Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Smoking and diabetes cause telomere shortening among alcohol use disorder patients

The length of telomeres located at the ends of chromosomes has attracted attention as an indicator of cellular and individual aging. Various diseases or stresses cause telomere shortening, and it has been reported that alcohol use disorder patients actually have shorter telomeres than healthy patients. However, the factors that contribute to the reduction in telomere length among alcohol use disorder patients have not been clarified in detail. Therefore, in this study, we explored the factors that reduce telomere length in alcohol use disorder patients. A questionnaire survey and a measurement of leukocyte telomere length were conducted among alcohol use disorder patients. The mean telomere length of leukocyte was measured by ∆∆Ct analysis using a real-time PCR. We compared the telomere length between alcohol use disorder patients and the control group (Japanese special health check-up examinee). Moreover, we searched for factors associated with telomere length from drinking/smoking characteristics and history of comorbidities. A total of 74 subjects had alcohol use disorder, and 68 were in the control group. Compared to the control group, alcohol use disorder patients had significantly shorter telomere lengths (p < 0.001). A multivariate analysis revealed that a longer duration of smoking resulted in a significantly shorter telomere length (p = 0.0129). In addition, a comparison of the telomere length between the groups with and without a history of suffering from each disease revealed that telomere length was significantly shorter in the group with diabetes than in the group without diabetes (p = 0.0371). This study reveals that in individuals with alcohol dependence, particularly, prolonged smoking habits and the presence of diabetes contribute to telomere shortening. Medication and support for abstinence from alcohol has been mainly provided for alcohol use disorder patients. Our findings demonstrate a potential support approach via smoking cessation programs and controlling diabetes, which may be helpful to suppress the shortening of healthy life expectancy among alcohol use disorder patients.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and medical traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and medical traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and medical traits were calculated in European-ancestry (EUR; n=5,691) participants and, when discovery datasets were available, for African-ancestry (AFR; n=4,918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGS MDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGS BMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and medical traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

The Spanish language version of the TAPS tool: protocol for a validation and implementation study in primary care

BACKGROUND

The TAPS Tool ("Tobacco, Alcohol, Prescription drug, and illicit Substance use") is a screening and brief assessment for detecting unhealthy substance use in healthcare settings that was developed by the National Institute on Drug Abuse Clinical Trials Network and validated in a multisite study. Our team developed a Spanish language version of the TAPS Tool that supports provider- and self-administration screening using a mobile/web-based platform, the TAPS Electronic Spanish Platform (TAPS-ESP).

METHODS

This article describes the protocol and rationale for a study to validate the TAPS-ESP in a sample of Spanish-speaking primary care patients recruited from a network of community-based clinics in Texas (target N = 1,000). The TAPS-ESP will be validated against established substance use disorder diagnostic measures, alternative screening tools, and substance use biomarkers. The study will subsequently examine barriers and facilitators to screening with the TAPS-ESP from a provider workflow perspective using qualitative interviews with providers.

DISCUSSION

Validating a Spanish language version of the TAPS Tool could expand access to evidence-based, linguistically accurate, and culturally relevant substance use screening and brief assessment for an underserved health disparity population.

TRIAL REGISTRATION

The study was registered with www.

CLINICALTRIALS

gov : NCT05476588, 07/22/2022.

Lessons learned and future directions: A scoping review of American Indian and Alaska Native participants in the National Drug Abuse Treatment Clinical Trials Network

INTRODUCTION

American Indian and Alaska Native (AI/AN) populations are disproportionately affected by substance use disorders (SUDs) and related health disparities in contrast to other ethnoracial groups in the United States. Over the past 20 years, substantial resources have been allocated to the National Institute on Drug Abuse Clinical Trials Network (CTN) to disseminate and implement effective SUD treatments in communities. However, we know little about how these resources have benefitted AI/AN peoples with SUD who arguably experience the greatest burden of SUDs. This review aims to determine lessons learned about AI/AN substance use and treatment outcomes in the CTN and the role of racism and Tribal identity.

METHOD

We conducted a scoping review informed by the Joanna Briggs framework and PRISMA Extension for Scoping Reviews checklist and explanation. The study team conducted the search strategy within the CTN Dissemination Library and nine additional databases for articles published between 2000 and 2021. The review included studies if they reported results for AI/AN participants. Two reviewers determined study eligibility.

RESULTS

A systematic search yielded 13 empirical articles and six conceptual articles. Themes from the 13 empirical articles included: (1) Tribal Identity: Race, Culture, and Discrimination; (2) Treatment Engagement: Access and Retention; (3) Comorbid Conditions; (4) HIV/Risky Sexual Behaviors; and (5) Dissemination. The most salient theme was Tribal Identity: Race, Culture, and Discrimination, which was present in all articles that included a primary AI/AN sample (k = 8). Themes assessed but not identified for AI/AN peoples were Harm Reduction, Measurement Equivalence, Pharmacotherapy, and Substance Use Outcomes. The conceptual contributions used AI/AN CTN studies as exemplars of community-based and Tribal participatory research (CBPR/TPR).

CONCLUSION

CTN studies conducted with AI/AN communities demonstrate culturally congruent methods, including CBPR/TPR strategies; consideration/assessment of cultural identity, racism, and discrimination; and CBPR/TPR informed dissemination plans. Although important efforts are underway to increase AI/AN participation in the CTN, future research would benefit from strategies to increase participation of this population. Such strategies include reporting AI/AN subgroup data; addressing issues of cultural identity and experiences of racism; and adopting an overall effort for research aimed at understanding barriers to treatment access, engagement, utilization, retention, and outcomes for both treatment and research disparities for AI/AN populations.

Diagnostic rate estimation from Medicare records: Dependence on claim numbers and latent clinical features

OBJECTIVE

International Classification of Disorders version 10 (ICD-10) codes contribute heavily to healthcare data. Medicare claims and other data-sources are used to constitute study populations and appraise healthcare processes. How variability in claims-per-beneficiary impacts diagnostic determinations is inadequately understood. The objective of this study is so assess distributional properties of Medicare claims, and examine claim rates impact on code utilization and rate determinations.

