Patient-reported Data Research Articles

Collecting Real-Time Patient-Reported Outcome Data During Latent Labor: Feasibility Study of the MyCap Mobile App in Prospective Person-Centered Research.

The growing emphasis on patient experience in medical research has increased the focus on patient-reported outcomes and symptom measures. However, patient-reported outcomes data are subject to recall bias, limiting reliability. Patient-reported data are most valid when reported by patients in real time; however, this type of data is difficult to collect from patients experiencing acute health events such as labor. Mobile technologies such as the MyCap app, integrated with the REDCap (Research Electronic Data Capture) platform, have emerged as tools for collecting patient-generated health data in real time offering potential improvements in data quality and relevance. This study aimed to evaluate the feasibility of using MyCap for real-time, patient-reported data collection during latent labor. The objective was to assess the usability of MyCap in characterizing patient experiences during this acute health event and to identify any challenges in data collection that could inform future research. In this descriptive cohort study, we quantified and characterized data collected prospectively through MyCap and the extent to which participants engaged with the app as a research tool for collecting patient-reported data in real time. Longitudinal quantitative and qualitative surveys were sent to (N=18) enrolled patients with term pregnancies planning vaginal birth at Oregon Health Sciences University. Participants were trained in app use prenatally. Then participants were invited to initiate the research survey on their personal smartphone via MyCap when they experienced labor symptoms and were asked to return to MyCap every 3 hours to provide additional longitudinal symptom data. Out of 18 enrolled participants, 17 completed the study. During latent labor, 13 (76.5%) participants (all those who labored at home and two-thirds of those who were induced) recorded at least 1 symptom report during latent labor. A total of 191 quantitative symptom reports (mean of 10 per participant) were recorded. The most commonly reported symptoms were fatigue, contractions, and pain, with nausea and diarrhea being less frequent but more intense. Four participants recorded qualitative data during labor and 14 responded to qualitative prompts in the postpartum period. The study demonstrated that MyCap could effectively capture real-time patient-reported data during latent labor, although qualitative data collection during active symptoms was less robust. MyCap is a feasible tool for collecting prospective data on patient-reported symptoms during latent labor. Participants engaged actively with quantitative symptom reporting, though qualitative data collection was more challenging. The use of MyCap appears to reduce recall bias and facilitate more accurate data collection for patient-reported symptoms during acute health events outside of health care settings. Future research should explore strategies to enhance qualitative data collection and assess the tool's usability across more diverse populations and disease states.

Machine learning models including patient-reported outcome data in oncology: a systematic literature review and analysis of their reporting quality.

To critically examine the current state of machine learning (ML) models including patient-reported outcome measure (PROM) scores in cancer research, by investigating the reporting quality of currently available studies and proposing areas of improvement for future use of ML in the field. PubMed and Web of Science were systematically searched for publications of studies on patients with cancer applying ML models with PROM scores as either predictors or outcomes. The reporting quality of applied ML models was assessed utilizing an adapted version of the MI-CLAIM (Minimum Information about CLinical Artificial Intelligence Modelling) checklist. The key variables of the checklist are study design, data preparation, model development, optimization, performance, and examination. Reproducibility and transparency complement the reporting quality criteria. The literature search yielded 1634 hits, of which 52 (3.2%) were eligible. Thirty-six (69.2%) publications included PROM scores as a predictor and 32 (61.5%) as an outcome. Results of the reporting quality appraisal indicate a potential for improvement, especially in the areas of model examination. According to the standards of the MI-CLAIM checklist, the reporting quality of ML models in included studies proved to be low. Only nine (17.3%) publications present a discussion about the clinical applicability of the developed model and reproducibility and only three (5.8%) provide a code to reproduce the model and the results. The herein performed critical examination of the status quo of the application of ML models including PROM scores in published oncological studies allowed the identification of areas of improvement for reporting and future use of ML in the field.

A Pilot Study on the Collection of Adverse Event Data from the Patient Using an Electronic Platform in a Cancer Clinical Trial Unit.

