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2 results

  • Chapter 2 - Why Measure Outcomes?

  • Kathleen E. Carberry, University of Texas at Austin
  • Book:
    How to Measure Health Outcomes
    Published online:
    27 April 2023
    Print publication:
    11 May 2023, pp 11-16

  • Summary

    This chapter discusses the four main reasons to measure outcomes: 1. measuring the change in outcomes tells you how you are doing with respect to providing health care; 2. with outcome data you can identify opportunities for learning and improvement; 3. outcome data give patients and their families critical information about what to expect when they seek care from you or your organization (or, if you work for a payer organization or employer, from the health care providers within your network); and 4. you have an ethical obligation to understand whether the care you provide is helping or harming.

  • Weight impacts 1-year congenital heart surgery outcomes independent of race/ethnicity and payer

  • Saira Siddiqui, Brett R. Anderson, Damien J. LaPar, David Kalfa, Paul Chai, Emile Bacha, Lindsay Freud
  • Journal:
    Cardiology in the Young / Volume 31 / Issue 2 / February 2021
    Published online by Cambridge University Press:
    19 November 2020, pp. 279-285

  • Body mass index, race/ethnicity, and payer status are associated with operative mortality in congenital heart disease (CHD). Interactions between these predictors and impacts on longer term outcomes are less well understood. We studied the effect of body mass index, race/ethnicity, and payer on 1-year outcomes following elective CHD surgery and tested the degree to which race/ethnicity and payer explained the effects of body mass index. Patients aged 2–25 years who underwent elective CHD surgery at our centre from 2010 to 2017 were included. We assessed 1-year unplanned cardiac re-admissions, re-interventions, and mortality. Step-wise, multivariable logistic regression was performed.

    Of the 929 patients, 10.4% were underweight, 14.9% overweight, and 8.5% obese. Non-white race/ethnicity comprised 40.4% and public insurance 29.8%. Only 0.5% died prior to hospital discharge with one additional death in the first post-operative year. Amongst patients with continuous follow-up, unplanned re-admission and re-intervention rates were 14.7% and 12.3%, respectively. In multivariable analyses adjusting for surgical complexity and surgeon, obese, overweight, and underweight patients had higher odds of re-admission than normal-weight patients (OR 1.40, p = 0.026; OR 1.77, p < 0.001; OR 1.44, p = 0.008). Underweight patients had more than twice the odds of re-intervention compared with normal weight (OR 2.12, p < 0.001). These associations persisted after adjusting for race/ethnicity, payer, and surgeon.

    Pre-operative obese, overweight, and underweight body mass index were associated with unplanned re-admission and/or re-intervention 1-year following elective CHD surgery, even after accounting for race/ethnicity and payer status. Body mass index may be an important modifiable risk factor prior to CHD surgery.