High-value Care Research Articles

Strengthening the pain care ecosystem to support equitable, person-centered, high-value musculoskeletal pain care

Abstract Improving health and wellbeing outcomes for people experiencing chronic musculoskeletal pain requires collective efforts across multiple levels of a healthcare ecosystem. System-wide barriers to care equity must however be addressed (eg, lack of co-designed services; overuse of low value care/underuse of high value care; inadequate health workforce; inappropriate funding models; inequitable access to medicines and technologies; inadequate research and innovation). In this narrative review, utilizing a systems’ thinking framework, we synthesize novel insights on chronic musculoskeletal pain research contextualized through the lens of this complex, interconnected system, the “pain care ecosystem.” We examine the application of systems strengthening research to build capacity across this ecosystem to support equitable person-centred care and healthy ageing across the lifespan. This dynamic ecosystem is characterized by three interconnected levels. At its centre is the person experiencing chronic musculoskeletal pain (micro-level). This level is connected with health services and health workforce operating to co-design and deliver person-centred care (meso-level), underpinned further upstream by contemporary health and social care systems (macro-level context). We provide emerging evidence for how we, and others, are working towards building ecosystem resilience to support quality musculoskeletal pain care: at the macro-level (eg, informing musculoskeletal policy and health strategy priorities); at the meso-level (eg, service co-design across care settings; health workforce capacity); and downstream, at the micro-level (eg, person-centred care). We outline the mechanisms and methodologies utilized and explain the outcomes, insights and impact of this research, supported by real world examples extending from Australian to global settings.

6.Y.1. Defining, measuring, and reducing low-value care in Europe - proposing a new definition and framework

Abstract The EU Expert Group on Health Systems Performance Assessment (HSPA) selected value-based healthcare, with a focus on low-value care, as the work topic for 2023-2024. Against the backdrop of increasing healthcare expenditures and the overall aim to deliver high quality and efficient healthcare, efforts to reduce waste and inefficiencies have long been emerging in health systems worldwide. Value-based healthcare shifts the focus towards improving patient outcomes; the concept of low-value care in particular aims to identify health services that provide little or no health benefits but expose patients to potential harm. The COVID-19 pandemic clearly demonstrated that value-based healthcare is a prerequisite for high-performing health systems and the need to steer resource allocation to those services that maintain or improve health. The reduction in certain elective services observed during the pandemic (e.g. tonsillectomies) indicates that there may be areas for potential dis-investment and reallocation of resources to higher-value care. The pandemic has thereby emphasized the need for identifying and systematizing measurable efforts directed at reducing low-value care. Tackling low-value care can contribute to alleviating health workforce constraints by ensuring that efforts are focused where they are most beneficial, and not on unnecessary services. Engaging and educating the health workforce about low-value care and how to reduce it is a key measure in this direction. What is more, there is increasing awareness about the health sector’s considerable environmental footprint. Reducing low-value care would contribute to less greenhouse gas emissions, energy consumption and air pollution from the delivery of health services. Despite intensified efforts to address waste and inefficiencies in healthcare in the last decade, the ability of health systems in Europe to identify and reduce low-value care varies. Through the Expert Group’s work, a new comprehensive definition was proposed and a framework to distinguish different types of low-value care was developed as a basis for identifying and tackling low-value care in EU Member States. Indicators to measure low-value care as well as measures to reduce it were collected. This workshop aims to present the findings of the Expert Group´s work on low-value care and to discuss them with conference participants to both raise awareness and identify priority elements for future activities. After a brief introduction on the definition, framework, obstacles and solutions, the panelists will share their views and experiences, followed by a facilitated discussion with the audience. Key messages • A comprehensive definition of low-value care and an accompanying framework for categorizing and identifying low-value care is proposed. • Country experiences with indicators to measure low-value care and strategies to reduce it, as well as related methodological obstacles, offer substantial opportunities for cross-country learning.

Digital health apps : How to achieve the successful integration into healthcare

Digital health applications (apps) have been available on prescription since 2019 and offer a multitude of functions in health monitoring, symptom recognition, follow-up monitoring and patient care. The Digital Care Act from 2023 strives for a comprehensive integration of apps into medical care. The utilization of artificial intelligence (AI) in health apps promises an earlier diagnosis, sensitive symptom monitoring, optimization of courses of treatment, more effective doctor-patient communication and saving of resources. The integration of health apps and AI can enable a stronger personalized high-value care.

