Virtual rehabilitation for patients with osteoporosis or other musculoskeletal disorders: a systematic review.

This study aims to identify effective ways to design virtual rehabilitation to obtain physical improvement (e.g. balance and gait) and support engagement (i.e. motivation) for people with osteoporosis or other musculoskeletal disorders. Osteoporosis is a systemic skeletal disorder and is among the most prevalent diseases globally, affecting 0.5 billion adults. Despite the fact that the number of people with osteoporosis is similar to, or greater than those diagnosed with cardiovascular disease and dementia, osteoporosis does not receive the same recognition. Worldwide, osteoporosis causes 8.9 million fractures annually; it is associated with substantial pain, suffering, disability and increased mortality. The importance of physical therapy as a rehabilitation strategy to avoid osteoporosis fracture cannot be over-emphasised. However, the main rehabilitation challenges relate to engagement and participation. The use of virtual rehabilitation to address such challenges in the delivery of physical improvement is gaining in popularity. As there currently is a paucity of literature applying virtual rehabilitation to patients with osteoporosis, the authors broadened the search parameters to include articles relating to the virtual rehabilitation of other skeletal disorders (e.g. Ankylosing spondylitis, spinal cord injury, motor rehabilitation, etc.). This systematic review initially identified 130 titles, from which 23 articles (involving 539 participants) met all eligibility and selection criteria. Four groups of devices supporting virtual rehabilitation were identified: a head-mounted display, a balance board, a camera and more specific devices. Each device supported physical improvement (i.e. balance, muscle strength and gait) post-training. This review has shown that: (a) each device allowed improvement with different degrees of immersion, (b) the technology choice is dependent on the care need and (c) virtual rehabilitation can be equivalent to and enhance conventional therapy and potentially increase the patient's engagement with physical therapy.

Vertebral Fractures in Ireland: A Sub-analysis of the DXA HIP Project.

Osteoporosis is an important global health problem resulting in fragility fractures. The vertebrae are the commonest site of fracture resulting in extreme illness burden, and having the highest associated mortality. International studies show that vertebral fractures (VF) increase in prevalence with age, similarly in men and women, but differ across different regions of the world. Ireland has one of the highest rates of hip fracture in the world but data on vertebral fractures are limited. In this study we examined the prevalence of VF and associated major risk factors, using a sample of subjects who underwent vertebral fracture assessment (VFA) performed on 2 dual-energy X-ray absorptiometry (DXA) machines. A total of 1296 subjects aged 40 years and older had a valid VFA report and DXA information available, including 254 men and 1042 women. Subjects had a mean age of 70 years, 805 (62%) had prior fractures, mean spine T-score was - 1.4 and mean total hip T-scores was - 1.2, while mean FRAX scores were 15.4% and 4.8% for major osteoporotic fracture and hip fracture, respectively. Although 95 (7%) had a known VF prior to scanning, 283 (22%) patients had at least 1 VF on their scan: 161 had 1, 61 had 2, and 61 had 3 or more. The prevalence of VF increased with age from 11.5% in those aged 40-49 years to > 33% among those aged ≥ 80 years. Both men and women with VF had significantly lower BMD at each measured site, and significantly higher FRAX scores, P < 0.01. These data suggest VF are common in high risk populations, particularly older men and women with low BMD, previous fractures, and at high risk of fracture. Urgent attention is needed to examine effective ways to identify those at risk and to reduce the burden of VF.

Machine Learning Can Improve Clinical Detection of Low BMD: The DXA-HIP Study.

