Methods:
This is a retrospective cohort analysis of women at a single high-volume
academic institution who underwent a cesarean section and were
discharged from the hospital. This study included 1,494 women
hospitalized for cesarean delivery from July 1, 2016 to December 31,
2016 and then from January 1, 2018 to August 31, 2018, excluding women
within the one year surrounding the deadline for the NYSDOH mandated
Opioid Prescriber Training Program (January 1, 2017 to December 31,
2017). This tertiary center is in an urban area with a multilingual,
racially and ethnically diverse population. Over 80 attending
physicians, residents, and physician assistants employed by the hospital
system treated these patients.
At our institution, women routinely receive neuraxial anesthesia
(epidural and/or spinal) for cesarean delivery. In the post-operative
period, the obstetrical team manages pain, and women generally receive
multi-modal pain management including long acting narcotics, most
commonly oxycodone or Percocet (oxycodone-acetaminophen). Discharge
medications are prescribed at the individual provider’s discretion.
There are no current guidelines at our hospital for inpatient or
outpatient narcotic prescriptions. Though there is a post-Cesarean order
set in our electronic medical record system EPIC, there is no discharge
navigator or discharge order set that includes prescriptions.
The Institutional Review Board at Montefiore Medical Center, Albert
Einstein College of Medicine approved this study. We obtained
information via chart review within EPIC. Our center’s electronic
medical record system includes all outpatient and inpatient records. We
queried demographic information including age, race, ethnicity and
primary language. We then obtained all clinical and pharmacologic data,
including patient and surgery specific characteristic as well as
inpatient medications and outpatient prescriptions, directly from the
electronic medical record. The data was transferred to an electronic
database and double checked independently by two members of the research
team. If there was missing data, it was labeled as “unknown”. We used
the same electronic record to see if a narcotic was prescribed at
patient discharge, and if so, we included information on the type,
strength and number of narcotic pills prescribed. We converted all
narcotics into total morphine milligram equivalents (MME) using
conversion rates from CDC.gov to more effectively compare amounts among
the different opioids.7 We obtained this value by
converting each opioid dosage to MME and then multiplying by the number
of pills.8 The literature frequently uses this MME
conversion to compare amounts between narcotics. Our primary outcome was
total MME prescribed for outpatient use. We analyzed the total
outpatient MME prescribed at discharge before and after the mandated
NYSDOH Opioid Prescriber Training. Secondary outcomes included analyzing
outpatient opioid prescription habits by provider level as well as
identifying trends in outpatient opioid prescription patterns related to
the amount of inpatient narcotic use, and patient, surgical and
hospital-specific factors. Since this study was not focused on actual
patient use, we did not collect information on whether the prescriptions
were filled or not.
We computed descriptive statistics (frequencies, medians and
interquartile ranges) to summarize patient, surgical and
hospital-specific factors pre and post intervention, as well as across
all patients. We assessed the association between cohort (pre vs.
post-intervention) and each factor via chi-square test. In-house opioid
use was categorized as < 50, 50-100, and > 100
MME. Total amount of opioid prescribed at discharge was categorized as
0, <150, 150, and >150 MME. These categories were
chosen for the discharge prescriptions since 150 MME was the median
amount of narcotic prescribed both pre and post-intervention. In order
to examine the association between opioid prescription and patient,
surgical and hospital factors, ordinal logistic regression models were
estimated for both the pre and post-intervention periods. We examined
univariate and fully adjusted models based on a set of a prioriclinically relevant variables. Age was categorized as ≤25 years, 26-30,
31-35,36-40,41-45,46-50, and > 50. BMI was categorized as
normal (<25), overweight (25-29.99), obese 1 (30-34.99), obese
2 (35-39.99) and obese 3 (40+). Surgical time was categorized as
< 30 minutes to > 180 minutes in 30-minute
increments. Age, surgical time, and BMI were entered into the model as
ordinal variables based on the above categorization. Odds ratios (OR)
and corresponding 95% confidence limits were estimated. Two-sided
p-values less than 0.05 were considered statistically significant. All
analyses were performed in SAS version 9.4 (SAS Institute Inc., Cary
NC).