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      Improving patient-provider communication about chronic pain: development and feasibility testing of a shared decision-making tool

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          Abstract

          Background

          Chronic pain has emerged as a disease in itself, affecting a growing number of people. Effective patient-provider communication is central to good pain management because pain can only be understood from the patient’s perspective. We aimed to develop a user-centered tool to improve patient-provider communication about chronic pain and assess its feasibility in real-world settings in preparation for further evaluation and distribution.

          Methods

          To identify and prioritize patient treatment goals for chronic pain, strategies to improve patient-provider communication about chronic pain, and facilitate implementation of the tool, we conducted nominal group technique meetings and card sorting with patients with chronic pain and experienced providers ( n = 12). These findings informed the design of the PainAPP tool. Usability and beta-testing with patients ( n = 38) and their providers refined the tool and assessed its feasibility, acceptability, and preliminary impact.

          Results

          Formative work revealed that patients felt neither respected nor trusted by their providers and focused on transforming providers’ negative attitudes towards them, whereas providers focused on gathering patient information. PainAPP incorporated areas prioritized by patients and providers: assessing patient treatment goals and preferences, functional abilities and pain, and providing patients tailored education and an overall summary that patients can share with providers.

          Beta-testing involved 38 patients and their providers. Half of PainAPP users shared their summaries with their providers. Patients rated PainAPP highly in all areas. All users would recommend it to others with chronic pain; nearly all trusted the information and said it helped them think about my treatment goals (94%), understand my chronic pain (82%), make the most of my next doctor’s visit (82%), and not want to use opioids (73%) . Beta-testing revealed challenges delivering the tool and summary report to patients and providers in a timely manner and obtaining provider feedback.

          Conclusions

          PainAPP appears feasible for use, but further adaptation and testing is needed to assess its impact on patients and providers.

          Trial registration

          This study was approved by the University of New England Independent Review Board for the Protection of Human Subjects in Research (012616–019) and was registered with ClinicalTrials.gov (protocol ID: NCT03425266) prior to enrollment. The trial was prospectively registered and was approved on February 7, 2018.

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          Decision aids for people facing health treatment or screening decisions.

          Decision aids are interventions that support patients by making their decisions explicit, providing information about options and associated benefits/harms, and helping clarify congruence between decisions and personal values.
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            Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016

