Publications

BACKGROUND: In 2011, the Advisory Committee on Immunization Practices recommended hepatitis B (HepB) vaccination for previously unvaccinated adults (aged 19-59 years) with diabetes. Despite these recommendations, vaccination coverage for HepB vaccination for persons with diabetes remains low.

OBJECTIVES: The primary objective was to determine the impact of a community pharmacist-led motivational interviewing (MI) intervention on HepB vaccination initiation among adults with diabetes who were previously unvaccinated against HepB. The secondary objective was to describe HepB vaccination series completion among adults with diabetes who initiated the first dose of a HepB vaccine.

METHODS: A prospective, nonrandomized, controlled cluster trial was conducted across 58 regional grocery store chain pharmacies: a total of 29 pharmacies in the MI group and 29 pharmacies in the control group. Pharmacy location-level baseline data were collected during a 12-month pre-program period. The MI program was delivered over 10 months. Alerts were generated during prescription processing throughout the study period for eligible patients at each MI pharmacy location. The MI consisted of a face-to-face conversation between the pharmacist and the patient at the time of prescription pick-up. The difference in the primary outcome of HepB vaccination series initiation between patients receiving MI and control patients was assessed using a difference-in-differences analysis. For series completion, patients who initiated the HepB vaccination series were followed up for over 12 months after their first HepB vaccine dose.

RESULTS: There was a statistically significant 3.711% increase in HepB vaccination when comparing eligible individuals who received the MI intervention (n = 1569) to eligible individuals in the control group (n = 3640). Of the patients in the MI group who initiated HepB vaccination, 40 of 65 patients (61.5%) completed the vaccination series.

CONCLUSION: A pharmacist-led MI intervention increased HepB vaccination rates among adult patients with diabetes. Community pharmacists can effectively provide vaccinations that require multiple doses to complete the vaccination series.

Pharmacy accessibility is critical for equity in medication access and is jeopardized by pharmacy closures, which disproportionately affect independent pharmacies. We conducted a geographic information systems analysis to quantify how many individuals across the US do not have optimal pharmacy access or solely rely on independent pharmacies for access. We generated service areas of pharmacies using OpenStreetMap data. For each individual in a 30% random sample of the 2020 RTI US Household Synthetic Population™ (n=90,778,132), we defined optimal pharmacy access as having a driving distance to the closest pharmacy ≤2 miles in urban counties, ≤5 miles in suburban counties, and ≤10 miles in rural counties. Individuals were then categorized according to their access to chain and independent pharmacies. Five percent of the sample or  15.1 million individuals nationwide relied on independent pharmacies for optimal access. Individuals relying on independent pharmacies for optimal access were more likely to live in rural areas, be 65 years or older, and belong to low-income households. Another 19.5% of individuals in the sample did not have optimal pharmacy access, which corresponds to 59.0 million individuals nationwide. Our findings demonstrate that independent pharmacies play a critical role in ensuring equity in pharmacy access.

OBJECTIVE: COVID-19 has caused tremendous damage to U.S. public health, but COVID vaccines can effectively reduce the risk of COVID-19 infections and related mortality. Our study aimed to quantify the association between proximity to a community healthcare facility and COVID-19 related mortality after COVID vaccines became publicly available and explore how this association varied across racial and ethnic groups.

RESULTS: Residents living farther from a facility had higher COVID-19-related mortality across U.S. counties. This increased mortality incidence associated with longer distances was particularly pronounced in counties with higher proportions of Black and Hispanic populations.

This patient case report describes a first experience in late 2022 and early 2023 with over-the-counter (OTC) hearing aids for a 71-year-old male with self-perceived, age-related hearing loss. The patient reported no "red flag" medical conditions that would preclude him from safely using an OTC hearing aid device. After also meeting inclusionary criteria required to be printed on the device label, the patient was offered FDA registered OTC hearing aids. The first device pair was returned due to malfunction. The second device pair was an in-the-canal style, black in color, and powered by disposable batteries. He required help setting up the device from his spouse, an audiologist, and a pharmacist. Improved scores on the Self-Assessment of Communication and Significant Other Assessment of Communication were noted from the patient and his spouse. The patient continued to use the second device pair for 6 months after first use with no additional help. Our experience supports the pharmacist's role in identifying appropriate candidates for OTC hearing aids, helping patients select a device, and supporting device setup and self-fitting processes at community pharmacies. Further experiences are needed to demonstrate how pharmacists can support OTC hearing aid purchases at community pharmacies.

