Extracting forced vital capacity from the electronic health record through natural language processing in rheumatoid arthritis-associated interstitial lung disease.

PURPOSE: To develop a natural language processing (NLP) tool to extract forced vital capacity (FVC) values from electronic health record (EHR) notes in patients with rheumatoid arthritis-interstitial lung disease (RA-ILD). METHODS: We selected RA-ILD patients (n = 7485) in the Veterans Health Administration (VA) between 2000 and 2020 using validated ICD-9/10 codes. We identified numeric values in proximity to FVC string patterns from clinical notes in the EHR. Subsequently, we performed processing steps to account for variability in note structure, related pulmonary function test (PFT) output, and values copied across notes, then assigned dates from linked administrative procedure records. NLP-derived FVC values were compared to values recorded directly from PFT equipment available on a subset of patients. RESULTS: We identified 5911 FVC values (n = 1844 patients) from PFT equipment and 15 383 values (n = 4982 patients) by NLP. Among 2610 date-matched FVC values from NLP and PFT equipment, 95.8% of values were within 5% predicted. The mean (SD) difference was 0.09% (5.9), and values strongly correlated (r = 0.94, p < 0.001), with a precision of 0.87 (95% CI 0.86, 0.88). NLP captured more patients with longitudinal FVC values (n = 3069 vs. n = 1164). Mean (SD) change in FVC %-predicted per year was similar between sources (-1.5 [30.0] NLP vs. -0.9 [16.6] PFT equipment; standardized response mean = 0.05 for both). CONCLUSIONS: NLP of EHR notes increases the capture of accurate, longitudinal FVC values by three-fold over PFT equipment. Use of this NLP tool can facilitate pharmacoepidemiologic research in RA-ILD and other lung diseases by capturing this critical measure of disease severity.

Serum alarmins and the risk of incident interstitial lung disease in rheumatoid arthritis.

OBJECTIVES: To quantify associations of serum alarmins with risk of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). METHODS: Using serum collected at enrolment, three alarmins (interleukin [IL]-33, thymic stromal lymphopoietin [TSLP], and IL-25) were measured in a multicentre prospective RA cohort. ILD was classified using systematic medical record review. Cross-sectional associations of log-transformed (IL-33, TSLP) or quartile (IL-25) values with RA-ILD at enrolment (prevalent RA-ILD) were examined using logistic regression, while associations with incident RA-ILD developing after enrolment were examined using Cox proportional hazards. Covariates in multivariate models included age, sex, race, smoking status, RA disease activity score, and anti-cyclic citrullinated antibody positivity. RESULTS: Of 2,835 study participants, 115 participants (4.1%) had prevalent RA-ILD at baseline and an additional 146 (5.1%) developed incident ILD. There were no associations between serum alarmin concentrations and prevalent ILD in unadjusted or adjusted logistic regression models. In contrast, there was a significant inverse association between IL-33 concentration and the risk of developing incident RA-ILD in unadjusted (HR 0.73 per log-fold increase; 95% CI 0.57-0.95; p= 0.018) and adjusted (HR 0.77; 95% CI 0.59-1.00, p= 0.047) models. No significant associations of TSLP or IL-25 with incident ILD were observed. CONCLUSIONS: In this study, we observed a significant inverse association between serum IL-33 concentration and the risk of developing incident RA-ILD, but no associations with prevalent ILD. Additional investigation is required to better understand the mechanisms driving this relationship and how serum alarmin IL-33 assessment might contribute to clinical risk stratification in patients with RA.

Risk of Total Wrist Arthrodesis Following Proximal Row Carpectomy: An Analysis of 1,070 Patients.

