Protection or harm? Suppressing substance-use data

Use of Big Data and Ethical Issues for Populations With Substance Use Disorder

With expanding data availability and computing power, health research is increasingly relying on big data from a variety of sources. We describe a state-level effort to address aspects of the opioid epidemic through public health research, which has resulted in an expansive data resource combining dozens of administrative data sources in Massachusetts. The Massachusetts Public Health Data Warehouse is a public health innovation that serves as an example of how to address the complexities of balancing data privacy and access to data for public health and health services research. We discuss issues of data protection and data access, and provide recommendations for ethical data governance. Keeping these issues in mind, the use of this data resource has the potential to allow for transformative research on critical public health issues.

Perspectives on Challenges and Opportunities for Interoperability: Findings From Key Informant Interviews With Stakeholders in Ohio

BACKGROUND

Interoperability-the exchange and integration of data across the health care system-remains a challenge despite ongoing policy efforts aimed at promoting interoperability.

OBJECTIVE

This study aimed to identify current challenges and opportunities to advancing interoperability across stakeholders.

METHODS

Primary data were collected through qualitative, semistructured interviews with stakeholders (n=24) in Ohio from July to October 2021. Interviewees were sampled using a stratified purposive sample of key informants from 4 representative groups as follows: acute care and children's hospital leaders, primary care providers, behavioral health providers, and regional health information exchange networks. Interviews focused on key informant perspectives on electronic health record implementation, the alignment of public policy with organizational strategy, interoperability implementation challenges, and opportunities for health information technology. The interviews were transcribed verbatim followed by rigorous qualitative analysis using directed content analysis.

RESULTS

The findings illuminate themes related to challenges and opportunities for interoperability that align with technological (ie, implementation challenges, mismatches in interoperability capabilities across stakeholders, and opportunities to leverage new technology and integrate social determinants of health data), organizational (ie, facilitators of interoperability and strategic alignment of participation in value-based payment programs with interoperability), and environmental (ie, policy) domains.

CONCLUSIONS

Interoperability, although technically feasible for most providers, remains challenging for technological, organizational, and environmental reasons. Our findings suggest that the incorporation of end user considerations into health information technology development, implementation, policy, and standard deployment may support interoperability advancement.

A Scoping Review of Data Sources for the Conduct of Policy-Relevant Substance Use Research

OBJECTIVE

Existing administrative and survey data are critical for understanding the effects of exigent policies on population health outcomes related to opioid, cannabis, and other substance use disorders (SUDs). The objective of this study was to determine the state of the data available for evaluating SUD-related health outcomes.

METHODS

We performed a scoping review of national and state government data sources to measure and evaluate the effects of state policy changes on substance use and SUD-related health outcomes and health care use. We used Massachusetts as a case study for availability of relevant state-level data as well as national datasets with state-level indicators available to measure outcomes. We compared key features of each dataset to assess their usefulness for research and policy evaluation. We conducted our review during November 2018-March 2019, and we updated data availability as of March 2019 for all data sources.

RESULTS

We identified 11 survey datasets, 12 national administrative datasets, and 10 state administrative datasets as being suitable for policy-relevant research and practice purposes. These datasets varied substantially in their usefulness for evaluation and research. Despite substantial data limitations, including prohibitive regulatory and monetary costs to obtain the data and limited availability, these data can be mined to examine a diversity of policy-relevant questions.

CONCLUSIONS

Findings provide a comprehensive resource for using survey and administrative data to evaluate the health effects of SUD-related policies and interventions. The construction of state-level public health data warehouses or record linkage projects connecting individual-level information in state data sources is valuable for analyzing the effects of policy changes. Understanding strengths and limitations of available data sources is important for ongoing research and evaluation.

APCDs can Provide Important Insights for Surveilling the Opioid Epidemic, With Caveats

State-level all-payer claims databases (APCDs) are a possible new public health surveillance tool, but their reliability is unclear. We compared Colorado's APCD with other state-level databases for use in monitoring the opioid epidemic (Colorado Hospital Association and Colorado's Prescription Drug Monitoring Program database for 2010-2017), using descriptive analyses comparing quarterly counts/rates of opioid-involved inpatient and emergency department visits and counts/rates of 30-day opioid fills between databases. Utilization is lower in the Colorado APCD than the other databases for all outcomes but trends are parallel and consistent between databases. State APCDs hold promise for researchers, but they may be better suited to individual-level analyses or comparisons of providers than for surveillance of public health trends related to addiction.

