Primary care clinicians' opinions before and after implementation of cancer screening and prevention clinical decision support in a clinic cluster-randomized control trial: a survey research study.

BACKGROUND: Electronic health record (EHR)-linked clinical decision support (CDS) may impact primary care clinicians' (PCCs') clinical care opinions. As part of a clinic cluster-randomized control trial (RCT) testing a cancer prevention and screening CDS system with patient and PCC printouts (with or without shared decision-making tools [SDMT]) for patients due for breast, cervical, colorectal, and lung cancer screening and/or human papillomavirus (HPV) vaccination compared to usual care (UC), we surveyed PCCs at study clinics pre- and post-CDS implementation. Our primary aim was to learn if PCCs' opinions changed over time within study arms. Secondary aims including examining whether PCCs' opinions in study arms differed both pre- and post-implementation, and gauging PCCs' opinions on the CDS in the two intervention arms. METHODS: This study was conducted within a healthcare system serving an upper Midwestern population. We administered pre-implementation (11/2/2017-1/24/2018) and post-implementation (2/2/2020-4/9/2020) cross-sectional electronic surveys to PCCs practicing within a RCT arm: UC; CDS; or CDS + SDMT. Bivariate analyses compared responses between study arms at both time periods and longitudinally within study arms. RESULTS: Pre-implementation (53%, n = 166) and post-implementation (57%, n = 172) response rates were similar. No significant differences in PCC responses were seen between study arms on cancer prevention and screening questions pre-implementation, with few significant differences found between study arms post-implementation. However, significantly fewer intervention arm clinic PCCs reported being very comfortable with discussing breast cancer screening options with patients compared to UC post-implementation, as well as compared to the same intervention arms pre-implementation. Other significant differences were noted within arms longitudinally. For intervention arms, these differences related to CDS areas like EHR alerts, risk calculators, and ordering screening. Most intervention arm PCCs noted the CDS provided overdue screening alerts to which they were unaware. Few PCCs reported using the CDS, but most would recommend it to colleagues, expressed high CDS satisfaction rates, and thought patients liked the CDS's information and utility. CONCLUSIONS: While appreciated by PCCs with high satisfaction rates, the CDS may lower PCCs' confidence regarding discussing patients' breast cancer screening options and may be used irregularly. Future research will evaluate the impact of the CDS on cancer prevention and screening rates. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230, December 6, 2016.

The impact of personalized clinical decision support on primary care patients' views of cancer prevention and screening: a cross-sectional survey.

BACKGROUND: Few studies have assessed the impact of clinical decision support (CDS), with or without shared decision-making tools (SDMTs), on patients' perceptions of cancer screening or prevention in primary care settings. This cross-sectional survey was conducted to understand primary care patient's perceptions on cancer screening or prevention. METHODS: We mailed surveys (10/2018-1/2019) to 749 patients aged 18 to 75 years within 15 days after an index clinical encounter at 36 primary care clinics participating in a clinic-randomized control trial of a CDS system for cancer prevention. All patients were overdue for cancer screening or human papillomavirus vaccination. The survey compared respondents' answers by study arm: usual care; CDS; or CDS + SDMT. RESULTS: Of 387 respondents (52% response rate), 73% reported having enough time to discuss cancer prevention options with their primary care provider (PCP), 64% reported their PCP explained the benefits of the cancer screening choice very well, and 32% of obese patients reported discussing weight management, with two-thirds reporting selecting a weight management intervention. Usual care respondents were significantly more likely to decide on colorectal cancer screening than CDS respondents (p < 0.01), and on tobacco cessation than CDS + SDMT respondents (p = 0.02) and both CDS and CDS + SDMT respondents (p < 0.001). CONCLUSIONS: Most patients reported discussing cancer prevention needs with PCPs, with few significant differences between the three study arms in patient-reported cancer prevention care. Upcoming research will assess differences in screening and vaccination rates between study arms during the post-intervention follow-up period. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230 , December 6, 2016.

Pre-implementation adaptation of primary care cancer prevention clinical decision support in a predominantly rural healthcare system.

