Pub Date : 2025-07-16DOI: 10.1016/j.hjdsi.2025.100766
Ranjani K. Paradise , Carolyn Fisher , Hanna H. Haptu , Deborah McManus , Jennifer Cochran
•
The Massachusetts Department of Public Health partnered with Lynn Community Health Center (LCHC) to scale up testing and treatment for latent tuberculosis infection (LTBI) for a non-US born patient population. The project team developed a workflow to manage patients through the LTBI care cascade with screening performed in primary care and diagnostic testing, evaluation, and treatment undertaken by a TB team within the health center. To support the clinical workflow, the team implemented process improvements, addressed access barriers, and made electronic health record (EHR) enhancements.
•
LCHC successfully increased LTBI testing and treatment for non-US born patients, while sustaining engagement through the care cascade.
•
Strategic distribution of responsibilities, attention to process refinement, EHR enhancements, and collaboration with public health experts helped make the scale-up possible.
•
Three core factors kept patients more engaged, minimized gaps in treatment, and alleviated burdens associated with LTBI treatment: 1) flexibility with scheduling visits, 2) focus on building trusting, supportive relationships between care providers and patients, and 3) consistent outreach, reminders, and follow-up with patients on treatment.
•
Maintaining high testing and treatment volumes requires consistent effort, sustained attention, and staffing continuity.
{"title":"Transforming latent tuberculosis infection (LTBI) testing and treatment at a federally qualified health center","authors":"Ranjani K. Paradise , Carolyn Fisher , Hanna H. Haptu , Deborah McManus , Jennifer Cochran","doi":"10.1016/j.hjdsi.2025.100766","DOIUrl":"10.1016/j.hjdsi.2025.100766","url":null,"abstract":"<div><div><ul><li><span>•</span><span><div>The Massachusetts Department of Public Health partnered with Lynn Community Health Center (LCHC) to scale up testing and treatment for latent tuberculosis infection (LTBI) for a non-US born patient population. The project team developed a workflow to manage patients through the LTBI care cascade with screening performed in primary care and diagnostic testing, evaluation, and treatment undertaken by a TB team within the health center. To support the clinical workflow, the team implemented process improvements, addressed access barriers, and made electronic health record (EHR) enhancements.</div></span></li><li><span>•</span><span><div>LCHC successfully increased LTBI testing and treatment for non-US born patients, while sustaining engagement through the care cascade.</div></span></li><li><span>•</span><span><div>Strategic distribution of responsibilities, attention to process refinement, EHR enhancements, and collaboration with public health experts helped make the scale-up possible.</div></span></li><li><span>•</span><span><div>Three core factors kept patients more engaged, minimized gaps in treatment, and alleviated burdens associated with LTBI treatment: 1) flexibility with scheduling visits, 2) focus on building trusting, supportive relationships between care providers and patients, and 3) consistent outreach, reminders, and follow-up with patients on treatment.</div></span></li><li><span>•</span><span><div>Maintaining high testing and treatment volumes requires consistent effort, sustained attention, and staffing continuity.</div></span></li></ul></div></div>","PeriodicalId":29963,"journal":{"name":"Healthcare-The Journal of Delivery Science and Innovation","volume":"13 2","pages":"Article 100766"},"PeriodicalIF":2.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633806","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}
Pub Date : 2025-06-24DOI: 10.1016/j.hjdsi.2025.100765
Alexis K. Barrett , John P. Cashy , John Roehm , Xinhua Zhao , Maria K. Mor , Katie J. Suda , Chester B. Good , Shari S. Rogal , Kelvin A. Tran , Jennifer A. Hale , Ron Nosek , Carolyn T. Thorpe , Francesca Cunningham , Michael J. Fine , Walid F. Gellad
Background
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.
Methods
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.
Results
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 < .001).
Conclusions
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.
Implications
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.
Level of evidence
Cross-sectional analysis of national VA data.
退伍军人事务部(VA)现在为符合条件的退伍军人提供紧急护理福利,包括访问和在VA以外的14天处方。在VA以外编写和分发的处方缺乏VA签发的处方的临床决策支持,引起了对安全性和多药的担忧。迄今为止,通过紧急护理效益对处方模式的分析有限。方法采用重复横断面设计,对2019年7月30日至2023年3月20日期间开具非va紧急护理处方的退伍军人进行调查。数据来自社区医疗报销系统(CCRS),该系统跟踪所有由va支付的非va药房分发的药物。我们将潜在的不合规处方确定为不符合VA紧急护理福利限制的处方。我们还确定了在紧急护理填补后30天内继续在VA使用的处方为“新的VA药物”。结果总体而言,83862名退伍军人收到了271476张非va紧急护理处方。退伍军人的平均年龄为55.9岁,其中79.3%为男性,73.0%为白人,86.7%为非西班牙裔,41.4%为农村居民。紧急护理使用从2020年3月的341张处方增加到2023年1月的9738张。经常配药的处方包括抗菌剂(n = 114,492, 42.2%)和激素/合成物/调节剂,如类固醇(n = 44,457, 16.4%)。潜在的不合规处方占9.3%,其中6.7%不在紧急/紧急处方中,2.6%的处方超过14天。超过70,704(26.0%)处方在VA紧急护理后访问中继续使用,其中15%没有先前的VA填充(即新的VA药物)。有新的持续退伍军人VA处方的退伍军人更有可能是男性(79.4%对73.9%)和来自城市地区(59.3%对57.5%)(All P <;措施)。从2019年到2023年,退伍军人越来越多地通过社区紧急护理中心获得非VA处方,包括由于处方不当(如类固醇)或药物相互作用(如抗生素)的潜在风险而引起VA感兴趣的药物类别。CCRS数据库可以与其他VA数据库集成,作为质量改进工具,以改善护理协调和药物安全。本评价强调了改进非VA处方的临床决策支持的必要性,并展示了集成数据系统在VA内监测和加强药物安全性和协调方面的潜力。证据水平:全国VA数据的横断面分析。
{"title":"Measuring prescriptions dispensed from urgent care through the VA community care benefit","authors":"Alexis K. Barrett , John P. Cashy , John Roehm , Xinhua Zhao , Maria K. Mor , Katie J. Suda , Chester B. Good , Shari S. Rogal , Kelvin A. Tran , Jennifer A. Hale , Ron Nosek , Carolyn T. Thorpe , Francesca Cunningham , Michael J. Fine , 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 < .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}
Pub Date : 2025-05-17DOI: 10.1016/j.hjdsi.2025.100764
Brendin R. Beaulieu-Jones , Margaret T. Berrigan , Jayson S. Marwaha , Chris J. Kennedy , Kortney A. Robinson , Larry A. Nathanson , Charles H. Cook , Jordan D. Bohnen , Gabriel A. Brat
Implementation lessons
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.
