Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes.

BACKGROUND: Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes. OBJECTIVE: Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes. DESIGN, PARTICIPANTS, MEASURES: In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities. RESULTS: Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52). CONCLUSIONS: Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Identifying hypertensive disorders of pregnancy, a comparison of two epidemiologic definitions.

Introduction: Studies of hypertension in pregnancy that use electronic health care data generally identify hypertension using hospital diagnosis codes alone. We sought to compare results from this approach to an approach that included diagnosis codes, antihypertensive medications and blood pressure (BP) values. Materials and methods: We conducted a retrospective cohort study of 1,45,739 pregnancies from 2009 to 2014 within an integrated healthcare system. Hypertensive pregnancies were identified using the "BP-Inclusive Definition" if at least one of three criteria were met: (1) two elevated outpatient BPs, (2) antihypertensive medication fill plus an outpatient hypertension diagnosis, or (3) hospital discharge diagnosis for preeclampsia or eclampsia. The "Traditional Definition" considered only delivery hospitalization discharge diagnoses. Outcome event analyses compared rates of preterm delivery and small for gestational age (SGA) between the two definitions. Results: The BP-Inclusive Definition identified 14,225 (9.8%) hypertensive pregnancies while the Traditional Definition identified 13,637 (9.4%); 10,809 women met both definitions. Preterm delivery occurred in 20.9% of BP-Inclusive Definition pregnancies, 21.8% of Traditional Definition pregnancies and 6.6% of non-hypertensive pregnancies; for SGA the numbers were 15.6, 16.3, and 8.6%, respectively (p < 0.001 for all events compared to non-hypertensive pregnancies). Analyses in women meeting only one hypertension definition (21-24% of positive cases) found much lower rates of both preterm delivery and SGA. Conclusion: Prevalence of hypertension in pregnancy was similar between the two study definitions. However, a substantial number of women met only one of the study definitions. Women who met only one of the hypertension definitions had much lower rates of adverse neonatal events than women meeting both definitions.

Accuracy of ICD-10-CM encounter diagnoses from health records for identifying self-harm events.

OBJECTIVE: Assess the accuracy of ICD-10-CM coding of self-harm injuries and poisonings to identify self-harm events. MATERIALS AND METHODS: In 7 integrated health systems, records data identified patients reporting frequent suicidal ideation. Records then identified subsequent ICD-10-CM injury and poisoning codes indicating self-harm as well as selected codes in 3 categories where uncoded self-harm events might be found: injuries and poisonings coded as undetermined intent, those coded accidental, and injuries with no coding of intent. For injury and poisoning encounters with diagnoses in those 4 groups, relevant clinical text was extracted from records and assessed by a blinded panel regarding documentation of self-harm intent. RESULTS: Diagnostic codes selected for review include all codes for self-harm, 43 codes for undetermined intent, 26 codes for accidental intent, and 46 codes for injuries without coding of intent. Clinical text was available for review for 285 events originally coded as self-harm, 85 coded as undetermined intent, 302 coded as accidents, and 438 injury events with no coding of intent. Blinded review of full-text clinical records found documentation of self-harm intent in 254 (89.1%) of those originally coded as self-harm, 24 (28.2%) of those coded as undetermined, 24 (7.9%) of those coded as accidental, and 48 (11.0%) of those without coding of intent. CONCLUSIONS: Among patients at high risk, nearly 90% of injuries and poisonings with ICD-10-CM coding of self-harm have documentation of self-harm intent. Reliance on ICD-10-CM coding of intent to identify self-harm would fail to include a small proportion of true self-harm events.

Maternal and neonatal outcomes of antihypertensive treatment in pregnancy: A retrospective cohort study.

