Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,426
datasets available to search
ShareScore release 0.9.0
Dataset results
3,426 results for “patient care”
Myeloperoxidase can differentiate between sepsis and non-infectious SIRS and predicts mortality in intensive care patients with SIRS.
<p>Dataset of "Myeloperoxidase can differentiate between sepsis and non-infectious SIRS and predicts mortality in intensive care patients with SIRS."</p>
Study protocol and data dictionary: Effectiveness of a GP delivered medication review in reducing polypharmacy and potentially inappropriate prescribing in older patients with multimorbidity in Irish primary care: a cluster randomised controlled trial (SPPiRE study)
<p><strong>Methods</strong></p> <p><strong>Study design and participants</strong></p> <p>The methods for the SPPiRE cluster RCT have been described in the trial protocol (21). This study is reported in line with the CONSORT 2010 cluster RCT checklist (22), see Appendix 1, and was approved by the Irish College of General Practitioners Research Ethics Committee. In brief, SPPiRE was a pragmatic two arm cluster RCT, with the intervention delivered to GP clusters and analysis of outcomes at the patient level. Information about the trial was publicised through a variety of GP research, teaching and training networks throughout Ireland. Eligible practices expressing an interest were formally invited. Practices were eligible to participate if they had at least 300 registered patients aged ≥65 years (based on the need to identify a sufficient number of eligible participants) and used either of the two Irish GP practice management systems (PMS) with over 80% national cover; this enabled use of a SPPiRE patient finder tool which was developed and embedded into these systems. Practices were excluded if they were currently involved in a medication management or prescribing trial or if they were unable to recruit at least five participants.</p> <p>Eligible patients were aged ≥65 years and prescribed ≥15 repeat medicines. A repeat medicine was defined as any unique item with a World Health Organisation Anatomical Therapeutic Chemical code on the patient’s current repeat prescription. Patients were excluded if they had been recruited into a practice that was unable to recruit at least four other participants, they were judged by their GP as unable to give informed consent or they were unable to attend the practice for a face to face medication review, (e.g. nursing home residents and house bound patients). Recruited GPs ran the SPPiRE patient finder tool and screened the generated list to ensure only eligible patients were invited. Practices who identified more than 40 eligible patients were supported in selecting a random sample of 30 patients to invite. All recruited practices and patients gave fully informed consent and baseline data was collected prior to practice allocation, to reduce the likelihood of selection bias.</p> <p><strong>Randomisation and masking</strong></p> <p>Recruited practices were allocated to intervention or control groups by minimisation using Minimpy software (23) by the trial statistician (FB) who had no knowledge of participating practices. Minimisation variables included practice size (number of GP sessions per week, 0-14, 14-28 and 28 or more) and location (urban, rural or mixed). Considering the nature of the intervention, it was not possible to blind GPs or patients to the intervention, however to reduce the risk of detection bias the two primary outcome measures; the number of repeat medicines and whether a PIP was present were assessed by an independent blinded pharmacist (MF).</p> <p><strong>Procedures</strong></p> <p>Intervention GPs received unique login details to the SPPiRE website where they had access to five training videos and a template for performing the SPPiRE medication review. The training videos provided background information on multimorbidity and polypharmacy, PIP, eliciting patient treatment priorities and conducting a brown bag medication review. GPs were instructed to book a double appointment and to ask their patients to bring all their medicines in to the medication review visit with them. The SPPiRE medication review process had two main components; gather and record information and then to discuss and agree changes with their patient based on the recorded information, with a focus on deprescribing medicines that were potentially inappropriate, figure 1. The website provided suggested treatment alternatives for identified PIP but all treatment decisions were ultimately at the discretion of the individual GP, based on their clinical judgement and their patients’ individual priorities.