Patient-centered Data Research Articles

DiabeticChain: a novel blockchain approach for patient-centric diabetic data management

DiabeticChain: a novel blockchain approach for patient-centric diabetic data management

Patient feasibility as a novel approach for integrating IRT and LCA statistical models into patient-centric qualitative data-a pilot study.

Clinical research increasingly recognizes the role and value of patient-centric data incorporation in trial design, aiming for more relevant, feasible, and engaging studies for participating patients. Despite recognition, research on analytical models regarding qualitative patient data analysis has been insufficient. This pilot study aims to explore and demonstrate the analytical framework of the "patient feasibility" concept-a novel approach for integrating patient-centric data into clinical trial design using psychometric latent class analysis (LCA) and interval response theory (IRT) models. A qualitative survey was designed to capture the diverse experiences and attitudes of patients in an oncological indication. Results were subjected to content analysis and categorization as a preparatory phase of the study. The analytical phase further employed LCA and hybrid IRT models to discern distinct patient subgroups and characteristics related to patient feasibility. LCA identified three latent classes each with distinct characteristics pertaining to a latent trait defined as patient feasibility. Covariate analyses further highlighted subgroup behaviors. In addition, IRT analyses using the two-parameter logistic model, generalized partial credit model, and nominal response model highlighted further distinct characteristics of the studied group. The results provided insights into perceived treatment challenges, logistic challenges, and limiting factors regarding the standard of care therapy and clinical trial attitudes.

Carotid ultrasound to identify head and neck cancer survivors with high cardiovascular risk after radiation therapy: rationale and design of a prospective, cross-sectional pilot study.

Background: Radiation therapy is an integral component of treatment that can predispose to carotid artery stenosis (CAS) and increase the risk of cerebrovascular events for head and neck cancer survivors. The utility of screening for CAS with carotid ultrasound in asymptomatic head and neck cancer survivors is unclear.Methods: In this prospective, cross-sectional pilot study, 60 patients who have no evidence of cancer at least 2years from completion of RT will undergo screening carotid ultrasound to identify patients with high risk of cardiovascular events.Results: Outcomes will include clinically significant CAS, carotid intima-media thickness, acceptability/feasibility of screening, barriers to care and preliminary data on changes to medical management because of screening. Correlative multi-omics analyses will examine biomarkers of CAS after radiation therapy.Conclusion: The results of this study will provide valuable data on the prevalence of CAS and preliminary patient-centered data that will inform the design of a future large-scale, multi-site clinical trial.Clinical Trial Registration: NCT05490875 (ClinicalTrials.gov).

Otolaryngic Allergy Patient Journey Mapping: A Framework for Allergy Immunotherapy Adherence.

Allergen-specific immunotherapy (AIT) is an effective treatment for allergic disease but requires long treatment duration and premature cessation is of significant concern. Drivers of premature cessation remain poorly understood and no predictive models currently exist. We hypothesized that a novel patient journey map and de novo real-time patient electronic health status instruments (eHSIs) could effectively capture patient perceived cost, commitment, and treatment benefit to identify individual patients at risk for premature AIT cessation. Cross-Sectional Observational Study. A single Otolaryngology allergy immunotherapy (AIT) program was studied over 5 years. Instances of premature cessation were classified. An Otolaryngic Allergy Patient Journey Map was developed to identify and target automated, real-time, patient-reported, electronic health status instrument responses. Data capture was robust, with 61,406 data points collected and an eHSI survey completion rate of 81.3%. However, based on correlation analysis and logistic regression alone, real-time eHSI responses were not predictive of individual patient premature AIT cessation. A total of 597 AIT patients discontinued treatment prematurely: 64.4% stopping within the first year. Specifically, 74.0%-76.3% of subcutaneous AIT patients and 88.5%-100% of sublingual AIT patients did not complete the minimum recommended treatment duration of 3 years. Patient journey mapping can aid in the design of longitudinal care models and patient engagement strategies. Yet, eHSI patient responses of perception of AIT cost, benefit, and convenience did not correlate with the likelihood of premature treatment cessation. Our imperfect clinical intuition may not account for the dynamic drivers of premature AIT discontinuation. Future development of predictive tools feed by large patient-centric data sets may be incorporated into routine practice resulting in delivery of a more streamlined and personalized approach with reduced premature AIT cessation, improved outcomes, and reduced health care expenditures. NA Laryngoscope, 2024.

