Abstract
Background
Identifying social determinants of health has become a priority for many researchers,
health care providers, and payers. The vast amount of patient and population-level
data available on social determinants creates, however, both an opportunity and a
challenge as these data can be difficult to synthesize and analyze.
Methods
Medicare beneficiaries who underwent 1 of 4 common operations between 2013 and 2017
were identified. Using a machine learning algorithm, the primary independent variable,
surgery social determinants of health index, was derived from 15 common, publicly
available social determents of health measures. After development of a surgery social
determinants of health index, multivariable logistic regression was used to estimate
the association of this index with textbook outcomes, as well as the component metrics
of textbook outcomes.
Results
A novel surgery social determinants of health index was developed with factor component
weights that varied relative to their impact on postoperative outcomes. Factors with
the highest weight in the algorithm relative to postoperative outcomes were the proportion
of noninstitutionalized civilians with a disability and persons without high school
diploma, while components with the lowest weights were the proportion of households
with more people than rooms and persons below poverty. Overall, an increase in surgery
social determinants of health index was associated with 6% decreased odds (95% confidence
interval: 0.93–0.94) of achieving a textbook outcome. In addition, an increase in
surgery social determinants of health index was associated with increased odds of
each of the individual components of textbook outcome; ranging from 3% increased odds
(95% confidence interval: 1.03–1.04) for 90-day readmission to 10% increased odds
(95% confidence interval: 1.09–1.11) for 90-day mortality. Further, there was 6% increased
odds (95% confidence interval: 1.05–1.07) of experiencing a complication and 7% increased
odds (95% confidence interval: 1.06–1.07) of having an extended length of stay. Minority
patients from a high surgery social determinants of health index had 38% lower odds
(95% confidence interval: 0.60–0.65) of achieving a textbook outcome compared with
White/non-Hispanic patients from a low surgery social determinants of health index
area.
Conclusion
Using a machine learning approach, we developed a novel social determents of health
index to predict the probability of achieving a textbook outcome after surgery.
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Article info
Publication history
Published online: June 14, 2022
Accepted:
May 14,
2022
Footnotes
J. Madison Hyer and Adrian Diaz share co-first authorship.
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
