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Randomised controlled trial of an automated, interactive telephone intervention to improve type 2 diabetes… Bird, Dominique; Oldenburg, Brian; Cassimatis, Mandy; Russell, Anthony; Ash, Susan; Courtney, Mary D; Scuffham, Paul A; Stewart, Ian; Wootton, Richard; Friedman, Robert H Oct 12, 2010

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STUDY PROTOCOL Open AccessRandomised controlled trial of an automated,interactive telephone intervention to improvetype 2 diabetes self-management (Telephone-Linked Care Diabetes Project): study protocolDominique Bird1*, Brian Oldenburg1, Mandy Cassimatis2, Anthony Russell3,4, Susan Ash5, Mary D Courtney6,Paul A Scuffham7, Ian Stewart5, Richard Wootton8, Robert H Friedman9AbstractBackground: An estimated 285 million people worldwide have diabetes and its prevalence is predicted to increaseto 439 million by 2030. For the year 2010, it is estimated that 3.96 million excess deaths in the age group 20-79years are attributable to diabetes around the world. Self-management is recognised as an integral part of diabetescare. This paper describes the protocol of a randomised controlled trial of an automated interactive telephonesystem aiming to improve the uptake and maintenance of essential diabetes self-management behaviours.Methods/Design: A total of 340 individuals with type 2 diabetes will be randomised, either to the routine carearm, or to the intervention arm in which participants receive the Telephone-Linked Care (TLC) Diabetes program inaddition to their routine care. The intervention requires the participants to telephone the TLC Diabetes phonesystem weekly for 6 months. They receive the study handbook and a glucose meter linked to a data uploadingdevice. The TLC system consists of a computer with software designed to provide monitoring, tailored feedbackand education on key aspects of diabetes self-management, based on answers voiced or entered during thecurrent or previous conversations. Data collection is conducted at baseline (Time 1), 6-month follow-up (Time 2),and 12-month follow-up (Time 3). The primary outcomes are glycaemic control (HbA1c) and quality of life (ShortForm-36 Health Survey version 2). Secondary outcomes include anthropometric measures, blood pressure, bloodlipid profile, psychosocial measures as well as measures of diet, physical activity, blood glucose monitoring, footcare and medication taking. Information on utilisation of healthcare services including hospital admissions,medication use and costs is collected. An economic evaluation is also planned.Discussion: Outcomes will provide evidence concerning the efficacy of a telephone-linked care intervention forself-management of diabetes. Furthermore, the study will provide insight into the potential for more widespreaduptake of automated telehealth interventions, globally.Trial Registration Number: ACTRN12607000594426BackgroundDiabetes is a leading cause of death and morbidity andis a health priority in Australia and worldwide. Over 285million people have diabetes around the world [1] (90%of whom are diagnosed with type 2 diabetes). For theyear 2010, it is estimated that 3.96 million excess deathsin the age group 20-79 years are attributable to diabetesaround the world [2]. The number of people living withdiabetes is predicted to reach 439 million in 2030 [1].Poor glycaemic control, as measured by HaemoglobinA1c (HbA1c), significantly increases one’s risk of costlydiabetes-related complications [3,4].Self-management is an integral component of effectivediabetes care [5]. Systematic reviews of interventions* Correspondence: dominique.bird@monash.edu1Department of Epidemiology and Preventive Medicine, School of PublicHealth and Preventive Medicine, Monash University, 3rd Floor BurnettBuilding The Alfred Hospital, Melbourne, 3004, AustraliaFull list of author information is available at the end of the articleBird et al. BMC Public Health 2010, 10:599http://www.biomedcentral.com/1471-2458/10/599© 2010 Bird et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.targeting diabetes self-management indicate that theeffectiveness of these programs is significantly related totheir duration [6,7]. This emphasises the importance ofongoing follow-up and support for successful long-termglycaemic control [8].The delivery of ongoing support to the fast growingnumber of people living with diabetes presents a realchallenge for most health systems and this will not beaddressed by any modest increase in the