Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity.

BACKGROUND: Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice - essential heterogeneity. METHODS: We simulated eleven populations with identical treatment effect distributions based on patient factors. The populations varied in the extent that treatment effect heterogeneity influenced treatment choice. We used the generalized random forest application (CFA-GRF) to estimate patient-specific treatment effects for each population. Average differences between true and estimated effects for patient subsets were evaluated. RESULTS: CFA-GRF performed well across the population when treatment effect heterogeneity did not influence treatment choice. Under essential heterogeneity, however, CFA-GRF yielded treatment effect estimates that reflected true treatment effects only for treated patients and were on average greater than true treatment effects for untreated patients. CONCLUSIONS: Patient-specific estimates produced by CFAs are sensitive to why patients in real-world practice make different treatment choices. Researchers using CFAs should develop conceptual frameworks of treatment choice prior to estimation to guide estimate interpretation ex post.

Association between household opioid prescriptions and risk for overdose among family members not prescribed opioids.

BACKGROUND: Prescription opioids have contributed to the rise in opioid-related overdoses and deaths. The presence of opioids within households may increase the risk of overdose among family members who were not prescribed an opioid themselves. Larger quantities of opioids may further increase risk. OBJECTIVES: To determine the risk of opioid overdose among individuals who were not prescribed an opioid but were exposed to opioids prescribed to other family members in the household, and evaluate the risk in relation to the total morphine milligram equivalents (MMEs) present in the household. METHODS: We conducted a cohort study using a large database of commercial insurance claims from 2001 to 2021. For inclusion in the cohort, we identified individuals not prescribed an opioid in the prior 90 days from households with two or more family members, and determined the total MMEs prescribed to other family members. Individuals were stratified into monthly enrollment strata defined by household opioid exposure and other confounders. A generalized linear model was used to estimate incidence rate ratios (IRRs) for overdose. RESULTS: Overall, the incidence of overdose among enrollees in households where a family member was prescribed an opioid was 1.73 (95% confidence interval [CI]: 1.67-1.78) times greater than households without opioid prescriptions. The risk of overdose increased continuously with the level of potential MMEs in the household from an IRR of 1.23 (95% CI: 1.16-1.32) for 1-100 MMEs to 4.67 (95% CI: 4.18-5.22) for >12,000 MMEs. The risk of overdose associated with household opioid exposure was greatest for ages 1-2 years (IRR: 3.46 [95% CI: 2.98-4.01]) and 3-5 years (IRR: 3.31 [95% CI: 2.75-3.99]). CONCLUSIONS: The presence of opioids in a household significantly increases the risk of overdose among other family members who were not prescribed an opioid. Higher levels of MMEs, either in terms of opioid strength or quantity, were associated with increased levels of risk. Risk estimates may reflect accidental poisonings among younger family members.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

IMPORTANCE: This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. OBJECTIVES: The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. METHODS: A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. RESULTS: To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. CONCLUSION: The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

Patient preferences and willingness-to-pay for community pharmacy-led Medicare Part D consultation services: A discrete choice experiment.

INTRODUCTION: Community pharmacies currently offer Medicare Part D consultation services, often at no-cost. Despite facilitating plan-switching behavior, identifying potential cost-savings, and increasing medication adherence, patient uptake of these services remains low. OBJECTIVES: To investigate patient preferences for specific service-offering attributes and marginal willingness-to-pay (mWTP) for an enhanced community pharmacy Medicare Part D consultation service. METHODS: A discrete choice experiment (DCE) guided by the SERVQUAL framework was developed and administered using a national online survey panel. Study participants were English-speaking adults (≥65 years) residing in the United States enrolled in a Medicare Part D or Medicare Advantage plan and had filled a prescription at a community pharmacy within the last 12 months. An orthogonal design resulted in 120 paired-choice tasks distributed equally across 10 survey blocks. Data were analyzed using mixed logit and latent class models. RESULTS: In total, 540 responses were collected, with the average age of respondents being 71 years. The majority of respondents were females (60%) and reported taking four or more prescription medication (51%). Service attribute levels with the highest utility were: 15-min intervention duration (0.392), discussion of services + a follow-up phone call (0.069), in-person at the pharmacy (0.328), provided by a pharmacist the patient knew (0.578), and no-cost (3.382). The attribute with the largest mWTP value was a service provided by a pharmacist the participant knew ($8.42). Latent class analysis revealed that patient preferences for service attributes significantly differed by gender and difficulty affording prescription medications. CONCLUSIONS: Quantifying patient preference using discrete choice methodology provides pharmacies with information needed to design service offerings that balance patient preference and sustainability. Pharmacies may consider providing interventions at no-cost to subsets of patients placing high importance on a service cost attribute. Further, patient preference for 15-min interventions may inform Medicare Part D service delivery and facilitate service sustainability.

