Association Between the Modified Frailty Index and Outcomes Following Lobectomy.

INTRODUCTION: Elective thoracic surgery is safe in well-selected elderly patients. The association of frailty with postoperative morbidity in elective-lobectomy patients is understudied. We examined frailty as defined by abbreviated modified frailty index (mFI-5), mFI-11 in the thoracic surgery population, and the correlation between frailty and postoperative complications. METHODS: We studied outcomes of patients in two cohorts, 2010-2012 and 2013-2019, from the National Surgical Quality Improvement Program (NSQIP) database and used multivariable logistic regression models to predict all postoperative morbidity, mortality, and major morbidity. The mFI-5 could be calculated for all subjects (both 2010-2012, and 2013-2019); the mFI-11 could only be calculated for the 2010-2012 cohort. Patient frailty was defined as mFI≥3 (with either index). We used odds ratios (ORs) to examine associations of preoperative characteristics with postoperative complications and C-statistics to assess overall predictive power. RESULTS: Complications were less prevalent in the 2013-2019 cohort (17.9% versus 19.5%, P = 0.008). Open lobectomies were more common in the 2010-2012 cohort (53.9% versus 34.6%) and were strongly associated with postoperative morbidity and mortality (ORs >1.5) in both cohorts. Each frailty measure was associated with morbidity and mortality (ORs >1.4) after adjusting for other significant preoperative factors. Models on the 2010-2012 cohort had nearly identical C-statistics using the mFI-11 versus mFI-5 frailty indices (0.6142 versus 0.6139; P > 0.8). CONCLUSIONS: Frailty, as captured in the mFI-5, is a significant associated factor of postoperative morbidity and mortality following elective lobectomies. As a modifiable risk factor, frailty should be considered in surgical decision-making and when counseling patients regarding perioperative risks.

Maintaining Program Fidelity in a Changing World: National Implementation of a School-Based HIV Prevention Program.

Large-scale, evidence-based interventions face challenges to program fidelity of implementation. We developed implementation strategies to support teachers implementing an evidence-based HIV prevention program in schools, Focus on Youth in The Caribbean (FOYC) and Caribbean Informed Parents and Children Together (CImPACT) in The Bahamas. We examined the effects of these implementation strategies on teachers' implementation in the subsequent year after the initial implementation during the COVID-19 pandemic. Data were collected from 79 Grade 6 teachers in 24 government elementary schools. Teachers completed training workshops and a pre-implementation questionnaire to record their characteristics and perceptions that might affect their program fidelity. School coordinators and peer mentors provided teachers with monitoring, feedback, and mentoring. In Year 1, teachers on average taught 79.3% of the sessions and 80.8% of core activities; teachers in Year 2 covered 84.2% of sessions and 72.9% of the core activities. Teachers with "good" or "excellent" school coordinators in the second year taught significantly more sessions on average (7.8 vs. 7.0, t = 2.04, P < 0.05) and more core activities (26.3 vs. 23.0, t = 2.41, P < 0.05) than teachers with "satisfactory" coordinators. Teachers who had a "good" or "satisfactory" mentor taught more sessions than teachers who did not have a mentor (7.9 vs. 7.3; t = 2.22; P = 0.03). Two-level mixed-effects model analysis indicated that teachers' program fidelity in Year 1, confidence in the execution of core activities, and school coordinators' performance were significantly associated with Year 2 implementation dose. Implementation of FOYC + CImPACT was significantly associated with improved student outcomes. Teachers maintained high fidelity to a comprehensive HIV prevention program over 2 years during the COVID-19 pandemic. Future program implementers should consider additional implementation support to improve the implementation of school-based programs.

Association of Social Determinants of Health With Adherence to Second-generation Antipsychotics for People With Bipolar Disorders in a Medicaid Population.