number of rele-vant health professionals to provide such services.Addressing this challenge requires new cost-effectiveapproaches that will reach a large number of individualsregularly, in particular, those people who already havepoor access to current services, due to geographical,financial or other barriers.Programs using automated information and telecom-munication technologies offer a potential solution tochronic disease management as they can be conveni-ently accessed from home or office and at any time ofthe day or night. Reviews of such interactive automatedtechnologies in chronic disease care, including diabetes[9-11], report positive effects on users’ self-care knowl-edge, clinical and behavioural outcomes, social supportand health care utilisation. In addition, acceptability ofautomated telephone programs among users has beenshown to be high [12]. Further, the logical structure, onwhich computerised interventions are built, means thatthey offer a consistency of delivery which is difficult toachieve in programs delivered by health professionals.Therefore, these technologies hold promise as a newapproach to overcome barriers associated with the tradi-tional delivery of chronic disease self-management pro-grams by offering effectiveness, accessibility andconsistency. They may also prove to be cost-effective.The use of a telephone as the mode of access to theseprograms makes them available to the majority of thepopulation. The Telephone-Linked Care (TLC) systemis an interactive computer assisted telephone systemwhich has been shown to improve health behavioursand to be acceptable to users [13-17]. This system con-sists of a computer connected to the telephone network,equipped with speech recognition, numerous pre-recorded conversation statements and a database inwhich users’ answers are stored. It is designed to emu-late telephone conversations between patients andhealth professionals. It tailors its responses, includingfeedback and encouragement, according to data enteredin the TLC database and the answers that it receivesduring the current and previous calls.This paper presents the study protocol for a rando-mised controlled trial (RCT) of a TLC system aiming toimprove type 2 diabetes management, TLC Diabetes.We hypothesise that participants in the interventionarm will demonstrate greater improvements in HbA1cand health-related quality of life (QoL) compared tothose in the control arm. Secondly, we hypothesise thatthe intervention will be cost-effective compared with thecontrol arm. The results of this study will provide valu-able information about the efficacy, cost-effectiveness,acceptability and feasibility of a novel way to improvetype 2 diabetes self-management.Methods/designStudy designThe study is a two-arm prospective RCT in which atotal of 340 adults with type 2 diabetes will be rando-mised to either the intervention (TLC Diabetes pro-gram) or ‘routine care’ control arm. Participants in botharms complete assessments at baseline (Time 1),6-month follow-up (Time 2), and 12-month follow-up(Time 3).Study aimsPrimary Aim: To investigate the effects of the TLC Dia-betes program on health outcomes (primary outcomevariables include HbA1c and QoL measured using theShort Form-36 version 2 [SF-36v2]) post intervention(Time 2) and at 12- month follow-up (Time 3).Secondary Aim: To examine the cost-effectiveness ofthe intervention arm in comparison with the controlarm.Study sampleEligibility criteriaEligibility criteria include: a type 2 diabetes diagnosis ofat least 3 months; aged 18 - 70 years; residing in thegreater Brisbane area (Australia); an HbA1c level of atleast 7.5%; stable diabetes pharmacotherapy type for atleast 3 months; stable pharmacotherapy dosage for atleast 4 weeks; ability to clearly speak and understandEnglish via the telephone, and weekly access to a tele-phone. Participants are excluded if they are: diagnosedwith a condition with likely poor prognosis within 1year; diagnosed with dementia or a psychiatric co-mor-bidity; pregnant, lactating, or planning to become preg-nant within the next 12 months; currently enrolled inanother intervention trial; or have undergone bariatricsurgery in the past 2 years.Sample recruitment proceduresA range of recruitment strategies are used includingadvertisements in newspapers and community newslet-ters and distribution of flyers to a large number ofhealth professionals to provide to patients diagnosedwith type 2 diabetes. Patients of diabetes clinics of threemajor hospitals in Brisbane and clients of