Physician Antipsychotic Overprescribing Letters and Cognitive, Behavioral, and Physical Health Outcomes Among People With Dementia: A Secondary Analysis of a Randomized Clinical Trial

Importance

Antipsychotics, such as quetiapine, are frequently prescribed to people with dementia to address behavioral symptoms but can also cause harm in this population.

Objective

To determine whether warning letters to high prescribers of quetiapine can successfully reduce its use among patients with dementia and to investigate the impacts on patients' health outcomes.

Design, Setting, and Participants

This is a secondary analysis of a randomized clinical trial of overprescribing letters that began in April 2015 and included the highest-volume primary care physician (PCP) prescribers of quetiapine in original Medicare. Outcomes of patients with dementia were analyzed in repeated 90-day cross-sections through December 2018. Analyses were conducted from September 2021 to February 2024.

Interventions

PCPs were randomized to a placebo letter or 3 overprescribing warning letters stating that their prescribing of quetiapine was high and under review by Medicare.

Main Outcomes and Measures

The primary outcome of this analysis was patients' total quetiapine use in days per 90-day period (the original trial primary outcome was total quetiapine prescribing by study PCPs). Prespecified secondary outcomes included measures of cognitive function and behavioral symptoms from nursing home assessments, indicators of depression from screening questionnaires in assessments and diagnoses in claims, metabolic diagnoses derived from assessments and claims, indicators of use of the hospital and other health care services, and death. Outcomes were analyzed separately for patients living in nursing homes and in the community.

Results

Of the 5055 study PCPs, 2528 were randomized to the placebo letter, and 2527 were randomized to the 3 warning letters. A total of 84 881 patients with dementia living in nursing homes and 261 288 community-dwelling patients with dementia were attributed to these PCPs. There were 92 874 baseline patients (mean [SD] age, 81.5 [10.5] years; 64 242 female [69.2%]). The intervention reduced quetiapine use among both nursing home patients (adjusted difference, -0.7 days; 95% CI, -1.3 to -0.1 days; P = .02) and community-dwelling patients (adjusted difference, -1.5 days; 95% CI, -1.8 to -1.1 days; P < .001). There were no detected adverse effects on cognitive function (cognitive function scale adjusted difference, 0.01; 95% CI, -0.01 to 0.03; P = .19), behavioral symptoms (agitated or reactive behavior adjusted difference, -0.2%; 95% CI -1.2% to 0.8% percentage points; P = .72), depression, metabolic diagnoses, or more severe outcomes, including hospitalization and death.

Conclusions and Relevance

This study found that overprescribing warning letters to PCPs safely reduced quetiapine prescribing to their patients with dementia. This intervention and others like it may be useful for future efforts to promote guideline-concordant care.

Trial Registration

ClinicalTrials.gov Identifier: NCT05172687.

Prescription drug monitoring program use by opioid prescribers: a cross-sectional study

Clinician use of prescription drug monitoring programs (PDMPs) has been linked to better patient outcomes, but state requirements to use PDMPs are unevenly enforced. We assessed PDMP use in Minnesota, which requires opioid prescribers to hold accounts and, in most cases, search the PDMP before prescribing, but where enforcement authority is limited. Using 2023 PDMP data, we found that 4 in 10 opioid prescribers did not search and 2 in 10 did not hold an account. PDMP use was strongly associated with prescribing volume, but even among the top decile of opioid prescribers, 8% never searched the PDMP. Thirty-two percent of opioid fills came from clinicians who did not search the PDMP. Failures to use the PDMP may be driven by a lack of information about state requirements, beliefs that these requirements are not enforced, and the costs of accessing the PDMP relative to the benefits. These results highlight the potential for policy makers to promote safer and better-informed prescribing of opioids and other drugs by addressing the forces that have limited PDMP use so far.

