Search

Background The exponential growth of the biomedical literature necessitates investigating strategies to reduce systematic reviewer burden while maintaining the high standards of systematic review validity and comprehensiveness. Methods We compared the traditional systematic review screening process with (1) a review-of-reviews (ROR) screening approach and (2) a semi-automation screening approach using two publicly available tools (RobotAnalyst and AbstrackR) and different types of training sets (randomly selected citations subjected to dual-review at the title-abstract stage, highly curated citations dually reviewed at the full-text stage, and a combination of the two). We evaluated performance measures of sensitivity, specificity, missed citations, and workload burden Results The ROR approach for treatments of early-stage prostate cancer had a poor sensitivity (0.54) and studies missed by the ROR approach tended to be of head-to-head comparisons of active treatments, observational studies, and outcomes of physical harms and quality of life. Title and abstract screening incorporating semi-automation only resulted in a sensitivity of 100% at high levels of reviewer burden (review of 99% of citations). A highly curated, smaller-sized, training set (n = 125) performed similarly to a larger training set of random citations (n = 938). Conclusion Two approaches to rapidly update SRs—review-of-reviews and semi-automation—failed to demonstrate reduced workload burden while maintaining an acceptable level of sensitivity. We suggest careful evaluation of the ROR approach through comparison of inclusion criteria and targeted searches to fill evidence gaps as well as further research of semi-automation use, including more study of highly curated training sets.

Background The In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS) Survey is the first patient reported outcome measure included in the U.S. Medicare End Stage Renal Disease Quality Incentive Program. Administered twice yearly, it assesses in-center dialysis experience and survey responses are tied to dialysis facility payments. Low response rates, currently approximately 35%, raise concern for possible underrepresentation of patient groups. Methods Cross-sectional analysis of survey administration in 2012 to all in-center hemodialysis patients in Dialysis Clinic, Inc. (DCI) facilities nationally over 18 years old who received hemodialysis at their facility for at least 3 months. Patient-level covariates included demographic, clinical, laboratory, and functional characteristics. Random effects multivariable logistic regression was used to assess survey non-response. Results Among 11,055 eligible patients 6541 (59%) were non-responders. Of the remaining 4514 responders, 549 (14%) surveys were not usable due to presence of proxy help or incomplete responses. Non-responders were more likely to be men, non-white, younger, single, dual Medicare/Medicaid eligible, less educated, non-English speaking, and not active on the transplant list; non-responders had longer ESRD vintage, lower body mass index, lower serum albumin, worse functional status, and more hospitalizations, missed treatments, and shortened treatments. Similar associations were found using more parsimonious multivariable analyses and after imputing missing data. Conclusions Non-responders to the ICH CAHPS significantly differed from responders, broadly spanning individuals with fewer socioeconomic advantages and greater illness burden, raising limitations in interpreting facility survey results. Future research should assess reasons for non-response to improve ICH CAHPS generalizability and utility. Electronic supplementary material The online version of this article (10.1186/s12913-018-3618-4) contains supplementary material, which is available to authorized users.

Objective To identify predictors of participation of patients with advanced cancer in clinical encounters with oncologists and to assess the impact of patient and caregiver participation on perceptions of physician support. Methods This is a secondary data analysis from the Values and Options in Cancer Care study, a cluster randomized clinical trial of a patient-centered communication intervention. Patients and caregivers completed pre-visit and post-visit health and communication measures. Audio recorded patient-caregiver (when present)-physician encounters were coded for active patient/caregiver participation behaviors (eg, question asking, expressing concern) and for physicians' facilitative communication (eg, partnership-building, support). Mixed linear regression models were used to identify patient, physician, and situational factors predicting patient and patient plus caregiver communication behaviors and post-visit outcomes. Results Physician partnership building predicted greater expressions of concern and more assertive responses from patients and patient-caregiver pairs. Patients' perceptions of greater connectedness with their physician predicted fewer patient expressions of concern. Patient perceptions of physician respect for their autonomy were lower among patients accompanied by caregivers. Caregiver perceptions of physician respect for patient autonomy decreased with increasing patient age and varied by site. Conclusions In advanced cancer care, patient and caregiver communication is affected by ecological factors within their consultations. Physicians can support greater patient participation in clinical encounters through facilitative communication such as partnership-building and supportive talk. The presence of a caregiver complicates this environment, but partnership building techniques may help promote patient and caregiver participation during these visits.

