A systematic review of the impact of routine collection of .../media/Non-Clinical/Files-PDFs... · Methods Existing systematic reviews and rationale for the current review In order

Chen et al. BMC Health Services Research 2013, 13:211http://www.biomedcentral.com/1472-6963/13/211

RESEARCH ARTICLE Open Access

A systematic review of the impact of routinecollection of patient reported outcome measureson patients, providers and health organisations inan oncologic settingJack Chen1,2*, Lixin Ou1,2 and Stephanie J Hollis1,2

Abstract

Background: Despite growing interest and urges by leading experts for the routine collection of patient reportedoutcome (PRO) measures in all general care patients, and in particular cancer patients, there has not been anupdated comprehensive review of the evidence regarding the impact of adopting such a strategy on patients,service providers and organisations in an oncologic setting.

Methods: Based on a critical analysis of the three most recent systematic reviews, the current systematic reviewdeveloped a six-method strategy in searching and reviewing the most relevant quantitative studies betweenJanuary 2000 and October 2011 using a set of pre-determined inclusion criteria and theory-based outcomeindicators. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was usedto rate the quality and importance of the identified publications, and the synthesis of the evidence was conducted.

Results: The 27 identified studies showed strong evidence that the well-implemented PROs improved patient-provider communication and patient satisfaction. There was also growing evidence that it improved the monitoringof treatment response and the detection of unrecognised problems. However, there was a weak or non-existentevidence-base regarding the impact on changes to patient management and improved health outcomes, changesto patient health behaviour, the effectiveness of quality improvement of organisations, and on transparency,accountability, public reporting activities, and performance of the health care system.

Conclusions: Despite the existence of significant gaps in the evidence-base, there is growing evidence in supportof routine PRO collection in enabling better and patient-centred care in cancer settings.

Keywords: Cancer, Quality of Life, Patient Reported Outcomes, Health Services Research

BackgroundPatient reported outcome (PRO) measures includehealth status assessments and measures for health-related quality-of-life (HRQOL), symptom reporting,satisfaction with care, treatment satisfaction, economicimpact, and specific dimensions of patient experiencesuch as depression and anxiety [1]. The USA Food andDrug Agency (FDA) adopts a much broader definition[2] as “A PRO is any report coming directly from patients

* Correspondence: [email protected] Simpson Centre for Health Services Research, South Western SydneyClinical School, University of New South Wales, Liverpool 2170NSW, Australia2Australian Institute of Health Innovation, Level 1, AGSM Building, Universityof New South Wales, Randwick 2052, Australia

© 2013 Chen et al.; licensee BioMed Central LCommons Attribution License (http://creativecreproduction in any medium, provided the or

about a health condition and its treatment”, meaningthat PROs capture patients’ perspectives about how ill-ness or new therapies impact on their general well-being. There is a growing interest from clinicians, researchers,industry and policy-makers in routinely collecting PROsto facilitate timely, patient-centred and evidence-basedcare. For example, the National Health Service (NHS) ofthe UK has been implementing a world-leading initiativefor the routine collection of PROs that firstly includeda few selected elective surgeries (e.g. unilateralhip replacements, unilateral knee replacements, groinhernia surgery or varicose vein surgery) [3] but are soonexpanding to many other conditions such as mastectomy

td. This is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andiginal work is properly cited.

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Chen et al. BMC Health Services Research 2013, 13:211 Page 2 of 24http://www.biomedcentral.com/1472-6963/13/211

and breast cancer, among others. In the USA, thePatient-Reported Outcomes Measurement InformationSystem (PROMIS), a National Institutes of Healthfunded initiative starting in 2004, is providing a publiclyavailable web-based resource that can be used to meas-ure key health symptoms and HRQOL [4]. The trad-itional paper-based PROs instruments are limited by itslack of flexibility, language and literacy requirement,[5,6] possible inappropriateness towards minoritygroups, [7,8] lack of timeliness (in generating instantan-eous clinical meaningful interpretations) [9] and inabilityto adopt state-of-the-art measurement science such asItem Response Theory (IRT) and Computer AdaptedTest (CAT) technique [10]. To overcome the difficultyof integrating the administration and analysis of PRO in-struments into clinical practice, researchers are develop-ing and validating alternatives to traditional paper-based instruments such as office-based touch-screencomputers, [11-13] telephone-based interactive voice-response (IVR) systems, [14-16] hand-held computers,[17,18] mobile phones, [19-21] and more recently, theInternet [22-24]. Some rationales [25-28] put forwardfor measuring PROs in a cancer setting include, but notlimited to: 1) better communication and shared decisionmaking by patients and providers; 2) assessing the healthstatus of patients entering therapy and identifying treat-able problems; 3) determining the degree and sourcesof the patient’s decreased ability to function; 4)distinguishing between types of problems, includingphysical, emotional, and social; 5) detecting adverse ef-fects of therapy; 6) monitoring the effects of disease pro-gression and response to therapy; 7) informing decisionsabout changing treatment plans, and 8) predicting thecourse of disease and outcomes of care.However, despite growing interest and urges by the lead-

ing experts for applying routinely collected PROs for allcancer patients, there has not been an updated compre-hensive review of the evidence regarding the impact ofadopting such a strategy on patients, services providersand organisations. The most recent review focused onlyon clinical trial design [26] studies of cancer patients, andonly assessed a limited number of outcomes. The currentproject aims to provide the much needed comprehensivereview update, including all relevant quantitative studiesinvestigating the effectiveness of routine PRO collection incancer patients. The review research questions were:

1. What are the impacts of composite measures ofPROs collected on cancer patients during treatmentwith regards to:

a) Provider behaviour for improving care delivered;b) Organisational changes within health care settings

for improving processes and models of care(e.g. targeting and tailoring care);

c) Improving clinical outcomes for patients; andd) Improving patient experience of care (e.g. self-care).2. What mechanisms are involved in the link between

PROs and the impacts identified in 1(a)?3. What factors moderate the extent of the impacts

identified in 1(a)?

MethodsExisting systematic reviews and rationale for the currentreviewIn order to develop an efficient search and review strat-egy, over 200 existing reviews on the same or similartopics were firstly systematically examined (identified ina broad search covering PROs and quality of life mea-sures between January 2000 and October 2011). Threereviews [26-28] were identified as the baseline reviewsfor this project and their review strategies were carefullyexamined in aspects such as the aim and scope, timespan, search strategy and search terms used, articles in-cluded in each review, and conclusions drawn. A tablesummarising the three systematic reviews is presented inTable 1.

Review search strategyAnalysing the results of above three systematic reviewsdemonstrates the importance of search strategies in de-termining what literature will be included in the study,which in turn, may influence what conclusions will bederived. Valderas et al.’s (2008) [27] review excludedthree out of the five clinical trials on cancer patients thatwere included in Marshall et al.’s (2006) [28] review.Lucket et al.’s (2009) review [26] excluded one article(Taenzer et al. (2000), [33] a before-after study) fromMarshall et al.’s review [27]. A mixed methodologysearch was developed in order to maximise the identifi-cation of recent literature in a short period of time. Thesearch was conducted in six different ways as follows:

1. A text-based search strategy was developed based onprevious reviews. To elicit previous reviews, a searchwas conducted for the text terms ‘patient reportedoutcome*’, ‘self-reported’, ‘self-assessed’ anywhere intitle, abstract and key words, combined with ‘qualityof life’, ‘symptom’, ‘functional status’, ‘health status’,‘patient satisfaction’, ‘unmet need*’ anywhere in title,abstract and key words. For original articles, asearch was conducted using the same strategy asabove but restricted to those with ‘neoplasm’ or‘cancer’ in the key words. The search results wererestricted to between January 2000 and October2011 (full search strategy is listed in Additional file 1:Appendix 1).