            Chronic pain, one of the most common reasons adults seek medical care ( 1 ), has been linked to restrictions in mobility and daily activities ( 2 , 3 ), dependence on opioids ( 4 ), anxiety and depression ( 2 ), and poor perceived health or reduced quality of life ( 2 , 3 ). Population-based estimates of chronic pain among U.S. adults range from 11% to 40% ( 5 ), with considerable population subgroup variation. As a result, the 2016 National Pain Strategy called for more precise prevalence estimates of chronic pain and high-impact chronic pain (i.e., chronic pain that frequently limits life or work activities) to reliably establish the prevalence of chronic pain and aid in the development and implementation of population-wide pain interventions ( 5 ). National estimates of high-impact chronic pain can help differentiate persons with limitations in major life domains, including work, social, recreational, and self-care activities from those who maintain normal life activities despite chronic pain, providing a better understanding of the population in need of pain services. To estimate the prevalence of chronic pain and high-impact chronic pain in the United States, CDC analyzed 2016 National Health Interview Survey (NHIS) data. An estimated 20.4% (50.0 million) of U.S. adults had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain, with higher prevalences of both chronic pain and high-impact chronic pain reported among women, older adults, previously but not currently employed adults, adults living in poverty, adults with public health insurance, and rural residents. These findings could be used to target pain management interventions. NHIS is a cross-sectional, in-person, household health survey of the civilian noninstitutionalized U.S. population, conducted by the National Center for Health Statistics (NCHS).* Data from the 2016 Sample Adult Core for adults aged ≥18 years (33,028; response rate = 54.3%) † were analyzed. Information about pain was collected through responses to the following questions: “In the past six months, how often did you have pain? Would you say never, some days, most days, or every day?” and “Over the past six months, how often did pain limit your life or work activities? Would you say never, some days, most days, or every day?” Chronic pain was defined as pain on most days or every day in the past 6 months, as recommended by the International Association for the Study of Pain, § modified to account for intermittent pain, and used in both the National Pain Strategy and National Institutes of Health Task Force on Chronic Back Pain ( 6 ). As suggested in the National Pain Strategy, high-impact chronic pain was defined as chronic pain that limited life or work activities on most days or every day during the past 6 months ( 5 ). The prevalence of chronic pain and high-impact chronic pain (both crude and age-adjusted, with 95% confidence intervals) were estimated for the U.S. adult population overall and by various sociodemographic characteristics. These characteristics, collected with the Family Core questionnaire, included age, sex, race/ethnicity, education level, current employment status, ¶ poverty status (calculated using NHIS imputed income files),** veteran status, health insurance coverage type (reported separately for adults aged <65 and ≥65 years), and urbanicity. All prevalence estimates met NCHS reliability standards. †† Because pain prevalence varies by age, age-adjusted estimates were used in comparisons of chronic pain and high-impact chronic pain between subgroups. Based on two-tailed Z-tests, all reported differences between subgroups are statistically significant (unless otherwise noted; p<0.05). Analyses were conducted using statistical software that accounts for the stratification and clustering of households in the NHIS sampling design. Estimates incorporated the final sample adult weights adjusted for nonresponse and calibrated to population control totals to enable generalization to the civilian noninstitutionalized population aged ≥18 years. In 2016, an estimated 20.4% of U.S. adults (50.0 million) had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain (Table), with higher prevalence associated with advancing age. Age-adjusted prevalences of both chronic pain and high-impact chronic pain were significantly higher among women, adults who had worked previously but were not currently employed, adults living in or near poverty, and rural residents. In addition, the age-adjusted prevalences of chronic pain and high-impact chronic pain were significantly lower among adults with at least a bachelor’s degree compared with all other education levels. TABLE Prevalence of chronic pain* and high impact chronic pain † among U.S. adults aged ≥18 years, by sociodemographic characteristics—National Health Interview Survey, 2016 Characteristic Chronic pain* High-impact chronic pain† Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Total 50,009,000 20.4 (19.7–21.0) 19.4 (18.7–20.0) 19,611,000 8.0 (7.6–8.4) 7.5 (7.1–7.9) Age group (yrs) 18–24 2,082,000 7.0 (5.8–8.5) —** 446,000 1.5 (0.9–2.3) —** 25–44 11,042,000 13.2 (12.3–14.1) —** 3,681,000 4.4 (3.9–5.0) —** 45–64 23,269,000 27.8 (26.6–29.0) —** 10,044,000 12.0 (11.2–12.9) —** 65–84 11,808,000 27.6 (26.4–29.0) —** 4,578,000 10.7 (9.9–11.6) —** ≥85 1,766,000 33.6 (30.1–37.3) —** 830,000 15.8 (13.2–18.9) —** Sex Male 21,989,000 18.6 (17.7–19.5) 17.8 (17.0–18.7) 8,276,000 7.0 (6.5–7.6) 6.7 (6.2–7.3) Female 28,049,000 22.1 (21.2–23.0) 20.8 (19.9–21.6) 11,296,000 8.9 (8.4–9.4) 8.2 (7.7–8.7) Race/Ethnicity Hispanic 5,856,000 15.1 (13.6–16.7) 16.7 (15.2–18.4) 2,754,000 7.1 (6.0–8.3) 7.9 (6.9–9.2) White, non-Hispanic 36,226,000 23.0 (22.2–23.8) 21.0 (20.3–21.8) 13,230,000 8.4 (7.9–8.9) 7.4 (7.0–7.9) Black, non-Hispanic 5,148,000 17.9 (16.4–19.6) 17.8 (16.3–19.4) 2,387,000 8.3 (7.2–9.4) 8.1 (7.1–9.2) Other, non-Hispanic†† 2,774,000 13.8 (12.1–15.7) 14.4 (12.7–16.3) 1,326,000 6.6 (5.3–8.1) 7.0 (5.7–8.5) Education Less than high school 7,809,000 26.1 (24.2–28.2) 23.7 (21.7–25.7) 4,069,000 13.6 (12.3–15.2) 12.1 (10.7–13.7) High school/GED 14,441,000 23.7 (22.5–25.0) 22.6 (21.2–23.9) 5,910,000 9.7 (9.0–10.6) 9.1 (8.4–10.0) Some college 17,129,000 22.6 (21.5–23.8) 22.9 (21.8–24.0) 6,518,000 8.6 (7.9–9.4) 8.7 (8.0–9.5) Bachelor's degree or higher 10,383,000 13.4 (12.6–14.3) 12.4 (11.7–13.3) 2,944,000 3.8 (3.4–4.3) 3.5 (3.1–4.0) Employment status Employed 22,085,000 14.7 (14.1–15.5) 14.5 (13.8–15.2) 5,108,000 3.4 (3.1–3.8) 3.2 (2.9–3.6) Not employed; worked previously 25,737,000 31.5 (30.3–32.7) 29.2 (27.8–30.6) 13,318,000 16.3 (15.4–17.2) 16.1 (15.0–17.3) Not employed; never worked 2,083,000 15.9 (13.8–18.2) 18.7 (16.1–21.6) 1,192,000 9.1 (7.6–10.9) 11.1 (9.1–13.4) Poverty status <100% FPL 8,017,000 25.8 (24.2–27.6) 29.6 (27.9–31.3) 4,630,000 14.9 (13.6–16.4) 17.5 (16.1–19.0) 100% ≤FPL<200% 11,357,000 26.2 (24.5–27.9) 25.9 (24.2–27.7) 5,375,000 12.4 (11.3–13.6) 12.3 (11.2–13.5) 200% ≤FPL<400% 14,181,000 20.3 (19.2–21.4) 19.3 (18.3–20.4) 5,100,000 7.3 (6.7–8.1) 6.9 (6.2–7.6) ≥400% FPL 16,441,000 16.3 (15.4–17.2) 14.6 (13.8–15.5) 4,438,000 4.4 (4.0–4.9) 3.9 (3.5–4.4) Veteran Yes 6,379,000 29.1 (27.1–31.2) 26.0 (23.5–28.7) 2,258,000 10.3 (9.1–11.8) 9.2 (7.7–11.1) No 43,519,000 19.5 (18.9–20.2) 19.0 (18.4–19.7) 17,407,000 7.8 (7.4–8.2) 7.5 (7.1–7.9) Health insurance coverage§§ Age <65 yrs Private 20,539,000 15.1 (14.3–15.8) 14.0 (13.3–14.8) 5,713,000 4.2 (3.8–4.7) 3.8 (3.4–4.2) Medicaid and other public coverage 8,215,000 29.3 (27.3–31.5) 30.0 (28.0–32.2) 4,822,000 17.2 (15.6–19.0) 17.8 (16.2–19.6) Other 3,860,000 43.5 (40.0–47.2) 34.8 (31.2–38.7) 2,263,000 25.5 (22.5–28.8) 19.3 (16.4–22.5) Uninsured 3,683,000 16.2 (14.4–18.2) 17.0 (15.2–19.0) 1,319,000 5.8 (4.7–7.2) 6.2 (5.0–7.6) Age ≥65 yrs Private 5,606,000 28.0 (26.3–29.9) 28.1 (26.3–30.0) 1,842,000 9.2 (8.1–10.5) 9.3 (8.2–10.6) Medicare and Medicaid 1,428,000 42.5 (37.6–47.5) 42.5 (37.6–47.5) 816,000 24.3 (20.4–28.6) 24.3 (20.4–28.6) Medicare Advantage 3,094,000 25.5 (23.1–28.1) 25.8 (23.4–28.4) 1,226,000 10.1 (8.5–11.8) 10.3 (8.7–12.1) Medicare only, excluding Medicare Advantage 2,115,000 25.9 (23.1–28.9) 25.9 (23.1–28.9) 939,000 11.5 (9.5–13.7) 11.5 (9.5–13.7) Other 1,229,000 31.6 (27.2–36.3) 31.8 (27.4–36.5) 545,000 14.0 (11.3–17.3) 14.3 (11.5–17.7) Uninsured 