Physician Time Burden Associated with Querying Prescription Drug Monitoring Programs.

Objective: Prescription drug monitoring programs (PDMPs) enable prescribers to review patient prescription histories, and their use is mandatory in many states. We estimated the cost of physicians retrieving PDMP patient reports compared with a model where a delegate (i.e., administrative staff) retrieves reports. Methods: We performed a cost analysis with a one-year time horizon, from the perspective of physicians' employers. We obtained specialty-specific estimates of controlled substance prescribing frequency from the National Ambulatory Medical Care Survey, 2012-2014. We defined three PDMP usage cases based on the frequency of queries: comprehensive (before every Schedule II-IV controlled substance prescription), selective (before new Schedule II-IV prescriptions and every six months for continuing medications), and minimal (before new Schedule II or III prescriptions and annually for continuing medications). Results: The delegate model was less costly for all specialties in the comprehensive usage case and most specialties in the selective usage case, and it was similar to physician model costs in the minimal usage case. Estimated annual costs of the physician model to a large health care system (1,000 full-time equivalent physicians) were $1.6 million for comprehensive usage, $1.1 million for selective usage, and $645,313 for minimal usage. The delegate model was less costly in the comprehensive (savings of $907,283) and selective usage cases (savings of $156,216). Conclusions: Relying on delegates vs physicians to retrieve reports is less costly in most cases. Automation and integration of PDMP data into electronic health records may reduce costs further. Physicians, health care systems, and states should collaborate to streamline access to PDMPs.

Opioid Discussion in the Twittersphere.

BACKGROUND: The rise in opioid use and overdose has increased the importance of improving data collection methods for the purpose of targeting resources to high-need populations and responding rapidly to emerging trends. OBJECTIVE: To determine whether Twitter data could be used to identify geographic differences in opioid-related discussion and whether opioid topics were significantly correlated with opioid overdose death rate. METHODS: We filtered approximately 10 billion tweets for keywords related to opioids between July 2009 and October 2015. The content of the messages was summarized into 50 topics generated using Latent Dirchlet Allocation, a machine learning analytic tool. The correlation between topic distribution and census region, census division, and opioid overdose death rate were quantified. RESULTS: We evaluated a tweet cohort of 84,023 tweets from 72,211 unique users across the US. Unique opioid-related topics were significantly correlated with different Census Bureau divisions and with opioid overdose death rates at the state and county level. Drug-related crime, language of use, and online drug purchasing emerged as themes in various Census Bureau divisions. Drug-related crime, opioid-related news, and pop culture themes were significantly correlated with county-level opioid overdose death rates, and online drug purchasing was significantly correlated with state-level opioid overdoses. CONCLUSIONS: Regional differences in opioid-related topics reflect geographic variation in the content of Twitter discussion about opioids. Analysis of Twitter data also produced topics significantly correlated with opioid overdose death rates. Ongoing analysis of Twitter data could provide a means of identifying emerging trends related to opioids.

Is there an advantage? Considerations for researchers studying the effects of the type of Medicare coverage.

OBJECTIVE: To describe common methodological problems that arise in comparisons of Medicare Advantage (MA) and Traditional Medicare (TM) and within-MA studies and provide suggestions of how researchers can address these issues. STUDY SETTING: Published research evaluating Medicare coverage options in the United States. STUDY DESIGN: We considered key conceptual challenges and promising solutions that have been used thus far and suggest additional directions. DATA COLLECTION: Not available. PRINCIPAL FINDINGS: Many existing studies of MA versus TM include significant limitations, such as failing to account for unobserved confounders driving both beneficiary coverage choice and health outcomes once enrolled, not accounting for variation in benefit generosity, provider networks, or plan design across MA plans, and/or having been conducted at a time when MA enrollment was less than a third of all Medicare beneficiaries. We provide a review of methods that can help researchers to overcome these weaknesses and suggest additional methods and data sources that may aid future research. CONCLUSIONS: The MA program is becoming an essential part of the US healthcare system. By accounting for non-random movement into and out of MA and studying the heterogeneity of beneficiary experience across plan and market characteristics, researchers can provide the high-quality evidence necessary for policymakers to design the program and reform TM in ways that maximize beneficiary outcomes.

COVID-19 unemployment and access to statin medications in the United States.

Objective: To quantify the effect of the unemployment created by COVID-19 on access to (sales of) statin drugs in the United States population. Methods: Approximately half a billion transactions for statin drugs in the United States between January 2018 and September 2020 are analyzed. We studied the potential causal relation between abnormal levels of unemployment during the first wave of COVID-19 in the U.S. and abnormal levels of sales of statin products (both variables defined at the state/week level). Variables are analyzed using the Two-Stage Least Squares (2SLS) method, which exploits comparisons of statin sales between states where, given the occupational distribution of their workforce, unemployment was more structurally vulnerable to mobility restrictions derived from COVID-19 against states where it was less structurally vulnerable. Results: While we do not find unemployment effects on statin sales on most of the population, our estimates link COVID-fueled unemployment with a sharp sales reduction among Medicaid-insured populations, particularly those in working age. For the period between March and August of 2020, these estimates imply a 31% drop of statin sales among this population. Discussion: COVID-fueled unemployment may have had a negative and significant effect on access to statin populations among Medicaid-insured populations.

Medication safety in older adults: home-based practice patterns.

OBJECTIVES: To identify the current state of medication-taking practices of community-dwelling older adults on high-risk medications. DESIGN: Telephone survey of older adults filling prescriptions for warfarin, digoxin, or phenytoin from May 2, 2002, through June 30, 2003. SETTING: The Pennsylvania Pharmacy Assistance Contract for the Elderly (PACE) Program, a state-run program providing prescription drug coverage for poor older adults. PARTICIPANTS: PACE members. MEASUREMENTS: Patients self-reported sources of information on current medications as well as home-based practices for organizing medication regimens. RESULTS: Four thousand nine hundred fifty-five PACE members were interviewed. Thirty-two percent of the sample reported that they had not received any specific instructions about their medications, 35% reported that they received instructions from their primary care provider, and 46% indicated they received them from a pharmacist. Fifty-four percent of participants indicated that they used a pillbox for organizing their medications. Older adults prescribed warfarin were more likely to report receiving instructions than those prescribed digoxin or phenytoin. CONCLUSION: A substantial proportion of older adults on high-risk medications do not recall receiving instructions for the use of their medications and do not take advantage of existing systems for organizing medication regimens. Improved patient education and delivery of medication organization systems are immediate opportunities to potentially reduce the risk of medication errors in older people.

A general model of the impact of absenteeism on employers and employees.

Most studies on the indirect costs of an illness and the cost effectiveness of a medical intervention or employer-sponsored wellness program assume that the value of reducing the number of days employees miss from work due to illness is the wage rate. This paper presents a general model to examine the magnitude and incidence of costs associated with absenteeism under alternative assumptions regarding the size of the firm, the production function, the nature of the firm's product, and the competitiveness of the labor market. We conclude that the cost of lost work time can be substantially higher than the wage when perfect substitutes are not available to replace absent workers and there is team production or a penalty associated with not meeting an output target. In the long run, workers are likely to bear much of the incidence of the costs associated with absenteeism, and therefore be the likely beneficiaries of any reduction in absenteeism.