2014; 10(4): e215–e222. 72. Kotronoulas G, Kearney N, Maguire R et al. What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. J Clin Oncol 2014; 32(14): 1480–1501. 73. Greenhalgh J, Long AF, Flynn R. The use of patient reported outcome measures in routine clinical care: lack of impact or lack of theory? Soc Sci Med 2005; 60: 833–843. 74. Howell D, Hack TF, Green E, Fitch M. Cancer distress screening data: translating knowledge into clinical action for a quality response. Palliat Support Care 2014; 12 (1): 39–51. 75. Cella D, Hahn EA, Dineen K. Meaningful change in cancer-specific quality of life scores: differences between improvement and worsening. Qual Life Res 2002; 11: 207–221. 76. Epstein RM, Street RL, Jr. Patient-Centered Communication in Cancer Care: Promoting Healing and Reducing Suffering. National Cancer Institute, NIH Publication No. 07–6225. Bethesda, MD, 2007. 77. Basch E, Snyder C, McNiff K et al. Patient-reported outcome performance measures in oncology. J Oncol Pract 2014; 10: 209–211.

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37. Perry S, Kowalski TL, Chang CH. Quality of life assessment in women with breast cancer: benefits, acceptability and utilization. [Review]. Health Qual Life Outcomes 2007; 5: 24. 38. Abernethy AP, Ahmad A, Zafar SY et al. Electronic patient-reported data capture as a foundation of rapid learning cancer care. Med Care 2010; 48(6 Suppl): S32–S38. 39. Boyes A, Newell S, Girgis A et al. Does routine assessment and real-time feedback improve cancer patients’ psychosocial well-being? Eur J Cancer Care 2006; 15(2): 163–171. 40. Hilarius DL, Kloeg PH, Gundy CM, Aaronson NK. Use of health-related quality-oflife assessments in daily clinical oncology nursing practice: a community hospitalbased intervention study. Cancer 2008; 113(3): 628–637. 41. Judson T, Bennett AV, Rogak L et al. Feasibility of long-term patient self-reporting of toxicities from home via the Internet during routine chemotherapy. J Clin Oncol 2013; 31(20): 2580–2585. 42. Kim NY, Richardson L, He W, Jones G. Patient preference to use a questionnaire varies according to attributes. Patient Educ Couns 2011; 84(2): 191–199. 43. Seow H, Sussman J, Martelli-Reid L et al. Do high symptom scores trigger clinical actions? An audit after implementing electronic symptom screening. J Oncol Pract 2012; 8(6): e142–e148. 44. Snyder CF, Jensen RE, Geller G et al. Relevant content for a patient-reported outcomes questionnaire for use in oncology clinical practice: putting doctors and patients on the same page. Qual Life Res 2010; 19(7): 1045–1055. 45. Snyder C, Blackford A, Wolff A et al. Feasibility and value of Patient-Viewpoint: a web system for patient-reported outcomes assessment in clinical practice. Psychooncology 2013; 22(4): 895–901. 46. Takeuchi EE, Keding A, Awad N et al. Impact of patient-reported outcomes in oncology: a longitudinal analysis of patient-physician communication. J Clin Oncol 2011; 29(21): 2910–2917. 47. Velikova G, Booth L, Smith AB et al. Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial. J Clin Oncol 2004; 22(4): 714–724. 48. Rosenbloom SK, Victorson DE, Hahn EA et al. Assessment is not enough: a randomized controlled trial of the effects of HRQL assessment on quality of life and satisfaction in oncology clinical practice. Psychooncology 2007; 16(12): 1069–1079. 49. Bruner DW, Bryan CJ, Aaronson N et al. Issues and challenges with integrating patient-reported outcomes in clinical trials supported by the National Cancer Institute-sponsored clinical trials networks. J Clin Oncol 2007; 25(32): 5051–5057. 50. Erharter A, Giesinger J, Kemmler G et al. Implementation of computer-based quality-of-life monitoring in brain tumor outpatients in routine clinical practice. J Pain Symptom Manage 2010; 39(2): 219–229. 51. Nicklasson M, Elfstrom ML, Olofson J, Bergman B. The impact of individual quality of life assessment on psychosocial attention in patients with chest malignancies: a randomized study. Support Care Cancer 2013; 21(1): 87–95. 52. Wright P, Smith A, Roberts K et al. Screening for social difficulties in cancer patients: clinical utility of the Social Difficulties Inventory. Br J Cancer 2007; 97(8): 1063–1070. 53. Basch E, Artz D, Dulko D et al. Patient online self-reporting of toxicity symptoms during chemotherapy. J Clin Oncol 2005; 23(15): 3552–3561. 54. Berry DL, Blumenstein BA, Halpenny B et al. Enhancing patient-provider communication with the electronic self-report assessment for cancer: a randomized trial. J Clin Oncol 2011; 29(8): 1029–1035. 55. Engelen V, Detmar S, Koopman H et al. Reporting health-related quality of life scores to physicians during routine follow-up visits of pediatric oncology patients: is it effective? Pediatr Blood Cancer 2012; 58(5): 766–774. 56. Underhill ML, Boucher J, Roper K, Berry DL. Symptom management excellence initiative: promoting evidence-based oncology nursing practice. Clin J Oncol Nurs 2012; 16(3): 247–250. 57. Cox A, Illsley M, Knibb W et al. The acceptability of e-technology to monitor and assess patient symptoms following palliative radiotherapy for lung cancer. Palliat Med 2011; 25(7): 675–681.

review

Patient-reported outcomes in routine cancer clinical practice: a scoping review of use, impact on health outcomes, and implementation factors.

This review focused on the identification of patient-reported outcome measures (PROMs) used in routine cancer clinical practice, the impact on patient...
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