Electronic Health Record Platform Research Articles

Sex, sexual orientation, and gender identity data collection across electronic health record platforms: a national cross-sectional survey.

To assess the current state of sex, sexual orientation, and gender identity (SSOGI) data collection options in US electronic health record (EHR) platforms. We utilized an anonymous survey distributed via purposive snowball sampling to assess EHR platforms across the United States. Of 90 surveys started, 41 (45.6%) were completed and used for data analysis. Respondents represented a geographically diverse sample of health care centers across the United States. EPIC was the most used EHR platform (70.7%) followed by Cerner (9.8%). Across reported platforms, a majority utilized structured fields to collect and document patient SSOGI data (n = 25, 61.0%). There was variability across platforms regarding SSOGI data elements collected. No platform collected all recommended SSOGI data elements. Significant variation exists across EHR platforms and across health care settings using the same EHR platform. National standards need to be followed for SSOGI data collection in EHR platforms.

Serotonergic Antidepressants are Associated With Higher Rates of Hematoma After Anterior Cervical Spine Surgery: A Large Propensity-matched Cohort Analysis.

Large database propensity-matched retrospective cohort analysis. This study aimed to investigate the potential effects of serotonergic antidepressants on outcomes after anterior cervical spine surgery (ACSS). It was hypothesized that the perioperative use of serotonergic antidepressants would be associated with higher rates of hematoma formation and worse outcomes after ACSS. Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) have been associated with worse outcomes after orthopaedic procedures. A retrospective cohort analysis was performed using TriNetX, an aggregated and de-identified electronic health record platform. Patients who underwent anterior cervical surgery were included via Current Procedural Terminology (CPT) codes and the International Classification of Disease (ICD-10) encounter diagnosis codes. Cohorts were 1:1 propensity matched across seven demographic and medical comorbidity parameters, and outcomes were compared. The incidence of adverse outcomes, as well as healthcare utilization, within 14 days, 30 days, 90 days and 2-years post-operatively was evaluated. Following propensity matching, each cohort consisted of 9,249 patients, for a total of 18,498 patients included in final statistical analysis. SSRI/SNRI's were associated with higher odds of hematoma formation within 7-days (0.69% vs. 0.46%, OR 1.5 [95% CI 1.02-2.2], P=0.04) and within 14-days postoperatively (0.81% vs. 0.52%, OR 1.6 [95% CI 1.1-2.3], P=0.01. Within 30- and 90-days, SSRI/SNRI's were associated with higher risk of emergency department utilization (30-day OR 1.30 [1.1-1.4]; 90-day OR 1.3 [1.2-1.4]) and irrigation & debridement (I&D) (30-day OR 1.9 [1.2-3.0]). SSRIs/SNRIs were also associated with significantly higher risk of I&D within 2-years (OR 1.3 [1.1-1.6]). The use of serotonergic antidepressants perioperatively was associated with higher odds and risk of numerous outcomes, including hematoma formation, emergency department utilization and the need for irrigation & debridement. Future prospective studies are required to confirm these results. III; retrospective cohort analysis.

Effect of Cannabis Usage on Thyroid Eye Disease.

The purpose of this study is to investigate the association between cannabis usage and thyroid eye disease (TED) in patients with autoimmune hyperthyroidism. While the association between cigarette smoking and TED is well established, the effect of cannabis on TED is unclear. This cohort study examined data from TriNetX, an electronic health record platform, for patients with autoimmune hyperthyroidism between December 1, 2003, and December 1, 2023. Primary outcomes were TED presentation (exophthalmos, eyelid retraction, eyelid edema, orbital edema, strabismus, and optic neuropathy) and treatment (teprotumumab, methylprednisolone, tarsorrhaphy, and orbital decompression) in cannabis users, nicotine users, and control patients. Propensity matching was performed to control for characteristics such as age, sex, race, prior thyroidectomy, and/or radio ablation. Relative risk between cohorts was calculated for each outcome in 6-month, 1-year, and 2-year intervals following diagnosis of autoimmune hyperthyroidism. Of 36,186 patients with autoimmune hyperthyroidism, 783 were cannabis users, 17,310 were nicotine users, and 18,093 were control patients without cannabis or nicotine usage. Compared with control patients, cannabis users were more likely to be younger, male, and Black/African American and have anxiety or depression. After propensity matching, cannabis users were 1.9 times more likely to develop exophthalmos (p = 0.03) and 1.6 times more likely to develop any TED presentation (p = 0.049) in the 1-year interval although these differences did not remain statistically significant in the 2-year interval. Cannabis users had a significantly increased risk for TED outcomes in the 1-year interval. Further research is needed to inform TED management.