METHODS

The study population was Medicare beneficiaries aged 75-79.99 with claim(s) in the 5% standard analytical Carrier and Outpatient files, alive and participating in Medicare part B for all 12 months of 2017. Medicare beneficiary files were processed to create records containing all ICD-10 codes specified, key demographics, Part B and vital status, and the total claims for each 2017 beneficiary. Claim number cohorts were characterized.

RESULTS

Beneficiaries meeting inclusion criteria totaled 221,625, these having 7,617,503 claims; 96.4% had between 1 and 120 claims. Median claims were 24 for males (females 25); modal claims were 11 (13). Average distinct codes per beneficiary increased with claims number. The assignment of ICD-10 codes, i.e., 'diagnostic rate estimates' (DRE), increased as claim numbers increased for most codes among those most commonly utilized. For some conditions, mostly benign and age-related, DREs plateaued as claim numbers increased. For other conditions, typically associated with clinical acuity, e.g., chest pain, DREs increased steeply with claims.

CONCLUSIONS

Older adult Medicare beneficiaries aged 75-80 exhibited varying claims activity over the course of a year. Although DRE dependence on claim numbers varies across ICD-10 codes, rate estimates are higher for beneficiaries with claim numbers above the median.

Untreated substance use disorder affects glycemic control: Results in patients with type 2 diabetes served within a network of community-based healthcare centers in Florida

Introduction

Patients with diabetes and comorbid substance use disorders (SUD) experience poor diabetes management, increased medical complications and mortality. However, research has documented that patients engaged in substance abuse treatment have better management of their comorbid conditions. The current study examines diabetes management among patients with type 2 diabetes, with and without comorbid SUD, receiving care at Florida-based Federally Qualified Health Centers (FQHC) of Health Choice Network (HCN).

Methods

A retrospective analysis was conducted using deidentified electronic health records of 37,452 patients with type 2 diabetes who received care at a HCN site in Florida between 2016 and 2019. A longitudinal logistic regression analysis examined the impact of SUD diagnosis on achievement of diabetes management [HbA1c < 7.0% (53 mmol/mol)] over time. A secondary analysis evaluated, within those with an SUD diagnosis, the likelihood of HbA1c control between those with and without SUD treatment.

Results

The longitudinal assessment of the relationship between SUD status and HbA1c control revealed that those with SUD (N = 6,878, 18.4%) were less likely to control HbA1c over time (OR = 0.56; 95% CI = 0.49-0.63). Among those with SUD, patients engaged in SUD treatment were more likely to control HbA1c (OR = 5.91; 95% CI = 5.05-6.91).

Discussion

Findings highlight that untreated SUD could adversely affect diabetes control and sheds light on the opportunity to enhance care delivery for patients with diabetes and co-occurring SUD.

Health outcomes associated with patterns of substance use disorders among patients with type 2 diabetes and hypertension: Electronic health record findings

AIMS

To identify substance use disorder (SUD) patterns and their association with T2DM health outcomes among patients with type 2 diabetes and hypertension.

METHODS

We used latent class analysis on electronic health records from the MetroHealth System (Cleveland, Ohio) to obtain the target SUD groups: i) only tobacco (TUD), ii) tobacco and alcohol (TAUD), and iii) tobacco, alcohol, and at least one more substance (PSUD). A matching program with Mahalanobis distance within propensity score calipers created the matched control groups: no SUD (NSUD) for TUD and TUD for the other two SUD groups. The numbers of participants for the target-control groups were 8009 (TUD), 1672 (TAUD), and 642 (PSUD).

RESULTS

TUD was significantly associated with T2DM complications. Compared to TUD, the TAUD group showed a significantly higher likelihood for all-cause mortality (adjusted odds ratio (aOR) = 1.46) but not for any of the T2DM complications. Compared to TUD, the PSUD group experienced a significantly higher risk for cerebrovascular accident (CVA) (aOR = 2.19), diabetic neuropathy (aOR = 1.76), myocardial infarction (MI) (aOR = 1.76), and all-cause mortality (aOR = 1.66).

CONCLUSIONS

The findings of increased risk associated with PSUDs may provide insights for better management of patients with T2DM and hypertension co-occurrence.

Automated Detection of Substance-Use Status and Related Information from Clinical Text

This study aims to develop and evaluate an automated system for extracting information related to patient substance use (smoking, alcohol, and drugs) from unstructured clinical text (medical discharge records). The authors propose a four-stage system for the extraction of the substance-use status and related attributes (type, frequency, amount, quit-time, and period). The first stage uses a keyword search technique to detect sentences related to substance use and to exclude unrelated records. In the second stage, an extension of the NegEx negation detection algorithm is developed and employed for detecting the negated records. The third stage involves identifying the temporal status of the substance use by applying windowing and chunking methodologies. Finally, in the fourth stage, regular expressions, syntactic patterns, and keyword search techniques are used in order to extract the substance-use attributes. The proposed system achieves an F1-score of up to 0.99 for identifying substance-use-related records, 0.98 for detecting the negation status, and 0.94 for identifying temporal status. Moreover, F1-scores of up to 0.98, 0.98, 1.00, 0.92, and 0.98 are achieved for the extraction of the amount, frequency, type, quit-time, and period attributes, respectively. Natural Language Processing (NLP) and rule-based techniques are employed efficiently for extracting substance-use status and attributes, with the proposed system being able to detect substance-use status and attributes over both sentence-level and document-level data. Results show that the proposed system outperforms the compared state-of-the-art substance-use identification system on an unseen dataset, demonstrating its generalisability.

Five-year incidence of substance use and mental health diagnoses following exposure to opioids or opioids with benzodiazepines during an emergency department encounter for traumatic injury

BACKGROUND

Benzodiazepines and opioids are used alone or in conjunction in certain care settings, but each have the potential for misuse.

