Jeffrey C Andrews

Bio: Jeffrey C Andrews is an academic researcher from Becton Dickinson. The author has contributed to research in topics: Medical encyclopedia & Cervical intraepithelial neoplasia. The author has an hindex of 22, co-authored 56 publications receiving 4678 citations. Previous affiliations of Jeffrey C Andrews include Vanderbilt University & Vanderbilt University Medical Center.

Closing the quality gap: revisiting the state of the science (vol. 3: quality improvement interventions to address health disparities).

Abstract: Objective This review evaluates the effectiveness of quality improvement (QI) strategies in reducing disparities in health and health care. Data sources We identified papers published in English between 1983 and 2011 from the MEDLINE® database, the Cumulative Index of Nursing and Allied Health Literature (CINAHL), Web of Science Social Science Index, and PsycINFO. Review methods All abstracts and full-text articles were dually reviewed. Studies were eligible if they reported data on effectiveness of QI interventions on processes or health outcomes in the United States such that the impact on a health disparity could be measured. The review focused on the following clinical conditions: breast cancer, colorectal cancer, diabetes, heart failure, hypertension, coronary artery disease, asthma, major depressive disorder, cystic fibrosis, pneumonia, pregnancy, and end-stage renal disease. It assessed health disparities associated with race or ethnicity, socioeconomic status, insurance status, sexual orientation, health literacy/numeracy, and language barrier. We evaluated the risk of bias of individual studies and the overall strength of the body of evidence based on risk of bias, consistency, directness, and precision. Results Nineteen papers, representing 14 primary research studies, met criteria for inclusion. All but one of the studies incorporated multiple components into their QI approach. Patient education was part of most interventions (12 of 14), although the specific approach differed substantially across the studies. Ten of the studies incorporated self-management; this would include, for example, teaching individuals with diabetes to check their blood sugar regularly. Most (8 of 14) included some sort of provider education, which may have focused on the clinical issue or on raising awareness about disparities affecting the target population. Studies evaluated the effect of these strategies on disparities in the prevention or treatment of breast or colorectal cancer, cardiovascular disease, depression, or diabetes. Overall, QI interventions were not shown to reduce disparities. Most studies have focused on racial or ethnic disparities, with some targeted interventions demonstrating greater effect in racial minorities--specifically, supporting individuals in tracking their blood pressure at home to reduce blood pressure and collaborative care to improve depression care. In one study, the effect of a language-concordant breast cancer screening intervention was helpful in promoting mammography in Spanish-speaking women. For some depression care outcomes, the collaborative care model was more effective in less-educated individuals than in those with more education and in women than in men. Conclusions The literature on QI interventions generally and their ability to improve health and health care is large. Whether those interventions are effective at reducing disparities remains unclear. This report should not be construed to assess the general effectiveness of QI in the health care setting; rather, QI has not been shown specifically to reduce known disparities in health care or health outcomes. In a few instances, some increased effect is seen in disadvantaged populations; these studies should be replicated and the interventions studied further as having potential to address disparities.

Grading quality of evidence and strength of recommendations in clinical practice guidelines part 3 of 3. The GRADE approach to developing recommendations.

Abstract: This is the third and last article in the series about the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to grading the quality of evidence and the strength of recommendations in clinical practice guidelines and its application in the field of allergy. We describe the factors that influence the strength of recommendations about the use of diagnostic, preventive and therapeutic interventions: the balance of desirable and undesirable consequences, the quality of a body of evidence related to a decision, patients' values and preferences, and considerations of resource use. We provide examples from two recently developed guidelines in the field of allergy that applied the GRADE approach. The main advantages of this approach are the focus on patient important outcomes, explicit consideration of patients' values and preferences, the systematic approach to collecting the evidence, the clear separation of the concepts of quality of evidence and strength of recommendations, and transparent reporting of the decision process. The focus on transparency facilitates understanding and implementation and should empower patients, clinicians and other health care professionals to make informed choices.