Toolkit for detecting misused epidemiological methods

BACKGROUND

Critical knowledge of what we know about health and disease, risk factors, causation, prevention, and treatment, derives from epidemiology. Unfortunately, its methods and language can be misused and improperly applied. A repertoire of methods, techniques, arguments, and tactics are used by some people to manipulate science, usually in the service of powerful interests, and particularly those with a financial stake related to toxic agents. Such interests work to foment uncertainty, cast doubt, and mislead decision makers by seeding confusion about cause-and-effect relating to population health. We have compiled a toolkit of the methods used by those whose interests are not aligned with the public health sciences. Professional epidemiologists, as well as those who rely on their work, will thereby be more readily equipped to detect bias and flaws resulting from financial conflict-of-interest, improper study design, data collection, analysis, or interpretation, bringing greater clarity-not only to the advancement of knowledge, but, more immediately, to policy debates.

METHODS

The summary of techniques used to manipulate epidemiological findings, compiled as part of the 2020 Position Statement of the International Network for Epidemiology in Policy (INEP) entitled Conflict-of-Interest and Disclosure in Epidemiology, has been expanded and further elucidated in this commentary.

RESULTS

Some level of uncertainty is inherent in science. However, corrupted and incomplete literature contributes to confuse, foment further uncertainty, and cast doubt about the evidence under consideration. Confusion delays scientific advancement and leads to the inability of policymakers to make changes that, if enacted, would-supported by the body of valid evidence-protect, maintain, and improve public health. An accessible toolkit is provided that brings attention to the misuse of the methods of epidemiology. Its usefulness is as a compendium of what those trained in epidemiology, as well as those reviewing epidemiological studies, should identify methodologically when assessing the transparency and validity of any epidemiological inquiry, evaluation, or argument. The problems resulting from financial conflicting interests and the misuse of scientific methods, in conjunction with the strategies that can be used to safeguard public health against them, apply not only to epidemiologists, but also to other public health professionals.

CONCLUSIONS

This novel toolkit is for use in protecting the public. It is provided to assist public health professionals as gatekeepers of their respective specialty and subspecialty disciplines whose mission includes protecting, maintaining, and improving the public's health. It is intended to serve our roles as educators, reviewers, and researchers.

US Privacy Laws Go Against Public Preferences: Impeding Public Health and Research (Preprint)

Background

Reaping the benefits from massive volumes of data collected in all sectors to improve population health, inform personalized medicine, and transform biomedical research requires the delicate balance between the benefits and risks of using individual-level data. There is a patchwork of US data protection laws that vary depending on the type of data, who is using it, and their intended purpose. Differences in these laws challenge big data projects using data from different sources. The decisions to permit or restrict data uses are determined by elected officials; therefore, constituent input is critical to finding the right balance between individual privacy and public benefits.

Objective

This study explores the US public’s preferences for using identifiable data for different purposes without their consent.

Methods

We measured data use preferences of a nationally representative sample of 504 US adults by conducting a web-based survey in February 2020. The survey used a choice-based conjoint analysis. We selected choice-based conjoint attributes and levels based on 5 US data protection laws (Health Insurance Portability and Accountability Act, Family Educational Rights and Privacy Act, Privacy Act of 1974, Federal Trade Commission Act, and the Common Rule). There were 72 different combinations of attribute levels, representing different data use scenarios. Participants were given 12 pairs of data use scenarios and were asked to choose the scenario they were the most comfortable with. We then simulated the population preferences by using the hierarchical Bayes regression model using the ChoiceModelR package in R.

Results

Participants strongly preferred data reuse for public health and research than for profit-driven, marketing, or crime-detection activities. Participants also strongly preferred data use by universities or nonprofit organizations over data use by businesses and governments. Participants were fairly indifferent about the different types of data used (health, education, government, or economic data).

Conclusions

Our results show a notable incongruence between public preferences and current US data protection laws. Our findings appear to show that the US public favors data uses promoting social benefits over those promoting individual or organizational interests. This study provides strong support for continued efforts to provide safe access to useful data sets for research and public health. Policy makers should consider more robust public health and research data use exceptions to align laws with public preferences. In addition, policy makers who revise laws to enable data use for research and public health should consider more comprehensive protection mechanisms, including transparent use of data and accountability.

Association of Mental Health Disorders With Health Care Spending in the Medicare Population

IMPORTANCE

The degree to which the presence of mental health disorders is associated with additional medical spending on non-mental health conditions is largely unknown.

OBJECTIVE

To determine the proportion and degree of total spending directly associated with mental health conditions vs spending on other non-mental health conditions.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study of 4 358 975 fee-for-service Medicare beneficiaries in the US in 2015 compared spending and health care utilization among Medicare patients with serious mental illness (SMI; defined as bipolar disease, schizophrenia or related psychotic disorders, and major depressive disorder), patients with other common mental health disorders (defined as anxiety disorders, personality disorders, and posttraumatic stress disorder), and patients with no known mental health disorders. Data analysis was conducted from February to October 2019.

EXPOSURE

Diagnosis of an SMI or other common mental health disorder.