6635 A Call for High-Value Diabetic Retinopathy Screening and the Introduction of a Novel Predictive Model

Abstract Disclosure: P.J. Williams: None. C. Kim: None. K. Ziadeh: None. E. White: None. C.S. Chen-Milhone: None. L.D. Lugo: None. K.B. Ellis: None. M.S. Juzych: None. Introduction: Diabetic retinopathy (DR) remains one of the leading causes of preventable blindness in middle-aged and older populations. Late-stage DR is often visually symptomatic; however, early DR is generally asymptomatic and requires screening. For type 2 diabetes mellitus (T2DM), the American Diabetes Association and the National Institute of Diabetes and Digestive and Kidney Diseases recommend an initial dilated eye exam with follow-up every 1-3 years, or annually if diabetic retinopathy is detected. Despite these guidelines, providers and insurers in the United States routinely recommend annual screening regardless of other factors. Methods: A cross-sectional analysis with prospective data verification was done for new diabetic eye exam referrals from August 2021 through July 2022 to address screening discrepancies. Established patients and referrals unrelated to hyperglycemia were excluded. Data collection included duration of diabetes, last hemoglobin A1c (HbA1c), maximum HbA1c, age, race, gender, BMI, relevant medication use, and imaging, as well as the presence of hypertension, hypercholesterolemia, diabetic peripheral neuropathy (DPN), diabetic nephropathy, diabetic amputation, and DR and data was verified against objective records up to 2 years later. Logistical multivariate analysis was conducted by a trained statistician. Results: 474 consecutive patients were referred over 1 year. Among all referrals, 2.11% (10/474) of patients were prediabetic. Among the patients with diabetes, 5.39% (25/464) were type 1 and 94.6% (439/464) were type 2. Among patients with T2DM, the average age was 57.64±11.52 (range = 25-98) and females made up 52.16% (229/439). The average diabetes duration among T2DM patients with DR was 19.39±8.45 years (range = 11-51) compared to 6.12±5.77 years (range = 0-31 years) without DR. Maximum lifetime HbA1c (p=0.0016), duration of diabetes (p<0.0001), and presence of DPN (p = 0.0047) were the strongest predictors of DR in patients with T2DM. A predictive model for DR was created utilizing these variables and hypercholesterolemia (p=0.048) with a predictive accuracy of 89.5% (chi-squared value (4)=121.451, p<0.001, Nagelkerke R2=57%). Sensitivity and specificity measured 92.31% and 87.99% respectively. The area under the ROC curve measured 0.952 (CI 0.925 to 0.972, p<0.0001). Conclusion: Duration of diabetes, maximum HbA1c, and DPN are strongly associated with DR among patients with T2DM and should be tracked to guide screening. Among T2DM patients with a well-documented recent onset of diabetes, maximum HbA1c less than 8, and benign initial eye exam, annual diabetic eye exams are unlikely to reveal DR in the first 10 years after onset. Based on our data, annual diabetic screening exams are unnecessary for many patients, and upper limits of screening intervals should be considered in low-risk patients to increase high-value care. Presentation: 6/2/2024

340B Participation and Safety Net Engagement Among Federally Qualified Health Centers

The 340B program provides discounts on outpatient drugs to certain hospitals and federally supported clinics (covered entities) that can be used to generate revenue to fund safety net care. While numerous studies have found no association between 340B and safety net care provision for most hospital covered entities, less is known about whether federally qualified health centers (FQHCs), the largest group of covered entities after hospitals, use the program to enhance safety net care. To assess whether a proxy for 340B revenue was associated with increased safety net care provision among FQHCs. This descriptive, retrospective cohort study examined care provided from 2005 to 2022 by 1468 FQHCs that submitted to the Health Resources and Services Administration Uniform Data System. FQHC and year-level fixed effects were included, as well as a control for differential Medicaid expansion over time. The data were analyzed between March and December 2023. One-year lagged number of locations registered to dispense or administer 340B-discounted drugs (registered locations), which included child sites, in-house pharmacies, and contract pharmacies in the 340B Outpatient Pharmacy Affairs Database. Natural logarithm of patient volume by payer, low-income status, and use of enabling services. Natural logarithm of visits in which low-profit preventive services were provided. An additional registered location was associated with increased patient volume, especially for uninsured (0.4%; 95% CI, 0.3%-0.5%) and privately insured (0.4%; 95% CI, 0.2%-0.5%) patients and low-income (0.4%; 95% CI, 0.2%-0.6%), unhoused (0.3%; 95% CI, 0.1%-0.5%), and non-English-speaking (0.3%; 95% CI, 0.1%-0.5%) patients. An additional registered location was associated with increased visits with an HIV test (0.7%; 95% CI, 0.4%-0.9%), serum lead test (0.8%; 95% CI, 0.6%-1.1%), seasonal influenza shot (0.4%; 95% CI, 0.3%-0.5%), Papanicolaou smear (0.5%; 95% CI, 0.4%-0.7%), and tobacco cessation counseling (1.0%; 95% CI, 0.5%-1.4%). Across the study period, the average annual increase in locations was 1.5. The results of this cohort study suggest that there are statistically significant increases in the provision of low-profit but high-value preventive services and care to safety net populations (those who lack insurance, have a low income, or require enabling services) and that, like public hospitals, FQHCs might use 340B revenues to enhance safety net care. This finding may inform debates on the 340B program by supporting differential 340B reforms across hospital and nonhospital covered entities.

