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Older Persons’ Transitions in Care (OPTIC): a study protocol Cummings, Greta G; Reid, R C; Estabrooks, Carole A; Norton, Peter G; Cummings, Garnet E; Rowe, Brian H; Abel, Stephanie L; Bissell, Laura; Bottorff, Joan L; Robinson, Carole A; Wagg, Adrian; Lee, Jacques S; Lynch, Susan L; Masaoud, Elmabrok Dec 14, 2012

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STUDY PROTOCOL Open AccessOlder Persons’ Transitions in Care (OPTIC): a studyprotocolGreta G Cummings1,8*, R Colin Reid2, Carole A Estabrooks1, Peter G Norton3, Garnet E Cummings4, Brian H Rowe4,Stephanie L Abel1, Laura Bissell2, Joan L Bottorff5, Carole A Robinson5, Adrian Wagg6, Jacques S Lee7,Susan L Lynch1 and Elmabrok Masaoud1AbstractBackground: Changes in health status, triggered by events such as infections, falls, and geriatric syndromes, arecommon among nursing home (NH) residents and necessitate transitions between NHs and EmergencyDepartments (EDs). During transitions, residents frequently experience care that is delayed, unnecessary, notevidence-based, potentially unsafe, and fragmented. Furthermore, a high proportion of residents and their familycaregivers report substantial unmet needs during transitions. This study is part of a program of research whoseoverall aim is to improve quality of care for frail older adults who reside in NHs. The purpose of this study is toidentify successful transitions from multiple perspectives and to identify organizational and individual factors relatedto transition success, in order to inform improvements in care for frail elderly NH residents during transitions to andfrom acute care. Specific objectives are to:1. define successful and unsuccessful elements of transitions from multiple perspectives;2. develop and test a practical tool to assess transition success;3. assess transition processes in a discrete set of transfers in two study sites over a one year period;4. assess the influence of organizational factors in key practice locations, e.g., NHs, emergency medical services(EMS), and EDs, on transition success; and5. identify opportunities for evidence-informed management and quality improvement decisions related to themanagement of NH – ED transitions.Methods/Design: This is a mixed-methods observational study incorporating an integrated knowledge translation(IKT) approach. It uses data from multiple levels (facility, care unit, individual) and sources (healthcare providers,residents, health records, and administrative databases).Discussion: Key to study success is operationalizing the IKT approach by using a partnership model in which theOPTIC governance structure provides for team decision-makers and researchers to participate equally in developingstudy goals, design, data collection, analysis and implications of findings. As preliminary and ongoing study findingsare developed, their implications for practice and policy in study settings will be discussed by the research teamand shared with study site administrators and staff. The study is designed to investigate the complexities oftransitions and to enhance the potential for successful and sustained improvement of these transitions.Keywords: Seniors, Elderly, Transitions, Quality of care, Handovers, Communications, Emergency Departments,Emergency Medical Services, Nursing homes, Measurement* Correspondence: gretac@ualberta.ca1Faculty of Nursing, University of Alberta, Edmonton, AB, Canada8Faculty of Nursing, Edmonton Clinic Health Academy, University of Alberta,11405-87 Ave, Edmonton, AB T6G 0C1, CanadaFull list of author information is available at the end of the article© 2012 Cummings et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of theCreative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited.Cummings et al. BMC Geriatrics 2012, 12:75http://www.biomedcentral.com/1471-2318/12/75BackgroundIn 2006, the number of Canadians aged 65 and overexceeded four million for the first time [1]. By 2011, thisrepresented 14.8% of the entire population (11.1% inAlberta; 15.7% in British Columbia – the two provincesrepresented in the present study) [2]. The greatest in-crease is among those aged 85 and older, with an averageannual rate of growth reported to be 3.8% [3,4]. By 2050,the over 85 age group could account for one-fifth of allolder persons [4]. These demographic trends increasinglychallenge healthcare systems as older people often requireboth more and different health services than do youngerpeople [5].Similar to other Organization for Economic Cooper-ation & Development (OECD) countries, almost half ofCanadian seniors will be residents of nursing homes(NHs) at some point during their lives [6-8]. Almost half(45%) of Canadians in NHs are 80+ years of age, overhalf suffer from dementia [9-11] and a substantial major-ity (73%) are women [6]. NH residents form a highlyvulnerable group with complex care needs and a highdegree of dependency on care providers [12].Changes in health status among NH residents – oftentriggered by events such as falls [13], infection [14], de-pression and other changes in mental status [15], andfailure to thrive [16] – necessitate transitions betweenNHs and emergency department (ED). While researchhas shown that not all emergency transitions arerequired, transferred residents frequently experiencecare that is unnecessary, delayed, not evidence-based,potentially unsafe, and fragmented [17-21]. Furthermore,a high proportion of residents and their family care-givers report substantial unmet needs resulting fromtransitions [22,23].Study purpose & objectivesThe Older Persons’ Transitions in Care (OPTIC) studyis a three year Canadian Institutes of Health ResearchPartnership for Health System Improvement (CIHR-PHSI) grant that involves the Central Okanagan districtof the Interior Health (IH) region in British Columbiaand the Edmonton Zone of Alberta Health Services(AHS) in Alberta. The purpose of this study is to iden-tify successful transitions from multiple perspectivesand to identify organizational and individual factorsrelated to transition success, in order to informimprovements in care for frail elderly NH residentsduring transitions to and from acute care. Specificobjectives are to:1. 1.define successful and unsuccessful elements oftransitions from multiple perspectives;2. 2.develop and test a practical tool to assess transitionsuccess;3. 