BACKGROUND: Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical decision support (CDS) may assist PCPs in addressing patients' cancer prevention and screening needs during short clinic visits. In this paper, we describe pre-implementation study design and cancer screening and prevention CDS changes made to maximize utilization and better fit a healthcare system's goals and culture. We employed the Consolidated Framework for Implementation Research (CFIR), useful for evaluating the implementation of CDS interventions in primary care settings, in understanding barriers and facilitators that led to those changes. METHODS: In a three-arm, pragmatic, 36 clinic cluster-randomized control trial, we integrated cancer screening and prevention CDS and shared decision-making tools (SDMT) into an existing electronic medical record-linked cardiovascular risk management CDS system. The integrated CDS is currently being tested within a predominately rural upper Midwestern healthcare system. Prior to CDS implementation, we catalogued pre-implementation changes made from 2016 to 2018 based on: pre-implementation site engagement; key informant interviews with healthcare system rooming staff, providers, and leadership; and pilot testing. We identified influential barriers, facilitators, and changes made in response through qualitative content analysis of meeting minutes and supportive documents. We then coded pre-implementation changes made and associated barriers and facilitators using the CFIR. RESULTS: Based on our findings from system-wide pre-implementation engagement, pilot testing, and key informant interviews, we made changes to accommodate the needs of the healthcare system based on barriers and facilitators that fell within the Intervention Characteristics, Inner Setting, and Outer Setting CFIR domains. Changes included replacing the expansion of medical assistant roles in one intervention arm with targeted SDMT, as well as altering cancer prevention CDS and study design elements. CONCLUSIONS: Pre-implementation changes to CDS may help meet healthcare systems' evolving needs and optimize the intervention by being responsive to real-world implementation barriers and facilitators. Frameworks like the CFIR are useful tools for identifying areas where pre-implementation barriers and facilitators may result in design changes, both to research studies and CDS systems. TRIAL REGISTRATION: NCT02986230.

Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

BACKGROUND: In the United States, primary care providers (PCPs) routinely balance acute, chronic, and preventive patient care delivery, including cancer prevention and screening, in time-limited visits. Clinical decision support (CDS) may help PCPs prioritize cancer prevention and screening with other patient needs. In a three-arm, pragmatic, clinic-randomized control trial, we are studying cancer prevention CDS in a large, upper Midwestern healthcare system. The web-based, electronic health record (EHR)-linked CDS integrates evidence-based primary and secondary cancer prevention and screening recommendations into an existing cardiovascular risk management CDS system. Our objective with this study was to identify adoption barriers and facilitators before implementation in primary care. METHODS: We conducted semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR) with 28 key informants employed by the healthcare organization in either leadership roles or the direct provision of clinical care. Transcribed interviews were analyzed using qualitative content analysis. RESULTS: EHR, CDS workflow, CDS users (providers and patients), training, and organizational barriers and facilitators were identified related to Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals CFIR domains. CONCLUSION: Identifying and addressing key informant-identified barriers and facilitators before implementing cancer prevention CDS in primary care may support a successful implementation and sustained use. The CFIR is a useful framework for understanding pre-implementation barriers and facilitators. Based on our findings, the research team developed and instituted specialized training, pilot testing, implementation plans, and post-implementation efforts to maximize identified facilitators and address barriers. TRIAL REGISTRATION: clinicaltrials.gov , NCT02986230 , December 6, 2016.

Understanding primary care providers' perceptions of cancer prevention and screening in a predominantly rural healthcare system in the upper Midwest.

BACKGROUND: Cancer is the leading cause of death in the United States, with the burden expected to rise in the coming decades, increasing the need for effective cancer prevention and screening options. The United States Preventive Services Task Force has suggested that a shared decision-making process be used when clinicians and patients discuss cancer screening. The electronic medical record (EMR) often provides only reminders or alerts to primary care providers (PCPs) when screenings are due, a strategy with limited efficacy. METHODS: We administered a cross-sectional electronic survey to PCPs (n = 165, 53% response rate) at 36 Essentia Health primary care clinics participating in a large, National Cancer Institute-funded study on a cancer prevention clinical decision support (CDS) tool. The survey assessed PCP demographics, perceptions of the EMR's ability to help assess and manage patients' cancer risk, and experience and comfort level discussing cancer screening and prevention with patients. RESULTS: In these predominantly rural clinics, only 49% of PCPs thought the EMR was well integrated to help assess and manage cancer risk. Both advanced care practitioners and physicians agreed that cancer screening and informed discussion of cancer risks are important; however, only 53% reported their patients gave cancer screening a high priority relative to other health issues. CONCLUSIONS: The impact of EMR-linked CDS delivered to both patients and PCPs may improve cancer screening, but only if it is easy to use and saves PCPs time.