OBJECTIVE

This longitudinal observational study evaluated substance use and mental health outcomes associated with providing opioids with or without benzodiazepine to treat traumatic injury in the emergency department (ED) setting.

METHODS

We analyzed a limited dataset obtained through the IBM Watson Health Explorys. Matched cohorts were defined for: 1) patients treated with opioids during the ED encounter (ED-Opioid) vs. neither opioid or benzodiazepine treatment (No medication) (n = 5372); 2) patients treated with opioids and benzodiazepines during the ED encounter (ED-Opioid+Benzodiazepines) vs. No Medication (n = 2454); and 3) ED-Opioid+Benzodiazepines vs. ED-Opioid (n = 2454). Patients consisted of adults with an emergency department encounter in the MetroHealth System (Cleveland, Ohio) with a chief complaint of traumatic injury and medical records for five years following the encounter. Control patients for each cohort were matched to the exposure patients on demographics, body mass index, and residential zip code median income. Outcomes were five-year incidence rates for alcohol, substance use, depression, and anxiety-related diagnoses.

RESULTS

Our results indicate that, although receiving opioids during the ED visit predicted a relatively lower likelihood of subsequent substance use and mental health diagnoses, the brief co-use of benzodiazepines was strongly associated with poorer outcomes.

CONCLUSIONS

Even brief exposure to co-prescribed opioids and benzodiazepines during emergency traumatic injury care may be associated with negative substance use and mental health consequences in the years following the event.

On the Nature of Informative Presence Bias in Analyses of Electronic Health Records

Electronic health records (EHRs) offer unprecedented opportunities to answer epidemiologic questions. However, unlike in ordinary cohort studies or randomized trials, EHR data are collected somewhat idiosyncratically. In particular, patients who have more contact with the medical system have more opportunities to receive diagnoses, which are then recorded in their EHRs. The goal of this article is to shed light on the nature and scope of this phenomenon, known as informative presence, which can bias estimates of associations. We show how this can be characterized as an instance of misclassification bias. As a consequence, we show that informative presence bias can occur in a broader range of settings than previously thought, and that simple adjustment for the number of visits as a confounder may not fully correct for bias. Additionally, where previous work has considered only underdiagnosis, investigators are often concerned about overdiagnosis; we show how this changes the settings in which bias manifests. We report on a comprehensive series of simulations to shed light on when to expect informative presence bias, how it can be mitigated in some cases, and cases in which new methods need to be developed.

A historical cohort study of glycemic control in patients with concurrent type 2 diabetes and substance use disorder treated in a primary care setting

BACKGROUND

Substance use disorder (SUD) is a known barrier to patient-self-management, which can hinder efforts to achieve treatment goals in type 2 diabetes (T2D) when the conditions coexist.

OBJECTIVE

Identify the association between SUD and glycemic control in patients with T2D treated in a primary care setting.

METHODS

This retrospective cohort study included patients with T2D treated by providers at family medicine clinics at an academic medical center and its affiliated regional sites from January 2014 to October 2019. Study index date was the first A1c recorded when T2D and SUD diagnoses had both been documented in the medical record. Glycemic control, measured by hemoglobin A1c (A1c), was identified at baseline and over a 12-month follow-up period and was compared between SUD and non-SUD patients.

RESULTS

Of 9568 included patients with T2D, 468 (4.9%) had a SUD diagnosis. In 237 SUD and 4334 non-SUD patients with A1c data, mean (SD) baseline A1c was 8.2% (2.5) and 7.9% (2.1), respectively (P = 0.043). A1c reduction was statistically greater in SUD patients than non-SUD patients (-0.31% versus -0.06%, respectively; P = 0.015), although the clinical significance is modest. In a multivariable linear regression analysis, follow-up A1c was lower in the SUD versus non-SUD patients (coefficient -0.184, 95% CI -0.358, -0.010; P = 0.038).

CONCLUSIONS

Patients with T2D and SUD had higher baseline A1c but this difference was minimized over a 12-month follow-up period. Additional research is warranted to determine long-term glycemic control and barriers to attaining and maintaining glycemic control in patients with T2D and SUD.

[Mental disorders in type 2 diabetes]

OBJECTIVE

To assess the prevalence of mental disorders in patients with type 2 diabetes mellitus (DM2) and their relationship with laboratory findings, somatic comorbidities and psychosocial consequences.

MATERIAL AND METHODS

In the frames of the INTERPRET-DD multicenter 200 T2DM patients from primary care (47 men and 153 women) from the Russian sample were studied. The psychometric assessment included MINI-6, HAMD-17, PHQ-9, PAID, WHO-5.

RESULTS

One hundred and seventeen patients (58.5%) have mental disorders. Current mental disorders were diagnosed in 93 (46.5%) of patients. Depression (depressive episode, recurrent depressive disorder, bipolar affective disorder type II) was identified in 34 (17.0%), dysthymia in 26 (13.0%), and anxiety spectrum disorders in 39 (19.5%). In about half of the cases, anxiety disorders were combined with depression. The most severe problems were observed in the patients with depression and dysthymia. Patients with social phobia had significantly higher levels of glycated hemoglobin compared to patients without mental disorders. The significant decrease of systolic arterial pressure and body mass index was observed in patients with agoraphobia compared to patients without mental disorders. In addition, there was an increased prevalence of chronic ischemic heart disease in recurrent depression, dysthymia and generalized anxiety disorder, higher prevalence of neuropathy in depressive episode and recurrent depression and nephropathy in panic disorder.

CONCLUSION

Depressive and anxiety disorders, as well as severe psychosocial problems, are consistently associated with T2DM. At the same time, concomitant somatic disorders and complications of DM2 are not just by chance comorbid to various forms of mental disorders, which allows for a new look at the problem of comorbidity/multimorbidity in T2DM.

Cannabis Significantly Reduces the Use of Prescription Opioids and Improves Quality of Life in Authorized Patients: Results of a Large Prospective Study

OBJECTIVES

This article presents findings from a large prospective examination of Canadian medical cannabis patients, with a focus on the impacts of cannabis on prescription opioid use and quality of life over a 6-month period.