3.assess transition processes in a discrete set oftransfers in two study sites over a one year period;4. assess the influence of organizational factors in keypractice locations, e.g., NHs, emergency medicalservices (EMS), and EDs, on transition success; and5. identify opportunities for evidence-informedmanagement and quality improvement decisionsrelated to the management of NH – ED transitions.RationaleWhile a number of US investigators have reported ontransitions for NH residents, in particular NH-ED transi-tions [24-29], few Canadian studies exist that report ontransitions for NH residents [30-32]. We do know thatthe in-hospital, and in particular ED experience for thefrail NH resident is characterized by serious quality andsafety concerns [33-36]. Sub-optimal quality of care inNH settings [37], and in pre-hospital and ED settings[38,39] have been described in many international [8],national [40], and provincial reports [41]. These reportsalso highlight high rates of burnout among family care-givers [39,42]. Given these reports and the cognitive im-pairment of many NH residents [9-11], the complexityof delivering effective and appropriate care can increaseduring transitions [36,43]. This complexity is often mademore difficult by compromised communication betweendifferent agencies involved in the transition [44].Previous research linking organizational factors withthe success or quality of the transition process signalsthe need for further exploration. Carter linked 1991–1993 Medicaid reimbursement data from Massachusettswith specific facility-level organizational and structuralattributes and showed that nursing home case-mix andlocal hospital bed supply levels predicted hospitalizationrates of NH residents [45]. However, Boockvar and Bur-ack found no management level relationships betweenNHs, hospitals and the quality of transitions [26].Little attention has been devoted to developing mea-sures that could address the quality of care delivered andreceived during transitions from NH to ED. One instru-ment, Coleman’s Care Transitions Measure tool, hasbeen used to measure performance around transitions[28,29,46,47], primarily focusing on identifying care defi-ciencies and approaches to address these deficiencies.However, this is a self-report tool which has been usedonly with community based participants and is thereforenot appropriate for most residents in NHs, who havesome degree of cognitive impairment [9-11]. Saliba andassociates developed a structured implicit review formfor use with retrospective chart audits to determine theappropriateness of ED transitions [48]. This tool is usefulfor research purposes; however, it is less applicable tothe needs of decision-makers and managers who needdata for quality management prospectively. Members ofCummings et al. BMC Geriatrics 2012, 12:75 Page 2 of 14http://www.biomedcentral.com/1471-2318/12/75our research team have previously constructed instru-ments to measure contextual factors in nursing homesthat influence care outcomes [49]. In that work weestablished two criteria for such a measure: (1) feasibility(brevity and ease of completion; the instrument can becompleted in 10–15 minutes), and (2) modifiability(focus on concepts that are potentially modifiable). Wewill apply these criteria to the development of the transi-tions success tool.MethodsDesignThis is a mixed-methods observational study using datafrom multiple levels (facility, care unit, individual) andsources (healthcare providers, residents, residents’ fam-ilies, health records, and administrative databases). Wewill examine the quality of transitions of NH residentsbetween and among three care settings (NHs, EMS, andEDs) over a one-year period in two cities in the pro-vinces of British Columbia and Alberta. The study’s gov-ernance structure is founded on an integrated knowledgetranslation (IKT) approach. The CIHR-PHSI granting ve-hicle provides for decision-makers and researchers on theOPTIC team to participate equally in developing the studygoals, design, data collection, analysis, recommendationsand dissemination of findings. As preliminary and ongoingstudy findings are gathered and interpreted, their implica-tions for practice and policy in study settings will be dis-cussed and shared with study site administrators and staff,rather than waiting for traditional modes of academic dis-semination of findings before changes to the workplaceare made.Theoretical framing of the studyThe research team developed the OPTIC TransitionFramework (Figure 1) informed by prior work of Parkeand Hunter [50] to guide data collection procedures.Our work is also informed by the Institute of Medicine(IOM) quality framework [51] (Figure 2). The IOMmodel stresses that health care and its systems and pro-cesses should be safe – avoiding injuries to patients fromthe care that is intended to help them; effective – provid-ing services based on scientific knowledge to all whocould benefit, and refraining from providing services tothose not likely to benefit; patient-centred – providingcare that is respectful of and responsive to individualFigure 1 OPTIC Transitions Framework. Developed by the OPTIC Team from Parke & Hunter, 2009.Cummings et al. BMC Geriatrics 2012, 12:75 Page 3 of 14http://www.biomedcentral.com/1471-2318/12/75patient preferences, needs, and values, and ensuring thatpatients’ values guide all clinical decisions; timely – reducingwaits and sometimes harmful delays for both those who re-ceive and those who provide care; efficient – avoiding waste,including that of equipment, supplies, ideas, and energy;and, equitable – providing care that does not vary in qualitybecause of personal characteristics such as age, gender, eth-nicity, geographic location, and socioeconomic status. Thusour work will identify and propose system and processimprovements that address several of these six elements of aquality healthcare system [51].The design and analysis of questions related to factorsthat influence the success of implementing new models ofcare is guided by the Andersen Behavioral Model of HealthServices Use [52] shown in Figure 3. The Andersen modelspecifies relationships among contextual factors (e.g., envir-onmental, population, health behaviour, and outcomes)and population characteristics (e.g., need, access, and pre-disposing characteristics) that influence the use of healthservices. We have also done considerable work in previousstudies, specifically in continuing care seniors’ facilities,that expands knowledge of the influence of organizationalcontextual factors in health services [49,53-55]. The im-portance of studying the health services context is also