OBJECTIVE: To compare maternal and infant outcomes with different antihypertensive medications in pregnancy. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente, a large healthcare system in the United States. POPULATION: Women aged 15-49 years with a singleton birth from 2005-2014 treated for hypertension. METHODS: We identified medication exposure from automated pharmacy data based on the earliest dispensing after the first prenatal visit. Using logistic regression, we calculated weighted outcome prevalences, adjusted odds ratios (aORs) and 95% confidence intervals, with inverse probability of treatment weighting to address confounding. MAIN OUTCOME MEASURES: Small for gestational age, preterm delivery, neonatal and maternal intensive care unit (ICU) admission, preeclampsia, and stillbirth or termination at > 20 weeks. RESULTS: Among 6346 deliveries, 87% with chronic hypertension, the risk of the infant being small for gestational age (birthweight < 10th percentile) was lower with methyldopa than labetalol (prevalence 13.6% vs. 16.6%; aOR 0.77, 95% CI 0.63 to 0.92). For birthweight < 3rd percentile the aOR was 0.57 (0.39 to 0.80). Compared with labetalol (26.0%), risk of preterm delivery was similar for methyldopa (26.5%; aOR 1.10 [0.95 to 1.27]) and slightly higher for nifedipine (28.5%; aOR 1.25 [1.06 to 1.46]) and other ß-blockers (31.2%; aOR 1.58 [1.07 to 2.23]). Neonatal ICU admission was more common with nifedipine than labetalol (25.9% vs. 23.3%, aOR 1.21 [1.02 to 1.43]) but not elevated with methyldopa. Risks of other outcomes did not differ by medication. CONCLUSIONS: Risk of most outcomes was similar comparing labetalol, methyldopa and nifedipine. Risk of the infant being small for gestational age was substantially lower for methyldopa, suggesting this medication may warrant further consideration.

Effect of Offering Care Management or Online Dialectical Behavior Therapy Skills Training vs Usual Care on Self-harm Among Adult Outpatients With Suicidal Ideation: A Randomized Clinical Trial.

Importance: People at risk of self-harm or suicidal behavior can be accurately identified, but effective prevention will require effective scalable interventions. Objective: To compare 2 low-intensity outreach programs with usual care for prevention of suicidal behavior among outpatients who report recent frequent suicidal thoughts. Design, Setting, and Participants: Pragmatic randomized clinical trial including outpatients reporting frequent suicidal thoughts identified using routine Patient Health Questionnaire depression screening at 4 US integrated health systems. A total of 18 882 patients were randomized between March 2015 and September 2018, and ascertainment of outcomes continued through March 2020. Interventions: Patients were randomized to a care management intervention (n = 6230) that included systematic outreach and care, a skills training intervention (n = 6227) that introduced 4 dialectical behavior therapy skills (mindfulness, mindfulness of current emotion, opposite action, and paced breathing), or usual care (n = 6187). Interventions, lasting up to 12 months, were delivered primarily through electronic health record online messaging and were intended to supplement ongoing mental health care. Main Outcomes and Measures: The primary outcome was time to first nonfatal or fatal self-harm. Nonfatal self-harm was ascertained from health system records, and fatal self-harm was ascertained from state mortality data. Secondary outcomes included more severe self-harm (leading to death or hospitalization) and a broader definition of self-harm (selected injuries and poisonings not originally coded as self-harm). Results: A total of 18 644 patients (9009 [48%] aged 45 years or older; 12 543 [67%] female; 9222 [50%] from mental health specialty clinics and the remainder from primary care) contributed at least 1 day of follow-up data and were included in analyses. Thirty-one percent of participants offered care management and 39% offered skills training actively engaged in intervention programs. A total of 540 participants had a self-harm event (including 45 deaths attributed to self-harm and 495 nonfatal self-harm events) over 18 months following randomization: 172 (3.27%) in care management, 206 (3.92%) in skills training, and 162 (3.27%) in usual care. Risk of fatal or nonfatal self-harm over 18 months did not differ significantly between the care management and usual care groups (hazard ratio [HR], 1.07; 97.5% CI, 0.84-1.37) but was significantly higher in the skills training group than in usual care (HR, 1.29; 97.5% CI, 1.02-1.64). For severe self-harm, care management vs usual care had an HR of 1.03 (97.5% CI, 0.71-1.51); skills training vs usual care had an HR of 1.34 (97.5% CI, 0.94-1.91). For the broader self-harm definition, care management vs usual care had an HR of 1.10 (97.5% CI, 0.92-1.33); skills training vs usual care had an HR of 1.17 (97.5% CI, 0.97-1.41). Conclusions and Relevance: Among adult outpatients with frequent suicidal ideation, offering care management did not significantly reduce risk of self-harm, and offering brief dialectical behavior therapy skills training significantly increased risk of self-harm, compared with usual care. These findings do not support implementation of the programs tested in this study. Trial Registration: ClinicalTrials.gov Identifier: NCT02326883.

