Accuracy of diagnostic codes for prenatal opioid exposure and neonatal opioid withdrawal syndrome.

OBJECTIVE: Determine the accuracy of diagnostic codes in identifying Prenatal Opioid Exposure (POE) and Neonatal Opioid Withdrawal Syndrome (NOWS). STUDY DESIGN: A cross-sectional study of 374,222 mother-infant dyads with delivery from 01/01/2010 to 12/31/2019. We ascertained maternal diagnostic codes for opioid use during pregnancy and infant diagnostic codes for drug exposure and withdrawal. We assessed sensitivity and positive predictive value (PPV) for POE and NOWS, defined using laboratory, pharmacy, and clinical data. RESULTS: Maternal codes had low sensitivity (36.4%) and PPV (34.7%) for POE. Infant codes for drug exposure were neither sensitive for POE (14%) nor NOWS (31.6%) and had low PPV. Codes for newborn withdrawal had low sensitivity (31.6%) for detecting NOWS, but high PPV (85%). Sensitivity improved (95.1%) for NOWS requiring pharmacologic treatment. CONCLUSIONS: Diagnostic codes identify POE and NOWS poorly. Improved case identification would include pharmacy and laboratory results, and clearly defined criteria for evidence of withdrawal.

Comparing Resource Use in Medical Admissions of Children With Complex Chronic Conditions.

BACKGROUND: Children with complex chronic conditions (CCCs) utilize a disproportionate share of hospital resources. OBJECTIVE: We asked whether some hospitals display a significantly different pattern of resource utilization than others when caring for similar children with CCCs admitted for medical diagnoses. RESEARCH DESIGN: Using Pediatric Health Information System data from 2009 to 2013, we constructed an inpatient Template of 300 children with CCCs, matching these to 300 patients at each hospital, thereby performing a type of direct standardization. SUBJECTS: Children with CCCs were drawn from a list of the 40 most common medical principal diagnoses, then matched to patients across 40 Children's Hospitals. MEASURES: Rate of intensive care unit admission, length of stay, resource cost. RESULTS: For the Template-matched patients, when comparing resource use at the lower 12.5-percentile and upper 87.5-percentile of hospitals, we found: intensive care unit utilization was 111% higher (6.6% vs. 13.9%, P<0.001); hospital length of stay was 25% higher (2.4 vs. 3.0 d/admission, P<0.001); and finally, total cost per patient varied by 47% ($6856 vs. $10,047, P<0.001). Furthermore, some hospitals, compared with their peers, were more efficient with low-risk patients and less efficient with high-risk patients, whereas other hospitals displayed the opposite pattern. CONCLUSIONS: Hospitals treating similar patients with CCCs admitted for similar medical diagnoses, varied greatly in resource utilization. Template Matching can aid chief quality officers benchmarking their hospitals to peer institutions and can help determine types of their patients having the most aberrant outcomes, facilitating quality initiatives to target these patients.

Comparing International and United States Undergraduate Medical Education and Surgical Outcomes Using a Refined Balance Matching Methodology.

OBJECTIVE: The aim of this study is to compare surgical outcomes of international medical graduates (IMGs) and United States medical graduates (USMGs). SUMMARY OF BACKGROUND DATA: IMGs represent 15% of practicing surgeons in the United States (US), and their training pathways often differ substantially from USMGs. To date, differences in the clinical outcomes between the 2 cohorts have not been examined. METHODS: Using a unique dataset linking AMA Physician Masterfile data with hospital discharge claims from Florida and New York (2008-2011), patients who underwent 1 of 32 general surgical operations were stratified by IMG and USMG surgeon status. Mortality, complications, and prolonged length of stay were compared between IMG and USMG surgeon status using optimal sparse network matching with balance. RESULTS: We identified 972,718 operations performed by 4581 surgeons (72% USMG, 28% IMG). IMG and USMG surgeons differed significantly in demographic (age, gender) and baseline training (years of training, university affiliation of training hospital) characteristics. USMG surgeons performed complex procedures (13.7% vs 11.1%, P < 0.01) and practiced in urban settings (79.4% vs 75.6%, P < 0.01) more frequently, while IMG surgeons performed a higher volume of studied operations (50.7 ±â€Š5.1 vs 57.8 ±â€Š8.4, P < 0.01). In the matched cohort analysis of 396,810 patients treated by IMG and USMG surgeons, rates of mortality (USMG: 2.2%, IMG: 2.1%; P < 0.001), complications (USMG: 14.5%, IMG: 14.3%; P = 0.032), and prolonged length of stay (pLOS) (USMG: 22.7%, IMG: 22.8%; P = 0.352) were clinically equivalent. CONCLUSION: Despite considerable differences in educational background, surgical training characteristics, and practice patterns, IMG and USMG-surgeons deliver equivalent surgical care to the patients whom they treat.

Large, Sparse Optimal Matching with Refined Covariate Balance in an Observational Study of the Health Outcomes Produced by New Surgeons.

Every newly trained surgeon performs her first unsupervised operation. How do the health outcomes of her patients compare with the patients of experienced surgeons? Using data from 498 hospitals, we compare 1252 pairs comprised of a new surgeon and an experienced surgeon working at the same hospital. We introduce a new form of matching that matches patients of each new surgeon to patients of an otherwise similar experienced surgeon at the same hospital, perfectly balancing 176 surgical procedures and closely balancing a total of 2.9 million categories of patients; additionally, the individual patient pairs are as close as possible. A new goal for matching is introduced, called "refined covariate balance," in which a sequence of nested, ever more refined, nominal covariates is balanced as closely as possible, emphasizing the first or coarsest covariate in that sequence. A new algorithm for matching is proposed and the main new results prove that the algorithm finds the closest match in terms of the total within-pair covariate distances among all matches that achieve refined covariate balance. Unlike previous approaches to forcing balance on covariates, the new algorithm creates multiple paths to a match in a network, where paths that introduce imbalances are penalized and hence avoided to the extent possible. The algorithm exploits a sparse network to quickly optimize a match that is about two orders of magnitude larger than is typical in statistical matching problems, thereby permitting much more extensive use of fine and near-fine balance constraints. The match was constructed in a few minutes using a network optimization algorithm implemented in R. An R package called rcbalance implementing the method is available from CRAN.

Variable-ratio matching with fine balance in a study of the Peer Health Exchange.

In some observational studies of treatment effects, matched samples are created so treated and control groups are similar in terms of observable covariates. Traditionally, such matched samples consist of matched pairs. However, alternative forms of matching may have desirable features. One strategy that may improve efficiency is to match a variable number of control units to each treated unit. Another strategy to improve balance is to adopt a fine balance constraint. Under a fine balance constraint, a nominal covariate is exactly balanced, but it does not require individually matched treated and control subjects for this variable. Here, we propose a method to allow for fine balance constraints when each treated unit is matched to a variable number of control units, which is not currently possible using existing matching network flow algorithms. Our approach uses the entire number to first determine the optimal number of controls for each treated unit. For each stratum of matched treated units, we can then apply a fine balance constraint. We then demonstrate that a matched sample for the evaluation of the Peer Health Exchange, an intervention in schools designed to decrease risky health behaviors among youths, using a variable number of controls and fine balance constraint is superior to simply using a variable-ratio match. Copyright © 2015 John Wiley & Sons, Ltd.