METHODS

The Tilray Observational Patient Study took place at 21 medical clinics throughout Canada. This analysis includes 1,145 patients who had at least one postbaseline visit, with follow-up at 1, 3, and 6 months. Instruments included a comprehensive cannabis use inventory, the World Health Organization Quality of Life Short Form (WHOQOL-BREF), and a detailed prescription drug questionnaire.

RESULTS

Participants were 57.6% female, with a median age of 52 years. Baseline opioid use was reported by 28% of participants, dropping to 11% at 6 months. Daily opioid use went from 152 mg morphine milligram equivalent (MME) at baseline to 32.2 mg MME at 6 months, a 78% reduction in mean opioid dosage. Similar reductions were also seen in the other four primary prescription drug classes identified by participants, and statistically significant improvements were reported in all four domains of the WHOQOL-BREF.

CONCLUSIONS

This study provides an individual-level perspective of cannabis substitution for opioids and other prescription drugs, as well as associated improvement in quality of life over 6 months. The high rate of cannabis use for chronic pain and the subsequent reductions in opioid use suggest that cannabis may play a harm reduction role in the opioid overdose crisis, potentially improving the quality of life of patients and overall public health.

Joint effect of diabetes and opiate use on all-cause and cause-specific mortality: the Golestan cohort study

BACKGROUND

Many diabetic individuals use prescription and non-prescription opioids and opiates. We aimed to investigate the joint effect of diabetes and opiate use on all-cause and cause-specific mortality.

METHODS

Golestan Cohort study is a prospective population-based study in Iran. A total of 50 045 people-aged 40-75, 28 811 women, 8487 opiate users, 3548 diabetic patients-were followed during a median of 11.1 years, with over 99% success follow-up. Hazard ratio and 95% confidence intervals (HRs, 95% CIs), and preventable death attributable to each risk factor, were calculated.

RESULTS

After 533 309 person-years, 7060 deaths occurred: 4178 (10.8%) of non-diabetic non-opiate users, 757 (25.3%) diabetic non-users, 1906 (24.0%) non-diabetic opiate users and 219 (39.8%) diabetic opiate users. Compared with non-diabetic non-users, HRs (95% CIs) for all-cause mortality were 2.17 (2.00-2.35) in diabetic non-opiate users, 1.63 (1.53-1.74) in non-diabetic opiate users and 2.76 (2.40-3.17) in diabetic opiate users. Among those who both had diabetes and used opiates, 63.8% (95% CI: 58.3%-68.5%) of all deaths were attributable to these risk factors, compared with 53.9% (95% CI: 50%-57.4%) in people who only had diabetes and 38.7% (95% CI: 34.6%-42.5%) in non-diabetic opiate users. Diabetes was more strongly associated with cardiovascular than cancer mortality. The risk of early mortality in known cases of diabetes did not depend on whether they started opiate use before or after their diagnosis.

CONCLUSIONS

Using opiates is detrimental to the health of diabetic patients. Public awareness about the health effects of opiates, and improvement of diabetes care especially among individuals with or at risk of opiate use, are necessary.

"Just tell me what's going on": The views of parents of children with genetic conditions regarding the research use of their child's electronic health record

OBJECTIVE

The purpose of this study was to understand the ethical, legal, and social issues described by parents of children with known or suspected genetic conditions that cause intellectual and developmental disabilities regarding research use of their child's electronic health record (EHR).

MATERIALS AND METHODS

We conducted 4 focus groups with parents of children with a known (n = 12) or suspected (n = 11) genetic condition, as well as 2 comparison groups with parents who had a child with no known genetic condition (n = 15). Focus group transcripts were coded and analyzed using directed content analysis.

RESULTS

After weighing the risks and benefits, parents of children with known or suspected genetic conditions were willing to share their child's EHR for research studies under certain conditions. Preferences were for studies conducted by universities or nonprofits that might benefit their child or others with the same condition. Parents also valued return of research results.

DISCUSSION

Trust, transparency, altruism, and concerns about privacy emerged as factors that affect parents' willingness to allow research use of their child's EHR.

CONCLUSION

Researchers should consider how to build trust with parents by increasing transparency of the research process and explaining specifically how they will ensure the confidentiality of EHR data.

The association between regular cocaine use, with and without tobacco co-use, and adverse cardiovascular and respiratory outcomes

BACKGROUND

Understanding the potential impact of cocaine use on health is increasingly important as cocaine use rises in the U.S.

OBJECTIVES

This study evaluated the associations of regular cocaine use, with and without tobacco co-use, with cardiovascular and respiratory outcomes.

METHODS

Analysis of a limited dataset obtained through IBM Watson Health Explorys, a platform integrating electronic health record data. Matched controls were defined for: 1) cocaine-using patients (n = 8244; 44 % female); and subgroups of cocaine-using patients: 2) with an encounter diagnosis for tobacco use disorder (TUD; n = 4706); and 3) without a TUD diagnosis (non-TUD; n = 3538). Patients had at least one documented medical evaluation in the MetroHealth System (Cleveland, Ohio). Cocaine-using patients had an encounter diagnosis of cocaine abuse/dependence and/or ≥2 cocaine-positive drug screens. Control patients, with no documented cocaine-use, were matched to the cocaine-using patients on demographics, residential zip code median income, body mass index, and, for the total sample, TUD-status. Outcomes were encounter diagnosis (yes/no) of cerebrovascular accident, heart arrhythmia, myocardial infarction, subarachnoid hemorrhage, asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and all-cause mortality.

RESULTS

TUD-patients had the greatest prevalence of cardiovascular and respiratory disease, regardless of cocaine-use indication. In the total sample, TUD, and non-TUD subgroups, regular cocaine use was significantly associated with greater risk for cerebrovascular accident, arrhythmia, myocardial infarction, asthma, COPD, pneumonia and mortality.