Racial/Ethnic Disparities in the Performance of Prediction Models for Death by Suicide After Mental Health Visits.

Importance: Clinical prediction models estimated with health records data may perpetuate inequities. Objective: To evaluate racial/ethnic differences in the performance of statistical models that predict suicide. Design, Setting, and Participants: In this diagnostic/prognostic study, performed from January 1, 2009, to September 30, 2017, with follow-up through December 31, 2017, all outpatient mental health visits to 7 large integrated health care systems by patients 13 years or older were evaluated. Prediction models were estimated using logistic regression with LASSO variable selection and random forest in a training set that contained all visits from a 50% random sample of patients (6 984 184 visits). Performance was evaluated in the remaining 6 996 386 visits, including visits from White (4 031 135 visits), Hispanic (1 664 166 visits), Black (578 508 visits), Asian (313 011 visits), and American Indian/Alaskan Native (48 025 visits) patients and patients without race/ethnicity recorded (274 702 visits). Data analysis was performed from January 1, 2019, to February 1, 2021. Exposures: Demographic, diagnosis, prescription, and utilization variables and Patient Health Questionnaire 9 responses. Main Outcomes and Measures: Suicide death in the 90 days after a visit. Results: This study included 13 980 570 visits by 1 433 543 patients (64% female; mean [SD] age, 42 [18] years. A total of 768 suicide deaths were observed within 90 days after 3143 visits. Suicide rates were highest for visits by patients with no race/ethnicity recorded (n = 313 visits followed by suicide within 90 days, rate = 5.71 per 10 000 visits), followed by visits by Asian (n = 187 visits followed by suicide within 90 days, rate = 2.99 per 10 000 visits), White (n = 2134 visits followed by suicide within 90 days, rate = 2.65 per 10 000 visits), American Indian/Alaskan Native (n = 21 visits followed by suicide within 90 days, rate = 2.18 per 10 000 visits), Hispanic (n = 392 visits followed by suicide within 90 days, rate = 1.18 per 10 000 visits), and Black (n = 65 visits followed by suicide within 90 days, rate = 0.56 per 10 000 visits) patients. The area under the curve (AUC) and sensitivity of both models were high for White, Hispanic, and Asian patients and poor for Black and American Indian/Alaskan Native patients and patients without race/ethnicity recorded. For example, the AUC for the logistic regression model was 0.828 (95% CI, 0.815-0.840) for White patients compared with 0.640 (95% CI, 0.598-0.681) for patients with unrecorded race/ethnicity and 0.599 (95% CI, 0.513-0.686) for American Indian/Alaskan Native patients. Sensitivity at the 90th percentile was 62.2% (95% CI, 59.2%-65.0%) for White patients compared with 27.5% (95% CI, 21.0%-34.7%) for patients with unrecorded race/ethnicity and 10.0% (95% CI, 0%-23.0%) for Black patients. Results were similar for random forest models, with an AUC of 0.812 (95% CI, 0.800-0.826) for White patients compared with 0.676 (95% CI, 0.638-0.714) for patients with unrecorded race/ethnicity and 0.642 (95% CI, 0.579-0.710) for American Indian/Alaskan Native patients and sensitivities at the 90th percentile of 52.8% (95% CI, 50.0%-55.8%) for White patients, 29.3% (95% CI, 22.8%-36.5%) for patients with unrecorded race/ethnicity, and 6.7% (95% CI, 0%-16.7%) for Black patients. Conclusions and Relevance: These suicide prediction models may provide fewer benefits and more potential harms to American Indian/Alaskan Native or Black patients or those with undrecorded race/ethnicity compared with White, Hispanic, and Asian patients. Improving predictive performance in disadvantaged populations should be prioritized to improve, rather than exacerbate, health disparities.