wellsupported by others [56,57,58].SettingThis study is being conducted in Kelowna, BritishColumbia, and Edmonton, Alberta. These two cities andsurrounding areas are different in size, population andhealth system composition. In 2006, Kelowna’s popula-tion was approximately 110,000 while Edmonton’s wasjust over 1 million. Kelowna has an older populationcompared to Edmonton (18% compared to 10.7%) [60].The following definitions of each component adapted for the OPTIC studyEquity - no bias associated with access to continuum of care. Timeliness – actions resulting in no unnecessary or unwanted delay.Effectiveness - actions that align best available evidence with optimal outcomeEfficiency - actions which cause no overuse or underuse of resources, e.g. investigations, treatments, etc.Resident Centered - actions informed by knowledge of and respect for diversity, values, choices, and needs of residents. Emphasizes care coordination, continuity, communication, education, and shared decision-making (Coleman)Safety - actions that cause no unnecessary harmFigure 2 The Institute of Medicine Model for Quality in Healthcare.Figure 3 Andersen Behavioral Model of Health Services Use.Cummings et al. BMC Geriatrics 2012, 12:75 Page 4 of 14http://www.biomedcentral.com/1471-2318/12/75The two regions are organized differently with regard toNH-ED transitions. In Kelowna, the General Hospital(KGH) is the sole receiving hospital for all 13 nursinghomes in the Central Okanagan district and the only ter-tiary referral hospital in the Okanagan area, whereas inEdmonton, the University of Alberta Hospital (UAH) isone of five receiving hospitals within the city, one of 11within the greater Edmonton region, and one of two ter-tiary referral hospitals. These factors offer an opportun-ity to study NH-ED transitions in two contrasting butadjacent provinces, enabling us to assess whether twocontextually different systems may offer relative advan-tages or disadvantages to a successful transition experi-ence. Both IH and AHS have a strong desire to buildlong term research capacity with committed researchers/decision-makers.Sample and inclusion criteriaAll data collection will use purposive, convenience sam-ples drawn from the populations as specified below.1.Nursing Homes: The population consists of 50 NHs(13 in Central Okanagan and 37 in Edmonton).Forty-two of the 50 NHs send residents to these twoEDs (all NHs in Central Okanagan and 29 of 37 inEdmonton). We will examine transfers from these 42NHs and will do in-depth analyses on a sample ofNHs using a sampling matric of high and lowtransfers (calculated as the number of annualtransfers per number of beds per facility), and public,and private ownership. Eligible research participantsinclude all individuals in the following groups –transferred NH residents and their families,physicians, registered and licensed practical nurses,healthcare aides and care managers.2. Emergency Medical Services: All 88 EMS staff (6 fulltime and 6 part time ambulance crews) in Kelownaand the 556 EMS and 145 Inter-hospital Transport(IHT) staff in Edmonton will be eligible, as are themedical and administrative supervisors in each city.3. Emergency departments: The physicians, nurses andother ED staff of the two EDs (KGH and the UAH)will be eligible for inclusion.Preparatory work for transition tracking - qualitativeinterviews & tool developmentWe received preliminary ethical and operationalapprovals to conduct the study in both provinces. Subse-quent ethics amendments were approved once the datacollection instruments were developed.The study is being conducted in three phases; Phase 1consisted of qualitative methods to investigate multipleperspectives of NH-ED care transitions and was completedto determine: (a) elements contributing to successful andunsuccessful transitions of care, and (b) measureable indi-cators for the initial Older Persons’ Transitions in CareSuccess (OPTICS) tool to track transitions in Phase 2.Thus the Phase 1 interviews informed the development ofthis protocol for Phases 2 and 3 (the focus of this manu-script). See Figure 4 for the OPTIC Study Timeline.Phase 1 qualitative interviews allowed us to exploredifferent perspectives of care transition experiences inour three settings. Semi-structured face-to-face inter-views with 71 participants consisting of three groups ofstakeholders (residents and families, frontline healthcareproviders, and managers/administrators) in both pro-vinces were employed to elicit key elements of successin all transition settings (NH, EMS and ED).The findings of the qualitative interviews included fiveelements that contributed to the success of transitionsand reflected a patient- and family-centered approach tocare. Transitions were influenced by the complex inter-play of multiple elements that included: knowing theresident; critical geriatric knowledge and skilled assess-ment; positive relationships; effective communication;and timeliness. When one or more of these elementswas absent or compromised, the success of the transitionwas also compromised [59]. More information on thequalitative phase can be found elsewhere [59]. These ele-ments and the IOM Model for Quality [51] led us to de-velop the OPTIC definition of successful transitions - Asuccessful transition is a coordinated set of actions thatoptimizes safety, resident centeredness, effectiveness, effi-ciency, timeliness and equity, across the entire transition.Development of the Transition Tracking Tool (T3)The Transition Tracking Tool (T3) was developed fromthe OPTIC Transition Framework (Figure 1) and thefindings from Phase 1 interviews [59]. It will be used toobtain case related transition data about individual NHresidents beginning with the decision to transfer fromthe NH to the ED and ending with the return of theresident to the NH (understanding that some of thesepersons will die in hospital). The T3 consists of approxi-mately 800 data points and incorporates the followingcategories of elements obtained by OPTIC staff from theresident/patient care records in each transition setting.NH: Demographic and medical data (includingmedications), reason(s) for transfer, information aboutthe decision and timing of transfer, accompanyingdocumentation during resident transfer from EMS andED, an assessment of handover communicationbetween NH and EMS, and documentation of resident’spersonal aides to daily living (such as eyeglasses,hearing aids, dentures);EMS: The Canadian Triage Acuity Scale (CTAS)[44,45] was developed by the Canadian