Accurate and robust adverse event (AE) data collection is crucial in cancer clinical trials to ensure participant safety. Frameworks have been developed to facilitate the collection of AE data and now the traditional workflows are facing renewal to include patient-reported data, improving completeness of AE data. We explored one of these workflows in a cancer clinical trial unit. The study was a single-site study conducted at a tertiary hospital located in Australia. Patients consenting to a clinical trial were eligible for inclusion in this study. Participants used an electronic platform-My Health My Way (MHMW)-to report their symptomatic data weekly for 24 weeks. A symptom list was included within the platform, along with a free text field. Data reported via the platform was compared with data recorded in the patient's medical chart. Time taken to compile data from each source was recorded, along with missing data points. Agreement between patient-reported data and data recorded in the medical notes was assessed using Kappa and Gwet's AC1; time taken to compile data and missing data points were assessed using a Wilcoxon signed rank test. Low agreement was found between patient- and clinician-reported data (-0.482 and -0.159 by Kappa and Gwet's AC1 respectively). Only 127 (30%) of the total 428 AEs were reported by both MHMW and medical notes. Patients reported higher rates of symptoms from the symptom list, while clinicians reported higher rates of symptoms outside of the symptom list. Time taken to compile the data from MHMW was significantly less than that taken to review medical notes (2.19min versus 5.73min respectively; P < 0.001). There were significantly less missing data points from the MHMW data compared with the medical notes (1.4 versus 7.8; P<0.001). This study confirms previous reports that patient- and clinician-reported adverse event data show low agreement. This study also shows that clinical trial sites could significantly reduce the work performed by research staff in the collection of adverse event data by implementing an electronic, patient-reported platform.

Identifying and Optimizing Psychosocial Frailty in Surgical Practice

Psychosocial frailty is under-screened for and under-treated in patients undergoing surgery, even though patients with psychosocial frailty are at increased risk for postoperative complications. Numerous approaches exist to identifying psychosocial frailty in the preoperative period, ranging from neighborhood-level indices to patient-level, patient-reported data. Presurgical optimization of psychosocial frailty has returned mixed results, focusing primarily on psychological well-being with limited attention paid to addressing a patient's social risk profile. Mediators of psychosocial frailty in surgical outcomes must be further elucidated before investigators can appropriately trial psychosocial optimization programs that benefit patients. In recent years, new policies and system-level changes have incentivized screening for psychosocial frailty, and additional reimbursement strategies should be formulated to address frailty in the preoperative period in a feasible, sustainable, and cost-effective manner.

Analyzing patient-reported outcome data in oncology care

Analyzing patient-reported outcome data in oncology care

Comparing Pain Outcomes and Treatment Adherence Between In-Person and Virtual Interdisciplinary Pain Rehabilitation Programs at the San Francisco VA Health Care System.

This study compares clinical pain outcomes between patients in a pain treatment program that was conducted in-person, compared to a virtual program. In-Person (N=127) and Virtual (N=101) pain treatment programs were compared based on patient-reported, practitioner-collected, and medical record data. The patients were measured at baseline and post treatment (week 12 for In-Person and week 8 for Virtual patients). We employed last observation carried forward (LOCF) to handle missing data. Both the In-Person and Virtual groups were similar in regard to all baseline outcomes, except the In-Person group having significantly more co-morbidities at baseline, with particularly more cases of mental, behavioral, or neurodevelopmental diseases. Both groups demonstrated significant improvements in the pain-related measurements of pain interference and pain catastrophizing thoughts, but neither group displayed a change in average pain across treatment. Further, both groups improved significantly on emotional well-being scores, but not on physical functioning scores. No significant differences existed between groups on outcomes, except for pain catastrophizing, which was higher in the Virtual group at both time points. The Virtual group had lower rates of dropouts compared to In-Person, while the In-Person group had a larger proportion reach a clinically meaningful change in pain-related outcomes, defined as a >30% improvement. While some changes were unique to the In-Person program, overall, patients in the Virtual program achieved similar treatment outcomes, suggesting that it can successfully treat Veterans seeking pain management, with less need for in-person facilities for both patients and clinicians.