106,000 —¶¶ —¶¶ 59,000 —¶¶ —¶¶ Urbanicity*** Urban 38,401,000 19.0 (18.3–19.7) 18.4 (17.7–19.0) 14,754,000 7.3 (6.9–7.8) 7.0 (6.6–7.4) Rural 11,575,000 26.9 (25.4–28.5) 24.0 (22.5–25.6) 4,776,000 11.1 (10.2–12.2) 9.8 (8.8–10.9) Abbreviations: CI = confidence interval; FPL = federal poverty level; GED = General Educational Development certification. * Pain on most days or every day in the past 6 months. † Chronic pain limiting life or work activities on most days or every day in the past 6 months. § The estimated numbers, rounded to 1,000s, were annualized based on the 2016 data. Counts for adults of unknown status (responses coded as “refused,” “don’t know,” or “not ascertained”) with respect to chronic pain and high-impact chronic pain are not shown separately in the table, nor are they included in the calculation of percentages (as part of either the denominator or the numerator), to provide a more straightforward presentation of the data. ¶ Estimates are age-adjusted using the projected 2000 U.S. population as the standard population and five age groups: 18–29, 30–39, 40–49, 50–59, and ≥60 years. ** Not applicable. †† Non-Hispanic other includes non-Hispanic American Indian and Alaska Native only, non-Hispanic Asian only, non-Hispanic Native Hawaiian and Pacific Islander only, and non-Hispanic multiple race. §§ Based on a hierarchy of mutually exclusive categories. Adults reporting both private and Medicare Advantage coverage were assigned to the Medicare Advantage category. “Uninsured” includes adults who had no coverage as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. “Other” comprises military health care including TRICARE, VA, and CHAMP-VA, and certain types of local and state governmental coverage, not including the Children’s Health Insurance Program. ¶¶ Estimates are considered unreliable according to the National Center for Health Statistics’ standards of reliability. *** Based on U.S. Census Bureau definitions of urban and rural areas (https://www2.census.gov/geo/pdfs/reference/ua/Defining_Rural.pdf). Whereas non-Hispanic white adults had a significantly higher age-adjusted prevalence of chronic pain than did all other racial and ethnic subgroups, no significant differences in high-impact chronic pain prevalence by race/ethnicity were observed. Similarly, the age-adjusted prevalence of chronic pain was significantly higher among veterans than among nonveterans, but no significant difference was observed in the prevalence of high-impact chronic pain. Among adults aged <65 years, the age-adjusted prevalences of chronic pain and high-impact chronic pain were higher among those with Medicaid and other public health care coverage or other insurance (e.g., Veteran’s Administration, certain local and state government) than among adults with private insurance or those who were uninsured. Among adults aged ≥65 years, those with both Medicare and Medicaid had higher age-adjusted prevalences of chronic pain and high-impact chronic pain than did adults with all other types of coverage. Discussion Pain is a component of many chronic conditions, and chronic pain is emerging as a health concern on its own, with negative consequences to individual persons, their families, and society as a whole ( 4 , 5 ). Healthy People 2020 (https://www.healthypeople.gov/), the nation’s science-based health objectives, has a developmental objective to “decrease the prevalence of adults having high-impact chronic pain.” This analysis extends previous national studies of chronic pain prevalence by identifying adults with high-impact chronic pain. In 2016, approximately 20% of U.S. adults had chronic pain (approximately 50 million), and 8% of U.S. adults (approximately 20 million) had high-impact chronic pain. This estimate of high-impact chronic pain is similar to or slightly lower than estimates reported in the few studies that have looked at pain using a similar construct. For example, a recent study that used a measure of high-impact chronic pain similar to the one used in this study reported an estimate of 13.7% among a sample of U.S. adult health plan enrollees ( 7 ). Similarly, a 2001 study of adults from a region in Scotland found that 14.1% of survey participants reported significant chronic pain, and 6.3% reported severe chronic pain, and a 2001 study of Australian adults reported that 11.0% of men and 13.5% of women reported chronic pain that interfered, to some degree, with daily life activities ( 3 , 8 ). The results of subgroup analyses in the current study were consistent with findings in these studies ( 3 , 8 ) insofar as the prevalence of high-impact chronic pain was higher among women, adults who had achieved lower levels of education, and those who were not employed at the time of the survey, and was lower among adults with private health insurance compared with public and other types of coverage. In addition, high-impact chronic pain was also found to be higher among adults living in poverty and among rural residents. Socioeconomic status appears to be a common factor in many of the subgroup differences in high-impact chronic pain prevalence reported here. Indicators of socioeconomic status such as education, poverty, and health insurance coverage have been determined to be associated with both general health status and the presence of specific health conditions ( 9 ) as well as with patients’ success in navigating the health care system ( 9 ). Identifying populations at risk is necessary to inform efforts for developing and targeting quality pain services. The findings in this report are subject to at least five limitations. First, data are self-reported and subject to recall bias. Second, data are cross-sectional, precluding drawing causal inferences. This might be particularly relevant for socioeconomic status, which can be both a risk factor for and a consequence of chronic pain or high-impact chronic pain, or both. Third, no information is available on treatment for chronic pain to assess the prevalence of chronic pain and high-impact chronic pain among those with and without treatment. Fourth, NHIS excludes important populations, such as active duty military and residents of long-term care facilities or prisons. And finally, NHIS does not collect data on chronic pain or high-impact chronic pain in children. Despite these limitations, three strengths of this study are that it used a large, nationally representative data source to produce estimates of chronic pain and high-impact chronic pain across many demographic subgroups, it used standard broad definitions of pain that were not limited to one or more specific health conditions (e.g., headache or arthritis), and it used the standard case definition for high-impact chronic pain proposed by the National Pain Strategy. Chronic pain contributes to an estimated $560 billion each year in direct medical costs, lost productivity, and disability programs ( 4 ). The National Pain Strategy, which is the first national effort to transform how the population burden of pain is perceived, assessed, and treated, recognizes the need for better data to inform action and calls for estimates of chronic pain and high-impact chronic pain in the general population ( 5 ). This report helps fulfill this objective and provides data to inform policymakers, clinicians, and researchers focused on pain care and prevention. Summary What is already known about this topic? Chronic pain has been linked to numerous physical and mental conditions and contributes to high health care costs and lost productivity. A limited number of studies estimate that the prevalence of chronic pain ranges from 11% to 40%. What is added by this report? In 2016, an estimated 20.4% of U.S. adults had chronic pain and 8.0% of U.S. adults had high-impact chronic pain. Both were more prevalent among adults living in poverty, adults with less than a high school education, and adults with public health insurance. What are the implications for public health practice? This report helps fulfill a National Pain Strategy objective of producing more precise estimates of chronic pain and high-impact chronic pain.
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              Developing a quality criteria framework for patient decision aids: online international Delphi consensus process.

