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Learn more: PMC Disclaimer | PMC Copyright Notice BMC Health Serv Res . 2026 Mar 5;26:507. doi: 10.1186/s12913-026-14269-9 Search in PMC Search in PubMed View in NLM Catalog Add to search Barriers and facilitators to data-informed care planning in long-term care in Nova Scotia, Canada: a qualitative study Nazanin Nasiri Nazanin Nasiri 1 School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS Canada Find articles by Nazanin Nasiri 1 , Michael Kalu Michael Kalu 2 School of Kinesiology and Health Sciences, York University, Toronto, ON Canada Find articles by Michael Kalu 2 , Mirella Veras Mirella Veras 3 Department of Physiotherapy, University of Manitoba, Winnipeg, MB Canada Find articles by Mirella Veras 3 , Parisa Ghanouni Parisa Ghanouni 4 School of Occupational Therapy, Dalhousie University, Halifax, NS Canada Find articles by Parisa Ghanouni 4 , John P Hirdes John P Hirdes 5 School of Public Health, University of Waterloo, Waterloo, ON Canada 6 Balsillie School of Management, Waterloo, ON Canada Find articles by John P Hirdes 5, 6 , Andrea Iaboni Andrea Iaboni 7 Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON Canada Find articles by Andrea Iaboni 7 , Steve Iduye Steve Iduye 8 Rankin School of Nursing, St. Francis Xavier University, Antigonish, NS Canada Find articles by Steve Iduye 8 , Elaine Moody Elaine Moody 9 School of Nursing, Dalhousie University, Halifax, NS Canada Find articles by Elaine Moody 9 , Kathleen Norman Kathleen Norman 10 Nova Scotia Health, Halifax, NS Canada Find articles by Kathleen Norman 10 , Sam Searle Sam Searle 11 Department of Geriatric Medicine, Dalhousie University, Halifax, NS Canada Find articles by Sam Searle 11 , Olga Theou Olga Theou 1 School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS Canada Find articles by Olga Theou 1 , Luke A Turcotte Luke A Turcotte 12 Department of Health Sciences, Brock University, St Catherines, ON Canada Find articles by Luke A Turcotte 12 , Linda Verlinden Linda Verlinden 13 Martime SPOR Support Unit Halifax, Halifax, NS Canada Find articles by Linda Verlinden 13 , Lori Weeks Lori Weeks 14 School of Health Administration, Dalhousie University, Halifax, NS Canada Find articles by Lori Weeks 14 , Caitlin McArthur Caitlin McArthur 1 School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS Canada Find articles by Caitlin McArthur 1, ✉ Author information Article notes Copyright and License information 1 School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS Canada 2 School of Kinesiology and Health Sciences, York University, Toronto, ON Canada 3 Department of Physiotherapy, University of Manitoba, Winnipeg, MB Canada 4 School of Occupational Therapy, Dalhousie University, Halifax, NS Canada 5 School of Public Health, University of Waterloo, Waterloo, ON Canada 6 Balsillie School of Management, Waterloo, ON Canada 7 Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON Canada 8 Rankin School of Nursing, St. Francis Xavier University, Antigonish, NS Canada 9 School of Nursing, Dalhousie University, Halifax, NS Canada 10 Nova Scotia Health, Halifax, NS Canada 11 Department of Geriatric Medicine, Dalhousie University, Halifax, NS Canada 12 Department of Health Sciences, Brock University, St Catherines, ON Canada 13 Martime SPOR Support Unit Halifax, Halifax, NS Canada 14 School of Health Administration, Dalhousie University, Halifax, NS Canada ✉ Corresponding author. Received 2025 Oct 17; Accepted 2026 Feb 23; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13072555 PMID: 41787446 Abstract Background Long-term care (LTC) homes in Canada provide essential care for individuals requiring ongoing support. While data-informed care planning is increasingly advocated for, its implementation remains inconsistent, limiting its potential to enhance resident-centered care. The interRAI long-term care facilities assessment (LTCF) and real-time location systems (RTLS) are two sources of routinely collected data that can inform care planning. However, how they are currently used to inform care planning and what hinders or supports their use remains unclear. We describe the current use of routinely collected data in LTC and identify barriers and facilitators to informing care planning from the perspectives of staff, residents, and family caregivers in Nova Scotia, Canada. Methods We employed Sally Thorne’s Interpretive Description qualitative design with purposeful sampling: 10 LTC residents, 14 family members, and 22 staff (12 nurses, 2 nursing assistants, 2 physiotherapy/occupational therapy assistants, plus one administrator, one recreational/music therapist, and one dietitian). Data collection occurred in two stages: initial interviews (individual or focus group) followed by care observations, with additional interviews as needed after observation. Each session, lasting for one hour, was audio recorded, transcribe verbatim for analysis. Data were analyzed using thematic analysis by multiple coders. Results Findings revealed that while interRAI LTCF and RTLS data were available, their integration into care planning was inconsistent due to outdated admission records, data interpretation challenges, communication gaps, and staff shortages. Residents and families often lacked awareness of care plans, limiting their engagement in decision-making. However, facilitators such as incorporating residents’ social histories, leveraging RTLS to track activity patterns, ensuring regular data updates, and fostering interdisciplinary collaboration improved data utilization. Enhanced training, structured implementation strategies, and tailored communication methods were identified as essential to strengthening data-informed care planning. Conclusions Although routinely collected data have the potential to enhance resident-centered care planning, systemic barriers hinder their effective use in LTC settings. Addressing these challenges through targeted interventions, improved staff training, and knowledge user engagement can optimize data-driven decision-making and improve resident outcomes. Future efforts should focus on integrating digital health tools and structured implementation frameworks to maximize the benefits of data-informed care planning in LTC homes. Clinical Trial Number Not applicable. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-026-14269-9. Keywords: Long-term care, Care planning, Real-time location services, Data Background Long-term care (LTC) homes in Canada deliver health and personal care services for individuals with medical or physical needs requiring constant nursing, personal care, and therapeutic support [ 1 , 2 ]. The population within LTC facilities is diverse, with a range of chronic conditions, making it crucial to design personalized care plans that address each resident’s health and social needs [ 3 , 4 ]. Care planning involves a comprehensive and collaborative approach between LTC residents and healthcare providers to create an individualized plan assessing the impact of residents’ conditions on their lives and determining the most effective support for their overall health and well-being [ 5 ]. Care planning includes resident assessment, and development, implementation, and evaluation of the care plan [ 5 ]. The Nursing Act, which establishes the scope of practice statements and controlled acts authorized in nursing across the Canadian province of Nova Scotia, mandates that care plans include prioritized health issues, resident goals, nursing interventions, and evaluations of resident responses within care plans [ 5 ]. However, there have been ongoing issues regarding the quality of care plans in LTC homes, where traditional standardized care plans often overlook the specific needs or preferences of residents [ 6 ]. Recently, resident-centered