Healthcare-The Journal of Delivery Science and Innovation最新文献

{"title":"Measuring prescriptions dispensed from urgent care through the VA community care benefit","authors":"Alexis K. Barrett ,&nbsp;John P. Cashy ,&nbsp;John Roehm ,&nbsp;Xinhua Zhao ,&nbsp;Maria K. Mor ,&nbsp;Katie J. Suda ,&nbsp;Chester B. Good ,&nbsp;Shari S. Rogal ,&nbsp;Kelvin A. Tran ,&nbsp;Jennifer A. Hale ,&nbsp;Ron Nosek ,&nbsp;Carolyn T. Thorpe ,&nbsp;Francesca Cunningham ,&nbsp;Michael J. Fine ,&nbsp;Walid F. Gellad","doi":"10.1016/j.hjdsi.2025.100765","DOIUrl":"10.1016/j.hjdsi.2025.100765","url":null,"abstract":"<div><h3>Background</h3><div>The Department of Veterans Affairs (VA) now offers eligible Veterans an urgent care benefit covering visits and 14-day prescriptions outside of VA. Prescriptions written and dispensed outside VA lack the clinical decision support of VA-issued prescriptions, raising concerns about safety and polypharmacy. To date, there has been limited analyses of prescribing patterns through the urgent care benefit.</div></div><div><h3>Methods</h3><div>We used a repeated cross-sectional design to examine Veterans who filled non-VA urgent care prescriptions from 07/30/2019 to 03/20/2023. Data were sourced from the Community Care Reimbursement System (CCRS), which tracks all VA-paid medications dispensed by non-VA pharmacies. We identified potentially noncompliant prescriptions as those not meeting VA urgent care benefit restrictions. We also identified prescriptions continued in VA as a “new VA medication” after 30-days from the urgent care fill.</div></div><div><h3>Results</h3><div>Overall, 83,862 Veterans received 271,476 non-VA urgent care prescriptions. Veterans’ average age was 55.9, with 79.3 % male, 73.0 % White, 86.7 % non-Hispanic, and 41.4 % rural dwelling. Urgent care use increased from 341 prescription fills in March 2020 to 9738 in January 2023. Frequently filled prescriptions included antimicrobials (n = 114,492, 42.2 %) and hormones/synthetics/modifiers, like steroids (n = 44,457, 16.4 %). Potentially noncompliant prescriptions accounted for 9.3 %, with 6.7 % not on the urgent/emergent formulary and 2.6 % supplied for over 14 days. Over 70,704 (26.0 %) prescriptions were continued in VA post-urgent care visit, of which 15 % had no prior VA fill (i.e., new VA medication). Veterans with new continued VA prescriptions were more likely to be male (79.4 % vs. 73.9 %) and from urban areas (59.3 % vs. 57.5 %) (All P &lt; .001).</div></div><div><h3>Conclusions</h3><div>Veterans increasingly received non-VA prescriptions through urgent care centers in the community from 2019 to 2023, including drug classes of interest to VA due to potential risks of inappropriate prescribing (e.g., steroids) or drug interactions (e.g., antibiotics). The CCRS database can be integrated with other VA databases as a quality improvement tool to improve care coordination and drug safety.</div></div><div><h3>Implications</h3><div>This evaluation highlights the need for improved clinical decision support for non-VA prescriptions and demonstrates the potential of integrated data systems to monitor and enhance medication safety and coordination within VA.</div></div><div><h3>Level of evidence</h3><div>Cross-sectional analysis of national VA data.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 2","pages":"Article 100765"},"PeriodicalIF":2.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical decision support amidst a global pandemic: Value of near real-time feedback in advancing appropriate post-discharge opioid prescribing for surgical patients","authors":"Brendin R. Beaulieu-Jones ,&nbsp;Margaret T. Berrigan ,&nbsp;Jayson S. Marwaha ,&nbsp;Chris J. Kennedy ,&nbsp;Kortney A. Robinson ,&nbsp;Larry A. Nathanson ,&nbsp;Charles H. Cook ,&nbsp;Jordan D. Bohnen ,&nbsp;Gabriel A. Brat","doi":"10.1016/j.hjdsi.2025.100764","DOIUrl":"10.1016/j.hjdsi.2025.100764","url":null,"abstract":"<div><h3>Implementation lessons</h3><div>Non-evidence based factors influence post-surgical opioid prescribing practices. Delivering automated near real-time opioid prescribing feedback may encourage providers to prescribe opioid quantities which are more aligned with patient consumption and institutional guidelines.</div><div>COVID-19 presented unprecedented challenges to healthcare delivery. We observed a substantial deviation in guideline-concordant opioids prescribing during the initial outbreak. However, our institution's pre-existing opioid prescribing feedback system and decision aid may have helped limit the duration and magnitude of the observed deviations by informing prescribers of atypically large opioid prescriptions and encouraging use of institutional data.</div><div>Combined with provider education, a non-directive decision aid, in the form of near, real-time email feedback, may be an effective mechanism to advance evidence-based opioid prescribing, as it retains flexibility and provider autonomy while encouraging data-driven decision making.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100764"},"PeriodicalIF":2.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One cutoff is not enough: Assessing different area deprivation index cutoffs for insurance types on surgical Desirability of Outcome Ranking (DOOR)","authors":"Susanne Schmidt ,&nbsp;Michael A. Jacobs ,&nbsp;Daniel E. Hall ,&nbsp;Karyn B. Stitzenberg ,&nbsp;Lillian S. Kao ,&nbsp;Bradley B. Brimhall ,&nbsp;Chen-Pin Wang ,&nbsp;Laura S. Manuel ,&nbsp;Hoah-Der Su ,&nbsp;Jonathan C. Silverstein ,&nbsp;Paula K. Shireman","doi":"10.1016/j.hjdsi.2025.100762","DOIUrl":"10.1016/j.hjdsi.2025.100762","url":null,"abstract":"<div><h3>Background</h3><div>Social Determinants of Health impact health outcomes. Area Deprivation Index (ADI) is used to risk-adjust for neighborhood affluence/deprivation but guidance on choosing deprivation cutoffs is lacking. We hypothesize that different ADI cutoffs are required for different insurance types.