The natural history of large abdominal aortic aneurysms in patients without timely repair.

OBJECTIVE: Contemporary data on the natural history of large abdominal aortic aneurysms (AAAs) in patients undergoing delayed or no repair are lacking. In this study, we examine the impact of large AAA size on the incidence of rupture and mortality. METHODS: From a prospectively maintained aneurysm surveillance registry, patients with an unrepaired, large AAA (≥5.5 cm in men and ≥5.0 cm in women) at baseline (ie, index imaging) or who progressed to a large size from 2003 to 2017 were included, with follow-up through March 2020. Outcomes of interest obtained by manual chart review included rupture (confirmed by imaging/autopsy), probable rupture (timing/findings consistent with rupture without more likely cause of death), repair, reasons for either no or delayed (>1 year after diagnosis of large AAA) repair and total mortality. Cumulative incidence of rupture was calculated using a nonparametric cumulative incidence function, accounting for the competing events of death and aneurysm repair and was stratified by patient sex. RESULTS: Of the 3248 eligible patients (mean age, 83.6 ± 9.1 years; 71.2% male; 78.1% white; and 32.0% current smokers), 1423 (43.8%) had large AAAs at index imaging, and 1825 progressed to large AAAs during the follow-up period, with a mean time to qualifying size of 4.3 ± 3.4 years. In total, 2215 (68%) patients underwent repair, of which 332 were delayed >1 year; 1033 (32%) did not undergo repair. The most common reasons for delayed repair were discrepancy in AAA measurement between surgeon and radiologist (34%) and comorbidity (20%), whereas the most common reasons for no repair were patient preference (48%) and comorbidity (30%). Among patients with delayed repair (mean time to repair, 2.6 ± 1.8 years), nine (2.7%) developed symptomatic aneurysms, and an additional 11 (3.3%) ruptured. Of patients with no repair, 94 (9.1%) ruptured. The 3-year cumulative incidence of rupture was 3.4% for initial AAA size 5.0 to 5.4 cm (women only), 2.2% for 5.5 to 6.0 cm, 6.0% for 6.1 to 7.0 cm, and 18.4% for >7.0 cm. Women with AAA size 6.1 to 7.0 cm had a 3-year cumulative incidence of rupture of 12.8% (95% confidence interval, 7.5%-19.6%) compared with 4.5% (95% confidence interval, 3.0%-6.5%) in men (P = .002). CONCLUSIONS: In this large cohort of AAA registry patients over 17 years, annual rupture rates for large AAAs were lower than previously reported, with possible increased risk in women. Further analyses are ongoing to identify those at increased risk for aneurysm rupture and may provide targeted surveillance regimens and improve patient counseling.

The Contribution of First-name Information to the Accuracy of Racial-and-Ethnic Imputations Varies by Sex and Race-and-Ethnicity Among Medicare Beneficiaries.

BACKGROUND: Data on race-and-ethnicity that are needed to measure health equity are often limited or missing. The importance of first name and sex in predicting race-and-ethnicity is not well understood. OBJECTIVE: The objective of this study was to compare the contribution of first-name information to the accuracy of basic and more complex racial-and-ethnic imputations that incorporate surname information. RESEARCH DESIGN: We imputed race-and-ethnicity in a sample of Medicare beneficiaries under 2 scenarios: (1) with only sparse predictors (name, address, sex) and (2) with a rich set (adding limited administrative race-and-ethnicity, demographics, and insurance). SUBJECTS: A total of 284,627 Medicare beneficiaries who completed the 2014 Medicare Consumer Assessment of Healthcare Providers and Systems survey and reported race-and-ethnicity were included. RESULTS: Hispanic, non-Hispanic Asian/Pacific Islander, and non-Hispanic White racial-and-ethnic imputations are more accurate for males than females under both sparse-predictor and rich-predictor scenarios; adding first-name information increases accuracy more for females than males. In contrast, imputations of non-Hispanic Black race-and-ethnicity are similarly accurate for females and males, and first names increase accuracy equally for each sex in both sparse-predictor and rich-predictor scenarios. For all 4 racial-and-ethnic groups, incorporating first-name information improves prediction accuracy more under the sparse-predictor scenario than under the rich-predictor scenario. CONCLUSION: First-name information contributes more to the accuracy of racial-and-ethnic imputations in a sparse-predictor scenario than in a rich-predictor scenario and generally narrows sex gaps in accuracy of imputations.