Chorioamnionitis-exposure alters serum cytokine trends in premature neonates.

OBJECTIVES: Determine if chronologic age and/or chorioamnionitis exposure alter normal serum cytokine and chemokine levels in uninfected preterm neonates during their initial NICU stay. STUDY DESIGN: A 7-plex immunoassay measured levels of serum IL-1ß, IL-6, IL-8, IL-10, TNF-α, CCL2, and CCL3 longitudinally from chorioamnionitis-exposed and unexposed preterm neonates under 33 weeks' gestation. RESULTS: Chorioamnionitis-exposed and unexposed preterm neonates demonstrated differences in the trends of IL-1ß, IL-6, IL-8, IL-10, TNF-α, and CCL2 over the first month of life. The unexposed neonates demonstrated elevated levels of these inflammatory markers in the first two weeks of life with a decrease by the third week of life, while the chorioamnionitis-exposed neonates demonstrated differences over time without a predictable pattern. Chorioamnionitis-exposed and unexposed neonates demonstrated altered IL-10 and TNF-α trajectories over the first twelve weeks of life. CONCLUSION: Chorioamnionitis induces a state of immune dysregulation in preterm neonates that persists beyond the immediate neonatal period.

Generating Practice-Based Evidence in the Use of Guideline-Recommended Combination Therapy for Secondary Prevention of Acute Myocardial Infarction.

Background: Clinical guidelines recommend beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin-receptor blockers, and statins for the secondary prevention of acute myocardial infarction (AMI). It is not clear whether variation in real-world practice reflects poor quality-of-care or a balance of outcome tradeoffs across patients. Methods: The study cohort included Medicare fee-for-service beneficiaries hospitalized 2007-2008 for AMI. Treatment within 30-days post-discharge was grouped into one of eight possible combinations for the three drug classes. Outcomes included one-year overall survival, one-year cardiovascular-event-free survival, and 90-day adverse events. Treatment effects were estimated using an Instrumental Variables (IV) approach with instruments based on measures of local-area practice style. Pre-specified data elements were abstracted from hospital medical records for a stratified, random sample to create "unmeasured confounders" (per claims data) and assess model assumptions. Results: Each drug combination was observed in the final sample (N = 124,695), with 35.7% having all three, and 13.5% having none. Higher rates of guideline-recommended treatment were associated with both better survival and more adverse events. Unmeasured confounders were not associated with instrumental variable values. Conclusions: The results from this study suggest that providers consider both treatment benefits and harms in patients with AMIs. The investigation of estimator assumptions support the validity of the estimates.

Assessing the ability of an instrumental variable causal forest algorithm to personalize treatment evidence using observational data: the case of early surgery for shoulder fracture.