</div></div><div><h3>Methods</h3><div>National Surgical Quality Improvement Program data 2013–2019 merged with electronic health records from three academic healthcare systems. Desirability of Outcome Ranking (DOOR) assessed the association of ADI cutoffs for different insurance types, adjusted for operative stress, frailty, and case status (elective, urgent, emergent). Secondary analyses assessed the association of ADI with case status.</div></div><div><h3>Results</h3><div>Patients with Private insurance living in areas with ADI&gt;85 had higher/worse DOOR outcomes, which lost significance after adjusting for case status. Medicare cases with ADI&gt;75 exhibited higher/worse DOOR outcomes even after adjusting for case status. ADI was not associated with outcomes in the Medicaid and Uninsured groups. High ADI was associated with increased odds of urgent and emergent cases for the Private and Medicare but not Medicaid or Uninsured groups.</div></div><div><h3>Conclusions</h3><div>ADI is a useful metric to identify at-risk patients and can be used for risk adjustment. Health systems must understand their population demographics and use their data to determine ADI cutoffs. Patients in deprived neighborhoods have higher odds of urgent and emergent surgeries, despite having Private insurance or Medicare, suggesting that delays/barriers to primary and preventive care may be a major driver of worse outcomes. While insurance coverage is important, healthcare policies supporting reductions in urgent/emergent cases could have the largest impact on improving outcomes.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100762"},"PeriodicalIF":2.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking handoffs to optimize continuity: Four practical lessons from a novel hospitalist model","authors":"Andrew W. Schram ,&nbsp;Caleb J. Murphy ,&nbsp;David O. Meltzer","doi":"10.1016/j.hjdsi.2025.100763","DOIUrl":"10.1016/j.hjdsi.2025.100763","url":null,"abstract":"","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100763"},"PeriodicalIF":2.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Delivering health equity at scale: Organizational experience with value-based care focused on marginalized populations","authors":"Michael Tang ,&nbsp;Charisse Hunter ,&nbsp;Shoshanah Brown ,&nbsp;Aarthi Rao ,&nbsp;Pooja K. Mehta ,&nbsp;Kameron Matthews","doi":"10.1016/j.hjdsi.2025.100760","DOIUrl":"10.1016/j.hjdsi.2025.100760","url":null,"abstract":"","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100760"},"PeriodicalIF":2.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143894977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using codesign to engage primary care practices in a participatory change process","authors":"Sarah J. Fadem ,&nbsp;Benjamin F. Crabtree ,&nbsp;Lawrence C. Kleinman","doi":"10.1016/j.hjdsi.2025.100761","DOIUrl":"10.1016/j.hjdsi.2025.100761","url":null,"abstract":"<div><div>Healthcare has experienced significant transformation in recent years with many changes being imposed on practices from outside sources. When tailoring outside interventions to specific settings, it is important to engage practice members in participatory processes. Yet, tailoring remains a difficult and poorly understood element of implementation. Codesign is one method to achieve context-sensitive, bottom-up change by engaging stakeholders in the design process. With a complex adaptive system (CAS) perspective, codesign reframes interventions as tools to empower practices to drive change based on local challenges and experiences rather than change being imposed upon them. Observing adaptations and facilitating innovations of practice members offers insight into dynamics of the CAS, implementation context, and its limitations. Here, the codesign process is illustrated through a pediatric primary care practice adopting integrated health.</div><div>Contextual inquiry was performed using ethnographic observations to identify barriers and facilitators to integrated health. Observation findings informed codesign workshops with clinicians. Workshop transcripts and drawings were analyzed using an immersion/crystallization approach guided by the Practice Change Model (PCM), an established framework based on complexity science concepts. In these workshops, clinicians described tension between their motivations to care for complex patients and limitations imposed by the health system. Participants’ knowledge of their real-world context allowed them to identify resources and opportunities for changes they could make within their current environment. The reconciliation of the ideal and the real is a core benefit of codesign methods. This innovative approach can be applied more generally to support the development, implementation, and evaluation of interventions that reflect real world interactions and complexities.