Comparison of Low-Value Care Among Commercial and Medicaid Enrollees

Medicaid Insurance is Associated With Decreased MRI Use for Ankle Sprains Compared With Private Insurance: A Retrospective Database Analysis

BACKGROUND

Advanced imaging modalities are expensive, and access to advanced imaging services may vary by socioeconomic factors, creating the potential for unwarranted variations in care. Ankle sprains are a common injury for which variations in MRI use can occur, both via underuse of indicated MRIs (appropriate use) and overuse of nonindicated MRIs (inappropriate use). High-value, equitable healthcare would decrease inappropriate use and increase appropriate use of MRI for this common injury. It is unknown whether socioeconomic factors are associated with underuse of indicated MRIs and overuse of nonindicated MRIs for ankle sprains.

QUESTIONS/PURPOSES

Using ankle sprains as a paradigm injury, given their high population incidence, we asked: (1) Does MRI use for ankle sprains vary by insurance type? (2) After controlling for relevant confounding variables, did patients who received an MRI have higher odds of undergoing ankle surgery?

METHODS

Between 2011 and 2019, a total of 6,710,223 patients were entered into the PearlDiver Mariner Patient Records Database with a diagnosis of ankle sprain. We considered patients with continuous enrollment in the database for at least 1 year before and 2 years after the diagnosis as potentially eligible. Based on that, 68% (4,567,106) were eligible; a further 20% (1,372,478) were excluded because of age younger than 18 years, age at least 65 years with Medicaid insurance, or age < 65 years with Medicare insurance. Another 0.1% (9169) had incomplete data, leaving 47% (3,185,459) for analysis here. Patients with Medicaid insurance differed from patients with Medicare Advantage or private insurance with respect to age, gender, region, and comorbidity burden. The primary outcome was ankle MRI occurring within 12 months after diagnosis. The use of ankle surgery after MRI in each cohort was measured as a secondary outcome. We used multivariable logistic regression models to evaluate the association between insurance type and MRI use while adjusting for age, gender, region, and comorbidity burden. Separate multivariable regression models were created to evaluate the association between receiving an MRI and subsequent ankle surgery for each insurance type, adjusting for age, gender, region, and comorbidity burden. Within 12 months of an ankle sprain diagnosis, 1% (3522 of 339,457) of patients with Medicaid, 2% (44,793 of 2,627,288) of patients with private insurance, and 1% (1660 of 218,714) of patients with Medicare Advantage received an MRI.

RESULTS

After controlling for age, gender, region, and comorbidity burden, patients with Medicaid had lower odds of receiving an MRI within 12 months after ankle sprain diagnosis than patients with private insurance (odds ratio 0.60 [95% confidence interval 0.57 to 0.62]; p < 0.001). Patients with Medicaid who received an MRI had higher adjusted odds of undergoing subsequent ankle surgery (OR 23 [95% CI 21 to 26]; p < 0.001) than patients with private insurance (OR 12.7 [95% CI 12 to 13]; p < 0.001).

CONCLUSION

Although absolute MRI use was generally low, there was substantial relative variation by insurance type. Given the high incidence of ankle sprains in the general population, these relative differences can translate to tens of thousands of MRIs. Further studies are needed to evaluate the reasons for decreased appropriate MRI use in patients with Medicaid and overuse of MRI in patients with private insurance. The establishment of clinical practice guidelines by orthopaedic professional societies and more stringent gatekeeping for MRI use by health insurers could reduce unwarranted variations in MRI use.

LEVEL OF EVIDENCE

Level III, prognostic study.

Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review

PURPOSE

The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments.

METHODS

We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results.

RESULTS

Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE.

CONCLUSIONS

There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.