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Screening with fecal occult blood tests (FOBT) reduces colorectal cancer mortality. Failure to complete repeat tests may compromise screening effectiveness. We conducted a systematic review of repeat FOBT across diverse health care settings. We searched MEDLINE, Embase, and the Cochrane Library for studies published from 1997 to 2017 and reported repeat FOBT over ≥2 screening rounds. Studies (n = 27 reported in 35 articles) measured repeat FOBT as (i) proportion of Round 1 participants completing repeat FOBT in Round 2; (ii) proportion completing two, consecutive FOBT; or (iii) proportion completing ≥3 rounds. Among those who completed FOBT in Round 1, 24.6% to 89.6% completed repeat FOBT in Round 2 [median: 82.0%; interquartile range (IQR): 73.7%-84.6%]. The proportion completing FOBT in two rounds ranged from 16.4% to 80.0% (median: 46.6%; IQR: 40.5%-50.0%), and in studies examining ≥3 rounds, repeat FOBT ranged from 0.8% to 64.1% (median: 39.2%; IQR: 19.7%-49.4%). Repeat FOBT appeared higher in mailed outreach (69.1%-89.6%) compared with opportunistic screening (24.6%-48.6%). Few studies examined correlates of repeat FOBT. In summary, we observed a wide prevalence of repeat FOBT, and prevalence generally declined in successive screening rounds. Interventions that increase and maintain participation in FOBT are needed to optimize effectiveness of this screening strategy.

BackgroundOver the past decade, nearly half of internal medicine residencies have implemented block clinic scheduling; however, the effects on residency-related outcomes are unknown. The authors systematically reviewed the impact of block versus traditional ambulatory scheduling on residency-related outcomes, including (1) resident satisfaction, (2) resident-perceived conflict between inpatient and outpatient responsibilities, (3) ambulatory training time, (4) continuity of care, (5) patient satisfaction, and (6) patient health outcomes.MethodThe authors reviewed the following databases: Ovid MEDLINE, Ovid MEDLINE InProcess, EBSCO CINAHL, EBSCO ERIC, and the Cochrane Library from inception through March 2017 and included studies of residency programs comparing block to traditional scheduling with at least one outcome of interest. Two authors independently extracted data on setting, participants, schedule design, and the outcomes of interest.ResultsOf 8139 studies, 11 studies of fair to moderate methodologic quality were included in the final analysis. Overall, block scheduling was associated with marked improvements in resident satisfaction (n = 7 studies, effect size range - 0.3 to + 0.9), resident-perceived conflict between inpatient and outpatient responsibilities (n = 5, effect size range + 0.3 to + 2.6), and available ambulatory training time (n = 5). Larger improvements occurred in programs implementing short (1 week) ambulatory blocks. However, block scheduling may result in worse physician continuity (n = 4). Block scheduling had inconsistent effects on patient continuity (n = 4), satisfaction (n = 3), and health outcomes (n = 3).DiscussionAlthough block scheduling improves resident satisfaction, conflict between inpatient and outpatient responsibilities, and ambulatory training time, there may be important tradeoffs with worse care continuity.

BACKGROUND:Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown. METHODS AND RESULTS:We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models. CONCLUSIONS:Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.

RationalePredicting which patients are at highest risk for readmission after hospitalization for pneumonia could enable hospitals to proactively reallocate scarce resources to reduce 30-day readmissions.ObjectivesTo synthesize the available literature on readmission risk prediction models for adults who are hospitalized because of pneumonia and describe their performance.MethodsWe systematically searched Ovid MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature databases from inception through July 2015. We included studies of adults discharged with pneumonia that developed or validated a model that predicted hospital readmission. Two independent reviewers abstracted data and assessed the risk of bias.Measurements and main resultsOf 992 citations reviewed, 7 studies met inclusion criteria, which included 11 unique risk prediction models. All-cause 30-day readmission rates ranged from 11.8 to 20.8% (median, 17.3%). Model discrimination (C statistic) ranged from 0.59 to 0.77 (median, 0.63) with the highest-quality, best-validated model, the Centers for Medicare and Medicaid Services Pneumonia Administrative Model performing modestly (C Statistic of 0.63 in 4 separate multicenter cohorts). The best performing model (C statistic of 0.77) was a single-site study that lacked internal validation. The models had adequate calibration, with patients predicted as high risk for readmission having a higher average observed readmission rate than those predicted to be low risk. None of the studies included pneumonia illness severity scores, and only one included measures of in-hospital clinical trajectory and stability on discharge, robust predictors of readmission.ConclusionsWe found a limited number of validated pneumonia-specific readmission models, and their predictive ability was modest. To improve predictive accuracy, future models should include measures of pneumonia illness severity, hospital complications, and stability on discharge.

