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Abstract In a primary care population of 327 older adults (age 60+) with chronic osteoarthritis (OA) pain and insomnia, we examined the relationship between short-term improvement in sleep or pain and long-term sleep, pain, depression, and fatigue by secondary analyses of randomized controlled trial data. Study participants, regardless of trial arm, were classified as Sleep or Pain Improvers with ≥30% baseline to 2-month reduction on the Insomnia Severity Index or the Brief Pain Inventory, respectively, or Sleep or Pain Non-Improvers. After controlling for trial arm and potential confounders, both Sleep and Pain Improvers showed significant (p < .01) sustained improvements across 12 months compared to respective Non-Improvers for the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index, Brief Pain Inventory-short form (total, Interference, and Severity subscales), Patient Health Questionnaire, and Flinders Fatigue Scale. The effect sizes (Cohen’s f2) for the sustained benefits in both Sleep and Pain Improvers compared to their respective Non-Improvers for all variables were small (<0.15) with the exception of medium effect size for sustained reduction in insomnia symptoms for the Sleep Improvers. We conclude that short-term sleep improvements in pain populations with comorbid insomnia precede benefits not only for long-term improvement in sleep but also for reduced pain over the long-term, along with associated improvements in depression and fatigue. Short-term improvements in pain appear to have similar long-term sequelae. Successfully improving sleep in pain populations with comorbid insomnia may have the additional benefits of improving both short- and long-term pain, depression, and fatigue. Trial Registration: OsteoArthritis and Therapy for Sleep (OATS) NCT02946957: https://clinicaltrials.gov/ct2/show/NCT02946957.

Objective The Graded Chronic Pain Scale (GCPS) is frequently used in pain research and treatment to classify mild, bothersome, and high impact chronic pain. This study’s objective was to validate the revised version of the GCPS (GCPS-R) in a US Veterans Affairs (VA) healthcare sample to support its use in this high-risk population. Methods Data were collected from Veterans (n = 794) via self-report (GCPS-R and relevant health questionnaires) and electronic health record extraction (demographics and opioid prescriptions). Logistic regression, adjusting for age and gender, was used to test for differences in health indicators by pain grade. Adjusted odds ratio (AOR) with 95% confidence intervals (CIs) were reported with CIs not including an AOR of 1 indicating that the difference exceeded chance. Results In this population, the prevalence of chronic pain (pain present most or every day, prior 3 months) was 49.3%: 7.1% with mild chronic pain (mild pain intensity and lower interference with activities); 23.3% bothersome chronic pain (moderate to severe pain intensity with lower interference); and 21.1% high impact chronic pain (higher interference). Results of this study mirrored findings in the non-VA validation study; differences between bothersome and high impact were consistent for activity limitations and present but not fully consistent for psychological variables. Those with bothersome chronic pain or high impact chronic pain were more likely to receive long-term opioid therapy compared to those with no/mild chronic pain. Conclusions Findings highlight categorical differences captured with the GCPS-R, and convergent validity supports use of the GCPS-R in US Veterans.

Abstract Background Multisite chronic pain (MSCP) is associated with increased chronic pain impact, but methods for identifying MSCP for epidemiological research have not been evaluated. Objective We assessed the validity of identifying MSCP using electronic health care data compared with survey questionnaires. Methods Stratified random samples of adults served by Kaiser Permanente Northwest and Washington (N = 2,059) were drawn for a survey, oversampling persons with frequent use of health care for pain. MSCP and single-site chronic pain were identified by two methods, with electronic health care data and with self-report of common chronic pain conditions by survey questionnaire. Analyses were weighted to adjust for stratified sampling. Results MSCP was somewhat less common when ascertained by electronic health records (14.7% weighted prevalence) than by survey questionnaire (25.9% weighted prevalence). Agreement of the two MSCP classifications was low (kappa agreement statistic of 0.21). Ascertainment of MSCP with electronic health records was 30.9% sensitive, 91.0% specific, and had a positive predictive value of 54.5% relative to MSCP identified by self-report as the standard. After adjusting for age and gender, patients with MSCP identified by either electronic health records or self-report showed higher levels of pain-related disability, pain severity, depressive symptoms, and long-term opioid use than persons with single-site chronic pain identified by the same method. Conclusions Identification of MSCP with electronic health care data was insufficiently accurate to be used as a surrogate or screener for MSCP identified by self-report, but both methods identified persons with heightened chronic pain impact.