models have gained support, advocating for resident involvement in their own care, in partnership with families and healthcare providers [ 6 ]. The quality of care in LTC has been a longstanding concern, and the COVID-19 pandemic has intensified calls for improvement in LTC homes [ 7 ]. A review of 48 Canadian LTC reports on quality of care between 2010 and 2020 revealed that 45.8% of the reports recommended that LTC care planning be data driven [ 8 ]. However, effective methods of integrating data and resident preferences into care planning remains challenging and requires substantial behavioral shifts within the sector as new data sources are available for use. Routinely collected data, including the interRAI Long-Term Care Facilities (LTCF) instrument and location-tracking data from Real-time Location Systems (RTLS), are available to inform care planning in many LTC settings across Canada and internationally. The interRAI LTCF is a standardized comprehensive assessment tool with approximately 150 items that is widely used in Canadian provinces and internationally [ 9 ]. Mandated for use in all LTC homes in several Canadian provinces, including Nova Scotia, this comprehensive assessment is administered at admission, every three months thereafter, or with significant status changes. Trained coordinators, typically nurses, complete the interRAI LTCF through discussions and observations with residents, family members, and staff. Data are collected on health and social items such as pain, mood, functional abilities, skin integrity, social engagement, and health conditions (e.g., diagnoses, falls, fractures) and are entered into a digital health platform such as an electronic medical record (EMR). The interRAI LTCF has shown strong validity and reliability in LTC [ 9 ]. By utilizing data collected through the interRAI LTCF, clinical assessment protocols (CAP) are activated via embedded algorithms programmed within the digital platform to identify residents at risk of adverse outcomes and those with the potential for improvement [ 10 ]. For instance, the Activities of Daily Living CAP flags residents at risk for functional decline [ 10 ]. CAPs are one example of a data informed output that can be used to inform care planning by identifying at risk residents. A scoping review found that interRAI LTCF data provides a practical method to collect clinical information, assess residents, identify risks, and inform individualized care plans, improving care quality at the facility level [ 6 ]. Overall, using interRAI LTCF data has been linked to increased care plan utilization and more effective care plan [ 11 ]. Yet, studies examining the use of interRAI LTCF data to inform care planning has found inconsistent use of care plans, sometimes leading to poorer health outcomes for residents [ 12 – 14 ]. These varied results may stem from suboptimal integration of interRAI LTCF information into the care planning process, which does not adequately address the needs of knowledge users. Additionally, healthcare providers often view the collection of interRAI LTCF data as a demanding administrative task rather than a valuable resource for enhancing care planning [ 15 ]. Thus, it is not well understood how LTC homes are using interRAI LTCF data to inform care planning or barriers and facilitators to its use. RTLS are a newer technology typically involving a software application and reference points to track real-time resident location and movement through positioning data from wireless tags, such as bracelets, worn by residents [ 16 ]. RTLS data capture position relative to the reference point over time and constructs that can be derived from these include time spent in specific locations, movement patterns, gait speed, and motor agitation. n healthcare, RTLS have been used to monitor handwashing [ 17 ], prevent falls [ 18 ], track individual behavioural patterns and measures of well-being [ 17 , 19 ], promote independence [ 20 , 21 ], and collect health data [ 18 , 22 ]. Evidence supports RTLS in enhancing resident independence and physical safety and improving in-person monitoring; however, its application in care planning remains limited. A scoping review identified several barriers to RTLS adoption in LTC, including poor technical expertise, infrastructure challenges, and insufficient shared understanding in care planning [ 23 ]. This review also highlighted a need for implementation science theory to optimize outcomes [ 23 ]. Although providers and organizations express interest in incorporating RTLS into workflows to improve care quality, studies repeatedly report challenges in using RTLS to streamline clinical processes [ 22 , 24 ]. The same scoping review suggested that integrating RTLS with local work routines, policies, and procedures and considering the perspectives of knowledge users, including residents, families, and care providers, could facilitate its adoption. Understanding how data from RTLS are currently being used and what makes it easier or harder to use these data to inform care planning will help plan future interventions to improve its use. This study is the first step in a larger project that will develop a data-informed care planning improvement intervention to use routinely collected data to guide resident-centered care planning in LTC [ 25 ]. Given care planning is a behaviour performed by nursing staff in LTC homes and there is an identified change that must occur (i.e., use of data), it is prudent to use behaviour change and implementation science theory to design a future data-informed care planning improvement intervention. The Behaviour Change Wheel (Fig. 1 ) is one of many available frameworks that uses behaviour change theory to inform the understanding, selection, and specification of the target behaviour, prior to designing interventions [ 26 ]. The first step in the BCW is to define the problem in behavioural terms and select and specify the target behaviour. Here, we define the target behaviour as effectively and efficiently using interRAI LTCF and RTLS data to inform care planning. Our first objective is to understand how the target behaviour is currently performed by describing how, where, and why routinely collected data are used in current resident-centred care planning processes in LTC homes in Nova Scotia, Canada. The next step in the BCW is to identify what needs to change to achieve the target behaviour. Therefore, our second objective is to identify barriers and facilitators to using data to inform resident-centred care planning from the perspectives of staff, residents, and family caregivers. Note we will not be evaluating if data are being used effectively and efficiently, rather exploring how data are being used and barriers and facilitators to their use. Fig. 1. Open in a new tab The behaviour change wheel. Used under CC BY-NC 4.0 ( https://creativecommons.org/licenses/by-nc/4.0/)/n o modifications Methods Study design We employed Sally Thorne’s Interpretive Description (ID) qualitative design grounded in constructivism and naturalistic interpretive inquiry to co-create knowledge with staff, LTC residents, and their families to develop practical solutions for utilizing routinely collected data in LTC environments [ 27 ]. We report our findings in accordance with the Consolidated Criteria for Reporting Qualitative Research (COREQ) Checklist (see Appendix 1 ) [ 28 ]. Patient engagement Guided by the Strategy for Patient Oriented Research (SPOR), we actively involved knowledge users throughout the entire project. Two project advisory committees oversaw the initiative. The first committee included one resident, one family member, and two LTC staff members from one LTC home, and the second committee consisted of one family member and three LTC staff