DiabetesAustralia - Queensland’s shops and information semi-nars are also informed of the study by research staff orby flyers placed in reception areas.Bird et al. BMC Public Health 2010, 10:599http://www.biomedcentral.com/1471-2458/10/599Page 2 of 6Individuals expressing interest in participating arescreened in two stages. They are firstly assessed againsteligibility criteria at first contact via telephone or in per-son. If deemed potentially eligible, they attend a baselineappointment at one of two large teaching hospitals, thePrincess Alexandra Hospital (PAH) or the RoyalBrisbane and Women’s Hospital (RBWH) in Brisbane,where they are provided with a comprehensive explana-tory statement. After signing the study consent form,they complete the baseline questionnaires and a hospitalphlebotomist takes the blood specimens required. Theyare excluded if the HbA1c result from this blood testdoes not meet the HbA1c criterion.Sample size calculationsA total of 340 eligible participants will be recruited tothe study. It is anticipated that there will be an attritionrate of up to 30% over the 12 months of follow-up, sowe expect complete data on 238 participants. With 238completing participants, we shall be able to detect, with90% power and type I error of 5% (two-tailed), excessintervention effects over routine care effects of at least0.4% (from baseline 8.9% to 8.5%) in HbA1c. The calcu-lations for HbA1c were based on standard deviations ofchange of 1% in both groups, conservatively estimatedassuming maximum physiological range of 3% improve-ment or deterioration of individuals. An effect size of0.4% in our primary outcome, HbA1c, was chosen forour sample size calculations as per Toobert [18], whocalculated that a change of 0.4% translates into a clini-cally meaningful 14% reduction in risk of diabetes com-plications based on the analysis of the UK ProspectiveDiabetes Study in patients with type 2 diabetes. For SF-36v2 physical and mental component summary scores, asample of 238 completed participants has 90% power todetect a difference of 3.9 units (assuming standarddeviation of 10 [19]).Ethics approvalEthics approval was received from Human ResearchEthics Committees of the Princess Alexandra Hospital(No. 2007/029), Royal Brisbane and Women’s Hospital(No. HREC/09/QRBW/21), Prince Charles Hospital(No. HREC/O9/QPC HJ26), the University of Queens-land (No. 2007000899) and Monash University (No.CF07/0313 - 2007/0102).Study armsAll participants receive a quarterly newsletter consistingof general health information; this aims to maintainparticipation.Control armControl participants are advised to continue their rou-tine medical care.Intervention armIntervention participants also continue their routinemedical care. In addition, they receive the TLC Diabetesprogram which was developed collaboratively betweenthe Australian research team and USA researchers atthe Medical Information Systems Unit, Boston Univer-sity [20,21]. The TLC Coordinator, whose role is to sup-port intervention group participants in all aspects of useof the TLC Diabetes program, meets with participantswithin one week of their Time 1 data collection to pro-vide them with the TLC Diabetes kit containing theTLC Handbook, an ACCU-CHEK® Advantage glucosemeter, test strips, and a Bluetooth™ device with which toupload their blood glucose results to the TLC Diabetessystem. The TLC Handbook contains instructions andgeneral information on the TLC Diabetes program, anumber of Diabetes Australia diabetes management factsheets plus sheets on which to record notes and infor-mation related to the program. A quit smoking informa-tion pack, containing a self-help booklet and brochures,is also provided to current smokers. During this meet-ing, participants also receive instructions on how tooperate the glucose meter and the uploading Bluetooth™device and complete a training call to the TLC Diabetessystem. Participants are asked to perform all blood glu-cose self-monitoring with the study glucose meter andto upload its readings immediately preceding theirweekly telephone conversations with the TLC system.Participants choose a unique personal password whichthey enter at the start of each call to the system andwhich is linked to their database file and ensures correctsubject identification and confidentiality. Prior to theparticipants’ first call to the system the TLC Coordina-tor obtains personalised self-care clinical targets for theparticipants from their primary health care provider.This includes recommended number of