Background Structured Problem Solving (SPS) is a patient-centered approach to promoting behavior change that relies on productive collaboration between coaches and participants and reinforces participant autonomy. We aimed to describe the design, implementation, and assessment of SPS in the multicenter Prevention of Urinary Stones with Hydration (PUSH) randomized trial.Methods In the PUSH trial, individuals with a history of urinary stone disease and low urine output were randomized to control versus a multicomponent intervention including SPS that was designed to promote fluid consumption and thereby prevent recurrent stones. We provide details specifically about training and fidelity assessment of the SPS coaches. We report on implementation experiences related to SPS during the initial conduct of the trial.Results With training and fidelity assessment, coaches in the PUSH trial applied SPS to help participants overcome barriers to fluid consumption. In some cases, coaches faced implementation barriers such as variable participant engagement that required tailoring their work with specific participants. The coaches also faced challenges including balancing rapport with problem solving, and role clarity for the coaches.Conclusions We adapted SPS to the setting of kidney stone prevention and overcame challenges in implementation, such as variable patient engagement. Tools from the PUSH trial may be useful to apply to other health behavior change settings in nephrology and other areas of clinical care.Trial registration ClinicalTrials.gov Identifier NCT03244189.

Introduction: The United States lacks a national interfacility patient transfer coordination system. During the coronavirus 2019 (COVID-19) pandemic, many hospitals were overwhelmed and faced difficulties transferring sick patients, leading some states and cities to form transfer centers intended to assist sending facilities. In this study we aimed to explore clinician experiences with newly implemented transfer coordination centers. Methods: This mixed-methods study used a brief national survey along with in-depth interviews. The American College of Emergency Physicians Emergency Medicine Practice Research Network (EMPRN) administered the national survey in March 2021. From September-December 2021, semi-structured qualitative interviews were conducted with administrators and rural emergency clinicians in Arizona and New Mexico, two states that started transfer centers during COVID-19. Results: Among 141 respondents (of 765, 18.4% response rate) to the national EMPRN survey, only 30% reported implementation or expansion of a transfer coordination center during COVID-19. Those with new transfer centers reported no change in difficulty of patient transfers during COVID-19 while those without had increased difficulty. The 17 qualitative interviews expanded upon this, revealing four major themes: 1) limited resources for facilitating transfers even before COVID-19; 2) increased number of and distance to transfer partners during the COVID-19 pandemic; 3) generally positive impacts of transfer centers on workflow, and 4) the potential for continued use of centers to facilitate transfers. Conclusion: Transfer centers may have offset pandemic-related transfer challenges brought on by the COVID-19 pandemic. Clinicians who frequently need to transfer patients may particularly benefit from ongoing access to such transfer coordination services. [West J Emerg Med. 2024;25(5)758-766.]

Marketplace health plans provide multiple levels of health care coverage with premiums based on five standard criteria: age, geographic location, tobacco use, individual versus family, and tiered categories that define how costs are shared between the insured person and the insurance company. Because plans are offered by insurance companies, they are often optimized to maximize profit rather than primarily considering patient affordability.1Health Insurance Marketplace. How Health Insurance Marketplace Plans Set Your Premiums. 2021. Accessed September 7, 2021. https://www.healthcare.gov/how-plans-set-your-premiums/Google Scholar Despite the ubiquitous availability and variety of marketplace health plans, few studies have investigated the level of asthma-related out-of-pocket (OOP) spending for commercially insured patients across different asthma types, plan types, and income levels.2Galbraith A.A. Ross-Degnan D. Zhang F. Wu A.C. Sinaiko A. LeCates R.F. et al.Association of controller use and exacerbations for high-deductible plan enrollees with and without family members with asthma.Ann Am Thorac Soc. 2021; 18: 1255-1260Google Scholar Understanding this association would enable health care policy-makers to understand how the structure of health care plans influence patient care and, if needed, to optimize and regulate the plan to ensure fair access to asthma-related care. In the current issue, Sinaiko et al3Sinaiko A. Gaye M. Wu A. Bambury E. Zhang F. Xu X. et al.Out-of-pocket spending for asthma-related care among commercially insured patients, 2004-2016.J Allergy Clin Immunol Pract. 