MAIN OUTCOMES AND MEASURES

Risk-adjusted, standardized spending and health care utilization. Multivariable linear regression models were used to adjust for patient characteristics, including demographic characteristics and other medical comorbidities, using hospital referral region fixed effects.

RESULTS

Of 4 358 975 Medicare beneficiaries, 987 379 (22.7%) had an SMI, 326 991 (7.5%) had another common mental health disorder, and 3 044 587 (69.8%) had no known mental illness. Compared with patients with no known mental illness, patients with an SMI were younger (mean [SD] age, 72.3 [11.6] years vs 67.4 [15.7] years; P < .001) and more likely to have dual eligibility (633 274 [20.8%] vs 434 447 [44.0%]; P < .001). Patients with an SMI incurred more mean (SE) spending on mental health services than those with other common mental health disorders or no known mental illness ($2024 [3.9] vs $343 [6.2] vs $189 [2.1], respectively; P < .001). Patients with an SMI also had substantially higher mean (SE) spending on medical services for physical conditions than those with other common mental health disorders or no known mental illness ($17 651 [23.6] vs $15 253 [38.2] vs $12 883 [12.8], respectively; P < .001), reflecting $4768 (95% CI, $4713-$4823; 37% increase) more in costs for patients with an SMI and $2370 (95% CI, $2290-$2449; 18.4% increase) more in costs for patients with other common mental health disorders. Among Medicare beneficiaries, $2 686 016 110 of $64 326 262 104 total Medicare spending (4.2%) went to mental health services and an additional $5 482 791 747 (8.5%) went to additional medical spending associated with mental illness, representing a total of 12.7% of spending associated with mental health disorders.

CONCLUSIONS AND RELEVANCE

In this study, having a mental health disorder was associated with spending substantially more on other medical conditions. These findings quantify the extent of additional spending in the Medicare fee-for-service population associated with a diagnosis of a mental health disorder.

Patient Privacy Perspectives on Health Information Exchange in a Mental Health Context: Qualitative Study

BACKGROUND

The privacy of patients with mental health conditions is prominent in health information exchange (HIE) discussions, given that their potentially sensitive personal health information (PHI) may be electronically shared for various health care purposes. Currently, the patient privacy perspective in the mental health context is not well understood because of the paucity of in-depth patient privacy research; however, the evidence suggests that patient privacy perspectives are more nuanced than what has been assumed in the academic and health care community.

OBJECTIVE

This study aimed to generate an understanding on how patients with mental health conditions feel about privacy in the context of HIE in Canada. This study also sought to identify the factors underpinning their privacy perspectives and explored how their perspectives influenced their attitudes toward HIE.

METHODS

Semistructured interviews were conducted with patients at a Canadian academic hospital for addictions and mental health. Guided by the Antecedent-Privacy Concern-Outcome macro-model, interview transcripts underwent deductive and inductive thematic analyses.

RESULTS

We interviewed 14 participants. Their privacy concerns varied, depending on the participant's privacy experiences and health care perceptions. Media reports of privacy breaches and hackers had little impact on participants' privacy concerns because of a fatalistic belief that privacy breaches are a reality in the digital age. Rather, direct observations and experiences with the mistreatment of PHI in health care settings caused concern. Decisions to trust others with PHI depended on past experiences with the individual (or institution) and health care needs. Participants had little knowledge of patient privacy rights and legislation but were willing to participate in HIE because of perceived individual and societal benefits.

CONCLUSIONS

This study introduces evidence that patients with mental health conditions would support HIE. Participants were pragmatic, supporting HIE because they wanted the best care possible. They also understood that their PHI was critical in supporting the single-payer Canadian health care system. Participant health care experiences informed their privacy perspectives, trust, and PHI sharing attitudes-all accentuating the importance of the patient experience in building trust in HIE. Their lack of knowledge about patient rights and PHI uses highlights the degree of trust they have in the health care system to protect their privacy. These findings suggest that the patient privacy discourse should extend beyond the oft-cited barrier of patient privacy concerns to include discussions about building trust, communicating the benefits of HIE, and improving patient experiences. Although our findings are in the Canadian context, this study highlights the importance of engaging patients in privacy policy discussions, regardless of jurisdiction, to ensure their nuanced perspectives are reflected in policy decisions on their PHI.

Trends in medication adherence in HIV patients in the US, 2001 to 2012: an observational cohort study

INTRODUCTION

Adherence to antiretroviral therapy (ART) is essential to reduce HIV-related morbidity and mortality as well as the risk of virological failure and HIV transmission. We determined the trends in ART adherence during the periods of therapeutic advances, wider use of ART and greater attention to ART adherence. To understand the general trends in medication adherence, we compared ART adherence with medications for other common chronic conditions.