PURPOSE: Proximal row carpectomy (PRC) is a motion-sparing procedure with good patient-reported and clinical outcomes. Although some studies have investigated the risk of conversion to total wrist arthrodesis (TWA) after PRC, additional larger studies evaluating the specific risk factors that lead to failure are required. This study aimed to investigate the patient and procedure factors that are associated with increased risk for conversion to TWA in a large cohort of patients who underwent PRC. METHODS: The current procedural technology codes identified patients in a National Veteran's Health database undergoing a PRC over a 26-year period. Risk factors of interest comprised age, posterior interosseous nerve neurectomy, wrist arthritis pattern, bilateral surgery, smoking, comorbidities, and preoperative opioid use. The primary outcome was the rate of conversion to TWA. Cox proportional hazard regression was used to create hazard ratios of selected factors for reoperation. RESULTS: There were 1,070 PRCs performed, with a mean follow-up of 79.8 ± 59.6 months. A total of 5.3% (57/1,070) wrists underwent conversion to TWA. Younger age at the time of PRC (<50 years) significantly increased the risk of TWA (hazard ratio, 3.8; 95% confidence interval, 2.2-6.6). With every 1-year increase in age, there was a reduction of 4% (hazard ratio, 0.96; 95% confidence interval: 0.94-0.98) in the hazard of conversion to TWA. No other factors, including concomitant posterior interosseous nerve neurectomy or bilateral PRC, increased the risk of conversion to TWA. CONCLUSIONS: Proximal row carpectomy is a motion-preserving salvage procedure with a low rate of conversion to wrist arthrodesis. Younger patient age increases the risk of conversion to arthrodesis, whereas posterior interosseous nerve neurectomy, bilateral PRCs, and comorbidity status do not appear to have an impact on the risk of arthrodesis. TYPE OF STUDY/LEVEL OF EVIDENCE: Prognostic II.

Estimating the optimal individualized treatment rule from a cost-effectiveness perspective.

Optimal individualized treatment rules (ITRs) provide customized treatment recommendations based on subject characteristics to maximize clinical benefit in accordance with the objectives in precision medicine. As a result, there is growing interest in developing statistical tools for estimating optimal ITRs in evidence-based research. In health economic perspectives, policy makers consider the tradeoff between health gains and incremental costs of interventions to set priorities and allocate resources. However, most work on ITRs has focused on maximizing the effectiveness of treatment without considering costs. In this paper, we jointly consider the impact of effectiveness and cost on treatment decisions and define ITRs under a composite-outcome setting, so that we identify the most cost-effective ITR that accounts for individual-level heterogeneity through direct optimization. In particular, we propose a decision-tree-based statistical learning algorithm that uses a net-monetary-benefit-based reward to provide nonparametric estimations of the optimal ITR. We provide several approaches to estimating the reward underlying the ITR as a function of subject characteristics. We present the strengths and weaknesses of each approach and provide practical guidelines by comparing their performance in simulation studies. We illustrate the top-performing approach from our simulations by evaluating the projected 15-year personalized cost-effectiveness of the intensive blood pressure control of the Systolic Blood Pressure Intervention Trial (SPRINT) study.

A new methodological framework for hazard detection models in health information technology systems.

The adoption of health information technology (HIT) has facilitated efforts to increase the quality and efficiency of health care services and decrease health care overhead while simultaneously generating massive amounts of digital information stored in electronic health records (EHRs). However, due to patient safety issues resulting from the use of HIT systems, there is an emerging need to develop and implement hazard detection tools to identify and mitigate risks to patients. This paper presents a new methodological framework to develop hazard detection models and to demonstrate its capability by using the US Department of Veterans Affairs' (VA) Corporate Data Warehouse, the data repository for the VA's EHR. The overall purpose of the framework is to provide structure for research and communication about research results. One objective is to decrease the communication barriers between interdisciplinary research stakeholders and to provide structure for detecting hazards and risks to patient safety introduced by HIT systems through errors in the collection, transmission, use, and processing of data in the EHR, as well as potential programming or configuration errors in these HIT systems. A nine-stage framework was created, which comprises programs about feature extraction, detector development, and detector optimization, as well as a support environment for evaluating detector models. The framework forms the foundation for developing hazard detection tools and the foundation for adapting methods to particular HIT systems.

Real-world practice patterns and outcomes in Veterans with relapsed/refractory diffuse large B-cell lymphoma.