members from another LTC home. The project advisory committee met with the research group bi-monthly to discuss the project, including recruitment, methods, analysis, progress, dissemination strategies, and next steps. Members of the project advisory committee were also involved in participant recruitment and the dissemination of knowledge translation products (e.g., presentations, videos). We documented our engagement with knowledge users using the SPOR Patient-Oriented Level of Engagement Tool (see Appendix 2 ). Research team and reflexivity The research team comprised an interdisciplinary group of researchers and clinicians with extensive expertise in health care provision and the use of routinely collected data, such as the interRAI LTCF and RTLS LTC setting. During the study’s conceptualization, data collection, and analysis phases, the authors engaged in reflexivity, identifying their ‘Subjective I’s’—their values, beliefs, and assumptions shaped by their backgrounds as clinicians with experience in the LTC setting, familiarity with interRAI and RTLS, and methodological expertise. The senior author (CM) is a physiotherapist with experience working in LTC and an interRAI fellow (PhD, MScPT). She has extensive expertise with interRAI data from a research lens and the LTC sector from a clinical and research perspective. The first author (NN) is a research assistant with a BSc in Kinesiology, and she has contributed to multiple projects focused on enhancing quality of life and mobility for older adults in LTC. She has worked on several studies involving interRAI assessments, which informed her understanding of the data and context explored in this study. In addition, her previous research in health administration and health equity shaped her critical perspective on how care is delivered and how data can be used to support more equitable outcomes in LTC. The other research team members have expertise in interRAI assessment systems, RTLS data collection and analysis, geriatrics, physiotherapy, occupational therapy, and health administration. Their expertise and previous experience shaped the final critical review of the manuscript. A relationship was not established between the interviewers and participants prior to recruitment. Participants were informed that the research team included clinicians and researchers with experience in LTC and in the use of interRAI and RTLS data. The interviewers introduced themselves and explained the purpose of the study, which was to better understand how routinely collected data are used in care planning and to explore the barriers and facilitators to more effective, person-centered use of this data in LTC settings. Study setting and recruitment We used purposive, criterion-based, and maximum variation sampling throughout the project, both for selecting LTC homes and recruiting participants within one organization. A maximum variation purposive sampling approach helped us choose a diverse set of four LTC homes, including facilities already using interRAI LTCF and those currently implementing or transitioning to RTLS. This selection of LTC homes provided a well-rounded representation of current and emerging technology use across various geographical contexts. We aimed to recruit four homes across different LTC home sizes and within variable surrounding population areas. LTC home sizes were defined as small (1 to 29 beds), medium (30 to 99 beds), or large (100 or more beds) [ 29 ]. Surrounding population sizes were categorized based on Statistics Canada definitions: small (1,000–29,999), medium (30,000–99,999), and large (over 100,000) [ 29 ]. Individual participants were recruited from the four selected LTC homes using multiple strategies: spontaneous recruitment, snowball sampling, and advertisements. First, for spontaneous recruitment, members of the advisory committee hosted a one-hour workshop to introduce the project to LTC residents, family members, and staff. Participants interested in joining expressed interest at the end of the workshop. Second, through snowball sampling, staff (e.g., registered nurses, licensed practical nurses, home administrators, physiotherapists, and geriatricians), family caregivers, and residents attending the workshop were encouraged to share information about the project with others who might be interested. Potential participants then contacted the research team. Third, through advertisements, we emailed each LTC home a flyer containing the study information. This flyer was posted on strategic notice boards and in the LTC homes’ weekly newsletters, along with the research team’s contact information. Participants interested in taking part reached out to the research team via email or phone. Inclusion criteria LTC residents were eligible if they had resided in the selected LTC home for at least two months (to ensure they had transitioned into living in the home and had some experience with care planning), could communicate in English, and were willing to participate. We included residents with dementia or cognitive impairments, as our research team developed inclusive methods of communication, such as using writing and drawing, to support their active engagement in the research [ 30 ]. Family caregivers were eligible if they had been visiting the LTC resident for at least two months, could provide insight into the care planning needs of the resident, and were willing to participate. Staff (e.g., nurses, continuing care aides, community managers, recreation therapists, physiotherapists, occupational therapists, social workers, and physicians) were eligible if they had been working full- or part-time at the LTC home for at least six months and could communicate in English. We aimed to recruit 4 to 5 participants from each group (LTC residents, family caregivers, and staff) at each LTC home. This sample size was selected to encourage a broad range of perspectives in focus group discussions, in line with recommendations for interpretive qualitative description research [ 27 ]. Data collection Demographic information was gathered for each participant through a self-reported questionnaire including age, gender, highest level of education, employment status (e.g., full-time, part-time), number of months/years employed in LTC, job role (staff), number of months/years living in LTC (residents), resident’s relationship to family member (e.g., spouse, parent, friend), frequency of visits to resident per week/month (family members). Data collection took place over six months, divided into three stages, and involved focus group discussions (FGDs), individual interviews, and care observation sessions conducted by principal investigator and research assistants. In Stage 1, care directors and administrators were invited to participate in semi-structured individual interviews, conducted either in person, by phone, or virtually. LTC residents, family caregivers, and staff took part in separate FGDs tailored to their group and guided by a semi-structured guide (See Appendix 3 , 4 ). The initial interview or FGD aimed to explore how, where, and why routinely collected data had been used in care planning in LTC. We were specifically focused on data collected through the interRAI LTCF or RTLS in the discussions. However, participants often brought up other sources of data that were important to them (e.g., observation, conversations with family members, chart notes), thus we did not limit the conversations or subsequent analyses to the original two data sources of interest. We did not specifically assess whether data were being used effectively, rather we sought to understand what limited or helped staff, family, and residents’ effective use of data to inform care planning. In Stage 2, staff, regardless of their participation in Stage 1, were