BACKGROUND: About 7 million people, 2.8% of US adults, have bipolar disorder (BD). While second-generation antipsychotics (SGA) are indicated as acute and maintenance treatments for BD, therapeutic success requires medication adherence and reported nonadherence estimates to range as high as 60%. Identifying patient risk factors for nonadherence is important for reducing it. OBJECTIVE: The objective of this study was to quantify the associations of risk factors, including social determinants of health, with SGA nonadherence among patients with BD. METHODS: In this cross-sectional study of 2015-2017 MassHealth Medicaid data, we examined several definitions of adherence and used logistic regression to identify risk factors for nonadherence (medication possession ratio <0.8) among all adults aged 18-64 diagnosed with BD who could be followed for 12 months following SGA initiation. RESULTS: Among 5197 patients, the mean (±SD) age was 37.7 (±11.4) years, and 42.3% were men. Almost half (47.7%) of patients were nonadherent to SGAs when measured by medication possession ratio. The prevalence of nonadherence peaked at middle age for men and younger for women. Nonadherence was less common among Massachusetts' Department of Mental Health clients (odds ratio=0.60, 95% confidence limit: 0.48-0.74) and among those who used other psychotropic medications (odds ratios between 0.45 and 0.81); in contrast, increase in neighborhood socioeconomic stress was associated with increased odds of nonadherence. CONCLUSIONS/IMPLICATIONS: Adherence to SGA treatment is suboptimal among people with BD. Recognizing risk factors, including those related to social determinants of health, can help target interventions to improve adherence for people at high risk and has implications for adherence-based quality measures.

Complex Patients Have More Emergency Visits: Don't Punish the Systems That Serve Them.

IMPORTANCE: Better patient management can reduce emergency department (ED) use. Performance measures should reward plans for reducing utilization by predictably high-use patients, rather than rewarding plans that shun them. OBJECTIVE: The objective of this study was to develop a quality measure for ED use for people diagnosed with serious mental illness or substance use disorder, accounting for both medical and social determinants of health (SDH) risks. DESIGN: Regression modeling to predict ED use rates using diagnosis-based and SDH-augmented models, to compare accuracy overall and for vulnerable populations. SETTING: MassHealth, Massachusetts' Medicaid and Children's Health Insurance Program. PARTICIPANTS: MassHealth members ages 18-64, continuously enrolled for the calendar year 2016, with a diagnosis of serious mental illness or substance use disorder. EXPOSURES: Diagnosis-based model predictors are diagnoses from medical encounters, age, and sex. Additional SDH predictors describe housing problems, behavioral health issues, disability, and neighborhood-level stress. MAIN OUTCOME AND MEASURES: We predicted ED use rates: (1) using age/sex and distinguishing between single or dual diagnoses; (2) adding summarized medical risk (DxCG); and (3) further adding social risk (SDH). RESULTS: Among 144,981 study subjects, 57% were women, 25% dually diagnosed, 67% White/non-Hispanic, 18% unstably housed, and 37% disabled. Utilization was higher by 77% for those dually diagnosed, 50% for members with housing problems, and 18% for members living in the highest-stress neighborhoods. SDH modeling predicted best for these high-use populations and was most accurate for plans with complex patients. CONCLUSION: To set appropriate benchmarks for comparing health plans, quality measures for ED visits should be adjusted for both medical and social risks.

Twenty-five year trends (1986-2011) in hospital incidence and case-fatality rates of ventricular tachycardia and ventricular fibrillation complicating acute myocardial infarction.

BACKGROUND: Long-term trends in the incidence rates (IRs) and hospital case-fatality rates (CFRs) of ventricular tachycardia (VT) and ventricular fibrillation (VF) among patients hospitalized with acute myocardial infarction (AMI) have not been recently examined. METHODS: We used data from 11,825 patients hospitalized with AMI at all 11 medical centers in central Massachusetts on a biennial basis between 1986 and 2011. Multivariable adjusted logistic regression modeling was used to examine trends in hospital IRs and CFRs of VT and VF complicating AMI. RESULTS: The median age of the study population was 71 years, 57.9% were men, and 94.7% were white. The hospital IRs declined from 14.3% in 1986/1988 to 10.5% in 2009/2011 for VT and from 8.2% to 1.7% for VF. The in-hospital CFRs declined from 27.7% to 6.9% for VT and from 49.6% to 36.0% for VF between 1986/1988 and 2009/2011, respectively. The IRs of both early (<48 hours) and late VT and VF declined over time, with greater declines in those of late VT and VF. The incidence rates of VT declined similarly for patients with either an ST-segment elevation myocardial infarction (STEMI) or non-STEMI, whereas they only declined in those with VF and a STEMI. CONCLUSIONS: The hospital IRs and CHRs of VT and VF complicating AMI have declined over time, likely because of changes in acute monitoring and treatment practices. Despite these encouraging trends, efforts remain needed to identify patients at risk for these serious ventricular arrhythmias so that preventive and treatment strategies might be implemented as necessary.