Electronic Health Record–Based Screening for Intimate Partner Violence

Intimate partner violence (IPV) is a significant public health issue, with a 25% lifetime prevalence. Screening for IPV in primary care is a recommended practice whose effectiveness is debated. To assess the effect of an electronic health record (EHR)-based multifactorial intervention screening on the detection of IPV risk in primary care practice. This cluster randomized clinical trial used a stepped-wedge design to assign 15 family medicine primary care clinics in the Medical University of South Carolina Health System in the Charleston region to 3 matched blocks from October 6, 2020, to March 31, 2023. All women aged 18 to 49 years who were seen in these clinics participated in this study. A noninterruptive EHR alert combined with confidential screening by computer questionnaire using the EHR platform followed by risk assessment and a decision support template. The main outcomes were the rate at which patients were screened for IPV across the clinics and the rate at which patients at risk for IPV were detected by screening procedures. The study clinics cared for 8895 unique patients (mean [SD] age, 34.6 [8.7] years; 1270 [14.3%] with Medicaid or Medicare and 7625 [85.7%] with private, military, or other insurance) over the study period eligible for the screening intervention. The intervention had significant effects on the overall rate of screening for IPV, increasing the rate of screening from 45.2% (10 268 of 22 730 patient visits) to 65.3% (22 303 of 34 157 patient visits) when the noninterruptive alert was active (relative risk, 1.46 [95% CI, 1.44-1.49]; P < .001). The confidential screening process was more effective than baseline nurse-led oral screening at identifying patients reporting past-year IPV (130 of 8895 patients [1.5%] vs 9 of 17 433 patients [0.1%]). The intervention was largely effective in increasing screening adherence and the positive detection rate of IPV in primary care. A highly private approach to screening for IPV in primary care may be necessary to achieve adequate detection rates while addressing potential safety issues of patients experiencing IPV. ClinicalTrials.gov Identifier: NCT06284148.

Development and integration of a clinical dashboard within a dental school setting.

To describe the development and integration of an electronic health record-driven, student dashboard that displays real-time data relative to the students' patient management and clinic experiences at the University of Illinois Chicago, College of Dentistry. Following development and implementation of the student dashboard, various objective metrics were evaluated to identify any improvements in the clinical patient management. A cross-sectional retrospective chart review was completed of the electronic health record (axiUm, Exan, Coquitlam, BC, Canada) from January 2019 to April 2022 evaluating four performance metrics: student lockouts, note/code violations, overdue active patients, and overdue recall patients. Descriptive statistics were analyzed. The Kolmogorov-Smirnov test was applied to assess the normal distribution of data. Data were analyzed by the Kruskal-Wallis tests for potential differences between pre-dashboard and post-dashboard implementation years with the mean overdue active/recall patient to student ratio variables. Mann-Whitney U-tests for between-groups comparisons with Bonferroni correction for multiple comparisons were performed (α=0.05). Descriptive statistics were performed to analyze the student utilization frequency of the dashboard. Post-implementation analysis indicated a slight decrease in the number of lockouts and note/code violation; and a statistically significant decrease in overdue active patients post-dashboard (P<0.001). On average, students accessed their dashboards 3.3 times a week. Implementation of a student dashboard through the electronic health record platform within an academic dental practice has the potential to assist students with patient management and is utilized regularly by the students.

Only One Quarter of Family Physicians Are Very Satisfied with Their Electronic Health Records Platform.

Two decades into the era of Electronic Health Records (EHRs), the promise of streamlining clinical care, reducing burden, and improving patient outcomes has yet to be realized. A cross-sectional family physician census conducted by the American Board of Family Medicine in 2022 and 2023 included self-reported physician EHR satisfaction. Of the nearly 10,000 responding family physicians, only one-in-four (26.2%) report being very satisfied and one-in-three (33.8%) were not satisfied. These low levels of satisfaction point to the need for greater transparency in the marketplace and pressure to increase user-centric EHR design.