BACKGROUND: Identification of those at high risk before a fracture occurs is an essential part of osteoporosis management. This topic remains a significant challenge for researchers in the field, and clinicians worldwide. Although many algorithms have been developed to either identify those with a diagnosis of osteoporosis or predict their risk of fracture, concern remains regarding their accuracy and application. Scientific advances including machine learning methods are rapidly gaining appreciation as alternative techniques to develop or enhance risk assessment and current practice. Recent evidence suggests that these methods could play an important role in the assessment of osteoporosis and fracture risk. METHODS: Data used for this study included Dual-energy X-ray Absorptiometry (DXA) bone mineral density and T-scores, and multiple clinical variables drawn from a convenience cohort of adult patients scanned on one of 4 DXA machines across three hospitals in the West of Ireland between January 2000 and November 2018 (the DXA-Heath Informatics Prediction Cohort). The dataset was cleaned, validated and anonymized, and then split into an exploratory group (80%) and a development group (20%) using the stratified sampling method. We first established the validity of a simple tool, the Osteoporosis Self-assessment Tool Index (OSTi) to identify those classified as osteoporotic by the modified International Society for Clinical Densitometry DXA criteria. We then compared these results to seven machine learning techniques (MLTs): CatBoost, eXtreme Gradient Boosting, Neural network, Bagged flexible discriminant analysis, Random forest, Logistic regression and Support vector machine to enhance the discrimination of those classified as osteoporotic or not. The performance of each prediction model was measured by calculating the area under the curve (AUC) with 95% confidence interval (CI), and was compared against the OSTi. RESULTS: A cohort of 13,577 adults aged ≥40 yr at the age of their first scan was identified including 11,594 women and 1983 men. 2102 (18.13%) females and 356 (17.95%) males were identified with osteoporosis based on their lowest T-score. The OSTi performed well in our cohort in both men (AUC 0.723, 95% CI 0.659-0.788) and women (AUC 0.810, 95% CI 0.787-0.833). Four MLTs improved discrimination in both men and women, though the incremental benefit was small. eXtreme Gradient Boosting showed the most promising results: +4.5% (AUC 0.768, 95% CI 0.706-0.829) for men and +2.3% (AUC 0.833, 95% CI 0.812-0.853) for women. Similarly MLTs outperformed OSTi in sensitivity analyses-which excluded those subjects taking osteoporosis medications-though the absolute improvements differed. CONCLUSION: The OSTi retains an important role in identifying older men and women most likely to have osteoporosis by bone mineral density classification. MLTs could improve DXA detection of osteoporosis classification in older men and women. Further exploration of MLTs is warranted in other populations, and with additional data.

Utility of Osteoporosis Self-Assessment Tool as a Screening Tool for Osteoporosis in Irish Men and Women: Results of the DXA-HIP Project.

Many algorithms have been developed and publicised over the past 2 decades for identifying those most likely to have osteoporosis or low BMD, or at increased risk of fragility fracture. The Osteoporosis Self-assessment Tool index (OSTi) is one of the oldest, simplest, and widely used for identifying men and women with low BMD or osteoporosis. OSTi has been validated in many cohorts worldwide but large studies with robust analyses evaluating this or other algorithms in adult populations residing in the Republic of Ireland are lacking, where waiting times for public DXA facilities are long. In this study we evaluated the validity of OSTi in men and women drawn from a sampling frame of more than 36,000 patients scanned at one of 3 centres in the West of Ireland. 18,670 men and women aged 40 years and older had a baseline scan of the lumbar spine femoral neck and total hip available for analysis. 15,964 (86%) were female, 5,343 (29%) had no major clinical risk factors other than age, while 5,093 (27%) had a prior fracture. Approximately 2/3 had a T-score ≤-1.0 at one or more skeletal sites and 1/3 had a T-score ≤-1.0 at all 3 skeletal sites, while 1 in 5 had a DXA T-score ≤-2.5 at one or more skeletal sites and 5% had a T-score ≤-2.5 at all 3 sites. OSTi generally performed well in our population with area under the curve (AUC) values ranging from 0.581 to 0.881 in men and 0.701 to 0.911 in women. The performance of OSTi appeared robust across multiple sub-group analyses. AUC values were greater for women, proximal femur sites, those without prior fractures and those not taking osteoporosis medication. Optimal OSTi cut-points were '2' for men and '0' for women in our study population. OSTi is a simple and effective tool to aid identification of Irish men and women with low BMD or osteoporosis. Use of OSTi could improve the effectiveness of DXA screening programmes for older adults in Ireland.

Social connectedness and the role of virtual reality: experiences and perceptions of people living with dementia and their caregivers.

PURPOSE: People living with dementia are often at increased risk of becoming socially disconnected due to dementia-related challenges. In recent years, digital technology has been designed to help address the social health of people living with dementia and provide opportunities to promote or maintain their social connectedness. This paper presents the findings from phase two of a participatory action research project, which explored people living with dementia and their caregiver's experiences and perceptions of social connectedness and the potential role of Virtual Reality (VR) in promoting or maintaining same. MATERIALS AND METHODS: People living with dementia (n = 8) and their informal caregivers (n = 8) participated in an individual, 1:1 online interview. Data analysis was guided by reflexive thematic analysis. RESULTS: The findings presented four themes: social connectedness: lived experiences and insights, facilitating social connectedness, barriers to social connectedness and the potential of multi-user VR for social connectedness. People living with dementia experienced a range of personal, community and societal connectedness. Facilitators of social connectedness included supportive, non-judgemental, and reciprocal relationships, technology adoption, and personal and contextual facilitators. Dementia-related difficulties and periods of disruption or change were considered barriers to social connectedness. Multi-user VR was perceived as useful for promoting and maintaining social connectedness. CONCLUSIONS: The perceived usefulness of multi-user VR for social connectedness indicates its potential for use with this population. Understanding the lived experiences, barriers, and facilitators of social connectedness will assist researchers and the human-computer interaction community to inform the design of future multi-user VR for social connectedness outcomes with people living with dementia and their caregivers.