Emergency Department and Primary Care Use in Massachusetts 5 Years After Health Reform.

OBJECTIVE: Conceptually, access to primary care (through insurance) should reduce emergency department (ED) visits for primary care sensitive (PCS) conditions. We sought to identify characteristics of insured Massachusetts residents associated with PCS ED use, and compare such use for public versus private insurees. POPULATION AND SETTING: People under age 65 in the Massachusetts All-Payer Claims Data, 2011-2012. STUDY DESIGN: Retrospective, observational analysis of PCS ED use with nonurgent, urgent/primary care treatable, and urgent/potentially avoidable visits being considered PCS. We predicted utilization in 2012 using multivariable regression models and data available in 2011 administrative records. PRINCIPAL FINDINGS: Among 2,269,475 nonelderly Massachusetts residents, 40% had public insurance. Among public insurees, PCS ED use was higher than for private (mean, 36.5 vs. 9.0 per 100 persons; adjusted risk ratio, 2.53; 95% confidence limits, 2.49-2.56), while having any primary care visit was less common (70% vs. 83%), as was having any visit to one's own (attributed) primary care provider (38% vs. 44%). CONCLUSIONS: Public insurance was associated with less access to primary care and more PCS ED use; statewide labor shortages and low reimbursement rates from public insurance may have provided inadequate access to care that might otherwise have helped reduce PCS ED use.

Hyperglycemia and risk of ventricular tachycardia among patients hospitalized with acute myocardial infarction.

BACKGROUND: Little is known about the association of hyperglycemia with the development of ventricular tachycardia (VT) in patients hospitalized with acute myocardial infarction (AMI) which we examined in the present study. The objectives of this community-wide observational study were to examine the relation between elevated serum glucose levels at the time of hospital admission for AMI and occurrence of VT, and time of occurrence of VT, during the patient's acute hospitalization. METHODS: We used data from a population-based study of patients hospitalized with AMI at all central Massachusetts medical centers between 2001 and 2011. Hyperglycemia was defined as a serum glucose level ≥ 140 mg/dl at the time of hospital admission. The development of VT was identified from physicians notes and electrocardiographic findings by our trained team of data abstractors. RESULTS: The average age of the study population was 70 years, 58.0% were men, and 92.7% were non-Hispanic whites. The mean and median serum glucose levels at the time of hospital admission were 171.4 mg/dl and 143.0, respectively. Hyperglycemia was present in 51.9% of patients at the time of hospital admission; VT occurred in 652 patients (15.8%), and two-thirds of these episodes occurred during the first 48 h after hospital admission (early VT). After multivariable adjustment, patients with hyperglycemia were at increased risk for developing VT (adjusted OR = 1.48, 95% CI = 1.23-1.78). The presence of hyperglycemia was significantly associated with early (multivariable adjusted OR = 1.39, 95% CI = 1.11-1.73) but not with late VT. Similar associations were observed in patients with and without diabetes and in patients with and without ST-segment elevation AMI. CONCLUSIONS: Efforts should be made to closely monitor and treat patients who develop hyperglycemia, especially early after hospital admission, to reduce their risk of VT.

Neighborhood Socioeconomic Status Predicts Health After Hospitalization for Acute Coronary Syndromes: Findings From TRACE-CORE (Transitions, Risks, and Actions in Coronary Events-Center for Outcomes Research and Education).

OBJECTIVE: To explore the influence of contextual factors on health-related quality of life (HRQoL), which is sometimes used as an indicator of quality of care, we examined the association of neighborhood socioeconomic status (NSES) and trajectories of HRQoL after hospitalization for acute coronary syndromes (ACS). METHODS: We studied 1481 patients hospitalized with acute coronary syndromes in Massachusetts and Georgia querying HRQoL via the mental and physical components of the 36-item short-form health survey (SF-36) (MCS and PCS) and the physical limitations and angina-related HRQoL subscales of the Seattle Angina Questionnaire (SAQ) during hospitalization and at 1-, 3-, and 6-month postdischarge. We categorized participants by tertiles of the neighborhood deprivation index (a residence-census tract-based measure) to examine the association of NSES with trajectories of HRQoL after adjusting for individual socioeconomic status (SES) and clinical characteristics. RESULTS: Participants had mean age 61.3 (SD, 11.4) years; 33% were female; 76%, non-Hispanic white; 11.2% had household income below the federal poverty level. During 6 months postdischarge, living in lower NSES neighborhoods was associated with lower mean PCS scores (1.5 points for intermediate NSES; 1.8 for low) and SAQ scores (2.4 and 4.2 points) versus living in high NSES neighborhoods. NSES was more consequential for patients with lower individual SES. Individuals living below the federal poverty level had lower average MCS and SAQ physical scores (3.7 and 7.7 points, respectively) than those above. CONCLUSIONS: Neighborhood deprivation was associated with worse health status. Using HRQoL to assess quality of care without accounting for individual SES and NSES may unfairly penalize safety-net hospitals.