Breast implant illness: A United Kingdom patient-centred approach

Silicone breast implants are widely prevalent. An increasing group of patients detail self-reported somatic and psychological symptoms that have been ascribed as breast implant illness (BII) and seek capsulectomy and implant removal. To guide consultations and shared decision making, more outcome data relating to this intervention are required. To present a multicentre study of patient-centred (n = 100) outcome data, following total capsulectomy with implant removal for BII. A questionnaire survey was cross-referenced with medical records. Collected data included demographics, operation details, pre- and postoperative symptom scores, overall self-perceived percentage improvement in BII symptoms and breast shape satisfaction ratings after explantation. The 10 most frequently self-reported symptoms were fatigue (81%), pains/aches (72%), brain/memory fog (56%), mood disturbances (36%), neuropathic pain (28%), hair loss (28%), headaches (25%), gastric symptoms/intolerances (24%), eczema/rash (18%) and vision disturbance (17%). A high proportion of patients (98%) experienced a 62 ± 4% average symptom improvement; most self-reported symptoms (21/28) improved significantly after explantation with total capsulectomy (p < 0.05). Furthermore, patients had high overall self-perceived BII percentage improvement (76 ± 3%) and satisfaction with breast shape numerical rating score (8 ± 0.30) postoperatively. Despite BII not being a defined disease entity, symptom association with silicone breast implants continues for a growing number of patients. It is important to recognise that in this patient group, capsulectomy and implant removal may not be curative, however we have demonstrated that symptom improvement can occur. It is very difficult to prove a causal link between breast implants and BII; to do so will require extensive prospective data collection.

Real-world evidence evaluation of LDL-C in hospitalized patients: a population-based observational study in the timeframe 2021–2022

AimsEuropean registries and retrospective cohort studies have highlighted the failure to achieve low-density lipoprotein-cholesterol (LDL-C) targets in many very high-risk patients. Hospitalized patients are often frail, and frailty is associated with all-cause and cardiovascular mortality. The aim of this study is to evaluate LDL-C levels in a real-world inpatient setting, identifying cardiovascular risk categories and highlighting treatment gaps in the implementation of LDL-C management.MethodsThis retrospective, observational study included all adult patients admitted to an Italian hospital between 2021 and 2022 with available LDL-C values during hospitalization. Disease-related real-world data were collected from Hospital Information System using automated data extraction strategies and through the implementation of a patient-centered data repository (the Dyslipidemia Data Mart). We performed assessment of cardiovascular risk profiles, LDL-C target achievement according to the 2019 ESC/EAS guidelines, and use of lipid-lowering therapies (LLT).Results13,834 patients were included: 17.15%, 13.72%, 16.82% and 49.76% were low (L), moderate (M), high (H) and very high-risk (VH) patients, respectively. The percentage of on-target patients was progressively lower towards the worst categories (78.79% in L, 58.38% in M, 33.3% in H and 21.37% in VH). Among LLT treated patients, 28.48% were on-target in VH category, 47.60% in H, 69.12% in M and 68.47% in L. We also analyzed the impact of monotherapies and combination therapies on target achievement.ConclusionsWe found relevant gaps in LDL-C management in the population of inpatients, especially in the VH category. Future efforts should be aimed at reducing cardiovascular risk in these subjects.

Keys to Measuring Patient-Centered Care

A survey of the NEJM Catalyst Insights Council finds strong interest and engagement with a range of patient-centered data, including patient-reported outcomes measures.

Safety and quality of parenteral nutrition: Areas for improvement and future perspectives.

This article is based on presentations and discussions held at the International Safety and Quality of Parenteral Nutrition (PN) Summit (held November 8-10, 2021, at Charleston, SC, and Bad Homburg, Germany) and aims to raise awareness concerning unresolved issues associated with the PN process and potential future directions, including a greater emphasis on patients' perspectives and the role of patient support. Ensuring that every patient in need receives adequate PN support remains challenging. It is important to have a standardized approach to identify nutritional risk and requirements using validated nutritional screening and assessment tools. Gaps between optimal and actual clinical practices need to be identified and closed, and responsibilities in the nutrition support team clarified. Use of modern technology opens up opportunities to decrease workloads or liberate resources, allowing a more personalized care approach. Patient-centered care has gained in importance and is an emerging topic within clinical nutrition, in part because patients often have different priorities and concerns than healthcare professionals. Regular assessment of health-related quality of life, functional outcomes, and/or overall patient well-being should all be performed for PN patients. This will generate patient-centric data, which should be integrated into care plans. Finally, communication and patient education are prerequisites for patients' commitment to health and for fostering adherence to PN regimes. Moving closer to optimal nutritional care requires input from healthcare professionals and patients. Patient-centered care and greater emphasis on patient perspectives and priorities within clinical nutrition are essential to help further improve clinical nutrition.

