Gary E. Weissman

Physician Social Networks and Variation in Prostate Cancer Treatment in Three Cities

OBJECTIVE To examine whether physician social networks are associated with variation in treatment for men with localized prostate cancer. DATA SOURCE 2004-2005 Surveillance, Epidemiology and End Results-Medicare data from three cities. STUDY DESIGN We identified the physicians who care for patients with prostate cancer and created physician networks for each city based on shared patients. Subgroups of urologists were defined as physicians with dense connections with one another via shared patients. PRINCIPAL FINDINGS Subgroups varied widely in their unadjusted rates of prostatectomy and the racial/ethnic and socioeconomic composition of their patients. There was an association between urologist subgroup and receipt of prostatectomy. In city A, four subgroups had significantly lower odds of prostatectomy compared with the subgroup with the highest rates of prostatectomy after adjusting for patient clinical and sociodemographic characteristics. Similarly, in cities B and C, subgroups had significantly lower odds of prostatectomy compared with the baseline. CONCLUSIONS Using claims data to identify physician networks may provide an insight into the observed variation in treatment patterns for men with prostate cancer.

Patient Sharing Among Physicians and Costs of Care: A Network Analytic Approach to Care Coordination Using Claims Data

BACKGROUNDImproving care coordination is a national priority and a key focus of health care reforms. However, its measurement and ultimate achievement is challenging.OBJECTIVETo test whether patients whose providers frequently share patients with one another—what we term ‘care density’—tend to have lower costs of care and likelihood of hospitalization.DESIGNCohort studyPARTICIPANTS9,596 patients with congestive heart failure (CHF) and 52,688 with diabetes who received care during 2009. Patients were enrolled in five large, private insurance plans across the US covering employer-sponsored and Medicare Advantage enrolleesMAIN MEASURESCosts of care, rates of hospitalizationsKEY RESULTSThe average total annual health care cost for patients with CHF was

Physician Social Networks and Variation in Rates of Complications After Radical Prostatectomy

29,456, and

Intensive care unit capacity strain and adherence to prophylaxis guidelines.

14,921 for those with diabetes. In risk adjusted analyses, patients with the highest tertile of care density, indicating the highest level of overlap among a patient’s providers, had lower total costs compared to patients in the lowest tertile (

Natural Language Processing to Assess Documentation of Features of Critical Illness in Discharge Documents of Acute Respiratory Distress Syndrome Survivors

3,310 lower for CHF and

Construct validity of five sentiment analysis methods in the text of encounter notes of patients with critical illness

1,502 lower for diabetes, p < 0.001). Lower inpatient costs and rates of hospitalization were found for patients with CHF and diabetes with the highest care density. Additionally, lower outpatient costs and higher pharmacy costs were found for patients with diabetes with the highest care density.CONCLUSIONPatients treated by sets of physicians who share high numbers of patients tend to have lower costs. Future work is necessary to validate care density as a tool to evaluate care coordination and track the performance of health care systems.

A scoping review of patient-sharing network studies using administrative data

OBJECTIVES Variation in care within and across geographic areas remains poorly understood. The goal of this article was to examine whether physician social networks-as defined by shared patients-are associated with rates of complications after radical prostatectomy. METHODS In five cities, we constructed networks of physicians on the basis of their shared patients in 2004-2005 Surveillance, Epidemiology and End Results-Medicare data. From these networks, we identified subgroups of urologists who most frequently shared patients with one another. Among men with localized prostate cancer who underwent radical prostatectomy, we used multilevel analysis with generalized linear mixed-effect models to examine whether physician network structure-along with specific characteristics of the network subgroups-was associated with rates of 30-day and late urinary complications, and long-term incontinence after accounting for patient-level sociodemographic, clinical factors, and urologist patient volume. RESULTS Networks included 2677 men in five cities who underwent radical prostatectomy. The unadjusted rate of 30-day surgical complications varied across network subgroups from an 18.8 percentage-point difference in the rate of complications across network subgroups in city 1 to a 26.9 percentage-point difference in city 5. Large differences in unadjusted rates of late urinary complications and long-term incontinence across subgroups were similarly found. Network subgroup characteristics-average urologist centrality and patient racial composition-were significantly associated with rates of surgical complications. CONCLUSIONS Analysis of physician networks using Surveillance, Epidemiology and End Results-Medicare data provides insight into observed variation in rates of complications for localized prostate cancer. If validated, such approaches may be used to target future quality improvement interventions.