Association ofCummings et al. BMC Geriatrics 2012, 12:75 Page 5 of 14http://www.biomedcentral.com/1471-2318/12/75Emergency Physicians (CAEP) and the NationalEmergency Nurses Association (NENA) and is used byEMS and EDs to prioritize patient care requirements,and to ensure that the sickest patients are seen on apriority basis when ED capacity has been exceeded dueto high admission volume or restricted access to otherservices [45]. It has been shown to be valid and reliable,especially when applied by experienced nurses andusing electronic decision support tools. Categories ofdata collected include CTAS scores, an assessment ofdocumentation received from the nursing home thatwere prepared or received for ED use, timing ofnotification that a resident requires transfer(notification and actual transfer times, arrival at ED),an assessment of handover communication betweenthe NH and EMS not captured in the documentation;ED: Time of arrival, time of placement, time of EDphysician assessment, time of consultation, time ofdisposition, investigations, diagnostic lists, reason foradmission, overall length of ED stay (sub-divided intoadmitted and discharged patients);Disposition: The location of the resident followingtransfer to the ED (inpatient, return to original NH,transfer to another NH, or death);Discharge from ED to EMS: Adequacy ofcommunication between the ED and EMS,accompanying documentation with the resident duringtransfer, timing of notification and actual transfer; and,Return to NH: medical data from ED, accompanyingdocumentation during resident transfer from EMS andED, and assessment of communication at handover.Development of the ‘Older Persons’ Transitions in CareSuccess’ (OPTICS) Tool (Outcome Measure #1)For our work in Phase 2, we required a “transition qual-ity outcome” variable to measure transition success.Using the criteria of (1) feasibility (brevity and ease ofcompletion; the instrument can be completed in 10–15minutes), and (2) modifiability (focus on concepts thatare potentially modifiable), we developed the OPTICStool to measure success of residents’ care transitions asperceived by the residents and by their family caregivers.Figure 4 OPTIC TimeLine.Cummings et al. BMC Geriatrics 2012, 12:75 Page 6 of 14http://www.biomedcentral.com/1471-2318/12/75The OPTICS Scale for Residents and the OPTICS Scalefor Family Caregivers each consists of 14 questionsrelated to the care received during the EMS portion (6items based on the six quality domains in the IOMmodel and our definition of successful transitions), theED portion (6 items) of the transition and two overallquestions. To develop the two OPTICS scales, weengaged in an iterative process that involved the gener-ation of initial items based on Phase 1 qualitative inter-view data, an assessment of face validity and feasibility,further item revision, and field testing prior to final itemgeneration and assessment. With the services of NooroOnline Research (https://nooro.com), we developed anonline program using the iPad (Apple Inc. http://www.apple.com/ca/ipad) for entry of transition tracking data.During the final two months of Phase 1, we developedthe processes for recruiting residents and their familycaregivers into the study for each provincial study site,and for approaching the resident. Our approach to re-cruitment of residents differs depending on their level ofcognition. Residents with a Cognitive Performance Scalescore of 2 or less [60] who experience a transition willbe approached by the Care Manager or designate in theNH to obtain verbal consent for a researcher tocomplete the OPTICS tool. If they agree to participate,informed written consent will be obtained by theOPTIC research staff. A family member whom the NHstaff identify as being involved in the transition willalso be approached and asked to provide consent to beinterviewed about their own perceptions regarding theresident’s transition. Residents with a Cognitive Per-formance Score [60] 3 or more will not be approachedto complete the OPTICS tool. In such cases, their fam-ily members whom the NH staff identify as beinginvolved in the transition will be approached and askedto provide their own perspectives of the resident’stransition.Protocol for phases 2 and 3Phase 2 – transition trackingDuring Phase 2, the focus of this protocol, we will pilottest all of the data collection tools and then track approxi-mately 400 transitions at the individual level using the T3and OPTICS data collection instrument described above.We will also collect administrative data at the facility/organization, department and/or care unit levels for eachof the settings in the study to allow us to analyze costs oftransitions, to determine the relationship of organizationalcontext and other characteristics such as workload tothe successfulness of transitions. Each of these datameasures and sources are described below and sum-marized in Table 1. The OPTIC Conceptual Model ofthe relationships among study concepts is presented inFigure 5.MeasuresTransition Tracking Tool (T3)Individual level data from the first 50 consecutive resi-dents experiencing a transition (911 call to EMS)across the two provinces will be assessed in a feasibilitypilot to determine if and where data can be retrieved.We will also assess the timeliness of accessing patientrecords in each study setting to retrieve data. Thepiloted and revised T3 will then be used to track tran-sitions for the one year of transition tracking. Thesample will consist of all emergency (911) transitionsfrom NHs in the Kelowna area to their ED (N=ap-proximately 200) and all NH transitions from nursinghomes enrolled in the Edmonton area to the study ED(N=approximately 200). We will recruit and havecomplete detailed case tracking for these approxi-mately 400 cases from approximately 600 availablecases (based on pre-study data) accounting for lossesto attrition, inability to obtain consent, refusal to par-ticipate and incomplete records. We will attempt to re-cruit all available cases, even those who present duringtimes when research staff are not immediately avail-able. Transitions will be identified and accessed by theresearch team within three working days of occurrenceso that detail missing from the records can be soughtfrom healthcare providers.Older Persons’ Transitions in Care Success (OPTICS) toolThe OPTICS Scale for Residents and the OPTICS Scalefor Family Caregivers to assess transition successfulnesswill be pilot tested on the first 50 transitions and thenrevised as necessary