Non-fungible tokens (NFTs) in healthcare: a thematic analysis and research agenda.

In the big data era, where corporations commodify health data, non-fungible tokens (NFTs) present a transformative avenue for patient empowerment and control. NFTs are unique digital assets on the blockchain, representing ownership of digital objects, including health data. By minting their data as NFTs, patients can track access, monetize its use, and build secure, private health information systems. However, research on NFTs in healthcare is in its infancy, warranting a comprehensive review. This study conducted a systematic literature review and thematic analysis of NFTs in healthcare to identify use cases, design models, and key challenges. Five multidisciplinary research databases (Scopus, Web of Science, Google Scholar, IEEE Explore, Elsevier Science Direct) were searched. The approach involved four stages: paper collection, inclusion/exclusion criteria application, screening, full-text reading, and quality assessment. A classification and coding framework was employed. Thematic analysis followed six steps: data familiarization, initial code generation, theme searching, theme review, theme definition/naming, and report production. Analysis of 19 selected papers revealed three primary use cases: patient-centric data management, supply chain management for data provenance, and digital twin development. Notably, most solutions were prototypes or frameworks without real-world implementations. Four overarching themes emerged: data governance (ownership, tracking, privacy), data monetization (commercialization, incentivization, sharing), data protection, and data storage. The focus lies on user-controlled, private, and secure health data solutions. Additionally, data commodification is explored, with mechanisms proposed to incentivize data maintenance and sharing. NFTs are also suggested for tracking medical products in supply chains, ensuring data integrity and provenance. Ethereum and similar platforms dominate NFT minting, while compact NFT storage options are being explored for faster data access. NFTs offer significant potential for secure, traceable, decentralized healthcare data exchange systems. However, challenges exist, including dependence on blockchain, interoperability issues, and associated costs. The review identified research gaps, such as developing dual ownership models and data pricing strategies. Building an open standard for interoperability and adoption is crucial. The scalability, security, and privacy of NFT-backed healthcare applications require further investigation. Thus, this study proposes a research agenda for adopting NFTs in healthcare, focusing on governance, storage models, and perceptions.

A unique model: Partnership between community oncology and pharma for clinical trial enrichment.

1535 Background: Clinical trials are the foundation of oncologic drug development. Historically, only 23% of oncology trials are conducted in the community despite &gt;70% of patients being treated this setting, leading to a disconnect between the therapy being tested and target population. Also, patients are hesitant to enroll in trials- in 2020, only 49% were willing, down from 85% in 2019. One way to improve this is participation by community oncologists, allowing patients to stay close to home. Targeted therapies are increasingly being approved by the FDA, with 89 small molecule drugs approved by 2020. Given the above landscape, Precision Health Informatics (PHI) collaborated with Mirati Therapeutics to pilot a clinical trial enrichment program focused on increasing enrollment of patients in the community related to efficacy and outcomes of adagrasib (KRAS G12C inhibitor) for NSCLC and CRC. Methods: This pilot was launched in 2021, with a prescreening study (DetECT) to find eligible patients with KRASG12C mutations. The pilot was then expanded across Mirati ‘Krystal’ studies in 2022 and to “1719” studies in 2023. These studies were available to all investigators throughout Texas Oncology (TxO) via STAR model (clinical trial access to all TxO investigators/sites through a regulated but rapid approval process). Eligible patients were identified from PHI’s proprietary molecular data warehouse (that stores molecular results for &gt;400,000 patients treated at TxO). A data analyst identified patients with KRAS G12C mutation from the warehouse, and then cross-referenced patient-centric data in EMR to assess eligibility. The treating physician was then alerted of their patient’s eligibility. Patient demographic information was also collected from the EMR. Results: This collaboration resulted in accrual of 118 patients, engagement of 40 different PIs, across 8 different trials. 6 studies remain open across the practice. 21 patients were enrolled on Krystal-001, 7 on Krystal-007, 10 on Krystal-010 and 56 on DetECT. Enrollment was inclusive of patients from urban areas of DFW as well as rural populations in NE Texas, South and West Texas. In DetECT, TxO provided 84% of the total US enrollment, with a diverse population – 54% white, 23% Hispanic, 12% black, 9% Asian. Texas Oncology is the 2nd highest screening and enrolling site on Krystal studies. Conclusions: This pilot successfully demonstrates that community oncology can lead the way in clinical trial enrollment, even in early phase targeted therapy studies. Community physicians can be engaged so patients can benefit from research participation close to home. This model shows that a diverse population was accrued and may serve as a blueprint to help Pharma satisfy the diversity requirements for clinical trials. PHI, with its molecular database, may partner with Pharma to identify targetable mutations and drive rapid trial enrollment for targeted therapies.