2. All reviews were evaluated (over 200 in total onvarious topics but not limited to only cancer

Table 1 A comparison of three baseline reviews

First author,year

Aim and review scope Time span and the search strategy Search Terms Articles included inthe review

Major conclusions

Luckett et al.2009 [26]

To identify future strategies for (1)interventions to impact patientoutcomes; and (2) trials to identifytreatment effects.

MEDLINE and PsycINFO weresystematically searched to identifyreports of relevant randomisedcontrolled trials. The time span wasbetween 2006 and 1 August 2008.Four cancer trials were cited in aprevious review (Valderas et al. 2008)[27].

1. Examined the citations of the fourtrials 2. Adopted the strategy used byValderas et al. [27] and Espallargueset al. [29] which involved searching forthe terms ‘health status’, ‘functionalstatus’ or ‘quality of life’ and ‘clinicalpractice’, ‘clinical setting’, ‘practicesetting’, ‘medical practice’ or ‘medicalconsultation’ anywhere in the title,abstract or keywords. Results werelimited by publication date (2006–2008) and the MeSH or keywordneoplasm.

6 RCTs Future interventions should motivateand equip health professionals to usePROs data in managing patients,training patients in self-efficacy, usingmore specific PROs in clinics,improving the interpretability offeedback for both medical staff andpatients, and monitoring the use ofPROs to intervene when problemsarise. Future trials should use a clusterrandomised design to control forcontamination and enable systems-based interventions.

Valderas et al.2008 [27]

To summarize the best evidenceregarding the impact of providingpatient reported outcomes (PRO)information to health careprofessionals in daily clinical practice.

Systematic review of randomised clinicaltrials (Medline, Cochrane Library);reference lists of previous systematicreviews; and requests to authors andexperts in the field. Time span: Articlespublished between 1978 and 2007.

No exact search terms provided butindicated available from the authorupon request.

34 articlescorresponding to 28original studies; only 2(not 4) as mentioned inthe above review, are inan oncologic setting.

Methodological concerns limit thestrength of inference regarding theimpact of providing PROsinformation to clinicians. Resultssuggest great heterogeneity ofimpact; contexts and interventionsthat will yield important benefitsremain to be clearly defined.

Marshall et al.2006 [28]

To synthesize the evidence for usingpublically reported performance datato improve quality. Only articles thatprovided empirical evidence on theimpact of public reporting onoutcomes (effectiveness, patientsafety, and patient-centeredness) andunintended consequences, as well asselection and quality improvementactivity were included.

Webspirs Medline was searched forthe years from January 1976 toNovember 2004. Reference lists ofincluded studies and appropriatereviews (Greenhalgh & Meadows 1999[30]; Espallargues et al. 2000 [29];Gilbody et al. 2003 [31]) were alsosearched for relevant articles. Finally,PubMed’s ‘related articles’ feature wasused with several background andincluded articles (Drury et al. 2000 [32];Velikova et al. 2004 [13]) to identifypublications with a high proportion ofsimilar text in the title and abstract.

Terms used in relation to patient-reported outcome measures (forexample, ‘self report* near2measure*’) joined with an ‘and’command to terms related to routinepractice outcomes (for example,‘improve* near detect*’) or patientinvolvement in the health careprocess (such as ‘patient* nearprovider* near interaction*’).

40 articles included inthe review including 5publications from anoncologic setting.

The pattern of results suggests ageneral lack of clarity in the field,especially regarding appropriate goalsfor PROs and the mechanisms bywhich they might achieve them. Tofully evaluate their role in routinepractice, studies need to use PROs thatcapture issues of importance topatients and to measure impactsrelating to the patient–providerrelationship and patient contributionsto their well-being. Until studiesevaluate PROs as a means to facilitatepatient-centred care, their full potentialin clinical practice will remain unknown.

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patients) with three baseline reviews used as thestarting point for our top-down and bottom-up searchstrategy. We chose the three baseline reviews becausethat: 1) they are all systematic reviews that could behelpful in forming the structure or strategy of thecurrent review (but not necessarily restricted to cancerpatients); and 2) they were published after 2005.

3. All articles were examined if they cited the 7 keyrandomised controlled trials [33-39] listed in theabove reviews (bottom-up approach). Referenceswere also sought from the most recently publishedtrials, editorials, and commentaries (a top-downapproach). The powerful citation tracking feature ofScopus™ made this strategy feasible.

4. Simplified text terms (i.e. patient reported outcome,PRO, PROM, Quality of life, QOL) were used toconduct a web search for identifying grey literature.

5. Leading researchers and experts in the field (elicitedthrough the advice of Cancer Institute NSW (CINSW),editorials, review articles and most cited articles) werepurposefully searched in order to analyse the referencesand citations in their publications.

6. Some key cancer centres’ websites were alsosearched in order to get more detailed information.

The search was limited to the Scopus™ database as it isthe largest abstract and citation database of peer-reviewedliterature and quality web sources including 100% cover-age of Medline titles and EBASE. It also tracks, analysesand visualises publication results, which is well suited toour top-down and bottom-up search strategy.

Aim, study selection and endpoints of the reviewIn this review, the aim was to synthesize the evidence inrelation to the impact of routinely collected PROs on pa-tients, providers, and health organisations. The frame-works proposed by Greenhalgh and colleagues [25] and byAbernethy and colleagues [40] were adopted to guide ourevaluation of the existing literature. Greenhalgh et al. [25]proposed a framework (Figure 1) that depicts mechanismsbetween the routine collection of PROs and changes inpatient outcomes. The authors suggest that the multilayermediators (i.e. changes to doctor-patient communication,monitoring treatment responses, detecting unrecognisedproblems, changes to patient health behaviour, changes toclinicians’ management plans, and improved patient satis-faction) have complex relationships among them. Thestudies that revealed these complex relationships may as-sist in understanding whether and how the underlyingmechanisms of routinely collected PROs work to improvethe intended outcomes.Recently, Abernethy and colleagues [40] have argued

that the routine collection of PROs has the capacity toimpact not only at the patient-level, but by addressing

the logistics of data linkage, and could ensure that thesystem will grow to accommodate other clinical- andhealth system-level issues; for example, evaluating com-parative effectiveness of treatments, monitoring qualityof care, and translating basic science findings into clin-ical practice (Figure 2). The integration of data systemswill fuel rapid learning cancer care at the national andsocietal levels (see Figure 2a and b), making many typesof research and system learning possible across institu-tions and health sectors. The benefits and implicationsof such a rapid learning health care system may include,but is not limited to, strong and effective quality im-provement (QI), increased transparency, accountability,public reporting, better health system performance(monitoring, planning, financing, evaluating, responding)and better quality of care.Combining both frameworks, a list of outcome indica-

tors was developed (Table 2) against which each eligiblestudy was assessed. To include not only the doctors’ ex-perience with patients after collecting PROs, but also theexperience of other health services providers (i.e. nurses,allied health workers), the term ‘Patient-provider commu-nication’ was used instead of ‘doctor patient communica-tion’ as proposed by Greenhalgh et al. [25]. In order toanswer review questions 2 & 3 for the studies included, allpossible explicit mediation effects were reviewed throughexamining if a path-analysis or a mediation-analysis bymultiple, staged regression approach was presented in thepaper. To examine potential moderating effect, each studywas examined to determine if it explicitly tested the inter-action effect/moderating effect, or inexplicitly conductedsubgroup analysis. Significant possible mediating or mod-erating effect results were indicated as part of review end-points in Table 3. Inferences made and the discussionwere based on these results.