People living with dementia and their caregivers consider social connectedness a vital aspect of living well with dementia.People living with dementia experience social connectedness across personal, community and societal domains.Supportive, non-judgemental or reciprocal relationships, fostering technology, and personal and contextual factors facilitate social connectedness for people living with dementia.Dementia-related barriers and periods of disruption and change can negatively impact the social connectedness of people living with dementia.People living with dementia and their caregivers consider multi-user virtual reality a promising technology to promote and maintain their social connectedness.

Modelling future bone mineral density: Simplicity or complexity?

BACKGROUND: Osteoporotic fractures are a major global public health issue, leading to patient suffering and death, and considerable healthcare costs. Bone mineral density (BMD) measurement is important to identify those with osteoporosis and assess their risk of fracture. Both the absolute BMD and the change in BMD over time contribute to fracture risk. Predicting future fracture in individual patients is challenging and impacts clinical decisions such as when to intervene or repeat BMD measurement. Although the importance of BMD change is recognised, an effective way to incorporate this marginal effect into clinical algorithms is lacking. METHODS: We compared two methods using longitudinal DXA data generated from subjects with two or more hip DXA scans on the same machine between 2000 and 2018. A simpler statistical method (ZBM) was used to predict an individual's future BMD based on the mean BMD and the standard deviation of the reference group and their BMD measured in the latest scan. A more complex deep learning (DL)-based method was developed to cope with multidimensional longitudinal data, variables extracted from patients' historical DXA scan(s), as well as features drawn from the ZBM method. Sensitivity analyses of several subgroups was conducted to evaluate the performance of the derived models. RESULTS: 2948 white adults aged 40-90 years met our study inclusion: 2652 (90 %) females and 296 (10 %) males. Our DL-based models performed significantly better than the ZBM models in women, particularly our Hybrid-DL model. In contrast, the ZBM-based models performed as well or better than DL-based models in men. CONCLUSIONS: Deep learning-based and statistical models have potential to forecast future BMD using longitudinal clinical data. These methods have the potential to augment clinical decisions regarding when to repeat BMD testing in the assessment of osteoporosis.

Ireland DXA-FRAX may differ significantly and substantially to Web-FRAX.

Appropriate use of FRAX reduces the number of people requiring DXA scans, while contemporaneously determining those most at risk. We compared the results of FRAX with and without inclusion of BMD. It suggests clinicians to carefully consider the importance of BMD inclusion in fracture risk estimation or interpretation in individual patients. PURPOSE: FRAX is a widely accepted tool to estimate the 10-year risk of hip and major osteoporotic fracture in adults. Prior calibration studies suggest this works similarly with or without the inclusion of bone mineral density (BMD). The purpose of the study is to compare within-subject differences between FRAX estimations derived using DXA and Web software with and without the inclusion of BMD. METHOD: A convenience cohort was used for this cross-sectional study, consisting of 1254 men and women aged between 40 and 90 years who had a DXA scan and complete validated data available for analysis. FRAX 10-year estimations for hip and major osteoporotic fracture were calculated using DXA software (DXA-FRAX) and the Web tool (Web-FRAX), with and without BMD. Agreements between estimates within each individual subject were examined using Bland-Altman plots. We performed exploratory analyses of the characteristics of those with very discordant results. RESULTS: Overall median DXA-FRAX and Web-FRAX 10-year hip and major osteoporotic fracture risk estimations which include BMD are very similar: 2.9% vs. 2.8% and 11.0% vs. 11% respectively. However, both are significantly lower than those obtained without BMD: 4.9% and 14% respectively, P < 0.001. Within-subject differences between hip fracture estimates with and without BMD were < 3% in 57% of cases, between 3 and 6% in 19% of cases, and > 6% in 24% of cases, while for major osteoporotic fractures such differences are < 10% in 82% of cases, between 10 and 20% in 15% of cases, and > 20% in 3% of cases. CONCLUSIONS: Although there is excellent agreement between the Web-FRAX and DXA-FRAX tools when BMD is incorporated, sometimes there are very large differences for individuals between results obtained with and without BMD. Clinicians should carefully consider the importance of BMD inclusion in FRAX estimations when assessing individual patients.