Patient interpretations of patient-reported outcome measures to assess bowel urgency: qualitative interviews in ulcerative colitis

ObjectivesBowel urgency is an impactful core symptom of ulcerative colitis (UC). Patient-reported outcome (PRO) questionnaires have been developed and used to assess the patient experience of this important symptom. The objective of this paper is to present evidence from qualitative research conducted to support the use and interpretation of select PRO questionnaires to assess bowel urgency related to the UC patient experience.MethodsQualitative interviews were conducted with ten adults with a clinician-confirmed diagnosis of moderately to severely active UC. Interviews aimed to document patient interpretation of modified recall periods for the Urgency Numeric Rating Scale (Urgency NRS), two global assessments (i.e., the Patient Global Impression of Severity [PGIS] and Patient Global Impression of Change [PGIC]), and four items (Items 11, 16, 23, and 26) of the Inflammatory Bowel Disease Questionnaire (IBDQ), and explore the patient perspective of meaningful change on these questionnaires.ResultsBoth modified Urgency NRS versions (with 7-day or 3-day recall period) were interpreted as intended by most patients (≥ 88.9%), and slightly more than half of patients (60.0%) reported that the 7-day recall period was more relevant to their bowel urgency experience. Patients reported thinking of bowel urgency (≥ 80.0%) or bowel urgency-related accidents (70.0% of patients) when interpreting the global assessments and IBDQ items. Most patients reported a 1- to 3-point change as the smallest meaningful improvement that would be meaningful on the Urgency NRS (similar to findings on other questionnaires).ConclusionAdults with UC can understand and respond to the Urgency NRS with modified recall periods (i.e., 7-day or 3-day), interpret the conceptual content of the PGIS, PGIC, and select IBDQ items to be inclusive of bowel urgency and bowel urgency-related accidents, and select answers representing meaningful improvements on the Urgency NRS, PGIS, PGIC, and IBDQ item response scales. These results further contribute patient-centered data to existing UC and bowel urgency research.

Artificial intelligence based data curation: enabling a patient-centric European health data space.

The emerging European Health Data Space (EHDS) Regulation opens new prospects for large-scale sharing and re-use of health data. Yet, the proposed regulation suffers from two important limitations: it is designed to benefit the whole population with limited consideration for individuals, and the generation of secondary datasets from heterogeneous, unlinked patient data will remain burdensome. AIDAVA, a Horizon Europe project that started in September 2022, proposes to address both shortcomings by providing patients with an AI-based virtual assistant that maximises automation in the integration and transformation of their health data into an interoperable, longitudinal health record. This personal record can then be used to inform patient-related decisions at the point of care, whether this is the usual point of care or a possible cross-border point of care. The personal record can also be used to generate population datasets for research and policymaking. The proposed solution will enable a much-needed paradigm shift in health data management, implementing a 'curate once at patient level, use many times' approach, primarily for the benefit of patients and their care providers, but also for more efficient generation of high-quality secondary datasets. After 15 months, the project shows promising preliminary results in achieving automation in the integration and transformation of heterogeneous data of each individual patient, once the content of the data sources managed by the data holders has been formally described. Additionally, the conceptualization phase of the project identified a set of recommendations for the development of a patient-centric EHDS, significantly facilitating the generation of data for secondary use.