through an expedited team meeting.The revised tool will be used for the one year of transi-tion tracking along with the T3.Organizational factors (Facility Profile Forms)We will collect organizational data using a facility pro-file form for each NH, EMS, and ED. This will allow usto construct a comprehensive evaluation of currentworkload, staffing and transfer activity during theperiod of the study, to describe changes over time andto identify areas of highest priority for interventions.The sample includes facility management at all NHs,EMS and EDs. Data will be collected for the full yearof transition tracking by requesting monthly servicelevel data (e.g., ED visits, EMS calls and times, etc.)from each organization. We will also collect adminis-trative data from EMS that describes transfer activityfrom all NHs to all EDs in for the three-year studyperiod. This will allow us to compare our transitiontracking activity to the volume of all NH-ED transfersin each region for the year before and after our transi-tion tracking.Cummings et al. BMC Geriatrics 2012, 12:75 Page 7 of 14http://www.biomedcentral.com/1471-2318/12/75Table 1 Data sources and measuresVariable / Instrument Source of data Data type Purpose Unit of analysis CollectionphaseIndividual Level DataSemi Structured Interviews(Resident/family), andfocus groups (providers)Resident/family, healthcareproviders, managers/administrators in NH, EMS, EDQualitative Identify perspectives on transitions andkey indicators for initial development ofOPTICSSettings, residents, healthcareprovider groupsPhase 1Transition Tracking Tool(T3)NH, EMS, ED Mixed casespecificObtain case-related data to track processesand events in transitionIndividual Phase 2Reason for transfer, timing,communication, results oftransfer, disposition, priority,CTAS, etc.Perceptions of thetransition processHealth care providers (nurses,paramedics)Brief Survey To obtain perspectives on need for thetransition and quality of information sharingIndividual Phase 2Older Persons Transitionsin Care Success (OPTICS)Residents and their FamilyCaregiversMixed Evaluate care transitions Individual Phase 2Facility Level DataMDS-RAI 2.0 RUGS &CHESSBC: Interior Health Region Administrative To adjust for case mix by NH Facility Phase 2AB: Individual Nursing HomesDemographic Profile Form Facility and setting Managers inNH, EMS, EDSemi Structured Interviews /SurveysConstructing independent variable Facility Phase 2OPTIC Survey Data Health Care Aides in nursinghomesCAPI (computer assistedpersonal interviews)To obtain a measure of context, and workforcecharacteristics such as job satisfaction,burnout etc.Aggregated scores atUnit levelPhase 2(Organizational context,burnout, job satisfaction, etc.)Cummingsetal.BMCGeriatrics2012,12:75Page8of14http://www.biomedcentral.com/1471-2318/12/75Economic dataWe will measure direct costs at a variety of levels (healthsystem, facility, and individual transition) and developstatus quo cost per transition estimates for all NH-EDtransitions using administrative data from the health au-thorities in each of the provinces. Detailed costing datasuch as personnel time, tests, procedures, and ambu-lance costs, will be obtained from the health authorityadministrative databases and time estimates will also beobtained from the T3. We will analyze the direct systemcosts of both successful and unsuccessful transitions andreport differences. We will measure these status quocosts against our other health system outcome measureof interest - the direct cost per unsuccessful transitionavoided.Geographic dataWe will collect postal codes of the NHs and the EDs forspecific analysis of location and distance between facil-ities, on transition success. Transitions will be examinedthrough a geographic lens to better characterize the roleof places (NHs and EDs) in these events. This will cap-ture movement of individuals through the health caresystem (i.e., as they move from place to place) and pat-terns in the variables related to that movement.Purposeful examination of this aggregated data will fa-cilitate identification of strengths and gaps in transitionpatterns and contribute to hypothesis generation con-cerning attributes of successful (or not) transitions.Maps of transition patterns (and related variables includ-ing time, origin/destination attributes, transition volume,etc.) are useful visual aids to support communicationwith decision-makers and other key stakeholders. Fur-ther, ratings of transition success between institutions asmeasured by the OPTICS tool will be mapped relative tolocations and both location and transition attributes.Organizational contextAfter six months of transition tracking data have beencollected, we will select a representative sample of 4–5NHs in each province. We will identify in our samplingmatrix of high, medium and low transfer facilitiesmatched with large and small bed facilities, and public,private, not-for-profit ownership informed by the Trans-lating Research in Elder Care (TREC) study [61,62].These selected NHs will provide a total of 15 care unitsper province (average 3 units per facility), where we willcollect data to measure organizational context (discussedin detail below). We will adjust for resident acuity in aNH using Resource Utilization Groups (RUGs) andCHESSandRUGSTransition CharacteristicsTracked by SettingNH-EMS-ED-EMS-NHOrganizational FactorsGeographic FactorsOrganizational Contextual FactorsUnsuccessfulTransitionsAvoidedTransitionSuccessSafetyResident FocusedTimelinessEffectivenessEfficiencyEquitabilityCase Mix Adjustment Determinants (IndependentVariables)OutcomesResident Level Characteristics & FactorsSystem Cost of TransitionsAll transitions will be analyzed, with shadingindicating additional analyses for a subsetof included NH.OPTIC QualityIndicatorsFigure 5 OPTIC Conceptual Model.Cummings et al. BMC Geriatrics 2012, 12:75 Page 9 of 14http://www.biomedcentral.com/1471-2318/12/75Changes in Health, Endstage Disease and Symptoms andSigns (CHESS) scores.RUGS & CHESSThe Minimum Data Set-Resident Assessment Instrument(MDS-RAI 2.0) is part of an international system intendedto capture information about the health, physical, mental,and functional status of NH residents [63-71] and is rou-tinely collected by all NHs in BC and AB. We will collectRUGs and CHESS scores for the 30 care units (15 perprovince) in our sampling matrix. The scores will be usedto adjust for case mix at the NH unit level in our multi-variate analytic models (described below). The Version III(RUGs