invited to take part in care planning observations to deepen our understanding of care planning processes and to identify any practical barriers or facilitators. Staff members received prior notice regarding the purpose, date, and time of the observation. Since staff cared for residents during these observations, consent was also obtained from residents or their substitute decision-makers to observe the care planning sessions. Although there was a possibility of the Hawthorne effect—where individuals altered their behavior because they were being observed or studied—we clearly communicated to staff that we were not assessing their performance. Instead, we aimed to observe and record their use of data, if any, and to identify the facilitators and barriers to incorporating data into care planning. Care planning observations were conducted by researchers and the lead investigator, each guided by an observation protocol (see Appendix 5 ) to capture the development of multiple residents’ care plans. Researchers completed field notes during and after each observation. In Stage 3, LTC residents, family members, and staff were invited to a second FGD to discuss insights from the care planning observations and to identify any challenges or enablers in using data to support care planning processes. Each FGD or interview, lasting 45 to 90 min, was conducted using semi-structured interview guides (see Appendix 6 , 7 ), which were developed from a review of the literature on using interRAI and RTLS to inform care planning [ 14 , 15 , 23 ]. All FGDs and interviews were audio-recorded and transcribed using Otter.ai, an artificial intelligence-based transcription service, and were then reviewed manually to ensure accuracy. Data analysis Our approach drew on Sally Thorne’s Interpretive Description methodology, which incorporated techniques such as open coding, categorization, and constant comparison from various qualitative research methods [ 27 ]. This approach facilitated an understanding of the behaviors surrounding the routine use (or lack thereof) of data to inform LTC residents’ care. Interview and observation data underwent inductive content analysis to allow subjective interpretation of contextual meanings in the text through systematic coding and theme identification [ 31 ]. Data from all participant groups (e.g., residents, families, and staff) were analyzed and summarized together. The analysis process involved the following steps: Data Familiarization : Two coders (researchers) immersed themselves in the data through journaling and handwritten field notes to gain a thorough understanding of the interviews and observations. Initial Coding : The two coders independently conducted line-by-line coding of interview and FGDs’ transcripts, identifying codes and patterns that answers each study objectives mentioned above. Triangulation of Codes : Both coders met and compared similarities and differences in their open codes to create categories and develop a codebook, which were applied to the remaining transcribed interview. Disagreements on themes were resolved via majority by a third coder who was a member of the study team. Preliminary findings were shared with the broader research team and the project advisory committee for input. While feedback was invited, no additional changes were made to the analysis as no further input was provided. Mapping of barriers and facilitators to the BCW The central component of the BCW outlines that individuals require the c apability, o pportunity, and m otivation to complete a desired b ehaviour (i.e., the COM-B components). There are three COM-B components, with two sub-components per each main component for a total of six sub-components. Capability is the individual’s psychological (e.g., knowledge or psychological skills) or physical (e.g., physical skill, strength, or stamina) capacity to engage in the target skill, including having the necessary skills [ 26 ]. Opportunity describes factors external to the individual that facilitate or prompt the behaviours [ 26 ]. Opportunity can be physical which is that afforded by the environment such as time, resources, locations, cues, and physical affordances, or social which is that afforded by interpersonal influences, social cues, and cultural norms [ 26 ]. In this project, the cultural and social setting under examination will be that of the LTC working environment and norms are the shared expectations and learned behaviours inherent to this setting. Motivation reflects goals, conscious decision making and the cognitive processes that direct behaviour. Motivation can be reflective (e.g., conscious plans and evaluations) or automatic (e.g., emotional reactions, desires, impulses, inhibitions, drives states, and reflex responses) and includes decision making, building habits, and emotional responses [ 26 ]. We mapped the identified barriers and facilitators onto the six COM-B components to understand how to support future behaviour change. Mapping was completed by three team members (CM, MEK, and NN) who independently identified which of the six COM-B elements best represented the main concept of the previously identified barriers and facilitators. Barriers and facilitators could map onto more than one COM-B element. The team members then met via a two-hour online meeting to discuss discrepancies in their independent mapping and come to agreement on the final mapping results. To ensure rigor during the analysis phase, several strategies were employed. Analytic memos were used to document key findings, themes, patterns, and questions that emerged from the data. An audit trail tracked methodological decisions, including those made during brainstorming sessions and care observation debriefings. Triangulation was achieved by using multiple data collection methods—such as interviews, FGDs, and observations—to enhance credibility and provide a comprehensive understanding of the data. Reflexivity was maintained throughout the process to minimize potential biases and ensure the integrity of the analysis. Member checking was incorporated by summarizing and presenting emerging themes to participants for feedback at end of the project. Participants were given the opportunity to provide corrections, clarifications, or additional thoughts either by email or through individually scheduled meetings with researchers. To enhance transferability, thick description was employed, a qualitative research approach first introduced by Ryle [ 32 ], which involved interpreting and assigning meaning to an individual’s actions and behaviors while considering the context of the situation and the underlying present and future intentions of the behavior [ 12 ]. In practice, thick description entailed documenting detailed accounts of events during interviews, FGDs, and observations—details that might not have been fully reflected in the transcripts. To achieve this, field notes were used during the interview process [ 33 , 34 ]. By employing these rigorous qualitative research practices, this study ensured reliable and meaningful findings. This study was reviewed and approved by the Research Ethics Board at Dalhousie University (REB# 2023–6570). All participants provided informed written consent prior to participation. For all LTC residents who could not provide their own informed consent (as determined by the LTC home’s internal processes), written consent was obtained from their SDM and ongoing assent to participant was established from the resident at each research interaction. Results Ten LTC residents, 14 family caregivers of the LTC residents, and 22 staff members from four LTC homes participated in the study. Table 1 provides an overview of the characteristics of participants. Staff were on average 45 years old, and most were female (90.9%) and