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.

Chronic opioid use emerging after bariatric surgery.

PURPOSE: Little is known about opioid use after bariatric surgery among patients who did not use opioids chronically before surgery. Our purpose was to determine opioid use the year after bariatric surgery among patients who did not use opioids chronically pre-surgery and to identify pre-surgery characteristics associated with chronic opioid use after surgery. METHODS: This retrospective cohort study across nine US health systems included 10 643 patients aged 21 years or older who underwent bariatric surgery and who were not chronic opioid users pre-surgery. The main outcome was chronic opioid use the post-surgery year (excluding 30 post-operative days) defined as ≥10 dispensings over ≥90 days or ≥120 total days' supply. RESULTS: Overall, 4.0% (n = 421) of patients became chronic opioid users the post-surgery year. Pre-surgery opioid total days' supply was strongly associated with chronic use post-surgery (1-29 days adjusted odds ratio [OR] 1.89 [95%CI, 1.24-2.88]; 90-119 days OR, 14.29 [95%CI, 6.94-29.42] compared with no days). Other factors associated with increased likelihood of post-surgery chronic use included pre-surgery use of non-narcotic analgesics (OR, 2.22 [95%CI, 1.39-3.54]), antianxiety agents (OR, 1.67 [95%CI, 1.12-2.50]), and tobacco (OR, 1.44 [95%CI, 1.03-2.02]). Older age (OR, 0.84 [95%CI, 0.73-0.97] each decade) and a laparoscopic band procedure (OR, 0.42 [95%CI, 0.25-0.70] vs. laparoscopic bypass) were associated with decreased likelihood of chronic opioid use post-surgery. CONCLUSIONS: Most patients who became chronic opioid users the year after bariatric surgery used opioids intermittently before surgery.

Chronic use of opioid medications before and after bariatric surgery.

IMPORTANCE: Obesity is associated with chronic noncancer pain. It is not known if opioid use for chronic pain in obese individuals undergoing bariatric surgery is reduced. OBJECTIVES: To determine opioid use following bariatric surgery in patients using opioids chronically for pain control prior to their surgery and to determine the effect of preoperative depression, chronic pain, or postoperative changes in body mass index (BMI) on changes in postoperative chronic opioid use. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study in a distributed health network (10 demographically and geographically varied US health care systems) of 11,719 individuals aged 21 years and older, who had undergone bariatric surgery between 2005 and 2009, and were assessed 1 year before and after surgery, with latest follow-up by December 31, 2010. MAIN OUTCOMES AND MEASURES: Opioid use, measured as morphine equivalents 1 year before and 1 year after surgery, excluding the first 30 postoperative days. Chronic opioid use is defined as 10 or more opioid dispensings over 90 or more days or as dispensings of at least a 120-day supply of opioids during the year prior to surgery. RESULTS: Before surgery, 8% (95% CI, 7%-8%; n = 933) of bariatric patients were chronic opioid users. Of these individuals, 77% (95% CI, 75%-80%; n = 723) continued chronic opioid use in the year following surgery. Mean daily morphine equivalents for the 933 bariatric patients who were chronic opioid users before surgery were 45.0 mg (95% CI, 40.0-50.1) preoperatively and 51.9 mg (95% CI, 46.0-57.8) postoperatively (P < .001). For this group with chronic opiate use prior to surgery, change in morphine equivalents before vs after surgery did not differ between individuals with loss of more than 50% excess BMI vs those with 50% or less (>50% BMI loss: adjusted incidence rate ratio [adjusted IRR, 1.17; 95% CI, 1.07-1.28] vs ≤50% BMI loss [adjusted IRR, 1.03; 95% CI, 0.93-1.14] model interaction, P = .06). In other subgroup analyses of preoperative chronic opioid users, changes in morphine equivalents before vs after surgery did not differ between those with or without preoperative diagnosis of depression or chronic pain (depression only [n = 75; IRR, 1.08; 95% CI, 0.90-1.30]; chronic pain only [n = 440; IRR, 1.17; 95% CI, 1.08-1.27]; both depression and chronic pain [n = 226; IRR, 1.11; 95% CI, 0.96-1.28]; neither depression nor chronic pain [n = 192; IRR, 1.22; 95% CI, 0.98-1.51); and P values for model interactions when compared with neither were P = .42 for depression, P = .76 for pain, and P = .48 for both. CONCLUSIONS AND RELEVANCE: In this cohort of patients who underwent bariatric surgery, 77% of patients who were chronic opioid users before surgery continued chronic opioid use in the year following surgery, and the amount of chronic opioid use was greater postoperatively than preoperatively. These findings suggest the need for better pain management in these patients following surgery.