Validation of natural language processing to determine the presence and size of abdominal aortic aneurysms in a large integrated health system.

OBJECTIVE: Previous studies of the natural history of abdominal aortic aneurysms (AAAs) have been limited by small cohort sizes or heterogeneous analyses of pooled data. By quickly and efficiently extracting imaging data from the health records, natural language processing (NLP) has the potential to substantially improve how we study and care for patients with AAAs. The aim of the present study was to test the ability of an NLP tool to accurately identify the presence or absence of AAAs and detect the maximal abdominal aortic diameter in a large dataset of imaging study reports. METHODS: Relevant imaging study reports (n = 230,660) from 2003 to 2017 were obtained for 32,778 patients followed up in a prospective aneurysm surveillance registry within a large, diverse, integrated healthcare system. A commercially available NLP algorithm was used to assess the presence of AAAs, confirm the absence of AAAs, and extract the maximal diameter of the abdominal aorta, if stated. A blinded expert manual review of 18,000 randomly selected imaging reports was used as the reference standard. The positive predictive value (PPV or precision), sensitivity (recall), and the kappa statistics were calculated. RESULTS: Of the randomly selected 18,000 studies that underwent expert manual review, 48.7% were positive for AAAs. In confirming the presence of an AAA, the interrater reliability of the NLP compared with the expert review showed a kappa value of 0.84 (95% confidence interval [CI], 0.83-0.85), with a PPV of 95% and sensitivity of 88.5%. The NLP algorithm showed similar results for confirming the absence of an AAA, with a kappa of 0.79 (95% CI, 0.799-0.80), PPV of 77.7%, and sensitivity of 91.9%. The kappa, PPV, and sensitivity of the NLP for correctly identifying the maximal aortic diameter was 0.88 (95% CI, 0.87-0.89), 88.8%, and 88.2% respectively. CONCLUSIONS: The use of NLP software can accurately analyze large volumes of radiology report data to detect AAA disease and assemble a contemporary aortic diameter-based cohort of patients for longitudinal analysis to guide surveillance, medical management, and operative decision making. It can also potentially be used to identify from the electronic medical records pre- and postoperative AAA patients "lost to follow-up," leverage human resources engaged in the ongoing surveillance of patients with AAAs, and facilitate the construction and implementation of AAA screening programs.

Patient-Reported Care Coordination is Associated with Better Performance on Clinical Care Measures.

BACKGROUND: Prior studies using aggregated data suggest that better care coordination is associated with higher performance on measures of clinical care process; it is unclear whether this relationship reflects care coordination activities of health plans or physician practices. OBJECTIVE: Estimate within-plan relationships between beneficiary-reported care coordination measures and HEDIS measures of clinical process for the same individuals. DESIGN: Mixed-effect regression models in cross-sectional data. PARTICIPANTS: 2013 Medicare Advantage CAHPS respondents (n=152,069) with care coordination items linked to independently collected HEDIS data on clinical processes. MAIN MEASURES: Care coordination measures assessed follow-up, whether doctors had medical records during visits, whether doctors discussed medicines being taken, how informed doctors seemed about specialist care, and help received with managing care among different providers. HEDIS measures included mammography, colorectal cancer screening, cardiovascular LDL-C screening, controlling blood pressure, 5 diabetes care measures (LDL-C screening, retinal eye exam, nephropathy, blood sugar/HbA1c <9%, LCL-C<100 mg/dL), glaucoma screening in older adults, BMI assessment, osteoporosis management for women with a fracture, and rheumatoid arthritis therapy. KEY RESULTS: For 9 of the 13 HEDIS measures, within health plans, beneficiaries who reported better care coordination also received better clinical care (p<0.05) and none of the associations went in the opposite direction; HEDIS differences between those with excellent and poor coordination exceeded 5 percentage points for 7 measures. Nine measures had positive associations (breast cancer screening, colorectal cancer screening, cardiovascular care LDL-C screening, 4 of 5 diabetes care measures, osteoporosis management, and rheumatoid arthritis therapy). CONCLUSIONS: Within health plans, beneficiaries who report better care coordination also received higher-quality clinical care, particularly for care processes that entail organizing patient care activities and sharing information among different healthcare providers. These results extend prior research showing that health plans with better beneficiary-reported care coordination achieved higher HEDIS performance scores.

Predictors of Hyperkalemia and Hypokalemia in Individuals with Diabetes: a Classification and Regression Tree Analysis.