METHODS

A retrospective cohort study using Medicaid claims between 2001 and 2012 from 14 US states with the highest HIV prevalence. Medicaid is the largest source of care for HIV patients in the US. We identified Medicaid beneficiaries with HIV who initiated ART between 2001 and 2010 (n=23,343). Comparison groups included (1) HIV- persons who initiated a statin, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker (ACEI/ARB), or metformin and (2) HIV+ persons who initiated these control medications while on and not on ART. We estimated adjusted odds of >90% medication implementation during the two years following initiation.

RESULTS

The proportion of HIV+ persons with >90% ART implementation increased from 33.5% in those who initiated in 2001 to 46.4% in 2005 and 52.4% in 2010. ART initiators in 2007 to 2010 had 53% increased odds of >90% implementation compared to those in 2001 to 2003 (adjusted OR 1.53, 99% CI: 1.34 to 1.75). Older age, male, White race, newer ART regimens and absence of substance use indicators were also associated with increased odds of >90% ART implementation. No or minimal improvements were found in the implementation of control medications in HIV- persons. For HIV- persons, the adjusted ORs comparing 2007-2010 to 2001-2003 were 1.06, 1.01 and 1.19 for statins, ACEI/ARB, metformin respectively. HIV+ persons who were on ART had, on average, 15.0 (SD: 4.2) and 16.1 (SD: 3.4) percentage points higher >90% implementation rates of concurrent statins, ACEI/ARB or metformin compared to HIV- persons and HIV+ persons who were not on ART respectively.

CONCLUSIONS

Adherence to ART substantially improved between 2001 and 2012. Nevertheless, the absolute rates of >90% implementation were low for all groups examined. Substantial disparities by age, sex and race were present, drawing attention to the need to continue to enhance medication adherence. Further studies are required to examine whether these trends and disparities persist in the most recent period.

Effect of Integrating Substance Use Disorder Treatment into Primary Care on Inpatient and Emergency Department Utilization

BACKGROUND

Components of substance use disorder (SUD) treatment have been shown to reduce inpatient and emergency department (ED) utilization. However, integrated treatment using pharmacotherapy and recovery coaches in primary care has not been studied.

OBJECTIVE

To determine whether integrated addiction treatment in primary care reduces inpatient and ED utilization and improves outpatient engagement.

DESIGN

A retrospective cohort study comparing patients in practices with and without integrated addiction treatment including pharmacotherapy and recovery coaching during a staggered roll-out period.

PARTICIPANTS

A propensity score matched sample of 2706 adult primary care patients (1353 matched pairs from intervention and control practices) with a SUD diagnosis code, excluding cannabis or tobacco only, matched on baseline utilization.

INTERVENTION

A multi-modal strategy that included forming interdisciplinary teams of local champions, access to addiction pharmacotherapy, counseling, and recovery coaching. Control practices could refer patients to an addiction treatment clinic offering pharmacotherapy and behavioral interventions.

MAIN MEASURES

The number of inpatient admissions, hospital bed days, ED visits, and primary care visits.

KEY RESULTS

During the follow-up period, there were fewer inpatient days among the intervention group (997 vs. 1096 days with a mean difference of 7.3 days per 100 patients, p = 0.03). The mean number of ED visits was lower for the intervention group (36.2 visits vs. 42.9 per 100 patients, p = 0.005). There was no difference in the mean number of hospitalizations. The mean number of primary care visits was higher for the intervention group (317 visits vs. 270 visits per 100 patients, p < 0.001). Intervention practices had a greater increase in buprenorphine and naltrexone prescribing.

CONCLUSIONS

In a non-randomized retrospective cohort study, integrated addiction pharmacotherapy and recovery coaching in primary care resulted in fewer hospital days and ED visits for patients with SUD compared to similarly matched patients receiving care in practices without these services.

The importance of identification when measuring performance in addiction treatment

Background: Identifying and effectively treating individuals with substance use disorders (SUDs) is an important priority for state Medicaid programs, given the enormous toll that SUDs take on individuals, their families, and their communities. In this paper, we describe how the Healthcare Effectiveness Data and Information Set (HEDIS) measure "Identification of Alcohol and Other Drug Services" can be used, along with eligible population prevalence rates, to expand states' ability to track how well their Medicaid programs identify enrollees with SUDs and link them with treatment (measured by initiation and engagement performance measures). Methods: We use the 2009 Medicaid MAX data on utilization and enrollment along with information from the National Survey of Drug Use and Health (NSDUH) to obtain state-level estimates of alcohol and drug abuse and dependence among Medicaid beneficiaries for 7 illustrative states. We calculate identification, initiation, and engagement measures using specifications from the National Committee on Quality Assurance (NCQA). Results: NSDUH data showed that the eligible population prevalence rate (the average rate of alcohol or drug abuse or dependence) among the 7 states was 10.0%, whereas the average identification rate was 2.9%. The gap between the prevalence and identification rates ranged from 5.1% to 11.0% among the 7 states. The initiation rates ranged from 36.9% to 57.1%. The states' engagement rates ranged from 11.8% to 31.1%, although rates differ by age, gender, and race/ethnicity in some states. Conclusion: Including identification along with initiation and engagement measures allows states to determine how well they are performing in a more complete spectrum from need, to recognition and documentation of enrollees with SUDs, to initiation of treatment, to continuation of early treatment.