</p> <p>Control GPs delivered usual care during the six to twelve month study period. At the time of intervention delivery there was no structured chronic disease management programme in Irish primary care and many patients with multimorbidity attended multiple hospital specialists. In Ireland, the majority of people aged ≥70 years of age have access to free GP visits and medicines with some prescription charge co-payments. In the 65 – 69 year old age category a lower proportion have access to both free GP visits and prescription medicines. Access to specialists and diagnostics in secondary care is free for the entire population.</p> <p><strong>Outcomes</strong></p> <p>The two primary outcomes were the number of repeat medicines and the proportion of patients with any PIP, from a list of 34 pre-specified indicators (see Appendix 2). A series of secondary prescribing related outcome measure were pre-specified to allow a more in depth analysis of the effect of the intervention on prescribing. These were:</p> <ul> <li>The number of medicines stopped and started</li> <li>The proportion of patients with a reduction in significant polypharmacy (defined as ≥15 repeat medicines)</li> <li>The number of PIP</li> <li>The proportion of patients with a high risk PIP (see Appendix 2)</li> <li>The proportion of patients with any reduction in PIP</li> </ul> <p>Secondary patient reported outcomes measures were included to capture the effectiveness of the intervention from the patients’ perspective. These were:</p> <ul> <li>Health related Quality of life (EQ5D-5L)(24)</li> <li>Revised Patients' attitudes towards deprescribing (rPATD) (25)</li> <li>Multimorbidity Treatment Burden Questionnaire (MTBQ) (26)</li> </ul> <p>Health care utilisation data was collected to assess the effect of the intervention on health care usage and for the trial’s economic evaluation.</p> <p>Outcomes were collected at baseline and at six months after intervention delivery. Patient reported measures were collected by postal questionnaires. Data for all other measures including prescribed medicines, medical and investigations history and healthcare utilisation were collected by participating GPs and submitted to the study manager (CMC). This was a deviation from the original protocol, which indicated this data would be collected by the research team. This deviation related to changes in data protection and national health research regulations during the study period, which precluded research team access to the patients’ full clinical record.</p> <p><strong>Adverse events</strong></p> <p>Information on adverse events such as mortality, ED presentations and hospital admissions was collected at follow up. Given the deprescribing approach of the intervention a safety protocol for identifying and reporting any suspected adverse drug withdrawal events (ADWEs) was developed. An ADWE is defined as either recurrence of the condition for which the drug was prescribed (e.g. recurrence of angina after stopping a beta blocker) or a physiologic reaction to drug withdrawal (e.g. SSRI withdrawal syndrome) (27, 28). Although discontinuing medicines in older people has been demonstrated to be safe (29), given the paramount importance of the principle of “do no harm” in research ethics a vigorous and detailed method was established to ensure that any potential ADWEs precipitated by deprescribing in a SPPiRE medication review were captured. Intervention GPs were asked to report any possible ADWE following the SPPiRE medication review. The Naranjo ADR probability scale (30) has been adapted in other studies to assess the likelihood a reaction is related to drug withdrawal (27, 28). This tool was further adapted for SPPiRE and used to make an assessment on the causality of the ADWE. To ensure the patient perspective was included, self-reported possible ADWEs were also collected from patient follow up questionnaires. </p> <p> </p> <p><strong>Sample size</strong></p> <p>As outlined in the trial protocol (21), the study was designed with 90% power to detect a 20% reduction in the proportion with PIP and a mean difference of one medicine between intervention and control groups (based on a mean of 17.4 medicines SD (2.6)) and the sample size inflated to incorporate the effects of clustering (using an ICC of 0.025). The sample size was recalculated when it became apparent during early recruitment that it would not be possible to recruit clusters with an average of 15 participants, as was initially planned in the protocol. An average cluster size of eight was anticipated which inflated the original sample size from 30 practices (450 patients) to 50 practices (400 patients).