2021; 9: 4324-4331Google Scholar analyzed asthma-related OOP expenditures for commercially insured patients and the correlation with health care plan levels and patient income. The study compiled enrollment, claims, and geocoded census tract data from nearly 2 million patients aged 4 to 64 years from 2004 to 2016 who are enrolled in a commercial health plan. Patients enrolled under Medicare were not included. The study defined OOP spending as the total of the patient deductible, coinsurance, and copayment amounts. Out-of-pocket spending was sorted into five categories: (1) emergency department services, (2) inpatient services, (3) outpatient services, (4) asthma medications, and (5) asthma-related durable medical equipment (eg, spacers and nebulizers). Asthma medications were further divided into (1) controller medications (including inhaled corticosteroids, leukotriene inhibitors, and inhaled corticosteroid/long-acting β-agonists; (2) albuterol/non-albuterol rescue medications; and (3) oral steroids. Patient income level was captured by geographic poverty level through the census tract and categorized into quintiles. For all patients, the highest fraction of total asthma-related OOP spending was for asthma medications, in which increasing fraction was correlated with increasing income. Also, patients enrolled in high-deductible health plans (HDHP), defined in the study as a co-pay of $1000 or more per year, who have intermittent and persistent asthma, pay higher OOP expenses than low-deductible health plan patients with the same type of asthma. The study reveals, with high statistical significance, systematic differences in prescription drug spending between income levels: patients in the lowest-income quintile spent an average of $47/y and patients in the highest-income quintile spent an average of $66/y. In addition, of the prescription drugs, controller medication use is highest in the high-income quartile. Patients in the lowest-income quintile spent the highest proportion of OOP expenses on outpatient care, inpatient care, and emergency care. This indicates that a higher co-pay burden leads to increased illness and hospital expense, which is aligned with conclusions of previous studies.4Wharam J.F. Zhang F. Landon B.E. Soumerai S.B. Ross-Degnan D. Low-socioeconomic-status enrollees in high-deductible plans reduced high-severity emergency care.Health Aff (Millwood). 2013; 32: 1398-1406Google Scholar The HDHP data suggest that OOP spending is similar between low-income and high-income patients but results in a larger fractional income burden for low-income patients. Thus, there may be a bias toward preventative care through prescription drugs by higher-income patients and a bias toward reactionary care by lower-income individuals. With less use of controller medications, lower-income individuals are at risk for more acute illness episodes and higher long-term health spending. Since the end of the study, biologic medications, which are parenteral treatments for eosinophilic asthma and poorly controlled asthma, have become more widely used. The first biologic, omalizumab, was approved by the Food and Drug Administration in 2003, followed by mepolizumab in 2015, reslizumab in 2016, benralizumab in 2017, and dupilumab in 2019.5[email protected] FDA-Approved Drugs. 2021. Accessed August 28, 2021. https://www.accessdata.fda.gov/scripts/cder/daf/index.cfmGoogle Scholar These are the most expensive approved asthma medications, with an annual total cost upward of $30,000/patient.6Anderson III, W. Szefler S.J. Cost-effectiveness and comparative effectiveness of biologic therapy for asthma. Table 1.Ann Allergy Asthma Immunol. 2019; 122: 367-372Google Scholar Out-of-pocket spending for this new class of medications and their impact on health care plan tiers are important to understand and should be a focus of future studies. The study uncovers an interesting trend in which HDHP enrollment increased from 7% to 54% throughout the study period. During this time, OOP spending for those with intermittent asthma systematically decreased. However, patients with persistent asthma experienced an increase in OOP spending until 2009, and then OOP spending subsequently decreased through 2016 below 2004 levels. These may have fascinating implications for asthma-related health care costs and merit further study for underlying causal factors. The study was funded by the Patient-Centered Outcomes Research Institute (PCORI), a US-based nonprofit created in 2010 by the Affordable Care Act.7Patient-Centered Outcomes Research Institute. PCORI. 