Trends in acute myocardial infarction hospitalizations: Are we seeing the whole picture?

BACKGROUND: Payers and policy makers rely on studies of trends in acute myocardial infarction (AMI) hospitalizations and spending that count only hospitalizations where the AMI is the principal discharge diagnosis. Hospitalizations with AMI coded as a secondary diagnosis are ignored. The effects of excluding these hospitalizations on estimates of trends are unknown. METHODS: Observational study of all AMI hospitalizations in Fee-for-Service Medicare beneficiaries 65 years and older, from 2002 through 2011. RESULTS: We studied 3,663,137 hospitalizations with any AMI discharge diagnosis over 288,873,509 beneficiary-years. Of these, 66% had AMI coded as principal (versus secondary). From 2002 to 2011, AMI hospitalization rates declined 24.5% (from 1,485 per 100,000 beneficiary-years in 2002 to 1,122 in 2011). Meanwhile, the proportion of these hospitalizations with a secondary AMI diagnosis increased from 28% to 40%; by 2011 these secondary AMI hospitalizations accounted for 43% of all expenditures for hospitalizations with AMI, or $2.8 billion. Major changes in comorbidities, principal diagnoses and mean costs for hospitalizations with a non-principal AMI diagnosis occurred in the 2006-2008 timeframe. CONCLUSIONS: Current estimates of the burden of AMI ignore an increasingly large proportion of overall AMI hospitalizations and spending. Changes in the characteristics of hospitalizations that coincided with major payment and policy changes suggest that non-clinical factors affect AMI coding. Failing to consider all AMIs could inflate estimates of population health improvements, overestimate the value of AMI prevention and treatment and underestimate current and future AMI burden and expenditures.

Clinical Operations Variables are Associated With Blood Pressure Outcomes.

BACKGROUND: Uncontrolled blood pressure (BP), among patients diagnosed and treated for the condition, remains an important clinical challenge; aspects of clinical operations could potentially be adjusted if they were associated with better outcomes. OBJECTIVES: To assess clinical operations factors' effects on normalization of uncontrolled BP. RESEARCH DESIGN: Observational cohort study. SUBJECTS: Patients diagnosed with hypertension from a large urban clinical practice (2005-2009). MEASURES: We obtained clinical data on BP, organized by person-month, and administrative data on primary care provider (PCP) staffing. We assessed the resolution of an episode of uncontrolled BP as a function of time-varying covariates including practice-level appointment volume, individual clinicians' appointment volume, overall practice-level PCP staffing, and number of unique PCPs. RESULTS: Among the 7409 unique patients representing 50,403 person-months, normalization was less likely for the patients in whom the episode starts during months when the number of unique PCPs were high [the top quintile of unique PCPs was associated with a 9 percentage point lower probability of normalization (P<0.01) than the lowest quintile]. Practice appointment volume negatively affected the likelihood of normalization [episodes starting in months with the most appointments were associated with a 6 percentage point reduction in the probability of normalization (P=0.01)]. Neither clinician appointment volume nor practice clinician staffing levels were significantly associated with the probability of normalization. CONCLUSIONS: Findings suggest that clinical operations factors can affect clinical outcomes like BP normalization, and point to the importance of considering outcome effects when organizing clinical care.

Outcomes of anticoagulation therapy in patients with mental health conditions.