</p> <p><strong>Statistical analysis</strong></p> <p>Descriptive statistics were used to describe baseline characteristics of recruited practices and participants. All analyses were conducted under the intention-to-treat principle and those lost to follow up had their baseline data carried forward. The primary analysis was carried out using multi-level modelling. The first primary outcome measure, number of repeat medications, was assessed using mixed effects Poisson regression with the individual as the unit of analysis and the practice included as the random effect to control for the effects of clustering and results presented using incidence rate ratios (IRR) and 95% confidence intervals (CI). The baseline number of medicines, GP size (number of GP sessions per week) and GP location (urban/rural) were included in the analysis as fixed effects. The second outcome measure, proportion of patients with a PIP, was analysed in a similar manner using mixed effects logistic regression, including PIP at baseline, GP size and location, and results presented using odd ratios (OR) and 95% CIs. A number of pre-specified sensitivity analyses were conducted; complete case analysis, per protocol analysis and including “presence of a repeat prescribing policy” as a covariate. All secondary outcomes were analysed in a similar manner to the primary outcomes, using appropriate mixed effects regression methods (i.e. linear, logistic, Poisson).</p> <p> </p> <p>Note: Version 3 (published 28 April 2025) updates Version 2 by removing Participant GP1P4 following consent withdrawal. This version should be used for all future analyses.</p> <p> </p>
Compassion Fatigue and Compassion Satisfaction among Registered Nurses Caring for Cancer Patients: An Explorative Survey
<p>Compassion fatigue is a complex phenomenon, increasingly studied by health services. In addition to the analysis of the phenomenon, studies also consider the factors that influence the satisfaction deriving from nursing work, characterized by the compassion inherent in the relationship with the patient, in addition to the associated fatigue and the consequent risk of Burnout. . The aim of this study, conducted at the IOV - Veneto Oncology Institute in Padua, is to describe Compassion Fatigue and Compassion Satisfaction in nurses working in oncology, where the work requires a strong degree of sensitivity. An exploratory cross-sectional survey was conducted on a convenience sample of nurses from homogeneous medical and surgical areas who work with cancer patients. A validated Italian version of the Professional Quality of Life Scale: Compassion Satisfaction and Fatigue was applied. Socio-demographic and professional classification variables were also recorded.</p> <p> </p>
Generative AI in Healthcare: Revolutionizing Patient Care and Medical Innovation
<p><a href="https://autorexa.com/transforming-patient-care-the-role-of-generative-ai-in-modern-healthcare/">Generative AI in Healthcare</a> is revolutionizing the medical field by enhancing diagnostics, accelerating drug discovery, enabling personalized treatments, and improving patient engagement. From creating synthetic medical images for training to developing tailored treatment plans, this technology is transforming patient care and medical research. With its ability to analyze vast datasets and automate complex processes, generative AI is driving efficiency, reducing costs, and delivering precise solutions. Learn how generative AI is shaping the future of healthcare with innovation, accuracy, and accessibility.</p>
DATA BASE Effectiveness of an educational intervention in the integral care of patients with DM2
<p>the database of the article is presented without sensitive data of the participants.</p>
Psychological Characteristics of patients with Takotsubo Syndrome and patients with Acute Coronary Syndrome: an explorative study toward a better personalized care
<p>Database of the paper: Psychological Characteristics of patients with Takotsubo Syndrome and patients with Acute Coronary Syndrome: an explorative study toward a better personalized care</p>
Satisfaction with Telemedicine for Cancer Pain Management: A Model of Care and Cross-Sectional Patient Satisfaction Study
<p>Background: Since cancer pain requires complex modalities of care, the proper strategy for addressing its telemedicine-based management should be better defined. This study aimed to trace a pathway for a progressive implementation of the telemedicine process for the treatment of pain in the setting of cancer patients. Methods: The features of the model were investigated to dissect the dropout from the telemedicine pathway. A cross-sectional patient satisfaction study was conducted. The degree of satisfaction was evaluated through a developed 22-item questionnaire (Likert scale 0–7). Results: A total of 375 video consultations for 164 patients (mean age 62.9 years) were performed through remote consultations for cancer pain management between March 2021 and February 2022. After the exclusion of 72 patients, 92 (56.1%) were included in the analysis. The dropout ratio was 8.7%. The number of visits and pharmacological therapies for neuropathic pain correlated with the risk for readmission (p < 0.05). Overall, the satisfaction was very high (mean > 5.5 for all items). Conclusion: Feedback from patients reflected high satisfaction rates with the care provided. A methodological approach based on the degree of satisfaction combined with the analysis of the pathways can help to implement the quality of a service provided through telemedicine. While not without limitations, our hybrid protocol can be useful for addressing cancer pain through a patient-centered approach.</p>
