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Background: Fatal opioid-involved overdose rates increased precipitously from 5.0 per 100,000 population to 33.5 in Massachusetts between 1999 and 2022. Methods: We used spatial rate smoothing techniques to identify persistent opioid overdose-involved fatality clusters at the ZIP Code Tabulation Area (ZCTA) level. Rate smoothing techniques were employed to identify locations of high fatal opioid overdose rates where population counts were low. In Massachusetts, this included areas with both sparse data and low population density. We used Local Indicators of Spatial Association (LISA) cluster analyses with the raw incidence rates, and the Empirical Bayes smoothed rates to identify clusters from 2011 to 2021. We also estimated Empirical Bayes LISA cluster estimates to identify clusters during the same period. We constructed measures of the socio-built environment and potentially inappropriate prescribing using principal components analysis. The resulting measures were used as covariates in Conditional Autoregressive Bayesian models that acknowledge spatial autocorrelation to predict both, if a ZCTA was part of an opioid-involved cluster for fatal overdose rates, as well as the number of times that it was part of a cluster of high incidence rates. Results: LISA clusters for smoothed data were able to identify whether a ZCTA was part of a opioid involved fatality incidence cluster earlier in the study period, when compared to LISA clusters based on raw rates. PCA helped in identifying unique socio-environmental factors, such as minoritized populations and poverty, potentially inappropriate prescribing, access to amenities, and rurality by combining socioeconomic, built environment and prescription variables that were highly correlated with each other. In all models except for those that used raw rates to estimate whether a ZCTA was part of a high fatality cluster, opioid overdose fatality clusters in Massachusetts had high percentages of Black and Hispanic residents, and households experiencing poverty. The models that were fitted on Empirical Bayes LISA identified this phenomenon earlier in the study period than the raw rate LISA. However, all the models identified minoritized populations and poverty as significant factors in predicting the persistence of a ZCTA being part of a high opioid overdose cluster during this time period. Conclusion: Conducting spatially robust analyses may help inform policies to identify community-level risks for opioid-involved overdose deaths sooner than depending on raw incidence rates alone. The results can help inform policy makers and planners about locations of persistent risk. [ABSTRACT FROM AUTHOR]

Objective In this study, we explored key prescription drug monitoring program-related outcomes among clinicians from a broad cohort of Massachusetts healthcare facilities following prescription drug monitoring program (PDMP) and electronic health record (EHR) data integration. Methods Outcomes included seven-day rolling averages of opioids prescribed, morphine milligram equivalents (MMEs) prescribed, and PDMP queries. We employed a longitudinal study design to analyze PDMP data over a 15-month study period which allowed for six and a half months of pre- and post-integration observations surrounding a two-month integration period. We used longitudinal mixed effects models to examine the effect of EHR integration on each of the key outcomes. Results Following EHR integration, PDMP queries increased both through the web-based portal and in total (0.037, [95% CI = 0.017, 0.057] and 0.056, [95% CI = 0.035, 0.077]). Both measures of clinician opioid prescribing declined throughout the study period; however, no significant effect following EHR integration was observed. These results were consistent when our analysis was applied to a subset consisting only of continuous PDMP users. Conclusions Our results support EHR integration contributing to PDMP utilization by clinicians but do not support changes in opioid prescribing behavior. [ABSTRACT FROM AUTHOR]

Background: In 2016, Massachusetts passed the first-in-the-nation law limiting opioid naïve adults and all minors to a 7-day supply of opioids when prescribed in the outpatient setting. Objective: We hypothesized this policy would be associated with declines in the percent of opioid prescriptions with more than a 7-day supply among opioid naïve adults and minors for select prescriber groups. Methods: Interrupted time series analyses were conducted using measures from the Massachusetts Prescription Monitoring Program database for 2015 through 2017 (n = 13,672,325 opioid prescriptions; 54% to females). Outcomes were the monthly percent of opioid prescriptions greater than 7 days' supply in opioid naïve adults and in minors among select prescriber groups. Model estimates of the pre-policy trend, the average changes in the level pre/post-implementation, and the trend changes post-implementation were assessed. Results: Pre-policy trends showed significant monthly declines in the percent of opioid prescriptions greater than 7 days' supply for all prescriber groups. Policy implementation was associated with significant reduction in the level for opioid naïve adults among surgeons (−2.92%, p <.01), dentists (−0.23%, p <.01), and general medical providers (−2.22%, p =.04), and for minors among all-included prescribers (−2.97%, p <.01) and surgeons (−3.8%, p <.01). Post-implementation changes in trends were not significant except among opioid naïve adults for dentists (0.02%, p =.04). Conclusion: Within a context of significant reductions occurring in opioid prescriptions greater than 7 days' supply during this period, the Massachusetts policy was associated with further declines for opioid naïve adults and minors among select prescriber groups. [ABSTRACT FROM AUTHOR]

