Comparing the clinical and cost-effectiveness of remote (telehealth and online) cognitive behavioral therapy-based treatments for high-impact chronic pain relative to usual care: study protocol for the RESOLVE multisite randomized control trial.

BACKGROUND: Cognitive behavioral therapy for chronic pain (CBT-CP) is an effective but underused treatment for high-impact chronic pain. Increased access to CBT-CP services for pain is of critical public health importance, particularly for rural and medically underserved populations who have limited access due to these services being concentrated in urban and high income areas. Making CBT-CP widely available and more affordable could reduce barriers to CBT-CP use. METHODS: As part of the National Institutes of Health Helping to End Addiction Long-term® (NIH HEAL) initiative, we designed and implemented a comparative effectiveness, 3-arm randomized control trial comparing remotely delivered telephonic/video and online CBT-CP-based services to usual care for patients with high-impact chronic pain. The RESOLVE trial is being conducted in 4 large integrated healthcare systems located in Minnesota, Georgia, Oregon, and Washington state and includes demographically diverse populations residing in urban and rural areas. The trial compares (1) an 8-session, one-on-one, professionally delivered telephonic/video CBT-CP program; and (2) a previously developed and tested 8-session online CBT-CP-based program (painTRAINER) to (3) usual care augmented by a written guide for chronic pain management. Participants are followed for 1 year post-allocation and are assessed at baseline, and 3, 6, and 12 months post-allocation. The primary outcome is minimal clinically important difference (MCID; ≥ 30% reduction) in pain severity (composite of pain intensity and pain-related interference) assessed by a modified 11-item version of the Brief Pain Inventory-Short Form at 3 months. Secondary outcomes include pain severity, pain intensity, and pain-related interference scores, quality of life measures, and patient global impression of change at 3, 6, and 12 months. Cost-effectiveness is assessed by incremental cost per additional patient with MCID in primary outcome and by cost per quality-adjusted life year achieved. Outcome assessment is blinded to group assignment. DISCUSSION: This large-scale trial provides a unique opportunity to rigorously evaluate and compare the clinical and cost-effectiveness of 2 relatively low-cost and scalable modalities for providing CBT-CP-based treatments to persons with high-impact chronic pain, including those residing in rural and other medically underserved areas with limited access to these services. TRIAL REGISTRATION: ClinicalTrials.gov NCT04523714. This trial was registered on 24 August 2020.

Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities.

BACKGROUND: Systematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations. METHODS: Hybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014-2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture. SETTING: 19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems. PARTICIPANTS: any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic. METHODS: A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter. OUTCOMES: provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations. MEASURES: patient and provider surveys and EMR data. RESULTS: One thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%). CONCLUSIONS: Systematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health. TRIAL REGISTRATION: Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.

At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care.

BACKGROUND: Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment. METHODS: We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk. RESULTS: One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7-74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation. CONCLUSIONS: A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond. TRIAL REGISTRATION: Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.

Chronic pain diagnoses and opioid dispensings among insured individuals with serious mental illness.

BACKGROUND: Individuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia. METHODS: Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N = 65,750), BD (N = 38,117) or schizophrenia or schizoaffective disorder (N = 12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses. RESULTS: Multivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85-1.95) or BD (OR = 1.71; 95% CI = 1.66-1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR = 0.86; 95% CI = 0.82-0.90). Having a MDD (OR = 2.59; 95% CI = 2.44-2.75) or BD (OR = 2.12; 95% CI = 1.97-2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications. CONCLUSIONS: Individuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients. Future research is needed to evaluate the effectiveness of involving mental health clinicians in these efforts.

Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform.

OBJECTIVE: Investigate sociodemographic differences in the use of a patient-facing family health history (FHH)-based risk assessment platform. METHODS: In this large multisite trial with a diverse patient population, we evaluated the relationship between sociodemographic factors and FHH health risk assessment uptake using an information technology (IT) platform. The entire study was administered online, including consent, baseline survey, and risk assessment completion. We used multivariate logistic regression to model effect of sociodemographic factors on study progression. Quality of FHH data entered as defined as relatives: (1) with age of onset reported on relevant conditions; (2) if deceased, with cause of death and (3) age of death reported; and (4) percentage of relatives with medical history marked as unknown was analyzed using grouped logistic fixed effect regression. RESULTS: A total of 2,514 participants consented with a mean age of 57 and 10.4% minority. Multivariate modeling showed that progression through study stages was more likely for younger (p-value = 0.005), more educated (p-value = 0.004), non-Asian (p-value = 0.009), and female (p-value = 0.005) participants. Those with lower health literacy or information-seeking confidence were also less likely to complete the study. Most significant drop-out occurred during the risk assessment completion phase. Overall, quality of FHH data entered was high with condition's age of onset reported 87.85%, relative's cause of death 85.55% and age of death 93.76%, and relative's medical history marked as unknown 19.75% of the time. CONCLUSION: A demographically diverse population was able to complete an IT-based risk assessment but there were differences in attrition by sociodemographic factors. More attention should be given to ensure end-user functionality of health IT and leverage electronic medical records to lessen patient burden.