Use of Patient-Reported Outcomes in Risk Prediction Model Development to Support Cancer Care Delivery: A Scoping Review.

The integration of patient-reported outcomes (PROs) into electronic health records (EHRs) has enabled systematic collection of symptom data to manage post-treatment symptoms. The use and integration of PRO data into routine care are associated with overall treatment success, adherence, and satisfaction. Clinical trials have demonstrated the prognostic value of PROs including physical function and global health status in predicting survival. It is unknown to what extent routinely collected PRO data are used in the development of risk prediction models (RPMs) in oncology care. The objective of the scoping review is to assess how PROs are used to train risk RPMs to predict patient outcomes in oncology care. Using the scoping review methodology outlined in the Joanna Briggs Institute Manual for Evidence Synthesis, we searched four databases (MEDLINE, CINAHL, Embase, and Web of Science) to locate peer-reviewed oncology articles that used PROs as predictors to train models. Study characteristics including settings, clinical outcomes, and model training, testing, validation, and performance data were extracted for analyses. Of the 1,254 studies identified, 18 met inclusion criteria. Most studies performed retrospective analyses of prospectively collected PRO data to build prediction models. Post-treatment survival was the most common outcome predicted. Discriminative performance of models trained using PROs was better than models trained without PROs. Most studies did not report model calibration. Systematic collection of PROs in routine practice provides an opportunity to use patient-reported data to develop RPMs. Model performance improves when PROs are used in combination with other comprehensive data sources.

Implementation of Measurement-Based Care in Mental Health Service Settings for Youth: A Systematic Review.

Measurement-Based Care (MBC) is the systematic use of patient-reported data to inform care decisions and monitor treatment progress. MBC has been shown to improve patient outcomes across medical and mental health treatment settings for adults and youth. While many studies have examined the use of MBC in specific care settings, few have focused on the implementation of MBC among youth populations or across care settings. While a review has shown that use of MBC benefits youth, no published reviews exist that summarize the successful strategies and barriers to implementation models across studies in youth service settings. To address these gaps, the present systematic review (N = 25 studies) focuses on the implementation of MBC across four youth service settings, including outpatient mental health centers, medical centers/pediatric clinics, schools, and clinical psychology training clinics. Results suggest that few studies employ consistent implementation models or strategies to guide efforts. Further, there is significant overlap in the successful strategies employed as well as the barriers to implementation of MBC across youth service settings, at the client, clinician, and organizational levels. Broadly, the authors recommend on the basis of findings that future implementation work in youth service settings: incorporate comprehensive training in the use of MBC for clinicians; incorporate stakeholder feedback into the implementation process for initial and sustained use; employ digital measurement feedback systems to deliver MBC that allow for real-time feedback and continuous technical support; and employ a health equity lens in implementation efforts to help address disparities in access to and use of MBC so that all youth and families may benefit from this evidence-based practice.

6.H. Round table: Harnessing Patient-Reported Data for Health Innovation: Insights from the OECD PaRIS Initiative

Abstract Summary This round table will disseminate knowledge and foster discussions on data reported by patients with a chronic disease in primary care settings in 20 countries for enhancing health system responsiveness and effectiveness. By delving into the OECD’s Patient-Reported Indicator Surveys (PaRIS) survey’s development, adaptation, and analytical strategies, participants will leave with a richer understanding of how patient-reported data can inform and transform health policy and practice in Europe and beyond. Rationale The round table aligns with the Conference theme by focusing on the transformative potential of patient-reported data in health systems. OECD PaRIS provide a unique lens through which to examine patient-centered care, showcasing innovative methods to capture and utilize data across diverse health system contexts. This round table will explore the development, adaptation, and analysis of this flagship survey, revealing its critical role in shaping health policies and practices that are attuned to patient needs and experiences. Objectives 1. Understanding Development and Testing Processes: To gain insights into the systematic approaches used in developing patient-reported instruments that are both robust and sensitive across multiple healthcare settings; 2. Exploring Co-development and Adaptation: To discuss the challenges and strategies involved in adapting health surveys to various national contexts while ensuring stakeholder engagement and data relevancy; 3. Analyzing Data for Policy Making: To comprehend the analytical frameworks used in processing patient-reported data for crafting effective health policies and identifying factors that influence patient outcomes. Key messages • Patient reported data on experiences and outcomes provide essential information for health systems performance. • Unique insights into the systematic collection of such information can be gathered through the proposed discussion on the experience of designing and implementing the PaRIS Survey.