High-value care modeling: Evaluating cost conscious and potentially wasteful behaviors.

42 Background: Value-based care is key to decreasing waste, addressing increasing healthcare costs, and minimizing patient financial toxicity - especially in the treatment of high-cost diagnoses such as cancer. Medical student exposure to role-modeling of high-value care (HVC) behaviors may help shape professional identity formation and have long-term effects on future practices. Our study aimed to investigate the frequency and characteristics of faculty role-modeling of HVC in medical student core clinical rotations. Methods: A cross-sectional survey study was performed with third- and fourth-year medical students on clinical rotations at 11 U.S. medical schools. The survey assessed thirteen variables associated with cost conscious role-modeling behaviors or potentially wasteful role-modeling behaviors, as well as questions characterizing the rotation such behaviors were observed on, demographic information, and organizational culture around HVC. Results: Cost-conscious role-modeling behaviors were observed “sometimes” or “often” between 52.9-70.5% of the time across all clinical rotations, with the exception of observing a student or resident being praised for ordering a cost-effective diagnostic work-up (seen only 25.7% of the time). Potentially wasteful role modeling behaviors were observed “sometimes” or “often” 5%-14.3% of the time, except simultaneously ordering numerous tests before seeing results of initial screening tests (45.1%) and repeating tests rather than attempting to obtain recently performed test results (42.9%). HVC was most often observed on internal medicine rotations (58.3%) and least frequently on surgery rotations (34.5%). Attendings were significantly more likely to model HVC compared to residents/fellows in 5/7 domains. Organizational culture correlated with frequency of HVC behavior observed. Conclusions: HVC role-modeling behaviors, as observed by medical students, are variable across clinical rotations. HVC practices are essential not only within oncology, but across all medical specialties; future studies should strive to identify factors which promote or inhibit HVC modeling and understand differences between HVC education in undergraduate medical curriculum.

Impact of screening on mortality for patients diagnosed with hepatocellular carcinoma at a safety-net hospital: An opportunity for addressing disparities.

140 Background: Hepatocellular carcinoma (HCC) is a common and deadly cancer with a rising incidence in the US. HCC almost always develops on a background of chronic liver disease, which disproportionately affects individuals of lower socioeconomic status (SES), perpetuating existing disparities. Compounding these disparities, individuals of lower SES are less likely to participate in recommended cancer screening exams. Here, we describe the outcomes of patients diagnosed with HCC at a large urban safety-net hospital primarily serving the underserved. Methods: We identified patients diagnosed with HCC at John Peter Smith Hospital in Fort Worth, Texas from January 1, 2018, to March 31, 2021 to determine the impact of screening on survival. Patients were allocated to the screened cohort if they had undergone liver imaging within one year prior to HCC diagnosis. Kaplan-Meier methods and log-rank test were used to illustrate and compare 3-year survival curves from an index date of diagnosis until death. Cox proportional hazards model were used to calculate unadjusted and adjusted hazards ratios (HR) and 95% confidence intervals (CI). Lead time bias was adjusted in a sensitivity analysis using the Duffy adjustment and a sojourn time of 70 days and 140 days. Results: A total of 158 patients were included (n=53 screened, n=105 unscreened). The mean age was 62 years; 144 (91%) had cirrhosis, 78% were male, 34% were non-Hispanic white, and 8.2% had private insurance. Those in the unscreened cohort had more severe liver dysfunction (as measured by the ALBI grade) and produced higher levels of AFP, but were less likely to have cirrhosis than the screened cohort. The median overall survival (OS) for the screened cohort was 19.0 months (95% CI: 9.9-NA) and 5.4 months (95% CI: 3.7-8.5) in the unscreened cohort (HR death (unscreened v screened) = 2.4, 95% CI: 1.6-3.6; log rank P <0.0001). After adjusting for ALBI grade, AFP, hepatitis C, insurance status and initial treatment, there was a statistical difference in hazard of death in the three years (HR: 2.3; 95% CI: 1.5-3.6), favoring the screened cohort. The benefit for screening remained after adjusting for lead-time bias. With a mean sojourn time of 70 days, the HR death was 2.19 (95% CI 1.4-3.3, P =0.0002) and was 2.09 (1.4-3.2, P =0.0005) with a 140-day sojourn time. Conclusions: In an urban safety-net population, screening for HCC was associated with improved outcomes compared to patients with incidentally-diagnosed HCC. Altogether, this implies that earlier diagnosis and institution of treatment can positively improve survival for patients with newly diagnosed HCC in a population of patients evaluated at a safety-net hospital. Development of screening programs in accordance with accepted guidelines with outreach to high-risk individuals represents an area of high value care for safety-net hospitals.