Renin-Angiotensin-Aldosterone System Inhibitors and COVID-19 Infection or Hospitalization: A Cohort Study.

BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of coronavirus disease 2019 (COVID-19) infection or affect disease severity. Prior studies have not examined risks by medication dose. METHODS: This retrospective cohort study included people aged ≥18 years enrolled in a US integrated healthcare system for at least 4 months as of 2/29/2020. Current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections and hospitalizations were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for race/ethnicity, obesity, and other covariates. RESULTS: Among 322,044 individuals, 826 developed COVID-19 infection. Among people using ACEI/ARBs, 204/56,105 developed COVID-19 (3.6 per 1,000 individuals) compared with 622/265,939 without ACEI/ARB use (2.3 per 1,000), yielding an adjusted OR of 0.91 (95% CI 0.74-1.12). For use of <1 defined daily dose (DDD) vs. nonuse, the adjusted OR for infection was 0.92 (95% CI 0.66-1.28); for 1 to <2 DDDs, 0.89 (95% CI 0.66-1.19); and for ≥2 DDDs, 0.92 (95% CI 0.72-1.18). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 26% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.98 (95% CI 0.63-1.54), and there was no association with dose. CONCLUSIONS: These findings support current recommendations that individuals on these medications continue their use.

Renin-angiotensin-aldosterone system inhibitors and COVID-19 infection or hospitalization: a cohort study.

There are plausible mechanisms by which angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of COVID-19 infection or affect disease severity. To examine the association between these medications and COVID-19 infection or hospitalization, we conducted a retrospective cohort study within a US integrated healthcare system. Among people aged ≥18 years enrolled in the health plan for at least 4 months as of 2/29/2020, current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate adjusted odds ratios (ORs) and 95% confidence intervals. Among 322,044 individuals, 720 developed COVID-19 infection. Among people using ACEI/ARBs, 183/56,105 developed COVID-19 (3.3 per 1000 individuals) compared with 537/265,939 without ACEI/ARB use (2.0 per 1000), yielding an adjusted OR of 0.94 (95% CI 0.75-1.16). For use of < 1 defined daily dose vs. nonuse, the adjusted OR for infection was 0.89 (95% CI 0.62-1.26); for 1 to < 2 defined daily doses, 0.97 (95% CI 0.71-1.31); and for ≥2 defined daily doses, 0.94 (95% CI 0.72-1.23). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 29% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.92 (95% CI 0.54-1.57), and there was no association with dose. These findings support current recommendations that individuals on these medications continue their use.

Identifying hypertension in pregnancy using electronic medical records: The importance of blood pressure values.

OBJECTIVE: To incorporate blood pressure (BP), diagnoses codes, and medication fills from electronic medical records (EMR) to identify pregnant women with hypertension. STUDY DESIGN: A retrospective cohort study of singleton pregnancies at three US integrated health delivery systems during 2005-2014. MAIN OUTCOME MEASURES: Women were considered hypertensive if they had any of the following: (1) ≥2 high BPs (≥140/90 mmHg) within 30 days during pregnancy (High BP); (2) an antihypertensive medication fill in the 120 days before pregnancy and a hypertension diagnosis from 1 year prior to pregnancy through 20 weeks gestation (Treated Chronic Hypertension); or (3) a high BP, a hypertension diagnosis, and a prescription fill within 7 days during pregnancy (Rapid Treatment). We described characteristics of these pregnancies and conducted medical record review to understand hypertension presence and severity. RESULTS: Of 566,624 pregnancies, 27,049 (4.8%) met our hypertension case definition: 24,140 (89.2%) with High BP, 5,409 (20.0%) with Treated Chronic Hypertension, and 5,363 (19.8%) with Rapid Treatment (not mutually exclusive). Of hypertensive pregnancies, 19,298 (71.3%) received a diagnosis, 9,762 (36.1%) received treatment and 11,226 (41.5%) had a BP ≥ 160/110. In a random sample (n = 55) of the 7,559 pregnancies meeting the High BP criterion with no hypertension diagnosis, clinical statements about hypertension were found in medical records for 58% of them. CONCLUSION: Incorporating EMR BP identified many pregnant women with hypertension who would have been missed by using diagnosis codes alone. Future studies should seek to incorporate BP to study treatment and outcomes of hypertension in pregnancy.