Prevalence of Low Bone Mass and Osteoporosis in Ireland: the Dual-Energy X-Ray Absorptiometry (DXA) Health Informatics Prediction (HIP) Project.

Osteoporosis is a common disease that has a significant impact on patients, healthcare systems, and society. World Health Organization (WHO) diagnostic criteria for postmenopausal women were established in 1994 to diagnose low bone mass (osteopenia) and osteoporosis using dual-energy X-ray absorptiometry (DXA)-measured bone mineral density (BMD) to help understand the epidemiology of osteoporosis, and identify those at risk for fracture. These criteria may also apply to men ≥50 years, perimenopausal women, and people of different ethnicity. The DXA Health Informatics Prediction (HIP) project is an established convenience cohort of more than 36,000 patients who had a DXA scan to explore the epidemiology of osteoporosis and its management in the Republic of Ireland where the prevalence of osteoporosis remains unknown. In this article we compare the prevalence of a DXA classification low bone mass (T-score < -1.0) and of osteoporosis (T-score ≤ -2.5) among adults aged ≥40 years without major risk factors or fractures, with one or more major risk factors, and with one or more major osteoporotic fractures. A total of 33,344 subjects met our study inclusion criteria, including 28,933 (86.8%) women; 9362 had no fractures or major risk factors, 14,932 had one or more major clinical risk factors, and 9050 had one or more major osteoporotic fractures. The prevalence of low bone mass and osteoporosis increased significantly with age overall. The prevalence of low bone mass and osteoporosis was significantly greater among men and women with major osteoporotic fractures than healthy controls or those with clinical risk factors. Applying our results to the national population census figure of 5,123,536 in 2022 we estimate between 1,039,348 and 1,240,807 men and women aged ≥50 years have low bone mass, whereas between 308,474 and 498,104 have osteoporosis. These data are important for the diagnosis of osteoporosis in clinical practice, and national policy to reduce the illness burden of osteoporosis. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Bone mineral density and fractures in patients with rheumatoid arthritis: the DXA-HIP project.

Objectives: RA is a chronic disabling disease affecting 0.5-1% of adults worldwide. People with RA have a greater prevalence of multimorbidity, particularly osteoporosis and associated fractures. Recent studies suggest that fracture risk is related to both non-RA and RA factors, whose importance is heterogeneous across studies. This study seeks to compare baseline demographic and DXA data across three cohorts: healthy controls, RA patients and a non-RA cohort with major risk factors and/or prior major osteoporotic fracture (MOF). Methods: This is a cross-sectional study using data collected from three DXA centres in the west of Ireland from January 2000 to November 2018. Results: Data were available for 30 503 subjects who met our inclusion criteria: 9539 (31.3%) healthy controls, 1797 (5.9%) with RA and 19 167 (62.8%) others. Although age, BMI and BMD were similar between healthy controls, the RA cohort and the other cohort, 289 (16.1%) RA patients and 5419 (28.3%) of the non-RA cohort had prior MOF. In the RA and non-RA cohorts, patients with previous MOF were significantly older and had significantly lower BMD at the femoral neck, total hip and spine. Conclusion: Although age, BMI and BMD were similar between a healthy control cohort and RA patients and others with major fracture risk factors, those with a previous MOF were older and had significantly lower BMD at all three measured skeletal sites. Further studies are needed to address the importance of these and other factors for identifying those RA patients most likely to experience fractures.

Introducing and Familiarising Older Adults Living with Dementia and Their Caregivers to Virtual Reality.