Eliminating Gender-Based Bias in Academic Medicine: More Than Naming the “Elephant in the Room”

PURPOSE The purpose of the study is to examine the relationship between different measures of capacity strain and adherence to prophylaxis guidelines in the intensive care unit (ICU). MATERIALS AND METHODS We conducted a retrospective cohort study within the Project IMPACT database. We used multivariable logistic regression to examine relationships between ICU capacity strain and appropriate usage of venous thromboembolism prophylaxis (VTEP) and stress ulcer prophylaxis (SUP). RESULTS Of 776,905 patient-days eligible for VTEP, appropriate therapy was provided on 68%. Strain as measured by proportion of new admissions (odds ratio [OR], 0.91; 95% confidence interval [CI], 0.90-0.91) and census (OR, 0.97; 95% CI, 0.97-0.98) was associated with decreased odds of receiving VTEP. With increasing strain as measured by new admissions, the degradation of VTEP utilization was more severe in ICUs with closed (OR, 0.85; 95% CI, 0.83-0.88) than open (OR, 0.91; 95% CI, 0.91-0.92) staffing models (interaction P<.001). Of 185425 patient-days eligible for SUP, 48% received appropriate therapy. Administration of SUP was not significantly influenced by any measure of strain. CONCLUSIONS Rising capacity strain in the ICU reduces the odds that patients will receive appropriate VTEP but not SUP. The variability among different types of ICUs in the extent to which strain degraded VTEP use suggests opportunities for systems improvement.

The Association Between Mentor-Mentee Network Features and Publication Productivity Among Early Career Academic Generalists

RATIONALE Transitions to outpatient care are crucial after critical illness, but the documentation practices in discharge documents after critical illness are unknown. OBJECTIVES To characterize the rates of documentation of various features of critical illness in discharge documents of patients diagnosed with acute respiratory distress syndrome (ARDS) during their hospital stay. METHODS We used natural language processing tools to build a keyword-based classifier that categorizes discharge documents by presence of terms from four groups of keywords related to critical illness. We used a multivariable modified Poisson regression model to infer patient- and hospital-level characteristics associated with documentation of relevant keywords. A manual chart review was used to validate the accuracy of the keyword-based classifier, and to assess for ARDS documentation during the hospital stay. MEASUREMENTS AND MAIN RESULTS Of 815 discharge documents, ARDS was identified in only 111 (13%). Mechanical ventilation was identified in 770 (92%) and intensive care unit (ICU) admission in 693 (83%) of discharge documents. Symptoms or recommendations related to post-intensive care syndrome were included in 306 (38%) of discharge documents. Patient age (older; relative risk [RR] = 0.97/yr, 95% confidence interval [CI] = 0.96-0.98) and higher PaO2:FiO2 (decreasing illness severity; RR = 0.96/10-unit increment, 95% CI = 0.93-0.98) were associated with decreased documentation of ARDS. Being discharged from a surgical (RR = 0.33, 95% CI = 0.22-0.50) compared with a medicine service was also associated with decreased rates of ARDS documentation. The manual chart review revealed 98% concordance between ARDS documentation in the discharge summary and during the hospital stay. Accuracy of the document classifier was 100% for ARDS and mechanical ventilation, 98% for ICU admission, and 95% for symptoms of post-intensive care syndrome. CONCLUSIONS In the discharge documents of survivors of ARDS, ARDS itself is rarely mentioned, but mechanical ventilation and ICU stay frequently are. The low rates of documentation of ARDS appear to be concordant with low rates of documentation during the hospital stay, consistent with known underrecognition in the ICU. Natural language processing tools can be used to effectively analyze large numbers of discharge documents of patients with critical illness.

Associations of ICU Capacity Strain with Disposition and Outcomes of Patients with Sepsis Presenting to the Emergency Department

Sentiment analysis may offer insights into patient outcomes through the subjective expressions made by clinicians in the text of encounter notes. We analyzed the predictive, concurrent, convergent, and content validity of five sentiment methods in a sample of 791,216 multidisciplinary clinical notes among 40,602 hospitalizations associated with an intensive care unit stay. None of these approaches improved early prediction of in-hospital mortality. However, positive sentiment measured by Pattern (OR 0.09, 95% Cl 0.04 – 0.17), sentimentr (OR 0.37, 95% Cl 0.25 – 0.63), and Opinion (OR 0.25, 95% Cl 0.07 – 0.89) were inversely associated with death on the concurrent day after adjustment for demographic characteristics and illness severity. Median daily lexical coverage ranged from 5.2% to 20.5%. While sentiment between all methods was positively correlated, their agreement was weak. Sentiment analysis holds promise for clinical applications, but will require a novel domain-specific method applicable to clinical text.