daily blood glu-cose tests, ideal fasting blood glucose range and clear-ance for physical activity. Once this information isentered into the database, participants start makingweekly calls to the system over a period of 24 weeks.The calls are at no cost to them and they can lastbetween 5 and 20 minutes (depending upon the contentof the call and the participant’s responses). Blood glu-cose monitoring is the first topic covered in each weeklycall. It is followed by one of the following topics: medi-cation-taking (calls 1-4; 13-16), physical activity (calls5-8; 17-20), and healthy eating (calls 9-12; 21-24). Whena participant does not take any medication prescribedfor diabetes, the medication-taking topic is replaced byphysical activity. When the treating physician does notprovide clearance for physical activity, this topic isreplaced by medication-taking. In cases when there isno clearance for physical activity and no pharmaceuticalBird et al. BMC Public Health 2010, 10:599http://www.biomedcentral.com/1471-2458/10/599Page 3 of 6treatment of diabetes, the participant does not hear asecond topic on calls 1-8, and 13-20.The TLC Coordinator phones participants after theirfirst two calls to the TLC system and at weeks 6, 12 and20, to identify and resolve any issues faced during theiruse of the TLC Diabetes system or to identify reasonsfor not calling regularly. Additionally, the TLC Diabetessystem sends email “alerts” to a dedicated project emailaddress to signal the need for the Coordinator to con-tact a participant regarding technical or other issues.Study integrityThe study design is according to the recommendationsof the CONSORT statement for randomised trials ofnon-pharmacologic treatment [22]. Randomisation to anexperimental group occurs after the Time 1 baselineassessment is completed. Arm allocation is conductedusing a 4 × 4 block randomised block design with theparticipant as the unit of randomisation. Due to thecomplex nature of the intervention, it is not possible toblind research staff to group allocation. The interventionprotocol is documented and the data generated duringthe calls made by participants is stored in the TLC data-base. All analyses will be conducted based on the princi-ple of intention to treat.MeasurementAll assessments (Table 1) are administered at the PAHor RBWH but at the same location for Time 1, 2 and 3.Blood specimens are collected according to QueenslandHealth guidelines. Waist and hip circumferences aremeasured according to WHO MONICA guidelines [23].Behaviour, psychosocial and health care utilisation(HCU) questionnaires are self-administered.Primary and secondary outcome variablesPrimary outcome variables are: HbA1c and health-relatedQoL measured by the SF-36v2 [24,25]. Secondary outcomevariables include: clinical measures (blood lipid profile,body mass index [BMI], waist and hip circumferences,blood pressure), psychosocial outcomes (depression andanxiety symptoms [26], social support [27]), nutrition andphysical activity self-efficacy [28], physical activity [29],diet [30], adherence to foot-care, medication taking andblood glucose testing [31]. Information pertaining to HCU(visits to health practitioners, hospital admissions, otherhospital services and medications), healthcare costs andcosts of the intervention is also collected. The measuresfor these variables are summarised in Table 1.Intervention implementationAdherence to the program is assessed by the proportionof completed calls to the system relative to the expectedTable 1 Primary and secondary outcome measures for times 1, 2 and 3Variable InstrumentPrimary outcome variablesGlycaemic control HbA1cQuality of life SF-36v2 [24,25]Secondary outcome variablesBlood lipids Total cholesterol, LDL cholesterol, HDL cholesterol, triglyceridesInsulin sensitivity HOMA scoreKidney function Creatinine and estimated Glomerular Filtration Rate (e-GFR)Blood pressure Measured twice using Welch-Allyn electronic sphygmomanometer on same arm. A thirdmeasure is taken when the first two readings differ by more than 10 mmHg and 6mmHgfor systolic and diastolic blood pressure respectively.Body Mass Index (BMI) Calculated from height and weight measured by research staffWaist and hip circumference Measured by research staff according to WHO MONICA project guidelines [23]Diet Anti Cancer Council of Victoria Food Frequency Questionnaire [30] (ACCVFFQ)Physical activity Active Australia Survey [29]Self-efficacy (nutrition and physical activity) Self-efficacy scales [28]Anxiety and depression Hospital