Impact of initiatives to reduce prescription opioid risks on medically attended injuries in people using chronic opioid therapy.

PURPOSE: The purpose of the study is to determine whether initiatives to improve the safety of opioid prescribing decreased injuries in people using chronic opioid therapy (COT). METHODS: We conducted an interrupted time series analysis using data from Group Health (GH), an integrated health care delivery system in the United States. In 2007, GH implemented initiatives which substantially reduced daily opioid dose and increased patient monitoring. Among GH members age 18 or older receiving COT between 2006 and 2014, we compared injury rates for patients in GH's integrated group practice (IGP; exposed to the initiatives) vs patients cared for by contracted providers (not exposed). Injuries were identified using a validated algorithm. We calculated injury incidence during the baseline (preintervention) period from 2006 to 2007; the dose reduction period, 2008 to 2010; and the risk stratification and monitoring period, 2010 to 2014. Using modified Poisson regression, we estimated adjusted relative risks (RRs) representing the relative change per year in injury rates. RESULTS: Among 21 853 people receiving COT in the IGP and 8260 in contracted care, there were 2679 injuries during follow-up. The baseline injury rate was 1.0% per calendar quarter in the IGP and 0.9% in contracted care. Risk reduction initiatives did not decrease injury rates: Within the IGP, the RR in the dose reduction period was 1.01 (95% CI, 0.95-1.07) and in the risk stratification and monitoring period, 0.99 (95% CI, 0.95-1.04). Injury trends did not differ between the two care settings. CONCLUSIONS: Risk reduction initiatives did not decrease injuries in people using COT.

Self-Reported Suicidal Ideation as a Predictor of Suicidal Behavior Among Outpatients With Diagnoses of Psychotic Disorders.

OBJECTIVE: Individuals with psychotic disorders are at high risk of suicidal behavior. The study examined whether response to item 9 of the Patient Health Questionnaire (PHQ-9), which asks about thoughts of death or self-harm, predicts suicidal behavior among outpatients with diagnoses of psychotic disorders. METHODS: Electronic health records (EHRs) from seven large integrated health systems were used to identify all outpatient visits by adults with a diagnosis of schizophrenia spectrum psychosis or unspecified psychosis from January 1, 2009, to June 30, 2015, during which a PHQ-9 was completed (N=32,982 visits by 5,947 patients). Suicide attempts over the 90 days following each visit were ascertained from EHRs and insurance claims. Suicide deaths were ascertained from state death certificate files. RESULTS: Risk of suicide attempt within 90 days of an outpatient visit was .8% among patients reporting no thoughts of death or self-harm and 3.5% among those reporting such thoughts "nearly every day." Over 90 days of follow-up, 47% of suicide attempts occurred among those who reported any recent thoughts of death or self-harm at the sampled visit. Also, 59% of attempts occurred among those reporting thoughts of death or self-harm at the index visit or any visit in the prior year. The number of suicide deaths within 90 days (N=10) was too small to accurately assess the relationship between PHQ-9 item 9 response and subsequent suicide death. CONCLUSIONS: Among outpatients with psychotic disorders, response to item 9 of the PHQ-9 accurately identified those at increased short-term risk of a suicide attempt.

Does Patient Adherence to Antidepressant Medication Actually Vary Between Physicians?