A Randomized Trial Of Letters To Encourage Prescription Monitoring Program Use And Safe Opioid Prescribing

To facilitate safer prescribing of opioids and other drugs, nearly all states operate prescription monitoring programs (PMPs), which collect and share data on controlled substance dispensing. Policy makers have sought to raise clinicians' engagement with these programs but lack evidence on effective interventions. Working with the Minnesota Prescription Monitoring Program, we conducted a randomized trial to assess whether letters to clinicians increased program use and decreased risky coprescribing of opioids with benzodiazepines or gabapentinoids. In March 2021 we randomly assigned 12,000 coprescribers to either a control arm or one of three study arms sent differing letters. The respective letters highlighted a new mandate to check the PMP before prescribing, provided information about coprescribing risks with a list of coprescribed patients, or contained both messages combined. Letters highlighting the mandate alone or along with coprescribing information increased PMP search rates by 4.5 and 4.0 percentage points, respectively, with no significant effect on coprescribing. These letters also increased PMP account-holding rates among clinicians. Effects persisted for at least eight months. The letter with only coprescribing information had no detected effects on key outcomes. Our results support the use of simple letter interventions as evidence-based tools to increase PMP engagement and potentially facilitate better-informed prescribing.

Technology adoption and market allocation: The case of robotic surgery

The adoption of health care technology is central to improving productivity in this sector. To provide new evidence on how technology affects health care markets, we focus on one area where adoption has been particularly rapid: surgery for prostate cancer. Within just eight years, robotic surgery grew to become the dominant intensive prostate cancer treatment method. Using a difference-in-differences design, we show that adopting a robot drives prostate cancer patients to the hospital. To test whether this result reflects market expansion or business stealing, we also consider market-level effects of adoption and find effects that are significant but smaller, suggesting that adoption expands the market while also reallocating some patients across hospitals. Marginal patients are relatively young and healthy, inconsistent with the concern that adoption broadens the criteria for intervention to patients who would gain little from it. We conclude by discussing implications for the social value of technology diffusion in health care markets.

Effect of Pharmacist Email Alerts on Concurrent Prescribing of Opioids and Benzodiazepines by Prescribers and Primary Care Managers

Question

Can pharmacist email alerts to practitioners reduce concurrent prescribing of opioids and benzodiazepines?

Findings

In this randomized clinical trial of 2237 patients coprescribed opioids and benzodiazepines and 789 practitioners who treated them, email alerts failed to detectably reduce concurrent prescribing of opioids and benzodiazepines, which can put patients at risk of overdose. The email alerts had no statistically significant effect on patient receipt of these medications or on practitioner prescribing.

Meaning

These findings suggest that alternative strategies may be more fruitful targets for efforts to make opioid prescribing safer and demonstrate that pairing randomization with quality improvement activities can generate evidence for stakeholders.

Importance

Policy makers have sought to discourage concurrent prescribing of opioids and benzodiazepines (coprescribing) because it is associated with overdose. Email alerts sent by pharmacists may reduce coprescribing, but this intervention lacks randomized evidence.

Objective

To investigate whether pharmacist emails to practitioners caring for patients who recently received opioids and benzodiazepines reduce coprescribing of these medications.

Design, Setting, and Participants

Randomized clinical trial (intention to treat) conducted in 2019-2021 of patients and their practitioners (prescribers and primary care managers) in the National Capital Region of the Military Health System. Participants were 2237 patients who were recently coprescribed opioids and benzodiazepines. These patients had 789 practitioners eligible for emails.

Interventions

Patients were randomized to email alerts to their practitioners or as-usual care. Clinical pharmacists sent the email alert. Messages were standardized and designed to facilitate coordination between practitioners, increase awareness of guidelines, and provide action steps and resources.

Main Outcomes and Measures

The primary outcomes were patients’ days received of opioids, benzodiazepines, and concurrent opioids and benzodiazepines during the 90 days following enrollment evaluated using 1-sided hypothesis tests. Secondary outcomes included total prescribing of opioids and benzodiazepines by patients’ practitioners, including to patients outside the study, to test for broader outcomes on their prescribing.

Results

Of 2237 patients, 1187 were assigned to treatment and 1050 to control; 1275 (57%) were women. Patients received a mean (SD) of 31 (44) days of opioids and 33 (34) days of benzodiazepines in the 90 days before enrollment. There were no detected differences in the primary end points, including patients’ receipt of opioids (adjusted difference, 1.1 days; 95% CI, -∞ to 3.0; P = .81), benzodiazepines (adjusted difference, −0.6 days; 95% CI, -∞ to 1.4; P = .30), and opioids and benzodiazepines together (adjusted difference, −0.1 days; 95% CI, -∞ to 0.7; P = .41). Of 789 practitioners, 429 were considered the treatment group, 325 were considered controls, and 35 were excluded. There were no detected differences in practitioners’ total prescribing of opioids, benzodiazepines, or both drug classes together.

