Background: Our objective was to examine the variation in telemedicine adoption by specialty line and patient demographic characteristics after the initial peak period of the coronavirus disease 2019 pandemic when in-person visits had resumed and visit volume returned to prepandemic levels. Materials and Methods: Aggregated encounter data were extracted for six service lines (dermatology, psychiatry, endocrinology, cardiology, orthopedics, and nonurgent primary care) in an integrated health system across three time periods: July 1 to September 30, 2019 ( n  = 239,803), July 1 to September 30, 2020 ( n  = 245,648), and December 29, 2019 to October 3, 2020 ( n  = 624,886). Risk ratios were calculated to assess the relative use of telemedicine compared with in-person encounters and telemedicine modality (i.e., synchronous audio/video vs. audio-only telephone) by patient race, age, sex, and insurance type. Results: By June 2020, total visit volume returned to prepandemic levels. Differences in patient demographics between July 1 to September 30, 2020 and the previous year's baseline were negligible. Telemedicine adoption varied by medical specialty, from 3.2% (dermatology) to 98.3% (psychiatry) of visits. African American and male patients were less likely to use telemedicine (telephone or video) compared with white and female patients. Among telemedicine encounters, African American, publicly insured, and older patients were less likely to use video compared with white, commercially insured, and younger patients. Discussion: Variation in telemedicine adoption and modality underscores the importance of balancing patient- and clinic-level implementation factors to promote sustainable, equitable telemedicine integration. Conclusion: Understanding current trends in the “new normal” of telemedicine provides valuable insights into future implementation and financing.

Background: Screening in primary care for unmet individual social needs (e.g., housing instability, food insecurity, unemployment, social isolation) is critical to addressing their deleterious effects on patients’ health outcomes. To our knowledge, this is the first study to apply an implementation science framework to identify implementation factors and best practices for social needs screening and response.Methods: Guided by the Health Equity Implementation Framework (HEIF), we collected qualitative data from clinicians and patients to evaluate barriers and facilitators to implementing the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), a standardized social needs screening and response protocol, in a federally qualified health center. Eligible patients who received the PRAPARE as a standard of care were invited to participate in semi-structured interviews. We also obtained front-line clinician perspectives in a semi-structured focus group. HEIF domains informed a directed content analysis.Results: Patients and clinicians (i.e., case managers) reported implementation barriers and facilitators across multiple domains (e.g., clinical encounters, patient and provider factors, inner context, outer context, and societal influence). Implementation barriers included structural and policy level determinants related to resource availability, discrimination, and administrative burden. Facilitators included evidence-based clinical techniques for shared decision making (e.g., motivational interviewing), team-based staffing models, and beliefs related to alignment of the PRAPARE with patient-centered care. We found high levels of patient acceptability and opportunities for adaptation to increase equitable adoption and reach.Conclusion: Our results provide practical insight into the implementation of the PRAPARE or similar social needs screening and response protocols in primary care at the individual encounter, organizational, community, and societal levels. Future research should focus on developing discrete implementation strategies to promote social needs screening and response, and associated multisector care coordination to improve health outcomes and equity for vulnerable and marginalized patient populations.

Background: The COVID‐19 pandemic resulted in a rapid implementation of telemedicine into clinical practice. This study examined whether early outpatient follow‐up via telemedicine is as effective as in‐person visits for reducing 30‐day readmissions in patients with heart failure. Methods and Results: Using electronic health records from a large health system, we included patients with heart failure living in North Carolina (N=6918) who were hospitalized between March 16, 2020 and March 14, 2021. All‐cause readmission within 30 days after discharge was examined using weighted logistic regression models. Overall, 7.6% (N=526) of patients received early telemedicine follow‐up, 38.8% (N=2681) received early in‐person follow‐up, and 53.6% (N=3711) did not receive follow‐up within 14 days of discharge. Compared with patients without early follow‐up, those who received early follow‐up were younger, were more likely to be Medicare beneficiaries, had more comorbidities, and were less likely to live in an disadvantaged neighborhood. Relative to in‐person visits, those with telemedicine follow‐up were of similar age, sex, and race but with generally fewer comorbidities. Overall, the 30‐day readmission rate (19.0%) varied among patients who received telemedicine visits (15.0%), in‐person visits (14.0%), or no follow‐up (23.1%). After covariate adjustment, patients who received either telemedicine (odds ratio [OR], 0.55; 95% CI, 0.44–0.72) or in‐person (OR, 0.52; 95% CI, 0.45–0.60) visits were similarly less likely to be readmitted within 30 days compared with patients with no follow‐up. Conclusions: During the COVID‐19 pandemic, the use of telemedicine visits for early follow‐up increased rapidly. Patients with heart failure who received outpatient follow‐up either via telemedicine or in‐person had better outcomes than those who received no follow‐up.