BACKGROUND: Patients with mental health conditions (MHCs) experience poor anticoagulation control when using warfarin, but we have limited knowledge of the association between specific mental illness and warfarin treatment outcomes. OBJECTIVE: To examine the relationship between the severity of MHCs and outcomes of anticoagulation therapy. DESIGN: Retrospective cohort analysis. PARTICIPANTS: We studied 103,897 patients on warfarin for 6 or more months cared for by the Veterans Health Administration during fiscal years 2007-2008. We identified 28,216 patients with MHCs using ICD-9 codes: anxiety disorders, bipolar disorder, depression, post-traumatic stress disorder, schizophrenia, and other psychotic disorders. MAIN MEASURES: Outcomes included anticoagulation control, as measured by percent time in the therapeutic range (TTR), as well as major hemorrhage. Predictors included different categories of MHC, Global Assessment of Functioning (GAF) scores, and psychiatric hospitalizations. KEY RESULTS: Patients with bipolar disorder, depression, and other psychotic disorders experienced TTR decreases of 2.63 %, 2.26 %, and 2.92 %, respectively (p < 0.001), after controlling for covariates. Patients with psychotic disorders other than schizophrenia experienced increased hemorrhage after controlling for covariates [hazard ratio (HR) 1.24, p = 0.03]. Having any MHC was associated with a slightly increased hazard for hemorrhage (HR 1.19, p < 0.001) after controlling for covariates. CONCLUSION: Patients with specific MHCs (bipolar disorder, depression, and other psychotic disorders) experienced slightly worse anticoagulation control. Patients with any MHC had a slightly increased hazard for major hemorrhage, but the magnitude of this difference is unlikely to be clinically significant. Overall, our results suggest that appropriately selected patients with MHCs can safely receive therapy with warfarin.

Screening colonoscopy and risk for incident late-stage colorectal cancer diagnosis in average-risk adults: a nested case-control study.

BACKGROUND: The effectiveness of screening colonoscopy in average-risk adults is uncertain, particularly for right colon cancer. OBJECTIVE: To examine the association between screening colonoscopy and risk for incident late-stage colorectal cancer (CRC). DESIGN: Nested case-control study. SETTING: Four U.S. health plans. PATIENTS: 1039 average-risk adults enrolled for at least 5 years in one of the health plans. Case patients were aged 55 to 85 years on their diagnosis date (reference date) of stage IIB or higher (late-stage) CRC during 2006 to 2008. One or 2 control patients were selected for each case patient, matched on birth year, sex, health plan, and prior enrollment duration. MEASUREMENTS: Receipt of CRC screening 3 months to 10 years before the reference date, ascertained through medical record audits. Case patients and control patients were compared on receipt of screening colonoscopy or sigmoidoscopy by using conditional logistic regression that accounted for health history, socioeconomic status, and other screening exposures. RESULTS: In analyses restricted to 471 eligible case patients and their 509 matched control patients, 13 case patients (2.8%) and 46 control patients (9.0%) had undergone screening colonoscopy, which corresponded to an adjusted odds ratio (AOR) of 0.29 (95% CI, 0.15 to 0.58) for any late-stage CRC, 0.36 (CI, 0.16 to 0.80) for right colon cancer, and 0.26 (CI, 0.06 to 1.11; P = 0.069) for left colon/rectum cancer. Ninety-two case patients (19.5%) and 173 control patients (34.0%) had screening sigmoidoscopy, corresponding to an AOR of 0.50 (CI, 0.36 to 0.70) overall, 0.79 (CI, 0.51 to 1.23) for right colon late-stage cancer, and 0.26 (CI, 0.14 to 0.48) for left colon cancer. LIMITATION: The small number of screening colonoscopies affected the precision of the estimates. CONCLUSION: Screening with colonoscopy in average-risk persons was associated with reduced risk for diagnosis of incident late-stage CRC, including right-sided colon cancer. For sigmoidoscopy, this association was seen for left CRC, but the association for right colon late-stage cancer was not statistically significant.

Composite model for profiling physicians across domains of care.