OBJECTIVES: Clinical decision support systems (CDSSs) are used in various aspects of healthcare to improve clinical decision-making, including in the ICU. However, there is growing evidence that CDSS are not used to their full potential, often resulting in alert fatigue which has been associated with patient harm. Clinicians in the ICU may be more vulnerable to desensitization of alerts than clinicians in less urgent parts of the hospital. We evaluated facilitators and barriers to appropriate CDSS interaction and provide methods to improve currently available CDSS in the ICU.

DESIGN: Sequential explanatory mixed-methods study design, using the BEhavior and Acceptance fRamework.

SETTING: International survey study.

PATIENT/SUBJECTS: Clinicians (pharmacists, physicians) identified via survey, with recent experience with clinical decision support.

INTERVENTIONS: An initial survey was developed to evaluate clinician perspectives on their interactions with CDSS. A subsequent in-depth interview was developed to further evaluate clinician (pharmacist, physician) beliefs and behaviors about CDSS. These interviews were then qualitatively analyzed to determine themes of facilitators and barriers with CDSS interactions.

MEASUREMENTS AND MAIN RESULTS: A total of 48 respondents completed the initial survey (estimated response rate 15.5%). The majority believed that responding to CDSS alerts was part of their job (75%) but felt they experienced alert fatigue (56.5%). In the qualitative analysis, a total of five facilitators (patient safety, ease of response, specificity, prioritization, and feedback) and four barriers (excess quantity, work environment, difficulty in response, and irrelevance) were identified from the in-depth interviews.

CONCLUSIONS: In this mixed-methods survey, we identified areas that institutions should focus on to improve appropriate clinician interactions with CDSS, specific to the ICU. Tailoring of CDSS to the ICU may lead to improvement in CDSS and subsequent improved patient safety outcomes.

Postoperative orthopedic patients are a high-risk group for receiving long-duration, large-dosage opioid prescriptions. Rigorous evaluation of state opioid duration limit laws, enacted throughout the country in response to the opioid overdose epidemic, is lacking among this high-risk group. We took advantage of Massachusetts' early implementation of a 2016 7-day-limit law that occurred before other statewide or plan-wide policies took effect and used commercial insurance claims from 2014-2017 to study its association with postoperative opioid prescriptions greater than 7 days' duration among Massachusetts orthopedic patients relative to a New Hampshire control group. Our sample included 14 097 commercially insured, opioid-naive adults aged 18 years and older undergoing elective orthopedic procedures. We found that the Massachusetts 7-day limit was associated with an immediate 4.23 percentage point absolute reduction (95% CI, 8.12 to 0.33 percentage points) and a 33.27% relative reduction (95% CI, 55.36% to 11.19%) in the percentage of initial fills greater than 7 days in the Massachusetts relative to the control group. Seven-day-limit laws may be an important state-level tool to mitigate longer duration prescribing to high-risk postoperative populations.

OBJECTIVES: To develop and validate a machine-learning algorithm to predict fatal overdose using Pennsylvania Prescription Drug Monitoring Program (PDMP) data.

METHODS: The training/testing (n = 3020,748) and validation (n = 2237,701) cohorts included Pennsylvania residents with a prescription dispensing from February 2018-September 2021. Potential predictors (n = 222) were measured in the 6 months prior to a random index date. Using a gradient boosting machine, we developed a 20-variable model to predict risk of fatal drug overdose in the 6 months after the index date.

RESULTS: Beneficiaries in the training (n = 1,812,448), testing (n = 1,208,300), and validation (n = 2,237,701) samples had similar age, with low rates of fatal overdose during 6-month follow up (0.12%, 0.12%, 0.04%, respectively). The validation c-statistic was 0.86 for predicting fatal overdose using 20 PDMP variables. When ranking individuals based on risk score, the prediction model more accurately identified fatal overdose at 6 months compared to using opioid dosage or opioid/benzodiazepine overlap, although the percentage of individuals in the highest risk percentile who died at 6 months was less than 1%.

CONCLUSIONS AND POLICY IMPLICATIONS: A gradient boosting machine algorithm predicting fatal overdose derived from twenty variables performed well in discriminating risk across testing and validation samples, improving on single factor risk measures like opioid dosage.