              To develop a set of quality criteria for patient decision support technologies (decision aids). Two stage web based Delphi process using online rating process to enable international collaboration. Individuals from four stakeholder groups (researchers, practitioners, patients, policy makers) representing 14 countries reviewed evidence summaries and rated the importance of 80 criteria in 12 quality domains on a 1 to 9 scale. Second round participants received feedback from the first round and repeated their assessment of the 80 criteria plus three new ones. Aggregate ratings for each criterion calculated using medians weighted to compensate for different numbers in stakeholder groups; criteria rated between 7 and 9 were retained. 212 nominated people were invited to participate. Of those invited, 122 participated in the first round (77 researchers, 21 patients, 10 practitioners, 14 policy makers); 104/122 (85%) participated in the second round. 74 of 83 criteria were retained in the following domains: systematic development process (9/9 criteria); providing information about options (13/13); presenting probabilities (11/13); clarifying and expressing values (3/3); using patient stories (2/5); guiding/coaching (3/5); disclosing conflicts of interest (5/5); providing internet access (6/6); balanced presentation of options (3/3); using plain language (4/6); basing information on up to date evidence (7/7); and establishing effectiveness (8/8). Criteria were given the highest ratings where evidence existed, and these were retained. Gaps in research were highlighted. Developers, users, and purchasers of patient decision aids now have a checklist for appraising quality. An instrument for measuring quality of decision aids is being developed.
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                Author and article information