Background: The brand name Suboxone and its generic formulation buprenorphine/naloxone is a medication for treating opioid use disorder. While this medication has been shown to be effective, little research has examined the extent to which it is being prescribed and under what circumstances.Objective: This study examined patterns of prescription claims for buprenorphine/naloxone in terms of volume and associated clinical conditions.Methods: The study was conducted using a statewide database comprising pharmacy and medical claims that were covered by commercial health insurance plans in Massachusetts between 2011 and 2015. Trends in prescription volume for buprenorphine/naloxone were assessed based on the annual number of patients with a prescription for buprenorphine/naloxone. To examine clinical conditions associated with buprenorphine/naloxone prescriptions, patients' pharmacy claims were linked to their medical claims within the prior three months. For patients with common pain-related conditions, the odds they were prescribed buprenorphine/naloxone rather than oxycodone, a widely used opioid for pain management, were also examined.Results: The number of patients with a buprenorphine/naloxone prescription increased substantially during the study period, from approximately 25,000 in 2011 to over 39,000 in 2015. The most common clinical condition associated with buprenorphine/naloxone prescribing was opioid use disorder, but a substantial percentage of prescriptions were preceded by diagnoses that included pain or were for pain alone.Conclusion: A substantial increase in the number of patients with a prescription for buprenorphine/naloxone was observed. While buprenorphine/naloxone is most frequently prescribed for opioid use disorder, clinicians also appear to prescribe it for pain, particularly for patients who may be at elevated risk for opioid use disorder. [ABSTRACT FROM AUTHOR]

Objective. State prescription drug monitoring programs (PDMPs) can help detect individuals with multiple provider episodes (MPEs; also referred to as doctor/pharmacy shopping), an indicator of prescription drug abuse and/or diversion. Although unsolicited reporting by PDMPs to prescribers of opioid analgesics is thought to be an important practice in reducing MPEs and the potential harm associated with them, evidence of its effectiveness is mixed. This exploratory research evaluates the impact of unsolicited reports sent by Massachusetts' PDMP to the prescribers of persons with MPEs. Methods. Individuals with MPEs were identified from PDMP records between January 2010 and July 2011 as individuals having Schedule II prescriptions (at least one prescription being an opioid) from four or more distinct prescribers and four or more distinct pharmacies within six months. Based on available MA-PDMP resources, an unsolicited report containing the patient's 12-month prescription history was sent to prescribers of a subset of patients who met the MPE threshold; a comparison group closely matched on demographics and baseline prescription history, whose prescribers were not sent a report, was generated using propensity score matching. The prescription history of each group was examined for 12 months before and after the intervention. Results. There were eighty-four patients (intervention group) whose prescribers received an unsolicited report and 504 matched patients (comparison group) whose prescribers were not sent a report. Regression analyses indicated significantly greater decreases in the number of Schedule II opioid prescriptions (P< 0.01), number of prescribers visited (P< 0.01), number of pharmacies used (P< 0.01), dosage units (P< 0.01), total days' supply (P< 0.01), total morphine milligram equivalents (MME; P< 0.01), and average daily MME (P< 0.05) for the intervention group relative to the comparison group. A post hoc analysis suggested that the observed intervention effects were greater for individuals with an average daily dose of less than 100 MMEs. Conclusions. This study suggests that PDMP unsolicited reporting to prescribers can help reduce risk measures in patients' prescription histories, which may improve health outcomes for patients receiving opioid analgesics from multiple providers. [ABSTRACT FROM AUTHOR]

Looks at the Integration of Design and Construction, a graduate-level course implemented by the Department of Civil and Environmental Engineering at Worcester Polytechnic Institute (WPI) in Massachusetts. Its goals; Approaches to civil engineering education in the United States; Information on the Master Builder Program of WPI.