(125) INTRAPARTUM AND 30-DAY POSTPARTUM COMPLICATIONS IN PREGNANCIES WITH ANTENATAL SARS-COV-2 INFECTION

Abstract Introduction While COVID-19 has been associated with adverse pregnancy outcomes, data regarding intrapartum and postpartum maternal complications after antenatal COVID-19 infection is limited and variable. Objective This study compares the intrapartum and postpartum complication rates between pregnant patients with and without an antenatal COVID-19 diagnosis in a national dataset. Methods This is a retrospective cohort study of patients who gave birth between January 2020 and May 2023 utilizing the TriNetx Analytics Research Network, an aggregated electronic health record platform. Our data searches were performed on May 1, 2023. ICD-10 codes were used to identify the encounter for delivery (ICD-10 code O80-O82) and pregnant individuals with a COVID-19 diagnosis (ICD-10 code U70.1) during their gestational period. The control group was defined as those with one encounter for delivery between January 2020 and May 2023 and without a diagnosis of COVID-19 during the gestational period. Complications included obstetric, cardiovascular, neurovascular, and pulmonary outcomes diagnosed from the day of delivery to 30 days postpartum. The cohort was propensity matched by age, race, and ethnicity. The relative risk values and 95% confidence intervals for the outcomes were calculated and compared. Results Of the 368,923 patients who had an encounter for delivery between January 2020 and May 2023, 26,974 (7%) had an antenatal COVID-19 diagnosis. Compared to our matched control cohort, patients with antenatal COVID-19 were at an increased risk of postpartum hemorrhage (RR 1.24, 95% CI 1.16-1.33), gestational hypertension without significant proteinuria (1.27 [1.21-1.34]), pre-eclampsia (1.25 [1.18-1.32]), eclampsia (1.66 [1.29-2.23]), and preterm labor (1.21 [1.12-1.31]). Patients with antenatal COVID-19 infections were also at an increased risk of postpartum complications, including cerebral infarction (1.74 [1.04-2.90]), pulmonary embolism (2.68 [1.74-4.13]), acute embolism and thrombosis of deep veins of lower extremity (2.32 [1.45-3.71]), sepsis (2.21 [1.54-3.19]), heart failure (1.55 [1.04-2.31]), and cardiomyopathy (2.08 [1.30-3.32]). There was no elevated risk of HELLP syndrome (1.18 [0.96-1.44]), placental abruption (1.14 [0.94-1.37]), and myocardial infarction (1.4 [0.62-3.15]). Conclusions Pregnant individuals with antenatal COVID-19 diagnosis were more likely to have intrapartum and postpartum encounter diagnoses for obstetric, cardiovascular, neurovascular, and pulmonary complications. This data allows providers to identify antenatal COVID-19 infection as a risk factor and monitor patients for complications. Disclosure No.

Advancing Healthcare Infrastructure: The Features of Iran’s Sina Electronic Health Record System

Background and aims: The Sina Electronic Health Record (SinaEHR) system was developed to support primary care delivery across Iran by enabling chronic disease monitoring, infectious disease surveillance, health policy decision-making, and quality improvement initiatives. Methods: The SinaEHR system was implemented by Mashhad University of Medical Sciences which contains health records of over 5 million people across various regions of Iran. It utilizes the International Classification of Diseases (ICD) version 10, integrating laboratory results through a laboratory information system to facilitate real-time clinical decision-making. Results: Widespread implementation of the SinaEHR system has established an invaluable healthcare infrastructure resource for the improvement of primary care services across Iran. Strict security and confidentiality measures are enforced to protect sensitive patient information. Conclusion: The SinaEHR system significantly advances Iran’s healthcare infrastructure by providing a comprehensive electronic health record platform to improve healthcare delivery and promote evidence-based decision-making.

The association of COVID-19 with increased pediatric ventriculoatrial shunt failures: a national retrospective cohort.