Unlocking success: Full year quality and utilization metrics of payer-provider OMH partnership.

41 Background: For more than a decade, CMS and commercial payers have sought to engage provider organizations in value-based cancer care payment models (VBPMs). Success of VBPMs requires payer/provider alignment on quality/utilization measures indicative of high-value care and the efficiency of data exchange between providers and payers. The following describes several key metrics from the first full year 2022 of the Tennessee Oncology (TO) and BlueCross BlueShield of Tennessee (BCBST) Oncology Medical Home (OMH) partnership. Methods: TO and BCBST implemented reporting methodologies for a combination of practice-reported quality and utilization measures and payer claims-based measures: Patient experience, Pathway adherence, Distress screening / interventions, Admissions/1000 patients, ED visits/1000 patients, Imaging utilization, and Observation stays. Bi-weekly meetings between practice and payer were necessary to review quality/utilization measure reporting, coordinate overall program administration, and monitor member attribution for care management and performance-based payments. Results: TO/BCBST co-developed a VBPM that included bi-directional reporting of practice-reported quality and utilization measures and payer claims-based measures. Technical challenges in data sharing and reporting occurred frequently and required regular troubleshooting. Questions regarding trends in observed data arose frequently for both TO and BCBST and required regular discussions between clinical/operational leaders of payer and practice (Table). Conclusions: These data suggest that payers and community oncology practices can co-develop value-based payment models that yield transparency in quality and utilization data reporting, and observed differences in performance and cost-efficiency among different practices in a market. Payers can gain increased transparency in quality and cost-efficiency of cancer care for their members. Practices can leverage care management payments and performance-based payments to support care delivery and quality/utilization data reporting improvements. Provider and payer capabilities to execute transparent QM/UM reporting is a major challenge in implementing OMH programs. 2022 OMH results. Measure % higher or lower than benchmarks Admissions /k -7.0 ED visit /k -8.4 Imaging utilization + 9.4 Observation stays -10.0 Patient experience NA Pathway adherence NA Distress screening / interventions NA Hospice reporting NA NA = not applicable, no benchmark data available/measured; /k = per 1000 patients; negative = lower than benchmarks; positive = higher than benchmarks.

Oncology care model cost data for breast, lung, and multiple myeloma: Influence of outpatient rehabilitation therapy services.

14 Background: High value cancer care is defined by access to coordinated, appropriate healthcare services that achieve optimal outcomes at a reasonable cost. Evidence supports outpatient cancer rehabilitation (physical, occupational or speech therapy) as a mechanism to improve outcomes such as health-related quality of life, suggesting that integration of these services is beneficial for cancer survivors. However, the impact of outpatient rehabilitation services on healthcare costs is unknown. We aimed to compare cost segments between those who attended community-based outpatient rehabilitation therapy services (Rehab) versus those who did not (Non-rehab). We hypothesized that healthcare costs would be lower for the Rehab group in the following cost segments: emergency department (ED), part D drugs, home health services, skilled nursing facility services (SNF), inpatient rehabilitation facilities (IRF), and hospice. Methods: This is a retrospective cohort study of Medicare beneficiaries who received chemotherapy at a large community oncology practice that participated in the oncology care model (OCM) program from 2018 to 2021. Two data sources were linked, OCM cost data and the rehabilitation medical record. This yielded sufficient sample sizes for analysis of breast, lung, or multiple myeloma (MM) cancer types. Rehab cases were then matched to Non-rehab cases 3:1 based on cancer type, stage, and sex. Cost variables included total cost of care (TCOC) and cost segments using OCM methodology. Mann-Whitney-Wilcoxon statistic (p<.05) was used for analysis. Results: Cases (N=3,033) primarily had early-stage cancer (0 to 2, 74.8%) and were 70.4±7.3 (Rehab) or 71.6±8.5 years old at diagnosis (Non-rehab). Most had breast cancer (81.2%), followed by lung cancer (11.7%) and MM (7.2%). TCOC was $32,387 and $26,257 for the Rehab and Non-rehab groups, respectively. Costs were significantly lower for the Rehab group in five of the six segments analyzed; IRF costs were lower, but not statistically significant (Table). Conclusions: To our knowledge, this is the first study to explore the influence of real-world, outpatient cancer rehabilitation therapy services on the cost of cancer care. Community-based therapy services were associated with significantly lower costs in ED, part D drugs, home health, SNF, and hospice segments. Future studies examining rehabilitation services as a relatively low-cost supportive care option to meet patient needs and enhance high-value care are warranted. Healthcare segment costs for rehab vs. non-rehab cases. Rehab Non-rehab Between-group Difference Mean, (SD) Mean (SD) p-value ED $85 (260) $104 (372) .019 Part D drugs $4,813 (18,221) $5,675 (18,797) <.001 Home health $433 (1,600) $705 (2,118) <.001 SNF $160 (1,988) $386 (3,943) .046 Hospice $75 (770) $198 (1,529) <.001 IRF $245 (2,275) $384 (3,277) .434

