Usual source of care and geographic region are largest predictors of healthcare quality for incident lupus nephritis in US Medicaid recipients
Bibliographic record
Abstract
Little is known about the quality of healthcare delivered to patients with lupus nephritis in the United States and the major determinants of quality remain unknown. We aimed to examine the sociodemographic, geographic, and healthcare system factors associated with performance on a healthcare quality measure in a nationwide cohort of Medicaid recipients with incident lupus nephritis. We used US Medicaid analytic extract (MAX) data from 2000 to 2004 containing person-level files on Medicaid eligibility, utilization and payments. We identified patients meeting a validated administrative data definition of incident lupus nephritis, and used this group as the denominator population for the quality metric (QM). The QM numerator assessed receipt of i nduction therapy with glucocorticoids and another immunosuppressant (azathioprine, mycophenolate mofetil, mycophenolic acid, cyclophosphamide, cyclosporine A, or tacrolimus) within 90 days of lupus nephritis onset. Patients with end-stage renal disease were excluded. We used multivariable logistic regression models to examine sociodemographic (age, sex, race/ethnicity), geographic (US region), and healthcare (health professional shortage areas, HPSAs, from the Area Resource File) predictors of higher performance. We also examined the restrictiveness of Medicaid benefits in each state, defined by less generous medication coverage policies (mandatory generic substitution, requirements for prior authorization and drug co-payments), and whether the patient's usual source of care was the emergency department or the ambulatory setting (>50% visits). A total of 974 Medicaid recipients met the definition of incident lupus nephritis. The mean age was 39 years (SD 12), 93% were female, and most were African American (African American 48%, White 27%, Hispanic 13%, Asian 6%). Individuals were geographically dispersed (20% Midwest, 22% Northeast, 34% South, 24% West), and 95% resided in partial or complete HPSAs. One hundred and sixty-four individuals resided in states with more restrictive Medicaid benefits. At 90 days, only 16% of patients met all numerator components of QM1; 45% of individuals received only steroids (mean prednisone dose 28 mg/day), and 3% received an immunosuppressant alone. Among those treated with an immunosuppressant, 31% received azathioprine, 47% received mycophenolate, 14% received cyclophosphamide, and 11% received a calcineurin inhibitor. For 20% ( n = 192) of patients, the usual source of care was in the emergency setting. In multivariable logistic regression models, younger individuals were more likely to receive optimal treatment (OR for 18 to 34 years vs. 51 to 64 years = 3.5, CI = 1.6 to 7.6), while those living in the South and Midwest were less likely (OR = 0.49, CI = 0.24 to 0.67 and OR = 0.30 CI = 0.15 to 0.61, respectively). Those whose usual source of care was the emergency department were less likely to receive optimal treatment (OR = 0.47, CI = 0.28 to 0.81). In this adjusted analysis, we did not find significant associations for race/ethnicity, HPSA or Medicaid restrictiveness with QM performance. Most US Medicaid recipients with incident lupus nephritis in our study did not receive timely induction therapy, and many were treated with high-dose steroids alone. We found significant geographic variation in performance, with the South and Midwest having lower performance than other regions. A substantial number of Medicaid patients with lupus nephritis used the emergency department as a usual source of care and performance on the QM is lower in this setting. These data suggest a need for targeted quality improvement interventions, including increasing access to appropriate ambulatory care for Medicaid recipients with lupus nephritis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".