Virtual Reality (VR) is increasingly being applied in dementia care across a range of applications and domains including health and wellbeing. Despite the commercial availability of VR, informants of design are not always aware of its functionality and capabilities, to meaningfully contribute to VR design. In designing VR applications for people living with dementia, it is recommended that older adults living with dementia and their support persons be involved in the design process using participatory approaches, thereby giving them a voice on the design of technology from the outset. A VR technology probe is a useful means of familiarising older adults living with dementia and their informal caregivers with the knowledge and understanding of interactive VR to employ technology that supports them to maintain their social health. This paper charts the implementation and evaluation of a VR technology probe, VR FOUNDations. To explore their experiences, nine older adults living with dementia and their nine informal caregivers trialled VR FOUNDations and completed semi-structured interviews after its use. Overall, older adults living with dementia and their informal caregivers perceived VR FOUNDations to achieve its aim of increasing understanding and inspiring future design decisions. The findings also identified promising positive experiences using a VR technology probe which may be indicative of its applicability to social health and wellbeing domains. This paper advocates for the structured design and implementation of VR technology probes as a pre-requisite to the participatory design of VR applications for the health and wellbeing of people living with dementia. The use of such technology probes may afford older adults living with dementia and their informal caregivers the best opportunity to contribute to design decisions and participate in technology design to support their health and wellbeing.

Key Stakeholders' Experiences and Perceptions of Virtual Reality for Older Adults Living With Dementia: Systematic Review and Thematic Synthesis.

BACKGROUND: Technology is increasingly being used and evolving in the dementia care landscape. One such technology that has gained traction over the last decade is virtual reality (VR). VR is being applied in many areas of dementia care, including cognitive assessment and training, reminiscence therapy, music therapy, and other recreational VR applications. Despite the plethora of applications, they are often not shaped by the experiences and perceptions of older adults living with dementia. Currently, there is no qualitative evidence synthesis (QES) to explore this area. This review aimed to provide qualitative evidence supporting existing systematic reviews in this area. OBJECTIVE: The aim of this QES was to explore key stakeholders' experiences and perceptions of VR for older adults living with dementia. It aimed to explore the barriers and facilitators to VR use and provide recommendations for future design and implementation. METHODS: QES was used, which involved a systematic search of 6 databases to identify studies that qualitatively explored key stakeholders' experiences and perceptions of VR for older adults living with dementia. Thematic synthesis was used to integrate the findings of 14 studies (from 15 reports). The Critical Appraisal Skills Programme tool was used to assess the methodological quality of the included studies. The confidence placed in the review findings was assessed using the GRADE-CERQUAL (Confidence in the Evidence from Reviews of Qualitative research). RESULTS: A total of 15 reports from 14 studies were included in the review, consisting of a range of levels of VR immersion, stages of dementia, and care contexts. Three analytical themes were generated: stepping into virtuality, a virtual world, and returning to reality. The results indicate the importance of sensitively designing and introducing VR to this population, as older adults living with dementia often have no prior experience of using this technology. VR can be a positive experience for older adults living with dementia and can provide meaningful interactions, positive expressions, and long-term impacts on everyday functioning. However, it should be acknowledged that some negative associations must be accounted for before, during, and after use. CONCLUSIONS: This review highlights the positive implications as well as negative associations of VR use. It emphasizes the need for VR design and implementation driven by the needs and views of older adults living with dementia as well as with other key stakeholders. Future research needs to explore the vital role that older adults living with dementia can play in the design process and how they can be empowered to meaningfully design and use this technology.

Conceptual design of the dual X-ray absorptiometry health informatics prediction system for osteoporosis care.

Osteoporotic fractures are a major and growing public health problem, which is strongly associated with other illnesses and multi-morbidity. Big data analytics has the potential to improve care for osteoporotic fractures and other non-communicable diseases (NCDs), reduces healthcare costs and improves healthcare decision-making for patients with multi-disorders. However, robust and comprehensive utilization of healthcare big data in osteoporosis care practice remains unsatisfactory. In this paper, we present a conceptual design of an intelligent analytics system, namely, the dual X-ray absorptiometry (DXA) health informatics prediction (HIP) system, for healthcare big data research and development. Comprising data source, extraction, transformation, loading, modelling and application, the DXA HIP system was applied in an osteoporosis healthcare context for fracture risk prediction and the investigation of multi-morbidity risk. Data was sourced from four DXA machines located in three healthcare centres in Ireland. The DXA HIP system is novel within the Irish context as it enables the study of fracture-related issues in a larger and more representative Irish population than previous studies. We propose this system is applicable to investigate other NCDs which have the potential to improve the overall quality of patient care and substantially reduce the burden and cost of all NCDs.

How does proximal femur BMD of healthy Irish adults compare to NHANES III? Results of the DXA-HIP Project.