Inequities in Unexpected Cost-Sharing for Preventive Care in the United States

Unexpected out-of-pocket (OOP) costs for preventive care reduce future uptake. Because adherence to service guidelines differs by patient populations, understanding the role of patient demographics and social determinants of health (SDOH) in the incidence and size of unexpected cost-sharing is necessary to address these disparities. This study examined the associations between patient demographics and cost-sharing for common preventive services. This cross-sectional study used a national sample of insurance claims for recommended preventive services provided to privately insured adult patients between 2017 and 2020. The relationships between patient demographics and OOP costs were adjusted for service type, insurance type, geographic location, and time trends using regression analysis. Analyses were conducted in 2024. The sample included 1,736,063 unique preventive care encounters of 1,078,010 individuals. Among preventive encounters, 40.3% resulted in OOP costs. Lower-educated patients had 9.4% (OR=1.094; 95% CI=1.082, 1.106) higher odds of incurring OOP costs than patients with college degrees. Low-income patients (annual household income of $49,999 or less) had 10.7% (OR=0.893; 95% CI=0.880, 0.906) lower odds of incurring OOP costs than high-income patients. Conditional on incurring costs, lower educated patients paid $15.07 (95% CI= -$15.24, -$14.91) less than higher educated patients, and low-income patients paid $11.76 (95% CI=$11.58, $11.95) more than high-income patients. Significant differences across racial and ethnic groups were observed. The likelihood and size of OOP costs for preventive care varied considerably by patient demographics; this may contribute to inequitable access to high-value care.

Social Determinants of Health and Insurance Claim Denials for Preventive Care.

The Patient Protection and Affordable Care Act (ACA) eliminated out-of-pocket cost-sharing for recommended preventive care for most privately insured patients. However, patients seeking preventive care continue to face cost-sharing and administrative hurdles, including claim denials, which may exacerbate inequitable access to care. To determine whether patient demographics and social determinants of health are associated with denials of insurance claims for preventive care. This cohort study of patients insured through their employers or the ACA Marketplaces used claims and remittance data from Symphony Health Solutions' Integrated DataVerse from 2017 to 2020; analysis was completed from January to July 2024. Seeking preventive care. The primary outcome was the frequency of insurer denials for preventive services across 5 categories: specific benefit denials, billing errors, coverage lapses, inadequate coverage, and other. Subgroup analysis was performed across patient household income, education, and race and ethnicity. Secondary outcomes included charges for denied claims, approximating patients' remaining financial responsibility for care. A total of 1 535 181 patients received 4 218 512 preventive services in 2 507 943 unique visits (mean [SD] age at visits, 54.02 [13.19] years; 1 804 637 visits for female patients [71.96%]); 585 299 patients (23.30%) had an annual household income $100 000 or higher, and 824 540 patients had some college education (32.88%). A total of 20 658 individuals (0.82%) were Asian, 139 950 (5.58%) were Hispanic, 219 646 (8.76%) were non-Hispanic Black, 1 372 223 (54.72%) were non-Hispanic White, and 25 412 (1.0%1) were other races and ethnicities not included in the other 4 groups. Of preventive claims, 1.34% (95% CI, 1.32%-1.36%) were denied, consisting mainly of specific benefit denials (0.67%; 95% CI, 0.66%-0.68%) and billing errors (0.51%; 95% CI, 0.50%-0.52%). The lowest-income patients had 43.0% higher odds of experiencing a denial than the highest-income patients (odds ratio, 1.43; 95% CI, 1.37-1.50; P < .001). The least educated enrollees had a denial rate of 1.79% (95% CI, 1.76%-1.82%) compared with 1.14% (95% CI, 1.12%-1.16%) for enrollees with college degrees. Denial rates for Asian (2.72%; 95% CI, 2.55%-2.90%), Hispanic (2.44%; 95% CI, 2.38%-2.50%), and non-Hispanic Black (2.04%; 95% CI, 1.99%-2.08%) patients were significantly higher than those for non-Hispanic White patients (1.13%; 95% CI, 1.12%-1.15%). In this cohort study of 1 535 181 patients seeking preventive care, denials of insurance claims for preventive care were disproportionately more common among at-risk patient populations. This administrative burden potentially perpetuates inequitable access to high-value health care.