Real-world evidence evaluation of LDL-C among hospitalized patients: a population-based observational study in the timeframe 2021-2022

Aims. European registries and retrospective cohorts highlighted the lack of low-density lipoprotein-cholesterol (LDL-C) goal achievement in many very high-risk patients. Hospitalized patients are often frail, and frailty is associated with all-cause mortality and cardiovascular mortality. Aim of this study is to evaluate LDL-C levels in a Real-World setting of inpatients, identify cardiovascular risk categories and highlight treatment gaps in the implementation of LDL-C control. Methods. This retrospective, observational study included all the adult patients admitted at an Italian hospital between 2021-2022 and with LDL-C values available during hospitalization. Disease-related real-world data were collected from Hospital Information Systems using automated data extraction strategies and through the implementation of a patient-centered data repository (the Dyslipidemia Data Mart). Assessment of cardiovascular risk profiles, LDL-C target achievement according to the 2019 ESC/EAS guidelines and lipid-lowering therapies (LLT) use were performed. Results. 13,834 patients were included: 17.15%, 13.72%, 16.82% and 49.76% were low (L), moderate (M), high (H) and very high-risk (VH) patients, respectively. The percentage of in-target patients was progressively lower moving towards worse categories (78.79% in L, 58.38% in M, 33.3% in H and 21.37% in VH). Among LLT treated patients in VH category, in-target are 28.48%; 47.6.% in H, 69.12% in M and 68.47% in L. The impact of monotherapies and combination therapies on target achievement was also analyzed. Conclusions. This study depicts LDL-C control among an entire population of inpatients, highlighting relevant gaps especially in VH category. Future efforts must aim to reduce the cardiovascular risk of these subjects.

Attribute-based key management for patient-centric and trusted data access in blockchain-enabled IoMT

Internet of Medical Things (IoMT) provides real-time data collection and access services to medical entities by connecting their devices to Internet. However, within such a complex architecture, achieving patient-centric data access still presents trustworthiness challenges of transmission security and usage reliability. Ciphertext-policy attribute-based encryption (CP-ABE) and blockchain are both the promising primitives that support patients with secure access control over their data. Nevertheless, both have their unique key management issues. In this paper, we propose a novel patient-centric and trusted data access (PCT-DA) system in blockchain-enabled IoMT. Firstly, we develop an online/offline encryption and verifiable outsourced decryption CP-ABE scheme to relieve the computation pressure on patients and users. Secondly, we design a flexible attribute-based key management mechanism to overcome the security drawbacks of encryption and attribute keys, such as single point of failure, key escrow and privacy leakage. Finally, we build a trusted integrity audit contract to guarantee the incentive fairness between patients and users in access services. Moreover, theoretical analyses prove that the PCT-DA system not only achieves confidentiality, integrity, traceability and forward/backward security, but also guarantees static security under random oracles. Simulation experiments indicate that our proposal reduces the time cost by approximately 14.10 seconds over state-of-the-art and is more practical in blockchain-enabled IoMT system.

Racial disparities with PRN medication usage in inpatient psychiatric treatment

Racial disparities in psychiatric diagnoses and treatment have significant public health implications, contributing to inequities in healthcare outcomes. We specifically examined racial disparities regarding pro re nata (PRN), or as needed, medications. Data from 14,616 encounters across 2019–2020 within Community Health Network’s inpatient psychiatric setting in Indianapolis, Indiana were included in this study. Due to the demographic sample size, analyses were narrowed to Black and White patients. Primary outcomes included comparisons across race for all PRN administrations and PRN administrations of antipsychotics vs. non-antipsychotics. Logistic regression was used to examine associations between race and PRN administrations by medication category, including all antipsychotics vs. non-antipsychotics overall, hydroxyzine, and lorazepam, independently. Significant differences in the percentage of administrations between Black and White patients were observed. Black patients received more PRN medications overall (71.0%) compared to White patients (67.7%) (p < 0.01). Further, while 17.7% of Black patients were administered PRN antipsychotics, this was true for only 8.2% of White patients (p < 0.001). When comparing antipsychotic PRNs with non-antipsychotic, hydroxyzine, and lorazepam PRNs, independently, Black patients were 58% (OR 1.58, p < 0.001), 109% (OR 2.09, p < 0.001), and 32% (OR 1.32, p < 0.001), more likely to receive antipsychotic PRNs, respectively, than White patients, controlling for sex, age, length of stay, and psychotic disorder diagnosis. Our study identifies yet another area of medical care with significant racial disparities. In this analysis of PRN medications during psychiatric admission, we identified significant differences in medication utilization by race. This information provides a basis for further investigation of disparities in patient-centered data.