Conclusions and Relevance

In this randomized clinical trial of pharmacist emails to practitioners, email alerts failed to detectably reduce coprescribing, highlighting the value of alternative approaches. Combining randomization with quality improvement activities may help stakeholders seeking evidence-based interventions to encourage guideline-concordant care.

Trial Registration

ClinicalTrials.gov Identifier: NCT03887247

Out of the Woodwork: Enrollment Spillovers in the Oregon Health Insurance Experiment

We analyze the impact of expanded adult Medicaid eligibility on the enrollment of already-eligible children. We analyze the 2008 Oregon Medicaid lottery, in which some low-income uninsured adults were randomly selected to be allowed to apply for Medicaid. Children in these households were eligible for Medicaid irrespective of the lottery outcome. We estimate statistically significant but transitory impacts of adult lottery selection on child Medicaid enrollment: at three months after the lottery, for every 9 adults who enrolled in Medicaid due to winning the lottery, one additional child also enrolled. Our results shed light on the existence, magnitude, and nature of so-called "woodwork effects".

Ten Rules for Conducting Retrospective Pharmacoepidemiological Analyses: Example COVID-19 Study

Since the beginning of the COVID-19 pandemic, pharmaceutical treatment hypotheses have abounded, each requiring careful evaluation. A randomized controlled trial generally provides the most credible evaluation of a treatment, but the efficiency and effectiveness of the trial depend on the existing evidence supporting the treatment. The researcher must therefore compile a body of evidence justifying the use of time and resources to further investigate a treatment hypothesis in a trial. An observational study can provide this evidence, but the lack of randomized exposure and the researcher's inability to control treatment administration and data collection introduce significant challenges. A proper analysis of observational health care data thus requires contributions from experts in a diverse set of topics ranging from epidemiology and causal analysis to relevant medical specialties and data sources. Here we summarize these contributions as 10 rules that serve as an end-to-end introduction to retrospective pharmacoepidemiological analyses of observational health care data using a running example of a hypothetical COVID-19 study. A detailed supplement presents a practical how-to guide for following each rule. When carefully designed and properly executed, a retrospective pharmacoepidemiological analysis framed around these rules will inform the decisions of whether and how to investigate a treatment hypothesis in a randomized controlled trial. This work has important implications for any future pandemic by prescribing what we can and should do while the world waits for global vaccine distribution.

Association of Quetiapine Overuse Letters With Prescribing by Physician Peers of Targeted Recipients: A Secondary Analysis of a Randomized Clinical Trial

This secondary analysis of a randomized clinical trial examines the association of antipsychotic overuse letters with changes in the prescription of quetiapine by physician peers.

Effect of Peer Comparison Letters for High-Volume Primary Care Prescribers of Quetiapine in Older and Disabled Adults: A Randomized Clinical Trial

IMPORTANCE

Antipsychotic agents, such as quetiapine fumarate, are frequently overprescribed for indications not supported by clinical evidence, potentially causing harm.

OBJECTIVE

To investigate if peer comparison letters targeting high-volume primary care prescribers of quetiapine meaningfully reduce their prescribing.

DESIGN, SETTING, AND PARTICIPANTS

Randomized clinical trial (intent to treat) conducted from 2015 to 2017 of prescribers and their patients nationwide in the Medicare program. The trial targeted the 5055 highest-volume primary care prescribers of quetiapine in 2013 and 2014 (approximately 5% of all primary care prescribers of quetiapine).

INTERVENTIONS

Prescribers were randomized (1:1 ratio) to receive a placebo letter or 3 peer comparison letters stating that their quetiapine prescribing was high relative to their peers and was under review by Medicare.

MAIN OUTCOMES AND MEASURES

The primary outcome was the total quetiapine days supplied by prescribers from the intervention start to 9 months. Secondary outcomes included quetiapine receipt from all prescribers by baseline patients, quetiapine receipt by patients with low-value or guideline-concordant indications for therapy, mortality, and hospital use. In exploratory analyses, the study followed outcomes to 2 years.