Decision aids for people facing health treatment or screening decisions

Abstract: Background Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. Objectives To assess the effects of decision aids for people facing treatment or screening decisions. Search methods For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). Selection criteria We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. Data collection and analysis Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were: A) 'choice made' attributes; B) 'decision-making process' attributes. Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. Main results This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each. Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies). A) Criteria involving 'choice made' attributes: Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13). B) Criteria involving 'decision-making process' attributes: Decision aids compared to usual care interventions resulted in: a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18); b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); and c) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18). Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice. C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable. The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. Authors' conclusions There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values. New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.

CDC Guideline for Prescribing Opioids for Chronic Pain—United States, 2016

Abstract: Importance Primary care clinicians find managing chronic pain challenging. Evidence of long-term efficacy of opioids for chronic pain is limited. Opioid use is associated with serious risks, including opioid use disorder and overdose. Objective To provide recommendations about opioid prescribing for primary care clinicians treating adult patients with chronic pain outside of active cancer treatment, palliative care, and end-of-life care. Process The Centers for Disease Control and Prevention (CDC) updated a 2014 systematic review on effectiveness and risks of opioids and conducted a supplemental review on benefits and harms, values and preferences, and costs. CDC used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework to assess evidence type and determine the recommendation category. Evidence Synthesis Evidence consisted of observational studies or randomized clinical trials with notable limitations, characterized as low quality using GRADE methodology. Meta-analysis was not attempted due to the limited number of studies, variability in study designs and clinical heterogeneity, and methodological shortcomings of studies. No study evaluated long-term (≥1 year) benefit of opioids for chronic pain. Opioids were associated with increased risks, including opioid use disorder, overdose, and death, with dose-dependent effects. Recommendations There are 12 recommendations. Of primary importance, nonopioid therapy is preferred for treatment of chronic pain. Opioids should be used only when benefits for pain and function are expected to outweigh risks. Before starting opioids, clinicians should establish treatment goals with patients and consider how opioids will be discontinued if benefits do not outweigh risks. When opioids are used, clinicians should prescribe the lowest effective dosage, carefully reassess benefits and risks when considering increasing dosage to 50 morphine milligram equivalents or more per day, and avoid concurrent opioids and benzodiazepines whenever possible. Clinicians should evaluate benefits and harms of continued opioid therapy with patients every 3 months or more frequently and review prescription drug monitoring program data, when available, for high-risk combinations or dosages. For patients with opioid use disorder, clinicians should offer or arrange evidence-based treatment, such as medication-assisted treatment with buprenorphine or methadone. Conclusions and Relevance The guideline is intended to improve communication about benefits and risks of opioids for chronic pain, improve safety and effectiveness of pain treatment, and reduce risks associated with long-term opioid therapy.

CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016.

Abstract: This guideline provides recommendations for primary care clinicians who are prescribing opioids for chronic pain outside of active cancer treatment, palliative care, and end-of-life care. The guideline addresses 1) when to initiate or continue opioids for chronic pain; 2) opioid selection, dosage, duration, follow-up, and discontinuation; and 3) assessing risk and addressing harms of opioid use. CDC developed the guideline using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework, and recommendations are made on the basis of a systematic review of the scientific evidence while considering benefits and harms, values and preferences, and resource allocation. CDC obtained input from experts, stakeholders, the public, peer reviewers, and a federally chartered advisory committee. It is important that patients receive appropriate pain treatment with careful consideration of the benefits and risks of treatment options. This guideline is intended to improve communication between clinicians and patients about the risks and benefits of opioid therapy for chronic pain, improve the safety and effectiveness of pain treatment, and reduce the risks associated with long-term opioid therapy, including opioid use disorder, overdose, and death. CDC has provided a checklist for prescribing opioids for chronic pain (http://stacks.cdc.gov/view/cdc/38025) as well as a website (http://www.cdc.gov/drugoverdose/prescribingresources.html) with additional tools to guide clinicians in implementing the recommendations.