Physician profiling methods are envisioned as a means of promoting healthcare quality by recognizing the contributions of individual physicians. Developing methods that can reliably distinguish among physicians' performance is challenging because of small sample sizes, incomplete data, and physician panel differences. In this study, we developed a hierarchical, weighted composite model to reliably compare primary care physicians across domains of care, and we demonstrated its use within a clinical system. We evaluated 199 primary care physicians from a large integrated healthcare delivery system using 19 quality and two efficiency measures taken from the Healthcare Effectiveness Data and Information Set and existing pay-for-performance programs. Individual measures were calculated, compared to benchmarks, and grouped into two composites: one focused on quality and one on efficiency. Each composite was fitted to the model, assessed for reliability (signal-to-noise ratio), and weighted to create a single summary score for each primary care physician. The quality-of-care composite had a median reliability of .98, with 99.5% of all physician reliability estimates exceeding threshold. The efficiency composite had a median reliability of .97, with 94.9% of all physician reliability estimates exceeding threshold. Our results demonstrate that reliable physician profiling is possible across care domains using a hierarchical composite model based on multiple data. The model was used to distribute incentive payouts among primary care physicians but is adaptable to many settings.

Strengthening Quality Measurement to Predict Success for Total Knee Arthroplasty: Results from a Nationally Representative Total Knee Arthroplasty Cohort.

BACKGROUND: When performed well on appropriate patients, total knee arthroplasty (TKA) can dramatically improve quality of life. Patient-reported outcome measures (PROMs) are increasingly used to measure outcome following TKA. Accurate prediction of improvement in PROMs after TKA potentially plays an important role in judging the surgical quality of the health-care institutions as well as informing preoperative shared decision-making. Starting in 2027, the U.S. Centers for Medicare & Medicaid Services (CMS) will begin mandating PROM reporting to assess the quality of TKAs. METHODS: Using data from a national cohort of patients undergoing primary unilateral TKA, we developed an original model that closely followed a CMS-proposed measure to predict success, defined as achieving substantial clinical benefit, specifically at least a 20-point improvement on the Knee injury and Osteoarthritis Outcome Score, Joint Arthroplasty (KOOS, JR) at 1 year, and an enhanced model with just 1 additional predictor: the baseline KOOS, JR. We evaluated each model's performance using the area under the receiver operator characteristic curve (AUC) and the ratio of observed to expected (model-predicted) outcomes (O:E ratio). RESULTS: We studied 5,958 patients with a mean age of 67 years; 63% were women, 93% were White, and 87% were overweight or obese. Adding the baseline KOOS, JR improved the AUC from 0.58 to 0.73. Ninety-four percent of those in the top decile of predicted probability of success under the enhanced model achieved success, compared with 34% in its bottom decile. Analogous numbers for the original model were less discriminating: 77% compared with 57%. Only the enhanced model predicted success accurately across the spectrum of baseline scores. The findings were virtually identical when we replicated these analyses on only patients ≥65 years of age. CONCLUSIONS: Adding a baseline knee-specific PROM score to a quality measurement model in a nationally representative cohort dramatically improved its predictive power, eliminating ceiling and floor effects and mispredictions for readily identifiable patient subgroups. The enhanced model neither favors nor discourages care for those with greater knee dysfunction and requires no new data collection. LEVEL OF EVIDENCE: Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Health Insurance Type and Outpatient Specialist Care Among Children With Asthma.

Importance: Although children with asthma are often successfully treated by primary care clinicians, outpatient specialist care is recommended for those with poorly controlled disease. Little is known about differences in specialist use for asthma among children with Medicaid vs private insurance. Objective: To examine differences among children with asthma regarding receipt of asthma specialist care by insurance type. Design, Setting, and Participants: In this cross-sectional study using data from the Massachusetts All Payer Claims Database (APCD) between 2014 to 2020, children with asthma were identified and differences in receipt of outpatient specialist care by whether their insurance was public (Medicaid and the Children's Health Insurance Program) or private were examined. Eligible participants included children with asthma in 2015 to 2020 aged 2 to 17 years. Data analysis was conducted from January 2023 to April 2024. Exposure: Medicaid vs private insurance. Main Outcomes and Measures: The primary outcome was receipt of specialist care (any outpatient visit with a pulmonology, allergy and immunology, or otolaryngology physician). Multivariable logistic regression models estimated differences in receipt of specialist care by insurance type accounting for child and area characteristics including demographics, health status, persistent asthma, calendar year, and zip code characteristics. Additional analyses examined if the associations of specialist care with insurance type varied by asthma persistence and severity, and whether associations varied over time. Results: Among 198 101 unique children, there were 432 455 child-year observations (186 296 female [43.1%] and 246 159 male [56.9%]; 211 269 aged 5 to 11 years [48.9%]; 82 108 [19.0%] with persistent asthma) including 286 408 (66.2%) that were Medicaid insured and 146 047 (33.8%) that were privately insured. Although persistent asthma was more common among child-year observations with Medicaid vs private insurance (57 381 [20.0%] vs 24 727 [16.9%]), children with Medicaid were less likely to receive specialist care. Overall, 64 239 child-year observations (14.9%) received specialist care, with substantially lower rates for children with Medicaid vs private insurance (34 093 child-year observations [11.9%] vs 30 146 child-year observations [20.6%]). Regression-based estimates confirmed these disparities; children with Medicaid had 55% lower odds of receiving specialist care (adjusted odds ratio, 0.45; 95% CI, 0.43 to 0.47) and a regression-adjusted 9.7 percentage point (95% CI, -10.4 percentage points to -9.1 percentage points) lower rate of receipt of specialist care. Compared with children with private insurance, there was an additional 3.2 percentage point (95% CI, 2.0 percentage points to 4.4 percentage points) deficit for children with Medicaid with persistent asthma. Conclusions and Relevance: In this cross-sectional study, children with Medicaid were less likely to receive specialist care, with the largest gaps among those with persistent asthma. These findings suggest that closing this care gap may be one approach to addressing ongoing disparities in asthma outcomes.