During the COVID-19 pandemic, the authors' institution managed ventriculoatrial (VA) shunt complications in 2 teenage patients in close proximity to a symptomatic COVID-19 infection. Systemic thrombotic events are an established complication of COVID-19 infection due to a hypercoagulable state. Thrombotic complications, particularly elevated central venous pressure, can cause VA shunt failure. The true effect of COVID-19 on patients with intravascular devices is currently unknown. In this study, the authors aimed to determine if there was an association between COVID-19 infection and VA shunt failure. TriNetX, an aggregated electronic health record platform, was used to analyze data of more than 13 million US pediatric patients. Two matched cohorts of patients < 18 years of age with a VA shunt were defined. Group 1 (n = 311) had a positive laboratory test for COVID-19 from March 1, 2020, to March 31, 2022. Group 2 (n = 311), a control group, had any medical appointment from March 1, 2020, to March 31, 2022, and never had a positive laboratory test for COVID-19. The authors analyzed outcomes 1 year after testing positive for COVID-19 in group 1, and after the medical appointment in group 2. Outcomes included shunt complications, shunt revisions or replacements, and thromboembolic complications. To protect patient privacy, individual results of fewer than 10 patients are not specified in TriNetX. Group 1 had a greater odds of mechanical shunt complication than group 2 (20% vs 4%, OR 5.71, 95% CI 3.07-10.62). Group 1 had a greater odds of shunt reoperation than group 2 (11% vs < 3%, OR > 3.7, 95% CI 1.72-7.62). There were 1-10 patients in group 1 (≤ 3% of group 1) who experienced a thromboembolism due to the shunt, compared with no patients in group 2 who had a thromboembolism due to the shunt. This analysis demonstrates an association of shunt complications, reoperations, and thromboembolic events in patients with VA shunts following COVID-19 infection.

Assessing readiness to use electronic health record data for outcome ascertainment in clinical trials – A case study

BackgroundVariable data quality poses a challenge to using electronic health record (EHR) data to ascertain acute clinical outcomes in multi-site clinical trials. Differing EHR platforms and data comprehensiveness across clinical trial sites, especially if patients received care outside of the clinical site's network, can also affect validity of results. Overcoming these challenges requires a structured approach. MethodsWe propose a framework and create a checklist to assess the readiness of clinical sites to contribute EHR data to a clinical trial for the purpose of outcome ascertainment, based on our experience with the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) study, which enrolled 5451 participants in 86 primary care practices across 10 healthcare systems (sites). ResultsThe site readiness checklist includes assessment of the infrastructure (i.e., size and structure of the site's healthcare system or clinical network), data procurement (i.e., quality of the data), and cost of obtaining study data. The checklist emphasizes the importance of understanding how data are captured and integrated across a site's catchment area and having a protocol in place for data procurement to ensure consistent and uniform extraction across each site. ConclusionsWe suggest rigorous, prospective vetting of the data quality and infrastructure of each clinical site before launching a multi-site trial dependent on EHR data. The proposed checklist serves as a guiding tool to help investigators ensure robust and unbiased data capture for their clinical trials. Original trial registration numberNCT02475850

Developing an integrated clinical decision support system for the early identification and management of kidney disease—building cross-sectoral partnerships

BackgroundThe burden of chronic conditions is growing in Australia with people in remote areas experiencing high rates of disease, especially kidney disease. Health care in remote areas of the Northern Territory (NT) is complicated by a mobile population, high staff turnover, poor communication between health services and complex comorbid health conditions requiring multidisciplinary care.AimThis paper aims to describe the collaborative process between research, government and non-government health services to develop an integrated clinical decision support system to improve patient care.MethodsBuilding on established partnerships in the government and Aboriginal Community-Controlled Health Service (ACCHS) sectors, we developed a novel digital clinical decision support system for people at risk of developing kidney disease (due to hypertension, diabetes, cardiovascular disease) or with kidney disease. A cross-organisational and multidisciplinary Steering Committee has overseen the design, development and implementation stages. Further, the system’s design and functionality were strongly informed by experts (Clinical Reference Group and Technical Working Group), health service providers, and end-user feedback through a formative evaluation.ResultsWe established data sharing agreements with 11 ACCHS to link patient level data with 56 government primary health services and six hospitals. Electronic Health Record (EHR) data, based on agreed criteria, is automatically and securely transferred from 15 existing EHR platforms. Through clinician-determined algorithms, the system assists clinicians to diagnose, monitor and provide guideline-based care for individuals, as well as service-level risk stratification and alerts for clinically significant events.ConclusionDisconnected health services and separate EHRs result in information gaps and a health and safety risk, particularly for patients who access multiple health services. However, barriers to clinical data sharing between health services still exist. In this first phase, we report how robust partnerships and effective governance processes can overcome these barriers to support clinical decision making and contribute to holistic care.

