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Development of an integrated electronic platform for patient self-report and management of adverse events during cancer treatment.

ABSTRACT: Background:Significant adverse events (AE) during cancer therapy disrupt treatment and escalate to emergency admissions. Approaches to improve the timeliness and accuracy of AE reporting may improve safety and reduce health service costs. Reporting AE via patient reported outcomes (PROs), can improve clinician-patient communication and making data available to clinicians in 'real-time' using electronic PROs (ePROs) could potentially transform clinical practice by providing easily accessible records to guide treatment decisions. This manuscript describes the development of eRAPID (electronic patient self-Reporting of Adverse-events: Patient Information and aDvice) is a National Institute for Health Research-funded programme, a system for patients to self-report and manage AE online during and after cancer treatment. Materials and methods:A multidisciplinary team of IT experts, staff and patients developed using agile principles a secure web application interface (QStore) between an existing online questionnaire builder (QTool) displaying real-time ePRO data to clinicians in the electronic patient record at Leeds Teaching Hospitals NHS Trust. Hierarchical algorithms were developed corresponding to Common Terminology Criteria for Adverse Events grading using the QTool question dependency function. Patient advocates (N?=?9), patients (N?=?13), and staff (N?=?19) usability tested the system reporting combinations of AE. Results:The eRAPID system allows patients to report AE from home on PC, tablet or any web enabled device securely during treatment. The system generates immediate self-management advice for low or moderate AE and for severe AE advice to contact the hospital immediately. Clinicians can view patient AE data in the electronic patient record and receive email notifications when patients report severe AE. Conclusions:Evaluation of the system in a randomised controlled trial in breast, gynaecological and colorectal cancer patients undergoing systemic therapy is currently underway. To adapt eRAPID for different treatment groups, pilot studies are being undertaken with patients receiving pelvic radiotherapy and upper gastrointestinal surgery. ISRCTN88520246.

SUBMITTER: Holch P

PROVIDER: S-EPMC5834137 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Development of an integrated electronic platform for patient self-report and management of adverse events during cancer treatment.

Holch P P Warrington L L Bamforth L C A LCA Keding A A Ziegler L E LE Absolom K K Hector C C Harley C C Johnson O O Hall G G Morris C C Velikova G G

Annals of oncology : official journal of the European Society for Medical Oncology 20170901 9

<h4>Background</h4>Significant adverse events (AE) during cancer therapy disrupt treatment and escalate to emergency admissions. Approaches to improve the timeliness and accuracy of AE reporting may improve safety and reduce health service costs. Reporting AE via patient reported outcomes (PROs), can improve clinician-patient communication and making data available to clinicians in 'real-time' using electronic PROs (ePROs) could potentially transform clinical practice by providing easily accessi ...[more]

PMID: 28911065

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Project description:BackgroundAn estimated 17,000 patients are treated annually in the UK with radical radiotherapy (RT) for pelvic cancer. New treatment approaches in RT have increased survivorship and changed the subjective toxicity profile for patients who experience acute and long-term pelvic-related adverse events (AE). Multi-disciplinary follow-up creates difficulty for monitoring and responding to these events during treatment and beyond. Originally developed for use in systemic oncology therapy eRAPID (electronic patient self-Reporting of Adverse-events: Patient Information and aDvice) is an online system for patients to report AEs from home. eRAPID enables patient data to be integrated into the electronic patient records for use in clinical practice, provides patient management advice for mild and moderate AE and advice to contact the hospital for severe AE. The system has now been developed for pelvic RT patients, and we aim to test the intervention in a pilot study with staff and patients to inform a future randomised controlled trial (RCT).MethodsEligible patients are those attending St James's University hospital cancer centre and The Christie Hospital Manchester undergoing pelvic radiotherapy+/-chemotherapy/hormonotherapy for prostate, lower gastrointestinal and gynaecological cancers. A prospective 1:1 randomised (intervention or usual care) parallel group design with repeated measures and mixed methods will be employed. We aim to recruit 168 patients following recommendations for sample size estimates for pilot studies. Participants using eRAPID will report AE (at least weekly) from home weekly for 6 weeks and 6 weeks post-treatment (12-week total) then at 18 and 24 weeks. Hospital staff will review eRAPID reports and use information during consultations. Notifications will be sent to the relevant clinical team when severe symptoms are reported. We will measure patient-reported outcomes using validated questionnaires (Functional Assessment in Cancer Therapy Scale-General (FACT-G), European Organisation for Research and Treatment of Cancer Core Quality of Life questionnaire (EORTC-QLQ-C30), process of care impact (hospital records of patient contacts and admissions) and economic variables (EQ5D-5L, patient use of resources)). Staff and patient experiences will be explored via semi-structured interviews.DiscussionThe objectives are to establish feasibility, recruitment, integrity of the system and attrition rates, determine effect sizes and aid selection of the primary outcome measure for a future RCT. We will also refine the intervention by exploring staff and patient views. The overall goal of this complex intervention is to improve the safe delivery of cancer treatments, enhance patient care and standardise documentation of AE within the clinical datasets.Trial registrationClinicalTrials.gov NCT02747264.