Implementing patient-reported outcomes assessment in clinical practice: a review of the options and considerations.

PURPOSE: While clinical care is frequently directed at making patients "feel better," patients' reports on their functioning and well-being (patient-reported outcomes [PROs]) are rarely collected in routine clinical practice. The International Society for Quality of Life Research (ISOQOL) has developed a User's Guide for Implementing Patient-Reported Outcomes Assessment in Clinical Practice. This paper summarizes the key issues from the User's Guide. METHODS: Using the literature, an ISOQOL team outlined considerations for using PROs in clinical practice; options for designing the intervention; and strengths, weaknesses, and resource requirements associated with each option. RESULTS: Implementing routine PRO assessment involves a number of methodological and practical decisions, including (1) identifying the goals for collecting PROs in clinical practice, (2) selecting the patients, setting, and timing of assessments, (3) determining which questionnaire(s) to use, (4) choosing a mode for administering and scoring the questionnaire, (5) designing processes for reporting results, (6) identifying aids to facilitate score interpretation, (7) developing strategies for responding to issues identified by the questionnaires, and (8) evaluating the impact of the PRO intervention on the practice. CONCLUSIONS: Integrating PROs in clinical practice has the potential to enhance patient-centered care. The online version of the User's Guide will be updated periodically.

Clinical Decision Support with or without Shared Decision Making to Improve Preventive Cancer Care: A Cluster-Randomized Trial.

BACKGROUND: Innovative interventions are needed to address gaps in preventive cancer care, especially in rural areas. This study evaluated the impact of clinical decision support (CDS) with and without shared decision making (SDM) on cancer-screening completion. METHODS: In this 3-arm, parallel-group, cluster-randomized trial conducted at a predominantly rural medical group, 34 primary care clinics were randomized to clinical decision support (CDS), CDS plus shared decision making (CDS+SDM), or usual care (UC). The CDS applied web-based clinical algorithms identifying patients overdue for United States Preventive Services Task Force-recommended preventive cancer care and presented evidence-based recommendations to patients and providers on printouts and on the electronic health record interface. Patients in the CDS+SDM clinic also received shared decision-making tools (SDMTs). The primary outcome was a composite indicator of the proportion of patients overdue for breast, cervical, or colorectal cancer screening at index who were up to date on these 1 y later. RESULTS: From August 1, 2018, to March 15, 2019, 69,405 patients aged 21 to 74 y had visits at study clinics and 25,198 were overdue for 1 or more cancer screening tests at an index visit. At 12-mo follow-up, 9,543 of these (37.9%) were up to date on the composite endpoint. The adjusted, model-derived percentage of patients up to date was 36.5% (95% confidence interval [CI]: 34.0-39.1) in the UC group, 38.1% (95% CI: 35.5-40.9) in the CDS group, and 34.4% (95% CI: 31.8-37.2) in the CDS+SDM group. For all comparisons, the screening rates were higher than UC in the CDS group and lower than UC in the CDS+SDM group, although these differences did not reach statistical significance. CONCLUSION: The CDS did not significantly increase cancer-screening rates. Exploratory analyses suggest a deeper understanding of how SDM and CDS interact to affect cancer prevention decisions is needed. Trial registration: ClinicalTrials.gov ID: NCT02986230, December 6, 2016.

Human Papillomavirus vaccination clinical decision support for young adults in an upper midwestern healthcare system: a clinic cluster-randomized control trial.