nurses (54.5%) or continuing care assistants (9.1%). The mean age of participating residents was 78.0 years (range 57 to 96 years), most were female (60.0%), and they had been living in LTC on average 3.7 years. Family members were mostly spouses (42.9%) or children (42.9%) of residents, were on average 66.2 years old, mostly female (64.3%), and visited the residents two or more days per week (78.6%). Two of the participating LTC homes were in large population areas, one in a medium population area, and one in a small surrounding population area. Of these four homes, two were large, one was medium-sized, and one was small. All homes used the interRAI LTCF, and two homes also used RTLS. Residents, family members, and staff took part in two rounds of FGDs and interviews. In the first round, we conducted three FGDs and two interviews with residents, seven FGDs and three interviews with family members, and four FGDs and four interviews with staff. In the second round, there were no resident participants (none responded to the request), while three family members and two staff members took part in individual interviews. Table 1. Demographic characteristics of participants Characteristic Group Staff Residents Family Members Total participants 22 10 14 Mean age (years) 45.0 78.0 66.2 Age range (years) 22–62 57–96 50–82 Gender, n (%) women 20 (90.9) 6 (60.0) 9 (64.3) Highest level of education, n (%) Master’s - - 1 (7.1) Diploma or Certificate 11 (50.0) 4 (40) 5 (35.7) Bachelor’s 9 (40.9) 1 (10) 4 (28.6) High school 2 (9.1) 4 (40) 4 (28.6) Employment status, n (%) Full-time 21 (95.5) Part-time 1 (4.5) Mean years employed in LTC, years 13.7 Job roles, n (%) Nurses 12 (54.5) CCA 2 (9.1) PTA/OTA 2 (9.1) Administrator 1 (4.5) Recreation therapist 1 (4.5) Music therapist 1 (4.5) Dietitian 1 (4.5) Others 2 (9.1) Mean length of stay in LTC, years 3.7 Resident’s relationship to family member, n (%) Spouse 6 (42.9) Parent 6 (42.9) Sibling 2 (14.2) Frequency of visits 2 or more days per week 11 (78.6) 1 day per week or less 3 (21.4) Open in a new tab How, where, and why data inform care planning Routinely collected data informed both initial and ongoing care planning. During the first 24 h following admission, an admission nurse develops preliminary care plans (See Fig. 2 ). These are based on pre-admission interviews, family input, and paper assessments from the resident’s previous care setting. Fourteen days after the resident’s admission, the interdisciplinary team completes the initial comprehensive care plan. In doing so, they draw on data from the initial LTCF assessment (including a 72-hour look-back period with triggered CAPs and outcome scales), along with staff observations and input from both the resident and their family. Some items of the LTCF are completed by point of care staff (continuing care aides) on paper tracking charts for the 72-hour look-back period, while other data are collected by the licensed practical nurse responsible for the unit. An LTCF coordinator gathers all the information from both sources, and enters it into the EMR, ensuring that it is accurate and complete. Six weeks after admission, the interdisciplinary team conducts the first care conference. Information sources at this stage includes the LTCF assessment, RTLS data where applicable, input from the interdisciplinary team, and feedback from the resident and their family. The RTLS data are not reported for each resident, rather for specific questions brought forward by the team. For example, if a family member had concerns that a resident was wandering into the resident’s room frequently, data from the RTLS about visitor residents would be included at the care conference. Following this initial conference, these meetings take place annually. Ninety-two days after admission and every subsequent 92 days after that, the interdisciplinary team completes an updated comprehensive care plan (See Fig. 2 ). This plan is informed by the LTCF assessment (including a 72-hour look-back period), staff observations, family and resident input, and RTLS data where available and relevant. For example, RTLS data might reveal that a resident spends most of their time in their room with limited movement throughout the facility, prompting the team to incorporate strategies into the care plan to increase social interaction and encourage participation in communal activities. Updates to the care plan were also implemented at any time—daily, weekly, or monthly—as needed, or in response to any significant changes in the resident’s condition. Digital platforms, such as EMRs, played an important role in how data were used to inform care planning. The interRAI LTCF individual items and associated outputs (e.g., outcome scales, CAPs) were housed in the EMR which staff accessed through laptops. The RTLS data resided on a separate digital application which staff accessed via smartphones. The two digital platforms did not interface. Fig. 2. Open in a new tab How, where, and why routinely collected data are used in care planning Barriers and facilitators to using data to inform care planning Figure 3 summarizes the themes describing barriers and facilitators to using data to inform care planning which were grouped into the phases of data management (collection, analysis, reporting) corresponding with clinical practice tasks associated with data (assessment, interpretation, communication). These three themes were situated within two additional themes of awareness of data and the LTC context. Fig. 3. Open in a new tab Barriers and facilitators to using data to guide care planning LTCF=Long-Term Care Facilities Assessment; RTLS=Real Time Location Systems; LTC=Long-Term Care Data collection (assessment) The first theme focused on how data are collected, which corresponds to the assessment phase in clinical practice. This theme mapped onto the COM-B components of social and physical opportunity, psychological capability, and reflective motivation. One subtheme indicated outdated admission packages where crucial patient details, such as medication lists, were missing, creating gaps in essential information. Social and physical opportunity were barriers here as staff could not use data because factors external to them limited its use. Indeed, one staff member reported: We’re definitely missing information. So, like, when we get a package for a new admission, it comes from continuing care and placement… we have standard kind of assessments that come with that package. A lot of the times I feel like we’re missing information that might be beneficial — that doesn’t come up until later. For example, if an issue arises with a resident, then a family member will say, ‘Oh, well, that was something that was addressed by [another] aspect of the healthcare team prior,’ but it was never included in our admission package. So I find there are times that there’s information that could have been included that isn’t — that would really help and benefit us with planning for that resident’s care. Additionally, there were instances of misinterpretation or misuse of coding procedures within the LTCF, leading to inconsistencies in the data collected or poor use of the data because it is not understandable. One staff member explained: “ And then we get one that’s all letters and numbers , which I try to avoid. It’s confusing , because in each section it’s a different number or letter as you go through it.” This mapped onto the psychological capability component of the COM-B where the barrier was the knowledge and skills of staff to interpret and use the data. It also mapped onto social opportunity because the data were not presented in the digital platform in a way that was meaningful and useful to staff, thus limiting their ability to use it for care planning. Incorporating