Although self-management is recommended for persons with epilepsy, its optimal strategies and effects are uncertain. To evaluate the components and efficacy of self-management interventions in the treatment of epilepsy in community-dwelling persons. English-language searches of MEDLINE, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL in April 2018; the MEDLINE search was updated in March 2019. Randomized and nonrandomized comparative studies of self-management interventions for adults with epilepsy. An investigator assessed study characteristics; intervention details, including 6 components of self-management; and outcomes, which were verified by a second reviewer. Risk of bias (ROB) was assessed independently by 2 investigators. 13 randomized and 2 nonrandomized studies (2514 patients) evaluated self-management interventions. Interventions were delivered primarily in group settings, used a median of 4 components, and followed 2 general strategies: 1 based on education and the other on psychosocial therapy. Education-based approaches improved self-management behaviors (standardized mean difference, 0.52 [95% CI, 0.0 to 1.04]), and psychosocial therapy–based approaches improved quality of life (mean difference, 6.64 [CI, 2.51 to 10.77]). Overall, self-management interventions did not reduce seizure rates, but 1 educational intervention decreased a composite of seizures, emergency department visits, and hospitalizations. High ROB in most studies, incomplete intervention descriptions, and studies limited to English-language publications. There is limited evidence that self-management strategies modestly improve some patient outcomes that are important to persons with epilepsy. Overall, self-management research in epilepsy is limited by the range of interventions tested, the small number of studies using self-monitoring technology, and uncertainty about components and strategies associated with benefit. U.S. Department of Veterans Affairs. (PROSPERO: CRD42018098604)

Purpose of Review This study reviews contemporary literature on RASP and HoLEP to evaluate perioperative outcomes, common complications, cost analytics, and future directions of both procedures. Recent Findings RASP is indicated for prostates > 80 mL, while HoLEP is size-independent. No notable differences were found in operative time, PSA nadir (surrogate for enucleation volume), re-catheterization rates, or long-term durability. Prolonged incontinence and bladder neck contracture rates are low for both surgeries. Patients experience similar satisfaction outcomes and improvements in uroflowmetry and post-void residual volumes. HoLEP demonstrates shorter hospitalizations, lower transfusion rates, lower costs, and higher rates of same-day discharge. RASP offers a shorter learning curve and lower rates of early postoperative urinary incontinence. Summary HoLEP is a size-independent surgery that offers advantages for patients seeking a minimally invasive procedure with the potential for catheter-free same-day discharge. Future directions with single-port simple prostatectomy may offer parity in same-day discharge, but further research is needed to determine broader feasibility.

Telemedicine can facilitate population health management by extending the reach of providers to efficiently care for high-risk, high-utilization populations. However, for telemedicine to be maximally useful, data collected using telemedicine technologies must be reliable and readily available to healthcare providers. To address current gaps in integration of patient-generated health data into the electronic health record (EHR), we examined 2 patient-facing platforms, Epic MyChart and Apple HealthKit, both of which facilitated the uploading of blood glucose data into the EHR as part of a diabetes telemedicine intervention. All patients were offered use of the MyChart platform; we subsequently invited a purposive sample of patients who used the MyChart platform effectively (n = 5) to also use the Apple HealthKit platform. Patients reported both platforms helped with diabetes self-management, and providers appreciated the convenience of the processes for obtaining patient data. Providers stated that the EHR data presentation format for Apple HealthKit was challenging to interpret; however, they also valued the greater perceived accuracy the Apple HealthKit data. Our findings indicate that patient-facing platforms can feasibly facilitate transmission of patient-generated health data into the EHR and support telemedicine-based care.