BACKGROUND: Comparative effectiveness research (CER) using observational databases has been suggested to obtain personalized evidence of treatment effectiveness. Inferential difficulties remain using traditional CER approaches especially related to designating patients to reference classes a priori. A novel Instrumental Variable Causal Forest Algorithm (IV-CFA) has the potential to provide personalized evidence using observational data without designating reference classes a priori, but the consistency of the evidence when varying key algorithm parameters remains unclear. We investigated the consistency of IV-CFA estimates through application to a database of Medicare beneficiaries with proximal humerus fractures (PHFs) that previously revealed heterogeneity in the effects of early surgery using instrumental variable estimators. METHODS: IV-CFA was used to estimate patient-specific early surgery effects on both beneficial and detrimental outcomes using different combinations of algorithm parameters and estimate variation was assessed for a population of 72,751 fee-for-service Medicare beneficiaries with PHFs in 2011. Classification and regression trees (CART) were applied to these estimates to create ex-post reference classes and the consistency of these classes were assessed. Two-stage least squares (2SLS) estimators were applied to representative ex-post reference classes to scrutinize the estimates relative to known 2SLS properties. RESULTS: IV-CFA uncovered substantial early surgery effect heterogeneity across PHF patients, but estimates for individual patients varied with algorithm parameters. CART applied to these estimates revealed ex-post reference classes consistent across algorithm parameters. 2SLS estimates showed that ex-post reference classes containing older, frailer patients with more comorbidities, and lower utilizers of healthcare were less likely to benefit and more likely to have detriments from higher rates of early surgery. CONCLUSIONS: IV-CFA provides an illuminating method to uncover ex-post reference classes of patients based on treatment effects using observational data with a strong instrumental variable. Interpretation of treatment effect estimates within each ex-post reference class using traditional CER methods remains conditional on the extent of measured information in the data.

What are the health consequences associated with differences in medical malpractice liability laws? An instrumental variable analysis of surgery effects on health outcomes for proximal humeral facture across states with different liability rules.

BACKGROUND: States enacted tort reforms to lower medical malpractice liability, which are associated with higher surgery rates among Medicare patients with shoulder conditions. Surgery in this group often entails tradeoffs between improved health and increased risk of morbidity and mortality. We assessed whether differences in surgery rates across states with different liability rules are associated with surgical outcomes among Medicare patients with proximal humeral fracture. METHODS: We obtained data for 67,966 Medicare beneficiaries with a diagnosis of proximal humeral fracture in 2011. Outcome measures included adverse events, mortality, and treatment success rates, defined as surviving the treatment period with < $300 in shoulder-related expenditures. We used existing state-level tort reform rules as instruments for surgical treatment and separately as predictors to answer our research question, both for the full cohort and for stratified subgroups based on age and general health status measured by Charlson Comorbidity Index and Function-Related Indicators. RESULTS: We found a 0.32 percentage-point increase (p < 0.05) in treatment success and a 0.21 percentage-point increase (p < 0.01) in mortality for every 1 percentage-point increase in surgery rates among patients in states with lower liability risk. In subgroup analyses, mortality increased among more vulnerable patients, by 0.29 percentage-point (p < 0.01) for patients with Charlson Comorbidity Index > = 2 and by 0.45 percentage-point (p < 0.01) among those patients with Function-Related Indicator scores > = 2. On the other hand, treatment success increased in patients with lower Function-Related Index scores (< 2) by 0.54 percentage-point (p < 0.001). However, younger Medicare patients (< 80 years) experienced an increase in both mortality (0.28 percentage-point, p < 0.01) and treatment success (0.89 percentage-point, p < 0.01). The reduced-form estimates are consistent with our instrumental variable results. CONCLUSIONS: A tradeoff exists between increased mortality risk and increased treatment success across states with different malpractice risk levels. These results varied across patient subgroups, with more vulnerable patients generally bearing the brunt of the increased mortality and less vulnerable patients enjoying increased success rates. These findings highlight the important risk-reward scenario associated with different liability environments, especially among patients with different health status.

Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection.