Hospital Management System using Blockchain

Electronic health records are health information of patients that are saved digitally in a network. The information of the patient are stored in the blockchain and these details are stored in the block chain as a blocks of data. The data is encrypted by the algorithm known as AES which is used to encrypt all the data of the patients. A Blockchain network is used in the healthcare system to exchange patient data improve the performance, security, and transparency of sharing medical data in the health care system. The three main feature of blockchain techonlogy security. Decentralization Transparency make any application secure and not accessible by unauthorized parties. Key Words: Health records, Blockchain, Encryption of data, Decryption of data, Security.

Perspectives from persons living with dementia and their caregivers on emergency department visits, care transitions, and outpatient follow-up: A qualitative study.

Persons living with dementia (PLWD) experience frequent and costly emergency department (ED) visits, with poor outcomes attributed to suboptimal care and postdischarge care transitions. Yet, patient-centered data on ED care experiences and postdischarge needs are lacking. The objective of this study was to examine the facilitators and barriers to successful ED care and care transitions after discharge, according to PLWD and their caregivers. We conducted a qualitative study involving ED patients ages 65 and older with confirmed or suspected dementia and their caregivers. The semistructured interview protocol followed the National Quality Forum's ED Transitions of Care Framework and addressed ED care, care transitions, and outpatient follow-up care. Interviews were conducted during an ED visit at an urban, academic ED. Traditional thematic analysis was used to identify themes. We interviewed 11 patients and 19 caregivers. Caregivers were more forthcoming than patients about facilitators and challenges experienced. Characteristics of the patients' condition (e.g., resistance to care, forgetfulness), the availability of family resources (e.g., caregiver availability, primary care access), and system-level factors (e.g., availability of timely appointments, hospital policies tailored to persons with dementia) served as facilitators and barriers to successful care. Some resources that would ameliorate care transition barriers could be easily provided in the ED, for example, offering clear discharge instructions and care coordination services and improving patient communication regarding disposition timeline. Other interventions would require investment from other parts of the health care system (e.g., respite for caregivers, broader insurance coverage). ED care and care transitions for PLWD are suboptimal, and patient-level factors may exacerbate existing system-level deficiencies. Insight from patients and their caregivers may inform the development of ED interventions to design specialized care for this patient population. This qualitative study also demonstrated the feasibility of conducting ED-based studies on PLWD during their ED visit.

Patient experience of medication administration and development of a Patient Experience and Preference Questionnaire (PEPQ) for patients with advanced or metastatic cancer.

Introduction: A better understanding of patient experience of intravenous (IV) or subcutaneous (SC) routes of administration is fundamental to providing optimal administration of medical therapies to oncology patients. The objective of this study was to examine patient experiences of IV and SC treatment with nivolumab and confirm the relevance of item concepts in the Patient Experience and Preference Questionnaire (PEPQ). The PEPQ is a clinical outcomes' assessment instrument developed to obtain patient-centric data and understand the experience with IV and SC treatment administration. Methods: Embedded qualitative interviews were conducted with a subset of participants from three treatment cohorts with metastatic non-small-cell lung cancer (NSCLC), renal cell carcinoma (RCC), unresectable or advanced metastatic melanoma, hepatocellular carcinoma (HCC), or colorectal cancer (CRC) from the CA209-8KX clinical trial. Concept elicitation interviews were conducted within 14days of the initial treatment cycle and patient experiences with IV and SC treatment administration were assessed. Concepts from interviews were mapped to the PEPQ version 1.0 questions to assess relevance and convergence of concepts. Results: Interviews were conducted with 43 trial participants from clinical sites opting to participate from six countries (Argentina, France, the Netherlands, Poland, Spain, and New Zealand). The mean age of sub-study participants was 66 ± 11.3years (range 24-80years), and 67.4% (N = 29) were male. Sub-study participants with experience of SC most frequently reported symptoms or signs of injection-related redness (27.9%), itching (14.0%), and pain (of needle), and described the pain as pricking, stinging, or tingling (11.0% each). The amount of pain and time burden were widely endorsed as important factors for satisfaction and related to the route of medication administration. For 11 sub-study participants with experience with both IV and SC treatments, 10 (90.9%) preferred SC over IV treatment administration. Conclusion: This study summarizes the experience and satisfaction of receiving IV or SC treatment and confirms the relevance of the PEPQ in a subgroup of CA209-8KX clinical trial participants with metastatic NSCLC, RCC, melanoma, HCC, and CRC. Participant treatment experience and satisfaction with the route of medication mapped to the PEPQ question content support the relevance of PEPQ v2.0 in clinical trials as a self-report measure.