Inclusion and exclusion criteriaThe inclusion criteria were: 1) substantial content in pre-senting empirical evidence on the impact of routinely col-lected PROs on at least one of the outcomes listed inTable 2; 2) adult cancer patients; 3) conducted in an onco-logic setting including inpatient, outpatient and outreachservices; and 4) studies using a composite PRO. We defineda composite PRO as those PROs are often based on a well-developed instrument and with an aim for measuring asubstantial aspect of patient conditions (or treatment) withat least 4 items. To reflect the demanding and complex na-ture of evaluating the impact of routine collected PROs, eli-gible studies included a variety of designs including, but notlimited to, randomised controlled trials (RCTs), controlledbefore-after trials (CBA) and interrupted time series (ITS).ITS designs have a longitudinal character, with repeatedmeasurements and at least three data points before andafter the intervention point. Surveys and clinical audits

BEvidence: + CHANGES TO DOCTOR PATIENT COMMUNICATION

Clinicians talk to patients about their feelings/health status Develop a shared view of treatment goals/health status/reason for the visit

GEvidence: - IMPROVED PATIENT SATISFACTION

AEvidence: + IMPROVED HEALTH OUTCOMES

CEvidence: +/- MONITOR TREATMENT RESPONSE

EEvidence: - CHANGES TO PATIENT HEALTH BEHAVIOUR

Visit to the clinician Adherence to treatment

DEvidence: +/- DETECT UNRECOGNISED PROBLEMS

FEvidence: - CHANGES TO CLINICIAN’S MANAGEMENT OF PATIENT

Changes to/initiation of treatment Referrals to other agencies Tests to investigate problem further Advice on problem management

APROVISION OF INFORMATION FROM HEALTH STATUS MEASURES TO CLINICIANS

Alone or supplemented with management guidelines With or without training in interpretation of scores Fed back once or several times Graphical displays of scores or written summaries, with or without population norms, with or without previous scores

Figure 1 A hypothetical framework to understand the impact of routinely collected PROs on patient health outcomes (adopted fromGreenhalgh et al. (2005) [25] with permission).


were also included if the studies provided quantitative re-sults relevant to the listed outcomes.Studies were excluded if they were non-English lan-

guage articles, opinion and theoretical articles, historicaldescriptions, review articles, feasibility studies of somePROs collection devices, studies investigating child

Figure 2 (a) A data linkage framework (b): A learning health care systwith permission.

cancer patients or qualitative studies with no substantialquantitative results on the review endpoints.

Data extraction and quality assessmentElectronic search results were downloaded into EndNotebibliographic software. Two reviewers independently

em. Note: Figures 2: adopted from Aberthnethy et al. (2010) [40]

Table 2 Outcome indicators assessed for each eligiblestudy included in the reviewNumber Outcomes

1 Patient-provider communication

2 Monitor treatment response

3 Detect unrecognised problems

4 Changes to patient health behaviour

5 Changes to patient management

6 Improved patient satisfaction

7 Improved health outcomes

8 Strong & effective quality improvement

9 Increased transparency, accountability, public reporting

10 Better system performance (monitoring, planning, financing;evaluating, responding)

11 Mediating variables on the effect (both at individual andorganisation level)

12 Possible subgroup effects

Note: Both 11 & 12 are combined in the summarising tables as few studieshave explored such issues.


(JC, LO) screened all titles and abstracts of citationsidentified by the electronic search, applied the selectioncriteria to potentially relevant papers, and extracted datafrom included studies using a standardised form. Anydisagreements concerning studies to be included wereresolved by consensus.All studies were classified into two domains. Domain 1

correlated sample characteristics with population widecharacteristics, and Domain 2 focused on study design.The data extraction form was adapted from other reviewstudies using the outcome measures discussed above(see Table 4). For each eligible study, a list was made in-cluding the leading author, country and jurisdiction, de-sign, sample, outcome measures, the PROs used, timesof feedback and intervention, members of medical teamsgiven feedback, management plans offered to teams, andtraining (see Table 5). All qualifying studies were listedchronologically with the outcome indicators (seeTable 3).In Domain 1, the routinely collected PROs in particu-

lar participants or samples was classified as rated on a 4-point scale representing how closely the participants orsamples overlapped with the characteristics and needs ofthe intended study populations(1 star=very weakly re-lated to 4 stars =very strong related). For example, for astudy conducted in the US on a sample of lung cancerpatients, the degree of overlap of the study sample withthe characteristics of lung cancer patients in the US over-all was assessed by considering the study setting, samplesize and sampling frame, response rate, loss-to-follow-up,and characteristics of the study sample. In Domain 2,study design was classified and rated on 4 categories with1 star indicating the weakest design and 4 stars indicating

the strongest design. Four stars indicated a randomisedtrial or experimental study; 3 stars indicated a controlledtrial, pre–post trial with control (controlled before–aftertrial), time series, or observational cohort with multivari-able adjustment; 2 stars indicated a pre–post trial withoutcontrol, observational cohort study without multivariableadjustment, cross-sectional study without multivariableadjustment, analysis of time trends without control, orwell-designed qualitative study; and 1 star indicated a caseseries, other qualitative study, or survey (descriptive)study.Revised appraisal criteria were adapted from the guide-

lines on the assessment of quality improvement inter-ventions [58,59]. A global rating was also created usingthe Grading of Recommendations, Assessment, Develop-ment, and Evaluation (GRADE) system [60]. The BritishMedical Journal has recommended the GRADE systemsince 2006 for grading evidence when submitting a clin-ical guidelines article. It has multiple advantages and isuseful for systematic reviews and health technology as-sessments, as well as for evaluating research on clinicalguidelines. The global rating created in the current studywas based on the integration of the Domain 1 and Do-main 2 ratings, as well as the intervention fidelity (thedegree of success of the interventional strategy, the pa-tients’ and providers’ adherence to the intervention strat-egy), dose–response gradient, precision and validity ofoutcomes (potential confounding factors and biases),and uncertainty of the direction of results. The globalrating was divided into three categories; indication thatthe study should carry great (3 checks), moderate (2checks), or little (1 check) weight when considering thestrength of evidence (see Table 4). Any experimental re-search that is reported in the manuscript was performedwith the approval of an appropriate ethics committee.No attempt was made to quantitatively synthesize the re-

sults as the data were too heterogeneous to support pooling.

ResultsThe multi-method search strategy yielded 27 publica-tions that were eligible to be included in the review – asignificant increase compared with most of the recentreviews. The detailed flowchart of the search strategiesand its relative results was presented (Figure 3). The re-sults and conclusions drawn were based on the 27 stud-ies included in the analyses despite the large number offull-text articles extracted.Of the 27 publications, 16 were identified as randomised

controlled trials, 2 as before-after studies and 9 observa-tional studies with 11 studies published before 2009. Thecharacteristics and quality of the studies are presented inTable 5 with their impact on outcome indicators presentedin Table 3. As Trowbridge et al. (1997) was the onlyarticle in the 1990s included in two of the previous

Table 3 The characteristics of design and study quality

Reference Country /Jurisdiction

Design Sample /Population

Outcomemeasures

PROS used Intervention /Number oftimes feedback

Members ofmedical teamgiven feedback

Managementplan offeredto team

Training tostaff

Domain1

Domain2

GlobalRating

Trowbridgeet al. (1997)[39]

USA (CentralIndianaCommunityCancer Centres,Indianapolis)

RCT:Intervention /Control

320 canceroutpatients,13 oncologistsand 23 clinics

PainManagementIndex(ref); painmedication level(0–3) minus painlevel: Patientassessment ofpain, painregiments andrelief receivedPatterns ofanalgesicprescription

Estimates ofaverage andworst pain overthe previous 7days, satisfactionwith current painregimens anddegree of reliefreceived

One Doctorsonly (12)

No No ** *** √√

Tazenzeret al. (2000)[33]

Canada (TomBaker CancerCentre , Calgary,Alberta)

Before-aftertrial: usualcare group /Interventiongroup withbefore ascontrol

53 lung cancerpatientsattending anoutpatient lungcancer clinic

EORTIC QLQ-C3011-item PatientSatisfactionQuestionnaire(PDIS) ( adaptedthrough Falvoand Smith,1983)Exit Interview(patient’sperception if QLissues had beenaddressed duringthe visit) MedicalRecord Audit onpatients’ care plan