BACKGROUND: Both hyperkalemia and hypokalemia can lead to cardiac arrhythmias and are associated with increased mortality. Information on the predictors of potassium in individuals with diabetes in routine clinical practice is lacking. OBJECTIVE: To identify predictors of hyperkalemia and hypokalemia in adults with diabetes. DESIGN: Retrospective cohort study, with classification and regression tree (CART) analysis. PARTICIPANTS: 321,856 individuals with diabetes enrolled in four large integrated health care systems from 2012 to 2013. MAIN MEASURES: We used a single serum potassium result collected in 2012 or 2013. Hyperkalemia was defined as a serum potassium ≥ 5.5 mEq/L and hypokalemia as < 3.5 mEq/L. Predictors included demographic factors, laboratory measurements, comorbidities, medication use, and health care utilization. KEY RESULTS: There were 2556 hypokalemia events (0.8%) and 1517 hyperkalemia events (0.5%). In univariate analyses, we identified concordant predictors (associated with increased probability of both hyperkalemia and hypokalemia), discordant predictors, and predictors of only hyperkalemia or hypokalemia. In CART models, the hyperkalemia "tree" had 5 nodes and a c-statistic of 0.76. The nodes were defined by prior potassium results and eGFRs, and the 5 terminal "leaves" had hyperkalemia probabilities of 0.2 to 7.2%. The hypokalemia tree had 4 nodes and a c-statistic of 0.76. The hypokalemia tree included nodes defined by prior potassium results, and the 4 terminal leaves had hypokalemia probabilities of 0.3 to 17.6%. Individuals with a recent potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no hypokalemia in the previous year had a < 1% rate of either hypokalemia or hyperkalemia. CONCLUSIONS: The yield of routine serum potassium testing may be low in individuals with a recent serum potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no recent history of hypokalemia. We did not examine the effect of recent changes in clinical condition or medications on acute potassium changes.

Preoperative Vision and Surgeon Volume as Predictors of Visual Outcomes after Cataract Surgery.

PURPOSE: To evaluate the relationship between preoperative vision and surgeon volume with visual outcomes after cataract surgery. DESIGN: Retrospective cohort study. PARTICIPANTS: Patients aged ≥18 years old enrolled in the Kaiser Permanente Southern California Health Plan who underwent cataract surgery by nontrainee surgeons. METHODS: Patients who underwent cataract surgery between January 1, 2013 and December 31, 2015, were included. A multivariate analysis using Generalized Additive Mixed Models was performed to determine the relationship between surgeon volume and postoperative visual acuity after controlling for patient age, preoperative visual acuity, history of diabetes, and history of diabetic retinopathy. Modeling was done for the relationship between preoperative vision and visual outcomes while controlling for surgeon volume, patient age, history of diabetes, and history of diabetic retinopathy. MAIN OUTCOME MEASURE: Absolute letter change and percentage of patients to achieve ≥5 Early Treatment Diabetic Retinopathy Study (ETDRS) letter gain postoperatively. RESULTS: There were 103 920 cataract surgeries performed by 136 surgeons included in this analysis. Patients whose surgeons performed <91.0 surgeries/year (95% confidence interval [CI], 61.1-139; P < 0.05) gained fewer letters postoperatively than the overall average, whereas those whose surgeons performed >91 but <227 surgeries/year (95% CI, 169-∞; P < 0.05) gained more letters than average. Although statistically significant, the difference between the lowest and highest performing surgeons was approximately 1.25 letters. Surgeons who performed <110 surgeries/year (95% CI, 81.7-149; P < 0.05) had fewer patients who gained ≥5 letters. Surgeons who performed >110 but <293 surgeries/year (95% CI, 232-∞; P < 0.05) were approximately 15% more likely to have patients who gained ≥5 letters. Patients with preoperative vision <74.7 letters (95% CI, 74.7-74.8; P < 0.05) and <75.8 letters (95% CI, 75.8-75.9; P < 0.05) gained more letters and were more likely to gain ≥5 letters postoperatively, respectively. CONCLUSIONS: Patients whose vision is approximately 20/32 or worse are more likely to have significant visual gains after cataract surgery. Although statistically significant differences exist in postoperative vision based on surgeon volume, these do not appear to be clinically meaningful. Overall, visual outcomes are functionally comparable across a wide range of surgeon volumes.