Postoperative outcomes of transperitoneal versus retroperitoneal robotic partial nephrectomy: a propensity-score matched comparison focused on patient mobilization, return to bowel function, and pain

Literature meta-analyses comparing transperitoneal versus retroperitoneal approach to robotic partial nephrectomy (RPN) suggested some advantages favoring retroperitoneoscopy. Unfortunately, patient-centered data about mobilization, canalization, pain, and use of painkillers remained anecdotally reported. The present analysis aimed to compare transperitoneal versus retroperitoneal RPN focusing on such outcomes. Study data including baseline variables, perioperative, and postoperative outcomes of interest were retrieved from prospectively maintained institutional database (Jan 2018–May 2023) and compared between treatment groups (transperitoneal versus retroperitoneal). Propensity score matching was performed using the STATA command psmatch2 considering age, sex, body mass index, previous abdominal surgery, RENAL score, tumor size and location, and cT stage. The logit of propensity score was used for matching, with a 1:1 nearest neighbor algorithm, without replacement (caliper of 0.001). A total of 442 patients were included in the unmatched analysis: 330 underwent transperitoneal RPN 112 retroperitoneal RPN. After propensity score, 98 patients who underwent retroperitoneal RPN were matched with 98 patients who underwent transperitoneal RPN. Matched cohorts had comparable patients’ demographics and tumor features. We found similarity between the two laparoscopic accesses in all outcomes but in blood loss, which favored retroperitoneoscopic RPN (median 150 (IQR 100–300) versus 100 (IQR 0–100) ml, p = 0.03). No differences were found in terms of time to mobilization with ambulation, return to complete bowel function, postoperative pain, but higher painkillers consumption was reported after transperitoneal RPN (p < 0.004). The present study compared the transperitoneal versus the retroperitoneal approach to RPN, confirming the similarity between the two approaches in all perioperative outcomes. Based on our findings, the choice of the surgical approach to RPN may remain something that the surgeon decides.

Data analytics in healthcare: A review of patient-centric approaches and healthcare delivery

The integration of data analytics in healthcare has revolutionized the industry, ushering in a new era of personalized and patient-centric approaches to healthcare delivery. This review explores the multifaceted role of data analytics in reshaping the landscape of healthcare, with a specific focus on patient-centric methodologies and their impact on healthcare delivery. The advent of electronic health records (EHRs) and wearable devices has generated an unprecedented volume of healthcare data. Leveraging advanced analytics, healthcare providers can extract valuable insights from this data to enhance patient care. Patient-centric approaches involve the utilization of individualized health data to tailor treatment plans, predict disease outcomes, and optimize preventive measures. This review delves into the methodologies employed in patient-centric data analytics, examining the utilization of machine learning algorithms, predictive modeling, and artificial intelligence to develop personalized healthcare interventions. Furthermore, the review explores the transformative impact of data analytics on healthcare delivery. The optimization of operational processes, resource allocation, and the identification of cost-effective interventions are vital components of healthcare management. By harnessing the power of data analytics, healthcare systems can streamline their operations, reduce inefficiencies, and allocate resources more effectively. Additionally, predictive analytics aids in forecasting disease outbreaks, enabling proactive measures for containment and resource allocation. The review also highlights the ethical considerations and challenges associated with the implementation of data analytics in healthcare. Patient privacy, data security, and the responsible use of sensitive health information are critical aspects that demand careful attention in the era of digital healthcare. This review underscores the pivotal role of data analytics in fostering patient-centric healthcare approaches and optimizing healthcare delivery. As the healthcare industry continues to evolve, the integration of advanced analytics promises to revolutionize the way healthcare is administered, ensuring a more personalized, efficient, and effective approach to patient well-being.