Accurate detection and risk stratification of latent tuberculosis infection (LTBI) remains a major clinical and public health problem. We hypothesize that multiparameter strategies that probe immune responses to Mycobacterium tuberculosis can provide new diagnostic insights into not only the status of LTBI infection, but also the risk of reactivation. After the initial proof-of-concept study, we developed a 13-plex immunoassay panel to profile cytokine release from peripheral blood mononuclear cells stimulated separately with Mtb-relevant and non-specific antigens to identify putative biomarker signatures. We sequentially enrolled 65 subjects with various risk of TB exposure, including 32 subjects with diagnosis of LTBI. Random Forest feature selection and statistical data reduction methods were applied to determine cytokine levels across different normalized stimulation conditions. Receiver Operator Characteristic (ROC) analysis for full and reduced feature sets revealed differences in biomarkers signatures for LTBI status and reactivation risk designations. The reduced set for increased risk included IP-10, IL-2, IFN-γ, TNF-α, IL-15, IL-17, CCL3, and CCL8 under varying normalized stimulation conditions. ROC curves determined predictive accuracies of > 80% for both LTBI diagnosis and increased risk designations. Our study findings suggest that a multiparameter diagnostic approach to detect normalized cytokine biomarker signatures might improve risk stratification in LTBI.

State medical malpractice laws and utilization of surgical treatment for rotator cuff tear and proximal humerus fracture: an observational cohort study.

BACKGROUND: How much does the medical malpractice system affect treatment decisions in orthopaedics? To further this inquiry, we sought to assess whether malpractice liability is associated with differences in surgery rates among elderly orthopaedic patients. METHODS: Medicare data were obtained for patients with a rotator cuff tear or proximal humerus fracture in 2011. Multivariate regressions were used to assess whether the probability of surgery is associated with various state-level rules that increase or decrease malpractice liability risks. RESULTS: Study results indicate that lower liability is associated with higher surgery rates. States with joint and several liability, caps on punitive damages, and punitive evidence rule had surgery rates that were respectively 5%-, 1%-, and 1%-point higher for rotator cuff tears, and 2%-, 2%- and 1%-point higher for proximal humerus fractures. Conversely, greater liability is associated with lower surgery rates, respectively 6%- and 9%-points lower for rotator cuff patients in states with comparative negligence and pure comparative negligence. CONCLUSIONS: Medical malpractice liability is associated with orthopaedic treatment choices. Future research should investigate whether treatment differences result in health outcome changes to assess the costs and benefits of the medical liability system.

Coherent silicon photonic interferometric biosensor with an inexpensive laser source for sensitive label-free immunoassays.

Over the past two decades, integrated photonic sensors have been of major interest to the optical biosensor community due to their capability to detect low concentrations of molecules with label-free operation. Among these, interferometric sensors can be read-out with simple, fixed-wavelength laser sources and offer excellent detection limits but can suffer from sensitivity fading when not tuned to their quadrature point. Recently, coherently detected sensors were demonstrated as an attractive alternative to overcome this limitation. Here we show, for the first time, to the best of our knowledge, that this coherent scheme provides sub-nanogram per milliliter limits of detection in C-reactive protein immunoassays and that quasi-balanced optical arm lengths enable operation with inexpensive Fabry-Perot-type lasers sources at telecom wavelengths.

Increased opioid use following rotator cuff repair associated with prior opioid use and surgeon prescription patterns.