Impact of Social Needs Navigation on Utilization Among High Utilizers in a Large Integrated Health System: a Quasi-experimental Study.

BACKGROUND: Programs addressing social determinants of health for high-utilizing patients are gaining interest among health systems as an avenue to promote health and decrease utilization. OBJECTIVE: To evaluate impacts of a social needs screening and navigation program for adult predicted high utilizers on total medical visit utilization. DESIGN: A prospective, quasi-experimental study using an intent-to-treat propensity-weighted difference-in-differences approach. Stratified analyses assessed intervention effects among three low-socioeconomic status sub-samples: patients in low-income areas, in low-education areas, and with Medicaid insurance. PARTICIPANTS: Predicted high utilizers-patients predicted to be in the highest 1% for total utilization in a large integrated health system. INTERVENTION: A telephonic social needs screening and navigation program. MAIN MEASURES: Primary difference-in-difference analyses compared total visit count utilization, including outpatient, emergency department (ED), and inpatient utilization, between the intervention and control groups at both in-network and out-of-network facilities. Prevalence of social needs among sample patients and their connection rates to social needs resources are also described. KEY RESULTS: The study included 34,225 patients (7107 intervention, 27,118 control). Most (53%) patients screened reported social needs, but only a minority (10%) of those with a need were able to connect with resources to address these needs. Primary analysis found total utilization visits decreased 2.2% (95% CI - 4.5%, 0.1%; p = 0.058) in the intervention group. Stratified analyses showed decreases in total utilization for all low-socioeconomic status subgroups receiving the intervention compared with controls: - 7.0% (95% CI - 11.9%, - 1.9%; p = 0.008) in the low-income area group, - 11.5% (- 17.6%, 5.0%; p < 0.001) in the low-education area group, and - 12.1% (- 18.1%, - 5.6%; p < 0.001) in the Medicaid group. CONCLUSIONS: Social needs navigation programs for high-utilizing patients may have modest effects on utilization for the population overall. However, significant decreases in utilization were found among low-socioeconomic status patients more likely to experience social needs.

How Do Gender Differences in Quality of Care Vary Across Medicare Advantage Plans?

BACKGROUND: Healthcare Effectiveness Data and Information Set (HEDIS) quality measures have long been used to compare care across health plans and to study racial/ethnic and socioeconomic disparities among Medicare Advantage (MA) beneficiaries. However, possible gender differences in seniors' quality of care have received less attention. OBJECTIVE: To test for the presence and nature of any gender differences in quality of care across MA Plans, overall and by domain; to identify those most at risk of poor care. DESIGN: Cross-sectional analysis of individual-level HEDIS measure scores from 23.8 million records using binomial mixed-effect models to estimate the effect of gender on performance. For each measure, we assess variation in gender gaps and their correlation with plan performance. PARTICIPANTS: Beneficiaries from 456 MA plans in 2011-2012 HEDIS data. MAIN MEASURES: Performance on 32 of 34 HEDIS measures which were available in both measurement years. The two excluded measures had mean performance scores below 10%. KEY RESULTS: Women experienced better quality of care than men for 22/32 measures, with most pertaining to screening or treatment. Men experienced better quality on nine measures, including four related to cardiovascular disease and three to potentially harmful drug-disease interactions. Plans varied substantially in the magnitude of gender gaps for 21/32 measures; in general, the gender gap in quality of care was least favorable to men in low-performing plans. CONCLUSIONS: Women generally experienced better quality of care than men. However, women experienced poorer care for cardiovascular disease-related intermediate outcomes and potentially harmful drug-disease interactions. Quality improvement may be especially important for men in low-performing plans and for cardiovascular-related care and drug-disease interactions for women. Gender-stratified reporting could reveal gender gaps, identify plans for which care varies by gender, and motivate efforts to address faults and close the gaps in the delivery system.

What Role Does Efficiency Play in Understanding the Relationship Between Cost and Quality in Physician Organizations?

BACKGROUND: The belief that there is inefficiency, or the potential to improve patient health at current levels of spending, is driving the push for greater value in health care. Previous studies demonstrate overuse of a narrow set of services, suggesting provider inefficiency, but existing studies neither quantify inefficiency more broadly nor assess its variation across physician organizations (POs). DATA AND METHODS: We used data on quality of care and total cost of care from 129 California POs participating in a statewide value-based pay-for-performance program. We estimated a production function with quality as the output and cost as the input, using a stochastic frontier model, to develop a measure of relative efficiency for each PO. To validate the efficiency measure, we examined correlations of PO efficiency estimates with indicators representing overuse of services. RESULTS: The estimated production function showed that PO quality was positively associated with costs, although there were diminishing marginal returns to spending. A certain minimum level of spending was associated with high quality even among efficient POs. Most strikingly, however, POs had substantial variation in efficiency, producing widely differing levels of quality for the same cost. CONCLUSIONS: Differences among POs in the efficiency with which they produce quality suggest opportunities for improvements in care delivery that increase quality without increasing spending.