Our study aims to establish PROMIS Pain Interference score (PI) ranges that clinicians and persons living with chronic pain (PLwCP) associate with none, mild, moderate, and high impact chronic pain. We employed the PRO-Bookmarking technique to identify threshold scores that delineate different levels of chronic pain impact. PROMIS-PI score vignettes or “score stories” were developed to communicate the experience of living with different levels of pain interference. A panel of 10 PLwCP and another of 5 pain clinicians identified pairs of score vignettes they judged to represent the threshold between two levels of pain impact (e.g., ‘‘moderate impact” and ‘‘high impact”). We defined threshold scores as the mean score of the adjacent vignettes. We applied the obtained threshold scores to the distribution of PROMIS-PI scores in a sample of persons (n = 31,090) seen in a tertiary pain clinic. In another sample, we compared the Bookmarking and the revised Graded Chronic Pain Scale (GCPS-R) classifications. Patients and clinicians were in consensus on threshold scores for “no impact” to “mild impact” and “moderate impact” to “high impact,” scores of 47 and 69, respectively. However, for the threshold for “mild impact to “moderate impact,” the value was 65 for patients and 60 for clinicians. The comparison of classifications in the secondary sample revealed differences, especially for the 3rd level, high impact. The GCPS-R classified 58.2% as having high impact chronic pain; the Bookmarking thresholds classified 23.8% as such. The PRO-Bookmarking approach effectively delineated thresholds for classifying levels of chronic pain impact using PROMIS-PI scores. This method incorporates the perspectives of PLwCP and allows for post-hoc application to diverse patient samples.

Abstract Objective We aimed to determine if opioid risk reduction initiatives including dose reduction and risk mitigation strategies for chronic noncancer pain patients receiving chronic opioid therapy (COT) had a differential impact on average daily opioid doses of COT patients at higher risk for opioid-related adverse outcomes compared with lower-risk patients. Design Interrupted time series. Setting Group Health Cooperative (GH), a health care delivery system and insurance within Washington State, between 2006 and 2014. Population GH enrollees on COT defined as receiving a supply of 70 or more days of opioids within 90 days using electronic pharmacy data for filled prescriptions. Methods We compared the average daily morphine equivalent doses (MED) of COT patients with and without each of the following higher-risk characteristics: mental disorders, substance use disorders, sedative use, and male gender. Results In all four pairwise comparisons, the higher-risk subgroup had a higher average daily MED than the lower-risk subgroup across the study period. Adjusted for covariates, modest differences in the annual rate of reduction in average daily MED were noted between higher- and lower-risk subgroups in three pairwise comparisons: those with mental disorders vs without (–8.2 mg/y vs –5.2 mg/y, P = 0.005), with sedative use vs without (–9.2 mg/y vs –5.8 mg/y, P = 0.004); mg), in men vs women (–8.8 mg/y vs –5.9 mg/y, P = 0.01). Conclusion Using clinical policy initiatives in a health care system, dose reductions were achieved among COT patients at higher risk for opioid-related adverse outcomes that were at least as large as those among lower-risk patients.