III) system has been validated in multiple settings[72-74]. RUGs III is a case mix classification system devel-oped to monitor, track, and benchmark staffing and resi-dent resource use. Data have been used to guide local andorganizational decision making in regards to resource useand allocation [72,75], which acts as a proxy for residentneed. CHESS is comprised of MDS-RAI 2.0 data and isused to identify patients at risk for serious decline inhealth or mortality [76]. CHESS has predictive validity asit predicts mortality independent of age, sex, disability,cognitive performance, and Do Not Resuscitate orders[76]. Each increment on CHESS is associated with a dis-tinct survival curve, with higher scores corresponding to areduction in probability of survival. The sample will in-clude the 15 units in the 4–5 participating NHs in eachprovince where we will measure context.Context measureHealthcare aides (HCAs) in these selected facilities willbe asked to complete the Alberta Context Tool (ACT)[49]. The ACT measures 10 contextual concepts: (1)leadership, (2) culture, (3) evaluation, (4) social capital,(5) structural and electronic resources, (6) formal interac-tions, (7) informal interactions, (8) organizational slack -staffing, (9) organizational slack - space, and (10)organizational slack – time [49], and is a validated and re-liable instrument [49,62,77,78]. We will also collect datafrom healthcare aides on: Demographics including age, gender, education, jobtraining, length of time working in their primaryfacility, and shift most frequently worked. Job Satisfaction (using a single item) Burnout (using the Maslach Burnout Inventory,Short form GS [79])The sample will include 300 HCAs (10 HCAs per careunit for 15 care units per province) using conveniencesampling on each unit. Previous studies utilizing theACT have shown that 10 surveys per unit provide astable measure of unit-level context [62,77,78]. Theinclusion criteria for healthcare aides [80] to completethe survey are: Employed by their facility for at least 3 months; Work a minimum of 6 shifts per month; Able to identify a unit where they work most of thetime.Outcome measuresThere are four outcomes of interest in this study: theprimary outcome of Resident and Family Caregiver per-ceptions of the successfulness of their transition(OPTICS described in Phase 1) and three secondary out-comes, described below.Nurse and paramedic perceptions of quality (OutcomeMeasure #2)We will use a short instrument developed for this studyto obtain the perceptions of nurses in the ED, parame-dics in EMS, and nurses in the NH after the residentreturned. These questions will be asked for each transi-tion and will address the quality of the handover infor-mation received, the quality of the interchange, and theirperception of whether the transition could have beenavoided and, if they believe that it could have been pre-vented, what could have prevented the transition.OPTICS quality indicators (Outcome Measure #3)An intermediate outcome measure is the OPTICS QualityIndicators, being developed for this study (see Figure 5).These are a series of quality indicators for each of the sixdomains of quality in the IOM model which are beingderived from the growing research and guidelines litera-ture on transitions generally [81], specific to NH-ED[27,82], and in specific settings like EDs [82,83]. For ex-ample, we know that communication of resident informa-tion between healthcare providers during handover ofresponsibility for the resident across health system sectorsis an important safety indicator [84]. We will identify fromthe literature the key indicators of communication thatact to support resident safety during transitions [85].Unsuccessful transitions avoided (Outcome #4)Through research team analysis of T3 and OPTICSdata, we will identify unsuccessful transitions thatshould not have occurred. For example, our researchteam may determine that a transition was initiatedwhen the difficulty experienced by the resident couldhave more appropriately been dealt with in the NH.AnalysesPlanned analyses and deliverables are based on theOPTIC Conceptual Model (Figure 5).Cummings et al. BMC Geriatrics 2012, 12:75 Page 10 of 14http://www.biomedcentral.com/1471-2318/12/75Psychometrics of the OPTICS toolWe will use the first 50 cases to undertake refinement ofthe OPTICS tool and will use the remaining cases to as-sess its psychometric properties (assessing internalconsistency, item-total correlations, and dimensionalityusing exploratory factor analysis). We will have sufficientstatistical power for psychometric assessment using ex-ploratory factor analytic techniques with the remainingcases. We do not anticipate that we will have sufficientdata to carry out a confirmatory factor analysis. In an it-erative fashion, we will also carefully assess feasibilityand practicality of the tool. In this phase we will alsoidentify problems in the transition process and prelimin-ary solutions to these problems. During this trackingphase, the RUGS and CHESS scores for the NHs fromMDS-RAI 2.0 custodians will be collected. The data forgeographic analysis will also be collected at this point.Modeling the factors related to transition successWe will construct models of association between con-textual, economic, geographic, and resident indicatorsand transition success, to assess the relationships identi-fied in the OPTIC model (Figure 5). We will build andanalyze final models of association, for example, regres-sion models with cluster correction for organizationalunit, to determine which factors are significant predic-tors of transition success and unsuccessful transitionsavoided. Using a random coefficient model, these types ofequations will be of the following form: Yij = (a + ß.ij) +(vj.ij + μj+ eij), where Yij is the dependent variable for ob-servation i in cluster j; a is the intercept; b is the effect ofthe covariate of .ij ; vj is the amount by which the coeffi-cient of cluster j deviates from the average b; uj is theLevel-2 random effect (clustered or group); eij is theLevel-1 random effect (individual). We will construct amore refined description of the problems and potentialsolutions following careful assessment of these models,the process data we will collect throughout, and regularteam meetings and discussions. In this way, we will inves-tigate the role of context in the frequency, timing and typeof transitions from NH to ED. Similar analytic techniquesincorporating additional variables will be performed on asub-set of cases (N= approx. 