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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 25 of 411 Research Studies DisplayedMarkham JL, Richardson T, Stephens JR
Essential concepts for reducing bias in observational studies.
This study discussed ways to reduce bias in pediatric observational studies, which may be used instead of randomized controlled trials (RCTs) due to barriers within pediatric populations, including lower disease prevalence, high costs, inadequate funding, and additional regulatory requirements. Observational studies do not involve randomization and thus have more potential for bias when compared with RCTs because of imbalances that can exist between comparison groups. The authors describe techniques to minimize bias by controlling for important measurable covariates within observational studies and discuss the challenges and opportunities in addressing specific variables.
AHRQ-funded; HS028845.
Citation: Markham JL, Richardson T, Stephens JR .
Essential concepts for reducing bias in observational studies.
Hosp Pediatr 2023 Aug; 13(8):e234-e39. doi: 10.1542/hpeds.2023-007116..
Keywords: Research Methodologies, Health Services Research (HSR)
Strayer TE, Hollingsworth EK, Shah AS
Why do older adults decline participation in research? Results from two deprescribing clinical trials.
The objective of this study was to examine reasons why hospitalized older adults declined participation in two deprescribing clinical trials, Shed-MEDS (non-Veterans) and VA DROP (Veterans). The reasons given by participating patients were condensed into three themes: feeling overwhelmed by current health status; lack of interest or mistrust; hesitancy to participate. A greater proportion of Veterans expressed a lack of interest or, while more non-Veterans expressed feeling overwhelmed by their current health status. The authors concluded that understanding the reasons why older adults decline participation can inform future strategies to engage this multimorbid population.
AHRQ-funded; HS026122.
Citation: Strayer TE, Hollingsworth EK, Shah AS .
Why do older adults decline participation in research? Results from two deprescribing clinical trials.
Trials 2023 Jul 18; 24(1):456. doi: 10.1186/s13063-023-07506-7..
Keywords: Elderly, Research Methodologies, Health Services Research (HSR)
Li D, Lu W, Shu D
Distributed Cox proportional hazards regression using summary-level information.
This article proposed a way to not share individual-level data in multi-site studies by using a general distributed methodology to fit Cox proportional hazards models. The authors state that this approach can be applied to both stratified and unstratified models, accommodate both discrete and continuous exposure variables, and permit the adjustment of multiple covariates. The fitting of stratified Cox models can be carried out with only one file transfer of summary-level information. They derived the asymptotic properties of the proposed estimators and compared the proposed estimators with the maximum partial likelihood estimators using pooled individual-level data and meta-analysis methods through simulation studies. They applied the proposed method to a real-world data set to examine the effect of sleeve gastrectomy versus Roux-en-Y gastric bypass on the time to first postoperative readmission.
AHRQ-funded; HS026214.
Citation: Li D, Lu W, Shu D .
Distributed Cox proportional hazards regression using summary-level information.
Biostatistics 2023 Jul 14; 24(3):776-94. doi: 10.1093/biostatistics/kxac006..
Keywords: Research Methodologies
Dahabreh IJ, Robins JM, Haneuse SJA
Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population.
This paper describes how simple methods for sensitivity analysis using bias functions can extend inferences from a randomized trial to a target population. The authors show how the methods can be applied to non-nested trial designs, where the trial data are combined with a separately obtained sample of nonrandomized individuals, as well as to nested trial designs, where the trial is embedded within a cohort sampled from the target population.
AHRQ-funded; HS028373.
Citation: Dahabreh IJ, Robins JM, Haneuse SJA .
Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population.
Stat Med 2023 Jun 15; 42(13):2029-43. doi: 10.1002/sim.9550..
Keywords: Research Methodologies
Huo T, Glueck DH, Shenkman EA
Stratified split sampling of electronic health records
Data extracted from electronic health records may require very different approaches for model building and analysis than data from clinical research. Because electronic health record data is designed for clinical use, researchers need to engage in the iterative process of defining and provide clear definitions of outcome and predictor variables and assessing associations. This process can increase Type I error rates and decrease the chance of replicability. Failure to consider subgroups may mask heterogeneous relationships between predictor and outcome by subgroups, thus decreasing the generalizability of the findings. To improve the likelihood of both replicability and generalizability, the researchers recommended utilizing a stratified split sample approach for studies using electronic health records. The researchers illustrate the approach through an electronic health record study of the relationships between socio-demographic factors and uptake of hepatic cancer screening, and potential heterogeneity of association in subgroups defined by gender, self-identified race and ethnicity, census-tract level poverty and insurance type.