CONCLUSIONS

Cocaine use is associated with significantly greater risk of adverse cardiovascular and respiratory diagnoses and all-cause mortality.

The association between regular cannabis use, with and without tobacco co-use, and adverse cardiovascular outcomes: cannabis may have a greater impact in non-tobacco smokers

BACKGROUND

Understanding the potential impact of cannabis use on cardiovascular health is increasingly important as cannabis use rises in the U.S. Objectives: This study evaluated the associations between regular cannabis use, with and without tobacco co-use, and cardiovascular outcomes.

METHODS

Analysis of a limited dataset obtained through IBM Watson Health Explorys, a platform integrating electronic health record data. Matched controls using Mahalanobis distance within propensity score calipers were defined for: 1) cannabis-using patients (n = 8,944; 43% female); and subgroups of cannabis-using patients: 2) with an encounter diagnosis for tobacco use disorder (TUD; n = 4,682); and 3) without a TUD diagnosis (non-TUD; n = 4,262). Patients had ≥1 blood pressure measurement and blood chemistry lab result in the MetroHealth System (Cleveland, Ohio). Cannabis-using patients had an encounter diagnosis of cannabis abuse/dependence and/or ≥2 cannabis-positive urine drug screens. Control patients, with no cannabis-use-documentation, were matched to the cannabis-using patients on demographics, residential zip code median income, body mass index, and, for the total sample, TUD-status. Outcomes were encounter diagnosis (yes/no) of cerebrovascular accident (CVA), heart arrhythmia, myocardial infarction, subarachnoid hemorrhage (SAH), and all-cause mortality.

RESULTS

TUD-patients had the greatest prevalence of cardiovascular disease, regardless of cannabis-use indication. In the total sample and non-TUD subgroup, regular cannabis use was significantly associated with greater risk for CVA, arrhythmia, SAH, and mortality. In the TUD subgroup, regular cannabis use was significantly associated with greater risk for arrhythmia and SAH.

CONCLUSIONS

Cannabis use is associated with significantly greater risk of adverse cardiovascular diagnoses and overall death, particularly in non-tobacco users.

Alcohol and illicit drug use in people with diabetes

As the prevalence of type 1 and type 2 diabetes increases and population-level patterns of alcohol and illicit drug use evolve, clinicians will continue to encounter people with diabetes whose substance use is affecting health outcomes. Substance use contributes substantially to the population-level prevalence of cardiovascular events, cerebrovascular events, cancers, mental health conditions, road trauma, and domestic violence. Alcohol and drug use also have a measurable effect on diabetes incidence and the development of both acute and chronic diabetes-related complications. In this Review, we examine the effect of alcohol and illicit drug use on people with type 1 or type 2 diabetes. We describe evidence for substance use as a risk factor for new-onset diabetes, prevalence of use in people with diabetes, evidence linking substance use with diabetes-related health outcomes, and evidence on the management of these co-occurring conditions.

Regular cannabis use, with and without tobacco co-use, is associated with respiratory disease

BACKGROUND

Cannabis use is a potential risk factor for respiratory disease but its role apart from tobacco use is unclear. We evaluated the association between regular cannabis use, with and without tobacco co-use, and onset of asthma, chronic obstructive pulmonary disease (COPD), and pneumonia.

METHODS

Analysis of a limited data set obtained through IBM Watson Health Explorys, an electronic-health-record-integration platform. Matched controls using Mahalanobis distance within propensity score calipers were defined for: 1) cannabis-using patients (n = 8932); and subgroups of cannabis-using patients: 2) with an encounter diagnosis for tobacco use disorder (TUD; n = 4678); and 3) without a TUD diagnosis (non-TUD; n = 4254). Patients had at least: one recorded blood pressure measurement and one blood chemistry lab result in the MetroHealth System (Cleveland, Ohio). Cannabis-using patients had an encounter diagnosis of cannabis abuse/dependence and/or ≥2 cannabis-positive urine drug screens (UDSs). Control patients, not having cannabis-related diagnoses or cannabis-positive UDSs, were matched to the cannabis-using patients on demographics, residential zip code median income, body mass index, and, for the total sample, TUD-status.

RESULTS

Regular cannabis use was significantly associated with greater risk for asthma (odds ratio (OR) = 1.44; adjusted odds ratio (aOR) = 1.50; OR = 1.32), COPD (OR = 1.56; aOR = 1.44; OR = 2.17), and pneumonia (OR = 1.80; OR = 1.84; OR = 2.13) in the total sample and TUD and non-TUD subgroups, respectively. TUD-patients had the greatest prevalence of respiratory disease, regardless of cannabis-use indication.

CONCLUSIONS

Regular cannabis use is associated with significantly greater risk of respiratory disease regardless of TUD status. Future research to understand the impact of cannabis use on respiratory health is warranted.

Medical complications associated with substance use disorders in patients with type 2 diabetes and hypertension: electronic health record findings

BACKGROUND AND AIMS

Screening for substance use disorder (SUD) in general medical settings may be particularly important in patients with comorbid health conditions exacerbated by SUD. This study evaluated whether SUD is associated with type 2 diabetes mellitus (T2DM) complications in patients with co-occurring T2DM and hypertension.

DESIGN

Analysis of a limited data set obtained through IBM Watson Health Explorys, a platform integrating data from electronic health records. Matched controls were defined for each of five SUDs: tobacco use disorder (TUD), opioid use disorder (OUD), cocaine use disorder, cannabis use disorder (CUD) and alcohol use disorder (AUD) using Mahalanobis distance within propensity score calipers.

SETTING

All patients were seen in the MetroHealth System (Cleveland, OH, USA) and had diagnosis codes for T2DM and hypertension.

PARTICIPANTS

SUD group participants had a diagnosis of abuse/dependence for the substance of interest. Controls for each SUD group had no diagnosis code related to the SUD of interest and were selected to match the SUD patients on demographics, residential zip code median income and body mass index. Total sample sizes for each SUD-control comparison ranged from 1160 for CUD to 22 128 for TUD.