Implementation, adoption, and utility of family health history risk assessment in diverse care settings: evaluating implementation processes and impact with an implementation framework.

PURPOSE: This paper describes the implementation outcomes associated with integrating a family health history-based risk assessment and clinical decision support platform within primary care clinics at four diverse healthcare systems. METHODS: A type III hybrid implementation-effectiveness trial. Uptake and implementation processes were evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: One hundred (58%) primary care providers and 2514 (7.8%) adult patients enrolled. Enrolled patients were 69% female, 22% minority, and 32% Medicare/Medicaid. Compared with their respective clinic's population, patient-participants were more likely to be female (69 vs. 59%), older (mean age 57 vs. 49), and Caucasian (88 vs. 69%) (all p values <0.001). Female (81.3% of females vs. 78.5% of males, p value = 0.018) and Caucasian (Caucasians 90.4% vs. minority 84.1%, p value = 0.02) patient-participants were more likely to complete the study once enrolled. Patient-participant survey responses indicated MeTree was easy to use (95%), and patient-participants would recommend it to family/friends (91%). Minorities and those with less education reported greatest benefit. Enrolled providers reflected demographics of underlying provider population. CONCLUSION: Family health history-based risk assessment can be effectively implemented in diverse primary care settings and can effectively engage patients and providers. Future research should focus on finding better ways to engage young adults, males, and minorities in preventive healthcare.

Enhancing Risk Assessment in Patients Receiving Chronic Opioid Analgesic Therapy Using Natural Language Processing.

OBJECTIVES: Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to initiating opioid therapy. Despite recent dramatic increases in prescription opioid misuse and abuse, use of screening tools by clinicians continues to be underutilized. This research evaluated natural language processing (NLP) together with other data extraction techniques for risk assessment of patients considered for opioid therapy as a means of predicting opioid abuse. DESIGN: Using a retrospective cohort of 3,668 chronic noncancer pain patients with at least one opioid agreement between January 1, 2007, and December 31, 2012, we examined the availability of electronic health record structured and unstructured data to populate the Opioid Risk Tool (ORT) and other selected outcomes. Clinician-documented opioid agreement violations in the clinical notes were determined using NLP techniques followed by manual review of the notes. RESULTS: Confirmed through manual review, the NLP algorithm had 96.1% sensitivity, 92.8% specificity, and 92.6% positive predictive value in identifying opioid agreement violation. At the time of most recent opioid agreement, automated ORT identified 42.8% of patients as at low risk, 28.2% as at moderate risk, and 29.0% as at high risk for opioid abuse. During a year following the agreement, 22.5% of patients had opioid agreement violations. Patients classified as high risk were three times more likely to violate opioid agreements compared with those with low/moderate risk. CONCLUSION: Our findings suggest that NLP techniques have potential utility to support clinicians in screening chronic noncancer pain patients considered for long-term opioid therapy.

Medicare hospital charges in the last year of life: distribution by quarter for rural and urban nursing home decedents with cognitive impairment.

BACKGROUND: Medicare beneficiaries incur 27%-30% of lifetime charges in the last year of life; most charges occur in the last quarter. Factors associated with high end-of-life Medicare charges include less advanced age, non-white race, absence of advance directive, and urban residence. METHODS: We analyzed Medicare hospital charges in the last year of life for nursing home residents with severe cognitive impairment, focusing on rural-urban differences. The study population consisted of 3,703 nursing home residents (1,882 rural, 1,821 urban) in Minnesota and Texas who died in 2000-2001. Data on Medicare hospital charges were obtained from 1998-2001 Centers for Medicare and Medicaid Services MedPAR files. RESULTS: During the last year of life, unadjusted charges averaged $12,448 for rural subjects; $31,780 for urban. The charges were distributed across the last 4 quarters similarly for the 2 populations, with 15%-20% of charges incurred in each of the first 3 quarters, and 47% (rural) and 52% (urban) in the last quarter. At the individual level, a higher percentage of hospital charges were incurred in the last 90 days by urban than by rural residents (P < .001). A larger proportion of urban (43%) than rural (37%) residents were hospitalized in the final quarter. The charges for hospitalized residents (N = 1,994) were distributed similarly to those of the entire study population. DISCUSSION: Medicare hospital charges during the last year of life were lower for rural nursing home residents with cognitive impairment than for their urban counterparts. Charges tend to be more concentrated in the last 90 days of life for urban residents.