Aim: To describe practices and outcomes in veterans with relapsed/refractory diffuse large B-cell lymphoma. Patients & methods: Using Veteran Affairs Cancer Registry System and electronic health record data, we identified relapsed/refractory diffuse large B-cell lymphoma patients completing second-line treatment (2L) in 2000-2016. Treatments were classified as aggressive/nonaggressive. Analyses included descriptive statistics and the Kaplan-Meier estimation of progression-free survival and overall survival. Results: Two hundred and seventy patients received 2L. During median 9.7-month follow-up starting from 2L, 470 regimens were observed, averaging 2.7 regimens/patient: 219 aggressive, 251 nonaggressive. One hundred and twenty-one patients proceeded to third-line, 50 to fourth-line and 18 to fifth-line treatment. Median progression-free survival in 2L was 5.2 months. Median overall survival was 9.5 months. Forty-four patients (16.3%) proceeded to bone marrow transplant. Conclusion: More effective, less toxic treatments are needed and should be initiated earlier in treatment trajectory.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology.

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co-administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

Pharmacist-led collaborative medication management programs for oral antineoplastic therapies: A systematic literature review.

OBJECTIVES: The aim of this systematic review is to summarize the structure, process, and outcomes of pharmacist-led collaborative medication management programs for oral antineoplastic therapies (OATs). METHODS: Included studies were peer-reviewed journal articles published in English, between January 2000 to May 2020, and reporting on pharmacist-led collaborative medication management programs for patients on OATs. To be included, studies had to report on the pharmacy practice model, pharmacist interventions, and outcomes of the medication management program. The Donabedian model informed the data extraction and summary. Two independent researchers assessed the risk of bias (confounding) for all included studies (n = 12) using the NIH tool and Cochrane ROBINS-I for observational research. RESULTS: There were 12 studies that met inclusion criteria. The structure of the programs included hiring oncology pharmacists to deliver interventions, standardized templates for electronic medical record documentation, and administrative workflow changes (e.g., automatic referrals). The most common pharmacist interventions (processes) were patient education and counseling, adverse event monitoring, and dose modifications. All studies reported one or more positive outcomes, including improved patient adherence, safety, cost savings, cost avoidance, and patient satisfaction. All included studies used an observational study designs, and the majority of studies had moderate to high risk of bias. CONCLUSION: The evidence suggests that pharmacist-led collaborative medication management programs may have beneficial clinical and economic outcomes. The implementation of these programs could be strengthened by using a conceptual framework to guide program development, implementation, and evaluation and effectiveness-hybrid study designs to assess clinical and implementation outcomes. The risk of bias should be addressed by using more robust study designs and rigorous data collection and analysis methods.

Perioperative Continuation of Biologic Medications Increases Odds of Periprosthetic Joint Infection in Patients With Inflammatory Arthropathy.

BACKGROUND: Rates of prosthetic joint infection (PJI) are elevated among patients with inflammatory arthropathy (IA). The effect of continuing biologic drugs perioperatively with regard to PJI is unknown. The purpose of this study is to compare rates of perioperative biologic continuation in IA patients who did and did not develop PJI after primary total joint arthroplasty (TJA). METHODS: All cases of PJI within 1 year of primary TJA in IA patients on biologic medications were retrospectively reviewed from 2005 to 2018 in the US Veterans Affairs Corporate Data Warehouse. Matched controls who did not develop PJI after TJA were populated from the same database. Biologic suspension, defined as medication interruption prior to TJA with surgery occurring after the end of the dosing cycle and resumption after wound healing, was compared among cases and controls. RESULTS: Biologic medications were continued through surgery in 35% (9/26) of patients who developed PJI compared to 14% (8/58) of controls (P = .031; adjusted odds ratio of 3.46 [1.11-10.78]). No significant difference existed among cases (n = 26) and controls (n = 58) for age, gender, procedure, body mass index, rates of diabetes or chronic kidney disease, smoking status, or preoperative opioid use (all P > .05). CONCLUSION: With the limited sample sizes available in this study, we found an association with perioperative continuation of biologic medications and PJI. This data may provide support for current guidelines from the American Association of Hip and Knee Surgeons to withhold biologics before TJA with surgery scheduled at the end of the dosing cycle and medication resumption only after wound healing.