EORTC QLQ-C30(on a PC)

Once Doctors andnurses

No Ground roundintroductionand training

* *** √√

McLachlanet al. (2001)[38]

Australia (PeterMacCallumCancer Centre,Melbourne)

RCT:Intervention /control (ratio: 2:1)

450 cancerpatientsattendingambulatoryclinics

Patient HRQoL(EORTC QLQ-C30)32-item Patientneeds (CancerNeedsQuestionnaireShort Form [CNQ]Patient distress(Beck DepressionInventory (BDI)Patient satisfaction(in 6-month)Services providedfor thoseidentified asrequired bycoordinationnurse

EORTC QLQ-C30,CNQ, BDI (througha touch-screen PC)

One Doctor andcoordinationnurse (numbersnot reporter)

Individualisedplandeveloped bycoordinationnurse inaccordancewith genericpsychosocialguidelines

No ** *** √√

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Table 3 The characteristics of design and study quality (Continued)

Detmar et al.(2002) [37]

Netherland(NetherlandsCancer Institute,Amsterdam)

RCT:(Cross-overdesign)Intervention/control

214 palliativecancer patientsin a outpatientclinic of acancer hospital

Patient-doctorcommunicationDoctor’sawareness ofpatient HRQoLPatientmanagementPatients’/doctors’satisfactionPatient HRQoL(SF-36) Patients’/doctors’evaluation ofintervention

EORTC QLQ-30 Three Doctors (n=10) No Doctors given30-minstraining andpatientmailed aleaflet

*** **** √√√

Mooneyet al. (2002)[16]

USA (Universityof Utah, SaltLake City, Utah)

A pilotProspectivestudy over amonth periodwith dailymeasures

27 patientsreceivingcancerchemotherapyat a cancercentreoutpatient clinic

Telephone-LinkedCare system forChemotherapy(TLC-ChemoAlert) Sevensymptoms(nausea andvomiting, fatigue,trouble sleeping,sore mouth, fever,feeling blue,feeling anxious)Exit interview

TLC-Chemo Alert Patients askedto report dailyduring thecycle and thealerts weresent toproviders

Doctors (n=2) Yes Patientstrained (10minutes TLCorientation)

** ** √

Velikovaet al. (2004)[36]

UK (CancerResearch UKClinical Centre– Leeds)

RCT:Intervention/control-attention/controlin a ratio of 2:1:1

286 canceroutpatientsattending alarge cancercentre of ateachinghospital

Patient HRQoL(FACT-G)Discussion ofHRQoL issues inconsultationMedical actions(decisions oncancer treatment,symptomatic/supportivetreatment,investigations andreferrals) Non-medical actions(advice on lifestyle,copying andreassurance)Physician checklistassessing theclinical usefulnessof PROM data

EORTC QOQ-C30Hospital Anxietyand DepressionScale (HADS)

Regular clinicvisit over anaverage of 6months

Doctor (n=28) No One to onetraining andmanualprovided

*** **** √√√

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Basch et al.(2005) [41]

USA (MemorialSloan-KetteringCancer Center,New York)

Prospective pilotstudy of patientonline self-reporting oftoxicitysymptoms

80 patientsdiagnosed witha gynaecologicmalignancystarting a newchemotherapyregimen

Pattern of use ofa Self-reportedonline SymptomTrack andReporting (STAR)system Patientimpression ofsuch systembased on an exitquestionnairesurvey Clinicianfeedback(through surveyand teamdebriefing)

Symptom Trackand Reporting(STAR) based onNCI CATAE system

Any clinic visitsduring 8-wkstudy period(mean=3,range 1–6) ,also possiblelog in at homeduring theperiod

Doctors andstudy team(n=unreported)

Yes Trainingprovide topatients butunreportedto staff

** ** √

Boyes et al.(2006) [35]

Australia(Centre forHealth Research& Psycho-oncology,University ofNewcastle)

Pilot controlledtrial: Intervention/control

80 canceroutpatientsattending onecancer centre

Patient symptomsPatient anxiety/depression(HADS)Patient needs(Supportive CareNeeds Survey[SCNS]Acceptability ofintervention topatient anddoctors

Symptoms,HADS SCNS

1st consultation– 100% patients:2nd: 83%; 3rd:71%; 4th: 60%

Doctors (n=4) List of patientsneedsaccompaniedbysuggestionsforappropriatereferral

None ** *** √√

Hoeskstraet al. (2006)[42]

Netherlands(AcademicMedicalCentre,University ofAmsterdam)

RCT: Interventiongroup withsymptommonitoring /control

146 palliativecancer patientsrecruitedthrough twohospitals andlocal GPs

10 symptomsfrom theSymptomMonitor Severityof the reportedsymptom(0–10 score)

Symptom MonitorExtensiveQuestionnaire

Weekly self-assessedSymptomMonitor athome;Extensivequestionnaireevery 2-month

GPs (98 times)and medicalspecialists(96 times)

No No ** *** √√

Korniblithet al. (2006)[43]

USA (Dana-Farber CancerInstitute,Boston)

RCT : TelephoneMonitoring (TM)versus TM+EducationMaterial (EM)

192 cancerpatients withadvanceddisease andreceiving activetreatment

EORTC-QLQ-30HADS

EORTC-QLQ-30ǂ Once a monthover 6 months

Ontologicalnurses

Yes Yes *** **** √√√

HADS

MOS-SS

GDS (short form)

QARSQ-PH

UMPSI

GSRE

Patient Satisfactionwith the ResearchProgram BOMCtest;

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Basch et al.(2007) [44]

USA (MemorialSloan-KetteringCancer Center,New York)

Prospective pilotstudy of apatient onlineself-reporting oftoxicitysymptoms

107 patientsdiagnosed withthoracicgynaecologicmalignancystarting a newchemotherapyregimen

Feasibility/Patternof use of a Self-reported onlineSymptom Trackand Reporting(STAR) systemPatientsatisfactionsurvey(an exitquestionnairesurvey) Nursingsurvey (throughan exit survey)

Symptom Trackand Reporting(STAR) based onNCI CATAEsystem

Any clinic visitsduring 42-wkstudy period(mean=12,range 1–40) ,also possible login at homeduring theperiod

Nurses andstudy team(n=unreported)

No Trainingprovide topatients butunreported tostaff

** ** √

Rosenbloomet al. (2007)[34]

USA (Center onOutcomes,Research andEducation,EvanstonNorthwesternHealthcare

RCT: Structuredinterview anddiscussion /assessmentcontrol /standard care

213 patientswith advancedbreast, lung orcolorectalcancer

Patient HRQoL(FunctioningLiving Index –Cancer [FLIC])Patient affect(Brief Profile ofMood States[Brief POMS])Patientsatisfaction[PSQ-III] Clinicaltreatmentchanges asreported by nurse(supportive carechanges, referrals,‘other’ clinicalchanges andchanges instandard dose ofchemotherapy asa result of PROs)

FACT-G and asingle itemasking patientswhether aparticularsymptom orproblem wasbetter than,worse than, oras expected

Clinic visits atbaseline ,and 1,2,3 and 6months

Treatingnurses (n=notreported)

No No *** **** √√√

Weaver et al.(2007) [45]

UK (OxfordRadcliffeHospitalsNHS Trust)

A pilot study ofnovel mobilephonetechnology

6 colon cancerpatients

Questionnaire onsymptomsderived from theCommonTerminologyCriteria forAdverse Events(CTCAE) gradingsystem

Questionnairederived from theCommonTerminologyCriteria forAdverse Events(CTCAE) gradingsystem

Twice dailyduring thechemotherapycircle (onemorning, oneevening)

Nurses(n= notreported)

Yes Yes ** ** √

Butt et al.(2008) [46]