Utilization of medical services at the end of life in older adults with cognitive impairment: focus on outliers.

BACKGROUND: The use of intensive medical care near end of life is often questioned because of potential burden to patients, their families, and society. Efforts to moderate intensive end-of-life care may be facilitated by early identification of those at greatest risk for receiving such care. OBJECTIVE: To examine factors associated with intensive end-of-life medical care utilization in nursing home residents with severe cognitive impairment. DESIGN: Retrospective review of existing Medicare data: 1998-2001 Minimum Data Set (MDS), Medicare Denominator, MedPAR, and hospice files. METHODS: Subjects were Minnesota and Texas nursing home residents from rural and urban counties (USDA metro-nonmetro continuum codes: 0-2 urban, 6-9 rural), who had severe cognitive impairment and who died during 2000-2001. Hospice and managed care enrollees were excluded. High medical care users were defined as subjects with 7+ intensive care unit (ICU) days in the last 90 days of life. Measures of end-of-life medical care utilization intensity included tube feeding on the last MDS report, number of hospital and ICU days, and total hospital charges during the study period. RESULTS: The study population included 1494 nursing home residents who were hospitalized within 90 days prior to death; 82 (5%) met the high medical care user criteria. In multivariable analysis: urban location (p < 0.001), lack of do-not-resuscitate directive (p = 0.002), non-white race (p = 0.021), and having 3+ comorbidities (p = 0.021) were independently associated with high medical care utilization. CONCLUSIONS: Urban nursing home location and lack of do-not-resuscitate directives were the strongest predictors of high medical care utilization near the end of life.

Rural-urban differences in cancer care: results from the Lake Superior Rural Cancer Care Project.

Past studies have shown significant differences between rural and urban cancer patients in many measures of cancer care. There is little recent information about this disparity, which generally has shown disadvantages in rural populations. This study reports the rural and urban differences in cancer care using data from the Lake Superior Rural Cancer Care Project. The study used a prospective, population-based design that included all incident cases of breast, colorectal, lung, and prostate cancers diagnosed in northeastern Minnesota, northwestern Wisconsin, and the western portion of Michigan's Upper Peninsula from 1992 to 1997. The outcome measures were 9 endpoints that represented state-of-the-art cancer care during the study. Rural cancer patients as compared with their urban counterparts were disadvantaged in proportion staged, stage at diagnosis, initial management procedures, post-treatment surveillance testing, and participation in cancer clinical trials. These findings are similar to previously published studies. Further research is needed to determine more clearly the barriers in rural cancer care and to find more effective strategies.

Improving rural cancer patients' outcomes: a group-randomized trial.

CONTEXT: Significant barriers exist in the delivery of state-of-the-art cancer care to rural populations. Rural providers' knowledge and practices, their rural health care delivery systems, and linkages to cancer specialists are not optimal; therefore, rural cancer patient outcomes are less than achievable. PURPOSE: To test the effects of a strategy targeting rural providers and their practice environment on patient travel for care, satisfaction, economic barriers, and health-related quality of life. METHODS: A group-randomized trial was conducted with 18 rural communities in the north-central United States. Twelve of these communities were included and defined as the unit of analysis for the patient outcomes portion of the study. The intervention targeted rural providers and their practice environment. The subjects were patients with breast, colorectal, lung, and prostate cancers from the rural communities. The main outcomes were patients' travel to obtain health care, satisfaction with care, perceptions of economic barriers to care, and health-related quality of life. In total, 881 patients were included. RESULTS: Group randomization was balanced. Travel for health care was significantly reduced in the community group exposed to the intervention during months 13 to 24 following cancer diagnosis. The mean miles traveled per patient were 1,326 (SE = 306) for the experimental group and 2,186 (SE = 347) for the control group (P = 0.03). No significant differences in satisfaction with care, economic barriers to care, or health-related quality of life were found. CONCLUSIONS: The intervention significantly reduced cancer patient travel for health care, which suggests that access to care improved in the experimental group. The results of this study do not allow conclusion that there was no effect on other patient outcomes. The results supported the study's conceptual framework and many of its hypotheses.