An increased mortality risk is associated with abnormal iron status in diabetic and non-diabetic Veterans with predialysis chronic kidney disease.

Iron parameters have not been well characterized in pre-dialysis patients with chronic kidney disease (CKD), and it remains unclear if abnormal iron balance is associated with increased mortality. Therefore, we performed a historical cohort study using data from the Veterans Affairs Corporate Data Warehouse to evaluate the relationship between iron status and mortality. We identified a pre-dialysis CKD cohort with at least one set of iron indices between 2006-2015. The cohort was divided into four iron groups based on the joint quartiles of serum transferrin saturation (percent) and ferritin concentration (ng/ml): reference (16-28%, 55-205 ng/ml), low iron (0.4-16%, 0.4-55 ng/ml), high iron (28-99.6%, 205-4941 ng/ml), and function iron deficiency (0.8-16%, 109-2783 ng/ml). We compared mortality risk between the iron groups using matching weights based on multinomial propensity score models and Poisson rate-based regression. We also evaluated if the association between iron groups and mortality differs between the diabetic and non-diabetic subgroups. Of the 80,067 eligible veterans, 32,489 were successfully matched. During the mean follow-up period of 4.0 years, adjusted relative rate (95% confidence interval) for all-cause mortality in three abnormal iron groups were increased compared to the reference: functional iron deficiency [1.21 (1.17, 1.25)], low iron [1.10 (1.07, 1.14)], and high iron [1.09 (1.06, 1.13)]. The mortality risk was similar between diabetic and non-diabetic subgroups for each iron group. Thus, an abnormal iron balance, particularly functional iron deficiency, is associated with increased mortality in CKD.

Utility of administrative and clinical data to predict major change in medical treatment in US Veterans enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry.

OBJECTIVES: To examine factors associated with major therapeutic changes (MTC) among US Veterans with moderate/severe rheumatoid arthritis (RA) based on Disease Activity Score based on 28 joints (DAS28). METHODS: We used data from patients enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry from 1/1/2006 through 12/31/2014. The index date was a clinic visit with DAS28 >3.2 (moderate/severe disease) following an 18-month pre-index period that included ≥2 DAS28 measurements ≥60 days apart. The patients were followed for MTC from 7 days pre-index through 90 days post-index. Poisson multivariable regression models were used to identify associations with MTC. Chart review of a subset of randomly selected patients explored factors that impacted therapeutic decisions. RESULTS: Among 941 patients, 396 (42.1%) had MTC. Of these, 369 (39.2%) patients had worsening DAS28 at index, 118 (12.5%) had DAS28 improvements, and 454 (48.2%) patients had no change in DAS28 versus pre-index DAS28. Of the patients with worsening DAS28, no change in DAS28, and improved DAS28, respectively, 50.5%, 62.6%, and 70.3% had no MTC. Regression analyses showed index DAS28, oral steroid or non-biologic disease-modifying anti-rheumatic drug (nbDMARD) use in the previous year were associated with an increased likelihood of MTC; use of nbDMARDs in the previous 90 days was associated with a decreased likelihood of MTC. The most common reason for not modifying therapy despite DAS28 >3.2 was a judgement of mild disease. CONCLUSIONS: Clinicians frequently do not institute major therapeutic changes despite DAS28 indicating moderate/severe disease activity; multiple factors are involved in real-world treatment decisions.

Body mass index and persistence of conventional DMARDs and TNF inhibitors in rheumatoid arthritis.