USA (Centeron Outcomes,Research and

Prospectivestudy to explorethe longitudinal

99 cancerpatients withsolid tumor of

FACT-G FACT-Fatigue subscaleBrief Pain

FACT-G FACT-Fatigue subscaleBrief Pain

Baseline, 1month and 2

Doctors andnurses

? ? ** ** √

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Education(CORE), EvantonNorthwesternHealthcare)

screening andmanagement offatigue, pain, andemotionaldistress

lymphomaundergoingcancerundergoingcancertreatment

Inventory (BPI)HADS Structuredinterview withpatients on HRQLand symptommanagement

Inventory (BPI)HADS

months afterthe baseline

Given et al.(2008) [47]

USA( MichiganState University)

RCT: Nurse-AdministratedSymptomManagement(NASM) vsAutomatedTelephoneSymptomManagement(ATSM)intervention

129 breastcancer patients

Outcomesmeasured at10–16 wks: 15symptoms(0–10 scale)Responses &Non-responsesof symptomsTime toresponse

15 symptoms(0–10 scale)Severity of thesymptoms

6 contacts orself-reporting(1–4 wk, 6wk,8wk)

Nurses orATSM system

Yes Yes ** **** √√√

Hilarius et al.(2008) [48]

Netherland(HospitalPharmacy, RedCross Hospital,Beverwijk)

A sequentialcohort designwith repeatedmeasures toevaluate the useof HRQLassessments indaily clinicaloncologynursing practice

10 nurses and219 patientscancer patientswith eitheradjuvant orpalliativechemotherapyin a communityhospital

DartmouthPrimary CareCooperativeInformationFunctional HealthAssessment(COOPcharts)PatientManagementextracted frommedical recordPatientsatisfaction(an exit surveybased on PSQ,Form II) Patients’self-reportedHRQL (SF-36,FACT-BCS,FACT-C, FACT-L)Nurse and patientevaluation of theintervention (anexit survey)

EORTC QLQ-C30EORTC QLQ-BR23EORTC QLQ-CR38EORTC QLQ-LC13

Fourconsecutivevisits afterbaseline forboth pre(control arm)and post(interventionarm) with atwo-month‘wash-out’period

Patients andnurses beforeconsultations

No Yes *** *** √√

Mark et al.(2008) [49]

USA (ThomsonHealthcare,WashingtonDC)

A cross-sectionalsurvey of the ofboth patients’and healthprofessionals’experience; Abefore-after

100 cancerpatients and 92healthprofessionalson theexperience ofThe PatientAssessment,

Questionnairesurvey of 102providers Thepatientssatisfaction survey(n=100) including8-item on PCM200 patient chart

PCM Aneducationcomponent (notreported inthis study)

Each visit toclinic

Clinicians(n=unreported)

No ? ** *** √√

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patient chartreview

Care andEducation (PACE)System, includingPCM instrumentand an educationcomponent

reviews (100charts before and100 charts afterthe PACE system)

Kearney et al.(2009) [50]

UK (CancerCare ResearchCentre,University ofStirling, Stirling)

RCT: Controlgroup versusinterventiongroup (mobilephone-basedremotemonitoring ofsymptoms) overfive time points

56 patients withlung, breast orcolorectal cancerfor each group(total 112patients)

Paper version ofelectronic, Mobilephone-basedAdvancedSymptomManagementSystems (ASyMS©)based onCommon ToxicityCriteria AdverseEvents (CTCAE)grading systemand theChemotherapySymptomAssessment Scale

Mobile phone-based (ASyMS©)includingchemotherapy-related morbidityof six commonsymptoms(nausea, vomiting,fatigue, mucositis,hand-footsyndrome anddiarrhoea)

Five timesincludingbaseline andeach of fourchemotherapycycles over aperiod of 14days

Doctors only(n=unreported)

Yes Yes ** **** √√

Carlson et al.(2010) [51]

Canada (TomBaker CancerCentre,University ofCalgary,Alberta)

RCT: minimumscreening(distress) / fullscreening /Triage : fullscreening +referring toappropriateservices

585 breastcancer patients+ 549 lungcancer patients

Patient distress at3-month follow-up; Depressionand anxiety at 3-month follow-up

Minimumscreening: Distressthermometer (DT)Full screening: DT+ Psychologicalscan for cancerpart C (PSSCAN)

Baseline Screening teammember(n=unreported)

Yes Yes **** **** √√√

Dinkel et al.(2010) [52]

German(Department ofPsychotherapyandPsychosomaticMedicine,TechnischeUniversityMunchen)

Pairedcomparison : acomputerisedand a paperversion of StressIndex RadioOncology (SIRO)tool Prospectivesurvey

177 cancerpatients instudy 1, 273cancer patientsin study 2(n=142 forcomputerisedversion andn=131 forpaper versionof SIRO) 27Patients, urses/radiographsand 15 physiciansevaluated thescreeningprocedure

Agreementbetweencomputer andpaper version ofSIRO Patientsatisfaction; Timeneed for bothmodes; Perceivedutility; Perceivedimpact oncommunication;Perceived impacton patientoutcome

SIRO Any visit Doctors andnurses(n=unreported)

No No *** ** √√

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Halkett et al.(2010) [11]

Australian(WA Centre forCancer andPalliative Care,CurtinUniversity)

Pilot study ofusing computertouch-screentechnologyto assespsychologicaldistress inpatients

60 patientswith variousgynaecologicalcancers

Patientsatisfaction withboth touch-screen and paperquestionnaire;Perceived utilityof both modes bypatients andhealthprofessionals

EORTC QLQ-C30HADS TheSupportive CareNeeds Scale TheDistressThermometerFollowquestionnairesurvey onperceived utilityof both modes

Once Nurses anddoctors

Yes Yes * ** √

Ruland et al.(2011) [53]

Norway (Centrefor SharedDecisionMaking andNursingResearch,Oslo UniversityHospital, Oslo)

RCT: acomputer-assisted,interactivetailoredassessment(ITPA) withfeedback vs ITPAonly in oncologypractice

145 patientstreated forleukaemia orlymphoma

Number ofpatient symptomsand problemsaddressedChanges insymptom distressChanges inpatients’ need forsymptommanagementsupport overtime, SF-36,Center forEpidemiologicalStudiesDepression Scale(CES-D), MedicalOutcome StudySocial SupportScale (MOS – SS)

Choice ITPA(19symptoms(0–4 scale onbothersome)and a severityscaleof 0–10)

Every inpatientadmission withup to fourfollow-up visits

Doctorsand nurses(n=unreported)

No seeap riate)

Yes *** **** √√√

Velikovaet al. (2010)[54]

UK (CancerResearch UKClinical Centre– Leeds)

RCT:Intervention/control-attention/controlin a ratio of 2:1:1

286 cancerpatientscommencingtreatment atthe MedicalOncology Clinicat St JamesHospital

Medical CareQuestionnaire(MCQ): 15-itemthree subscales:Communication,Coordination,PatientpreferencesSatisfaction withcare Patients’ andphysicians’evaluation of theintervention K-index (Continuityof care:K=(number ofvisits – number ofdoctors)/(numberof visits −1).