AHRQ-funded; HS028283.
Citation: Huo T, Glueck DH, Shenkman EA .
Stratified split sampling of electronic health records
BMC Med Res Methodol 2023 May 25; 23(1):128. doi: 10.1186/s12874-023-01938-0..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Research Methodologies, Health Services Research (HSR)
Chandanabhumma PP, Zhou S, Fetters MD
Expanding our methodological toolbox to improve quality: the role of mixed-methods evaluations.
This article discusses ways that using mixed-methods studies can enhance quality improvement interventions instead of relying solely on quantitative evidence. Mixed-methods design helped to advance an evidence-based, customizable infection prevention toolkit for durable left ventricular assist device therapy. Strengths of using mixed-methods studies include: (1) the use of qualitative research methodologies (eg, eliciting patient or clinician perspectives on barriers and facilitators of best practices) and (2) integrating qualitative and quantitative data and analyses to understand more fully effective strategies for achieving optimal care and outcomes for these patients across diverse settings. The study: 1) used quantitative clinical data merged with Medicare claims to evaluate interhospital variability in the incidence of infection; 2) used qualitative methods to understand local practice patterns across low- and high-performing centers; and 3) integrated both data sources to gain a comprehensive understanding of the overall findings.
AHRQ-funded; HS026003.
Citation: Chandanabhumma PP, Zhou S, Fetters MD .
Expanding our methodological toolbox to improve quality: the role of mixed-methods evaluations.
Circ Cardiovasc Qual Outcomes 2023 May; 16(5):e009629. doi: 10.1161/circoutcomes.122.009629..
Keywords: Research Methodologies, Quality Improvement, Quality of Care
Kahwati LC, Kelly BJ, Johnson M
End-user understanding of qualitative comparative analysis used within evidence synthesis: a mixed-methods study.
This study’s purpose was to identify effective approaches to communicating results from a qualitative comparative analysis (QCA) within a systematic review. Interviews with 11 end-users followed by a randomized experiment with 254 participants provided QCA results for a hypothetical review presented through three formats (text, table, and figure). The authors observed a significant different in subjective comprehension across three presentation formats, with figure and text formats scoring higher compared to the table. Overall, there were no significant different for objective comprehension. However, interpretation (a unique component of QCA results) scores among participants that received the figure format were significantly higher than scores for participants who received the text or table. No significant differences were observed in objective comprehension for configuration interpretation.
AHRQ-funded; HS026258.
Citation: Kahwati LC, Kelly BJ, Johnson M .
End-user understanding of qualitative comparative analysis used within evidence synthesis: a mixed-methods study.
Res Synth Methods 2023 Mar;14(2):180-92. doi: 10.1002/jrsm.1602.
Keywords: Comparative Effectiveness, Evidence-Based Practice, Research Methodologies
Temkin-Greener H, Mao Y, Li Y
Using Medicare enrollment data to identify beneficiaries in assisted living.
The authors developed an approach for identifying Medicare beneficiaries residing in US assisted living (AL) communities in 2018. Data sources included a national directory of licensed ALs, a file of US addresses and their associated 9-digit ZIP codes (ZIP+4), the Medicare Enrollment Database (EDB), the Master Beneficiary Summary File (MBSF), and the Minimum Data Set (MDS). The cohorts of beneficiaries identified as AL residents exhibited good construct validity; AL residents also showed similar demographic characteristics to the 2018 sample from the National Survey of Long-Term Care Providers. The authors concluded that, as this residential setting continues to grow, future studies will need effective approaches such as their proposed methodology for identifying Medicare beneficiaries who reside in AL facilities in order to evaluate the quality of care they receive.
AHRQ-funded; HS026893.
Citation: Temkin-Greener H, Mao Y, Li Y .
Using Medicare enrollment data to identify beneficiaries in assisted living.
J Am Med Dir Assoc 2023 Mar;24(3):277-83. doi: 10.1016/j.jamda.2022.01.062.
Keywords: Medicare, Nursing Homes, Research Methodologies
Majumder MS, Cusick M, Rose S
Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.