MEASUREMENTS

Outcome was diagnosis (yes/no) of four T2DM complications (cerebrovascular accident, diabetic neuropathy, diabetic renal disease, myocardial infarction) and all-cause mortality.

FINDINGS

Logistic regressions revealed that SUD was significantly associated with greater risk of cerebrovascular accident [TUD odds ratio (OR) = 1.79, OUD-OR = 1.94, cocaine use disorder OR = 2.67], diabetic neuropathy [TUD-adjusted OR (aOR) = 1.47, cocaine use disorder-aOR = 1.35, AUD-aOR = 1.27], diabetic renal disease (TUD-aOR = 1.25, OUD-OR = 1.34), myocardial infarction (TUD-OR = 1.96, OUD-OR = 2.01, cocaine use disorder-OR = 2.68, CUD-OR = 2.48, AUD-OR = 1.42) and mortality (TUD-OR = 1.15, cocaine use disorder-OR = 1.61, CUD-OR = 1.49, AUD-OR = 1.35).

CONCLUSIONS

Among patients in Ohio USA with both type 2 diabetes mellitus (T2DM) and hypertension, those with substance use disorders appear to have greater risk for T2DM complications and all-cause mortality.

Social and Psychosocial Determinants of Health Associated With Uncontrolled Diabetes in a Federally Qualified Health Center Population

PURPOSE

Many people with diabetes have difficulty achieving glycemic targets, and social and psychosocial determinants of health may influence their ability to obtain glycemic goals. The objective of this study was to identify characteristics independently associated with A1C >9% or untested A1C compared to those with A1C ≤9% at a federally qualified health center.

METHODS

This retrospective cohort study included people with a diagnosis of diabetes, who were 18-89 years of age and had a medical evaluation from a primary care provider between 1 September 2016 and 31 August 2017. The primary outcome was to identify characteristics associated with an A1C >9% or untested A1C compared to those with an A1C ≤9%.

RESULTS

Of 6,185 patients meeting inclusion criteria, 2,965 (48%) had uncontrolled A1C. In the uncontrolled A1C group, 1,549 patients (52%) were female, 1,296 (44%) preferred care in a language other than English (1,273 [43%] in Spanish), and 535 (18%) had a concurrent mental health diagnosis. Multivariable logistic regression of 4,774 patients with complete data revealed that poor appointment adherence (odds ratio [OR] 3.24, 95% CI 2.30-4.57) and/or a positive Patient Health Questionnaire-2 depression screen (OR 1.35, 95% CI 1.12-1.62) had an increased risk of being in the uncontrolled A1C group. Patients with a prescription for antidepressant medication were more likely to be in the controlled group.

CONCLUSION

Poor adherence to appointments and presence of depressive symptoms were associated with high A1C values. Interventions can be developed targeting these determinants to improve blood glucose levels.

Diabetes and anxiety symptoms: A systematic review and meta-analysis

Although some studies have been conducted on the association between diabetes and anxiety symptoms, the data on this association remain controversial. The purpose of this meta-analysis was to examine the association between diabetes and anxiety symptoms. The authors systematically searched PubMed, Scopus, and Google Scholar databases until July 2018. After the screening process, 23 studies were included in the meta-analysis. Stata-14 was used for meta-analyzing. Forest plot was calculated for the whole 23 studies and subgroups, and publication bias was also examined. Overall, diabetes was positively associated with anxiety; pooled odds ratio was equal to1.48; 95% confidence interval was 1 .27-1.74. In cross-sectional study, the result was odds ratio = 1.50; 95% confidence interval = 1.26-1.77, and in prospective-cohort study, the result was odds ratio = 1.34; 95% confidence interval = 1.21-1.49. There was small evidence of publication bias. Overall, our findings indicate that diabetes is a risk factor for anxiety symptoms. Therefore, having a healthy medical condition can be an anxiety prevention agent.

Multicomorbidity of chronic diseases and substance use disorders and their association with hospitalization: Results from electronic health records data

BACKGROUND

Chronic diseases are prevalent and the leading causes of mortality. Comorbidity of substance use disorders (SUDs) and chronic diseases is understudied to inform behavioral healthcare integration.

OBJECTIVES

This study leveraged electronic health record (EHR) data of 211,880 adults from a large health system to examine prevalence and correlates of comorbidity of SUDs and nine chronic disease groups and to determine their association with hospitalization.

METHODS

Logistic regression analyses were conducted to estimate associations between chronic diseases and SUDs. To control for severity of diagnosis, analyses of associations between SUD and hospitalization were stratified by the number of chronic conditions.

RESULTS

In the sample, 48.3% had ≥1 chronic condition (hypertension 33.7%, arthritis 16.2%, diabetes 13.7%, chronic kidney disease 9.9%, asthma 9.1%, chronic obstructive pulmonary disease 8.9%, ischemic heart disease 8.3%, cancer 4.6%, and hepatitis 1.3%). Prevalence of SUD (overall 13.3%) among patients increased with multiple chronic conditions (14.3% having SUD among patients with one condition; 21.2% having SUD among patients with two to three conditions; and 32.5% having SUD among patients with 4-9 conditions). Chronic conditions were associated with increased odds of SUDs. For all SUD groups, hospitalization was more prevalent among patients with SUD than those without it; prevalence of hospitalization increased with the number of comorbid chronic conditions.

CONCLUSIONS

Findings reveal a striking pattern of multicomorbidity of SUD and chronic diseases and its positive association with hospitalization. Behavioral healthcare integration should consider efforts to assess and treat comorbid SUD and chronic diseases, especially among adults with multiple chronic conditions.

Care outcomes and alcohol-related treatment utilisation profiles of patients with alcohol-use disorder: A prospective cohort study using electronic health records

Background:

We examined the probabilities of longitudinal care outcomes of working-aged patients with alcohol-use disorder (AUD) and their alcohol-related treatment utilisation patterns across the healthcare services, by using linked electronic health records.