Introduction: In response to the opioid overdose crisis, providers were urged to taper and discontinue patients from long-term opioid therapy; however, abrupt discontinuation may lead to poor health outcomes. This study aims to determine abrupt and tapered discontinuation rates and identify the patient and provider characteristics associated with abrupt discontinuation.Methods: Data were from the Massachusetts Prescription Monitoring Program, 2015-2018. Patients discontinued from long-term opioid therapy were included in the analysis. Differences between abrupt and tapered discontinuations were identified with bivariate correlations, and variables independently associated with abrupt discontinuation were identified using multivariable Poisson regression analyses. Data were analyzed during 2019-2021.Results: In total, 277,485 patients experienced 359,320 discontinuations, of which 33.7% (n=120,964) were abrupt. Of all discontinuations, 55.7% were among female patients, and 57.9% were among patients aged >55 years. The ratio of abrupt to tapered discontinuations increased from 1:2.11 in 2015 to 1:1.75 in 2018. In bivariate analysis, prescribers with more patients receiving monthly opioid prescriptions were less likely to abruptly discontinue patients (29.0, IQR=13.9, 55.3 vs 18.8, IQR=5.84, 43.9, p<0.001), as were prescribers who wrote more monthly opioid prescriptions (36.0, IQR=16.8, 70.8 vs 25.4, IQR=7.40, 58.3, p<0.001). Multivariable results indicated that abrupt discontinuation was independently associated with male sex (RR=1.31, 95% CI=1.29, 1.1.32), younger age (RR=0.872, 95% CI=0.869, 0.874), greater distance between patient and prescriber (RR=1.0075, 95% CI=1.0072, 1.0078), and longer long-term opioid therapy duration (RR=1.021, 95% CI=1.021, 1.0122 for every month increase).Conclusions: Among all long-term opioid therapy discontinuations, abrupt discontinuation is increasing. Evidence-based approaches to managing and tapering long-term opioid therapy are urgently needed. [ABSTRACT FROM AUTHOR]

Background: Research has shown buprenorphine/naloxone to be an effective medication for treating individuals with opioid use disorder. At the same time, treatment discontinuation rates are reportedly high though much of the extant evidence comes from studies of the Medicaid population.Objectives: To examine the pattern and determinants of buprenorphine/naloxone treatment discontinuation in a population of commercially insured individuals.Research Design: We performed a retrospective observational analysis of Massachusetts All Payer Claims Data (MA APCD) covering years 2013 through 2017. We defined treatment discontinuation as a gap of 60 consecutive days without a prescription for buprenorphine/naloxone within a time frame of 24 months from the initiation of treatment. A mixed-effect Cox proportional hazard model examined the associated risk of discontinuing treatment with baseline predictors.Subjects: A total of 5134 individuals who were commercially insured during the study period.Measures: Buprenorphine/naloxone treatment discontinuation.Results: Overall 75% of individuals had discontinued treatment within two years of initiating treatment, and median time to discontinuation was 300 days. Patients aged between 18 and 24 years (HR = 1.436, 95%, CI = 1.240-1.663) and receiving treatment from prescribers with high panel-size (HR = 1.278, 95% CI = 1.112-1.468) had higher risk of discontinuing treatment. On the contrary, patients receiving treatment from multiple prescribers had lower associated risk of treatment discontinuation.Conclusions: A substantial percentage of patients discontinue treatment well before they can typically meet criteria for sustained remission. Further investigations should assess the clinical outcomes following premature discontinuation and identify strategies for retaining patients in treatment. [ABSTRACT FROM AUTHOR]