BACKGROUND: Prescription opioids are standard of care for postoperative pain management after musculoskeletal surgery, but there is no guideline or consensus on best practices. Variability in the intensity of opioids prescribed for postoperative recovery has been documented, but it is unclear whether this variability is clinically motivated or associated with provider practice patterns, or how this variation is associated with patient outcomes. This study described variation in the intensity of opioids prescribed for patients undergoing rotator cuff repair (RCR) and examined associations with provider prescribing patterns and patients' long-term opioid use outcomes. METHODS: Medicare data from 2010 to 2012 were used to identify 16,043 RCRs for patients with new shoulder complaints in 2011. Two measures of perioperative opioid use were created: (1) any opioid fill occurring 3 days before to 7 days after RCR and (2) total morphine milligram equivalents (MMEs) of all opioid fills during that period. Patient outcomes for persistent opioid use after RCR included (1) any opioid fill from 90 to 180 days after RCR and (2) the lack of any 30-day gap in opioid availability during that period. Generalized linear regression models were used to estimate associations between provider characteristics and opioid use for RCR, and between opioid use and outcomes. All models adjusted for patient clinical and demographic characteristics. Separate analyses were done for patients with and without opioid use in the 180 days before RCR. RESULTS: In this sample, 54% of patients undergoing RCR were opioid naive at the time of RCR. Relative to prior users, a greater proportion of opioid naive users had any opioid fill (85.7% vs. 75.4%), but prior users received more MMEs than naive users (565 vs. 451 MMEs). Providers' opioid prescribing for other patients was associated with the intensity of perioperative opioids received for RCR. Total MMEs received for RCR were associated with higher odds of persistent opioid use 90-180 days after RCR. CONCLUSIONS: The intensity of opioids received by patients for postoperative pain appears to be partially determined by the prescribing habits of their providers. Greater intensity of opioids received is, in turn, associated with greater odds of patterns of chronic opioid use after surgery. More comprehensive, patient-centered guidance on opioid prescribing is needed to help surgeons provide optimal postoperative pain management plans, balancing needs for short-term symptom relief and risks for long-term outcomes.

Impact of Silanization Parameters and Antibody Immobilization Strategy on Binding Capacity of Photonic Ring Resonators.

Ring resonator-based biosensors have found widespread application as the transducing principle in "lab-on-a-chip" platforms due to their sensitivity, small size and support for multiplexed sensing. Their sensitivity is, however, not inherently selective towards biomarkers, and surface functionalization of the sensors is key in transforming the sensitivity to be specific for a particular biomarker. There is currently no consensus on process parameters for optimized functionalization of these sensors. Moreover, the procedures are typically optimized on flat silicon oxide substrates as test systems prior to applying the procedure to the actual sensor. Here we present what is, to our knowledge, the first comparison of optimization of silanization on flat silicon oxide substrates to results of protein capture on sensors where all parameters of two conjugation protocols are tested on both platforms. The conjugation protocols differed in the chosen silanization solvents and protein immobilization strategy. The data show that selection of acetic acid as the solvent in the silanization step generally yields a higher protein binding capacity for C-reactive protein (CRP) onto anti-CRP functionalized ring resonator sensors than using ethanol as the solvent. Furthermore, using the BS3 linker resulted in more consistent protein binding capacity across the silanization parameters tested. Overall, the data indicate that selection of parameters in the silanization and immobilization protocols harbor potential for improved biosensor binding capacity and should therefore be included as an essential part of the biosensor development process.

Risk Adjustment of the Modified Low Back Pain Disability Questionnaire and Neck Disability Index to Benchmark Physical Therapist Performance: Analysis From an Outcomes Registry.