300 health care aides) to de-termine the effects of organizational context factors(ACT) on transition success when controlling for casemix (RUGS and CHESS).Economic analysesWe will consider the economic impact of patient transi-tions to and from the ED by evaluating two costing sce-narios – status quo and successful transition. Data onhealth system average costs related to transitions of NHresidents from NH via EMS to EDs and back will bederived from the administrative data. We will analyzethe costs of loss of residents’ aids to daily living both inaverage financial costs and potential consequences forthe residents’ quality of life. We will also calculate thecosts associated with unsuccessful transitions avoided.This will allow us to build a complete and accurate pic-ture of transfer activity during the period of the study, todescribe changes over time and to identify areas of high-est priority for interventions.Geographic analysesUsing a health geographic lens to map care transitions,we will also characterize the role of place in the transi-tion process. Specifically, we will map locations of wheretransfers originated from and ended at, characteristics oforigin and destination locations related to attributes oftransitions (e.g., time, OPTICS score, etc.), and varia-tions in time taken for transfers between destinations toelucidate overall patterns (e.g., from initial call to ambu-lance at origin to arrival at hospital and all noted timepoints in between) relative to those (measured) context-ual factors that explain variation in overall transfertimes.Ethical research conduct and data managementEthics approval involved three different forms of consentprocedures, depending on the sample and data source.1) For Phase 2 Transition Tracking, we received ap-proval from the ethics board to waive written consentfrom each NH resident on the basis of the following:1. It would not be reasonable to ask a NH resident whomay have significant baseline cognitive deficits toprovide consent to participate in a study if they werealready in the process of a transition.2. It would not be reasonable to ask all NH residents inthe study cities (several thousands) to consent apriori to a study in the event that they may have atransition over the course of the following year.3. Frail elderly NH residents who might potentiallybenefit from the conduct of health services researchthat could inform ways to improve the care theyreceive should not be excluded from such research.4. Not all NH residents have a close family member/caregiver who had Power of Attorney to provideconsent on their behalf.5. Data collected using the T3 tool used resident/patient care records which would subsequently bede-identified.Residents and family caregivers provided informed ver-bal consent to be interviewed in Phase 1 and for Phase 2OPTICS questions. Healthcare providers providedinformed verbal consent to be interviewed in Phase 1and for Phase 2 perception questions.Cummings et al. BMC Geriatrics 2012, 12:75 Page 11 of 14http://www.biomedcentral.com/1471-2318/12/75This study is being conducted in accordance with theTri-Council standards for research with vulnerablepopulations [86] and the Health Research Ethics Boardguidelines at the involved Universities and healthregions. All data handling adheres to data security pol-icies of the Universities and Health Research EthicsBoards concerned. Data will be managed centrally in ac-cordance with Tri-Council standards and stored in thesecure data repository at the University of Alberta’sFaculty of Nursing. Appropriate access for Universityof British Columbia investigators, Interior Health andthe Edmonton region decision-makers will be made inaccordance with study specific data management andsecurity arrangements governed by the OPTIC DataManagement Committee. In this study it is not pos-sible to anonymize the NH, ED, or the EMS teams. Wehave discussed this explicitly with all participatingorganizations.Return on investment: knowledge translation anddisseminationThe return on this investment will take two majorforms: integrated KT approaches and end-of-grantknowledge translation (KT). IKT involves regular teammeetings and other forms of disciplined interaction, aswell as joint decision-making through project manage-ment committees comprised of a balanced set of keyresearchers and decision-makers. If additional funds canbe secured, we will host a Transitions symposium toresults and implications for a wider audience ofdecision-makers and clinicians. KT will consist of peerreview publications and conference presentations for re-search audiences and, for system administrators andmanagers, reports in trade journals and in relevantmeetings and conferences.DiscussionKey to study success is operationalizing the IKT approachby using a partnership model in which the OPTIC govern-ance structure provides for team decision-makers andresearchers to participate equally in developing studygoals, design, data collection, analysis and implications offindings. As preliminary and ongoing study findings aredeveloped, their implications for practice and policy instudy settings will be discussed by the research team andshared with study site administrators and staff. The studyis designed to investigate the complexities of transitionsand to enhance the potential for successful and sustainedimprovement of these transitions.Study deliverables related to transition include defini-tions for successful and unsuccessful transitions frommultiple perspectives, descriptions of potential problemsand solutions to the management of transitions, devel-opment and testing of a feasible and practical tool tomeasure success of transitions, and diagnostics to supportareas of strategic focus and development by decision-makers regarding seniors’ transitions. Advancements inprocesses for IKT will include (i) extended new KT prac-tices between decision-makers and researchers, (ii)increased health system knowledge and awareness ofissues, (iii) trained new scientists as a result of engaging re-search trainees, and (iv) continued development of profes-sional relationships that will, result future collaborations.AbbreviationsACT: Alberta Context Tool; AHS: Alberta Health Services; CIHR-PHSI: CanadianInstitutes of Health Research, Partnerships for Health System Improvement;CPS: Cognitive Performance Score; CTAS: Canadian Triage Assessment Score;ED: Emergency Department; EMS: Emergency Medical Services;HCA: Healthcare Aides; IH: Interior Health Authority; IKT: Integratedknowledge translation; LTC: Long term Care; NH: Nursing Homes;OPTIC: Older Persons’ Transitions in Care; OPTICS: Older Persons’ Transitionsin Care Success; T3: Transition Tracking Tool.