INTRODUCTION: Human papillomavirus (HPV) vaccination rates are low in young adults. Clinical decision support (CDS) in primary care may increase HPV vaccination. We tested the treatment effect of algorithm-driven, web-based, and electronic health record-linked CDS with or without shared decision-making tools (SDMT) on HPV vaccination rates compared to usual care (UC). METHODS: In a clinic cluster-randomized control trial conducted in a healthcare system serving a largely rural population, we randomized 34 primary care clinic clusters (with three clinics sharing clinicians randomized together) to: CDS; CDS+SDMT; UC. The sample included young adults aged 18-26 due for HPV vaccination with a study index visit from 08/01/2018-03/15/2019 in a study clinic. Generalized linear mixed models tested differences in HPV vaccination status 12 months after index visits by study arm. RESULTS: Among 10,253 patients, 6,876 (65.2%) were due for HPV vaccination, and 5,054 met study eligibility criteria. In adjusted analyses, the HPV vaccination series was completed by 12 months in 2.3% (95% CI: 1.6%-3.2%) of CDS, 1.6% (95% CI: 1.1%-2.3%) of CDS+SDMT, and 2.2% (95% CI: 1.6%-3.0%) of UC patients, and at least one HPV vaccine was received by 12 months in 13.1% (95% CI: 10.6%-16.1%) of CDS, 9.2% (95% CI: 7.3%-11.6%) of CDS+SDMT, and 11.2% (95% CI: 9.1%-13.7%) of UC patients. Differences were not significant between arms. Females, those with prior HPV vaccinations, and those seen at urban clinics had significantly higher odds of HPV vaccination in adjusted models. DISCUSSION: CDS may require optimization for young adults to significantly impact HPV vaccination. TRIAL REGISTRATION: clinicaltrials.gov NCT02986230, 12/6/2016.

Patient Perceptions of Using Clinical Decision Support for Cancer Screening and Prevention: "I wouldn't have thought about getting screened without it."

PURPOSE: We sought to gain an understanding of cancer prevention and screening perspectives among patients exposed to a clinical decision support (CDS) tool because they were due or overdue for certain cancer screenings or prevention. METHODS: Semi-structured qualitative interviews were conducted with 37 adult patients due or overdue for cancer prevention services in 10 primary care clinics within the same health system. Data were thematically segmented and coded using qualitative content analysis. RESULTS: We identified three themes: 1) The CDS tool had more strengths than weaknesses, with areas for improvement; 2) Many facilitators and barriers to cancer prevention and screening exist; and 3) Discussions and decision-making varied by type of cancer prevention and screening. Almost all participants made positive comments regarding the CDS. Some participants learned new information, reporting the CDS helped them make a decision they otherwise would not have made. Participants who used the tool with their provider had higher self-reported rates of deciding to be screened than those who did not. CONCLUSIONS: Learning about patients' perceptions of a CDS tool may increase understanding of how patient-tailored CDS impacts cancer screening and prevention rates. Participants found a personalized CDS tool for cancer screening and prevention in primary care useful and a welcome addition to their visit. However, many providers were not using the tool with eligible patients.

Design and rationale of an intervention to improve cancer prevention using clinical decision support and shared decision making: A clinic-randomized trial.

BACKGROUND: Despite decades of research the gap in primary and secondary cancer prevention services in the U. S. remains unacceptably wide. Innovative interventions are needed to address this persistent challenge. Electronic health records linked with Web-based clinical decision support may close this gap, especially if delivered to both patients and their providers. OBJECTIVES: The Cancer Prevention Wizard (CPW) study is an implementation, clinic-randomized trial designed to achieve these aims: 1) assess impact of the Cancer Prevention Wizard-Clinical Decision Support (CPW-CDS) alone and CPW-CDS plus Shared Decision Making Tools (CPW + SDMTs) compared to usual care (UC) on tobacco cessation counseling and drugs, HPV vaccinations, and screening tests for breast, cervical, colorectal, or lung cancer; 2) assess cost of the CPW-CDS intervention; and 3) describe critical facilitators and barriers for CPW-CDS implementation, use, and clinical impact using a mixed-methods approach supported by the CFIR and RE-AIM frameworks. METHODS: 34 predominantly rural, primary care clinics were randomized to CPW-CDS, CPW + SMDTs, or UC. Between August 2018 and October 2020, primary care providers and their patients who met inclusion criteria in intervention clinics were exposed to the CPW-CDS with or without SDMTs. Study outcomes at 12 months post index visit include patients up to date on screening tests and HPV vaccinations, overall healthcare costs, and diagnostic codes and billing levels for cancer prevention services. CONCLUSIONS: We will test in rural primary care settings whether CPW-CDS with or without SDMTs can improve delivery of primary and secondary cancer prevention services. The trial and analyses are ongoing with results expected in 2021.