BACKGROUND: Patient-reported outcomes (PROs) have been touted as the ultimate assessment of quality medical care and have been proposed as performance measures after appropriate risk adjustment. Although spine conditions represent the most common orthopedic disorders, the most used PROs for disabilities related to the back and neck-the Modified Low Back Pain Disability Questionnaire (MDQ) and the Neck Disability Index (NDI)-have not been evaluated as performance measures. OBJECTIVE: The objective of this study was to benchmark physical therapists' performance in the management of spine conditions not involving surgery through the use of risk-adjusted MDQ and NDI outcomes. DESIGN: This was a retrospective observational study. METHODS: Data were accessed for patients seeking physical therapy with no history of related surgery for back or neck pain (315,274 treatment episodes) between January 2015 and June 2018. Patients with complete data, including initial and matched final MDQ or NDI, were considered for analysis (182,276 patients; 2799 physical therapists). Linear models controlling for baseline PRO and patient characteristics predicted PRO change for each patient. An aggregated performance ratio of actual PRO change to predicted PRO change was calculated for each physical therapist, and then empirical bootstrapping was used to develop the median performance ratio and its confidence intervals. Physical therapists who met a 40-patient threshold for either cohort (MDQ or NDI) were classified as "outperforming," "meeting expectations," or "underperforming" relative to predicted values using these 95% confidence intervals. RESULTS: Performance ratios indicated that 10% and 11% of physical therapists outperformed, 79% and 78% met expectations, and 11% and 11% underperformed relative to the risk-adjusted predicted change in the MDQ (1240 therapists; 97,908 patients) and NDI (461 therapists; 26,123 patients), respectively. To demonstrate the clinical importance of risk adjustment, clinical performance was evaluated in the seemingly homogeneous subset of 208 physical therapists within 0.5 SD of the median baseline MDQ and the median actual change in the MDQ. Following risk adjustment, 2 physical therapists were classified in each of the outperforming and underperforming cohorts. LIMITATIONS: The secondarily obtained observational data used were not collected for research purposes. Additionally, the analyses were limited by missing baseline information and follow-up PROs. CONCLUSIONS: The risk-adjusted performance ratios for the MDQ and NDI resulted in disparate conclusions regarding the quality of care compared with the raw, unadjusted change scores. According to the baseline and unadjusted change in the MDQ, even physical therapists in the most homogeneous sample were differentiated following appropriate risk adjustment. Clinically important improvements in actual PROs were observed in the outperforming but not in the underperforming physical therapists. Clinically meaningful differences in the performance ratio are unknown and are a limitation to clinical application and an opportunity for future research.

Impact of Medicaid coverage expansion under the Affordable Care Act on mammography and pap tests utilization among low-income women.

INTRODUCTION: The Affordable Care Act (ACA) expanded the coverage of Medicaid to include entire population with income below 138% of federal poverty line. It remains unclear whether this policy change has improved access to and utilization of health care, particularly use of mammography and Pap tests among poor women. METHODS: We used a difference-in-difference (DID) design to estimate the impact of Medicaid expansion on mammography and Pap tests utilization among low-income women. Expansion states are the treatment group and non-expansion states are the control group. The years 2012-13 are the pre-expansion period and 2015-16 are the post-expansion period for the purpose of estimating the DID parameters. RESULTS: The difference-in-difference estimate show that likelihood of utilizing mammograms did not change significantly among low-income women after the implementation of Medicaid expansion (DID coefficient -0.0476 with t-statistics at -1.26), Pap test decreased (coefficient -0.0615, t-statistics -2.76), and Medicaid enrollment has increased significantly among low-income women living in expansion states (coefficient 0.0889 with t-value of 3.68). CONCLUSION: Expansion of Medicaid was associated with increased Medicaid enrollment but did not yield near-term improvement in use of mammography and Pap tests among low-income women. Factors beyond health insurance coverage may be important in determining the likelihood of obtaining these screenings. Policy makers should try to identify other barriers to cancer screenings among low-income women in the USA.

Impact of removing cost sharing under the affordable care act (ACA) on mammography and pap test use.

BACKGROUND: The Affordable Care Act (ACA) required private insurers and Medicare to cover recommended preventive services without any cost sharing to improve utilization of these services. This study is an attempt to identify the impact of removing cost sharing on mammography and pap test utilization rates. METHODS: Counterfactual analysis was used to predict what would have been the screening rates in post-ACA if ACA was not there. This was done by estimating a model that examines determinants of dependent variable for the pre-ACA year (pre-ACA year is 2009). The estimated model was then used to predict the dependent variable for the post-ACA year using individual characteristics and other relevant variables unlikely to be affected by ACA (post-ACA year is 2016). Effect of ACA is defined as the difference between the values of dependent variables in post-ACA and the predicted values of dependent variables in the post-ACA year using counterfactual. RESULTS: The counterfactual analysis show that the utilization of mammogram and pap test did not improve following ACA. CONCLUSION: Removal of cost-sharing under the ACA did not improve mammography or pap test rates. Therefore, financial barrier may not be an important factor in affecting utilization of the screening tests and policy makers should focus on other non-financial barriers in order to improve coverage of the tests.

