Long-Term Prospects for Telemedicine in Opioid Use Disorder (OUD) Treatment: Results from a Longitudinal Survey of OUD Clinicians.

BACKGROUND: During the pandemic, there was a dramatic shift to telemedicine for opioid use disorder (OUD) treatment. Little is known about how clinician attitudes about telemedicine use for OUD treatment are evolving or their preferences for future use. OBJECTIVE: To understand OUD clinician views of and preferences regarding telemedicine. DESIGN: Longitudinal survey (wave 1, December 2020; wave 2, March 2022). SUBJECTS: National sample of 425 clinicians who treat OUD. MAIN MEASURES: Self-reported proportion of OUD visits delivered via telemedicine (actual vs. preferred), comfort in using video visits for OUD, impact of telemedicine on work-related well-being. KEY RESULTS: The mean reported percentage of OUD visits delivered via telemedicine (vs. in person) dropped from 56.9% in December 2020 to 41.5% in March 2022; the mean preferred post-pandemic percentage of OUD visits delivered via telemedicine was 34.8%. Responses about comfort in using video visits for different types of OUD patients remained similar over time despite clinicians having substantially more experience with telemedicine by spring 2022 (e.g., 35.8% vs. 36.0% report being comfortable using video visits for new patients). Almost three-quarters (70.9%) reported that most of their patients preferred to have the majority of their visits via telemedicine, and 76.7% agreed that the option to do video visits helped their patients remain in treatment longer. The majority (58.7%) reported that telemedicine had a positive impact on their work-related well-being, with higher rates of a positive impact among those who completed training more recently (68.5% of those with < 10 years, 62.1% with 10-19 years, and 45.8% with 20 + years, p < 0.001). CONCLUSIONS: While many surveyed OUD clinicians were not comfortable using telemedicine for all types of patients, most wanted telemedicine to account for a substantial fraction of OUD visits, and most believed telemedicine has had positive impacts for themselves and their patients.

Conditional cross-design synthesis estimators for generalizability in Medicaid.

While much of the causal inference literature has focused on addressing internal validity biases, both internal and external validity are necessary for unbiased estimates in a target population of interest. However, few generalizability approaches exist for estimating causal quantities in a target population that is not well-represented by a randomized study but is reflected when additionally incorporating observational data. To generalize to a target population represented by a union of these data, we propose a novel class of conditional cross-design synthesis estimators that combine randomized and observational data, while addressing their estimates' respective biases-lack of overlap and unmeasured confounding. These methods enable estimating the causal effect of managed care plans on health care spending among Medicaid beneficiaries in New York City, which requires obtaining estimates for the 7% of beneficiaries randomized to a plan and 93% who choose a plan, who do not resemble randomized beneficiaries. Our new estimators include outcome regression, propensity weighting, and double robust approaches. All use the covariate overlap between the randomized and observational data to remove potential unmeasured confounding bias. Applying these methods, we find substantial heterogeneity in spending effects across managed care plans. This has major implications for our understanding of Medicaid, where this heterogeneity has previously been hidden. Additionally, we demonstrate that unmeasured confounding rather than lack of overlap poses a larger concern in this setting.

Uncertainty in lung cancer stage for survival estimation via set-valued classification.

The difficulty in identifying cancer stage in health care claims data has limited oncology quality of care and health outcomes research. We fit prediction algorithms for classifying lung cancer stage into three classes (stages I/II, stage III, and stage IV) using claims data, and then demonstrate a method for incorporating the classification uncertainty in survival estimation. Leveraging set-valued classification and split conformal inference, we show how a fixed algorithm developed in one cohort of data may be deployed in another, while rigorously accounting for uncertainty from the initial classification step. We demonstrate this process using SEER cancer registry data linked with Medicare claims data.

Patterns of Mental Health Care Before Initiation of Telemental Health Services.