This study’s objective was to investigate the strengths and limitations of sources currently being used for infectious disease research. This retrospective data analysis used four different data sources to determine differences in the yearly number of national-level and state-level disease-specific case counts and disease clusters for three diseases (measles, mumps, and varicella) during a 5-year study period (2013-2017). The four sources used were Optum (health insurance billing claims data), HealthMap (online news surveillance data), Morbidity and Mortality Weekly Reports (official government reports) and National Notifiable Disease Surveillance System (government case surveillance data). The authors found that when compared with the other three sources of interest, Optum data showed substantially higher, implausible standardized case counts for all three diseases. All four sources identified variations in state-level reporting.
AHRQ-funded; HS026128.
Citation: Majumder MS, Cusick M, Rose S .
Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.
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Keywords: Infectious Diseases, Research Methodologies
Shmuel S, Leonard CE, Bykov K
Breaking research silos and stimulating "innovation at the edges" in epidemiology.
The authors discuss the importance of promoting an exchange of ideas across seemingly disparate epidemiologic subdisciplines. This exchange could lead to opportunities to learn from and to merge knowledge across subdisciplines, as well as promote "innovation at the edges." The authors also outline specific steps to promote such innovation at the researcher, institution, and professional society level.
AHRQ-funded; HS027623.
Citation: Shmuel S, Leonard CE, Bykov K .
Breaking research silos and stimulating "innovation at the edges" in epidemiology.
Am J Epidemiol 2023 Feb 24;192(3):323-27. doi: 10.1093/aje/kwac192.
Keywords: Evidence-Based Practice, Research Methodologies, Medication
Coley RY, Liao Q, Simon N
Empirical evaluation of internal validation methods for prediction in large-scale clinical data with rare-event outcomes: a case study in suicide risk prediction.
Clinical prediction models for uncommon outcomes, such as suicide, psychiatric hospitalizations, and opioid overdose, are garnering increased attention. Precise model validation is essential for choosing the appropriate model and deciding on its application. Split-sample estimation and validation of clinical prediction models, where data are divided into training and testing sets, may decrease predictive accuracy and precision. Utilizing the entire dataset for estimation and validation improves the sample size for both processes, but overfitting or optimism must be accounted for. The researchers compared split-sample and whole-sample approaches for estimating and validating a suicide prediction model. The study found that both the split-sample and whole-sample prediction models demonstrated similar prospective performance. Performance estimates assessed in the testing set for the split-sample model and through cross-validation for the whole-sample model correctly represented prospective performance. Validation of the whole-sample model using bootstrap optimism correction overestimated prospective performance. The researchers concluded that although previous studies have validated the bootstrap optimism correction for parametric models in small samples, this method did not accurately validate the performance of a rare-event prediction model estimated with random forests in a large clinical dataset. Cross-validation of prediction models estimated using all available data offers precise independent validation while maximizing sample size.
AHRQ-funded; HS026369.
Citation: Coley RY, Liao Q, Simon N .
Empirical evaluation of internal validation methods for prediction in large-scale clinical data with rare-event outcomes: a case study in suicide risk prediction.
BMC Med Res Methodol 2023 Feb 1; 23(1):33. doi: 10.1186/s12874-023-01844-5..
Keywords: Research Methodologies, Risk
Robertson SE, Steingrimsson JA, Dahabreh IJ
Regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population.`
This study looked at recent work on estimating target population conditional average treatment effects (CATEs) using baseline covariate, treatment, and outcome data from the trial and covariate data from the target population that only allows for the examination of heterogeneity over distinct subgroups. The authors described flexible pseudo-outcome regression modeling methods for estimating target population CATEs conditional on discrete or continuous baseline covariates when the trial is embedded in a sample from the target population (i.e., in nested trial designs). They constructed pointwise confidence intervals for the CATE at a specific value of the effect modifiers and uniform confidence bands for the CATE function. Last, they illustrated the methods using data from the Coronary Artery Surgery Study (CASS) to estimate CATEs given history of myocardial infarction and baseline ejection fraction value in the target population of all trial-eligible patients with stable ischemic heart disease.
AHRQ-funded; HS028373.
Citation: Robertson SE, Steingrimsson JA, Dahabreh IJ .
Regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population.`
Eur J Epidemiol 2023 Feb; 38(2):123-33. doi: 10.1007/s10654-022-00901-5..
Keywords: Research Methodologies
Crits-Christoph P, Gallop R, Duong L
Repeated assessments of depressive symptoms in randomized psychosocial intervention trials: best practice for analyzing symptom change over time.