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.
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.
{"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 , Margaret T. Berrigan , Jayson S. Marwaha , Chris J. Kennedy , Kortney A. Robinson , Larry A. Nathanson , Charles H. Cook , Jordan D. Bohnen , 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}
Pub Date : 2025-05-15DOI: 10.1016/j.hjdsi.2025.100762
Susanne Schmidt , Michael A. Jacobs , Daniel E. Hall , Karyn B. Stitzenberg , Lillian S. Kao , Bradley B. Brimhall , Chen-Pin Wang , Laura S. Manuel , Hoah-Der Su , Jonathan C. Silverstein , Paula K. Shireman
Background
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.
Methods
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.
Results
Patients with Private insurance living in areas with ADI>85 had higher/worse DOOR outcomes, which lost significance after adjusting for case status. Medicare cases with ADI>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.
Conclusions
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.
{"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 , Michael A. Jacobs , Daniel E. Hall , Karyn B. Stitzenberg , Lillian S. Kao , Bradley B. Brimhall , Chen-Pin Wang , Laura S. Manuel , Hoah-Der Su , Jonathan C. Silverstein , 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>85 had higher/worse DOOR outcomes, which lost significance after adjusting for case status. Medicare cases with ADI>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}
Pub Date : 2025-05-13DOI: 10.1016/j.hjdsi.2025.100763
Andrew W. Schram , Caleb J. Murphy , David O. Meltzer
{"title":"Rethinking handoffs to optimize continuity: Four practical lessons from a novel hospitalist model","authors":"Andrew W. Schram , Caleb J. Murphy , 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}
Pub Date : 2025-05-02DOI: 10.1016/j.hjdsi.2025.100760
Michael Tang , Charisse Hunter , Shoshanah Brown , Aarthi Rao , Pooja K. Mehta , Kameron Matthews
{"title":"Delivering health equity at scale: Organizational experience with value-based care focused on marginalized populations","authors":"Michael Tang , Charisse Hunter , Shoshanah Brown , Aarthi Rao , Pooja K. Mehta , 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}
Pub Date : 2025-05-01DOI: 10.1016/j.hjdsi.2025.100761
Sarah J. Fadem , Benjamin F. Crabtree , Lawrence C. Kleinman
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.
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.
{"title":"Using codesign to engage primary care practices in a participatory change process","authors":"Sarah J. Fadem , Benjamin F. Crabtree , 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}
Pub Date : 2025-05-01DOI: 10.1016/j.hjdsi.2025.100759
Beth A. Hawks , Jennifer Perloff , V.S. Senthil Kumar , Mary Jo Larson , John D. Chapman
Background
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.
Methods
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.
Results
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.
Conclusions
We offer a novel tool for health systems to evaluate their practice patterns, which can generate valuable strategies for efficiency gains and slowing spending.
Implications
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.
{"title":"Looking at military health system surgical procedures through the lens of an episode grouper","authors":"Beth A. Hawks , Jennifer Perloff , V.S. Senthil Kumar , Mary Jo Larson , 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}
Pub Date : 2025-03-09DOI: 10.1016/j.hjdsi.2025.100758
Ashok Reddy , Jonathan Staloff , Jorge Rojas , Eric Gunnink , Scott Hagan , Alisa Becker , John Geyer , Stefanie A. Deeds , Karin Nelson , Edwin S. Wong
Background
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.
Objective
To describe and quantify changes in the provision of primary care services at two sites that have experienced EHR transition.
Design
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.
Data source and main measure
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.
Key results
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.
Conclusions
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.
{"title":"Changes in primary care encounter rates during the veteran health administration’s electronic health record transition","authors":"Ashok Reddy , Jonathan Staloff , Jorge Rojas , Eric Gunnink , Scott Hagan , Alisa Becker , John Geyer , Stefanie A. Deeds , Karin Nelson , 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}
Pub Date : 2025-01-29DOI: 10.1016/j.hjdsi.2025.100757
Danielle S. Browne , Ling Chu , Michael Burton , Joshua M. Liao
{"title":"AI-enabled decision support: The convergence of technology and decision science","authors":"Danielle S. Browne , Ling Chu , Michael Burton , 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}