BACKGROUND: Use of telemental health has increased among rural Medicare beneficiaries, particularly among individuals with serious mental illness (SMI). Little is known about what leads to the initiation of telemental health. OBJECTIVE: To categorize the different patterns of mental health care use before initiation of telemental health services among individuals with SMI. METHODS: A cohort of rural beneficiaries with SMI (defined as schizophrenia/related psychotic disorders or bipolar disorder) with an index telemental health visit in 2010-2017 was built using claims for a 20% random sample of fee-for-service Medicare beneficiaries. The authors used latent class analysis to identify classes of mental health care use in the 6 months before the index telemental health visits. Across the classes, the authors also described characteristics of index and subsequent mental health visits. RESULTS: The cohort included 4930 rural Medicare beneficiaries with SMI. Three classes of mental health care use before initiation of telemental health were identified. The largest class (n=3066) had minimal use of primary care provider mental health care and the second largest class (n=1537) had minimal specialty mental health care. The smallest class (n=327) was characterized by recent hospitalization or emergency department care. In the overall cohort, index visits were frequently established visits and were often with specialty prescribers. CONCLUSIONS: Our findings highlight 3 distinct patterns of care before telemental health initiation, providing insight into the role that telemedicine may play in mental health care for rural Medicare beneficiaries with SMI. Overall, telemental health was most often used to maintain care with existing providers.

Impact of an Episode-Based Payment Initiative by Commercial Payers in Arkansas on Procedure Volume: an Observational Study.

BACKGROUND: Episode-based payment (EBP) is gaining traction among payers as an alternative to fee-for-service reimbursement. However, there is concern that EBP could influence the number of episodes. OBJECTIVE: To examine how procedure volume changed after the introduction of EBP in 2013 and 2014 under the Arkansas Health Care Payment Improvement Initiative. DESIGN: Using 2011-2016 commercial claims data, we estimate a difference-in-differences model to assess the impact of EBP on the probability of a beneficiary having an episode for four procedures that were reimbursed under EBP in Arkansas: total joint replacement, cholecystectomy, colonoscopy, and tonsillectomy. PARTICIPANTS: Commercially insured beneficiaries in Arkansas serve as our treatment group, while commercially insured beneficiaries in neighboring states serve as our comparison group. INTERVENTIONS: Statewide implementation of EBP for various clinical conditions by two of Arkansas' largest commercial insurers. MAIN MEASURES: For a given procedure type, the primary outcomes are the annual rate of procedures (number of procedures per 1000 beneficiaries) and the probability of a beneficiary undergoing that procedure in a given quarter. KEY RESULTS: The relationship between EBP and procedure volume varies across procedures. After EBP was implemented, the probability of undergoing colonoscopy increased by 17.2% (point estimate, 2.63; 95% CI, 1.18 to 4.08; p < 0.001; Arkansas pre-period mean, 15.29). The probability of undergoing total joint replacement increased by 9.9% (point estimate, 0.091; 95% CI, - 0.011 to 0.19; p = 0.08; Arkansas pre-period mean, 0.91), though this effect is not significant. There is no discernable impact on cholecystectomy or tonsillectomy volume. CONCLUSIONS: We do not find clear evidence of deleterious volume expansion. However, because the impact of EBP on procedure volume may vary by procedure, payers planning to implement EBP models should be aware of this possibility.

Fair regression for health care spending.

The distribution of health care payments to insurance plans has substantial consequences for social policy. Risk adjustment formulas predict spending in health insurance markets in order to provide fair benefits and health care coverage for all enrollees, regardless of their health status. Unfortunately, current risk adjustment formulas are known to underpredict spending for specific groups of enrollees leading to undercompensated payments to health insurers. This incentivizes insurers to design their plans such that individuals in undercompensated groups will be less likely to enroll, impacting access to health care for these groups. To improve risk adjustment formulas for undercompensated groups, we expand on concepts from the statistics, computer science, and health economics literature to develop new fair regression methods for continuous outcomes by building fairness considerations directly into the objective function. We additionally propose a novel measure of fairness while asserting that a suite of metrics is necessary in order to evaluate risk adjustment formulas more fully. Our data application using the IBM MarketScan Research Databases and simulation studies demonstrates that these new fair regression methods may lead to massive improvements in group fairness (eg, 98%) with only small reductions in overall fit (eg, 4%).

Association Between Endoscopist Personality and Rate of Adenoma Detection.