Purpose: Oral-maxillofacial surgeons (OMSs) are frequent prescribers of opioid analgesics. It remains unclear if prescription patterns differ for urban versus rural patients, given potential differences in access to and delivery of care. This study aimed to characterize urban-rural differences in opioid analgesic prescriptions to patients in Massachusetts by OMSs from 2011 to 2021., Methods: This retrospective cohort study used the Massachusetts Prescription Monitoring Program database to identify Schedule II and III opioid prescriptions by providers with specialty of oral and maxillofacial surgery from 2011 to 2021. The primary predictor variable was patient geography (urban/rural) and secondary predictor was year (2011-2021). The primary outcome variable was milligram morphine equivalent (MME) per prescription. Secondary outcome variables were days' supply per prescription and number of prescriptions received per patient. Descriptive and linear regression statistics were performed to analyze differences in prescriptions to urban and rural patients each year and throughout the study period., Results: The study data, which includes OMS opioid prescriptions (n = 1,057,412) in Massachusetts from 2011 to 2021, ranged annually between 63,678 and 116,000 prescriptions to between 58,000 and 100,000 unique patients. The cohorts each year ranged between 48 and 56% female with mean ages between 37 and 44 years. There were no differences in the mean number of patients per provider in urban and rural populations in any year. The study sample had a large majority of urban patients (>98%). MME per prescription, days' supply per prescription, and prescriptions received per patient were all generally similar between urban and rural patients each year, with the largest MME per prescription difference in 2019 (87.3 for rural to 73.9 for urban patients, P < .01). From 2011 to 2021, all patients had a steady decrease in MME per prescription (β = -6.64, 95% confidence interval: -6.81, -6.48; R 2  = 0.39) and day's supply per prescription (β = -0.1, 95% confidence interval: -0.1, -0.09; R 2  = 0.37)., Conclusion: In Massachusetts, there were similar opioid prescribing patterns by oral and maxillofacial surgeons to urban and rural patients from 2011 to 2021. There has also been a steady decrease in the duration and total dosage of opioid prescriptions to all patients. These results are consistent with multiple statewide policies over the last several years aimed at curbing opioid overprescribing., (Copyright © 2023 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.)

Objectives. To develop an imputation method to produce estimates for suppressed values within a shared government administrative data set to facilitate accurate data sharing and statistical and spatial analyses. Methods. We developed an imputation approach that incorporated known features of suppressed Massachusetts surveillance data from 2011 to 2017 to predict missing values more precisely. Our methods for 35 de-identified opioid prescription data sets combined modified previous or next substitution followed by mean imputation and a count adjustment to estimate suppressed values before sharing. We modeled 4 methods and compared the results to baseline mean imputation. Results. We assessed performance by comparing root mean squared error (RMSE), mean absolute error (MAE), and proportional variance between imputed and suppressed values. Our method outperformed mean imputation; we retained 46% of the suppressed value's proportional variance with better precision (22% lower RMSE and 26% lower MAE) than simple mean imputation. Conclusions. Our easy-to-implement imputation technique largely overcomes the adverse effects of low count value suppression with superior results to simple mean imputation. This novel method is generalizable to researchers sharing protected public health surveillance data. ( Am J Public Health . 2021; 111(10):1830-1838. https://doi.org/10.2105/AJPH.2021.306432).

The accessibility of pharmacies may be an overlooked contributor to persistent racial and ethnic disparities in the use of prescription medications and essential health care services within urban areas in the US. We examined the availability and geographic accessibility of pharmacies across neighborhoods based on their racial/ethnic composition in the thirty most populous US cities. In all cities examined, we found persistently fewer pharmacies located in Black and Hispanic/Latino neighborhoods than White or diverse neighborhoods throughout 2007-15. In 2015 there were disproportionately more pharmacy deserts in Black or Hispanic/Latino neighborhoods than in White or diverse neighborhoods, including those that are not federally designated Medically Underserved Areas. These disparities were most pronounced in Chicago, Illinois; Los Angeles, California; Baltimore, Maryland; Philadelphia, Pennsylvania; Milwaukee, Wisconsin; Dallas, Texas; Boston, Massachusetts; and Albuquerque, New Mexico. We also found that Black and Hispanic/Latino neighborhoods were more likely to experience pharmacy closures compared with other neighborhoods. Our findings suggest that efforts to increase access to medications and essential health care services, including in response to COVID-19, should consider policies that ensure equitable pharmacy accessibility across neighborhoods in US cities. Such efforts could include policies that encourage pharmacies to locate in pharmacy deserts, including increases to Medicaid and Medicare reimbursement rates for pharmacies most at risk for closure.

In the National Pilot Program on Payment Bundling, a subset of Medicare providers will receive a single payment for an episode of acute care in a hospital, followed by postacute care in a skilled nursing or rehabilitation facility, the patient's home, or other appropriate setting. This article examines the promises and pitfalls of bundled payments and addresses two important design decisions for the pilot: which conditions to include, and how long an episode should be. Our analysis of Medicare data found that hip fracture and joint replacement are good conditions to include in the pilot because they exhibit strong potential for cost savings. In addition, these conditions pose less financial risk for providers than other common ones do, so including them would make participation in the program more appealing to providers. We also found that longer episode lengths captured a higher percentage of costs and hospital readmissions while adding little financial risk. We recommend that the Medicare pilot program test alternative design features to help foster payment innovation throughout the health system.