2021. Accessed August 30, 2021. https://www.pcori.org/Google Scholar The Board of Governors consists of the director of the Agency for Healthcare Research and Quality, the director of the National Institutes of Health, and other members who are appointed by the comptroller general. Their mission is to help people make informed health care decisions and improve health care delivery and outcomes. The current allocation of $2.66/insured life is assessed to each insurance company by congressional action to fund the PCORI. This PCORI-funded study is a part of a larger evaluation of the effect of HDHP on cost and morbidity, dubbed the AFFORD Study.7Patient-Centered Outcomes Research Institute. PCORI. 2021. Accessed August 30, 2021. https://www.pcori.org/Google Scholar Since these 2016 data, we have seen an increase in price transparency and in discount coupons such as Good Rx. Pharmaceutical firms are sponsoring co-pay assistance programs for low-income patients for the more expensive medications. The competing strategies of patient assistance programs and co-pay accumulator adjustment programs create confusion and administrative burden for clinicians and patients, potentially reducing adherence to clinically indicated services and worsening patient outcomes.8Fendrick A.M. Buxbaum J.D. Precision medicines need precision patient assistance programs.Am J Manag Care. 2019; 25: 317-318Google Scholar Affordability of drugs is a major barrier to medication compliance, and adherence to medication is a serious problem for disease management.9Sabaté E. Adherence to Long-term Therapies: Evidence for Action. World Health Organization, Geneva, Switzerland2003Google Scholar An experiment by Blue Cross Blue Shield of Louisiana removed co-pays from pharmaceuticals for asthma, diabetes, hypertension, and mental illness in almost 6500 patients, with a resultant decrease in insurance costs.10Cong M. Chaisson J. Cantrell D. Mohundro B.L. Carby M. Ford M. et al.Association of co-pay elimination with medication adherence and total cost.Am J Manag Care. 2021; 27: 249-254Google Scholar Thus, benefit designs that eliminate co-pays for patients with chronic illnesses may improve adherence and reduce the total cost of care. Because a greater percentage of the population is enrolled in HDHPs, the ability of patients to pay for OOP care will affect their health outcomes. This may shift patient care from a preventative to a reactive posture with increased patient risk. As one patient said, “It is good that grocery stores now have pharmacies. When you go in, you can decide if you should buy food or medicine.” This exemplifies the importance of providing patients of all income levels the comfort of affording the same type of categorical care. Out-of-Pocket Spending for Asthma-Related Care Among Commercially Insured Patients, 2004-2016The Journal of Allergy and Clinical Immunology: In PracticeVol. 9Issue 12PreviewOut-of-pocket (OOP) health care costs can cause financial burden and deferred care for many Americans. Little is known about OOP spending for asthma-related care among the commercially insured. Full-Text PDF

No AccessJournal of UrologyJU Forum1 Sep 2021Impact of COVID-19 on Prevention of Urinary Stones with Hydration (PUSH) Study: Challenges and Opportunities for Future Trials The Urinary Stone Disease Research Network (USDRN) Investigators The Urinary Stone Disease Research Network (USDRN) Investigators View All Author Informationhttps://doi.org/10.1097/JU.0000000000001833AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail References 1. : Clinical trials in urology: predictors of successes and failures. J Urol 2020; 204: 805. Link, Google Scholar 2. : Prevention of Urinary Stones with Hydration (PUSH): design and rationale of a clinical trial. Am J Kidney Dis 2021; 77: 898. Google Scholar 3. : An observational study of the association of video- versus text-based informed consent with multicenter trial enrollment: lessons from the PALM study (Patient and Provider Assessment of Lipid Management). Circ Cardiovasc Qual Outcomes 2018; 11: e004675. Google Scholar This research was supported by the National Institutes of Health/NIDDK, as follows: U01DK110961 (UPenn/CHOP—PP Reese, GE Tasian), U01KD110986 (Washington University in St. Louis—AC Desai, HH