BACKGROUND & AIMS: There is significant variation among endoscopists in their adenoma detection rates (ADRs). We explored associations between ADR and characteristics of endoscopists, including personality traits and financial incentives. METHODS: We collected electronic health record data from October 2013 through September 2015 and calculated ADRs for physicians from 4 health systems. ADRs were risk-adjusted for differences in patient populations. Physicians were surveyed to assess financial motivations, knowledge and perceptions about colonoscopy quality, and personality traits. Of 140 physicians sent the survey, 117 responded. RESULTS: The median risk-adjusted ADR for all surveyed physicians was 29.3% (interquartile range, 24.1%-35.5%). We found no significant association between ADR and financial incentives, malpractice concerns, or physicians' perceptions of ADR as a quality metric. ADR was associated with the degree of self-reported compulsiveness relative to peers: among endoscopists who described themselves as much more compulsive, the ADR was 33.1%; among those who described themselves as somewhat more compulsive, the ADR was 32.9%; among those who described themselves as about the same as others, the ADR was 26.4%; and among those who described themselves as somewhat less compulsive, the ADR was 27.3%) (P = .0019). ADR was also associated with perceived thoroughness (much more thorough than peers, ADR = 31.5%; somewhat more, 31.9%; same/somewhat less, 27.1%; P = .0173). Physicians who reported feeling rushed, having difficulty pacing themselves, or having difficulty in accomplishing goals had higher ADRs. A secondary analysis found the same associations between personality and adenomas per colonoscopy. CONCLUSIONS: We found no significant association between ADR and financial incentives, malpractice concerns, or perceptions of ADR as a quality metric. However, ADRs were higher among physicians who described themselves as more compulsive or thorough, and among those who reported feeling rushed or having difficulty accomplishing goals.

Double robust estimation for multiple unordered treatments and clustered observations: Evaluating drug-eluting coronary artery stents.

Postmarket comparative effectiveness and safety analyses of therapeutic treatments typically involve large observational cohorts. We propose double robust machine learning estimation techniques for implantable medical device evaluations where there are more than two unordered treatments and patients are clustered in hospitals. This flexible approach also accommodates high-dimensional covariates drawn from clinical databases. The Massachusetts Data Analysis Center percutaneous coronary intervention cohort is used to assess the composite outcome of 10 drug-eluting stents among adults implanted with at least one drug-eluting stent in Massachusetts. We find remarkable discrimination between stents. A simulation study designed to mimic this coronary intervention cohort is also presented and produced similar results.

Computational health economics for identification of unprofitable health care enrollees.

Health insurers may attempt to design their health plans to attract profitable enrollees while deterring unprofitable ones. Such insurers would not be delivering socially efficient levels of care by providing health plans that maximize societal benefit, but rather intentionally distorting plan benefits to avoid high-cost enrollees, potentially to the detriment of health and efficiency. In this work, we focus on a specific component of health plan design at risk for health insurer distortion in the Health Insurance Marketplaces: the prescription drug formulary. We introduce an ensembled machine learning function to determine whether drug utilization variables are predictive of a new measure of enrollee unprofitability we derive, and thus vulnerable to distortions by insurers. Our implementation also contains a unique application-specific variable selection tool. This study demonstrates that super learning is effective in extracting the relevant signal for this prediction problem, and that a small number of drug variables can be used to identify unprofitable enrollees. The results are both encouraging and concerning. While risk adjustment appears to have been reasonably successful at weakening the relationship between therapeutic-class-specific drug utilization and unprofitability, some classes remain predictive of insurer losses. The vulnerable enrollees whose prescription drug regimens include drugs in these classes may need special protection from regulators in health insurance market design.

Variation in Pathologist Classification of Colorectal Adenomas and Serrated Polyps.