Abstract Background. Chronic opioid therapy (COT) guidelines recommend developing a COT care plan at the initiation of COT. Objective. Assess the timeliness of care planning upon initiation of COT. Design. Observational cohort study in a setting incentivizing and tracking documentation of COT care plans in electronic health records (EHRs). Participants. Study participants (N = 896) were aged 45 years or older, had initiated an episode of opioid use within the prior 6 months, and reported regular use of prescription analgesics when screened for a baseline interview about 3 months after an index opioid prescription Measures. A timely care plan was defined by an EHR documented care plan prior to or within 4 months after the index opioid prescription. Results. Among COT initiators, 30% had a timely COT care plan documented in the EHR within 4 months following index prescription, while 51% had a documented COT care plan within 12 months following index prescription. Among those interviewed at 1 year follow-up (N = 735), 252 (34.2%) reported opioid use on 7 or more days in the prior 2 weeks. Less than half (45.6%) of the 252 individuals who sustained regular opioid use at 1 year had predicted at baseline that it was somewhat, very, or extremely likely they would be using opioids regularly in 1 year. Conclusions. Patients initiating COT were unlikely to have timely COT care plans. Many who sustained regular opioid use at 1 year had not anticipated using opioids long term.

In this trial, an intervention involving a medically supervised nurse providing guideline-based management, as compared with usual care, resulted in improved medical outcomes in patients who had depression and diabetes, coronary heart disease, or both. Evidence-based care management for single conditions improves outcomes among patients with diabetes, 1 coronary heart disease, 2 and depression, 3 but organizing diagnosis-specific programs is complex and costly, so such programs are not routinely available. 4 , 5 Care for patients with multiple chronic illnesses is expensive, and coordination of care among specialties can be inadequate. 5 , 6 In previous trials involving high-risk Medicare patients with diabetes, heart disease, or both, nurse care-management interventions did not improve patient outcomes. 7 However, these interventions were primarily delivered by telephone, had no physician supervision, did not include medication recommendations to primary care physicians, and were not integrated into primary . . .

The World Health Organization Disability Assessment Schedule (WHODAS 2.0) measures disability due to health conditions including diseases, illnesses, injuries, mental or emotional problems, and problems with alcohol or drugs. The 12 Item WHODAS 2.0 was used in the second Australian Survey of Mental Health and Well-being. We report the overall factor structure and the distribution of scores and normative data (means and SDs) for people with any physical disorder, any mental disorder and for people with neither. A single second order factor justifies the use of the scale as a measure of global disability. People with mental disorders had high scores (mean 6.3, SD 7.1), people with physical disorders had lower scores (mean 4.3, SD 6.1). People with no disorder covered by the survey had low scores (mean 1.4, SD 3.6). The provision of normative data from a population sample of adults will facilitate use of the WHODAS 2.0 12 item scale in clinical and epidemiological research.

The purpose of this study was to determine if primary care patients with low back pain (LBP) cluster into definable care utilization subgroups that can be explained by patient and provider characteristics. Adult primary care patients with an incident LBP encounter were identified from Geisinger Clinic electronic health records over 5 years. Two-thirds of the cohort had only one to two encounters. Principal component analysis was applied to the data from the remaining one-third on use of ambulatory, inpatient, emergency department, and surgery care and use of magnetic resonance imaging, injections, and opioids in 12 months following the incident encounter. Groups were compared on demographics, health behaviors, chronic and symptomatic disease burden, and a measure of physician efficiency. Six factors with eigenvalues >1.5 explained 71% of the utilization variance. Patient subgroups were defined as: 1-2 LBP encounters; 2+ surgeries; one surgery; specialty care without primary care; 3+ opioid prescriptions; laboratory dominant care; and others. The surgery and 3+ opioid subgroups, while accounting for only 10.4% of the cohort, had used disproportionately more magnetic resonance imaging, emergency department, inpatient, and injectable resources. The specialty care subgroup was characterized by heavy use of inpatient care and the lowest use of injectables. Anxiety disorder and depression were not more prevalent among the surgery patients than in the others. Surgery patients had features in common with specialty care patients, but were older, had higher prevalence of Fibromyalgia, and were associated primary care physicians with worse efficiency scores. LBP care utilization is highly variable and concentrated in small subgroups using disproportionate amounts of potentially avoidable care that reflect both patient and provider characteristics.