Regular clinicvisit over anaverage of 6months


*** **** √√√

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(asprop


Bainbridgeet al.(2011) [55]

Canada(JuravinskiCancer Centre,McMasterUniversity,Hamilton,Ontario)

Survey onthe utility of

128 nurses,physicians, andallied healthprofessionals

Perceptions ofuse and utility ofthe EdmontonSymptomAssessmentSystem (ESAS)adopted byOntario’s cancercentres since2007

ESAS Every clinic visit Doctors andnurses

Yes Yes * * √

Berry et al.(2011) [56]

USA (Dana-Faber CancerInstitute,Boston)

RCT:Intervention /Control

660 cancerpatients withvarious cancerdiagnoses andstages at twoinstitutions of acomprehensivecancer centre

1.Audio-recordedcontent of allcommunicationbetweenclinicians,patients andaccompanyingfriends or familymembers at eachT2 visit (4–6 wksafter thetreatment)

Patient reportedsymptoms andquality-of-life(SQLIs) from theElectronicSelf-ReportAssessment-Cancer (ESRA-C)

Every clinic visitduring thestudy period

Doctors(n=76 principlephysicians andother) orincorporatedinto charts(n=unreported)

No Yes *** **** √√√

2.Clinic visitduration

3. Physician exitquestionnairesurvey

Cleelandet al. (2011)[20]

USA (MDAndersonCancer Center,The Universityof Texas)

RCT: e-mail alertof symptom topatients’ clinicalteam versus noe-mail alert

79 lung cancerpatientsreceivingthoracotomy

1. Four targetedsymptom: pain,distress, disturbedsleep, andshortness ofbreath,constipation (nofatigue as noeffectiveresponse) 2. MDAndersonSymptomInventory (MDASI)at follow-up clinicvisit 3. An exitquestionnairesurvey

Automatedtelephone calls(IVR system):MDASI (13common cancerrelatedsymptoms)

Twice weekly,up to 4 wksafter discharge

Nurses(n=unreported)

Yes Training topatientsprovided

** **** √√

Takeuchiet al. (2011)[57]

UK (St James’sInstitute ofOncology,Leeds)

Longitudinalstudy of data aspart of Velikovaet al. (2004,2010) RCT

286 cancerpatientscommencingtreatment atthe Medical

Audio-recordedcontent ofPatient-physiciancommunication:Longitudinal


Fourconsecutivevisits frombaseline


*** **** √√√

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Oncology Clinicat St JamesHospital

impact of PROintervention;dynamics ofcommunication;associationbetween severityof symptoms/functions andclinic discussion

*: Four stars indicate a randomised trial or experimental study; 3 stars indicate a controlled trial, pre–post trial with control (controlled before–after trial), time ser s, or observational cohort with multivariableadjustment; 2 stars indicate a pre–post trial without control, observational cohort study without multivariable adjustment, cross-sectional study without multivari le adjustment, analysis of time trends without control,or well-designed qualitative study; and 1 star indicates a case series, other qualitative study, or survey (descriptive) study.√: Three checks indicate great weight in the stratum’s body of evidence, 2 checks indicate moderate weight, and 1 check indicates little weight.ǂ: EORTC QLQ-C30: European Organisation for Research and Treatment of Cancer Quality of Life (EORTC QLQ) Core Questionnaire; SF-36: The Short Form(36) He h Survey; FACT-G: Functional Assessment of CancerTherapy-general; EORTC QLQ-BR23: EORTC QLQ Breast Cancer Scale; EORTC QLQ-CR38: EORTC QLQ Colorectal Cancer Scale; EORTC QLQ-LC; EORTC QLQ Lung Ca er Scale; NCI CATAE: National Cancer InstituteCommon Terminology Criteria for Adverse Events; FACT-BCS: Functional Assessment for Cancer Therapy-Breast Cancer Subscale; FACT-C: Functional Assessment o Cancer Therapy-Colorectal Quality of Life Instrument;FACT-L: Functional Assessment of Cancer Therapy-Lung Cancer Subscale; MOS-SS: Medical Outcomes Study Social Support Survey; GDS: Geriatric Depression Sc (short form); QARSQ-PH: Physical Health subscale ofthe Older American Resources and Services Questionnaire (OARSQ); UMPSI: Utilisation of Mental Health and Psychosocial Services Instrument; GSRE: Geriatric Sch ule of Recent Experience Instrument;?: No data or unable to classify data available.

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ieab

altncfaleed

Table 4 The components, rating criteria and symbol, and categories used in summarising the study evidence in thecurrent study

Domain 1 Domain 2 Global (GRADE)

DecisionComponents

Subject of public reporting (orstudy population) and studyparticipants (sample)

Types of study (i.e. study designs) Components from Domain 1 & 2 as well asimplementation and adherence to intervention, dose–response gradient, precision and validity of theoutcomes, uncertainty of direction of the results.

Rating criteria How well does the study samplerepresent the study population?

How strong is the study designboth in terms of its external andinternal validity?

How much weight does the current study add to theevidence-base taking into considerations of all thecomponents above?

Symbol used &categories ofrating

1*: no overlap 1*: weakest design √: little weight

2*: modest overlap 2*: moderate design √√: moderate weight

3*: large overlap 3*: strong design √√√: great weight

4*: complete overlap 4*: strongest design


reviews, it was listed in the summation tables for thepurpose of comparison.

Overview of study qualityThere has been a marked increase in the volume andquality of the studies published recently in this area. Ofthe 16 randomised controlled trials included in this re-view, 7 were published between 2010 and 2011. Thequality of studies published since 2010 is also demon-strably improved with much larger sample sizes, includ-ing 3 trials [54,57,61] with a sample size greater than200 and 2 trials with a sample size over 580 [51,56].However, despite the increased volume and improved

quality of the studies, there remains a lack of largecluster randomised controlled design studies, asrecommended by Fayers [62] who argues that clusterRCTs are well suited to overcome the limitations of sim-ple RCTs. It is well-known that system intervention tri-als such as routine collection of PROs, and feedback tothe clinicians and systems, are prone to cross-contamination and to introducing investigator and par-ticipant biases. Two recently published studies [54,57]were the continuation of an earlier study published byVelikova et al. (2004) [36]. Most studies reviewed didnot systematically examine outcomes and mechanisms,and placed more emphasis on processes rather than out-come measures [25]. All studies were conducted in alimited setting (often in a single centre) thus restrictingthe generalisation of the findings.No studies have adopted a comprehensive theoretical

model and framework, despite the repeated demandfrom leading researchers in the area [25,63-65]. All stud-ies focused on the patient and health professional levelwithin the clinic setting. No study to date has examinedthe impact of collecting PROs on health care organisa-tions, health system improvement, quality improvementor population health at a system or societal level.

Overview of study findingsImpact on patient-provider communicationAcross the 27 studies included in this review, 4 studies[39,47,51,53] did not examine or report the effect of a rou-tinely collected PRO on patient-provider communication.Among the 23 studies that did report such an impact, 21studies (91.3%) reported a positive effect which includedwell-designed and conducted large RCTs [33,36,37,54,56,57].One study reported no significant improvement of patient-provider communication possibly due to a lower severitylevel of cancer patients (only 37% of patients received anti-cancer therapy, hence the reduced need for communicationfor the treatment) [38]. Another study reporting a negativeeffect had an already high communication level at baseline(hence a ceiling effect leaving little room for furtherimprovement) [34].

Impact on monitoring treatment responseDespite most of included 27 studies did not explicitly statetheir study objectives as to examine the impact on moni-toring treatment response, 11 of the 27 studies did reportan outcome (Table 3) [16,20,36,41,45-51]. All 11 studiesfound a strong or modest effect of implementing PROs onthe increased monitoring activities of treatment response.The strongest effect occurred in the studies that focusedon the monitoring of patient symptoms, side effects andtoxicity during and after chemotherapy for the outpatients.In particular, the real-time, patient reported symptomsand toxicity (through innovative mobile phone-based,web-based or IVR systems) significantly improved themonitoring of treatment response.