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsGGC is the nominated principal investigator for the OPTIC research program,is providing leadership and coordination for the program and is provinciallead for Alberta. RCR is a principal investigator, and provincial lead for BritishColumbia. CAE and PGN conceived of the original idea as complimentary tothe TREC (Translating Research in Elder Care) program, and workedcollaboratively with GGC and RCR to secure funding including partnershipgrants. GEC leads the Transitions Tracking Tool project (Phase 2) and is theEMS lead. BHR provides access to Emergency Department for data collectionas the Alberta ED lead. JLB and CAR led the qualitative working group(Phase 1). JL contributed a Gerontological ED perspective. LB, SA, SL and EMcontributed to detailing and operationalizing protocols for data collection.All authors read and approved the final submitted manuscript.AcknowledgementsWe are grateful for the active partnership and full contribution of theresearch team of decision-makers and researchers.Principal InvestigatorsGreta G. Cummings, Nominated Principal Applicant, University of AlbertaCarole A. Estabrooks, Principal Applicant, University of AlbertaPeter G. Norton, Principal Applicant, University of CalgaryR. Colin Reid, Principal Applicant, University of British Columbia OkanaganCo-InvestigatorsJoan Bottorff, Co-Applicant, University of British Columbia OkanaganGarnet E. Cummings, Co-Applicant, University of AlbertaNorah Keating, Co-Applicant, University of AlbertaJacques S. Lee, Co-Applicant,Sunnybrook Health Sciences CentreMeredith Lilly, Co-Applicant, University of British ColumbiaCandace Nykiforuk, Co-Applicant, University of AlbertaBelinda Parke, Co-Applicant, University of AlbertaCarole Robinson, Co-Applicant, University of British Columbia OkanaganBrian H. Rowe, Co-Applicant, University of AlbertaAdrian Wagg, Co-Applicant, University College HospitalPrincipal Decision MakersJoanne Konnert, Chief Operating Officer, Interior HealthGlenda Coleman-Miller, Vice President, University of Alberta HospitalDecision MakersCaroline Clark, Executive Director, Edmonton Zone, Alberta Health ServicesCindy Crane, Manager, Interior Health, Kelowna General HospitalMichael Ertel, Chief and Medical Director, Interior Health Kelowna GeneralHospitalKaren Latoszek, Senior Manager, Alberta Health ServicesTracy Buffam, Client Services Manager, Good Samaritan Southgate CareCenterCorinne Schalm, Vice President, Shepherd’s Care FoundationCummings et al. BMC Geriatrics 2012, 12:75 Page 12 of 14http://www.biomedcentral.com/1471-2318/12/75Cindy Regier, Director Residential Services, South OkanaganSunil Sookram, Medical Director EMS, Alberta Health ServicesAdditional MembersFaye Burch, Director Residential Services, Cottonwoods Care CentreWe also acknowledge funding from the following organizations: CanadianInstitutes of Health Research (CIHR PHE101863); Interior Health, BritishColumbia; Alberta Health Services; University of Alberta Hospital Foundation;Alberta Heritage Foundation for Medical Research (AHFMR); Michael SmithFoundation for Health Research (MSFHR); and the BC Network in AgingResearch (BCNAR). Dr. Greta Cummings holds a Population HealthInvestigator award from AHFMR; Dr Estabrooks hold a Tier I Canada ResearchChair in Knowledge Translation; Dr. Rowe holds a Tier I Canada ResearchChair in Evidence-based Emergency Medicine from CIHR.Author details1Faculty of Nursing, University of Alberta, Edmonton, AB, Canada. 2School ofHealth and Exercise Sciences, University of British Columbia’s Okanagancampus, Kelowna, BC, Canada. 3Department of Family Medicine, Faculty ofMedicine, University of Calgary, Calgary, AB, Canada. 4Department ofEmergency Medicine, Faculty of Medicine and Dentistry and School of PublicHealth, University of Alberta, Edmonton, AB, Canada. 5School of Nursing,University of British Columbia’s Okanagan campus, Kelowna, BC, Canada.6Division of Geriatric Medicine, Department of Medicine, Faculty of Medicineand Dentistry, University of Alberta, Edmonton, AB, Canada. 7Department ofEmergency Services, Sunnybrook Health Sciences Center, Toronto, ON,Canada. 8Faculty of Nursing, Edmonton Clinic Health Academy, University ofAlberta, 11405-87 Ave, Edmonton, AB T6G 0C1, Canada.Received: 17 November 2012 Accepted: 30 November 2012Published: 14 December 2012References1. 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Maslach C, Jackson SE, Leiter MP: Maslach Burnout Inventory Manual. CA:Mountain View; 1996.80. Estabrooks CA, Squires JE, Cummings GG, Teare G, Norton PG, Studyprotocol for the translating research in elder care (TREC): Building context -an organizational monitoring program in long-term care project. Impl Sci2009, 4(52):10.1186/1748-5908-4-52.81. Report on Health Information Exchange in Post-Acute and Long-Term Care.http://www.caretransitions.org/documents/Health%20Information%20Report%20-%205.0.pdf.82. Terrell KM, Hustey FM, Hwang U, Gerson LW, Wenger NS, Miller DK, onbehalf of the Society for Academic Emergency Medicine Geriatric TaskForce: Quality Indicators for Geriatric Emergency Care. Acad Emerg Med2009, 16(5):441–449.83. Schull MJ, Hatcher CM, Guttmann A, Leaver CA, Vermeulen M, Rowe BH,Anderson GM, Zwarenstein M: Development of a Consensus on Evidence-Based Quality of Care Indicators for Canadian Emergency Departments, ICESInvestigative Report. Toronto; 2010.84. Hustey FM: Care Transitions Between Nursing Homes and EmergencyDepartments: a Failure to Communicate. Ann Long-Term Care: Clin CareAging 2010, 18(4):17–19.85. Gillespie SM, Gleason LJ, Karuza J, Shah MN: Health Care Providers’Opinions on Communication Between Nursing Homes and EmergencyDepartments. J Am Med Dir Assoc 2010, 11(3):204–210.86. Canadian Institutes of Health Research, Natural Sciences and EngineeringResearch Council of Canada, Social Sciences and Humanities ResearchCouncil of Canada: Tri-Council Policy Statement: Ethical Conduct for ResearchInvolving Humans.(Vol. 0-662-40236-7). Ottawa; 2005.doi:10.1186/1471-2318-12-75Cite this article as: Cummings et al.: Older Persons’ Transitions in Care(OPTIC): a study protocol. BMC Geriatrics 2012 12:75.Cummings et al. BMC Geriatrics 2012, 12:75 Page 14 of 14http://www.biomedcentral.com/1471-2318/12/75


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