Revealed and stated preferences for sharing of patient-reported data in Austria

Abstract Objectives Routine collection of health data is essential for creating sustainable, efficient, and equitable health systems. While administrative health data are collected automatically, successful routine collection of patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) depends on voluntary participation. The aim of this study is to investigate how to increase participation in routine patient-reported data collection. Methods This mixed methods study used representative survey data from the Austrian population aged 18-70 (N = 1260) and 15 semi-structured narrative interviews with citizens and health data experts collected in 2024. Survey respondents were shown examples of PREMs and PROMs and indicated their willingness to share them, depending on the recipient and purpose. Interviewees answered the same questions while providing insight into their decision-making process, which was analyzed using thematic analysis. Wilcoxon rank sum tests were used to assess differences in willingness to share across recipients and data collection purposes. Results Survey respondents were more willing to share PREMs than PROMs (“rather yes” vs. “rather no”, p &amp;lt; 0.001). One explanation given in the interviews is that PROMs are more personal and convey sensitive information. In terms of sharing PROMs, people were most likely to share with their GP (81%) and least likely to share with private companies (7%). Facilitators for sharing identified in the interviews were improving personal care and the health system, while barriers were use for profit generation and fear of negative consequences for the person sharing. Conclusions The results suggest handling the collection of PROMs demands greater caution compared to PREMs. Furthermore, clearly communicating personal and societal benefits arising from the collection and analysis of self-reported health data may increase participation in routine self-reported health data collection. Key messages • The collection of self-reported health data depends on voluntary participation. Clearly communicating personal and societal benefits of sharing self-reported data can motivate participation. • Self-reported data collection is essential for sustainable and efficient health systems. Compared to PREMs, people are more reluctant to share PROMs because they contain sensitive information.

Measurement-Based Care in a Remote Intensive Outpatient Program: Pilot Implementation Initiative.

The ongoing mental health crisis, especially among youth, has led to a greater demand for intensive treatment at the intermediate level, such as intensive outpatient programs (IOPs). Defining best practices in remote IOPs more broadly is critical to understanding the impact of these offerings for individuals with high-acuity mental health service needs in the outpatient setting. Measurement-based care (MBC), or the routine and systematic collection of patient-reported data throughout the course of care to make meaningful changes to treatment, is one such practice that has been shown to improve patient outcomes in mental health treatment. Despite the literature linking MBC to beneficial clinical outcomes, the adoption of MBC in clinical practice has been slow and inconsistent, and more research is needed around MBC in youth-serving settings. The aim of this paper is to help bridge these gaps, illustrating the implementation of MBC within an organization that provides remote-first, youth-oriented IOP for individuals with high-acuity psychiatric needs. A series of 2 quality improvement pilot studies were conducted with select clinicians and their clients at Charlie Health, a remote IOP program that treats high-acuity teenagers and young adults who present with a range of mental health disorders. Both studies were carefully designed, including thorough preparation and planning, clinician training, feedback collection, and data analysis. Using process evaluation data, MBC deployment was repeatedly refined to enhance the clinical workflow and clinician experience. The survey completion rate was 80.08% (3216/4016) and 86.01% (4218/4904) for study 1 and study 2, respectively. Quantitative clinician feedback showed marked improvement from study 1 to study 2. Rates of successful treatment completion were 22% and 29% higher for MBC pilot clients in study 1 and study 2, respectively. Depression, anxiety, and psychological well-being symptom reduction were statistically significantly greater for MBC pilot clients (P<.05). Our findings support the feasibility and clinician acceptability of a rigorous MBC process in a real-world, youth-serving, remote-first, intermediate care setting. High survey completion data across both studies and improved clinician feedback over time suggest strong clinician buy-in. Client outcomes data suggest MBC is positively correlated with increased treatment completion and symptom reduction. This paper provides practical guidance for MBC implementation in IOPs and can extend to other mental health care settings.

