Dataset Information

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study.

ABSTRACT: BACKGROUND:People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist-client consultation. OBJECTIVE:This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system. METHODS:A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation. RESULTS:Pharmacists' agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent. CONCLUSIONS:A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development.

SUBMITTER: Downie AS

PROVIDER: S-EPMC7248808 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study.

Downie Aron Simon AS Hancock Mark M Abdel Shaheed Christina C McLachlan Andrew J AJ Kocaballi Ahmet Baki AB Williams Christopher M CM Michaleff Zoe A ZA Maher Chris G CG

JMIR medical informatics 20200511 5

<h4>Background</h4>People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A ...[more]

PMID: 32390593

Similar Datasets

Project description:BackgroundThe biopsychosocial model is recommended in the management of non-specific low back pain but musculoskeletal practitioners can lack skills in assessing and managing patients using a biopsychosocial framework. Educational interventions have produced equivocal results. There is a need for an alternative educational tool to support practitioners' development in the application of biopsychosocial model to manage low back pain.MethodsA mixed methods study assessed the feasibility and acceptability of an e-learning programme on the biopsychosocial management of non-specific low back pain for osteopaths with more than 15 years' experience. A sequential explanatory design was conducted, with a feasibility randomised controlled trial and semi-structured interviews explored with thematic analysis.ResultsA total of 45 participants participated in the RCT of which 9 also participated in the interview study. The a-priori sample size was not met (45 instead of 50). The recruitment strategies, randomisation, retention, data collection and outcome measures worked well and were found to be feasible for a main trial. The retention, satisfaction and participants' views of the programme demonstrated a good acceptability of the programme. Data from the semi-structured interviews were organised in three themes, the first two were related to the feasibility and acceptability of the e-learning programme (practical experience of following the course and engagement with the content) and the third relates to the impact of the intervention (perception of the BPS model).ConclusionA main RCT is feasible and the intervention was received well by the participants. A main RCT is required to assess the effectiveness of the e-learning programme. This work also provided data on aspects so far unreported, including osteopaths' views on continuing professional development, on e-learning as a form of continuing professional development and osteopaths' perceptions and challenges concerning the implementation of the biopsychosocial model in practice.

Project description:BackgroundDiagnostic errors pose significant health risks and contribute to patient mortality. With the growing accessibility of electronic health records, machine learning models offer a promising avenue for enhancing diagnosis quality. Current research has primarily focused on a limited set of diseases with ample training data, neglecting diagnostic scenarios with limited data availability.ObjectiveThis study aims to develop an information retrieval (IR)-based framework that accommodates data sparsity to facilitate broader diagnostic decision support.MethodsWe introduced an IR-based diagnostic decision support framework called CliniqIR. It uses clinical text records, the Unified Medical Language System Metathesaurus, and 33 million PubMed abstracts to classify a broad spectrum of diagnoses independent of training data availability. CliniqIR is designed to be compatible with any IR framework. Therefore, we implemented it using both dense and sparse retrieval approaches. We compared CliniqIR's performance to that of pretrained clinical transformer models such as Clinical Bidirectional Encoder Representations from Transformers (ClinicalBERT) in supervised and zero-shot settings. Subsequently, we combined the strength of supervised fine-tuned ClinicalBERT and CliniqIR to build an ensemble framework that delivers state-of-the-art diagnostic predictions.ResultsOn a complex diagnosis data set (DC3) without any training data, CliniqIR models returned the correct diagnosis within their top 3 predictions. On the Medical Information Mart for Intensive Care III data set, CliniqIR models surpassed ClinicalBERT in predicting diagnoses with <5 training samples by an average difference in mean reciprocal rank of 0.10. In a zero-shot setting where models received no disease-specific training, CliniqIR still outperformed the pretrained transformer models with a greater mean reciprocal rank of at least 0.10. Furthermore, in most conditions, our ensemble framework surpassed the performance of its individual components, demonstrating its enhanced ability to make precise diagnostic predictions.ConclusionsOur experiments highlight the importance of IR in leveraging unstructured knowledge resources to identify infrequently encountered diagnoses. In addition, our ensemble framework benefits from combining the complementary strengths of the supervised and retrieval-based models to diagnose a broad spectrum of diseases.