                Contributors
                Nananda@sdmresources.info
                hulls@emhs.org
                Vicky.Springmann@gmail.com
                ngo@bidmc.harvard.edu
                churn3@maine.rr.com
                sgold@desktoppub.com
                msprintz@cellarian.com
                noelpac60@gmail.com
                nnesin@pchc.com
                dbakk99@yahoo.com
                sanfilippof@northernlight.org
                richentel@gracest.org
                Lori.Pbert@umassmed.edu
                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central (London )
                1472-6947
                17 October 2020
                17 October 2020
                2020
                : 20
                : 267
                Affiliations
                [1 ]University of New England and Shared Decision Making Resources, 1119 Five Islands Road, Georgetown, ME 04548 USA
                [2 ]GRID grid.415360.5, ISNI 0000 0004 0441 047X, Northern Light Mercy Hospital, ; Portland, ME USA
                [3 ]GRID grid.239395.7, ISNI 0000 0000 9011 8547, Beth Israel Deaconess Medical Center, ; Boston, MA USA
                [4 ]Southern Maine Chronic Pain Support Group, Saco, ME USA
                [5 ]Custom Communications, Portland, ME USA
                [6 ]Sprintz Center for Pain and Dependency, The Woodlands, TX USA
                [7 ]Penobscot Community Health Care, Bangor, ME USA
                [8 ]GRID grid.429380.4, ISNI 0000 0004 0455 8490, Mainehealth, ; Portland, ME USA
                [9 ]GRID grid.168645.8, ISNI 0000 0001 0742 0364, University of Massachusetts Medical School, ; Worcester, MA USA
                Author information
                http://orcid.org/0000-0001-7106-662X
                Article
                1279
                10.1186/s12911-020-01279-8
                7568350
                33069228
                1cb44127-6de5-479d-82e9-d0ca92e7f3f4
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 8 June 2019
                : 30 September 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004319, Pfizer;
                Award ID: 20063933
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                © The Author(s) 2020

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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