Impact on detecting unrecognised problemsAlthough the idea of routinely collected PROs may providebetter opportunities for services providers (as well as pa-tients) to detect unrecognised problems through growingawareness, improved communication and monitoring seems

Table 5 The impact and effect sizes of the studies on patients, care providers and organisations*

Studies Doctor-patientcommunication

Monitortreatmentresponse

Detectunrecognisedproblems

Changesto patient health behaviour

Changes topatientmanagement

Improvedpatientsatisfaction

Improvedhealth outcomes

Feasibilityof theimplementation

Moderating andsubgroup effect

Trowbridgeet al. (1997)[39]

++ ++ + (but no changein PMI)

+++

Tazenzer et al.(2000)[33]

+++ ++ + - +++

McLachlanet al. (2001)[38]

-(no timedifferences inconsultationbetween twoarms)

-(only 37%patientsreceivinganticancertherapy atbaseline)

- - +++ + (on high BDI scoresubgroup)

Detmar et al.(2002)[37]

+++ (10 out of12 HRoLmeasures,especially onsocialfunctioning andfatigue)

++ + (increasedpatientcounselling) +(25% with familymembers andprimary carephysicians)

+ (emotionalsupport)

+ (SF-36) +++ + (before-afterimprovement byintervention group)

++ (informationsharing &communication)

Mooney et al.(2002)[16]

+++ ++ ++ +++ ++

Velikova et al.(2004)[36]

+++ ++ (64%encountersinvolvingreferring toHRoL byphysicians)

-(possible due tosimple codingbetween two arms)+(contributed topatientmanagement in11% of encountersintervention arm).

++(overall qualityof life andemotionalfunctioning)

++ (responserate 70%)

+ (more discussion ofHRoL subgroup hadbetter outcome withinintervention group)

Basch et al.(2005)[41]

+++ + ++ +++ + ++ (65% patientlog in beforeany verbalencouragement)

Boyes et al.(2006)[35]

+ (50%oncologists ininterventiongroup talkedwith patients)

- ++ (fewerdeliberatingsymptoms) -(anxiety anddepression)

+ -

Hoekstra et al.(2006)[42]

+/−(Only 18%patients used itenhancingcommunication)

- ++ (lowerprevalence in 9out of 10symptoms;deteriorated lessin 8 out of 10symptoms)

+ The beneficial effectswere pronounced in thedeteriorated group.

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Table 5 The impact and effect sizes of the studies on patients, care providers and organisations* (Continued)

Korniblith et al.(2006)[43]

+++ (both arms) ++ (morefrom TM+EMarm)

++ (both arms) ++ (better in TM+EM arm –reduction ofpsychologicaldistress)

++

Basch et al.(2007)[44]

+ ++ ++ (can beimprovedthroughreminder)

Rosenbloomet al. (2007)[34]

-(PossibleCeiling effect)

- - - ++ No effect even amongthe most highlydistressed patients

Weaver et al.(2007)[45]

+ (nurse-patientcommunication)

+ + + + + ++

Butt et al.(2008)[46]

++ + + + ++ ++

Given et al.(2008)[47]

+ + ++ (ATSM morelikely togeneratedresponses insymptommanagement andrequired less timeto do so)

++ + (Compared withpatients receivingcombinationchemotherapy protocols,those patients treatedwith single agent hadgreater response andshorter time toresponse)

Hilarius et al.(2008)[48]

++ + ++ + ++ ++

Mark et al.(2008)[49]

++ + + + ++ ++

Kearney et al.(2009)[50]

++ + ++ ++ ++ (Fatigue) +++

Carlson et al.(2010)[51]

+++ (distress) ++(decreaseddepression andanxiety related toreferral toservices)

+++

Dinkel et al.(2010)[52]

+ + + ++

Halkett et al.(2010)[11]

+ (around 25%of doctors)

+ (10% patientsreported changedoutcomes)

+ (patients isgenerally happywith bothmethods) -(Healthprofessionalsfound someissues)

+/− (some issuesidentified butnothingfundamental andpatients weregenerally happy)

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Table 5 The impact and effect sizes of the studies on patients, care providers and organisations* (Continued)

Ruland et al.(2010)[53]

++ ++ ++ ++

Velikova et al.(2010)[54]

++ (no difference incoordination ofcare & ‘preferencesto see usualdoctor’ subscale)

++(86% inintervention vs29% in theattention-control group)

++

Bainbridgeet al. (2011) [55]

+ + + ++ + 89% of nurses and55% of physiciansreferred to the ESAS inclinics ‘always’ or ‘ mostof the time’

Berry et al.(2011)[56]

++ (25%physicianexplicitlyreferred to SQLIsummary)

++ ++ (the treatment effecton communication isevident on overthreshold group oncognitive function,impact on sex and socialfunction)

Cleeland et al.(2011)[20]

++ + + + + ++ ++

Takeuchi et al.(2011)[57]

++ (onsymptom butnot function)

++

Note: +++ very strong effect; ++ strong effect; + some effect; +/- uncertain effect; - No effect; blank : untested or reported;*: Impacts on quality improvement, increased transparency, accountability, public reporting, better population and system performance (monitoring, planning, financing, evaluating, etc) were not listed due to lack ofdata.

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Records identified through database searching(n = 1062)

Scre

enin

gIn

clud

edE

ligib

ility

Iden

tifi

cati

on Additional records identified

through other sources (n =182)

Records after duplicates removed (n =62)

Records screened (n =1182)

Records excluded (n =1120)

Full-text articles assessed for eligibility

(n =62)

Full-text articles excluded, with reasons

(n = 35) description of information technique of PROs collection only(16) not including sufficient study endpoint(s) (12) not having sufficient quantitative analyses to enable assessment (7)Studies included in

qualitative synthesis(n = 27)

Figure 3 PRISMA Flow Diagram illustrating the systematic review process from electronic searching through to study inclusion.


intuitively plausible, only 16 out of 27 studies reported someresults related to the detection of unrecognised problems(Table 3). Amongst the 16 studies, 15 studies [16,20,33,36,37,39,41,43,45-50,53] reported either a strong or moderatepositive impact on detecting unrecognised problems. How-ever, a study by McLachlan and colleagues [38] did not findany difference between the intervention arm and controlarm.

Impact on changes to patient health behaviourNo study to date has provided a systematic evaluationon the impact of collecting PROs on changes to patienthealth behaviour. It is unknown whether and how pa-tient health behaviours have been changed.

Impact on changes to patient managementAmongst 17 studies that provided some results of changesto patient management, 13 studies [11,20,33,37,39,45,46,48-50,52,53,55] reported either a strong or modestpositive effect on the changes to patient managementwhilst 4 studies [34-36,54] found no such effect. However,it is worth noting that 10 studies did not provide any infor-mation about the changes to patient management and

there were often less complete descriptions of the resultson patient management when reported.

Impact on patient satisfactionAmong the 16 studies that reported results related tothe impact on patient satisfaction, 13 studies [11,16,20,37,41,43-46,48,49,52,54] reported a very strong to mod-erate positive effect on improved patient satisfaction. Forthe three studies [33,34,38] that did not find such a posi-tive effect, one study [33] reported a possible ceiling ef-fect meaning that both the intervention group andcontrol group had a very high baseline patient satisfac-tion level potentially impeding any demonstration of asignificant difference between two arms during thefollow-up period.

Impact on health outcomesAmongst the 15 studies that reported some results re-lated to the impact on health outcomes, 13 studies[20,35-37,39,41-43,45,47,50,51,53] reported some posi-tive improvement, ranging from modest to strong, whiletwo studies [34,38] failed to find any such effect. It ap-pears that symptoms, side effects and toxicity are most


likely to be improved, followed by emotional wellbeing.There is little evidence on the improvement of bothoverall HRQOLs as well as social wellbeing.

Impact on quality improvement, transparency, accountabilityand public reporting, and on better system performances(monitoring, planning, financing, evaluating, responding)No study to date has provided a meaningful, explicitframework nor relevant evidence on these endpoints.

Overall strength and direction of evidenceOverall, there is strong evidence supporting the notionthat routinely collected PROs, with feedback, improvespatient-provider communication and increases patientsatisfaction (Table 6). There is some evidence to supportthe notion that it improves the monitoring of treatmentresponses and detection of unrecognised problems, andthere is weak but positive evidence that, over time, itleads to changes in patient management. Despite someencouraging results, there is still a great degree of uncer-tainty regarding the impact of routinely collected PROs,with feedback, on patient health outcomes. There is littleor no evidence that it has led to significant positive im-provements in quality improvement, transparency, ac-countability, and public reporting, or in systemperformance at a population health or societal level.Apart from clinical trials and clinical practice, its impacton health services research and population health islargely unknown.