Lai), U01DK110994 (UT Southwestern—NM Maalouf), U01DK110954 (University of Washington—JD Harper, H Wessells), and U01DK110988 (Duke University—CD Scales, HR Al-Khalidi). Financial interest and/or other relationship with Allena Pharmaceuticals (CD Scales). © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue 3September 2021Page: 502-504 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.AcknowledgmentsUrinary Stone Disease Research Network: The following individuals were instrumental in the planning and conduct of the PUSH study at each of the participating institutions. Clinical Centers: University of Pennsylvania/Children’s Hospital of Pennsylvania, Philadelphia, Pennsylvania: Principal Investigator: Peter P. Reese, MD, MSCE, Gregory E. Tasian, MD, MSCE; Co-Investigators: Sandra Amaral, MD, MHS, Janet Audrain-McGovern, PhD; Study Coordinators: Emily Funsten, Brittney Henderson, Kristen Koepsell, Adam Mussell. University of Texas Southwestern Medical Center, Dallas, Texas: Principal Investigator: Naim M. Maalouf, MD; Co-Investigators: Jodi A. Antonelli, MD, Linda A. Baker, MD, Margaret S. Pearle, MD, PhD, Lakshmi Ananthakrishnan, MD; Study Coordinators: Joyce Obiaro, Cynthia Rangel, Martinez Hill, Madeline Worsham. University of Washington, Seattle, Washington: Principal Investigator: Jonathan D. Harper, MD, Hunter Wessells, MD; Co-Investigators: Fionnuala Cormack, MD, Mathew Sorensen, MD, Karyn Yonekawa, MD; Study Coordinators: Holly Covert, Tristan Baxter, Elsa Ayala. Washington University in St. Louis, St. Louis, Missouri: Principal Investigator: Alana C. Desai, MD, H. Henry Lai, MD; Co-Investigators: Vincent Mellnick, MD, Douglas Coplen, MD; Study Coordinators: Juanita Taylor, Aleksandra Klim, Deborah Ksiazek. Recruiting Centers: Cleveland Clinic Foundation, Cleveland, Ohio: Principal Investigator: Sri Sivalingam, MD, MSc, FRCSC; Co-Investigators: Katherine Dell, MD, Juan Calle, MD; Study Coordinators: Paige Gotwald, Marina Markovic. Mayo Clinic Foundation, Rochester, Minnesota: Principal Investigator: John Lieske, MD; Co-Investigators: Andrew Rule, MD, Stephen Erickson, MD, Aaron Potrezke, MD, Andrea Ferrero, PhD, David Sas, DO; Study Coordinators: Angela Waits, Courtney Lenort. Scientific Data Research Center: Duke Clinical Research Institute, Duke University, Durham, North Carolina: Principal Investigator: Charles D. Scales, Jr., MD, MSHS, Hussein R. Al-Khalidi, PhD; Co-Investigators: Kevin Weinfurt, PhD, Hayden Bosworth, MD; Statistician: Honqiu Yang, PhD; Project Lead: Laura Johnson; Lead CRA: Sharon Settles; CRA: Angela Venetta; Data Manager: Omar Thompson. National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): Project Scientist: Ziya Kirkali, MD; Program Official: Christopher Mullins, PhD. Data Safety and Monitoring Board: John Denstedt, MD (Chair), Dean G. Assimos, MD, Uri Alon, MD, Scott Cohen, MD, Michael A Freeman, MD, Rebecca A Krukowski, PhD, Jeannette Lee, PhD, Eric Taylor, MD, Jennifer Temple, PhD, Christopher H Schmid, PhD. Past members: Gary C. Curhan, MD, ScD, David S. Goldfarb, MD, Manoj Monga, MD, FACS, Andrew Rule, MD, Marshall Stoller, MD.Metrics Author Information The Urinary Stone Disease Research Network (USDRN) Investigators More articles by this author Expand All This research was supported by the National Institutes of Health/NIDDK, as follows: U01DK110961 (UPenn/CHOP—PP Reese, GE Tasian), U01KD110986 (Washington University in St. Louis—AC Desai, HH Lai), U01DK110994 (UT Southwestern—NM Maalouf), U01DK110954 (University of Washington—JD Harper, H Wessells), and U01DK110988 (Duke University—CD Scales, HR Al-Khalidi). Financial interest and/or other relationship with Allena Pharmaceuticals (CD Scales). Advertisement PDF downloadLoading ...

Anxiety, depression, and stress-related disorders are complex neurobehavioral diseases with a partially heritable genetic basis. This chapter explores how the appropriate use of rodent models can illuminate the neurobiological underpinnings of these disorders. Because these psychiatric disorders are uniquely human, rodent models typically model individual components rather than trying to recapitulate the disease itself. This chapter considers how both intermediate phenotypes and rodent models fit into this framework. Integrating these two concepts can be bidirectional: studying intermediate phenotypes in rodent models may lead to identifying risk genes that are present in humans, or human studies may uncover genetic variants linked to intermediate phenotypes and subsequent experiments in rodents may be employed to examine the causal mechanisms. This dynamic interplay is explored throughout the chapter.