Opportunity and Opportunism in Artificial-Intelligence-Powered Data Extraction: A Value-Centered Approach.

Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions. This charge is rapidly evolving due to forces such as artificial intelligence [AI], big data [opportunistic imaging, imaging prognostication], and advanced diagnostic technologies. A new "modernistic" paradigm is emerging whereby radiologists, in conjunction with computer algorithms, will be tasked with extracting as much information from imaging data as possible, often without a specific clinical question being posed and independent of any stated clinical need. In addition, AI algorithms are increasingly able to predict long-term outcomes using data from seemingly normal examinations, enabling AI-assisted prognostication. As these algorithms become a standard component of radiology practice, the sheer amount of information they demand will increase the need for streamlined workflows, communication, and data management techniques. In addition, the provision of such information raises reimbursement, liability, and access issues. Guidelines will be needed to ensure all patients have access to the benefits of this new technology and guarantee mined data do not inadvertently create harm. In this article, we discuss challenges and opportunities relevant to radiologists in this changing landscape, with an emphasis on ensuring that radiologists provide high-value care.

Evaluating the atherosclerosis cardiovascular disease risk score in patients with brain metastases: Associations with overall survival and high-value care outcomes

ObjectiveBrain metastases (BM) constitute the most common intracranial tumor in adults. Prior literature indicates the 10-year atherosclerotic cardiovascular disease (ASCVD) risk score is associated with increased risk of cancer, potentially attributable to shared risk factors. Understanding the role of ASCVD risk scores in BM may help optimize their care and inform clinical decision-making. Our aim was to explore associations between ASCVD risk score in BM patients and their overall survival, hospital charges, and non-routine discharge disposition. MethodsElectronic medical records were reviewed to collect clinical data for BM patients undergoing surgery at a single institution (2017–2021). Regression analyses were performed accordingly and maximally selected rank statistics were employed to identify an optimal cutoff for ASCVD risk scores. The random survival forest (RSF) machine learning technique identified the most important variable associated with survival outcomes in BM patients. ResultsA total of 139 patients were included with average age 62.93±9.29 years, 48.2 % male, 25.2 % with high hospital charges, and 23.7 % experiencing non-routine discharge. Among these patients, 32.3 % had prior history of an ASCVD event, while 67.7 % did not. Overall, this cohort had an average 10-year ASCVD risk score of 12.51±12.98, indicating intermediate risk of ASCVD among all BM patients. On multivariate logistic regression, prior history of ASCVD was associated with higher odds of high hospital charges (OR=3.670, p=0.018), and higher ASCVD risk scores were associated with greater odds of non-routine discharge (OR=1.059, p=0.012). On the multivariate Cox regression model, higher ASCVD risk scores correlated with worse overall survival (HR=1.031, p=0.014). A threshold of 25.1 was identified for high-risk ASCVD scores. Patients with ASCVD scores >25.1 exhibited reduced overall survival in Kaplan-Meier analysis (p=0.015) and multivariate Cox regression (HR: 2.811, p=0.016). Notably, ASCVD risk scores were found to be the most important variable in predicting worse survival outcomes in BM patients compared to other established frailty indices. ConclusionThis study indicates higher ASCVD risk scores in BM patients are associated with worse overall survival. Integrating ASCVD assessment into clinical workflow may facilitate more informed risk-based decision-making.

Alternative payment models in Dutch hospital care: what works, how, why and under what circumstances? Protocol for a realist evaluation study

IntroductionThe predominant provider payment models in healthcare, particularly fee-for-service, hinder the delivery of high-value care and can encourage healthcare providers to prioritise the volume of care over the value of...

A comparative analysis of the Trauma and Injury Severity Score and the Injury Severity Score in predicting high-value care outcomes in children with traumatic brain injury.