Anxiety and Depression Scale [26]Social support ENRICHD Social Support Inventory [27]Smoking Self-reportAdherence to recommendations for blood glucosetesting, foot-care and medicationSummary of Diabetes Self-Care Activities [31]Health care service utilisation, except hospitaladmissionsSelf-report for visit to health professionals, usage of hospital services not involvingadmissions and medicationsHospital admissions Electronic records maintained by Queensland Health, plus self-report for admissions toprivate hospitalsCo-morbidities Self-reportBird et al. BMC Public Health 2010, 10:599http://www.biomedcentral.com/1471-2458/10/599Page 4 of 6number of calls, time interval between calls, and callduration. In addition, satisfaction with and perception ofusefulness of the intervention are assessed by self-administered questionnaire at Time 2 and a semi-structured interview at Time 3.Socio-demographic variablesSelf-reported socio-demographic variables include gen-der, age, ethnicity, marital status, education, employ-ment status, private health insurance status andhousehold income.Data analysesAssessment of similarity of baseline characteristicsacross randomised groups will be performed usingappropriate summary statistics. If any imbalances ofcharacteristics between the two groups are identified,these will be adjusted for in the main analytical model-ling as supplementary analyses. Evaluation of the TLCDiabetes intervention effect will be based on an inten-tion-to-treat analysis. Analysis of covariance (with base-line score as the covariate) will be fitted to estimatedifferences by intervention group in changes over timeat each time point. Analysis across all time points usingall available data, including as much as possible those ofparticipants lost to follow-up, will employ generalisedestimating equations. Results will be expressed as esti-mated mean changes in primary and other outcomevariables by group, and as overall mean excess interven-tion over routine care effects, all with corresponding95% confidence intervals.Cost-effectiveness analysisDetailed economic data will be collected throughout thetrial to enable a comprehensive evaluation of the inter-vention’s efficiency when compared to routine care. Dataon HCU will be obtained from participants at times 1, 2and 3 and data on all public hospital admissions will beobtained from Queensland Health. Standard costs will beapplied to HCU in both arms (e.g. Australian-RevisedDiagnostic Related Groups for hospital admission costs).The intervention arm will also incur the costs of theintervention including set-up costs that will be annuitized(e.g. computer, telephone line connections) and operatingcosts (e.g. TLC Coordinator).Within-trial and modelled over the rest of life cost-utility analyses will be undertaken from the perspectiveof direct health care costs to the government. SF-36v2scores will be converted to utility weights using the SF-6D algorithm [32] for the calculation of quality-adjustedlife years (QALYs) - the primary outcome for the eco-nomic evaluation. The incremental costs and QALYswill be calculated as the differences between participantsin the intervention and routine care groups. The result-ing incremental cost-utility ratio will provide a measureof the relative value for money of the intervention usingthe additional cost per QALY gained. One-way andprobabilistic sensitivity analyses will be undertaken forall parameters with uncertainty and/or variability [33].DiscussionPrevious trials of automated TLC systems targeting phy-sical activity, nutrition and medication adherence havedemonstrated the effectiveness of such technology toimprove health behaviours and chronic disease self-management [13,16,17]. To date, this innovative andaccessible form of self-management support programhas not been formally tested in relation to diabetes man-agement and its cost-effectiveness has not been exam-ined. Therefore, this study will provide valuableinformation on the effectiveness, user-acceptability andfeasibility of this telehealth system. It addresses the needto investigate new approaches to deliver ongoing andregular diabetes self-management support to relievehealth systems from the growing demands caused by theincreasing prevalence of diabetes around the world.AcknowledgementsThe study is funded by a National Health Medical Research Council projectgrant (ID 443214), by the HCF Health and Medical Research Foundation andby Queensland Health. We wish to thank all participants taking part in thestudy, Diabetes