Keywords: Depression, Behavioral Health, Research Methodologies
Optional keywords: mental psychotherapy
Summary
The purpose of this study was to investigate the optimal statistical model for analyzing time effects in psychotherapy randomized trials, specifically when the primary outcome involves repeated assessments of depression symptoms. The researchers utilized data from three studies comparing psychotherapy treatments for major depressive disorder. Self-report ratings were used in Study 1 (N=237) and Study 2 (N=100), while clinician ratings were utilized in Study 3 (N=120). Depression symptoms were assessed at every session in Studies 1 and 2 and monthly in Study 3. Time patterns examined included linear, quadratic, cubic, logarithmic transformation of time, piecewise linear, and unstructured models. The researchers found that in Study 1, a logarithmic-linear model demonstrated the best fit. Study 2 found that all models had negligible support compared to the unstructured model, which was the best fitting. In Study 3, although the cubic model displayed the best fit, it was not significantly superior to the log-linear or unstructured model. The study concluded that when evaluating repeated measures of depression symptoms as the primary outcome, trials should consistently compare various time models, including an unstructured model.
Optional keywords: mental psychotherapy
Summary
The purpose of this study was to investigate the optimal statistical model for analyzing time effects in psychotherapy randomized trials, specifically when the primary outcome involves repeated assessments of depression symptoms. The researchers utilized data from three studies comparing psychotherapy treatments for major depressive disorder. Self-report ratings were used in Study 1 (N=237) and Study 2 (N=100), while clinician ratings were utilized in Study 3 (N=120). Depression symptoms were assessed at every session in Studies 1 and 2 and monthly in Study 3. Time patterns examined included linear, quadratic, cubic, logarithmic transformation of time, piecewise linear, and unstructured models. The researchers found that in Study 1, a logarithmic-linear model demonstrated the best fit. Study 2 found that all models had negligible support compared to the unstructured model, which was the best fitting. In Study 3, although the cubic model displayed the best fit, it was not significantly superior to the log-linear or unstructured model. The study concluded that when evaluating repeated measures of depression symptoms as the primary outcome, trials should consistently compare various time models, including an unstructured model.
AHRQ-funded; HS018440
Citation: Crits-Christoph P, Gallop R, Duong L .
Repeated assessments of depressive symptoms in randomized psychosocial intervention trials: best practice for analyzing symptom change over time.
Psychother Res 2023 Feb;33(2):158-72. doi: 10.1080/10503307.2022.2073289.
Keywords: Depression, Behavioral Health, Research Methodologies
Herman WH, Bullock A, Boltri JM
The National Clinical Care Commission report to Congress: background, methods, and foundational recommendations.
This AHRQ-authored paper describes the background, methods, and recommendations of the National Clinical Care Commission (NCCC) focused on factors likely to improve the delivery of high-quality care to all people with diabetes. It is the first in a series of five articles describing the recommendations. The Commission made recommendations at all levels: patient, practice, health system, and health policy. This is the first paper in a series of five articles about the NCCC recommendations. The five articles include recommendations to 1) reduce diabetes-related risks, prevent type 2 diabetes, and avert diabetes complications through changes in federal policies and programs affecting the general population; 2) prevent type 2 diabetes in at-risk individuals through targeted lifestyle and medication interventions; and 3) improve the treatment of diabetes and its complications to improve the health outcomes of people with diabetes. This first article reviews the successes and limitations of previous federal efforts to combat diabetes, describes the establishment of and charge to the NCCC, and discusses the development of a hybrid conceptual model that guided the NCCC’s novel all-of-government approach to address diabetes as a societal and medical problem. The authors then review the procedures used by the NCCC to gather information from federal agencies, stakeholders, key informants, and the public and to conduct literature reviews. Finally, they review the NCCC's three foundational recommendations: 1) improve the coordination of non-health-related and health-related federal agencies to address the social and environmental conditions that are accelerating the diabetes epidemic; 2) ensure that all Americans at risk for and with diabetes have health insurance and access to health care; and 3) ensure that all federal policies and programs promote health equity in diabetes.
AHRQ-authored; AHRQ-funded.
Citation: Herman WH, Bullock A, Boltri JM .
The National Clinical Care Commission report to Congress: background, methods, and foundational recommendations.
Diabetes Care 2023 Feb; 46(2):e14-e23. doi: 10.2337/dc22-0611..
Keywords: Diabetes, Chronic Conditions, Prevention, Research Methodologies
Anhang Price R, Quigley DD DD, Hargraves JL
A systematic review of strategies to enhance response rates and representativeness of patient experience surveys.
The purpose of this systematic review study was to explore evidence on survey administration strategies to increase response rates and representativeness of patient surveys. The researchers examined 40 peer-reviewed randomized experiments of administration protocols for patient experience surveys. The study found that when compared to mail-only or telephone-only administration of surveys, mail administration with telephone follow-up provides a median response rate benefit of 13%. Researchers also discovered that while surveys administered only by web usually result in lower response rates than those administered by mail or telephone, the limited evidence for a web-mail-telephone process suggests a potential response rate benefit over a mail-telephone process. Monetary incentives are related with substantial improvements in response rates. The study concluded that mixed-mode survey administration results in increased patient survey response rates than a single mode.
AHRQ-funded; HS025920.
Citation: Anhang Price R, Quigley DD DD, Hargraves JL .
A systematic review of strategies to enhance response rates and representativeness of patient experience surveys.
Med Care 2022 Dec;60(12):910-18. doi: 10.1097/mlr.0000000000001784..
Keywords: Patient Experience, Research Methodologies, Health Services Research (HSR)
Saldanha IJ, Adam GP, Bañez LL
Inclusion of nonrandomized studies of interventions in systematic reviews of interventions: updated guidance from the Agency for Health Care Research and Quality Effective Health Care program.
A guidance workgroup comprised systematic review experts utilized an informal consensus generation method to develop guidelines to inform decisions regarding the inclusion of nonrandomized studies of interventions (NRSIs) in systematic reviews (SRs) of the effects of interventions. The study found that varying topics may require varying decisions regarding NRSI inclusion. The researchers identified key considerations to inform the decisions; from refinement of topics through to development of protocols. During the scoping and refinement of topics, considerations were associated with the clinical decisional dilemma, adequacy of randomized controlled trials (RCTs) to address the crucial questions, risk of bias in NRSIs, and the degree to which NRSIs are likely to complement RCTs. When NRSIs are included, during SR team formation, familiarity with topic-specific data sources and advanced analytic methods for NRSIs should be considered. During protocol development, the decision regarding NRSI inclusion or exclusion should be justified, and potential implications explained. When NRSIs are included, the protocol should describe the processes for synthesizing evidence from RCTs and NRSIs and determining the overall strength of evidence. CONCLUSION: We identified specific considerations for decisions regarding NRSI inclusion in SRs and highlight the importance of flexibility and transparency.
AHRQ-authored; AHRQ-funded; 290-2017-00003 -C; 75Q80120D00001- 75Q8120D00003; 75Q80120D00005 - 75Q8120D00009.
Citation: Saldanha IJ, Adam GP, Bañez LL .
Inclusion of nonrandomized studies of interventions in systematic reviews of interventions: updated guidance from the Agency for Health Care Research and Quality Effective Health Care program.
J Clin Epidemiol 2022 Dec; 152:300-06. doi: 10.1016/j.jclinepi.2022.08.015..
Keywords: Evidence-Based Practice, Research Methodologies, Health Services Research (HSR)
Burgermaster M, Rodriguez VA
Psychosocial-behavioral phenotyping: a novel precision health approach to modeling behavioral, psychological, and social determinants of health using machine learning.
The purpose of this study was to demonstrate a novel application of machine learning for psychosocial-behavioral phenotyping, which includes the identification of subgroups with similar combinations of psychosocial characteristics. The researchers conducted a secondary analysis of psychosocial and behavioral data from a community cohort (n = 5,883). The study found 20 psychosocial-behavioral phenotypes. Each phenotype suggested different contextual considerations for intervention design. The researchers concluded that psychosocial-behavioral phenotypes can identify possible targets of intervention.
AHRQ-funded; HS019853.
Citation: Burgermaster M, Rodriguez VA .
Psychosocial-behavioral phenotyping: a novel precision health approach to modeling behavioral, psychological, and social determinants of health using machine learning.
Ann Behav Med 2022 Nov 18;56(12):1258-71. doi: 10.1093/abm/kaac012..
Keywords: Social Determinants of Health, Health Information Technology (HIT), Research Methodologies
Morrow EL, Duff MC, Mayberry LS
Mediators, moderators, and covariates: matching analysis approach for improved precision in cognitive-communication rehabilitation research.
This tutorial’s goals were to (a) increase awareness and use of mediation and moderation models in cognitive-communication rehabilitation research by describing options, benefits, and attainable analytic approaches for researchers with limited resources and sample sizes and (b) describe how these findings may be interpreted for clinicians consuming research to inform clinical care. The authors discuss the potential of mediation and moderation analyses to reduce the research-to-practice gap and describe how researchers may begin to implement these models, even in smaller sample sizes. They describe how researchers may begin to implement these models, even in smaller sample sizes. They believe it is critical to harness new approaches to advance clinical-translational research results for complex, heterogeneous groups with cognitive-communication disorders.
AHRQ-funded; HS026122.
Citation: Morrow EL, Duff MC, Mayberry LS .
Mediators, moderators, and covariates: matching analysis approach for improved precision in cognitive-communication rehabilitation research.
J Speech Lang Hear Res 2022 Nov 17;65(11):4159-71. doi: 10.1044/2022_jslhr-21-00551..
Keywords: Communication, Rehabilitation, Research Methodologies
Holtrop JS, Davis MM
Primary care research is hard to do during COVID-19: challenges and solutions.
This study examined challenges in conducting primary care research during the COVID-19 pandemic. The authors used their experience on over 15 individual projects during the pandemic. They identified 3 key challenges to conducting primary care research: (1) practice delivery trickle-down effects, (2) limited/changing resources and procedures for research, and (3) a generally tense milieu in US society during the pandemic. They presented strategies, informed by a set of questions, to help researchers decide how to address these challenges observed during our studies. They encouraged normalization and self-compassion; and encouraged researchers and funders to embrace pragmatic and adaptive research designs as the circumstances with COVID-19 evolve over time.
AHRQ-funded; HS027080.
Citation: Holtrop JS, Davis MM .
Primary care research is hard to do during COVID-19: challenges and solutions.
Ann Fam Med 2022 Nov-Dec; 20(6):568-72. doi: 10.1370/afm.2889..
Keywords: COVID-19, Primary Care, Health Services Research (HSR), Research Methodologies
Tourani R, Ma S, Usher M
Robust methods for quantifying the effect of a continuous exposure from observational data.
The purpose of this study was to introduce new clinical medicine methods for estimating the effect of intervening on a continuous exposure that are more expansive and robust towards violations of the existing sets of strict assumptions. The researchers based their methods on the critical observation that changes of exposure in the clinical setting are typically achieved gradually, so effect estimates must be "locally" robust in narrower exposure ranges. The study compared the researcher’s methods with a number of existing methods on three simulated studies with escalating complexity. The researchers also applied the methods to data from 14,000 sepsis patients to estimate the effect of antibiotic administration latency on prolonged hospital stay. The researchers concluded that the proposed methods resulted in good performance in all simulation studies.
AHRQ-funded; HS024532.
Citation: Tourani R, Ma S, Usher M .
Robust methods for quantifying the effect of a continuous exposure from observational data.
IEEE J Biomed Health Inform 2022 Nov;26(11):5728-37. doi: 10.1109/jbhi.2022.3201752..
Keywords: Research Methodologies
Russell LB, Huang Q, Lin Y
The electronic health record as the primary data source in a pragmatic trial: a case study.
Electronic health records are a series of overlapping and legacy systems that require time and expertise to use efficiently. Commonly measured patient characteristics are relatively easy to locate for most trial enrollees but less common characteristics are not. Acquiring essential supplementary data - in this trial, state data on hospital admission - can be a lengthy and difficult process.
AHRQ-funded; HS026372.
Citation: Russell LB, Huang Q, Lin Y .
The electronic health record as the primary data source in a pragmatic trial: a case study.
Med Decis Making 2022 Nov;42(8):975-84. doi: 10.1177/0272989x211069980..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Research Methodologies
Adam GP, Pappas D, Papageorgiou H
A novel tool that allows interactive screening of PubMed citations showed promise for the semi-automation of identification of biomedical literature.
This study looked at a novel tool named Pythia that allows interactive screening of PubMed citations to provide semi-automation of identification of biomedical literature for use with systematic reviews. Pythia incorporates a set of natural-language questions with machine-learning algorithms to rank all PubMed citations based on relevance, returning the 100 top-ranked citations. Of the seven systematic reviews conducted, the number of abstracts reviewed per relevant abstract number needed to read was lower than in the manually screened project in four reviews, higher in two, and had mixed results in one. The reviews that had greater overall sensitivity retrieved more relevant citations in early batches, but retrieval was generally unaffected by other aspects, such as study design, study size, and specific key question.
AHRQ-funded; HS027247.
Citation: Adam GP, Pappas D, Papageorgiou H .
A novel tool that allows interactive screening of PubMed citations showed promise for the semi-automation of identification of biomedical literature.
J Clin Epidemiol 2022 Oct;150:63-71. doi: 10.1016/j.jclinepi.2022.06.007..
Keywords: Research Methodologies, Evidence-Based Practice
Kalenderian E, Lee JH, Obadan-Udoh EM
Development of an inventory of dental harms: methods and rationale.
The authors sought to standardize the language of dental adverse events (AEs). Using a multimodal approach, they developed a broad list of dental AEs in which the AEs were classed into 12 categories, with hard tissue injury being noted frequently. Pain was the unexpected AE that was consistently identified with every modality used.
AHRQ-funded; HS024406.
Citation: Kalenderian E, Lee JH, Obadan-Udoh EM .
Development of an inventory of dental harms: methods and rationale.
J Patient Saf 2022 Sep 1;18(6):559-64. doi: 10.1097/pts.0000000000001033..
Keywords: Dental and Oral Health, Patient Safety, Research Methodologies
Oatis CA, Konnyu KJ, Franklin PD
Generating consistent longitudinal real-world data to support research: lessons from physical therapists.
The purpose of this study was to evaluate whether clinicians can generate consistent and standardized real-world data (RWD) to enhance data quality in the course of routine patient care. The researchers collaborated with PT clinicians and experts to generate a web-based comprehensive system to quantify the total dose of PT interventions with type of modality, quantity, intensity, and progressions over time. The system was designed to be implemented in outpatient PT clinics capable of residing alongside or within a clinic’s existing EHR. The study goal was to collect routine clinical data in a format useable by the general population of outpatient physical therapists treating patients post Total Knee Replacement (TKR) and in a structure that would allow easy quantification and analysis across patients, therapists, and sites. Uniform and efficient documentation of real-world PT practice following TKR is essential for the necessary comparative effectiveness research demanded by the currently unexplained practice variation. Over a period of 2 years, physical therapists and PT assistants located in three US states entered data for a total of 161 patients post TKR with 2615 patient visits. No technical problems with the data capture system were reported, and physical therapists noted that data entry was efficient and simple. The researchers concluded that the results demonstrate that routine PT interventions can be captured thoroughly in an efficient, systematic, and consistent manner across real-world therapists and sites.
AHRQ-funded; 75Q80120D00001.
Citation: Oatis CA, Konnyu KJ, Franklin PD .
Generating consistent longitudinal real-world data to support research: lessons from physical therapists.
ACR Open Rheumatol 2022 Sep;4(9):771-74. doi: 10.1002/acr2.11465..
Keywords: Research Methodologies, Patient-Centered Outcomes Research, Evidence-Based Practice
Golmakani MK, Hubbard RA, Miglioretti DL
Nonhomogeneous Markov chain for estimating the cumulative risk of multiple false positive screening tests.
This study addressed the general challenge of estimating the cumulative risk of multiple false positive test results. The authors proposed a nonhomogeneous multistate model to describe the screening process including competing events and developed alternative approaches for estimating the cumulative risk of multiple false positive results using this multistate model based on existing estimators for the cumulative risk of a single false positive. The multistate model was based on existing estimators for the cumulative risk of a single false positive. They compared the performance of the newly proposed models through simulation studies and illustrated model performance using data on screening mammography from the Breast Cancer Surveillance Consortium. They found that in the context of screening mammography that the cumulative risk of multiple false positive results is high. For a high-risk individual, the cumulative probability of at least two false positive mammography results after 10 rounds of annual screening is 40.4.
AHRQ-funded; HS018366.
Citation: Golmakani MK, Hubbard RA, Miglioretti DL .
Nonhomogeneous Markov chain for estimating the cumulative risk of multiple false positive screening tests.
Biometrics 2022 Sep;78(3):1244-56. doi: 10.1111/biom.13484..
Keywords: Research Methodologies, Screening, Imaging, Cancer: Breast Cancer, Cancer