Predicting high-value care outcomes is crucial in managing pediatric traumatic brain injuries (TBIs), where timely and accurate prognostication can significantly influence treatment decisions and resource allocation. This study aimed to enhance understanding of how well scoring systems such as the Trauma and Injury Severity Score (TRISS) can forecast high-value care outcomes. Furthermore, the authors compared the predictive power of TRISS with the routinely used Injury Severity Score (ISS). The authors performed a retrospective review of their institutional database from June 2016 to June 2023 to identify cases of TBI based on a modified Centers for Disease Control and Prevention framework. Prolonged length of stay (LOS) was defined as a hospital stay falling into the upper quartile of the overall cohort. Discharge to an inpatient rehabilitation facility, acute care hospital, or foster care or death was defined as a nonroutine discharge disposition. Emergency department (ED) transfer to the intensive care unit (ICU) or operating room (OR) was defined as a proxy for severity of injuries. Multivariate logistic regression models were used to explore the association between ISS, TRISS, and high-value care outcomes. The DeLong test was used to assess the differences between the areas under the receiver operating characteristic curve (AUROCs). This study included 2705 patients with a mean age ± SD of 7.28 ± 5.46 years (63% male). In the overall cohort, 28% experienced prolonged LOS, 7% had a nonroutine discharge disposition from the hospital, and 23% were transferred to the ICU/OR from the ED. In multivariate regression models, both TRISS and ISS were correlated with higher odds of prolonged LOS, nonroutine discharge disposition, and transfer to the ICU/OR from the ED (all p < 0.001). TRISS had a significantly greater AUROC than ISS for nonroutine discharge disposition (0.883 vs 0.849, p < 0.001) and transfer to the ICU/OR (0.898 vs 0.887, p = 0.045), but this result was not significant for prolonged LOS (0.873 vs 0.880, p = 0.140). TRISS and ISS are effective tools for predicting high-value care outcomes in pediatric TBI. Utilizing these resources can assist healthcare providers in making informed, risk-adjusted predictions.

Coverage of physical therapy assessments in the Observational Medical Outcomes Partnership Model common data model.

High-value care aims to enhance meaningful patient outcomes while reducing costs and is accelerated by curating data across healthcare systems through common data models (CDMs), such as Observational Medical Outcomes Partnership Model (OMOP). Meaningful patient outcomes, such as physical function, must be included in these CDMs. However, the extent that physical therapy assessments are covered in the OMOP CDM is unclear. Examine the extent that physical therapy assessments used in neurologic and orthopaedic conditions are in the OMOP CDM. After identifying assessments, two reviewer teams independently mapped the neurologic and orthopaedic assessments into the OMOP CDM. We quantified agreement within the reviewer team by the number of assessments mapped by both reviewers, one reviewer but not the other, or neither reviewer. The reviewer teams then reconciled disagreements, after which we examined agreement and the average number of concept ID numbers per assessment. Of the 81 neurologic assessments, 48.1% (39/81) were initially mapped by both reviewers, 9.9% (8/81) were mapped by one reviewer but not the other, and 42% (34/81) were unmapped. After reconciliation, 46.9% (38/81) were mapped by both reviewers and 53.1% (43/81) were unmapped. Of the 79 orthopaedic assessments, 46.8% (37/79) were initially mapped by both reviewers, 12.7% (10/79) were mapped by one reviewer but not the other, and 48.1% (38/79) were unmapped. After reconciliation, 48.1% (38/79) were mapped by both reviewers and 51.9% (41/79) were unmapped. Most assessments that were mapped had more than one concept ID number (2.2±1.3 and 4.3±4.4 concept IDs per neurologic and orthopaedic assessment, respectively). The OMOP CDM includes some assessments recommended for use in neurologic and orthopaedic conditions, but many have multiple concept IDs. Including more functional assessments in the OMOP CDM and creating guidelines for mapping would improve our ability to include functional data in large datasets.

Empowering Medical Students to Practice High-Value Care

Over the last decade, initiatives like the Choosing Wisely campaign have promoted the practice of evidence-based, cost-conscious care. However, education surrounding value in medicine has been largely restricted to graduate-level medical education or post-clerkship undergraduate medical education. Here, we present a mixed-methods study evaluating pre-clerkship medical student engagement with and response to new value-based curricular initiatives to assess whether high-value care (HVC) can be introduced successfully earlier in training. Initiatives were introduced into the pre-clerkship clinical curriculum without major alterations to the established curricular structure. These comprised an annual event devoted to self-reflecting on HVC observed in prior and current clinical experiences and subsequent small-group facilitated discussion. Engagement with and response to these initiatives were analyzed for two whole-class cohorts using an abductive, progressive focusing approach complementing quantitative survey data. Baseline familiarity with HVC and post-event response to the annual event was higher and more positive, respectively, among responders from the Class of 2025 compared with those from the Class of 2024. Analysis of reflection essays revealed the emergence of five primary themes differentiating the two class years: (1) understanding HVC, (2) addressing barriers to HVC, (3) medical waste and underserved communities, (4) patient–physician relationship and value, and (5) self-reflection. Evaluation of thematic patterns in light of survey response data suggests that early clinical exposure combined with intentional self-reflection could promote engagement with HVC topics in a way that shapes students’ foundational understanding of the practice of medicine.

Top Three Healthcare Trends in Orthopaedics Affecting Musculoskeletal Care in the Elderly.