OBJECTIVE: Previous research and improvement efforts have presumed that patients' nonadherence to antidepressant medication reflects physicians' quality of care. We used population-based health records to examine whether adherence to antidepressant medication actually varies between prescribing physicians. METHODS: Electronic health records and insurance claims data from 5 integrated health systems in Washington, Idaho, Minnesota, Colorado, Hawaii, and California were used to identify 150,318 adults starting new episodes of antidepressant treatment for depression between January 1, 2010, and December 31, 2012. Early adherence was defined as any refill or dispensing of antidepressant medication in the 180 days following an initial antidepressant prescription. Patient-level demographic and clinical characteristics potentially associated with adherence were identified from health system records. RESULTS: Average probability of early adherence was 82% for psychiatrists and 74% for primary care physicians. Among individual physicians, the range of raw or unadjusted early adherence rates (5th to 95th percentiles) was from 33% to 100% for psychiatrists and from 0% to 100% for primary care physicians. After accounting for sampling variation and case mix differences, the range of adjusted early adherence rates (5th to 95th percentiles) was from 72% to 78% for psychiatrists and from 64% to 69% for primary care physicians. CONCLUSIONS: After accounting for sampling variation and case mix differences, early adherence to antidepressant medication varies minimally among prescribing physicians. Early discontinuation of antidepressant treatment is not an appropriate measure of individual physician performance, and efforts to improve adherence should emphasize system-level interventions rather than the performance of individual physicians.

A Prospective Study of Predictors of Long-term Opioid Use Among Patients With Chronic Noncancer Pain.

BACKGROUND: Chronic pain patients at increased risk of unfavorable pain and opioid misuse outcomes may be those most likely to use opioids long-term, but this has not been evaluated prospectively. OBJECTIVES: To ascertain whether pain prognostic risk, problem opioid use risk, and depression predict opioid use 1 year later among patients recently initiating opioid therapy with a moderate likelihood of long-term opioid use. MATERIALS AND METHODS: Self-report and electronic health record data were collected from patients aged 45+ years who recently initiated opioid therapy (N=762), in an integrated health care system. Logistic regression models tested whether baseline patient chronic pain prognostic risk, problem opioid use risk, depression, and expectations concerning continued opioid use independently predicted continuing use at 1 year (≥30 d supply in the prior 4 mo). RESULTS: At 1 year, 46% of participants continued to use opioids. Baseline problem opioid use risk score (adjusted odds ratio, 1.15; 95% confidence interval, 1.04-1.26) and expectations about continuing opioid use, but not pain prognostic risk score or depression, were significant predictors of 1-year opioid use. Compared with patients who thought continued opioid use unlikely, those who thought it was extremely or very likely had 4 times the odds of opioid use at 1 year (adjusted odds ratio, 4.05; 95% confidence interval, 2.59-6.31). DISCUSSION: The strongest predictors of long-term opioid use were not patient-related or medication-related factors, but expectations about using opioids in the future. Asking about such expectations may be the easiest way to identify patients likely to continue opioid use long-term.

Antidepressants are not overprescribed for mild depression.

OBJECTIVE: To evaluate overprescribing of antidepressant medication for minimal or mild depression. METHOD: Electronic records data from 4 large health care systems identified outpatients aged 18 years or older starting a new episode of antidepressant treatment in 2011 with an ICD-9 diagnosis of depressive disorder (296.2, 296.3, 311, or 300.4). Patient Health Questionnaire-9 (PHQ-9) depression severity scores at time of treatment initiation were used to examine the distribution of baseline severity and the association between baseline severity and patients' demographic and clinical characteristics. RESULTS: Of 19,751 adults beginning treatment in 2011, baseline PHQ-9 scores were available for 7,051. In those with a baseline score, 85% reported moderate or severe symptoms (PHQ-9 score of 10 or more), 12% reported mild symptoms (PHQ-9 score of 5 to 9), and 3% reported minimal symptoms (PHQ-9 score of less than 5). The proportion reporting minimal or mild symptoms when starting treatment increased with age, ranging from 11% in those under age 65 years to 26% in those aged 65 and older. The proportion with minimal or mild symptoms was also moderately higher among patients living in wealthier neighborhoods and those treated by psychiatrists. Nevertheless, across all subgroups defined by sex, race/ethnicity, prescriber specialty, and treatment history, the proportions with minimal or mild symptoms did not exceed 18%. Secondary analyses, including weighting and subgroup analyses, found no evidence that estimates of baseline severity were biased by missing PHQ-9 scores. CONCLUSIONS: In these health systems, prescribing of antidepressant medication for minimal or mild depression is much less common than suggested by previous reports. Given that this practice may sometimes be clinically appropriate, our findings indicate that overprescribing of antidepressants for mild depression is not a significant public health concern.