Association of Team-Based Primary Care With Health Care Utilization and Costs Among Chronically Ill Patients

IMPORTANCE

Empirical study findings to date are mixed on the association between team-based primary care initiatives and health care use and costs for Medicaid and commercially insured patients, especially those with multiple chronic conditions.

OBJECTIVE

To evaluate the association of establishing team-based primary care with patient health care use and costs.

DESIGN, SETTING, AND PARTICIPANTS

We used difference-in-differences to compare preutilization and postutilization rates between intervention and comparison practices with inverse probability weighting to balance observable differences. We fit a linear model using generalized estimating equations to adjust for clustering at 18 academically affiliated primary care practices in the Boston, Massachusetts, area between 2011 and 2015. The study included 83 953 patients accounting for 138 113 patient-years across 18 intervention practices and 238 455 patients accounting for 401 573 patient-years across 76 comparison practices. Data were analyzed between April and August 2018.

EXPOSURES

Practices participated in a 4-year learning collaborative that created and supported team-based primary care.

MAIN OUTCOMES AND MEASURES

Outpatient visits, hospitalizations, emergency department visits, ambulatory care-sensitive hospitalizations, ambulatory care-sensitive emergency department visits, and total costs of care.

RESULTS

Of 322 408 participants, 176 259 (54.7%) were female; 64 030 (19.9%) were younger than 18 years and 258 378 (80.1%) were age 19 to 64 years. Intervention practices had fewer participants, with 2 or more chronic conditions (n = 51 155 [37.0%] vs n = 186 954 [46.6%]), more participants younger than 18 years (n = 337 931 [27.5%] vs n = 74 691 [18.6%]), higher Medicaid enrollment (n = 39 541 [28.6%] vs n = 81 417 [20.3%]), and similar sex distributions (75 023 women [54.4%] vs 220 097 women [54.8%]); however, after inverse probability weighting, observable patient characteristics were well balanced. Intervention practices had higher utilization in the preperiod. Patients in intervention practices experienced a 7.4% increase in annual outpatient visits relative to baseline (95% CI, 3.5%-11.3%; P < .001) after adjusting for patient age, sex, comorbidity, zip code level sociodemographic characteristics, clinician characteristics, and plan fixed effects. In a subsample of patients with 2 or more chronic conditions, there was a statistically significant 18.6% reduction in hospitalizations (95% CI, 1.5%-33.0%; P = .03), 25.2% reduction in emergency department visits (95% CI, 6.6%-44.0%; P = .007), and a 36.7% reduction in ambulatory care-sensitive emergency department visits (95% CI, 9.2%-64.0%; P = .009). Among patients with less than 2 comorbidities, there was an increase in outpatient visits (9.2%; 95% CI, 5.10%-13.10%; P < .001), hospitalizations (36.2%; 95% CI, 12.2-566.6; P = .003), and ambulatory care-sensitive hospitalizations (50.6%; 95% CI, 7.1%-329.2%; P = .02).

CONCLUSIONS AND RELEVANCE

While establishing team-based care was not associated with differences in the full patient sample, there were substantial reductions in utilization among a subset of chronically ill patients. Team-based care practice transformation in primary care settings may be a valuable tool in improving the care of sicker patients, thereby reducing avoidable use; however, it may lead to greater use among healthier patients.

The high burden of alcoholic cirrhosis in privately insured persons in the United States

Alcoholic cirrhosis (AC) is a major cause of liver-related morbidity and mortality in the United States. Rising rates of alcohol use disorders in the United States will likely result in more alcoholic liver disease. Our aim was to determine the prevalence, health care use, and costs of AC among privately insured persons in the United States. We collected data from persons aged 18-64 with AC (identified by codes from the International Classification of Diseases, Ninth and Tenth Revisions) enrolled in the Truven MarketScan Commercial Claims and Encounters database (2009-2015). We determined yearly prevalence, weighted to the national employer-sponsored, privately insured population. Using competing risk analysis, we estimated event rates for portal hypertensive complications and estimated the association between AC and costs as well as admissions and readmissions. In 2015, 294,215 people had cirrhosis and 105,871 (36%) had AC. Mean age at AC diagnosis was 53.5 years, and 32% were women. Over the 7 years queried, estimated national cirrhosis prevalence rose from 0.19% to 0.27% (P < 0.001) and for AC from 0.07% to 0.10% (P < 0.001). Compared to non-AC, AC enrollees were significantly more likely to have portal hypertensive complications at diagnosis and higher yearly cirrhosis and alcohol-related admissions (25 excess cirrhosis admissions and 6.3 excess alcohol-related admissions per 100 enrollees) as well as all-cause readmissions. Per-person costs in the first year after diagnosis nearly doubled for AC versus non-AC persons (US$ 44,835 versus 23,319).