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100761"},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Looking at military health system surgical procedures through the lens of an episode grouper","authors":"Beth A. Hawks ,&nbsp;Jennifer Perloff ,&nbsp;V.S. Senthil Kumar ,&nbsp;Mary Jo Larson ,&nbsp;John D. Chapman","doi":"10.1016/j.hjdsi.2025.100759","DOIUrl":"10.1016/j.hjdsi.2025.100759","url":null,"abstract":"<div><h3>Background</h3><div>With mounting accountability pressure on their publicly funded health system and the demand for a medically ready military force, the military health system (MHS) employs a strategy to optimize care delivery. Research suggests that analysis of episodes of care is a valuable tool for identifying the relative resource use for a given procedure and can direct enhancements in care delivery.</div></div><div><h3>Methods</h3><div>This proof-of-concept study investigates the feasibility of grouping services for surgical patients into episodes of care. These episodes of care served as a unit of analysis for evaluating resource use within a public healthcare system. Borrowing from a grouping tool developed for the Centers for Medicare and Medicaid Services by Brandeis University, we developed methods to employ it with MHS clinical encounter and claims data. Data included all care paid for by the MHS from FY2009-2015, including care delivered inside and outside of their facilities.</div></div><div><h3>Results</h3><div>Using this analytic grouping tool, we grouped 49 percent of our administrative data into episodes of care. In these episodes, we see variation in both the care provided directly by the MHS and care provided by the network of private sector providers in rates of sequelae based on the service area for specific surgical procedures.</div></div><div><h3>Conclusions</h3><div>We offer a novel tool for health systems to evaluate their practice patterns, which can generate valuable strategies for efficiency gains and slowing spending.</div></div><div><h3>Implications</h3><div>Outside of the traditional population-based metrics to evaluate efficiency, episodes of care are a valuable tool for identifying the mix of services used to produce a given surgical outcome.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100759"},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in primary care encounter rates during the veteran health administration’s electronic health record transition","authors":"Ashok Reddy ,&nbsp;Jonathan Staloff ,&nbsp;Jorge Rojas ,&nbsp;Eric Gunnink ,&nbsp;Scott Hagan ,&nbsp;Alisa Becker ,&nbsp;John Geyer ,&nbsp;Stefanie A. Deeds ,&nbsp;Karin Nelson ,&nbsp;Edwin S. Wong","doi":"10.1016/j.hjdsi.2025.100758","DOIUrl":"10.1016/j.hjdsi.2025.100758","url":null,"abstract":"<div><h3>Background</h3><div>Electronic health record (EHR) transitions can cause major disruptions in the provision of primary care services. Veteran Health Administration (VHA), one of the largest integrated healthcare systems, underwent a major EHR transition at two sites. To date, there is limited data on the experience of primary care service lines at EHR transition sites.</div></div><div><h3>Objective</h3><div>To describe and quantify changes in the provision of primary care services at two sites that have experienced EHR transition.</div></div><div><h3>Design</h3><div>We conducted a retrospective study of primary care encounters 12 months before and after EHR transition. In addition, we applied economic structural change analysis using the expanded length of time (10 years of prior primary care encounters at sites) to understand how the transition of EHR compares to other major changes in primary care encounter volume during this time period.</div></div><div><h3>Data source and main measure</h3><div>Primary care encounters were measured using algorithms pre- and post-EHR transition from the national VHA Corporate Data Warehouse (CDW) and Cerner Millennium (CDW2) Databases.</div></div><div><h3>Key results</h3><div>In Spokane, the average number of monthly primary care encounters decreased from 7155 (SD = 682) in the 12 months prior to October 2020 (transition date) to 4181 (SD = 813) in the 12 months after implementation, a decrease of 41.6 %. The average number of monthly primary care encounters decreased from 8029 (SD = 511) in the 12 months prior to April 2022 (transition date) to 6495 (SD = 1152) in the 12 months after implementation, a decrease of 19.1 %. The structural change analysis identified EHR transition dates at both sites, including a major decrease in volume of primary care encounters.</div></div><div><h3>Conclusions</h3><div>Given the substantial decrease in primary care services, VHA must identify strategies to mitigate both the amount and the duration of reduced primary care encounters during the EHR transition.</div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100758"},"PeriodicalIF":2.0,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enabled decision support: The convergence of technology and decision science","authors":"Danielle S. Browne ,&nbsp;Ling Chu ,&nbsp;Michael Burton ,&nbsp;Joshua M. Liao","doi":"10.1016/j.hjdsi.2025.100757","DOIUrl":"10.1016/j.hjdsi.2025.100757","url":null,"abstract":"","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 1","pages":"Article 100757"},"PeriodicalIF":2.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Reading the crystal ball: Primary care implications while awaiting outcomes for multi-cancer early detection tests\" [Healthcare 11 (2023) 100705].","authors":"Grace A Lin, Kathryn A Phillips, A Mark Fendrick","doi":"10.1016/j.hjdsi.2024.100755","DOIUrl":"https://doi.org/10.1016/j.hjdsi.2024.100755","url":null,"abstract":"","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":" ","pages":"100755"},"PeriodicalIF":2.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}