Australia for its generous provision of material for the studyhandbook and Diabetes Australia - Queensland for its endorsement of thestudy and assistance with recruitment. We would like to thank ProfessorAndrew Forbes for his advice in relation to statistics. We acknowledge thecommitment of the project staff: Megan Rollo, Wei-I Wu, Dr Stephen Bunker,Adrienne O’Neill and Vivien Harris. We would like to thank Dr StephanGaedhe, one of the principal developers of the TLC Diabetes system,Professor Kerrie Mengersen, and the Australian Diabetes EducatorsAssociation for their contributions. We are grateful for input from staff at theMedical Information Systems Unit, Boston University, including Andrew Rossiand Annemarie Haselgrove. Finally, we also wish to thank Roche DiagnosticsACCUCHEK for their supply of the glucose meters and Alive Technologiesfor all of their technical support and advice.Author details1Department of Epidemiology and Preventive Medicine, School of PublicHealth and Preventive Medicine, Monash University, 3rd Floor BurnettBuilding The Alfred Hospital, Melbourne, 3004, Australia. 2Centre for OnlineHealth, University of Queensland, Brisbane, Australia. 3Diamantina Institute,University of Queensland, Princess Alexandra Hospital, Brisbane, Australia.4Department of Diabetes and Endocrinology, Princess Alexandra Hospital,Brisbane, Australia. 5Institute of Health and Biomedical Innovation,Queensland University of Technology, Brisbane, Australia. 6Faculty of Healthand Social Development, University of British Columbia, Vancouver, Canada.7Centre for Applied Health Economics, School of Medicine, Griffith University,Logan, Australia. 8Norwegian Centre for Integrated Care and Telemedicine,University Hospital of North Norway, Tromsø, Norway. 9Medical InformationSystems Unit, Boston Medical Center, Boston University, Boston, USA.Authors’ contributionsBO and RHF conceived the original study design and its development. BO,RHF, AR, SA, MDC, RW, IS, PS and DB developed the intervention and studyprotocols. DB and MC drafted the manuscript. All authors read andcontributed to the final manuscript.Competing interestsThe authors declare that they have no competing interests.Bird et al. BMC Public Health 2010, 10:599http://www.biomedcentral.com/1471-2458/10/599Page 5 of 6Received: 6 October 2010 Accepted: 12 October 2010Published: 12 October 2010References1. Shaw JE, Sicree RA, Zimmet PZ: Global estimates of the prevalence ofdiabetes for 2010 and 2030. Diabetes Research and Clinical Practice 2010,87(1):4-14.2. International Diabetes Federation: IDF Diabetes Atlas Brussels, Belgium:International Diabetes Federation, 4 2009.3. UK Prospective Diabetes Study (UKPDS) Group: Intensive blood-glucosecontrol with sulphonylureas or insulin compared with conventionaltreatment and risk of complications in patients with type 2 diabetes(UKPDS 33). The Lancet 1998, 352(9131):837-853.4. 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Schwarzer R, Renner B: Social-cognitive predictors of health behavior:action self-efficacy and coping self-efficacy. Health Psychology 2000,19(5):487-495.29. Australian Institute of Health & Welfare: The Active Australia Survey: A guideand manual for implementation, analysis and reporting Canberra 2003.30. Hodge A, Patterson AJ, Brown WJ, Ireland P, Giles G: The Anti CancerCouncil of Victoria FFQ: relative validity of nutrient intakes comparedwith weighed food records in young to middle-aged women in a studyof iron supplementation. Australian and New Zealand Journal of PublicHealth 2000, 24(6):576-583.31. Toobert DJ, Hampson SH, Glasgow RE: The Summary of Diabetes Self-Care Activities measure: Results from 7 studies and a revised scale.Diabetes Care 2000, 23(7):943-950.32. Brazier J, Roberts J, Deveril M: The estimation of a preference-basedmeasure of health from the SF-36. Journal of Health Economics 2002,21(2):271-292.33. Doubilet P, Begg CB, Weinstein MC, Braun P, McNeil BJ: Probablisticsensitivity analysis using Monte Carlo simulations: a practical approach.Medical Decision Making 1985, 5(2):157-177.Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/10/599/prepubdoi:10.1186/1471-2458-10-599Cite this article as: Bird et al.: Randomised controlled trial of anautomated, interactive telephone intervention to improve type 2diabetes self-management (Telephone-Linked Care Diabetes Project):study protocol. BMC Public Health 2010 10:599.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitBird et al. 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