Potential moderating factors and links between routinePRO collection (with feedback) and patient outcomesAlthough the evidence is limited, it appears that routinecollected PROs with sufficient intensity of feedback(multiple times over a sustained period of time)

Table 6 The overall strength and direction of evidence

Results Strength anddirection of evidence

Patient-provider communication +++

Monitor treatment response ++

Detect unrecognised problems ++

Changes to patient health behaviour n/a

Changes to patient management +

Improved patient satisfaction +++

Improved health outcomes +/0

Strong & effective quality improvement n/a

Increased transparency, accountability, publicreporting

n/a

Better system performance (monitoring,planning, financing, evaluating, responding)

n/a

Note: ++++: the strongest positive effect; xxxx: the strongest negative effect;n/a: not available; 0: mutual (no significant effect).

[13,39,44,54], targeting multiple stakeholders (doctors,nurses, allied health workers, as well as patients) [35,52]with simple, clear, graphical and longitudinal meaningfulinterpretation of the results, and providing sufficienttraining for both health professionals and patients[20,57], are critical links between an intervention andthe intended outcomes. There is also evidence to suggestthat for some complex issues such as depression andlow social functioning, routine screening and feedbackmay need to be integrated with other strategies such asdecision-making aids, education, clear managementplans and clinical pathways including referrals, in orderto change patient outcomes [43,49,51]. There is prelim-inary evidence that some of the impacts of PROs may bemore pronounced amongst subgroups with more severeproblems at baseline (e.g. depression, symptoms)[38,42,65]. More studies are needed to fully understand-ing these mediating and moderating effects.

DiscussionThere is very strong evidence in supporting the notionthat routine collected PROs with timely feedback en-hances patient-provider communication. This currentstudy finding of a positive effect on patient-providercommunication is consistent with previous reviewsconducted in both cancer [26] and non-cancer settings[25,27,28]. There is also strong evidence to support thenotation that routine collected PROs significantly im-proved the monitoring of treatment response.There is reasonably strong evidence in supporting the

notation that routine collected PROs are helpful in identi-fying unrecognised problems in a large variety of settings.Within studies that reported, to some extent, the resultsrelated to unrecognised problems, there is a need for thedevelopment of more comprehensive and valid measures.Such a change in the measures would contribute towardsunderstanding specifically the PROs’ impact on identifyingthe underreported and unrecognised problems for differ-ent cancer patients at different settings.Overall, there is reasonable evidence in favouring the

hypothesis that implementing a routine collected PROssystem brings positive changes to patient management inthe settings where a patient management plan is inte-grated with a routine collection of PROs. It appears thatthe simple routine feedback of PROs may not be sufficientto improve patient management and outcomes [48]. Othernecessary resources may be needed such as education, re-ferral services and a detailed patient management plan fol-lowing the PROs [43]. There is also a need to developbetter measures of change to patient management as it isoften complex and difficult to quantify [57].There is strong evidence to support the notation that

routine collected PROs with timely feedback significantlyenhance patient’s experience and satisfaction. There may


be other improved experience and satisfaction in otherstakeholders such as patients’ family members, caregivers,as well as health professionals that were not measured orunreported. Future research into furthering the under-standing of stakeholder experience after implementingroutine collected PROs would be desirable.Although positive evidence in supporting the notion

that routine collected PROs may improve health out-comes is weak, this finding needs to be confirmed bybetter designed studies covering a large set of well-developed outcome measures. There is also a need tounderstand the impact on long-term health outcomessuch as survival rate. Most of the studies included in thisreview did not focus on health outcomes and some ofthe positive improvement on the outcomes only oc-curred on selective measures. It is not clear how thesepositive improvements can be generalised across differ-ent settings.There is a variety of models on how to routinely col-

lect PROs and how to feed back the data to differentstakeholders. Given that cancer patients are vastly differ-ent given their background, type and stage of cancer,prognosis, treatment, and the positions at the life coursecontinuum, precaution should be exercised whenattempting to apply the general observation above toeach and every different setting. For example, recentstudies demonstrated a positive impact of routine col-lected PROs on symptom control through either web-based or mobile phone based approach. However, suchpositive impacts were less pronounced on HRQOL.

Limitations of the current reviewOur review has several limitations. First, there was noattempt made to contact the authors to ask for potentialunpublished data on the topic. Thus, there may bechance of missing some grey literature or the studiesthat under preparation for publication. Second, given themultitude of endpoints included, and different types ofstudies involved, the assessment of eligibility for inclu-sion of potential studies required some degree of sub-jective judgement. Third, our application of GRADEsystem was rather simplistic restricted by large numberof endpoints and variability of studies included. Theselimitations may give rise to some uncertainty in terms ofsynthesis of the results. Fourth, our study follows a sys-tematic review approach with inclusion of both experi-mental trials and quantitative observational studies.However, we did not include qualitative studies in ourreview which may provide additional insight into thequestions raised. This is particularly relevant with re-spect to questions 2 and 3 as there was very little quanti-tative evidence from the included studies. It is importantto note that despite efforts to formulate the review end-points based on solid and well-established causal and

theoretical frameworks (providing insight into not onlyif but also how the introduction of PROs affects patientoutcomes), the causal mechanisms and process end-points included in the current review are by no meansexhaustive. There may be other important causal mecha-nisms that could be benefited from a realist review ap-proach [66].

ConclusionsThere is growing evidence supporting the routine collec-tion of PRO to enable better and patient-centred care,especially in cancer settings. Despite the strong evidencein supporting the notion that the well-implemented rou-tine collection of PROs enhances patient-provider com-munication and improves patient satisfaction, andgrowing evidence supporting ideas that it also improvesthe monitoring of treatment response and the detectionof the unrecognised problems, the evidence-base wasweak for its impact on changes to patient managementand improved health outcomes and non-existent forchanges to patient health behaviour, strong and effectivequality improvement, increased transparency, account-ability, public reporting and better health care systemperformance. These evidence gaps require further com-mitted and well-planned research in addition to thewell-accepted PROs. Decision-making agencies havebeen well positioned for leverage on the rapid advance-ment of different PRO models, the application of theitem response theory and computer adapted test in de-veloping PROs, and on the acceptance of such technol-ogy by patients and health professionals over the lastdecade. The real-time and routinely collected PROs willenable the development of a rapid learning health sys-tem with the potential to advance our knowledge of drugdevelopment, unsurpassed models of cancer patient careand a more patient-centred health care system.

Additional file

Additional file 1: Appendix 1. Full text search strategies used inScopus.

Competing interestsThe authors declare that they have no competing interests.

Authors’ contributionsJC contributed to the conceptualisation and design of the study. JC, LO, SHconducted the review. JC prepared the first draft of the paper and all otherauthors contributed to and approved the final manuscript.

AcknowledgementsThis article is based on An Evidence Check rapid review brokered by the SaxInstitute (http://www.saxinstitute.org.au) for the Cancer Institute NSW, 2012.The views expressed in this article are entirely those of the authors andshould not be interpreted as that of the Sax Institute or the Cancer InstituteNSW.

http://www.biomedcentral.com/content/supplementary/1472-6963-13-211-S1.doc

http://www.saxinstitute.org.au


Received: 31 October 2012 Accepted: 28 May 2013Published: 11 June 2013

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doi:10.1186/1472-6963-13-211Cite this article as: Chen et al.: A systematic review of the impact ofroutine collection of patient reported outcome measures on patients,providers and health organisations in an oncologic setting. BMC HealthServices Research 2013 13:211.

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