CONCLUSION

In a nationally representative cohort of privately insured persons, AC enrollees were disproportionately sicker at presentation, were admitted and readmitted more often, and incurred nearly double the per-person health care costs compared to those with non-AC. (Hepatology 2018).

A population-based examination of trends and disparities in medication treatment for opioid use disorders among Medicaid enrollees

BACKGROUND

Medication treatment (MT) with methadone and buprenorphine are effective treatments for opioid use disorders, but little information is available regarding the extent to which buprenorphine's approval resulted in more individuals receiving MT nor to what extent receipt of such treatment was equitable across communities.

METHODS

To examine changes in MT utilization and the association between MT utilization and county-level indicators of poverty, race/ethnicity, and urbanicity, we used Medicaid claims of non-dually eligible Medicaid enrollees aged 18-64 from 14 states for 2002-2009. We generated county-level aggregate counts of MT (methadone, buprenorphine, and any MT) by year (N = 7760 county-years). We estimated count data models to identify associations between MT and county characteristics, including levels of poverty and racial/ethnic concentration.

RESULTS

The number of Medicaid enrollees receiving MT increased 62% from 2002 to 2009. The number of enrollees receiving methadone increased 20%, with the remaining increase resulting from buprenorphine. Urban county residents were significantly more likely to receive MT in both 2002 and 2009 than rural county residents. However, buprenorphine substantially increased MT in rural counties from 2002 to 2009. Receipt of MT increased at a much higher rate for residents of counties with lower poverty rates and lower concentrations of black and Hispanic individuals than for residents of counties without those characteristics.

CONCLUSIONS

The increase in Medicaid enrollees receiving MT in the years following buprenorphine's approval is encouraging. However, it is concerning that MT trends varied so dramatically by characteristics of the county population and that increases in utilization were substantially lower in counties with populations that historically have been disadvantaged with respect to health care access and quality. Concerted efforts are needed to ensure that MT benefits are equitably distributed across society and reach disadvantaged individuals who may be at higher risk of experiencing opioid use disorders.

Long-Term Implications Of A Short-Term Policy: Redacting Substance Abuse Data

From 2013 to 2017 the Centers for Medicare and Medicaid Services redacted Medicare claims that included diagnosis or procedure codes related to substance abuse. The redaction policy was in effect as the Affordable Care Act and the opioid epidemic changed the health care landscape. The policy substantially altered prevalence estimates of common chronic conditions that co-occur with substance abuse.

Using prescription claims to detect aberrant behaviors with opioids: comparison and validation of 5 algorithms

OBJECTIVE

Compare and validate 5 algorithms to detect aberrant behavior with opioids: Opioid Misuse Score, Controlled Substance-Patterns of Utilization Requiring Evaluation (CS-PURE), Overutilization Monitoring System, Katz, and Cepeda algorithms.

STUDY DESIGN AND SETTING

We identified new prescription opioid users from 2 insurance databases: Medicaid (2000-2006) and Clinformatics Data Mart (CDM; 2004-2013). Patients were followed 1 year, and aberrant opioid behavior was defined according to each algorithm, using Cohen's kappa to assess agreement. Risk differences were calculated comparing risk of opioid-related adverse events for identified aberrant and nonaberrant users.

RESULTS

About 3.8 million Medicaid and 4.3 million CDM patients initiated prescription opioid use. Algorithms flagged potential aberrant behavior in 0.02% to 12.8% of initiators in Medicaid and 0.01% to 7.9% of initiators in CDM. Cohen's kappa values were poor to moderate (0.00 to 0.50 in Medicaid; 0.00 to 0.30 in CDM). Algorithms varied substantially in their ability to predict opioid-related adverse events; the Overutilization Monitoring System had the highest risk differences between aberrant and nonaberrant users (14.0% in Medicaid; 13.4% in CDM), and the Katz algorithm had the lowest (0.96% in Medicaid; 0.47% in CDM).

CONCLUSIONS

In 2 large databases, algorithms applied to prescription data had varying accuracy in identifying increased risk of adverse opioid-related events.