Methods:

A random sample (n = 396) of patients with alcohol-related visits to healthcare services in 2011–2012 was collected retrospectively from the electronic health record data in the North Karelia region of Finland and followed prospectively in time until the end of 2016. Data on care outcomes and alcohol-related healthcare use were gathered from the electronic health records. Three outcome groups were identified: (1) dead, (2) present AUD, and (3) remission. Group differences in alcohol-related health service use were compared.

Results:

At the end of the follow-up period, an increased mortality rate of 22.9% was observed, and 18.4% had achieved stable remission, while for the majority (56%), the AUD remained. Most of those in remission had contact with either specialised AUD services or mental health services. Conversely, the majority of those who had died had no contact with specialised AUD services during the follow-up period.

Conclusions:

The electronic-health-record-based register analysis captured mainly individuals with advanced forms of AUD. An excess mortality rate and other negative health consequences were observed. Training providers to identify and treat earlier the less severe forms of AUD could have major benefit to patients and also reduce health system costs.

Residential Racial Isolation and Spatial Patterning of Type 2 Diabetes Mellitus in Durham, North Carolina

Neighborhood characteristics such as racial segregation may be associated with type 2 diabetes mellitus, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. We constructed a local, spatial index of racial isolation (RI) for black residents in a defined area, measuring the extent to which they are exposed only to one another, to estimate associations of diabetes with RI and examine how RI relates to spatial patterning in diabetes. We obtained electronic health records from 2007-2011 from the Duke Medicine Enterprise Data Warehouse. Patient data were linked to RI based on census block of residence. We used aspatial and spatial Bayesian models to assess spatial variation in diabetes and relationships with RI. Compared with spatial models with patient age and sex, residual geographic heterogeneity in diabetes in spatial models that also included RI was 29% and 24% lower for non-Hispanic white and black residents, respectively. A 0.20-unit increase in RI was associated with an increased risk of diabetes for white (risk ratio = 1.24, 95% credible interval: 1.17, 1.31) and black (risk ratio = 1.07, 95% credible interval: 1.05, 1.10) residents. Improved understanding of neighborhood characteristics associated with diabetes can inform development of policy interventions.

Substance use disorders and medical comorbidities among high-need, high-risk patients with diabetes

BACKGROUND

The majority of the U.S. healthcare resources are utilized by a small population characterized as high-risk, high-need persons with complex care needs (e.g., adults with multiple chronic conditions). Substance use disorders (SUDs) and mental health disorders (MHDs) are a driver of poor health and additional healthcare costs, but they are understudied among high-need patients.

OBJECTIVE

We examine the prevalence and correlates of SUDs and MHDs among adults with high-risk diabetes, who are patients at the top 10% risk score for developing poor outcomes (hospital admission or death).

METHODS

A risk algorithm developed from Duke University Health System electronic health records (EHRs) data was used to identify patients with high-risk diabetes for targeting home-based primary care. The EHR data of the 263 patients with high-risk diabetes were analyzed to understand patterns of SUDs and MHDs to inform care-coordinating efforts.

RESULTS

Both SUDs (any SUD 48.3%, alcohol 12.5%, tobacco 38.8%, drug 23.2%) and MHDs (any MHD 74.9%, mood 53.2%, sleep 37.3%, anxiety 32.7%, schizophrenia/psychotics/delusional 14.8%, dementia/delirium/amnestic/cognitive 14.4%, adjustment 9.1%) were prevalent. Overall, 81.7% of the sample had SUD or MHD. Elevated odds of SUD were noted among men (tobacco, alcohol) and those who were never-married (alcohol, cannabis). African-American race (vs. other race/ethnicity) was associated with lower odds of anxiety disorders.

CONCLUSION

While data are limited to one large academic health system, they provide clinical evidence revealing that 82% of patients with high-risk diabetes had SUD and/or MHD recorded in their EHRs, highlighting a need for developing service models to optimize high-risk care.

Prevalence of mental disorders and related functioning and treatment engagement among people with diabetes

AIMS

To examine prevalence, functioning and treatment associated with all DSM-5 12-month mood, anxiety, eating and substance use disorders among people with diabetes in data obtained from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

METHODS

Through multistage stratified randomized sampling a sample representative of the United States civilian population was obtained. Prevalence of diabetes (Type 1 and 2), DSM-5 disorders, physical and mental functioning, and treatment utilization were assessed via telephone interview. Analyses of weighted data (N=36,138) included calculation of descriptive statistics, and chi-square, logistic and linear regression analyses.

RESULTS

Participants with (vs. without) diabetes (9.3% of weighted sample) had a significantly: (a) higher prevalence of any anxiety disorder and posttraumatic stress disorder (with and without adjustment for sociodemographic characteristics), and any mood disorder, major depressive disorder and specific phobia (with adjustment), (b) lower prevalence of any substance use disorder and alcohol and tobacco use disorders (with and without adjustment), and cannabis use disorder (without adjustment). Among participants with diabetes, mental disorder prevalence was consistently associated with sex and age, and to a lesser frequency, race/ethnicity. Lower levels of physical and mental functioning were found among participants with diabetes and a comorbid mental disorder. A minority of participants with diabetes and a comorbid mental disorder received treatment for mood and anxiety disorders, and few received treatment for eating and substance use disorders.

CONCLUSIONS

Multiple types of mood, anxiety, eating and substance use disorders are prevalent, problematic, and often untreated among people with diabetes.

The impact of substance use disorders on clinical outcomes in older-adult psychiatric inpatients

OBJECTIVE

To examine associations among substance use disorder (SUD) and measures of length of stay (LOS) and non-psychiatric medical comorbidity (MEDCO) in older-adult inpatients with serious mental illness (SMI), hypothesizing SUD would be related to worse clinical outcomes.