Project description:BackgroundSelf-management is the key recommendation for managing nonspecific low back pain (LBP). However, there are well-documented barriers to self-management; therefore, methods of facilitating adherence are required. Smartphone apps are increasingly being used to support self-management of long-term conditions such as LBP.ObjectiveThe aim of this study was to assess the usability and acceptability of the SELFBACK smartphone app, designed to support and facilitate self-management of non-specific LBP. The app provides weekly self-management plans, comprising physical activity, strength and flexibility exercises, and patient education. The plans are tailored to the patient's characteristics and symptom progress by using case-based reasoning methodology.MethodsThe study was carried out in 2 stages using a mixed-methods approach. All participants undertook surveys, and semistructured telephone interviews were conducted with a subgroup of participants. Stage 1 assessed an app version with only the physical activity component and a web questionnaire that collects information necessary for tailoring the self-management plans. The physical activity component included monitoring of steps recorded by a wristband, goal setting, and a scheme for sending personalized, timely, and motivational notifications to the user's smartphone. Findings from Stage 1 were used to refine the app and inform further development. Stage 2 investigated an app version that incorporated 3 self-management components (physical activity, exercises, and education). A total of 16 participants (age range 23-71 years) with ongoing or chronic nonspecific LBP were included in Stage 1, and 11 participants (age range 32-56 years) were included in Stage 2.ResultsIn Stage 1, 15 of 16 participants reported that the baseline questionnaire was easy to answer, and 84% (13/16) found the completion time to be acceptable. Overall, participants were positive about the usability of the physical activity component but only 31% (5/16) found the app functions to be well integrated. Of the participants, 90% (14/16) were satisfied with the notifications, and they were perceived as being personalized (12/16, 80%). In Stage 2, all participants reported that the web questionnaire was easy to answer and the completion time acceptable. The physical activity and exercise components were rated useful by 80% (8/10), while 60% (6/10) rated the educational component useful. Overall, participants were satisfied with the usability of the app; however, only 50% (5/10) found the functions to be well integrated, and 20% (2/10) found them to be inconsistent. Overall, 80% (8/10) of participants reported it to be useful for self-management. The interviews largely reinforced the survey findings in both stages.ConclusionsThis study has demonstrated that participants considered the SELFBACK app to be acceptable and usable and that they thought it would be useful for supporting self-management of LBP. However, we identified some limitations and suggestions useful to guide further development of the SELFBACK app and other mobile health interventions.

Project description:BackgroundLow back pain (LBP) is a long-term health condition with an unpredictable pattern of symptomatic episodes, remission, and recurrence. Recently published systematic reviews suggest that exercise is the most effective intervention for preventing recurrences of LBP in persons that have recovered. Similar programs may also be effective in preventing flare-ups in persistent LBP. The aim of this study was to test the feasibility of the Back to Living Well program (Physical activity + Education + Self-management) developed to prevent recurrence or flare-ups of LBP. The study evaluated feasibility in terms of recruitment rate, adherence, satisfaction with the exercise and education sessions, and the data collection procedures. We also aimed to evaluate barriers and facilitators to the engagement in the program.MethodsSeventeen participants with non-specific LBP recently discharged from care from physiotherapy, chiropractors or physician care (< 3 months) were referred to the study by health care providers or community advertisements between December 2018 and February 2019. Participants underwent a 12-week (1 session/week) individualized, group-based exercise in the community and 4 sessions (30 min each) of education. All participants completed an action plan weekly for 12 weeks and wore an activity monitor for 6 months. All participants responded to weekly pain measures and completed study questionnaires at baseline, 3- and 6-months. Feasibility outcomes included recruitment, attrition rates and satisfaction. At the end of the intervention, participants completed an end-of-program survey.ResultsTwenty-nine participants were screened for eligibility; 20 were deemed eligible, while 17 were included over a 2-month period meeting our feasibility targets. In total, 16 completed follow-up study questionnaires at 3 months, and 15 completed the 6-month follow-up. Fourteen participants responded to weekly messages, while 3 participants reported not having a mobile device or Internet access. In total, 15 participants responded to our end-of-program survey. Average age was 54.9 (11.7); 9 were female (53%), and the mean duration of LBP was 62.9 (69.7) months. All satisfaction responses in relation to the exercise program, education program and data collection procedures reached our threshold of 70% out of 100%. Reported barriers to engagement in the program included fear of injury, lack of motivation and travel. Facilitators included proximity to home, low cost, flexible schedule and friendly location.ConclusionThe results show the program is feasible in terms of recruitment, low attrition, and patient satisfaction. Participants highlighted the excellent, relevant education program and the positive, personalized exercise. Future studies should evaluate the effectiveness of this intervention within a fully powered randomized controlled trial.Trial registrationNCT03328689.

Project description:BackgroundPractice-based guidelines recommend patient education and exercise as first-line care for low back pain (LBP); however, these recommendations are not routinely delivered in practice. GLA:D® Back, developed in Denmark to assist clinicians to implement guideline recommendations, offers a structured education and supervised exercise program for people with LBP in addition to a clinical registry to evaluate patient outcomes. In this study we evaluated the feasibility of implementing the GLA:D® Back program in Australia. We considered clinician and patient recruitment and retention, program fidelity, exploring clinicians' and patients' experiences with the program, and participant outcome data collection.MethodsClinicians (chiropractors and physiotherapists) were recruited and participated in a 2-day GLA:D® Back training course. Patients were eligible to participate if they had persistent or recurrent LBP. Feasibility domains included the ability to: (1) recruit clinicians to undergo training; (2) recruit and retain patients in the program; (3) observe program fidelity; and (4) perceive barriers and facilitators for GLA:D® Back implementation. We also collected data related to: (5) clinician confidence, attitudes, and behaviour; and (6) patient self-reported outcomes related to pain, disability, and performance tests.ResultsTwenty clinicians (8 chiropractors, 12 physiotherapists) participated in the training, with 55% (11/20) offering GLA:D® Back to their patients. Fifty-seven patients were enrolled in the program, with 67% (38/57) attending the final follow-up assessment. Loss to follow up was mainly due to the effects of the COVID-19 pandemic. We observed program fidelity, with clinicians generally delivering the program as intended. Interviews revealed two clinician themes related to: (i) intervention acceptability; and (ii) barriers and facilitators to implementation. Patient interviews revealed themes related to: (i) intervention acceptability; and (ii) program efficacy. At 3 months follow-up, clinicians demonstrated high treatment confidence and biomedical orientation. Patient outcomes trended towards improvement.ConclusionGLA:D® Back implementation in Australia appears feasible based on clinician recruitment, program acceptability and potential benefits for patient outcomes from the small sample of participating clinicians and patients. However, COVID-19 impacted patient recruitment, retention, and data collection. To scale-up GLA:D® Back in private and public settings, further work is warranted to address associated barriers, and to leverage facilitators.