OBJECTIVES: Obese patients with rheumatoid arthritis (RA) may be more likely to discontinue therapy than non-obese patients, possibly signifying a more refractory phenotype. The purpose of this study was to examine the association between body mass index (BMI) and discontinuation rates for different RA treatments accounting for confounding factors. METHODS: Veterans Affairs administrative databases were used to define initial courses of methotrexate (MTX), hydroxychloroquine, sulfasalazine, prednisone, and self-injectable tumour necrosis factor inhibitors (TNFi). Discontinuation was defined as a lapse in drug refill >90 days. Using overweight BMI (25-30 kg/m2) as the referent group, multivariable Cox proportional hazards models were used to evaluate associations between BMI category and time to treatment discontinuation. RESULTS: There were 46,970 initial RA treatment courses identified from 2005-2014 among 23,669 Veterans with RA. In multivariable models, severe obesity (BMI >35 kg/m2), compared to overweight BMI, was not associated with treatment discontinuation with the exception of prednisone [HR 1.10 (1.04, 1.17) p<0.001]. Patients with low (<20 kg/m2) and normal BMI (20-25 kg/m2) were more likely to discontinue MTX, TNFi, and HCQ compared to overweight patients. Other factors associated with earlier MTX and/or TNFi discontinuation included female sex, black race, greater comorbidity, depression, malignancy, congestive heart failure, current smoking, and more recent calendar year. CONCLUSIONS: Obesity was not associated with therapy discontinuation among veterans with RA after accounting for confounding factors, suggesting that obesity is not a biological mediator of more refractory disease. Conversely, low BMI, comorbidity, and depression were identified as important predictors of drug discontinuation.

Cohort identification of axial spondyloarthritis in a large healthcare dataset: current and future methods.

BACKGROUND: Big data research is important for studying uncommon diseases in real-world settings. Most big data studies in axial spondyloarthritis (axSpA) have been limited to populations identified with billing codes for ankylosing spondylitis (AS). axSpA is a more inclusive concept, and reliance on AS codes does not produce a comprehensive axSpA study population. The first objective was to describe our process for establishing an appropriate sample of patients with and without axSpA for developing accurate axSpA identification methods. The second objective was to determine the classification performance of AS billing codes against the chart-reviewed axSpA reference standard. METHODS: Veteran Health Affairs clinical and administrative data, between January 2005 and June 2015, were used to randomly select patients with clinical phenotypes that represented high, moderate, and low likelihoods of an axSpA diagnosis. With chart review, the sampled patients were classified as Yes axSpA, No axSpA or Uncertain axSpA, and these classification assignments were used as the reference standard for determining the positive predictive value (PPV) and sensitivity of AS ICD-9 codes for axSpA. RESULTS: Six hundred patients were classified as Yes axSpA (26.8%), No axSpA (68.3%), or Uncertain axSpA (4.8%). The PPV and sensitivity of an AS ICD-9 code for axSpA were 83.3% and 57.3%, respectively. CONCLUSIONS: Standard methods of identifying axSpA patients in a large dataset lacked sensitivity. An appropriate sample of patients with and without axSpA was established and characterized for developing novel axSpA identification methods that are anticipated to enable previously impractical big data research.

Evidence generation from healthcare databases: recommendations for managing change.

There is an increasing reliance on databases of healthcare records for pharmacoepidemiology and other medical research, and such resources are often accessed over a long period of time so it is vital to consider the impact of changes in data, access methodology and the environment. The authors discuss change in communication and management, and provide a checklist of issues to consider for both database providers and users. The scope of the paper is database research, and changes are considered in relation to the three main components of database research: the data content itself, how it is accessed, and the support and tools needed to use the database. Copyright © 2016 John Wiley & Sons, Ltd.

The use of natural language processing on narrative medication schedules to compute average weekly dose.

PURPOSE: Medications with non-standard dosing and unstandardized units of measurement make the estimation of prescribed dose difficult from pharmacy dispensing data. A natural language processing tool named the SIG extractor was developed to identify and extract elements from narrative medication instructions to compute average weekly doses (AWDs) for disease-modifying antirheumatic drugs. The goal of this paper is to evaluate the performance of the SIG extractor. METHOD: This agreement study utilized Veterans Health Affairs pharmacy data from 2008 to 2012. The SIG extractor was designed to extract key elements from narrative medication schedules (SIGs) for 17 select medications to calculate AWD, and these medications were categorized by generic name and route of administration. The SIG extractor was evaluated against an annotator-derived reference standard for accuracy, which is the fraction of AWDs accurately computed. RESULTS: The overall accuracy was 89% [95% confidence interval (CI) 88%, 90%]. The accuracy was ≥85% for all medications and route combinations, except for cyclophosphamide (oral) and cyclosporine (oral), which were 79% (95%CI 72%, 85%) and 66% (95%CI 58%, 73%), respectively. CONCLUSIONS: The SIG extractor performed well on the majority of medications, indicating that AWD calculated by the SIG extractor can be used to improve estimation of AWD when dispensed quantity or days' supply is questionable or improbable. The working model for annotating SIGs and the SIG extractor are generalized and can easily be applied to other medications. Copyright © 2016 John Wiley & Sons, Ltd.