Estimating causal effects for multivalued treatments: a comparison of approaches.

Interventions with multivalued treatments are common in medical and health research, such as when comparing the efficacy of competing drugs or interventions, or comparing between various doses of a particular drug. In recent years, there has been a growing interest in the development of multivalued treatment effect estimators using observational data. In this paper, we compare the performance of commonly used regression-based methods that estimate multivalued treatment effects based on the unconfoundedness assumption. These estimation methods fall into three general categories: (i) estimators based on a model for the outcome variable using conventional regression adjustment; (ii) weighted estimators based on a model for the treatment assignment; and (iii) 'doubly-robust' estimators that model both the treatment assignment and outcome variable within the same framework. We assess the performance of these models using Monte Carlo simulation and demonstrate their application with empirical data. Our results show that (i) when models estimating both the treatment and outcome are correctly specified, all adjustment methods provide similar unbiased estimates; (ii) when the outcome model is misspecified, regression adjustment performs poorly, while all the weighting methods provide unbiased estimates; (iii) when the treatment model is misspecified, methods based solely on modeling the treatment perform poorly, while regression adjustment and the doubly robust models provide unbiased estimates; and (iv) when both the treatment and outcome models are misspecified, all methods perform poorly. Given that researchers will rarely know which of the two models is misspecified, our results support the use of doubly robust estimation.

Physician-reported barriers to referring cancer patients to specialists: prevalence, factors, and association with career satisfaction.

BACKGROUND: Quality care for patients with cancer often requires access to specialty providers, but little is known about barriers to referring cancer patients for specialized care. Referral barriers may also lessen physician career satisfaction. The study was aimed at determining what factors are associated with these barriers and whether greater barriers are associated with low career satisfaction. METHODS: This cross-sectional study examined 1562 primary care physicians (PCPs) and 2144 specialists responding to the multiregional Cancer Care Outcomes Research and Surveillance Consortium physician survey. The prevalence of physician-reported barriers to referring cancer patients for more specialized care (restricted provider networks, preauthorization requirements, patient inability to pay, lack of surgical subspecialists, and excessive patient travel time) was assessed. The 5 items were averaged to calculate a barrier score. A multivariate linear regression was used to determine physician and practice setting characteristics associated with the barrier score, and a multivariate logistic regression was used to analyze the association of the barrier score with physician career satisfaction. RESULTS: Three in 5 physicians reported always, usually, or sometimes encountering any barrier to cancer patient specialty referrals. In adjusted analyses of PCPs and specialists, international medical graduates, physicians practicing in solo or government-owned practices, and physicians with <90% of their patients in managed care plans had higher barrier scores than others (P < .05). High barrier scores were associated with lower physician career satisfaction among PCPs and specialists (P < .05). CONCLUSIONS: Many physicians experience barriers to specialty referral for cancer patients. Uniform systems for providing and tracking timely referrals may enhance care and promote physician career satisfaction.

Perceptions of the appropriateness of care in California adult intensive care units.