OBJECTIVES: Endoscopist quality measures such as adenoma detection rate (ADR) and serrated polyp detection rates (SPDRs) depend on pathologist classification of histology. Although variation in pathologic interpretation is recognized, we add to the literature by quantifying the impact of pathologic variability on endoscopist performance. METHODS: We used natural language processing to abstract relevant data from colonoscopy and related pathology reports performed over 2 years at four clinical sites. We quantified each pathologist's likelihood of classifying polyp specimens as adenomas or serrated polyps. We estimated the impact on endoscopists' ADR and SPDR of sending their specimens to pathologists with higher or lower classification rates. RESULTS: We observed 85,526 colonoscopies performed by 119 endoscopists; 50,453 had a polyp specimen, which were analyzed by 48 pathologists. There was greater variation across pathologists in classification of serrated polyps than in classification of adenomas. We estimate the endoscopist's average SPDR would be 0.5% if all their specimens were analyzed by the pathologist in our sample with the lowest classification rate and 12.0% if all their specimens were analyzed by the pathologist with the highest classification rate. In contrast, the endoscopist's average ADR would be 28.5% and 42.4% if their specimens were analyzed by the pathologist with lowest and highest classification rate, respectively. CONCLUSIONS: There is significant variation in pathologic interpretation, which more substantially affects endoscopist SPDR than ADR.

Physician characteristics associated with higher adenoma detection rate.

BACKGROUND AND AIMS: Patients who receive a colonoscopy from a physician with a low adenoma detection rate (ADR) are at higher risk of subsequent colorectal cancer. It is unclear what drives the variation across physicians in ADR. We describe physician characteristics associated with higher ADR. METHODS: In this retrospective cohort study a natural language processing system was used to analyze all outpatient colonoscopy examinations and their associated pathology reports from October 2013 to September 2015 for adults age 40 years and older across physicians from 4 diverse health systems. Physician performance on ADR was risk adjusted for differences in patient population and procedure indication. Our sample included 201 physicians performing at least 30 colonoscopy examinations during the study period, totaling 104,618 colonoscopy examinations. RESULTS: The mean ADR was 33.2% (range, 6.3%-58.7%). Higher ADR was seen among female physicians (4.2 percentage points higher than men, P = .020), gastroenterologists (9.4 percentage points higher than nongastroenterologists, P < .001), and physicians with ≤9 years since their residency completion (6.0 percentage points higher than physicians who have had 27-51 years of practice, P = .004). CONCLUSIONS: Gastroenterologists, female physicians, and more recently trained physicians had higher performance in adenoma detection.

Endoscopist factors that influence serrated polyp detection: a multicenter study.

BACKGROUND: Serrated polyps are important colorectal cancer precursors that are variably detected during colonoscopy. We measured serrated polyp detection rate (SPDR) in a large, multicenter, cross-sectional study of colonoscopy quality to identify drivers of SPDR variation. METHODS: Colonoscopy and pathology reports were collected for a 2-year period (10/2013-9/2015) from four sites across the United States. Data from reports, including size, location, and histology of polyps, were abstracted using a validated natural language processing algorithm. SPDR was defined as the proportion of colonoscopies with ≥ 1 serrated polyp (not including hyperplastic polyps). Multivariable logistic regression was performed to determine endoscopist characteristics associated with serrated polyp detection. RESULTS: A total of 104 618 colonoscopies were performed by 201 endoscopists who varied with respect to specialty (86 % were gastroenterologists), sex (18 % female), years in practice (range 1 - 51), and number of colonoscopies performed during the study period (range 30 - 2654). The overall mean SPDR was 5.1 % (SD 3.8 %, range 0 - 18.8 %). In multivariable analysis, gastroenterology specialty training (odds ratio [OR] 1.89, 95 % confidence interval [CI] 1.33 - 2.70), fewer years in practice (≤ 9 years vs. ≥ 27 years: OR 1.52, 95 %CI 1.14 - 2.04)], and higher procedure volumes (highest vs. lowest quartile: OR 1.77, 95 %CI 1.27 - 2.46)] were independently associated with serrated polyp detection. CONCLUSIONS: Gastroenterology specialization, more recent completion of training, and greater procedure volume are associated with serrated polyp detection. These findings imply that both repetition and training are likely to be important contributors to adequate detection of these important cancer precursors. Additional efforts to improve SPDR are needed.

Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of causal effect estimation use propensity score methods or G-computation, targeted maximum likelihood estimation (TMLE) is a well-established alternative method with desirable statistical properties. TMLE is a doubly robust maximum-likelihood-based approach that includes a secondary "targeting" step that optimizes the bias-variance tradeoff for the target parameter. Under standard causal assumptions, estimates can be interpreted as causal effects. Because TMLE has not been as widely implemented in epidemiologic research, we aim to provide an accessible presentation of TMLE for applied researchers. We give step-by-step instructions for using TMLE to estimate the average treatment effect in the context of an observational study. We discuss conceptual similarities and differences between TMLE and 2 common estimation approaches (G-computation and inverse probability weighting) and present findings on their relative performance using simulated data. Our simulation study compares methods under parametric regression misspecification; our results highlight TMLE's property of double robustness. Additionally, we discuss best practices for TMLE implementation, particularly the use of ensembled machine learning algorithms. Our simulation study demonstrates all methods using super learning, highlighting that incorporation of machine learning may outperform parametric regression in observational data settings.

Changes in health care spending and quality 4 years into global payment.

BACKGROUND: Spending and quality under global budgets remain unknown beyond 2 years. We evaluated spending and quality measures during the first 4 years of the Blue Cross Blue Shield of Massachusetts Alternative Quality Contract (AQC). METHODS: We compared spending and quality among enrollees whose physician organizations entered the AQC from 2009 through 2012 with those among persons in control states. We studied spending changes according to year, category of service, site of care, experience managing risk contracts, and price versus utilization. We evaluated process and outcome quality. RESULTS: In the 2009 AQC cohort, medical spending on claims grew an average of $62.21 per enrollee per quarter less than it did in the control cohort over the 4-year period (P<0.001). This amount is equivalent to a 6.8% savings when calculated as a proportion of the average post-AQC spending level in the 2009 AQC cohort. Analogously, the 2010, 2011, and 2012 cohorts had average savings of 8.8% (P<0.001), 9.1% (P<0.001), and 5.8% (P=0.04), respectively, by the end of 2012. Claims savings were concentrated in the outpatient-facility setting and in procedures, imaging, and tests, explained by both reduced prices and reduced utilization. Claims savings were exceeded by incentive payments to providers during the period from 2009 through 2011 but exceeded incentive payments in 2012, generating net savings. Improvements in quality among AQC cohorts generally exceeded those seen elsewhere in New England and nationally. CONCLUSIONS: As compared with similar populations in other states, Massachusetts AQC enrollees had lower spending growth and generally greater quality improvements after 4 years. Although other factors in Massachusetts may have contributed, particularly in the later part of the study period, global budget contracts with quality incentives may encourage changes in practice patterns that help reduce spending and improve quality. (Funded by the Commonwealth Fund and others.).

Insurance Transitions and Changes in Physician and Emergency Department Utilization: An Observational Study.

BACKGROUND: Shopping for health insurance is encouraged as a way to find the most affordable coverage that best meets an enrollee's needs. However, the extent to which individuals switch insurance and subsequent changes in health care utilization that might arise, particularly new physician visits, are not well understood. OBJECTIVE: To examine the relationship between insurance switching and new physician and emergency department visits around the time of a switch. DESIGN: Observational study using a difference-in-differences design to compare those switching insurance carriers with propensity score-matched controls who did not switch, stratified based on whether individuals initially had private or Medicaid insurance coverage. All analyses adjusted for individual and insurance characteristics. PARTICIPANTS: Continuously insured, non-elderly individuals with private or Medicaid insurance coverage in Massachusetts from 2010 to 2013. MAIN MEASURES: Rates of new primary care and specialist physician visits, as well as rates of emergency department visits. KEY RESULTS: Before matching, among 1,628,057 continuously insured individuals, 418,231 (26%) switched insurance carriers during a 2-year period. Characteristics of switchers and non-switchers were similar after matching (n = 316,343 in each group). After matching, switching plans was associated with a 203% and 47.5% increase in the rate of new primary care physician visits following switching for those initially with Medicaid or private coverage, respectively (both p < 0.001), with a large short-term increase, diminishing over time. Among those with Medicaid coverage, switching was associated with a 14.9% higher rate of ED visits during the month of switching (p < 0.001), but otherwise decreased modestly after switching. CONCLUSIONS: Insurance switching is common, and is associated with increased new physician visits and temporarily increased ED use among the publicly insured. As insurance markets become more volatile in the current policy environment, understanding changes in utilization after insurance switching may become increasingly important.

The impact of exclusion criteria on a physician's adenoma detection rate.

