Publications by Year: 2015

PURPOSE: Researchers have found mixed results about the risk to patient safety in July, when newly minted physicians enter U.S. hospitals to begin their clinical training, the so-called "July effect." However, patient and family satisfaction and perception of physician competence during summer months remain unknown.

METHOD: The authors conducted a retrospective observational cohort study of 815 family members of adult intensive care unit (ICU) patients who completed the Family Satisfaction with Care in the Intensive Care Unit instrument from eight ICUs at Beth Israel Deaconess Medical Center, Boston, Massachusetts, between April 2008 and June 2011. The association of ICU care in the summer months (July-September) versus other seasons and family perception of physician competence was examined in univariable and multivariable analyses.

RESULTS: A greater proportion of family members described physicians as competent in summer months as compared with winter months (odds ratio [OR] 1.9; 95% confidence interval [CI] 1.2-3.0; P = .003). After adjustment for patient and proxy demographics, severity of illness, comorbidities, and features of the admission in a multivariable model, seasonal variation of family perception of physician competence persisted (summer versus winter, OR of judging physicians competent 2.4; 95% CI 1.3-4.4; P = .004).

CONCLUSIONS: Seasonal variation exists in family perception of physician competence in the ICU, but opposite to the "July effect." The reasons for this variation are not well understood. Further research is necessary to explore the role of senior provider involvement, trainee factors, system factors such as handoffs, or other possible contributors.

BACKGROUND: Differences among hospitals in the use of inpatient consultation may contribute to variation in outcomes and costs for hospitalized patients, but basic epidemiologic data on consultations nationally are lacking.

OBJECTIVE: The purpose of the study was to identify physician, hospital, and geographic factors that explain variation in rates of inpatient consultation.

DESIGN: This was a retrospective observational study.

SETTING AND PARTICIPANTS: This work included 3,118,080 admissions of Medicare patients to 4,501 U.S. hospitals in 2009 and 2010.

MAIN MEASURES: The primary outcome measured was number of consultations conducted during the hospitalization, summarized at the hospital level as the number of consultations per 1,000 Medicare admissions, or "consultation density."

KEY RESULTS: Consultations occurred 2.6 times per admission on average. Among non-critical access hospitals, use of consultation varied 3.6-fold across quintiles of hospitals (933 versus 3,390 consultations per 1,000 admissions, lowest versus highest quintiles, p < 0.001). Sicker patients received greater intensity of consultation (rate ratio [RR] 1.18, 95% CI 1.17-1.18 for patients admitted to ICU; and RR 1.19, 95% CI 1.18-1.20 for patients who died). However, even after controlling for patient-level factors, hospital characteristics also predicted differences in rates of consultation. For example, hospital size (large versus small, RR 1.31, 95% CI 1.25-1.37), rural location (rural versus urban, RR 0.78, CI 95% 0.76-0.80), ownership status (public versus not-for-profit, RR 0.94, 95% CI 0.91-0.97), and geographic quadrant (Northeast versus West, RR 1.17, 95% CI 1.12-1.21) all influenced the intensity of consultation use.

CONCLUSIONS: Hospitals exhibit marked variation in the number of consultations per admission in ways not fully explained by patient characteristics. Hospital "consultation density" may constitute an important focus for monitoring resource use for hospitals or health systems.

STUDY DESIGN: Retrospective review of medical records and administrative data.

OBJECTIVE: Validate a claims-based algorithm for classifying surgical indication and operative features in lumbar surgery.

SUMMARY OF BACKGROUND DATA: Administrative data are valuable to study rates, safety, outcomes, and costs in spine surgery. Previous research evaluates outcomes by procedure, not indications and operative features. One previous study validated a coding algorithm for classifying surgical indication. Few studies examined claims data for classifying patients by operative features.

METHODS: Patients undergoing lumbar decompression or fusion at a single institution in 2009 for back pain, herniated disc, stenosis, spondylolisthesis, or scoliosis were included. Sensitivity and specificity of a claims-based algorithm for indication and operative features were examined versus medical record abstraction.

RESULTS: A total of 477 patients, including 246 (52%) undergoing fusion and 231 (48%) undergoing decompression were included in this study. Sensitivity of the claims-based coding algorithm for classifying the indication for the procedure was 71.9% for degenerative disc disease, 81.9% for disc herniation, 32.7% for spinal stenosis, 90.4% for degenerative spondylolisthesis, and 93.8% for scoliosis. Specificity was 87.9% for degenerative disc, 85.6% for disc herniation, 90.7% for spinal stenosis, 95.0% for degenerative spondylolisthesis, and 97.3% for scoliosis. Sensitivity and specificity of claims data for identifying the type of procedure for fusion cases was 97.6% and 99.1%, respectively. Sensitivity of claims data for characterizing key operative features was 81.7%, 96.4%, and 53.0% for use of instrumentation, combined (anterior and posterior) surgical approach, and 3 or more disc levels fused, respectively. Specificity was 57.1% for instrumentation, 94.5% for combined approaches, and 71.9% for 3 or more disc levels fused.

CONCLUSION: Claims data accurately reflected certain diagnoses and type of procedures, but were less accurate at characterizing operative features other than the surgical approach. This study highlights both the potential and current limitations of claims-based analysis for spine surgery.