INTRODUCTION: Increased demand for expensive intensive care unit (ICU) services may contribute to rising health-care costs. A focus on appropriate use may offer a clinically meaningful way of finding the balance. We aimed to determine the extent and characteristics of perceived inappropriate treatment among ICU doctors and nurses, defined as an imbalance between the amount or intensity of treatments being provided and the patient's expected prognosis or wishes. METHODS: This was a cross-sectional study of doctors and nurses providing care to patients in 56 adult ICUs in California between May and August 2013. In total, 1,363 doctors and nurses completed an anonymous electronic survey. RESULTS: Thirty-eight percent of 1,169 respondents (95% confidence interval (CI) 35% to 41%, 51.1% of physicians and 35.8% of nurses) identified at least one patient as receiving inappropriate treatment. Respondents most commonly reported that the amount of treatment provided was disproportionate to the patient's expected prognosis or wishes-325 out of 429 (76%, 95% CI 72% to 80%)--and that treatment was 'too much' in 93% of cases. Factors associated with perceived inappropriateness of treatment were the belief that death in their ICU is seen as a failure (odds ratio (OR) 5.75, 95% CI 2.28 to 14.53, P = 0.000), profession (doctors more than nurses) (OR 2.50, 95% CI 1.58 to 3.97, P = 0.000), lack of collaboration between doctors and nurses (OR 1.84, 95% CI 1.21 to 2.80, P = 0.004), intent to leave their job (OR 1.73, 95% CI 1.18 to 2.55, P = 0.005), and the perceived responsibility to control health-care costs (OR 1.57, 95% CI 1.05 to 2.33, P = 0.026). Providers supported formal communication training (90%, 95% CI 88% to 92%) and mandatory family meetings (89%, 95% CI 87% to 91%) as potential solutions to reduce the provision of inappropriate treatment. CONCLUSIONS: Doctors and nurses working in California ICUs frequently perceive treatment to be inappropriate. They also identified measures that could reduce the provision of inappropriate treatment.

Cardiovascular and mortality benefits of sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide 1 receptor agonists as third-step glucose-lowering medicine in patients with type 2 diabetes: a retrospective cohort analysis.

INTRODUCTION: Studies have found that sodium-glucose cotransporter 2 inhibitors (SGLT2) and glucagon-like peptide 1 receptor agonists (GLP1) have cardiovascular benefits for patients with type 2 diabetes (DM2) and atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD), or heart failure (HF). The literature does not provide evidence specifically for patients with these conditions who are adding one of these medicines to two glucose-lowering medications (ie, as "third-step" therapy). We explored the effects of different third-step medications on cardiovascular outcomes in patients with diabetes and these comorbid conditions. Specifically, we compared third-step SGLT2 or GLP1 to third-step dipeptidyl peptidase-4 inhibitors (DPP4), insulin, or thiazolidinediones (TZD). RESEARCH DESIGN AND METHODS: We assembled a retrospective cohort of adults at five Kaiser Permanente sites with DM2 and ASCVD, CKD, or HF, initiating third-step treatment between 2016 and 2020. Propensity score weighted Poisson models were used to calculate adjusted rate ratios (ARRs) for all-cause mortality, incident major adverse cardiovascular event (MACE), and incident HF hospitalization in patients initiating SGLT2 or GLP1 compared with DPP4, insulin, or TZD. RESULTS: We identified 27 542 patients initiating third-step treatment with one or more of these conditions (19 958 with ASCVD, 14 577 with CKD, and 3919 with HF). ARRs for GLP1 and SGLT2 versus DPP4, insulin, and TZD in the patient subgroups ranged between 0.22 and 0.55 for all-cause mortality, 0.38 and 0.81 for MACE, and 0.46 and 1.05 for HF hospitalization. Many ARRs were statistically significant, and all significant ARRs showed a benefit (ARR <1) for GLP1 or SGLT2 when compared with DPP4, insulin, or TZD. CONCLUSIONS: Third-step SGLT2 and GLP1 are generally associated with a benefit for these outcomes in these patient groups when compared with third-step DPP4, insulin, or TZD. Our results add to evidence of a cardiovascular benefit of SGLT2 and GLP1 and could inform clinical guidelines for choosing third-step diabetes treatment.

Reliability of evaluating hospital quality by colorectal surgical site infection type.

OBJECTIVE: To determine whether risk-adjusted colorectal SSI rates are statistically reliable as hospital quality measures. BACKGROUND: Policymakers use surgical site infections (SSI) for public reporting of hospital quality and pay-for-performance because they are a relatively common and costly cause of patient morbidity. METHODS: Patients who underwent a colorectal procedure in 2009 were identified from the American College of Surgeons National Surgical Quality Improvement Program. We developed hierarchical multivariate logistic models for (1) superficial SSI, (2) deep/organ-space SSI, and (3) "any SSI" and compared how each model ranked hospital-level risk-adjusted performance. Statistical reliability of hospital quality measurements was estimated on a scale from 0 to 1; with 0 indicating that apparent variation between a hospital's quality measurement and the average hospital is statistically unreliable, and 1 indicating that any observed variation is due to a real difference in performance. RESULTS: Mean reliability of hospital-level quality measurements was 0.650 for superficial, 0.404 for deep/organ-space, and 0.586 for "any SSI." Lower reliability was accounted for by relatively little variation in risk-adjusted SSI rates between hospitals and insufficient numbers of colorectal cases submitted by individual hospitals. In 2009, we estimate that 22.1% of all US hospitals performed a sufficient number of colorectal cases to report superficial SSI rates at a high standard of statistical reliability and 1.0% did for deep/organ-space SSI. CONCLUSIONS: As currently constructed, colorectal SSI quality measures might not meet a high standard of statistical reliability for most hospitals, limiting their ability to confidently differentiate high and low performance. Despite an expectation of improving statistical power, combining superficial and deep/organ-space SSI into an "any SSI" measure worsens reliability.