Geographic variation in the treatment of proximal humerus fracture: an update on surgery rates and treatment consensus.

BACKGROUND: Using a larger, more comprehensive sample, and inclusion of the reverse shoulder arthroplasty as a primary surgical approach for proximal humerus fracture, we report on geographic variation in the treatment of proximal humerus fracture in 2011 and comment on whether treatment consensus is being reached. METHODS: This was a retrospective cohort study of Medicare patients with an x-ray-confirmed diagnosis of proximal humerus fracture in 2011. Patients receiving reverse shoulder arthroplasty, hemiarthroplasty, or open reduction internal fixation within 60 days of their diagnosis were classified as surgical management patients. Unadjusted observed surgery rates and area treatment ratios adjusted for patient demographic and clinical characteristics were calculated at the hospital referral region level. RESULTS: Among patients with proximal humerus fracture (N = 77,053), 15.4% received surgery and 84.6% received conservative management. Unadjusted surgery rates varied from 1.7 to 33.3% across hospital referral regions. Among patients receiving surgery, 22.3% received hemiarthroplasty, 65.8% received open reduction internal fixation, and 11.8% received reverse shoulder arthroplasty. Patients that were female, were younger, had fewer medical comorbidities, had a lower frailty index, were white, or were not dual-eligible for Medicaid during the month of their index fracture were more likely to receive surgery (p < .0001). Geographic variation in the treatment of proximal humerus fracture persisted after adjustment for patient demographic and clinical differences across local areas. Average surgery rates ranged from 9.9 to 21.2% across area treatment ratio quintiles. CONCLUSIONS: Persistent geographic variation in surgery rates for proximal humerus fracture across the USA suggests no treatment consensus has been reached.

Athletic Trainers' Effect on Population Health: Improving Access to and Quality of Care.

CONTEXT: The scope of athletic training practice combined with the magnitude of scholastic athletic injuries means that the scholastic athletic trainer (AT) is uniquely positioned to positively affect the overall health care of this population. The AT is equipped to serve in the prevention and primary management of injuries and return to activity of scholastic athletes. However, to optimize the musculoskeletal health of all athletes within a given setting, the gaps in clinical care must be continuously evaluated. Quality improvement (QI) approaches are often used to establish a framework for delivering care that promotes the best health status of the targeted population. OBJECTIVE: To describe the creation, implementation, and early results of a QI initiative aimed at advancing the health of the scholastic athletes served in the Greenville County, South Carolina, school district. DESIGN: Cohort study. PATIENTS OR OTHER PARTICIPANTS: A total of 49 793 athletes. MAIN OUTCOME MEASURE(S): The QI framework consisted of a process that documented the magnitude of athletic injuries, established risk factors for injury, defined intervention steps for at-risk athletes, and evaluated the QI process before and after implementation. The results were regularly reported to participating stakeholders, including ATs, athletic directors, coaches, parents, and athletes. RESULTS: After the QI process, injury rates decreased (absolute risk difference between the 2011-2012 and 2016-2017 academic years = 22%) and resources were more strategically allocated, which resulted in a decrease in health care costs of more than 50%. CONCLUSIONS: Collectively, the QI framework as described provides a systematic process for empowering the AT as the foundation of the scholastic sports medicine team.

Comparison of Surgeon Performance of Rotator Cuff Repair: Risk Adjustment Toward a More Accurate Performance Measure.

