title: Regional density of cardiologists and rates of mortality for acute myocardial infarction and heart failure.
abstract: BACKGROUND
  Cardiologists are distributed unevenly across regions of the United States. It is unknown whether patients in regions with fewer cardiologists have worse outcomes after hospitalization for acute myocardial infarction (AMI) or heart failure (HF).
  
  
  RESULTS
  Using Medicare administrative claims data from 2010, we examined the relationship between regional density of cardiologists and risk of death after hospitalization for AMI and HF using hospitalizations for pneumonia as a comparison. We defined density as the number of cardiologists divided by population aged≥65 years within hospital referral regions, categorized into quintiles. Among 171 126 admissions for AMI, 352 853 admissions for HF, and 343 053 admissions for pneumonia, we tested associations between density of cardiologists and 30-day and 1-year mortality for each condition. We used 2-level hierarchical logistic regression models that adjusted for characteristics of patients and hospital referral regions. Patients hospitalized for AMI (odds ratios [OR], 1.13; 95% confidence interval [CI], 1.06-1.21) and HF (OR, 1.19; 95% CI, 1.12-1.27) in the lowest quintile of density had modestly higher 30-day mortality risk compared with patients in the highest quintile, unlike patients hospitalized for pneumonia (OR, 1.02; 95% CI, 0.96-1.09). Patients hospitalized for AMI (OR, 1.06; 95% CI, 1.00-1.12) and HF (OR, 1.09; 95% CI, 1.04-1.13) in the lowest quintile had slightly higher 1-year mortality risk, unlike patients hospitalized for pneumonia (OR, 1.00; 95% CI, 0.95-1.05).
  
  
  CONCLUSIONS
  Patients hospitalized for AMI and HF in regions with a low density of cardiologists experienced modestly higher 30-day and 1-year mortality risk, unlike patients with pneumonia.
authors.affiliation: Yale University School of Medicine, New Haven, CT 06510, USA.
authors.forename: Vivek T
authors.initials: VT
authors.lastname: Kulkarni
authors.forename: Joseph S
authors.initials: JS
authors.lastname: Ross
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Wang
authors.forename: Brahmajee K
authors.initials: BK
authors.lastname: Nallamothu
authors.forename: John A
authors.initials: JA
authors.lastname: Spertus
authors.forename: Sharon-Lise T
authors.initials: SL
authors.lastname: Normand
authors.forename: Frederick A
authors.initials: FA
authors.lastname: Masoudi
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002309:Cardiology; D015331:Cohort Studies; D005260:Female; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006333:Heart Failure / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D006760:Hospitalization; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D009203:Myocardial Infarction / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D016017:Odds Ratio; D010820:Physicians / Q000706:statistics & numerical data*; D011014:Pneumonia / Q000175:diagnosis / Q000401:mortality / Q000628:therapy; D011379:Prognosis; D012111:Residence Characteristics / Q000706:statistics & numerical data; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D000078329:Workforce
keywords: acute myocardial infarction; heart failure; mortality; region