each resident’s social history into their care plan and leveraging RTLS were highlighted as key facilitators. For example, care teams created more personalized, resident-centered plans by using RTLS to track elements such as residents’ sleep patterns, activity participation, room visitors, and staff locations. For example, a family member described how RTLS tracking resident location was a facilitator to using the data on a day-to-day basis: “And [residents] wear [RTLS]. So when you come in and you can’t find somebody , you can go to the front desk and say , ‘Can you look and see where so-and-so is?” Additionally, granting residents greater autonomy in making decisions about their care plans encouraged their active involvement and acknowledged their preferences. Here, social and physical opportunity were facilitators for using data to inform care planning because factors external to the individual were leveraged through the environment (i.e., RTLS data were available) and interpersonal influences (i.e., staff incorporated residents’ views into care plans). A family member explained how identifying the resident’s social history was an important component of data collection when they first moved into the LTC home: “And coming in here , there was a questionnaire that we filled out—even about her likes and dislikes , and what she was interested in and things like that. So it kind of found some common ground for them to interact with her , which I found really good.” Further, staff consciously planned to involve residents in care planning which represents the reflective motivation component of the COM-B. Indeed, one resident expressed: “We have a choice. I find we have. I do have a choice if I want to do something or I don’t want to do it.” Data analysis (interpretation) In the second theme, data analysis (interpretation), barriers included the discontinuation of previously helpful “cheat sheets” that continuing care assistants once relied on to guide care planning. Cheat sheets that summarized the care plan data on one page were previously generated and placed in the residents’ rooms where staff could easily access them to inform daily care. Without these practical tools, staff, especially those working directly with residents, struggled to interpret data effectively. One staff member explained: “So that’s what we liked — we used to have a cheat sheet with the actual computer care plan for continuing care aides. It was on paper , and we did our own , like… if they’re on a toileting schedule , what kind of path they used , what kind of product , what their mobility was — everything. And then at the end , we had care tips , like , you know , someone likes raisin bread toast before they go to bed and stuff like that. Those used to be great too , because they could look at that and know. But we don’t do those anymore either.” Here, social opportunity was the barrier as the cultural norm of having a cheat sheet summarizing data for point of care staff was removed limiting their ability to incorporate data into their daily tasks. Another challenge was that LTCF result reports were not consistently communicated to staff, leaving frontline workers without the insights they needed. Physical and social opportunity were barriers here where the physical environment and social norms of not sharing the LTCF data limited the ability of staff to incorporate it into their work. A staff member identified that: “I think they need to explain also to the staff , what was the result of this 72 hour [LTCF]?” Moreover, data analysis suffered during staff shift changes, when important information could be inadvertently overlooked or omitted: “So I know that when there’s a shift change , there’s a sort of rushed meeting because the people going off shift want to go home… and things just get missed , or ignored completely , or whatever.” This mapped onto social and physical opportunity because the busy LTC environment and social norms of shift change limited the ability to use data, psychological capability because in some cases data may be overlooked or omitted, and reflective motivation because staff’s focus may be on other matters. No facilitators were reported or observed within this theme. Data reporting (communication) The third theme, data reporting (communication), highlighted recurring communication gaps among staff members, particularly between point of care staff and LTCF care coordinators. These breakdowns in communication disrupted the seamless exchange of information. A staff member described a scenario where continuing care aides provide direct resident care were not informed of changes in mobility status: “And then they are emailing the nurses about what needs to be updated in the care plan , like if there’s any change with the ADLs , we have to update that , right? The nurses know it , but the continuing care aides don’t — they have to be informed too.” The barrier here was in social opportunity, where the social norms of the sector not sharing information with point of care staff limited the exchange of data to inform care planning. Additionally, how information was shared during care conferences could limit the effectiveness of communication. A staff member described some care conferences ran well but it depended on who was leading the conversation: “Depending on who’s leading those meetings , there’s more discussion rather than just information sharing — which , you know , I would hope would be the goal. It’s more about having a conversation than just presenting updates , but we’re working on that.” This mapped onto the COM-B components of psychological capability, social opportunity, and automatic motivation because it depended on the knowledge, skills, and views of staff towards care conferences but also the social norms of how care conferences are often organized in LTC. Family members valued receiving LTCF updates every three months. No facilitators were reported or observed within this theme, however several suggestions for improvement were made including more timely and consistent access to updated care plans and LTCF results for family members and residents, tools that automatically interpret LTCF data, a single, consistent point of contact for follow-up inquiries, an online centralized platform to track their loved one’s health status and care plan, as well as summarized reports on the care plan and key information. Families preferred care conferences that focused on specific concerns rather than solely providing broad updates. Their preferences for the frequency of these meetings varied—some felt that annual care conferences were sufficient, while others favored more frequent sessions. Families also recommended diverse communication options, including email, video conferencing (e.g. Zoom), and in-person meetings, to accommodate varying needs. Tailoring both communication methods and the depth of reported information (e.g., less detailed LTCF results for those not interested) would help ensure more meaningful, effective, and personalized exchanges. Awareness of data and care plan limits using data The fourth theme, awareness of data and care plan limits using data , highlighted that many residents and their families were often unaware that care plans even existed, let alone where they were located or how to access data collected. One resident expressed: “I have no idea where my care plan is.” Because of this lack of awareness, residents and families were less engaged in the care process and were unsure about what information family members had the right to see or discuss. Indeed, a family member reported: “I didn’t know our rights as a family. What we are entitled to know and what we are not.” This concept mapped onto psychological capability as it could be limited knowledge of residents and