Sex and Age Differences in Global Pain Status Among Patients Using Opioids Long Term for Chronic Noncancer Pain.

BACKGROUND: The use of chronic opioid therapy (COT) has risen dramatically in recent years, especially among women. However, little is known about factors influencing overall pain and function (global pain status) among COT users. Characterizing the typical experiences of COT patients by age-sex group could help clinicians and patients better weigh the risks and benefits of COT. Thus, we sought to characterize global pain status among COT users in community practice by age and sex. METHODS: Telephone survey of 2,163 health plan members aged 21-80 years using COT. We assessed average/usual pain (0-10 scale); pain-related interference (0-10); activity limitation days, last 3 months; and pain impact, last 2 weeks (0-11). Status on each indicator was classified as low (better pain/function), moderate, or high (worse pain/function). Global pain status was categorized as favorable if 2-4 indicators were low and 0-1 was high and unfavorable if 2-4 indicators were high and 0-1 was low. RESULTS: Among female COT patients, 15% (vs. 26% of males) had favorable global pain status and 59% (vs. 42% of males) had unfavorable status. Under age 65 years, women fared more poorly than men on every indicator. Among 65- to 80-year-olds, women and men had similar global pain status. CONCLUSIONS: Although pain and function among COT users vary considerably, only one in five reported low pain levels and high levels of function. Young and middle-aged women seem to be at particularly high risk for unfavorable global pain status. More research is needed about how to best manage pain in this group.

Chronic opioid therapy risk reduction initiative: impact on urine drug testing rates and results.

BACKGROUND: In response to epidemic levels of prescription opioid overdose, abuse, and diversion, routine urine drug tests (UDTs) are recommended for patients receiving chronic opioid therapy (COT) for chronic pain. However, UDT ordering for COT patients is inconsistent in primary care, and little is known about how to increase UDT ordering or the impact of increased testing on rates of aberrant results. OBJECTIVE: To compare rates and results of UDTs for COT patients before versus after implementation of an opioid risk reduction initiative in a large healthcare system. DESIGN: Pre-post observational study. PATIENTS: Group Health patients on COT October 2008-September 2009 (N = 4,821), October 2009-September 2010 (N = 5,081), and October 2010-September 2011 (N = 5,498). INTERVENTION: Multi-faceted opioid risk reduction initiative. MAIN MEASURES: Annual rates of UDTs and UDT results. KEY RESULTS: Half of COT patients received at least one UDT in the year after the initiative was implemented, compared to only 7 % 2 years prior. The adjusted odds of COT patients having at least one UDT in the first year of the opioid initiative were almost 16 times (adjusted OR = 15.79; 95 % CI: 13.96-17.87) those 2 years prior. The annual rate of UDT detection of marijuana and illicit drugs did not change (12.6 % after initiative implementation), and largely reflected marijuana use (detected in 11.1 % of all UDTs in the year after initiative implementation). In the year after initiative implementation, 10.7 % of UDTs were negative for opioids. CONCLUSIONS: The initiative appeared to dramatically increase urine drug testing of COT patients in the healthcare system without impacting rates of aberrant results. The large majority of aberrant results reflected marijuana use or absence of opioids in the urine. The utility of increased urine drug testing for COT patient safety and prevention of diversion remains uncertain.