Priorities Wizard: Multisite Web-Based Primary Care Clinical Decision Support Improved Chronic Care Outcomes with High Use Rates and High Clinician Satisfaction Rates.

INTRODUCTION: Priorities Wizard is an electronic health record-linked, web-based clinical decision support (CDS) system designed and implemented at multiple Health Care Systems Research Network (HCSRN) sites to support high quality outpatient chronic disease and preventive care. The CDS system (a) identifies patients who could substantially benefit from evidence-based actions; (b) presents prioritized evidence-based treatment options to both patient and clinician at the point of care; and (c) facilitates efficient ordering of recommended medications, referrals or procedures. METHODS: The CDS system extracts relevant data from electronic health records (EHRs), processes the data using Web-based clinical decision support algorithms, and displays the CDS output seamlessly on the EHR screen for use by the clinician and patient. Through a series of National Institutes of Health-funded projects led by HealthPartners Institute and the HealthPartners Center for Chronic Care Innovation and HCSRN partners, Priorities Wizard has been evaluated in cluster-randomized trials and expanded to include over 20 clinical domains. RESULTS: Cluster-randomized trials show that this CDS system significantly improved glucose and blood pressure control in diabetes patients, reduced 10-year cardiovascular (CV) risk in high-CV risk adults without diabetes, improved management of smoking in dental patients, and improved high blood pressure identification and management in adolescents. CDS output was used at 71-77 percent of targeted visits, 85-98 percent of clinicians were satisfied with the CDS system, and 94 percent reported they would recommend it to colleagues. CONCLUSIONS: Recently developed EHR-linked, Web-based CDS systems have significantly improved chronic disease care outcomes and have high use rates and primary care clinician satisfaction.

Educating generalist physicians about chronic pain: live experts and online education can provide durable benefits.

OBJECTIVE: Determine whether lectures by national experts and a publicly available online program with similar educational objectives can improve knowledge, attitudes, and beliefs (KAB) important to chronic pain management. DESIGN: A pretest-posttest randomized design with two active educational interventions in two different physician groups and a third physician group that received live education on a different topic to control for outside influences, including retesting effects, on our evaluation. PARTICIPANTS: A total of 136 community-based primary care physicians met eligibility criteria. All physicians attended the educational program to which they were assigned. Ninety-five physicians (70%) provided complete data for evaluation. MEASUREMENTS: Physician responses to a standardized 50-item pain management KAB survey before, immediately after, and 3 months following the interventions. RESULTS: The study groups and the 41 physicians not providing outcomes information were similar with respect to age, sex, race, percent engaged in primary care, and number of patients seen per week. Physician survey scores improved immediately following both pain education programs (live: 138.0-->150.6, P < 0.001; online: 143.6-->150.4, P = 0.007), but did not change appreciably in the control group (139.2-->142.5, P > 0.05). Findings persisted at 3 months. Satisfaction measures were high (4.00-4.72 on 1-5 scale) and not significantly different (P = 0.072-0.893) between groups. CONCLUSIONS: When used under similar conditions, national speakers and a publicly available online CME program were associated with improved pain management KAB in physicians. The benefits lasted for 3 months. These findings support the continued use of these pain education strategies.

KnowPain-50: a tool for assessing physician pain management education.

BACKGROUND: Despite a need for better physician pain management education, there are no widely accepted assessment or outcome measures to support this work. OBJECTIVE: Create a self-assessment tool to measure physician educational needs and the effectiveness of chronic pain educational programs. DESIGN: We used expert consensus to draft a 142-item survey that covered essential areas of chronic pain management. We tested the survey in 106 physicians, including 22 pain management experts and used predefined psychometric criteria to eliminate 70 items. We then eliminated 22 remaining items that did not correlate with the management of a standardized chronic pain patient by 27 academic physicians. We evaluated internal consistency using Cronbach's alpha. RESULTS: The final 50-item survey assessed physician knowledge, attitudes, and beliefs in: 1) initial pain assessment; 2) defining goals and expectations; 3) development of a treatment plan; 4) implementation of a treatment plan; 5) reassessment and management of longitudinal care; and 6) management of environmental issues. The survey demonstrated good internal consistency in all physician populations studied (alpha = 0.77-0.85). Average scores in 84 "pilot" physician users of a CME Website (135.8-138.5) were significantly lower (P < 0.01) than scores in 27 academic physicians (150.0), or 22 pain experts (177.5). CONCLUSIONS: This survey, the KnowPain-50, has good psychometric properties, correlates with clinical behaviors, and appears to distinguish between physicians with different levels of pain management expertise. It may be a useful measure of the effectiveness of physician pain management education programs.