Project description:BackgroundPromoting medication adherence is a recognized challenge for prescribers. In this study, we examine whether lower medication adherence is associated with adverse safety events in individuals with decreased estimated glomerular filtration rates (eGFRs).Study designCross-sectional baseline analysis of prospective cohort.Setting & participantsBaseline analysis of the Safe Kidney Care (SKC) Cohort Study, a prospective study of individuals with eGFRs<60 mL/min/1.73 m(2) intended to assess the incidence of disease-specific safety events. Kidney transplant recipients were excluded.PredictorSelf-reported medication adherence based on responses to 3 questions ascertaining degree of medication regimen adherence.OutcomesAdverse safety events were self-reported at baseline (class I events), such as hypoglycemia or fall thought to be related to a medication, or detected incidentally during the baseline visit (class II events), for example, hypotension or hyperkalemia. Potential drug-related problems (DRPs) were determined by analyzing participants' medications with respect to dosing guidelines based on their screening eGFRs at the time of medication reporting.MeasurementsRelationship between medication adherence and disease-specific patient safety events.ResultsOf 293 SKC participants, 154 (53%) were classified as having lower medication adherence. After multivariable adjustment, lower medication adherence was significantly associated with a class I or II safety event (prevalence ratio [PR], 1.21; 95% CI, 1.04-1.41) and potential DRPs (PR, 1.29; 95% CI, 1.02-1.63). Lower medication adherence was also significantly associated with multiple (≥2) class I events (PR, 1.71; 95% CI, 1.18-2.49), multiple class I or II events (PR, 1.35; 95% CI, 1.04-1.76), and multiple potential DRPs (PR, 2.11; 95% CI, 1.08-2.69) compared with those with higher medication adherence.LimitationsUse of self-reported medication adherence rather than pharmacy records. Clinical relevance of detected safety events is unclear.ConclusionsLower medication adherence is associated with adverse safety events in individuals with eGFRs<60 mL/min/1.73 m(2).

