Exploring Opioid Prescription Patterns and Overdose Rates in South Carolina (2017-2021): Insights into Rising Deaths in High-Risk Areas.

With opioid overdose rates on the rise, we aimed to develop a county-level risk stratification that specifically focused on access to medications for opioid use disorder (MOUDs) and high overdose rates. We examined over 15 million records from the South Carolina Prescription Tracking System (SCRIPTS) across 46 counties. Additionally, we incorporated data from opioid treatment programs, healthcare professionals prescribing naltrexone, clinicians with buprenorphine waivers, and county-level overdose fatality statistics. To assess the risk of opioid misuse, we classified counties into high-risk and low-risk categories based on their prescription rates, overdose fatalities, and treatment service availability. Statistical methods employed included the two-sample t-test and linear regression. The t-test assessed the differences in per capita prescription rates between high-risk and low-risk counties. Linear regression was used to analyze the trends over time. Our study showed that between 2017 and 2021, opioid prescriptions decreased from 64,223 to 41,214 per 100,000 residents, while fentanyl-related overdose deaths increased by 312%. High-risk counties had significantly higher rates of fentanyl prescriptions and relied more on out-of-state doctors. They also exhibited higher instances of doctor shopping and had fewer medical doctors per capita, with limited access to MOUDs. To effectively combat the opioid crisis, we advocate for improved local healthcare infrastructure, broader treatment access, stricter management of out-of-state prescriptions, and vigilant tracking of prescription patterns. Tailored local strategies are essential for mitigating the opioid epidemic in these communities.

In-Hospital Code Status Updates: Trends Over Time and the Impact of COVID-19.

OBJECTIVE: The primary objective was to evaluate if the percentage of patients with missing or inaccurate code status documentation at a Trauma Level 1 hospital could be reduced through daily updates. The secondary objective was to examine if patient preferences for DNR changed during the COVID-19 pandemic. METHODS: This retrospective study, spanning March 2019 to December 2022, compared the code status in ICU and ED patients drawn from two data sets. The first was based on historical electronic medical records (EHR), and the second involved daily updates of code status following patient admission. RESULTS: Implementing daily updates upon admission was more effective in ICUs than in the ED in reducing missing code status documentation. Around 20% of patients without a specific code status chose DNR under the new system. During COVID-19, a decrease in ICU patients choosing DNR and an increase in full code (FC) choices were observed. CONCLUSION: This study highlights the importance of regular updates and discussions regarding code status to enhance patient care and resource allocation in ICU and ED settings. The COVID-19 pandemic's influence on shifting patient preferences towards full code status underscores the need for adaptable documentation practices. Emphasizing patient education about DNR implications and benefits is key to supporting informed decisions that reflect individual health contexts and values. This approach will help balance the considerations for DNR and full code choices, especially during health care crises.

Evaluating State-Level Prescription Drug Monitoring Program (PDMP) and Pill Mill Effects on Opioid Consumption in Pharmaceutical Supply Chain.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study evaluates the impact of two categories of PDMP and Pill Mill regulations on the supply of opioid prescriptions at the level of dispensers and distributors (excluding manufacturers) using ARCOS data. The study uses a difference-in-difference method with a two-way fixed design to analyze the data. The study finds that both of the regulations are associated with reductions in the volume of opioid distribution. However, the study reveals that these regulations may have unintended consequences, such as shifting the distribution of controlled substances to neighboring states. For example, in Tennessee, the implementation of Operational PDMP regulations reduces the in-state distribution of opioid drugs by 3.36% (95% CI, 2.37 to 4.3), while the out-of-state distribution to Georgia, which did not have effective PDMP regulations in place, increases by 16.93% (95% CI, 16.42 to 17.44). Our studies emphasize that policymakers should consider the potential for unintended distribution shifts of opioid drugs to neighboring states with laxer regulations as well as varying impacts on different dispenser types.

The Impact of Opioid Prescribing Limits on Drug Usage in South Carolina: A Novel Geospatial and Time Series Data Analysis.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study investigates the impact of South Carolina's prescription limit law (S.C. Code Ann. 44-53-360), which aims to reduce opioid overdose deaths, on opioid prescription rates. The study utilizes South Carolina Reporting and Identification Prescription Tracking System (SCRIPTS) data and proposes a distance classification system to group records based on proximity and evaluates prescription volumes in each distance class. Prescription volumes were found to be highest in classes with pharmacies located further away from the patient. An Interrupted Time Series (ITS) model is utilized to assess the policy impact, with benzodiazepine prescriptions as a control group. The ITS models indicate an overall decrease in prescription volume, but with varying impacts across the different distance classes. While the policy effectively reduced opioid prescription volumes overall, an unintended consequence was observed as prescription volume increased in areas where prescribers were located at far distances from patients, highlighting the limitations of state-level policies on doctors. These findings contribute to the understanding of the effects of prescription limit laws on opioid prescription rates and the importance of considering location and distance in policy design and implementation.