Are trends in billing for high-intensity emergency care explained by changes in services provided in the emergency department? An observational study among US Medicare beneficiaries

OBJECTIVE

There has been concern that an increase in billing for high-intensity emergency care is due to changes in coding practices facilitated by electronic health records. We sought to characterise the trends in billing for high-intensity emergency care among Medicare beneficiaries and to examine the degree to which trends in high-intensity billing are explained by changes in patient characteristics and services provided in the emergency department (ED).

DESIGN, SETTING AND PARTICIPANTS

Observational study using traditional Medicare claims to identify ED visits at non-federal acute care hospitals for elderly beneficiaries in 2006, 2009 and 2012.

OUTCOMES MEASURES

Billing intensity was defined by emergency physician evaluation and management (E&M) codes. We tested for overall trends in high-intensity billing (E&M codes 99285, 99291 and 99292) and in services provided over time using linear regression models, adjusting for patient characteristics. Additionally, we tested for time trends in rates of admission to the hospital and to the intensive care unit (ICU). Next, we classified outpatient visits into 39 diagnosis categories and analysed the change in proportion of high-intensity visits versus the change in number of services. Finally, we quantified the extent to which trends in high-intensity billing are explained by changes in patient demographics and services provided in the ED using multivariable modelling.

RESULTS

High-intensity visits grew from 45.8% of 671 103 visits in 2006 to 57.8% of 629 010 visits in 2012 (2.0% absolute increase per year; 95% CI 1.97% to 2.03%) as did the mean number of services provided for admitted (1.28 to 1.41; +0.02 increase in procedures per year; 95% CI 0.018 to 0.021) and discharged ED patients (7.1 to 8.6; +0.25 increase in services per year; 95% CI 0.245 to 0.255). There was a reduction in hospital admission rate from 40.1% to 35.9% (-0.68% per year; 95% CI -0.71% to -0.65%; P<0.001), while the ICU rate of admission rose from 11.7% to 12.3% (+0.11% per year; 95% CI 0.09% to 0.12%; P<0.001). When we stratified by diagnosis category, there was a moderate correlation between change in visits billed as high intensity and the change in mean number of services provided per visit (r=0.38; 95% CI 0.07 to 0.63). Trends in patient characteristics and services provided accounted moderately for the trend in practice intensity for outpatient visits (pseudo R² of 0.47) but very little for inpatient visits (0.051) and visits overall (0.148).

CONCLUSIONS

Increases in services provided in the ED moderately account for the trends in billing for high-intensity emergency care for outpatient visits.

Effect of a high dosage opioid prior authorization policy on prescription opioid use, misuse, and overdose outcomes

BACKGROUND

High dosage opioid use is a risk factor for opioid-related overdose commonly cited in guidelines, recommendations, and policies. In 2012, the Oregon Medicaid program developed a prior authorization policy for opioid prescriptions above 120 mg per day morphine equivalent dose (MED). This study aimed to evaluate the effects of that policy on utilization, prescribing patterns, and health outcomes.

METHODS

Using administrative claims data from Oregon and a control state (Colorado) between 2011 and 2013, we used difference-in-differences analyses to examine changes in utilization, measures of high risk opioid use, and overdose after introduction of the policy. We also evaluated opioid utilization in a cohort of individuals who were high dosage opioid users before the policy.

RESULTS

Following implementation of Oregon's high dosage policy, the monthly probability of an opioid fill over 120 mg MED declined significantly by 1.7 percentage points (95% confidence interval [CI]; -2.0% to -1.4%), whereas it increased significantly by 1.0 percentage points (95% CI 0.4% to 1.7%) for opioid fills &lt; 61 mg MED. Fills of medications used to treat neuropathic pain also increased by 1.2 percentage points (95% CI 0.7% to 1.8%). The monthly probability of multiple pharmacy use declined by 0.1 percentage points (-0.2% to -0.0) following the prior authorization, but there were no significant changes in ED encounters or hospitalizations for opioid overdose. Among individuals who were using a high dosage opioid before the policy, there was a 20.3 percentage point (95% CI -15.3% to -25.3%) decline in estimated probability of having a high dosage fill after the policy.

CONCLUSIONS

Oregon's prior authorization policy was effective at reducing high dosage opioid prescriptions. While multiple pharmacy use also declined, we found no impact on opioid overdose were observed.

Comparing Care for Dual-Eligibles Across Coverage Models: Empirical Evidence From Oregon

Dual-eligible beneficiaries or "duals" are individuals enrolled in both the Medicare and Medicaid programs. For both Medicare and Medicaid, they may be enrolled in fee-for-service or managed care, creating a mix of possible coverage models. Understanding these different models is essential to improving care for duals. Using All-Payer All-Claims data, we empirically described health service use and quality of care for Oregon duals across five coverage models with different combinations of fee-for-service, managed care, and plan alignment status across Medicare and Medicaid. We found substantial heterogeneity in care across these five coverage models. We also found that duals in plans with aligned financial incentives for Medicare and Medicaid experienced more improvement in their care relative to those with nonaligned Medicare Advantage and Medicaid managed care plans. These results highlight the importance of developing policies that account for the heterogeneity of the dual population and their coverage options.