Early clubfoot recurrence can lead to more frequent and earlier second recurrences.

The frequency of multiple clubfoot recurrences following Ponseti casting and the effect on final outcomes have not been well studied. This study aims to evaluate the effect of early recurrence (during the first 2 years) on the timing and rate of subsequent recurrences. A retrospective review was conducted of children treated with Ponseti casting at a single institution from 2002 to 2023 with minimum follow-up until age 5. Patients who required comprehensive soft tissue surgery to obtain initial correction were excluded. Patient-Reported Outcomes Measurement Information System data were collected when available. A total of 86 patients were included; 69.8% (60) had idiopathic clubfoot. Average follow-up was 5.8 years. Early recurrence (recurrence before age 2) occurred in 26.7% (23). The rate of late recurrence (recurrence after age 2) was higher in the early recurrence group, 73.9% (17) vs. 39.7% (25), P = 0.005. Survival analysis revealed that patients with early recurrence experience late recurrence at a younger age of 3.9 vs. 6.7 years, P ≤ 0.001. The early recurrence group experienced more frequent recurrences, with a median of 3 [interquartile range (IQR): 1-5] total recurrences vs. 0 (IQR: 0-1), P ≤ 0.001. Patients with early recurrence had lower final mobility scores, 40.83 ± 10.88 vs. 48.00 ± 10.60, P = 0.029. In conclusion, this study suggests that early clubfoot recurrence leads to more frequent subsequent recurrence and earlier second recurrence. Patients with early recurrence had comparatively lower outcome scores, primarily due to multiple recurrences. Care providers could use this knowledge to educate parents about the natural history of recurrent clubfeet and emphasize the importance of brace compliance and routine monitoring.

Patient-reported data on the severity of Von Willebrand disease.

The severity of Von Willebrand disease (VWD) is currently based on laboratory phenotype. However, little is known about the severity of the patient's experience with the disease. The most recent VWD guidelines highlight the need for patient-reported outcomes (PROs) in VWD. The study aimed to investigate the patient-perspective on VWD severity and to identify key factors that determine the severity of disease experienced by patients. Patients participated in a nationwide cross-sectional study on VWD in the Netherlands (WiN-study). Patients filled in a questionnaire containing questions on the experienced severity of VWD (4-point scale), bleeding score (BS) and quality of life (QoL). We included 736 patients, median age of 41.0 years (IQR 23.0-55.0) and 59.5% were women. A total of 443 had type 1, 269 type 2 and 24 type 3 VWD. Self-reported severity of VWD was categorized as severe (n=52), moderate (n=171), mild (n=393) or negligible (n=120). Classification by historically lowest FVIII:C levels<0.20 IU/mL as a proxy for severe VWD aligned with patient-reported severity classification with a 72% accuracy. Type 3 VWD (OR=4.02, 95%CI: 1.72-9.45), higher BS (OR=1.09, 95%CI: 1.06-1.11), female sex (OR=1.36, 95%CI: 1.01-1.83), haemostatic treatment in the year preceding study inclusion (OR=1.53, 95%CI: 1.10-2.13) and historically lowest VWF:Act levels (OR=0.26, 95%CI: 0.07-1.00) were independent determinants of patient-reported severity. This study shows that patient-reported data provide novel insights into the determinants of experienced disease severity. Our findings highlight the need for studies on PROs with validated questionnaires to assess the burden of VWD.

The role of patient reported symptom data in co-producing meaning in rheumatoid arthritis.