family members about data and care plans, social and physical opportunity because the data are not made available to residents and family members in the physical or social environment of LTC, and reflective motivation because there is no conscious plan for how the data could be shared with residents and family members. Further, this theme affected the previous three themes: limited awareness of data and the care plan limited data collection, analysis, and reporting. In contrast to resident and family member’s limited awareness of care plans, most staff members’ familiarity with both interRAI LTCF and RTLS served as a facilitator. For example, one staff member reported: “Most of the information we use to develop the care plan comes from the LTCF assessment.” Here the facilitator was psychological capability where staff had the knowledge that the data existed. Additionally, ensuring that families or SDMs formally acknowledge the care plans (e.g., by signing off on them) created a greater sense of shared responsibility and transparent understanding of the care planning process. A family member shared: “We were there for the care conference. It probably lasted around two hours. There were some medical details we couldn’t really change or give input on , but we were still shown everything on the medical sheets. They gave us the paperwork to read through , page by page , and we had to sign off on it.” Social opportunity was the COM-B component this facilitator mapped onto as the social norm of having families formally acknowledge the care plan made it easier for data to inform care planning. LTC context influences using data Finally, the fifth theme, ltc context influences using data , identified systemic issues like inconsistent staffing and workforce shortages in LTC homes, which directly affected the quality and consistency of data use. Staff reported: “But then , you know , in healthcare , we know right now staffing and things like that—getting that time to sit and have an actual conversation is sometimes hard , especially in long-term care where we’re not staffed the best.” This theme mapped onto the COM-B component of physical opportunity where factors external to the individual such as resources were the barrier to data informing care planning. Like the previous theme, the LTC context influenced using data collection, analysis, reporting, awareness. Despite these challenges, several facilitators were identified that could improve the use of data in LTC care planning. Smaller LTC homes noted several advantages over their larger counterparts. They reported that more effective interdisciplinary teamwork, simpler observation processes, and more consistent staffing made it easier to use data effectively in care planning: “We’re a small facility and our staff — like , everybody knows each other , and everybody knows all the residents. So , although we’re divided into three units , because we’re such a small facility , you get to know everyone. I feel like that’s great because everybody is kind of involved in care.” Here, the physical opportunity afforded by a smaller home was the facilitator. Training emerged as an important recommendation, whether it involved education on the LTCF system itself, new technologies, or additional resources that enhance staff confidence and competence in utilizing data to guide care planning. Discussion Our findings show that while routinely collected data, such as interRAI LTCF assessments and RTLS information, are increasingly available in LTC settings, using these data to guide personalized care planning remains a complex undertaking. LTC homes currently integrate data at multiple points: within the first 24 h of admission, during the 14-day comprehensive plan, at the six-week care conference, and at the 92-day updated care plan. Additional data sources—such as pre-admission interviews, paper assessments from the resident’s previous care setting, staff observations, and input from both the interdisciplinary team and the resident and their family—further inform care plans. The COM-B components that were often barriers or facilitators to using data to inform care planning were social and physical opportunity, psychological capability, and reflective motivation. Indeed, the social and physical opportunities within the LTC context often limited use of data through limited resources and social norms that did not support data use. The knowledge and skills of staff, residents, and family members and their conscious plans relative to data use also limited its integration into care planning. Limited knowledge and skills about data use is likely related to the limited social and physical opportunities for using data within LTC. Improving opportunities for data to be used would improve knowledge and skills about data use. The BCW allows for a systematic examination of why a behaviour may not be occurring but does indicate the amount that each component may be contributing. Future work could examine the relative contribution of each component to data use for care planning in LTC. Digital systems such as EMRs provide the physical opportunity and support the social opportunity to use data to inform care planning. In our study, challenges during data collection such as errors and inconsistencies in LTCF coding procedures within the EMR were barriers. Further, the digital systems that collected the LTCF and the RTLS data did not interface so data could not be combined or exchanged. Similar challenges have been reported in other studies, where fragmented digital systems prevent seamless exchange of up-to-date medication information across care settings, compromising both patient safety and data quality [ 35 ]. Digital systems must be optimized to support data informed care planning. For example, digital systems must support interoperability where software can exchange and use information across multiple assessment and data types. Further, interfaces must be user friendly, easy to navigate, and in line with the flow of clinical practice (e.g., follow the same order as clinical practice: assessment, development, implementation, evaluation) to support point of care staff’s use. Communication gaps among interdisciplinary team members, limited resident and family awareness of care plans, staffing shortages, and inconsistent data utilization limit the social opportunity to share and learn about data to inform care planning. Similar issues of ineffective communication within teams and workforce shortages have been reported to hinder care planning and team collaboration in LTC settings [ 36 , 37 ]. These findings align with prior research emphasizing the importance of regular, person-centered communication, especially during care transitions and end-of-life stages and highlight the value of tailoring communication methods to meet the individual needs and preferences of families and residents [ 40 ]. The presence of a single, consistent point of contact for follow-ups and a platform for centralized access to health and care plan data can foster trust, transparency, and collaboration. Other studies support these observations, showing that structured communication methods, such as scheduled meetings, educational materials, and takeaway resources, significantly improve staff-family relationships and promote person-centered care [ 41 ]. However, these studies also acknowledge barriers to effective implementation, including time constraints, misunderstandings, and challenges related to technology use [ 41 ]. The COVID-19 pandemic has also exacerbated staffing shortages in LTC homes, placing additional pressure on remaining staff and affecting the quality of care and limiting the physical and social opportunities to use data to inform care planning [ 38 ]. In smaller LTC homes, where