Project description:IntroductionA patient record review study conducted in 2006 in a random sample of 21 Dutch hospitals found that 51%-77% of adverse events are related to perioperative care, while Centers for Disease Control and Prevention data in USA in 2013 estimated that the medical error is the third-leading cause of mortality. To capitalise on the potential of apps to enhance perioperative medical quality, there is a need for interventions developed in consultation with real-world users designed to support integrated management for perioperative adverse events (PAEs). This study aims: (1) to access the knowledge, attitude and practices for PAEs among physicians, nurses and administrators, and to identify the needs of healthcare providers for a mobile-based PAEs tool; (2) to develop a data-driven app for integrated PAE management that meets those needs and (3) to test the usability, clinical efficacy and cost-effectiveness of the developed app.Methods and analysisWe will adopt an embedded mixed-methods research technique; qualitative data will be used to assess user needs and app adoption, while quantitative data will provide crucial insights to establish the demand for the app, and measure the app effects. Phase 1 will enrol surgery-related healthcare providers from the West China Hospital and identify their latent demand for mobile-based PAEs management using a self-designed questionnaire underpinned by the knowledge, attitude and practice model, as well as expert interviews. In phase 2, we will develop the app for integrated PAE management and test its effectiveness and sustainability. In phase 3, the effects on the total number and severity of reported PAEs will be evaluated using Poisson regression with interrupted time-series analysis over a 2-year period, while users' engagement, adherence, process evaluation and cost-effectiveness will be evaluated using quarterly surveys and interviews.Ethics and disseminationThe West China Hospital of Sichuan University's Institutional Review Board authorised this study after approving the study protocol, permission forms and questionnaires (number: 2022-1364). Participants will be provided with study information, and informed written consent will be obtained. Study findings will be disseminated through peer-reviewed publications and conference presentations.

Project description:ImportanceHalf of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients.ObjectiveTo predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems.Design, setting, and participantsThis prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021.Main outcomes and measuresSuicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide.ResultsA total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians' assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts.Conclusions and relevanceThis prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data.

Project description:BackgroundMultimorbidity is defined as the presence of two or more chronic diseases and associated comorbidities. There is a need to improve best practices around the provision of well-coordinated, person-centered care for persons with multimorbidities. Present health systems across the European Union (EU) focus on supporting a single-disease framework of care; the primary challenge is to create a patient-centric, integrated care ecosystem to understand and manage multimorbidity. ProACT is a large-scale project funded by the European Commission under the Horizon 2020 programme, that involved the design, development, and evaluation of a digital health platform to improve and advance home-based integrated care, and supported self-management, for older adults (aged ≥65 years) living with multimorbidity.ObjectiveThis paper describes the trial implementation protocol of a proof-of-concept digital health platform (ProACT) in 2 EU member states (Ireland and Belgium) to support older persons with multimorbidities self-managing at home, supported by their care network (CN).MethodsResearch was conducted across 2 EU member states, Ireland and Belgium. A 12-month action research trial design, divided into 3 evaluation cycles and lasting 3 months each, with a reflective redesign and development phase of 1 month after cycles 1 and 2 was conducted. Participants were 120 (60/120, 50% in Ireland and 60/120, 50% in Belgium) older persons with multimorbidities diagnosed with two or more of the following chronic conditions: diabetes, chronic obstructive pulmonary disease, chronic heart failure, and cardiovascular diseases. With permission from persons with multimorbidities, members of their CN were invited to participate in the study. Persons with multimorbidities were provided with ProACT technologies (tablet, devices, or sensors) to support them in self-managing their conditions. CN members also received access to an app to remotely support their persons with multimorbidity. Qualitative and quantitative feedback and evaluation data from persons with multimorbidity and CN participants were collected across four time points: baseline (T1), at the end of each 3-month action research cycle (T2 and T3), and in a final posttrial interview (T4). Thematic analysis was used to analyze the qualitative interview data. Quantitative data were analyzed via platform use statistics (to assess engagement) and standardized questionnaires (using descriptive and inferential statistics). This study is approved by the ethics committees of Ireland and Belgium.ResultsThe trial implementation phase for this 44-month (2016-2019) funded study was April 2018 to June 2019. The trial outcomes are at various stages of publication since 2021.ConclusionsProACT aims to co-design and develop a digital intervention with persons with multimorbidities and their CN, incorporating clinical guidelines with the state of the art in human-computer interaction, behavioral science, health psychology, and data analytic methods to deliver a digital health platform to advance self-management of multimorbidity at home, as part of a proactive, integrated model of supported person-centered care.International registered report identifier (irrid)RR1-10.2196/22125.

Dataset Information

Development of an integrated electronic platform for patient self-report and management of adverse events during cancer treatment.

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Development of an integrated electronic platform for patient self-report and management of adverse events during cancer treatment.

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