BACKGROUND: Movement toward a value-based health-care system necessitates the development of performance measures to compare physicians, hospitals, and health-care systems. Patient-reported outcomes (PROs) are a potential metric. However, valid use of PROs hinges on the ability to risk-adjust for baseline patient differences across a surgeon's panel of patients. The purpose of this study was to propose an approach for baseline risk adjustment and evaluate the importance of risk adjustment when comparing surgeons' performance of rotator cuff repair. METHODS: Patients (n = 995) treated with arthroscopic rotator cuff repair by 34 surgeons from 2010 to 2017 were identified from a large sports medicine clinical data registry. A linear regression model was used to adjust for baseline PROs, patient demographics, and clinical characteristics to predict American Shoulder and Elbow Surgeons (ASES) change scores for each surgeon. A risk-adjusted performance measure was calculated as the difference between the average unadjusted ASES change scores and the risk-adjusted predicted ASES change scores across all patients treated by a surgeon. RESULTS: The differences between unadjusted and risk-adjusted performance scores varied widely across surgeons (range, -13.8 to 10.3 ASES points). Use of the risk-adjusted performance scores resulted in a dramatic change in the relative ranking of surgeons, compared with the ranking based on the observed ASES change scores, with 31 of the 34 surgeons' rank changing following risk adjustment. On average, the observed ASES scores improved from 49.5 ± 17.5 at baseline to 78.0 ± 22.5 at 6 months across all surgeons. In the risk-adjustment model (R = 0.44), male sex, Workers' Compensation status, higher scores on the Veterans RAND 12-item Health Survey (VR-12), lower baseline ASES scores, fair and poor tendon quality, and night pain all had a significant effect on the predicted ASES change scores (p < 0.05). CONCLUSIONS: Our results show wide variation of nearly 25 points in the risk-adjusted 6-month ASES performance difference from the highest to the lowest-performing surgeons. Additionally, 91% of surgeons' rank changed following risk adjustment. This suggests that performance measurement that does not account for baseline patient characteristics would likely result in incorrect conclusions about a surgeon's relative performance based on PROs. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Treatment for Rotator Cuff Tear Is Influenced by Demographics and Characteristics of the Area Where Patients Live.

BACKGROUND: Atraumatic rotator cuff tear is a common orthopaedic complaint for people >60 years of age. Lack of evidence or consensus on appropriate treatment for this type of injury creates the potential for substantial discretion in treatment decisions. To our knowledge, no study has assessed the implications of this discretion on treatment patterns across the United States. METHODS: All Medicare beneficiaries in the United States with a new magnetic resonance imaging (MRI)-confirmed atraumatic rotator cuff tear were identified with use of 2010 to 2012 Medicare administrative data and were categorized according to initial treatment (surgery, physical therapy, or watchful waiting). Treatment was modeled as a function of the clinical and demographic characteristics of each patient. Variation in treatment rates across hospital referral regions and the presence of area treatment signatures, representing the extent that treatment rates varied across hospital referral regions after controlling for patient characteristics, were assessed. Correlations between measures of area treatment signatures and measures of physician access in hospital referral regions were examined. RESULTS: Among patients who were identified as having a new, symptomatic, MRI-confirmed atraumatic rotator cuff tear (n = 32,203), 19.8% were managed with initial surgery; 41.3%, with initial physical therapy; and 38.8%, with watchful waiting. Patients who were older, had more comorbidity, or were female, of non-white race, or dual-eligible for Medicaid were less likely to receive surgery (p < 0.0001). Black, dual-eligible females had 0.42-times (95% confidence interval [CI], 0.34 to 0.50) lower odds of surgery and 2.36-times (95% CI, 2.02 to 2.70) greater odds of watchful waiting. Covariate-adjusted odds of surgery varied dramatically across hospital referral regions; unadjusted surgery and physical therapy rates varied from 0% to 73% and from 6% to 74%, respectively. On average, patients in high-surgery areas were 62% more likely to receive surgery than the average patient with identical measured characteristics, and patients in low-surgery areas were half as likely to receive surgery than the average comparable patient. The supply of orthopaedic surgeons and the supply of physical therapists were associated with greater use of initial surgery and physical therapy, respectively. CONCLUSIONS: Patient characteristics had a significant influence on treatment for atraumatic rotator cuff tear but did not explain the wide-ranging variation in treatment rates across areas. Local-area physician supply and specialty mix were correlated with treatment, independent of the patient's measured characteristics.