communication and interdisciplinary teamwork appear more fluid and staffing more stable, the integration of data into care planning seems more achievable. Chronic under-resourcing in LTC settings significantly limits interRAI LTCF coordinators’ ability to conduct broader comparative analyses, ultimately restricting their capacity to fully leverage data for quality improvement [ 39 ]. These systemic challenges—such as persistent staffing shortages and inadequate resource allocation—must be addressed to ensure LTCF data are effectively utilized to drive meaningful improvements in resident care. Our study revealed that psychological capability related to limited knowledge and skills for using and interpreting data was a barrier to its use in care planning. Challenges related to interpreting and applying interRAI LTCF data for quality improvement, often due to limited training and implementation support, have been reported by LTCF coordinators [ 39 ]. Education and training about how to interpret and use data tailored to residents, family members, and staff could be a way to improve data use in LTC. Our findings highlight that simply having more data does not automatically lead to improved decision-making. Instead, they emphasize the need for structured implementation strategies, continuous education, and a culture shift toward data-informed care. This aligns with research showing that targeted educational interventions significantly improved interRAI LTCF coordinators’ ability to interpret and apply data for quality improvement [ 39 ]. Additionally, addressing persistent staffing shortages and inadequate resource allocation is crucial to ensuring that data are effectively utilized to enhance resident care [ 39 ]. This project is timely given the growing emphasis on data-informed decision-making and the expanding use of digital health tools in LTC, including artificial intelligence for data generation and reporting [ 23 , 42 – 44 ]. Understanding how routinely collected data are currently utilized and identifying barriers and facilitators to its effective use are crucial steps toward integrating data into care planning processes. This study underscores the potential shift from viewing routinely collected data as an administrative task to recognizing it as a valuable resource for improving continuity, personalization, and quality of care. By placing residents and families at the center of these efforts, our findings can help guide future strategies to embed data-driven approaches into LTC care planning. Our next step will be linking the identified barriers and facilitators to potential behaviour change interventions to support selection of reasonable intervention components through a systematic analysis of whether they are affordable, practicable, effective, acceptable, safe, and equitable [ 26 ]. The methods and results of these subsequent steps and a thorough description of the developed intervention will be reported in a separate manuscript. Limitations We acknowledge several challenges in this research. Recruiting and maintaining ongoing consent or assent among LTC residents with dementia presented unique challenges [ 30 ]. These challenges were due to cognitive impairment and fluctuating capacity, which made it difficult to ensure consistent understanding and willingness to participate. Moreover, real and perceived communication barriers made it difficult to involve LTC residents with dementia as patient partners or study participants. Ethical considerations were central to this process, including the need to assess capacity continuously, monitor for signs of discomfort, and respect both verbal and non-verbal expressions of assent or dissent. Our team had prior experience in inclusive qualitative research and actively refined strategies to involve residents with cognitive impairments [ 33 ]. These approaches helped ensure that all voices were heard, particularly those who were traditionally underrepresented in research. Another limitation of this study is the transferability of our findings beyond the four recruited LTC homes that are owned by the same operator in Nova Scotia. While our results may not capture every nuance of diverse LTC environments, we aimed to provide adaptable insights that could inform care planning across various contexts (e.g., home and surrounding population size). The province of Nova Scotia has recently mandated provincial interRAI LTCF usage, and our findings offers guidance to those integrating these assessments into routine practice. Similarly, the insights gained regarding RTLS could guide LTC homes interested in adopting this technology and incorporating it into their care planning processes. A key strength of our project was our commitment to ongoing knowledge user engagement. By involving a project advisory committee of residents, family members, and staff, we ensured that the barriers and facilitators we identified for care planning were grounded in real-world experiences. This dedication to knowledge translation also extended to our dissemination strategies, where we produced accessible lay summaries and infographics tailored to our knowledge user groups. This ensured that our outputs were both meaningful and understandable to those directly benefiting from data-informed care planning, including the LTC residents, family members, and staff. Conclusions This study describes how routinely collected data are currently used to inform care planning within LTC homes while also revealing the challenges that hinder its effective use. Addressing these barriers can lead to more efficient data collection practices, ultimately fostering proactive, holistic, and resident-centered care planning. By refining how data are integrated into decision-making, LTC homes can enhance the quality of care, improve resident outcomes, and promote a more responsive and personalized care environment across Canada. The following step will be to develop an intervention to improve data-informed care planning in LTC by linking the barriers and facilitators to intervention functions using the BCW. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (40.1KB, docx) Acknowledgements We thank the residents, family members, and staff who generously shared their time and experiences with us, including our Advisory Council members. We also thank Shannex Inc. for their support with recruitment of homes and participants. Abbreviations FGD Focus group discussions LTC Long-term care LTCF Long-term care facilities assessment RTLS Real time location systems SDM Substitute decision maker Author contributions MK and CM conceptualized and designed the study. NN, MK, MV conducted the data analysis. All authors contributed to drafting the manuscript and/or critically revised the manuscript. All authors approved the final manuscript. Funding This work is funded by a Project Grant from the Canadian Institutes of Health Research. Data availability Contact the corresponding author to discuss data availability. Declarations Ethics approval and consent to participate The study adhered to the Declaration of Helsinki and received approval from the Research Ethics Board at Dalhousie University (2023–6570). The study’s aims, risks, benefits of participation, confidentiality, anonymity, and the right to withdraw from the study were explained to all participants. Only those who provided written and ongoing oral informed consent were included in the study. For LTC residents with moderate or severe dementia, we obtained ongoing consent from their substitute decision maker and assent from the resident. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. When a Nursing Home Is Home. How Do Canadian Nursing Homes Measure up on Quality? [Internet]. 2013 [cited 2022 Feb 13]. 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