Opioid Use During Pregnancy, Observations of Opioid Use, and Secular Trend From 2006 to 2014 at HealthPartners Medical Group.

OBJECTIVES: To determine the prevalence of opioid use before, during, and after pregnancy and describe its use based on patient-specific characteristics. Determine secular trend of opioid use 2006 to 2014. MATERIALS AND METHODS: Retrospective cohort study. A large Upper Midwest integrated health care system and insurer. Female individuals age 10 to 50 years with a delivery diagnosis from July 1, 2006 through June 30, 2014. MAIN OUTCOME MEASURE: prevalence of opioid use before, during, and after pregnancy; description of opioid use during these time periods. RESULTS: From 11,565 deliveries among 9690 unique women, 862 (7.5%) deliveries were associated with significant opioid use. Significant opioid use was associated with single marital status, Cesarean section, Medicaid coverage, tobacco use, depression, anxiety, bipolar disorder, substance use disorder, nonopioid analgesic use, and referral to physical therapy, psychotherapy, or pain specialists. From 2006 to 2014 opioid use decreased from 9% to 6% before, during, and after pregnancy with a rate of change per year of -0.2%. DISCUSSION: Known risk factors including tobacco and alcohol use, mental health diagnoses, substance use disorder, or Medicaid enrollment may enable enhanced assessments and targeted interventions to reduce unnecessary prescribing and use of opioids among pregnant women and those who might become pregnant. Strategies to decrease opioid use during pregnancy should be considered by health care systems and health plans to reduce opioid prescribing in this patient population.

The prognostic value of measuring health-related quality of life in hospice patients.

PURPOSE: Better prognostic instruments are sorely needed for patients near the end of life. Health-related quality of life instruments designed for hospice patients have not been previously studied for their prognostic properties. This study evaluated the prognostic property of the Missoula-Vitas Quality of Life Index (MVQOLI) with hospice patients. METHODS: A prospective, cross-sectional cohort design included all consecutive patients admitted to a hospice over a 19-month period. At admission to hospice, patients were asked to complete an MVQOLI. In addition, hospice nurses completed three functional status instruments. All patients were followed until death, study closure, or loss to follow-up. RESULTS: The sample included 1047 patients, but only 231 (22%) were able to complete an MVQOLI at admission. Functional status data were collected on nearly all of the patients. The Karnofsky performance score, modified activity of daily living score, and descriptive symptom score were significantly associated with survival time. Using Cox regression models these functional status assessments were strongly associated with survival time (p<0.001). However, the MVQOLI scores were not significantly associated with survival time, except for the function subscale (p=0.045). CONCLUSION: The MVQOLI global, total, and four of the five weighted-domain baseline scores were not associated with survival time in hospice patients. Other methods for prognostication at the end of life are needed.

Evaluation of care management intensity and bariatric surgical weight loss.

OBJECTIVES: To examine the effect of pre- and postoperative care management on weight loss following bariatric surgery. STUDY DESIGN: We conducted a retrospective cohort study supplemented by cross-sectional surveys across 9 bariatric surgery centers. METHODS: Based on the intensity of patient contact, care management intensity (CMI) was defined as high, moderate, or low for preoperative programs, and high or low for postoperative programs. Multivariable linear regression assessed 1- and 2-year post operative weight loss as a function of CMI. RESULTS: In the 9 centers, 4433 individuals underwent Roux-en-Y gastric bypass or adjustable gastric band placement between 2005 and 2009. Two sites had low, 5 had moderate, and 2 had high preoperative CMI; 5 sites had low and 4 had high postoperative CMI. In analyses stratified by procedure and adjusted for multiple covariates including site, we found no statistically significant associations between either preoperative or postoperative CMI and post operative change in body mass index at year 1 or year 2. Results were limited by heterogeneity of care management across sites and an inability to assess adherence to care management programs. CONCLUSIONS: Prospective investigations that incorporate quantifiable measures of CMI and measure individual adherence to components of care management programs are needed to more accurately determine the effect of care management on weight loss. Additional investigations should examine the effect of CMI on other relevant outcomes, such as nutritional status and quality of life, that may be more directly affected by care management.

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.