RESULTS

Of the 5055 prescribers, 231 (4.6%) were general practitioners, 2428 (48.0%) were in family medicine, and 2396 (47.4%) were in internal medicine; 4155 (82.2%) were male. All were included in the analyses. Over 9 months, the treatment arm supplied 11.1% fewer quetiapine days per prescriber vs the control arm (2456 vs 2864 days; percentage difference, 11.1% fewer days; 95% CI, -13.1% to -9.2% days; P < .001; adjusted difference, -319 days; 95% CI, -374 to -263 days; P < .001), which persisted through 2 years (15.6% fewer days; 95% CI, -18.1% to -13.0%; P < .001). At the patient level, individuals in the treatment arm received 3.9% (95% CI, -5.0% to -2.9%; P < .001) fewer days of quetiapine from all prescribers over 9 months, with a larger decrease among patients with low-value vs guideline-concordant indications (-5.9% [95% CI, -8.0% to -3.9%] vs -2.4% [95% CI, -4.0% to -0.9%], P = .01 for test that effects were equal for both patient groups). There was no evidence of substitution to other antipsychotics, and 9-month mortality and hospital use were similar between the treatment vs control arms.

CONCLUSIONS AND RELEVANCE

Peer comparison letters caused substantial and durable reductions in quetiapine prescribing, with no evidence of negative effects on patients.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02467933.

Adoption and learning across hospitals: The case of a revenue-generating practice

Performance-raising practices tend to diffuse slowly in the health care sector. To understand how incentives drive adoption, I study a practice that generates revenue for hospitals: submitting detailed documentation about patients. After a 2008 reform, hospitals could raise their Medicare revenue over 2% by always specifying a patient's type of heart failure. Hospitals only captured around half of this revenue, indicating that large frictions impeded takeup. Exploiting the fact that many doctors practice at multiple hospitals, I find that four-fifths of the dispersion in adoption reflects differences in the ability of hospitals to extract documentation from physicians. A hospital's adoption of coding is robustly correlated with its heart attack survival rate and its use of inexpensive survival-raising care. Hospital-physician integration and electronic medical records are also associated with adoption. These findings highlight the potential for institution-level frictions, including agency conflicts, to explain variations in health care performance across providers.

Medicare Letters To Curb Overprescribing Of Controlled Substances Had No Detectable Effect On Providers

Inappropriate prescribing is a rising threat to the health of Medicare beneficiaries and a drain on Medicare's finances. In this study we used a randomized controlled trial approach to evaluate a low-cost, light-touch intervention aimed at reducing the inappropriate provision of Schedule II controlled substances in the Medicare Part D program. Potential overprescribers were sent a letter explaining that their practice patterns were highly unlike those of their peers. Using rich administrative data, we were unable to detect an effect of these letters on prescribing. We describe ongoing efforts to build on this null result with alternative interventions. Learning about the potential of light-touch interventions, both effective and ineffective, will help produce a better toolkit for policy makers to improve the value and safety of health care.

Health Care Exceptionalism? Performance and Allocation in the US Health Care Sector

The conventional wisdom for the healthcare sector is that idiosyncratic features leave little scope for market forces to allocate consumers to higher performance producers. However, we find robust evidence - across several different conditions and performance measures - that higher quality hospitals have higher market shares and grow more over time. The relationship between performance and allocation is stronger among patients who have greater scope for hospital choice, suggesting that patient demand plays an important role in allocation. Our findings suggest that healthcare may have more in common with "traditional" sectors subject to market forces than often assumed.

Productivity Dispersion in Medicine and Manufacturing

The conventional wisdom in health economics is that large differences in average productivity across US hospitals are the result of idiosyncratic features of the healthcare sector which dull the role of market forces. Strikingly, however, we find that productivity dispersion in heart attack treatment across hospitals is, if anything, smaller than in narrowly defined manufacturing industries such as ready-mixed concrete. While this fact admits multiple interpretations, it suggests that healthcare may have more in common with “traditional” sectors than is often assumed, and relatedly, that insights from research on productivity and allocation in other sectors may enrich analysis of healthcare.