Utility index and vision related quality of life in patients awaiting specialist eye care
<p>Objectives:</p> <p>This study aimed to ascertain utility and vision-related quality of life in patients awaiting access to specialist eye care. A secondary aim was to evaluate the association of utility indices with demographic profile and waiting time.</p> <p>Methods:</p> <p>Consecutive patients that had been waiting for ophthalmology care answered the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25). The questionnaire was administered when patients arrived at the clinics for their first visit. We derived a utility index (VFQ-UI) from the patients' responses, then calculated the correlation between this index and waiting time and compared utility across demographic subgroups stratified by age, sex, and care setting.</p> <p>Results:</p> <p>536 individuals participated in the study (mean age 52.9±16.6 years; 370 women, 69% women). The median utility index was 0.85 (interquartile range [IQR] 0.70–0.92; minimum 0.40, maximum 0.97). The mean VFQ-25 score was 70.88±14.59. Utility correlated weakly and nonsignificantly with waiting time (-0.05, <em>P </em>= 0.24). It did not vary across age groups (<em>P </em>= 0.85) or care settings (<em>P </em>= 0.77). Utility was significantly lower for women (0.84, IQR 0.70–0.92) than men (0.87, IQR 0.73–0.93, <em>P </em>= 0.03), but the magnitude of this difference was small (Cohen's d = 0.13).</p> <p>Conclusion:</p> <p>Patients awaiting access to ophthalmology care had a utility index of 0.85 on a scale of 0 to 1. This measurement was not previously reported in the literature. Utility measures can provide insight into patients' perspectives and support economic health analyses and inform health policies.</p>
STROBE checklist_Study of compliance to treatment advised to patients attending medicine OPD in a tertiary care ruraral hospital
<p>STROBE checklist of the study titled, "Study of compliance to treatment advised to patients attending medicine OPD in a tertiary care ruraral hospital."</p>
Compliance worksheet_Study of compliance to treatment advised to patients attending medicine OPD in a tertiary care rural hospital
<p>This is a worksheet of the data obtained from the questionnaires used for the study titled, "Study of compliance to treatment advised to patients attending medicine OPD in a tertiary care rural hospital."</p>
Program of Intensive Support in Emergency Departments for Care Partners of Cognitively Impaired Patients
ClinicalTrials.gov study NCT03325608. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effectiveness of DECIDE in Patient-Provider Communication, Therapeutic Alliance & Care Continuation
ClinicalTrials.gov study NCT01947283. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Intravenous Exenatide in Coronary Intensive Care Unit (ICU) Patients
ClinicalTrials.gov study NCT00736229. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Reverse Innovation and Patient Engagement to Improve Quality of Care and Patient Outcomes
ClinicalTrials.gov study NCT02222909. IPD Sharing: NO. Countries: 1. Publications: 3.
Shared Decision-Making for Elderly Depressed Primary Care Patients
ClinicalTrials.gov study NCT01031134. IPD Sharing: NO. Countries: 1. Publications: 1.
Community Health Workers in an Interdisciplinary Outpatient CKD Clinic to Optimize Social Care Navigation, Patient Engagement, and Home Dialysis Utilization
ClinicalTrials.gov study NCT06925776. IPD Sharing: YES. Countries: 1. Publications: 14.
Integrated Multidisciplinary Patient and Family Advance Care Planning Trial
ClinicalTrials.gov study NCT03609658. IPD Sharing: NO. Countries: 1. Publications: 63.
Open Label Study Comparing Efficacy and Safety of Dabigatran Etexilate to Standard of Care in Paediatric Patients With Venous Thromboembolism (VTE)
ClinicalTrials.gov study NCT01895777. IPD Sharing: Not stated. Countries: 26. Publications: 4.
Supportive Care for Cognitively Impaired Patients and Families
ClinicalTrials.gov study NCT03881579. IPD Sharing: YES. Countries: 1. Publications: 0.
A Patient-Centered Communication Tool (UR-GOAL) Versus Usual Care for Older Patients With Acute Myeloid Leukemia, Their Caregivers, and Their Oncologists
ClinicalTrials.gov study NCT05335369. IPD Sharing: YES. Countries: 1. Publications: 3.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.