Differences in Health Care Utilization for Asthma by Children with Medicaid versus Private Insurance.

Asthma is the most common chronic disease in children, disproportionately affects families with lower incomes, and is a leading reason for acute care visits and hospitalizations. This retrospective cohort study used the Massachusetts All Payer Claims Database (2014-2018) to examine differences in acute care utilization and quality of care for asthma between Medicaid- and privately insured children in Massachusetts. Outcomes included acute care use (emergency department [ED] or hospitalization), ED visits with asthma, routine asthma visits, and filled prescriptions for asthma medications. Multivariable logistic regression was used to account for differences in demographics, ZIP codes, health status, and asthma severity. Overall, 10.0% of Medicaid-insured children and 5.6% of privately insured were classified as having asthma. Among 317,596 child-year observations for children with asthma, 64.4% were insured by Medicaid. Medicaid-insured children had higher rates of any acute care use (50.4% vs. 30.0%) and ED visits with an asthma diagnosis (27.2% vs. 13.3%) compared to privately insured children. Only 65.4% of Medicaid enrollees had at least one routine asthma visit compared to 74.3% of privately insured children. Most children received at least one asthma medication (88.6% Medicaid vs. 83.3% privately insured), but a higher percentage of Medicaid-insured children received at least one rescue medication (84.0% vs. 73.7%), and a lower percentage of Medicaid-insured (46.1% vs. 49.2%) received a controller medication. These results suggest that opportunities for improvement in childhood asthma persist, particularly for children insured by Medicaid.

A Novel Machine Learning Algorithm for Creating Risk-Adjusted Payment Formulas.

Importance: Models predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives. Objective: To develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians. Design, Setting, and Participants: DXIs were organized into disease hierarchies and assigned an Appropriateness to Include (ATI) score to reflect vagueness and gameability concerns. A novel automated DCG algorithm iteratively assigned DXIs in 1 or more disease hierarchies to DCGs, identifying sets of DXIs with the largest regression coefficient as dominant; presence of a previously identified dominating DXI removed lower-ranked ones before the next iteration. The Merative MarketScan Commercial Claims and Encounters Database for commercial health insurance enrollees 64 years and younger was used. Data from January 2016 through December 2018 were randomly split 90% to 10% for model development and validation, respectively. Deidentified claims and enrollment data were delivered by Merative the following November in each calendar year and analyzed from November 2020 to January 2024. Main Outcome and Measures: Concurrent top-coded total health care cost. Model performance was assessed using validation sample weighted least-squares regression, mean absolute errors, and mean errors for rare and common diagnoses. Results: This study included 35 245 586 commercial health insurance enrollees 64 years and younger (65 901 460 person-years) and relied on 19 clinicians who provided reviews in the base model. The algorithm implemented 218 clinician-specified hierarchies compared with the US Department of Health and Human Services (HHS) hierarchical condition category (HCC) model's 64 hierarchies. The base model that dropped vague and gameable DXIs reduced the number of parameters by 80% (1624 of 3150), achieved an R2 of 0.535, and kept mean predicted spending within 12% ($3843 of $31 313) of actual spending for the 3% of people with rare diseases. In contrast, the HHS HCC model had an R2 of 0.428 and underpaid this group by 33% ($10 354 of $31 313). Conclusions and Relevance: In this study, by automating DXI clustering within clinically specified hierarchies, this algorithm built clinically interpretable risk models in large datasets while addressing diagnostic vagueness and gameability concerns.

