Abstract
Background:Recurrent diverticulitis is the most common reason for elective colon surgery and, although professional societies now recommend against early resection, its use continues to rise. Shared decision making decreases use of low-value surgery but identifying which patients are most likely to elect surgery has proven difficult. We hypothesized that Machine Learning algorithms using health care utilization (HCU) data can predict future clinical events including early resection for diverticulitis.Study Design:We developed models for predicting future surgery among patients with new diagnoses of diverticulitis (2009–2012) from the MarketScan® database. Claims data (diagnosis, procedural, and drug codes) were used to train three Machine Learning algorithms to predict surgery occurring between 52 and 104 weeks following diagnosis.Results:Of 82,231 patients with incident diverticulitis (age 51 ± 8 years, 52% female), 1.2% went on to elective colon resection. Using maximal training data (152 consecutive weeks of claims), the Gradient Boosting Machine model predicted elective surgery with an area under the curve (AUC) of 75% (95% uncertainty interval [UI] 71–79%). Models trained on less data resulted in less accurate prediction (AUC: 68% [64–74%] using 128 weeks, 57% [53–63%] using 104 weeks). The majority of resections (85%) were identified as low-value.Conclusion:By applying Machine Learning to HCU data from the time around a diagnosis of diverticulitis, we predicted elective surgery weeks to months in advance, with moderate accuracy. Identifying patients who are most likely to elect surgery for diverticulitis provides an opportunity for effective shared decision making initiatives aimed at reducing the use of costly low-value care.
Highlights
Diverticular disease is common, affecting more than 50% of adults over age 60, of whom a third will go on to develop diverticulitis [1, 2]
We aimed to develop a model for predicting low-value care in diverticulitis by testing several Machine Learning algorithms
Cohort Selection We identified patients with a new diagnosis of diverticulitis using diagnosis codes (ICD-9: 562.11 & 562.13) between 2009 and 2012 who had been free from this disease during at least two years of continuous prior insurance enrollment
Summary
Diverticular disease is common, affecting more than 50% of adults over age 60, of whom a third will go on to develop diverticulitis [1, 2]. Guidelines from professional societies strongly advise against treating patients with uncomplicated diverticulitis by elective colectomy [5]. This represents a shift in guidelines away from use of surgery in most cases. Despite these recommendations, rates of elective colon resection for uncomplicated diverticulitis have continued to increase [6]. Recurrent diverticulitis is the most common reason for elective colon surgery and, professional societies recommend against early resection, its use continues to rise. Identifying patients who are most likely to elect surgery for diverticulitis provides an opportunity for effective shared decision making initiatives aimed at reducing the use of costly low-value care
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