Project description:BackgroundAccess to quality hypertension care is often poor in sub-Saharan Africa. Some community pharmacies offer hypertension monitoring services, with and without involvement of medical doctors. To directly connect pharmacy staff and cardiologists a care model including a mobile application (mHealth) for remote patient monitoring was implemented and pilot tested in Lagos, Nigeria. Pharmacists provided blood pressure measurements and counselling. Cardiologists enrolled patients in the pilot program and remotely monitored them, for which patients paid a monthly fee. We evaluated the feasibility of this care model at five private community pharmacies. Outcome measures were retention in care, blood pressure change, quality of care, and patients' and healthcare providers' satisfaction with the care model.MethodsPatients participated in the care model's pilot at one of the five pharmacies for approximately 6-8 months from February 2016. We conducted structured patient interviews and blood pressure measurements at pilot entry and exit, and used exports of the mHealth-application, in-depth interviews and focus group discussions with patients, pharmacists and cardiologists.ResultsOf 336 enrolled patients, 236 (72%) were interviewed at pilot entry and exit. According to the mHealth data 71% returned to the pharmacy after enrollment, with 3.3 months (IQR: 2.2-5.4) median duration of activity in the mHealth-application. Patients self-reported more visits than recorded in the mHealth data. Pharmacists mentioned use of paper records, understaffing, the application not being user-friendly, and patients' unwillingness to pay as reasons for underreporting. Mean systolic blood pressure decreased 9.9 mmHg (SD: 18). Blood pressure on target increased from 24 to 56% and an additional 10% had an improved blood pressure at endline, however this was not associated with duration of mHealth activity. Patients were satisfied because of accessibility, attention, adherence and information provision.ConclusionPatients, pharmacists and cardiologists adopted the care model, albeit with gaps in mHealth data. Most patients were satisfied, and their mean blood pressure significantly reduced. Usage of the mHealth application, pharmacy incentives, and a modified financing model are opportunities for improvement. In addition, costs of implementation and availability of involved healthcare providers need to be investigated before such a care model can be further implemented.

Project description:BackgroundThe prevalence of low back pain increases with age and has a profound impact on physical and psychosocial health. With increasing age comes increasing comorbidity, and this also has pronounced health consequences. Whilst exercise is beneficial for a range of health conditions, trials of exercise for low back pain management often exclude older adults. It is currently unknown whether an exercise program for older adults with low back pain, tailored for the presence of comorbidities, is acceptable for participants and primary healthcare providers (PHCPs). Therefore, this mixed-methods study will assess the feasibility of an 8-week comorbidity-adapted exercise program for older people with low back pain and comorbid conditions.MethodsThe 3-phased feasibility study will be performed in a primary healthcare setting. PHCPs will be trained to deliver a comorbidity-adapted exercise program for older people with low back pain and comorbidities. Healthcare-seeking adults > 65 will be screened for eligibility over telephone, with a recruitment target of 24 participants. Eligible participants will attend an initial appointment (diagnostic phase). During this initial appointment, a research assistant will collect patient demographics, self-reported outcome measurement data, and perform a physical and functional examination to determine contraindications and restrictions to an exercise program. During the development phase, PHCPs will adapt the exercise program to the individual and provide patient education. During the intervention phase, there will be two supervised exercise sessions per week, over 8 weeks (total of 16 exercise sessions). Each exercise session will be approximately 60 min in duration. A qualitative evaluation after the last exercise program session will explore the feasibility of the exercise program for participants and PHCPs. Progression criteria will determine the suitability for a fully powered randomised controlled trial.DiscussionThis mixed-methods feasibility study will assess an exercise program for older adults with low back pain and comorbidities. Once assessed for feasibility, the exercise program may be tested for effectiveness in a larger, fully powered randomised controlled trial. This information will add to the sparse evidence base on appropriate options for managing back pain in older adults.Trial registrationAustralian and New Zealand Clinical Trials Registry registration number: ACTRN12621000379819p (06/04/2021; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12621000379819p ).Trial sponsorMacquarie University, Department of Chiropractic, Faculty of Medicine, Health and Human Sciences, Macquarie University, NSW 2109, Australia.

Dataset Information

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study.

Publications

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets