Scoping review of measures of treatment burden in patients with multimorbidity: advancements and current gaps

Objectives: To identify, assess, and summarize the measures to assess burden of treatment in patients with multimorbidity (BoT-MMs) and their measurement properties. Study Design and Setting: MEDLINE via PubMed was searched from inception until May 2021. Independent reviewers extracted data from studies in which BoT-MMs were developed, validated, or reported as used, including an assessment of their measurement properties (e.g., validity and reliability) using the COnsensus-based Standards for the selection of health Measurement INstruments. Results: Eight BoT-MMs were identified across 72 studies. Most studies were performed in English (68%), in high-income countries (90%), without noting urban-rural settings (90%). No BoT-MMs had both sufficient content validity and internal consistency; some measurement properties were either insufficient or uncertain (e.g., responsiveness). Other frequent limitations of BoT-MMs included absent recall time, presence of floor effects, and unclear rationale for categorizing and interpreting raw scores. Conclusion: The evidence needed for use of extant BoT-MMs in patients with multimorbidity remains insufficiently developed, including that of suitability for their development, measurement properties, interpretability of scores, and use in low-resource settings. This review summarizes this evidence and identifies issues needing attention for using BoT-MMs in research and clinical practice

Interpreting systematic reviews: are we ready to make our own conclusions? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Independent evaluation of clinical evidence is advocated in evidence-based medicine (EBM). However, authors' conclusions are often appealing for readers who look for quick messages. We assessed how well a group of Malaysian hospital practitioners and medical students derived their own conclusions from systematic reviews (SRs) and to what extent these were influenced by their prior beliefs and the direction of the study results.</p> <p>Methods</p> <p>We conducted two cross-sectional studies: one with hospital practitioners (<it>n </it>= 150) attending an EBM course in June 2008 in a tertiary hospital and one with final-year medical students (<it>n </it>= 35) in November 2008. We showed our participants four Cochrane SR abstracts without the authors' conclusions. For each article, the participants chose a conclusion from among six options comprising different combinations of the direction of effect and the strength of the evidence. We predetermined the single option that best reflected the actual authors' conclusions and labelled this as our best conclusion. We compared the participants' choices with our predetermined best conclusions. Two chosen reviews demonstrated that the intervention was beneficial ("positive"), and two others did not ("negative"). We also asked the participants their prior beliefs about the intervention.</p> <p>Results</p> <p>Overall, 60.3% correctly identified the direction of effect, and 30.1% chose the best conclusions, having identified both the direction of effect and the strength of evidence. More students (48.2%) than practitioners (22.2%) chose the best conclusions (<it>P </it>< 0.001). Fewer than one-half (47%) correctly identified the direction of effect against their prior beliefs. "Positive" SRs were more likely than "negative" SRs to change the participants' beliefs about the effect of the intervention (relative risk (RR) 1.8, 95% confidence interval 1.3 to 2.6) and "convert" those who were previously unsure by making them choose the appropriate direction of effect (RR 1.9, 95% confidence interval 1.3 to 2.8).</p> <p>Conclusions</p> <p>The majority of our participants could not generate appropriate conclusions from SRs independently. Judicious direction from the authors' conclusions still appears crucial to guiding our health care practitioners in identifying appropriate messages from research. Authors, editors and reviewers should ensure that the conclusions of a paper accurately reflect the results. Similar studies should be conducted in other settings where awareness and application of EBM are different.</p> <p>Please see Commentary: <url>http://www.biomedcentral.com/1741-7015/9/31/</url>.</p

Assessing collaborative efforts of making care fit for each patient – A systematic review

Introduction: For too many people, their care plans are designed without fully accounting for who they are, the lives they live, what matters to them or what they aspire to achieve. We aimed to summarize instruments capable of measuring dimensions of patient–clinician collaboration to make care fit. Methods: We systematically searched several databases (Medline, Embase, Cochrane, Scopus and Web of Science) from inception to September 2021 for studies using quantitative measures to assess, evaluate or rate the work of making care fit by any participant in real-life clinical encounters. Eligibility was assessed in duplicate. After extracting all items from relevant instruments, we coded them deductively on dimensions relevant to making care fit (as presented in a recent Making Care Fit Manifesto), and inductively on the main action described. Results: We included 189 papers, mostly from North America (N = 83, 44%) and in the context of primary care (N = 54, 29%). Half of the papers (N = 88, 47%) were published in the last 5 years. We found 1243 relevant items to assess efforts of making care fit, included within 151 instruments. Most items related to the dimensions ‘Patient-clinician collaboration: content’ (N = 396, 32%) and ‘Patient-clinician collaboration: manner’ (N = 382, 31%) and the least related to ‘Ongoing and iterative process’ (N = 22, 2%) and in ‘Minimally disruptive of patient lives’ (N = 29, 2%). The items referred to 27 specific actions. Most items referred to ‘Informing’ (N = 308, 25%) and ‘Exploring’ (N = 93, 8%), the fewest items referred to ‘Following up’, ‘Comforting’ and ‘Praising’ (each N = 3, 0.2%). Discussion: Measures of the work that patients and clinicians do together to make care fit focus heavily on the content of their collaborations, particularly on exchanging information. Other dimensions and actions previously identified as crucial to making care fit are assessed infrequently or not at all. The breadth of extant measures of making care fit and the lack of appropriate measures of this key construct limit both the assessment and the successful implementation of efforts to improve patient care. Patient Contribution: Patients and caregivers from the ‘Making care fit Collaborative’ were involved in drafting the dimensions relevant to patient–clinician collaboration

Systematic reviews: a cross-sectional study of location and citation counts

BACKGROUND: Systematic reviews summarize all pertinent evidence on a defined health question. They help clinical scientists to direct their research and clinicians to keep updated. Our objective was to determine the extent to which systematic reviews are clustered in a large collection of clinical journals and whether review type (narrative or systematic) affects citation counts. METHODS: We used hand searches of 170 clinical journals in the fields of general internal medicine, primary medical care, nursing, and mental health to identify review articles (year 2000). We defined 'review' as any full text article that was bannered as a review, overview, or meta-analysis in the title or in a section heading, or that indicated in the text that the intention of the authors was to review or summarize the literature on a particular topic. We obtained citation counts for review articles in the five journals that published the most systematic reviews. RESULTS: 11% of the journals concentrated 80% of all systematic reviews. Impact factors were weakly correlated with the publication of systematic reviews (R(2 )= 0.075, P = 0.0035). There were more citations for systematic reviews (median 26.5, IQR 12 – 56.5) than for narrative reviews (8, 20, P <.0001 for the difference). Systematic reviews had twice as many citations as narrative reviews published in the same journal (95% confidence interval 1.5 – 2.7). CONCLUSIONS: A few clinical journals published most systematic reviews. Authors cited systematic reviews more often than narrative reviews, an indirect endorsement of the 'hierarchy of evidence'

An overview of the design and methods for retrieving high-quality studies for clinical care

BACKGROUND: With the information explosion, the retrieval of the best clinical evidence from large, general purpose, bibliographic databases such as MEDLINE can be difficult. Both researchers conducting systematic reviews and clinicians faced with a patient care question are confronted with the daunting task of searching for the best medical literature in electronic databases. Many have advocated the use of search filters or "hedges" to assist with the searching process. The purpose of this report is to describe the design and methods of a study that set out to develop optimal search strategies for retrieving sound clinical studies of health disorders in large electronics databases. OBJECTIVE: To describe the design and methods of a study that set out to develop optimal search strategies for retrieving sound clinical studies of health disorders in large electronic databases. DESIGN: An analytic survey comparing hand searches of 170 journals in the year 2000 with retrievals from MEDLINE, EMBASE, CINAHL, and PsycINFO for candidate search terms and combinations. The sensitivity, specificity, precision, and accuracy of unique search terms and combinations of search terms were calculated. CONCLUSION: A study design modeled after a diagnostic testing procedure with a gold standard (the hand search of the literature) and a test (the search terms) is an effective way of developing, testing, and validating search strategies for use in large electronic databases

Testing for heterogeneity among the components of a binary composite outcome in a clinical trial

<p>Abstract</p> <p>Background</p> <p>Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome.</p> <p>Methods</p> <p>Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression.</p> <p>Results</p> <p>We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high.</p> <p>Conclusions</p> <p>It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes.</p

The impact of decision aids to enhance shared decision making for diabetes (the DAD study): protocol of a cluster randomized trial

Background. Shared decision making contributes to high quality healthcare by promoting a patientcentered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient's values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice. Methods. We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms. Discussion. Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices

Bibliometrics of systematic reviews : analysis of citation rates and journal impact factors

Background: Systematic reviews are important for informing clinical practice and health policy. The aim of this study was to examine the bibliometrics of systematic reviews and to determine the amount of variance in citations predicted by the journal impact factor (JIF) alone and combined with several other characteristics. Methods: We conducted a bibliometric analysis of 1,261 systematic reviews published in 2008 and the citations to them in the Scopus database from 2008 to June 2012. Potential predictors of the citation impact of the reviews were examined using descriptive, univariate and multiple regression analysis. Results: The mean number of citations per review over four years was 26.5 (SD +/-29.9) or 6.6 citations per review per year. The mean JIF of the journals in which the reviews were published was 4.3 (SD +/-4.2). We found that 17% of the reviews accounted for 50% of the total citations and 1.6% of the reviews were not cited. The number of authors was correlated with the number of citations (r = 0.215, P =5.16) received citations in the bottom quartile (eight or fewer), whereas 9% of reviews published in the lowest JIF quartile (<=2.06) received citations in the top quartile (34 or more). Six percent of reviews in journals with no JIF were also in the first quartile of citations. Conclusions: The JIF predicted over half of the variation in citations to the systematic reviews. However, the distribution of citations was markedly skewed. Some reviews in journals with low JIFs were well-cited and others in higher JIF journals received relatively few citations; hence the JIF did not accurately represent the number of citations to individual systematic reviews