Patients with rheumatoid arthritis (RA) experience a range of symptoms including joint pain and inflammation, stiffness, fatigue, anxiety, and low mood. Similar to patients with other long-term conditions, they may have periods of time when their disease is under control, and times when their condition is less stable, requiring treatment adjustments. The REMORA2 feasibility study explored the implementation of an integrated symptom-tracking system using a smartphone application (app), enabling patients to track day-to-day symptoms. The data was available in the electronic health record to be viewed at subsequent consultations. This paper explores patients' comments on living with RA, and how patient-reported symptom data supports informed interactions as patients and clinicians work together to coproduce meaning from the data. Individual semi-structured interviews were conducted with 21 patients and 7 clinicians, supplemented by nonparticipant observations of 5 clinical appointments. Thematic analysis was used to analyse data from the interviews, with an ethnographic approach used to analyse the observational data. Both clinicians and patients reported the benefits of reviewing the data in the clinic together. This helped inform decisions about pain management and identified patients who might otherwise have dismissed symptoms such as pain, because of their natural inclination to be stoical. Improved insights on the care of RA were generated as patients and clinicians discuss symptom tracking data. This can assist the patient-clinician dyad in the process of two-way learning and shared decision-making on the management of a long-term condition.

Machine learning explains response variability of deep brain stimulation on Parkinson’s disease quality of life

Improving health-related quality of life (QoL) is crucial for managing Parkinson’s disease. However, QoL outcomes after deep brain stimulation (DBS) of the subthalamic nucleus (STN) vary considerably. Current approaches lack integration of demographic, patient-reported, neuroimaging, and neurophysiological data to understand this variability. This study used explainable machine learning to analyze multimodal factors affecting QoL changes, measured by the Parkinson’s Disease Questionnaire (PDQ-39) in 63 patients, and quantified each variable’s contribution. Results showed that preoperative PDQ-39 scores and upper beta band activity (>20 Hz) in the left STN were key predictors of QoL changes. Lower initial QoL burden predicted worsening, while improvement was associated with higher beta activity. Additionally, electrode positions along the superior-inferior axis, especially relative to the z = −7 coordinate in standard space, influenced outcomes, with improved and worsened QoL above and below this marker. This study emphasizes a tailored, data-informed approach to optimize DBS treatment and improve patient QoL.

Babcock versus Scissor Tensioning for Retropubic Mid-Urethral Slings: Comparing Two Intra-Operative Techniques Through 5 Years of Follow-Up.

The objective was to determine if mid-urethral sling (MUS) tensioning with a Mayo Scissor as a sub-urethral spacer compared with a Babcock clamp holding a loop of tape under the urethra results in differences in patient-reported outcomes and rates of repeat surgery over a 5-year follow-up. Follow-up 5 years after a randomized clinical trial, utilizing primary data collection linked to administrative health data, was carried out to create a longitudinal cohort. The primary outcome was participant-reported bothersome SUI symptoms, as defined by the Urogenital Distress Inventory (UDI-6) questionnaire. Secondary outcomes included participant-reported bothersome overactive bladder (OAB) scores, median scores of three validated urinary symptom questionnaires, and rates of subsequent surgery determined through patient report and administrative data. Two hundred and sixty (81.8%) of the original study participants provided participant-reported data at 5 years. Administrative data linkage was completed for all of the original participants (n = 318). Demographic characteristics remained similar in the two groups at the 5-year follow-up mark. No differences existed in the primary outcome of reported bothersome SUI symptoms (30.8% Scissors vs 26.8% Babcock, p = 0.559), proportion of participants with bothersome OAB, the median scores of three validated bladder questionnaires, or in rates and cumulative incidence of recurrent MUS surgery or surgical revision of mesh-related complications. Both the Scissor and Babcock tensioning techniques provided comparable outcomes at 5 years post-MUS surgery. The information from this study allows surgeons to better decide which technique to adopt in their practice, providing confidence in longer-term cure and safety.

Emerging lessons from experiences at transitions in care among hospitalised patients with cancer with postdischarge frequent emergency department use: a qualitative study using linked clinical and patient-reported interview data from Quebec, Canada

BackgroundWhile teamwork is essential to providing high-quality patient-centred care, challenges in interprofessional collaboration and decision-making in hospital settings are common, especially for patients with cancer. The purpose of this qualitative...

Systematic literature review of the humanistic and economic burden of focal epilepsy and primary generalized tonic-clonic seizures in adults.