Validity and feasibility of the american college of surgeons colectomy composite outcome quality measure.

OBJECTIVE: To develop a reliable, robust, parsimonious, risk-adjusted 30-day composite colectomy outcome measure. BACKGROUND: A fundamental aspect in the pursuit of high-quality care is the development of valid and reliable performance measures in surgery. Colon resection is associated with appreciable morbidity and mortality and therefore is an ideal quality improvement target. METHODS: From 2010 American College of Surgeons National Surgical Quality Improvement Program data, patients were identified who underwent colon resection for any indication. A composite outcome of death or any serious morbidity within 30 days of the index operation was established. A 6-predictor, parsimonious model was developed and compared with a more complex model with more variables. National caseload requirements were calculated on the basis of increasing reliability thresholds. RESULTS: From 255 hospitals, 22,346 patients were accrued who underwent a colon resection in 2010, most commonly for neoplasm (46.7%). A mortality or serious morbidity event occurred in 4461 patients (20.0%). At the hospital level, the median composite event rate was 20.7% (interquartile range: 15.8%-26.3%). The parsimonious model performed similarly to the full model (Akaike information criterion: 19,411 vs 18,988), and hospital-level performance comparisons were highly correlated (R = 0.97). At a reliability threshold of 0.4, 56 annual colon resections would be required and achievable at an estimated 42% of US and 69% of American College of Surgeons National Surgical Quality Improvement Program hospitals. This 42% of US hospitals performed approximately 84% of all colon resections in the country in 2008. CONCLUSIONS: It is feasible to design a measure with a composite outcome of death or serious morbidity after colon surgery that has a low burden for data collection, has substantial clinical importance, and has acceptable reliability.

Physician cost profiling--reliability and risk of misclassification.

BACKGROUND: Insurance products with incentives for patients to choose physicians classified as offering lower-cost care on the basis of cost-profiling tools are increasingly common. However, no rigorous evaluation has been undertaken to determine whether these tools can accurately distinguish higher-cost physicians from lower-cost physicians. METHODS: We aggregated claims data for the years 2004 and 2005 from four health plans in Massachusetts. We used commercial software to construct clinically homogeneous episodes of care (e.g., treatment of diabetes, heart attack, or urinary tract infection), assigned each episode to a physician, and created a summary profile of resource use (i.e., cost) for each physician on the basis of all assigned episodes. We estimated the reliability (signal-to-noise ratio) of each physician's cost-profile score on a scale of 0 to 1, with 0 indicating that all differences in physicians' cost profiles are due to a lack of precision in the measure (noise) and 1 indicating that all differences are due to real variation in costs of services (signal). We used the reliability results to estimate the proportion of physicians in each specialty whose cost performance would be classified inaccurately in a two-tiered insurance product in which the physicians with cost profiles in the lowest quartile were labeled as "lower cost." RESULTS: Median reliabilities ranged from 0.05 for vascular surgery to 0.79 for gastroenterology and otolaryngology. Overall, 59% of physicians had cost-profile scores with reliabilities of less than 0.70, a commonly used marker of suboptimal reliability. Using our reliability results, we estimated that 22% of physicians would be misclassified in a two-tiered system. CONCLUSIONS: Current methods for profiling physicians with respect to costs of services may produce misleading results.

Evaluation of a center of excellence program for spine surgery.