Bending the cost curve? Results from a comprehensive primary care payment pilot.

BACKGROUND: There is much interest in understanding how using bundled primary care payments to support a patient-centered medical home (PCMH) affects total medical costs. RESEARCH DESIGN AND SUBJECTS: We compare 2008-2010 claims and eligibility records on about 10,000 patients in practices transforming to a PCMH and receiving risk-adjusted base payments and bonuses, with similar data on approximately 200,000 patients of nontransformed practices remaining under fee-for-service reimbursement. METHODS: We estimate the treatment effect using difference-in-differences, controlling for trend, payer type, plan type, and fixed effects. We weight to account for partial-year eligibility, use propensity weights to address differences in exogenous variables between control and treatment patients, and use the Massachusetts Health Quality Project algorithm to assign patients to practices. RESULTS: Estimated treatment effects are sensitive to: control variables, propensity weighting, the algorithm used to assign patients to practices, how we address differences in health risk, and whether/how we use data from enrollees who join, leave, or change practices. Unadjusted PCMH spending reductions are 1.5% in year 1 and 1.8% in year 2. With fixed patient assignment and other adjustments, medical spending in the treatment group seems to be 5.8% (P=0.20) lower in year 1 and 8.7% (P=0.14) lower in year 2 than for propensity-weighted, continuously enrolled controls; the largest proportional 2-year reduction in spending occurs in laboratory test use (16.5%, P=0.02). CONCLUSIONS: Although estimates are imprecise because of limited data and quasi-experimental design, risk-adjusted bundled payment for primary care may have dampened spending growth in 3 practices implementing a PCMH.

Identifying the risks of anticoagulation in patients with substance abuse.

BACKGROUND: Warfarin is effective in preventing thromboembolic events, but concerns exist regarding its use in patients with substance abuse. OBJECTIVE: Identify which patients with substance abuse who receive warfarin are at risk for poor outcomes. DESIGN: Retrospective cohort study. Diagnostic codes, lab values, and other factors were examined to identify risk of adverse outcomes. PATIENTS: Veterans AffaiRs Study to Improve Anticoagulation (VARIA) database of 103,897 patients receiving warfarin across 100 sites. MAIN MEASURES: Outcomes included percent time in therapeutic range (TTR), a measure of anticoagulation control, and major hemorrhagic events by ICD-9 codes. RESULTS: Nonusers had a higher mean TTR (62 %) than those abusing alcohol (53 %), drugs (50 %), or both (44 %, p < 0.001). Among alcohol abusers, an increasing ratio of the serum hepatic transaminases aspartate aminotransferase/alanine aminotransferase (AST:ALT) correlated with inferior anticoagulation control; normal AST:ALT ≤ 1.5 predicted relatively modest decline in TTR (54 %, p < 0.001), while elevated ratios (AST:ALT 1.50-2.0 and > 2.0) predicted progressively poorer anticoagulation control (49 % and 44 %, p < 0.001 compared to nonusers). Age-adjusted hazard ratio for major hemorrhage was 1.93 in drug and 1.37 in alcohol abuse (p < 0.001 compared to nonusers), and remained significant after also controlling for anticoagulation control and other bleeding risk factors (1.69 p < 0.001 and 1.22 p = 0.003). Among alcohol abusers, elevated AST:ALT >2.0 corresponded to more than three times the hemorrhages (HR 3.02, p < 0.001 compared to nonusers), while a normal ratio AST:ALT ≤ 1.5 predicted a rate similar to nonusers (HR 1.19, p < 0.05). CONCLUSIONS: Anticoagulation control is particularly poor in patients with substance abuse. Major hemorrhages are more common in both alcohol and drug users. Among alcohol abusers, the ratio of AST/ALT holds promise for identifying those at highest risk for adverse events.

Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures.

BACKGROUND: Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. METHODS: Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. RESULTS: The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. CONCLUSIONS: The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F > 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r < 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r > 0.9).