Background: Despite the significant societal burden of human papillomavirus (HPV)–associated cancers, clinical screening interventions for HPV‐associated noncervical cancers are not available. Blood‐based biomarkers may help close this gap in care. Methods: Five databases were searched, 5687 articles were identified, and 3631 unique candidate titles and abstracts were independently reviewed by 2 authors; 702 articles underwent a full‐text review. Eligibility criteria included the assessment of a blood‐based biomarker within a cohort or case‐control study. Results: One hundred thirty‐seven studies were included. Among all biomarkers assessed, HPV‐16 E seropositivity and circulating HPV DNA were most significantly correlated with HPV‐associated cancers in comparison with cancer‐free controls. In most scenarios, HPV‐16 E6 seropositivity varied nonsignificantly according to tumor type, specimen collection timing, and anatomic site (crude odds ratio [cOR] for p16+ or HPV+ oropharyngeal cancer [OPC], 133.10; 95% confidence interval [CI], 59.40‐298.21; cOR for HPV‐unspecified OPC, 25.41; 95% CI, 8.71‐74.06; cOR for prediagnostic HPV‐unspecified OPC, 59.00; 95% CI, 15.39‐226.25; cOR for HPV‐unspecified cervical cancer, 12.05; 95% CI, 3.23‐44.97; cOR for HPV‐unspecified anal cancer, 73.60; 95% CI, 19.68‐275.33; cOR for HPV‐unspecified penile cancer, 16.25; 95% CI, 2.83‐93.48). Circulating HPV‐16 DNA was a valid biomarker for cervical cancer (cOR, 15.72; 95% CI, 3.41‐72.57). In 3 cervical cancer case‐control studies, cases exhibited unique microRNA expression profiles in comparison with controls. Other assessed biomarker candidates were not valid. Conclusions: HPV‐16 E6 antibodies and circulating HPV‐16 DNA are the most robustly analyzed and most promising blood‐based biomarkers for HPV‐associated cancers to date. Comparative validity analyses are warranted. Variations in tumor type–specific, high‐risk HPV DNA prevalence according to anatomic site and world region highlight the need for biomarkers targeting more high‐risk HPV types. Further investigation of blood‐based microRNA expression profiling appears indicated. A number of blood‐based biomarkers for HPV‐associated cancers have been evaluated. Among these, HPV‐16 E6 antibodies and circulating HPV DNA have exhibited the most promising performance characteristics. [ABSTRACT FROM AUTHOR]

Objective To review the effect of patient decision aids for adults making treatment decisions regarding the management of chronic musculoskeletal pain. Methods We performed a systematic review of randomized controlled trials of adults using patient decision aids to make treatment decisions for chronic musculoskeletal pain in the outpatient setting. Results Of 477 records screened, 17 met the inclusion criteria. Chronic musculoskeletal pain conditions included osteoarthritis of the hip, knee, or trapeziometacarpal joint and back pain. Thirteen studies evaluated the use of a decision aid for deciding between surgical and nonsurgical management. The remaining four studies evaluated decision aids for nonsurgical treatment options. Outcomes included decision quality, pain, function, and surgery utilization. The effects of decision aids on decision-making outcomes were mixed. Comparing decision aids with usual care, all five studies that examined knowledge scores found improvement in patient knowledge. None of the four studies that evaluated satisfaction with the decision-making process found a difference with use of a decision aid. There was limited and inconsistent data on other decision-related outcomes. Of the eight studies that evaluated surgery utilization, seven found no difference in surgery rates with use of a decision aid. Five studies made comparisons between different types of decision aids, and there was no clearly superior format. Conclusions Decision aids may improve patients' knowledge about treatment options for chronic musculoskeletal pain but largely did not impact other outcomes. Future efforts should focus on improving the effectiveness of decision aids and incorporating nonpharmacologic and nonsurgical management options. [ABSTRACT FROM AUTHOR]

Background: Over the past decade, nearly half of internal medicine residencies have implemented block clinic scheduling; however, the effects on residency-related outcomes are unknown. The authors systematically reviewed the impact of block versus traditional ambulatory scheduling on residency-related outcomes, including (1) resident satisfaction, (2) resident-perceived conflict between inpatient and outpatient responsibilities, (3) ambulatory training time, (4) continuity of care, (5) patient satisfaction, and (6) patient health outcomes.Method: The authors reviewed the following databases: Ovid MEDLINE, Ovid MEDLINE InProcess, EBSCO CINAHL, EBSCO ERIC, and the Cochrane Library from inception through March 2017 and included studies of residency programs comparing block to traditional scheduling with at least one outcome of interest. Two authors independently extracted data on setting, participants, schedule design, and the outcomes of interest.Results: Of 8139 studies, 11 studies of fair to moderate methodologic quality were included in the final analysis. Overall, block scheduling was associated with marked improvements in resident satisfaction (n = 7 studies, effect size range - 0.3 to + 0.9), resident-perceived conflict between inpatient and outpatient responsibilities (n = 5, effect size range + 0.3 to + 2.6), and available ambulatory training time (n = 5). Larger improvements occurred in programs implementing short (1 week) ambulatory blocks. However, block scheduling may result in worse physician continuity (n = 4). Block scheduling had inconsistent effects on patient continuity (n = 4), satisfaction (n = 3), and health outcomes (n = 3).Discussion: Although block scheduling improves resident satisfaction, conflict between inpatient and outpatient responsibilities, and ambulatory training time, there may be important tradeoffs with worse care continuity. [ABSTRACT FROM AUTHOR]