BACKGROUND: The Centers for Medicare and Medicaid Services and many private health plans are encouraging patients to seek orthopedic care at hospitals designated as centers of excellence. No evaluations have been conducted to compare patient outcomes and costs at centers of excellence versus other hospitals. The objective of our study was to assess whether hospitals designated as spine surgery centers of excellence by a group of over 25 health plans provided higher quality care. METHODS: Claims representing approximately 54 million commercially insured individuals were used to identify individuals aged 18-64 years with 1 of 3 types of spine surgery in 2007-2009: 1-level or 2-level cervical fusion (referred to as cervical simple fusion), 1-level or 2-level lumbar fusion (referred to as lumbar simple fusion), or lumbar discectomy and/or decompression without fusion. The primary outcomes were any complication (7 complications were captured) and 30-day readmission. The multivariate models controlled for differences in age, sex, and comorbidities between the 2 sets of hospitals. RESULTS: A total of 29,295 cervical simple fusions, 27,214 lumbar simple fusions, and 28,911 lumbar discectomy/decompressions were identified, of which 42%, 42%, and 47%, respectively, were performed at a hospital designated as a spine surgery center of excellence. Designated hospitals had a larger number of beds and were more likely to be an academic center. Across the 3 types of spine surgery (cervical fusions, lumbar fusions, or lumbar discectomies/decompressions), there was no difference in the composite complication rate [OR 0.90 (95% CI, 0.72-1.12); OR 0.98 (95% CI, 0.85-1.13); OR 0.95 (95% CI, 0.82-1.07), respectively] or readmission rate [OR 1.03 (95% CI, 0.87-1.21); OR 1.01 (95% CI, 0.89-1.13); OR 0.91 (95%, CI 0.79-1.04), respectively] at designated hospitals compared with other hospitals. CONCLUSIONS: On average, spine surgery centers of excellence had similar complication rates and readmission rates compared with other hospitals. These results highlight the importance of empirical evaluations of centers of excellence programs.

Evaluation of centers of excellence program for knee and hip replacement.

BACKGROUND: Medicare and private plans are encouraging individuals to seek care at hospitals that are designated as centers of excellence. Few evaluations of such programs have been conducted. This study examines a large national initiative that designated hospitals as centers of excellence for knee and hip replacement. OBJECTIVE: Comparison of outcomes and costs associated with knee and hip replacement at designated hospitals and other hospitals. RESEARCH DESIGN: Retrospective claims analysis of approximately 54 million enrollees. STUDY POPULATION: Individuals with insurance from one of the sponsors of this centers of excellence program who underwent a primary knee or hip replacement in 2007-2009. OUTCOMES: Primary outcomes were any complication within 30 days of discharge and costs within 90 days after the procedure. RESULTS: A total of 80,931 patients had a knee replacement and 39,532 patients had a hip replacement of which 52.2% and 56.5%, respectively, were performed at a designated hospital. Designated hospitals had a larger number of beds and were more likely to be an academic center. Patients with a knee replacement at designated hospitals did not have a statistically significantly lower overall complication rate with an odds ratio of 0.90 (P=0.08). Patients with hip replacement treated at designated hospitals had a statistically significant lower risk of complications with an odds ratio of 0.80 (P=0.002). There was no significant difference in 90-day costs for either procedure. CONCLUSIONS: Hospitals designated as joint replacement centers of excellence had lower rates of complications for hip replacement, but there was no statistically significant difference for knee replacement. It is important to validate the criteria used to designate centers of excellence.

Impact of socioeconomic adjustment on physicians' relative cost of care.

BACKGROUND: Ongoing efforts to profile physicians on their relative cost of care have been criticized because they do not account for differences in patients' socioeconomic status (SES). The importance of SES adjustment has not been explored in cost-profiling applications that measure costs using an episode of care framework. OBJECTIVES: We assessed the relationship between SES and episode costs and the impact of adjusting for SES on physicians' relative cost rankings. RESEARCH DESIGN: We analyzed claims submitted to 3 Massachusetts commercial health plans during calendar years 2004 and 2005. We grouped patients' care into episodes, attributed episodes to individual physicians, and standardized costs for price differences across plans. We accounted for differences in physicians' case mix using indicators for episode type and a patient's severity of illness. A patient's SES was measured using an index of 6 indicators based on the zip code in which the patient lived. We estimated each physician's case mix-adjusted average episode cost and percentile rankings with and without adjustment for SES. RESULTS: Patients in the lowest SES quintile had $80 higher unadjusted episode costs, on average, than patients in the highest quintile. Nearly 70% of the variation in a physician's average episode cost was explained by case mix of their patients, whereas the contribution of SES was negligible. After adjustment for SES, only 1.1% of physicians changed relative cost rankings >2 percentiles. CONCLUSIONS: Accounting for patients' SES has little impact on physicians' relative cost rankings within an episode cost framework.