METHODS

A cross-sectional study analyzed medical records from 2010 to 2016 of 7258 inpatients with SMI ≥ age 50, obtained from a 274-bed psychiatric hospital. Descriptive analyses examined prevalence rates for SUD status (+/-), individual drug classes, and total number of SUDs (polysubstance use disorders). Regression models examined the influence of 2 independent variables of interest: (1) SUD status (+/-) and (2) type of SUD (ie, specific drug), controlling for demographic factors and additional (non-SUD) psychiatric disorders. Two dependent (outcome) variables were examined: LOS and MEDCO.

RESULTS

The overall SUD rate was 26%; cocaine was the most common SUD (≈ 10%). SUD status and additional (non-SUD) psychiatric diagnoses were significantly associated with longer LOS (both P < 0.001). For individual SUDs, cocaine, marijuana, opiates, and alcohol were all significantly associated with LOS (all P < 0.01). SUD status, age, sex, admission status, and race were significantly associated with MEDCO (all P < 0.002). For individual SUDs, barbiturates, opiates, and alcohol were all significantly associated with MEDCO (P < 0.01).

CONCLUSIONS

The prevalence of SUD in this sample underscores concerns related to treating older adults presenting providers with comorbid SUD and SMI. This combination may increase the burden and complexity of care, warranting further investigation into mechanisms and long-term consequences.

A graduated food addiction classifications approach significantly differentiates depression, anxiety and stress among people with type 2 diabetes

AIMS

To examine differences in depression, anxiety, and stress across people with type 2 diabetes mellitus (t2d) classified according to a four level processed food addiction (PFA) severity indicator dichotomy.

METHODS

Four hundred and eight participants with a t2d diagnoses completed an online survey including the Yale Food Addiction Scale (YFAS) and the DASS-21. Based on YFAS symptom counts participants were classified as either: non-PFA; mild-PFA; moderate-PFA; or severe-PFA.

RESULTS

Multivariate, λ=0.422, F(9,978.51)=46.286, p<0.001, n_p²=0.250, and univariate analyses of variance demonstrated that depression F(3,408)=159.891, p<0.001, n_p²=0.543, anxiety F(3,408)=127.419, p<0.001, n_p²=0.486, and stress scores F(3,408)=129.714, p<0.001, n_p²=0.491, significantly and meaningfully increased from one PFA classification level to the next. Furthermore, the proportion of participants with more severe classifications of depression χ² (12)=297.820, p<0.001, anxiety χ² (12)=271.805, p<0.001, and stress χ² (12)=240.875, p<0.001, were significantly higher in the more severe PFA groupings.

CONCLUSION

For people with t2d, PFA is an important and meaningful associate of depression, anxiety, and stress, and that the adopted four level PFA severity indicator dichotomy is valid and useful.

Substance Use Disorders among Patients with Type 2 Diabetes: a Dangerous but Understudied Combination

PURPOSE OF REVIEW

This paper reviews research on substance use and disorders (SUDs) among adults with diabetes. It describes epidemiological data on SUDs in persons with type 2 diabetes, overviews effects of substance use on diabetes outcomes, and discusses treatments for SUDs in patients with diabetes.

RECENT FINDINGS

Rates of current smoking range from 10 to 26% and alcohol use disorders are 0-5%. Rates of illicit SUDs are 3-4%, but there are no population-based studies using nationally representative samples. Smoking increases the risk for long-term diabetes complications and premature death. Alcohol and illicit drug use can also impact long-term diabetes complications by impairing glucose homeostasis and adversely influencing self-management behaviors. There is mixed evidence about psychosocial smoking cessation interventions in adults with diabetes and little on alcohol and illicit SUD interventions. Limited data exist on pharmacotherapies for SUDs in this population, but a recent study suggests that varenicline is safe and effective for treating smoking in patients with diabetes. Substance use is an understudied problem in type 2 diabetes, and addressing substance use holds potential for improving outcomes. Additional large population-based epidemiological studies in those with type 2 diabetes are needed, particularly for alcohol and illicit SUDs. Longitudinal studies should be conducted to better understand the time course of diabetes onset and outcomes in relation to SUDs. Randomized controlled trials are needed to assess safety and efficacy of promising psychosocial and pharmacological interventions.

Controlling for Informed Presence Bias Due to the Number of Health Encounters in an Electronic Health Record

Electronic health records (EHRs) are an increasingly utilized resource for clinical research. While their size allows for many analytical opportunities, as with most observational data there is also the potential for bias. One of the key sources of bias in EHRs is what we term informed presence-the notion that inclusion in an EHR is not random but rather indicates that the subject is ill, making people in EHRs systematically different from those not in EHRs. In this article, we use simulated and empirical data to illustrate the conditions under which such bias can arise and how conditioning on the number of health-care encounters can be one way to remove this bias. In doing so, we also show when such an approach can impart M bias, or bias from conditioning on a collider. Finally, we explore the conditions under which number of medical encounters can serve as a proxy for general health. We apply these methods to an EHR data set from a university medical center covering the years 2007-2013.

Food addiction associations with psychological distress among people with type 2 diabetes

AIMS

To assess the relationship between a food addiction (FA) model and psychological distress among a type 2 diabetes (t2d) sample.

METHODS

A cross-sectional study of 334 participants with t2d diagnoses were invited to complete a web-based questionnaire. We measured variables of psychological distress implementing the Depression Anxiety and Stress Scale (DASS-21), the Yale Food Addiction Scale (YFAS), and other factors associated with t2d.

RESULTS

In our study a novel finding highlighted people with t2d meeting the FA criterion had significantly higher depression, anxiety, and stress scores as compared to participants who did not meet the FA criterion. Moreover, FA symptomology explained 35% of the unique variance in depression scores, 34% of the unique variance in anxiety scores, and 34% of the unique variance in stress scores, while surprisingly, BMI explained less than 1% of the unique variance in scores.

CONCLUSION

We identified that psychological distress among people with t2d was associated with the FA model, apparently more so than BMI, thereby indicating further research being necessary lending support for future research in this realm. Moreover the FA model may be beneficial when addressing treatment approaches for psychological distress among people with t2d.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study

BACKGROUND

The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs.

METHODS

We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention.

DISCUSSION

By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.