This systematic literature review (SLR) assessed the humanistic and economic burden of focal epilepsy and primary generalized tonic-clonic seizures (PGTCS) in adults to evaluate these domains in both populations and identify evidence gaps to inform future research. A search was conducted on December 7, 2022, using MEDLINE and Embase to identify studies published from 2012 onwards reporting humanistic burden (patient-reported or caregiver-reported outcomes or utilities, qualitative evaluations), economic burden (productivity loss, caregiver and societal costs of epilepsy), and sleep-related outcomes. Of the 2830 citations identified, 136 were included. Most studies were in the focal epilepsy population; very few studies reported outcomes in the PGTCS population. The presence of epilepsy-specific instruments varied based on the domain evaluated. Epilepsy exerted considerable humanistic and economic burden. Indicators of poor disease control (e.g., high seizure frequency, resistance to anti-seizure medications, polypharmacy) increased epilepsy burden. Seizure frequency and type, disease severity, and polypharmacy also affected work productivity. Adults with epilepsy, particularly focal epilepsy, reported higher indirect costs, more sick days accrued, and early entry into retirement. Caregivers similarly reported high productivity loss and absenteeism related to caregiving duties. The results of this SLR highlight the high humanistic and economic burden of focal epilepsy and PGTCS, although limited data were available for the PGTCS population. The results include patient-reported outcome data specific to focal epilepsy and PGTCS, expanding the limited humanistic burden evidence identified in previous reviews, and show the effect of poor disease control on individuals' lives and as a driver of indirect costs. PLAIN LANGUAGE SUMMARY: Our systematic literature review identified studies that evaluated the impact of focal epilepsy and primary generalized tonic-clonic seizures on patients and their caregivers. We found that focal epilepsy negatively impacted patients' mental health and sleep and was associated with higher indirect costs and lower work productivity in people with more severe disease. The impact of primary generalized tonic-clonic seizures on patients was rarely reported, and future research is needed.

The Challenges of Measuring Socioeconomic Inequality in Pharmacoepidemiology Studies.

Social conditions like socioeconomic status (SES) are critical sources of health disparities. In pharmacoepidemiology research, our ability to measure SES in retrospective, real world clinical data remains challenged by a lack of patient-reported data. Some broadly accepted concepts can be measured at the individual level, such as income, poverty, and education. Community-level measures such as the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) also exist. After reflecting on these existing measures and discussing the challenges for leveraging them with real world data, we offer three recommendations that we believe could improve the ability of pharmacoepidemiologists to better measure and interrogate the effect of SES in their own research. These recommendations include a greater collection of patient-reported metrics, reduced reliance on ZIP Codes and ZIP Code Tabulation Areas for creating community-level measures of deprivation, and the inclusion of GIS and demography specialists within pharmacoepidemiology teams.

Digital remote monitoring of chronic retinal conditions-A clinical future tool? : Remote monitoring of chronic retinal conditions

In view of the predicted increase in incidence and prevalence of chronic retinal diseases and undersupply of care in the population, telemedicine could contribute to reducing access barriers to healthcare and improving the results of treatment. A literature review on remote monitoring of chronic retinal diseases was carried out. The medical literature was searched for publications on remote monitoring of chronic retinal diseases. The results were compiled in anarrative overview. The four main topics in the literature are: validation studies, implementation strategies, acceptance/target group analyses and health economic analyses. Remote monitoring systems are based on visual function tests, imaging or patient reports and have been particularly investigated in age-related macular degeneration (AMD) and diabetic eye disease (DED). Studies indicate positive effects regarding an optimization of clinical care and afavorable safety profile but randomized controlled trials are lacking for the majority of monitoring tools. Remote monitoring could complement existing care structures for patients with chronic retinal diseases, especially AMD and DED. Promising systems are based on hyperacuity or optical coherence tomography, while patient-reported data are not commonly used; however, there is currently insufficient evidence justifying the use of remote monitoring systems in chronic retinal diseases in Europe and more research on the validation of remote monitoring systems is needed.