Integrated Electronic Health Records (EHR) Platform: Enhancing Patient-Centric Healthcare Management

In contemporary healthcare systems, digitizing medical records has become imperative to streamline and enhance patient care. This research paper explores the development and implementation of a website that integrates patients' medical records, aiming to provide a comprehensive and patient-centric approach to healthcare management. The platform seeks to facilitate seamless information exchange among healthcare providers, improve treatment decision- making, and empower patients in managing their health.

Real world performance of the 21st Century Cures Act population-level application programming interface.

To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule. We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR. Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12000 resources/min. The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Sprint-inspired One-on-One Post-Go-Live Training Session (Mini-Sprint) Improves Provider Electronic Health Record Efficiency and Satisfaction.

Inefficient electronic health record (EHR) usage increases the documentation burden on physicians and other providers, which increases cognitive load and contributes to provider burnout. Studies show that EHR efficiency sessions, optimization sprints, reduce burnout using a resource-intense five-person team. We implemented sprint-inspired one-on-one post-go-live efficiency training sessions (mini-sprints) as a more economical training option directed at providers. We evaluated a post-go-live mini-sprint intervention to assess provider satisfaction and efficiency. NorthShore University HealthSystem implemented one-on-one provider-to-provider mini-sprint sessions to optimize provider workflow within the EHR platform. The physician informaticist completed a 9-point checklist of efficiency tips with physician trainees covering schedule organization, chart review, speed buttons, billing, note personalization/optimization, preference lists, quick actions, and quick tips. We collected postsession survey data assessing for net promoter score (NPS) and open-ended feedback. We conducted financial analysis of pre- and post-mini-sprint efficiency levels and financial data. Seventy-six sessions were conducted with 32 primary care physicians, 28 specialty physicians, and 16 nonphysician providers within primary care and other areas. Thirty-seven physicians completed the postsession survey. The average NPS for the completed mini-sprint sessions was 97. The proficiency score had a median of 6.12 (Interquartile range (IQR): 4.71-7.64) before training, and a median of 7.10 (IQR: 6.25-8.49) after training. Financial data analysis indicates that higher level billing codes were used at a greater frequency post-mini-sprint. The revenue increase 12 months post-mini-sprint was $213,234, leading to a return of $75,559.50 for 40 providers, or $1,888.98 per provider in a 12-month period. Our data show that mini-sprint sessions were effective in optimizing efficiency within the EHR platform. Financial analysis demonstrates that this type of training program is sustainable and pays for itself. There was high satisfaction with the mini-sprint training modality, and feedback indicated an interest in further mini-sprint training sessions for physicians and nonphysician staff.

OpenSAFELY: Measuring BMI in 22 million patients in England

Background Body mass index (BMI) has been identified as a risk factor for clinical outcomes in patients with COVID-19. Studies identifying this risk have used electronic health record (EHR) platforms in which clinical conditions must be properly identified. We set out to define and evaluate various methods of deriving BMI measurements in OpenSAFELY-TPP, an EHR platform that has been used in many studies relating to the COVID-19 pandemic. Methods With the approval of NHS England, we use routine clinical data from &gt;22 million patients in England to define four derivations of BMI. We compare the number of patients with each type of BMI measurement and the number of measurements themselves. We also examine the plausibility of each derivation by looking at the distribution of measurements and counting values out of the expected range. To evaluate how frequently the BMI derivations are recorded, we track the number of new measurements recorded over time and the average time between updates in patients with multiple measurements. Results Primary constraints in creating the optimal BMI derivation is coverage, accuracy, and computational complexity. BMI derivations calculated from height and weight contain a few extreme outliers that affect aggregated statistics. SNOMED-recorded BMI records are more accurate on average and offer better coverage across the population. The canonical OpenSAFELY definition – which uses calculated BMI as a first instance and SNOMED-recorded BMI if missing – offers the best coverage, but contains the same extreme outliers found in calculated BMI and is the most computationally expensive of all methods. Conclusions Across all derivations, some cleaning should be performed to drop implausible outliers. Using calculated BMI on its own does not offer the best coverage or accuracy. In choosing between SNOMED-recorded BMI and the current OpenSAFELY implementation, users should decide whether they would like to maximise computational efficiency or coverage.

Promoting Learning Health System Cycles by Optimizing EHR Data Clinical Concept Encoding Processes.