This study examines the distribution of proximal femur bone mineral density in a cohort of healthy Irish adults. These values are similar to those of the NHANES III Caucasian cohorts, supporting international recommendations to use this reference group for calculating DXA T-scores and Z-scores in Irish adults. INTRODUCTION: Bone mineral density (BMD) is widely used in the assessment and monitoring of osteoporosis. International guidelines recommend referencing proximal femur BMD measurements to NHANES III values to calculate T-scores and Z-scores, but their validity for the Irish population has not been established. In this study, we compare BMD values of healthy Irish Caucasian adults to those of Caucasian men and women in the NHANES III cohort study. METHODS: Men and women without bone disease and/or major risk factors for fracture, and/or not taking osteoporosis medication who had a screening DXA scan (GE Lunar, Madison, USA) at one of 3 centres in the West of Ireland were selected for this study. We calculated the mean and standard deviation (SD) used by GE for calculating white female NHANES III T-scores at the femoral neck and total hip sites, and used these values to calculate white female T-scores for men and women across each decade in our study sample. We calculated mean white female T-scores for each decade for both Caucasian men and women in the NHANES III cohort using the published data. Finally, we plotted these results against those of our study population. RESULTS: In total, 6729 (18.5%) of 36,321 adults were included in our analyses, including 5923 (88%) women. The majority of the study population were aged between 40 and 89 years. Our results show that the proximal femur BMD of healthy Irish men and women is broadly similar to that of the NHANES III reference population, especially middle-aged adults. Results differ for very young and very old adults, likely reflecting the small sample size and a referral bias. Further studies of these populations and other manufacturers could help clarify these uncertainties. CONCLUSIONS: Our results support using the NHANES III reference population to calculate proximal femur adult T-scores and Z-scores to establish the presence or prevalence of osteoporosis in Ireland.

The Irish dual-energy X-ray absorptiometry (DXA) Health Informatics Prediction (HIP) for Osteoporosis Project.

PURPOSE: The purpose of the Irish dual-energy X-ray absorptiometry (DXA) Health Informatics Prediction (HIP) for Osteoporosis Project is to create a large retrospective cohort of adults in Ireland to examine the validity of DXA diagnostic classification, risk assessment tools and management strategies for osteoporosis and osteoporotic fractures for our population. PARTICIPANTS: The cohort includes 36 590 men and women aged 4-104 years who had a DXA scan between January 2000 and November 2018 at one of 3 centres in the West of Ireland. FINDINGS TO DATE: 36 590 patients had at least 1 DXA scan, 6868 (18.77%) had 2 scans and 3823 (10.45%) had 3 or more scans. There are 364 unique medical disorders, 186 unique medications and 46 DXA variables identified and available for analysis. The cohort includes 10 349 (28.3%) individuals who underwent a screening DXA scan without a clear fracture risk factor (other than age), and 9947 (27.2%) with prevalent fractures at 1 of 44 skeletal sites. FUTURE PLANS: The Irish DXA HIP Project plans to assess current diagnostic classification and risk prediction algorithms for osteoporosis and fractures, identify the risk predictors for osteoporosis and develop novel, accurate and personalised risk prediction tools, by using the large multicentre longitudinal follow-up cohort. Furthermore, the dataset may be used to assess, and possibly support, multimorbidity management due to the large number of variables collected in this project.

An exploratory study into the use of Lean Six Sigma to reduce medication errors in the Norwegian public healthcare context.

PURPOSE: Medication errors are a significant cause of injury in Norwegian hospitals. The purpose of this study is to explore how Lean Six Sigma (LSS) has been used in the Norwegian public health-care context to reduce medication errors. DESIGN/METHODOLOGY/APPROACH: A mixed method approach was used to gather data from participants working in the four regions served by the Norway health authorities. A survey questionnaire was distributed to 38 health-care practitioners and semi-structured interviews were conducted with 12 health-care practitioners. FINDINGS: The study finds that the implementation of LSS in the Norwegian public health-care context is still in its infancy. This is amidst several challenges faced by Norwegian hospitals such as the lack of top-management support, lack of LSS training and coaching and a lack of awareness around the benefits of LSS in health care. RESEARCH LIMITATIONS/IMPLICATIONS: Because of the large geographical area, it was difficult to reach participants from all health regions in Norway. However, the study managed to assess the current status of LSS implementation through the participants' perspectives. This is a fruitful area for future research whereby an action research methodology could be used. ORIGINALITY/VALUE: To the best of the authors' knowledge, this is the first empirical study into the use of LSS methodology in reducing medication errors. In addition, this study is valuable for health-care practitioners and professionals as a guideline to achieve the optimal benefit of LSS implementation to reduce medication errors.