Several trends toward patient-centered multi-care models employing translational research strategies are currently emerging in orthopaedics. These align seamlessly with epigenetics discussions in pain, a clinical approach to pain management that prioritizes tailoring healthcare to individual needs, preferences, and circumstances. Recognizing the unique genetic and epigenetic factors influencing pain perception, healthcare providers can integrate personalized insights into their patient-centered approach, offering more targeted and effective pain management strategies tailored to each individual's experience. Custom 3D-printing technologies may also become increasingly relevant to more effectively and reliably treat painful degenerative structural abnormalities. They are expected to go hand-in-hand with the precision medicine redefinition of musculoskeletal care. More effective analysis of surgeons' clinical decision-making and patients' perception of high-value orthopaedic care is needed. Shared Decision Making (SDM) is critical to identifying the best solution for each patient and improving stakeholders' understanding of factors influencing the diverse prioritizing values of surgical or non-surgical treatments by payers, systems, and other providers. Identifying high-value orthopaedic surgeries via effective SDM in orthopedic surgery requires more than just presenting patients with information. The Rasch analysis of patient expectations can provide this nuanced approach that involves understanding patient values, addressing misconceptions, and aligning surgical recommendations with patient-specific goals. Optimizing orthopaedic treatment within the patient-centered framework can drive innovation in reimbursement policies that support the field more broadly. Research on separating high-value from low-value orthopaedic procedures may likely impact healthcare decision- makers' resource allocation.

Hospital frailty risk score predicts high-value care outcomes following brain metastasis resection

ObjectiveBrain metastases (BM) are the most common adult intracranial tumors, representing a significant source of morbidity in patients with systemic malignancy. Frailty indices, including 11- and 5-factor modified frailty indices (mFI-11 and mFI-5), American Society of Anesthesiologists (ASA) physical status classification, and Charlson Comorbidity Index (CCI), have recently demonstrated an important role in predicting high-value care outcomes in neurosurgery. This study aims to investigate the efficacy of the newly developed Hospital Frailty Risk Score (HFRS) on postoperative outcomes in BM patients. MethodsAdult patients with BM treated surgically at a single institution were identified (2017–2019). HFRS was calculated using ICD-10 codes, and patients were subsequently separated into low (<5), intermediate (5−15), and high (>15) HFRS cohorts. Multivariate logistic regressions were utilized to identify associations between HFRS and complications, length of stay (LOS), hospital charges, and discharge disposition. Model discrimination was assessed using receiver operating characteristic (ROC) curves. ResultsA total of 356 patients (mean age: 61.81±11.63 years; 50.6 % female) were included. The mean±SD for HFRS, mFI-11, mFI-5, ASA, and CCI were 6.46±5.73, 1.31±1.24, 0.95±0.86, 2.94±0.48, and 8.69±2.07, respectively. On multivariate analysis, higher HFRS was significantly associated with greater complication rate (OR=1.10, p<0.001), extended LOS (OR=1.13, p<0.001), high hospital charges (OR=1.14, p<0.001), and nonroutine discharge disposition (OR=1.12, p<0.001), and comparing the ROC curves of mFI-11, mFI-5, ASA,and CCI, the predictive accuracy of HFRS was the most superior for all four outcomes assessed. ConclusionThe predictive ability of HFRS on BM resection outcomes may be superior than other frailty indices, offering a new avenue for routine preoperative frailty assessment and for managing postoperative expectations.

How Medical Students Benefit from Participating in a Longitudinal Resource Stewardship Medical Education Program (STARS): An International Descriptive Evaluation.

STARS (Students and Trainees Advocating for Resource Stewardship) is a medical student leadership program that promotes integration of resource stewardship (RS) into medical education in at least seven countries. Little is known about how participation affects student leaders. To understand how partaking in STARS impacted participants' knowledge, skills, and influenced career plans, and aspirations. We conducted qualitative semi-structured interviews with STARS participants (n = 27) from seven countries. STARS was designed to facilitate grassroots efforts that embed RS principles into medical education. STARS programs globally share common features: participation from several medical schools, centralized organizing hubs and leadership summits, and support from faculty mentors. Students take lessons learnt from centralized programming to implement changes that advance RS initiatives at their schools. Students finished STARS with better RS knowledge, enhanced change management skills (leadership, advocacy, collaboration), and a commitment to incorporate RS into future practice. Nearly all respondents hoped to pursue leadership activities in medicine, but most were unclear if they would focus efforts to advance RS. STARS participants gained knowledge as it relates to RS, change management skills, and catalyzed a commitment to incorporate high-value care into future practice. Medical education initiatives should be leveraged as a key strategic approach to build RS capacity.