Mortality associated with lithium and valproate treatment of US Veterans Health Administration patients with mental disorders.

BackgroundThe mood stabilisers lithium and valproate might plausibly have differing associations with mortality because of differing effects on mental health and various physiological indicators.AimsTo assess associations between lithium, valproate and non-suicide mortality.MethodIntention-to-treat, propensity score-matched cohort study.ResultsLithium was associated with significantly reduced non-suicide mortality in the intent-to-treat cohort over 0-90 days (hazard ratio (HR) = 0.67, 95% CI 0.51-0.87) but not longer. In secondary analyses, a sizeable reduction in mortality was observed during active treatment with lithium across all time periods studied (for example 365-day HR = 0.62, 95% CI 0.45-0.84), but significantly increased risks were observed among patients discontinuing lithium by 180 days (HR = 1.54, 95% CI 1.01-2.37).ConclusionsPatients initiating lithium had lower non-suicide mortality over 0-90 days than patients initiating valproate and consistently lower non-suicide mortality among patients maintaining treatment, but elevated risk among patients discontinuing treatment by 180 days. Although residual confounding or selection effects cannot be excluded, this study suggests potential benefits to enhancing lithium treatment persistence and the monitoring of patients discontinuing lithium. There is a need for further research.

Propofol is associated with favorable outcomes compared with benzodiazepines in ventilated intensive care unit patients.

RATIONALE: Mechanically ventilated intensive care unit (ICU) patients are frequently managed using a continuous-infusion sedative. Although recent guidelines suggest avoiding benzodiazepines for sedation, this class of drugs is still widely used. There are limited data comparing sedative agents in terms of clinical outcomes in an ICU setting. OBJECTIVES: Comparison of propofol to midazolam and lorazepam in adult ICU patients. METHODS: Data were obtained from a multicenter ICU database (2003-2009). Patient selection criteria included age greater than or equal to 18 years, single ICU admission with single ventilation event (>48 h), and treatment with continuously infused sedation (propofol, midazolam, or lorazepam). Propensity score analysis (1:1) was used and mortality measured. Cumulative incidence and competing risk methodology were used to examine time to ICU discharge and ventilator removal. MEASUREMENTS AND MAIN RESULTS: There were 2,250 propofol-midazolam and 1,054 propofol-lorazepam matched patients. Hospital mortality was statistically lower in propofol-treated patients as compared with midazolam- or lorazepam-treated patients (risk ratio, 0.76; 95% confidence interval [CI], 0.69-0.82 and risk ratio, 0.78; 95% CI, 0.68-0.89, respectively). Competing risk analysis for 28-day ICU time period showed that propofol-treated patients had a statistically higher probability for ICU discharge (78.9% vs. 69.5%; 79.2% vs. 71.9%; P < 0.001) and earlier removal from the ventilator (84.4% vs. 75.1%; 84.3% vs. 78.8%; P < 0.001) when compared with midazolam- and lorazepam-treated patients, respectively. CONCLUSIONS: In this large, propensity-matched ICU population, patients treated with propofol had a reduced risk of mortality and had both an increased likelihood of earlier ICU discharge and earlier discontinuation of mechanical ventilation.

Specialty of prescribers associated with prescription opioid fatalities in Utah, 2002-2010.