BACKGROUND: The adenoma detection rate (ADR) is a validated and widely used measure of colonoscopy quality. There is uncertainty in the published literature as to which colonoscopy examinations should be excluded when measuring a physician's ADR. OBJECTIVE: To examine the impact of varying the colonoscopy exclusion criteria on physician ADR. DESIGN: We applied different exclusion criteria used in 30 previous studies to a dataset of endoscopy and pathology reports. Under each exclusion criterion, we calculated physician ADR. SETTING: A private practice colonoscopy center affiliated with the University of Illinois College of Medicine. PATIENTS: Data on 20,040 colonoscopy examinations performed by 11 gastroenterologists from July 2009 to May 2013 and associated pathology notes. MAIN OUTCOME MEASUREMENTS: ADRs across all colonoscopy examinations, each physician's ADR, and ADR ranking. RESULTS: There were 28 different exclusion criteria used when measuring the ADR. Each study used a different combination of these exclusion criteria. The proportion of all colonoscopy examinations in the dataset excluded under these combinations of exclusion criteria ranged from 0% to 92.2%. The mean ADR across all colonoscopy examinations was 39.1%. The change in mean ADR after applying the 28 exclusion criteria ranged from -5.5 to +3.0 percentage points. However, the exclusion criteria affected each physician's ADR relatively equally, and therefore physicians' rankings via the ADR were stable. LIMITATIONS: ADR assessment was limited to a single private endoscopy center. CONCLUSION: There is wide variation in the exclusion criteria used when measuring the ADR. Although these exclusion criteria can affect overall ADRs, the relative rankings of physicians by ADR were stable. A consensus definition of which exclusion criteria are applied when measuring ADR is needed.

Public reporting of colonoscopy quality is associated with an increase in endoscopist adenoma detection rate.

BACKGROUND: Colonoscopy is the predominant method for colorectal cancer screening in the United States. Previous studies have documented variation across physicians in colonoscopy quality as measured by the adenoma detection rate (ADR). ADR is the primary quality measure of colonoscopy examinations and an indicator of the likelihood of subsequent colorectal cancer. There is interest in mechanisms to improve the ADR. In Central Illinois, a local employer and a quality improvement organization partnered to publically report physician colonoscopy quality. OBJECTIVE: We assessed whether this initiative was associated with an improvement in the ADR. DESIGN: We compared ADRs before and after public reporting at a private practice endoscopy center with 11 gastroenterologists in Peoria, Illinois, who participated in the initiative. To generate the ADR, colonoscopy and pathology reports from examinations performed over 4 years at the endoscopy center were analyzed by using previously validated natural language processing software. SETTING: A central Illinois endoscopy center. RESULTS: The ADR in the pre-public reporting period was 34.3% and 39.2% in the post-public reporting period (an increase of 4.9%, P < .001). The increase in the right-sided ADR was 5.1% (P < .01), whereas the increase in the left-sided ADR was 2.1% (P < .05). The increase in the ADR was 7.8% for screening colonoscopies (P < 0.05) and 3.5% for nonscreening colonoscopies (P < .05). All but 1 physician's ADR increased (range -2.7% to 10.5%). There was no statistically significant change in the advanced ADR (increase of 0.8%, P = .22). LIMITATIONS: There was no concurrent control group to assess whether the increased ADR was due to a secular trend. CONCLUSION: A public reporting initiative on colonoscopy quality was associated with an increase in ADR.

A double robust approach to causal effects in case-control studies.

In a recent issue of the Journal, VanderWeele and Vansteelandt (Am J Epidemiol. 2011;174(10):1197-1203) discussed an inverse probability weighting method for case-control studies that could be used to estimate an additive interaction effect, referred to as the "relative excess risk due to interaction." In this article, we reinforce the well-known disadvantages of inverse probability weighting and comment on the desirability of the described parameter. Further, we review an existing double robust estimator not considered by VanderWeele and Vansteelandt, the case-control-weighted targeted maximum likelihood estimator, which has improved properties in comparison with a previously described inverse-probability-weighted estimator. This targeted maximum likelihood estimator can be used to target various parameters of interest, and its implementation has been described previously for the risk difference, relative risk, and odds ratio.