Trends of Neonatal Abstinence Syndrome Epidemic and Maternal Risk Factors in Florida

OBJECTIVE

This study aimed to examine secular trends of (i) maternal prescription opioid use in late pregnancy, (ii) neonatal abstinence syndrome (NAS) stratified by late maternal prescription opioid use, and (iii) maternal risk factors among NAS deliveries.

METHODS

Women with a live birth who were enrolled 90 days before and 30 days after delivery in Florida Medicaid Analytic Extract billing records linked to birth certificates from 2000 to 2010 were identified for the study. Changes in the annual prevalence of prescription opioid use during pregnancy were tested with use of the Cochran-Armitage trend test. Temporal trends of NAS deliveries were estimated with the use of Poisson regression and stratified by prescription opioid exposure in the last 90 days of pregnancy in the study period. To identify contributors to the increase in NAS cases, variations in prevalence of opioid dispensing, tobacco use, antidepressant use, and substance use disorder among NAS and non-NAS deliveries were examined.

RESULTS

There were 41,968 (9.4%) deliveries exposed to at least one opioid prescription in late pregnancy, and this rate remained stable from 2000 to 2010. Among prescription opioid-exposed deliveries, frequency of NAS increased from 1.6 to 25.2 per 1000 live births during the study period (p<0.05). Although the prevalence of maternal use of prescription opioid, tobacco, and antidepressants remained stable among NAS deliveries from 2000 to 2010, the prevalence of substance use disorder diagnoses increased substantially from 38.9% in 2000 to 67.9% in 2006 (p<0.05).

CONCLUSIONS

The prevalence of NAS increased dramatically whereas the prevalence of major risk factors, including maternal prescription opioid use, remained stable in Florida between 2000 and 2010. The increase in substance use disorder may be responsible for the sharp increase in NAS deliveries.

The other side of the coin: Harm due to the non-use of health-related data

INTRODUCTION

It is widely acknowledged that breaches and misuses of health-related data can have serious implications and consequently they often carry penalties. However, harm due to the omission of health data usage, or data non-use, is a subject that lacks attention. A better understanding of this 'other side of the coin' is required before it can be addressed effectively.

APPROACH

This article uses an international case study approach to explore why data non-use is difficult to ascertain, the sources and types of health-related data non-use, its implications for citizens and society and some of the reasons it occurs. It does this by focussing on issues with clinical care records, research data and governance frameworks and associated examples of non-use.

RESULTS AND DISCUSSION

The non-use of health-related data is a complex issue with multiple explanations. Individual instances of data non-use can be associated with harm, but taken together, they can describe a trail of data non-use that may complicate and compound its impacts. There is ample indirect evidence that health data non-use is implicated in the deaths of many thousands of people and potentially £billions in financial burdens to societies.

CONCLUSIONS

Harm due to the non-use of health data is difficult to attribute unequivocally and actual proven evidence is sparse. Although it can be elusive, it is nevertheless a real problem with widespread and serious, if largely unquantifiable, consequences. The most effective initiatives to address specific contexts of data non-use will be those that: firstly, understand the pertinent sources, types and reasons for data non-use in a given domain in order to meet the challenges and create appropriate incentives and repercussions; and secondly, are cognisant of the multiple aspects to this complex issue in other domains to keep benefits and limitations in perspective, to move steadily towards socially responsible reuse of data becoming the norm to save lives and resources.

Redaction of Substance Abuse Claims in Medicare Research Files Affects Spending Outcomes for Nearly One in Five Beneficiaries with Serious Mental Illness

OBJECTIVE

To assess the impact of substance abuse claims redaction on Medicare spending estimates for beneficiaries with serious mental illness.

DATA SOURCES

The 2012 claims and unredacted beneficiary-level Medicare spending totals from CMS's Chronic Conditions Warehouse.

STUDY DESIGN

We identified beneficiaries with claims affected by the redaction by comparing claims-based spending estimates to unredacted spending totals. Differences in characteristics of beneficiaries with and without redacted claims were examined in bivariate analyses.

PRINCIPAL FINDINGS

Claims-based spending totals differed from unredacted totals for 19.7 percent of the cohort. Part A spending for those with redacted claims was underreported by 57.0 percent. Characteristics of beneficiaries with and without redacted claims differed significantly.

CONCLUSIONS

Researchers who rely on Medicare claims to analyze spending outcomes for beneficiaries with serious mental illness should be aware of the potential for bias due to nonrandom redaction of substance abuse data.