UNLABELLED: Opioid adverse events are widespread, and deaths have been directly attributed to opioids prescribed by medical professionals. Little information exists on the amount of opioids various medical specialties prescribe and the opioid fatality rate that would be expected if prescription opioid-related deaths were independent of medical specialty. OBJECTIVE: To compute the incidence of prescription opioid fatalities by medical specialty in Utah and to calculate the attributable risk (AR) of opioid fatality by medical specialty. DESIGN: Prevalence database study design linking the Utah Controlled Substance Database (CSD) for prescribing data with the Utah Medical Examiner data to identify prescription opioid fatalities. AR were calculated for each medical specialty and year. RESULTS: Opioid prescriptions are common with 23,302,892 recorded in the CSD for 2002-2010, 0.64% of which were associated with a fatality. We attached specialty to 90.2% of opioid prescriptions. Family medicine and internal medicine physicians wrote the largest proportion of prescriptions (24.1% and 10.8%) and were associated with the greatest number of prescription opioid fatalities. The number of active prescriptions at time of death decreased each year. The AR of fatality by provider specialty varied each year with some specialties, such as pain medicine and anesthesiology, consistently associated with more fatalities per 1,000 opioid prescriptions than internal medicine physicians the same year. CONCLUSIONS: Primary care providers were the most frequent prescribers and the most often associated with opioid fatalities and should be targeted for education about safe prescribing along with specialties that prescribe less frequently but are associated with a positive AR for opioid fatality.

Suicide risk in Veterans Health Administration patients with mental health diagnoses initiating lithium or valproate: a historical prospective cohort study.

BACKGROUND: Lithium has been reported in some, but not all, studies to be associated with reduced risks of suicide death or suicidal behavior. The objective of this nonrandomized cohort study was to examine whether lithium was associated with reduced risk of suicide death in comparison to the commonly-used alternative treatment, valproate. METHODS: A propensity score-matched cohort study was conducted of Veterans Health Administration patients (n=21,194/treatment) initiating lithium or valproate from 1999-2008. RESULTS: Matching produced lithium and valproate treatment groups that were highly similar in all 934 propensity score covariates, including indicators of recent suicidal behavior, but recent suicidal ideation was not able to be included. In the few individuals with recently diagnosed suicidal ideation, a significant imbalance existed with suicidal ideation more prevalent at baseline among individuals initiating lithium than valproate (odds ratio (OR) 1.30, 95% CI 1.09, 1.54; p=0.003). No significant differences in suicide death were observed over 0-365 days in A) the primary intent-to-treat analysis (lithium/valproate conditional odds ratio (cOR) 1.22, 95% CI 0.82, 1.81; p=0.32); B) during receipt of initial lithium or valproate treatment (cOR 0.86, 95% CI 0.46, 1.61; p=0.63); or C) after such treatment had been discontinued/modified (OR 1.51, 95% CI 0.91, 2.50; p=0.11). Significantly increased risks of suicide death were observed after the discontinuation/modification of lithium, compared to valproate, treatment over the first 180 days (OR 2.72, 95% CI 1.21, 6.11; p=0.015). CONCLUSIONS: In this somewhat distinct sample (a predominantly male Veteran sample with a broad range of psychiatric diagnoses), no significant differences in associations with suicide death were observed between lithium and valproate treatment over 365 days. The only significant difference was observed over 0-180 days: an increased risk of suicide death, among individuals discontinuing or modifying lithium, compared to valproate, treatment. This difference could reflect risks either related to lithium discontinuation or higher baseline risks among lithium recipients (i.e., confounding) that became more evident when treatment stopped. Our findings therefore support educating patients and providers about possible suicide-related risks of discontinuing lithium even shortly after treatment initiation, and the close monitoring of patients after lithium discontinuation, if feasible. If our findings include residual confounding biasing against lithium, however, as suggested by the differences observed in diagnosed suicidal ideation, then the degree of beneficial reduction in suicide death risk associated with active lithium treatment would be underestimated. Further research is urgently needed, given the lack of interventions against suicide and the uncertainties concerning the degree to which lithium may reduce suicide risk during active treatment, increase risk upon discontinuation, or both.