Electronic health records (EHRs) and other real-world data (RWD) are critical to accelerating and scaling care improvement and transformation. To efficiently leverage it for secondary uses, EHR/RWD should be optimally managed and mapped to industry standard concepts (ISCs). Inherent challenges in concept encoding usually result in inefficient and costly workflows and resultant metadata representation structures outside the EHR. Using three related projects to map data to ISCs, we describe the development of standard, repeatable processes for precisely and unambiguously representing EHR data using appropriate ISCs within the EHR platform lifecycle and mappings specific to SNOMED-CT for Demographics, Specialty and Services. Mappings in these 3 areas resulted in ISC mappings of 779 data elements requiring 90 new concept requests to SNOMED-CT and 738 new ISCs mapped into the workflow within an accessible, enterprise-wide EHR resource with supporting processes.

Making the EHR Work for You-Modifications of an Electronic Health Record System to Improve Tracking and Management of Patients Receiving Outpatient Parenteral Antibiotic Therapy.

Managing the complex needs of outpatient parenteral antibiotic therapy (OPAT) patients is challenging and time-consuming. We describe development of multimodal interventions to facilitate patient management within an Epic® (Epic Systems Corporation)-based electronic health record (EHR) platform. During 2016-2018, a multidisciplinary team created several modifications in our local EHR to improve gaps in OPAT care, including shared note templates, shared patient lists, automatically triggered notifications, and comprehensive order sets. A SmartForm was created, allowing collection of discrete, self-contained extractable data about each OPAT episode. We reviewed OPAT episodes from January 2019 through December 2022. The multimodal EHR interventions culminated in the creation of a patient report, the "OPAT Monitoring View" collating OPAT-relevant data from multiple sections of the chart onto 1 screen display. This view is accessible both within the patient chart and from multiple list-based, in-basket, and snapshot-anchored preview functions in the EHR. Implementation of the EHR bundle facilitated management of 3402 OPAT episodes from 2019 to 2022 (850 episodes/year), about 50% higher than anticipated based on 540 OPAT courses in 2016. The OPAT EHR bundle allowed efficient (<3 hours) multidisciplinary rounds for management of 130-145 patients each week, streamlining of care transitions, and increasing staff satisfaction. Bundled multimodal modifications to the local EHR increased patient care efficiency and staff satisfaction and facilitated data collection to support a large OPAT program. These modifications apply commonly available EHR functionalities to OPAT care and could be adapted to other settings with different EHR platforms.

Study protocol for a case series: implementation and evaluation of an integrated mental and physical healthcare programme to screen for mental health symptoms in people with epilepsy

IntroductionThe prevalence of mental health symptoms in people with epilepsy (PWE) is elevated compared with that of the general population. These symptoms can negatively impact epilepsy management and patient outcomes...

Systematic symptom management in the IMPACT Consortium: rationale and design for 3 effectiveness-implementation trials.

Cancer and its treatment produce deleterious symptoms across the phases of care. Poorly controlled symptoms negatively affect quality of life and result in increased health-care needs and hospitalization. The Improving the Management of symPtoms during And following Cancer Treatment (IMPACT) Consortium was created to develop 3 large-scale, systematic symptom management systems, deployed through electronic health record platforms, and to test them in pragmatic, randomized, hybrid effectiveness and implementation trials. Here, we describe the IMPACT Consortium's conceptual framework, its organizational components, and plans for evaluation. The study designs and lessons learned are highlighted in the context of disruptions related to the COVID-19 pandemic.

Implementation of Social Isolation Screening and an Integrated Community Resource Referral Platform.

Screening and referral programs for social isolation and loneliness in older patients increased during the COVID-19 pandemic in primary care settings to mitigate associated adverse health outcomes. This study explores community health centers' experiences implementing a social isolation and loneliness screening program involving a community resource referral platform integrated into the electronic health record to support referrals. A formative mixed methods evaluation in 4 community health centers. Semistructured interviews, observation of implementation meetings, facilitated group discussions, surveys, and utilization data extracted from the electronic health record and community resource referral platform were collected and analyzed concurrently. Screening for social isolation and loneliness can heighten health center staff knowledge and prioritization of socially isolated older patients. Participants indicate using an integrated community resource referral platform may only be useful in certain circumstances, particularly for those located outside urban areas. The experiences of these health centers indicate that when implementing interventions to mitigate patients' social isolation and loneliness, it is necessary to consider other resource directories, needed adjustments to referral and documentation workflows, and potential impacts on patients and care teams. Screening older patients for social isolation could increase care team awareness of social risk; assistance related referral options should be considered carefully.