Importance Prior studies suggesting clinician fulfillment or denial of requests affects patient satisfaction included limited adjustment for patient confounders. The studies also did not examine distinct request types, yet patient expectations and clinician fulfillment or denial might vary among request types. Objective To examine how patient satisfaction with the clinician is associated with clinician denial of distinct types of patient requests, adjusting for patient characteristics. Design, Setting, and Participants Cross-sectional observational study of 1319 outpatient visits to family physicians (n = 56) by 1141 adults at one Northern California academic health center. Main Outcomes and Measures We used 6 Consumer Assessment of Healthcare Providers and Systems Clinician and Group Adult Visit Survey items to measure patient satisfaction with the visit physician. Standardized items were averaged to form the satisfaction score (Cronbach α = 0.80), which was then percentile-transformed. Seven separate linear mixed-effects models examined the adjusted mean differences in patient satisfaction percentile associated with denial of each of the following requests (if present)—referral, pain medication, antibiotic, other new medication, laboratory test, radiology test, or other test—compared with fulfillment of the respective requests. The models adjusted for patient sociodemographics, weight, health status, personality, worry over health, prior visit with clinician, and the other 6 request categories and their dispositions. Results The mean (SD) age of the 1141 patients was 45.6 (16.1) years, and 902 (68.4%) were female. Among 1319 visits, 897 (68.0%) included at least 1 request; 1441 (85.2%) were fulfilled. Requests by category were referral, 294 (21.1%); pain medication, 271 (20.5%); antibiotic, 107 (8.1%); other new medication, 271 (20.5%); laboratory test, 448 (34.0%); radiology test, 153 (11.6%); and other tests, 147 (11.1%). Compared with fulfillment of the respective request type, clinician denials of requests for referral, pain medication, other new medication, and laboratory test were associated with worse satisfaction (adjusted mean percentile differences, −19.75 [95% CI, −30.75 to −8.74], −10.72 [95% CI, −19.66 to −1.78], −20.36 [95% CI, −29.54 to −11.18], and −9.19 [95% CI, −17.50 to −0.87]), respectively. Conclusions and Relevance Clinician denial of some types of requests was associated with worse patient satisfaction with the clinician, but not for others, when compared with fulfillment of the requests. In an era of patient satisfaction-driven compensation, the findings suggest the need to train clinicians to deal effectively with requests, potentially enhancing patient and clinician experiences.

Objective Assess patient-physician agreement on management goals for chronic musculoskeletal pain and its associations with patient and physician visit experiences. Materials and methods Pre-visit and post-visit questionnaires for 87 primary care visits that involved patients taking opioids for chronic musculoskeletal pain and primary care resident physicians. After each visit, patients and physicians independently ranked 5 pain treatment goals from most to least important. Results In total, 48% of patients ranked reducing pain intensity as their top priority, whereas 22% ranked finding a diagnosis as most important. Physicians ranked improving function as the top priority for 41% of patients, and ranked reducing medication side effects as most important for 26%. The greatest difference between patient and physician rankings was for reducing pain intensity. In regression analyses, neither overall agreement on goals (ie, the physician's first or second priority included the patient's top priority) nor difference in patient versus physician ranking of pain intensity was significantly associated with patient-reported visit experience (β for overall agreement, -0.08; 95% confidence interval [CI], -0.45 to 0.30; P=0.69; β for intensity, -0.06; 95% CI, -0.17 to 0.04; P=0.24) or physician-reported visit difficulty (β for overall agreement, 1.92; 95% CI, -2.70 to 6.55; P=0.41; β for intensity, 0.42; 95% CI, -0.87 to 1.71; P=0.53). Discussion Patients and physicians prioritize substantially different goals for chronic pain management, but there is no evidence that agreement predicts patient experience or physician-reported visit difficulty. Primary care physicians may have adapted to new recommendations that emphasize functional goals and avoidance of long-term opioid therapy, whereas patients continue to focus on reducing pain intensity.

© Meharry Medical College. A diverse physician workforce is needed to increase access to care for underserved populations, particularly as the Affordable Care Act expands insurance coverage. Yet legal restrictions constrain the extent to which medical schools may use race/ethnicity in admissions decisions. We conducted simulations using academic metrics and socioeconomic data from applicants to a California public medical school from 2011 to 2013. The simulations systematically adjusted medical school applicants’ academic metrics for socioeconomic disadvantage. We found that socioeconomic and under- represented minority disparities in admissions could be eliminated while maintaining academic readiness. Adjusting applicant academic metrics using socioeconomic information on medical school applications may be a race- neutral means of increasing the socioeconomic and racial/ethnic diversity of the physician workforce.

Background The breast cancer detection rate is a benchmark measure of screening mammography quality, but its computation requires linkage of mammography interpretive performance information with cancer incidence data. A Medicare claims-based measure of detected breast cancers could simplify measurement of this benchmark and facilitate mammography quality assessment and research. Objectives To validate a claims-based algorithm that can identify with high positive predictive value (PPV) incident breast cancers that were detected at screening mammography. Research design Development of a claims-derived algorithm using classification and regression tree analyses within a random half-sample of Medicare screening mammography claims followed by validation of the algorithm in the remaining half-sample using clinical data on mammography results and cancer incidence from the Breast Cancer Surveillance Consortium (BCSC). Subjects Female fee-for-service Medicare enrollees aged 68 years and older who underwent screening mammography from 2001 to 2005 within BCSC registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=233,044 mammograms obtained by 104,997 women). Measures Sensitivity, specificity, and PPV of algorithmic identification of incident breast cancers that were detected by radiologists relative to a reference standard based on BCSC mammography and cancer incidence data. Results An algorithm based on subsequent codes for breast cancer diagnoses and treatments and follow-up mammography identified incident screen-detected breast cancers with 92.9% sensitivity [95% confidence interval (CI), 91.0%-94.8%], 99.9% specificity (95% CI, 99.9%-99.9%), and a PPV of 88.0% (95% CI, 85.7%-90.4%). Conclusions A simple claims-based algorithm can accurately identify incident breast cancers detected at screening mammography among Medicare enrollees. The algorithm may enable mammography quality assessment using Medicare claims alone.

Since 2001, Medicare has reimbursed computer-aided detection (CAD) during screening mammography. The CAD software tool is used by radiologists to identify lesions suggestive of malignant disease. Research suggests that CAD use increases the rate of false-positive findings of screening mammography and the detection of ductal carcinoma in situ (DCIS).1 Increased DCIS detection could lead to overdiagnosis of breast cancer, particularly among older women at risk for competing causes of death. We estimated the fraction of diagnostic tests, DCIS treatments, and costs attributable to CAD dissemination within the Medicare population, among whom the risk for overdiagnosis may be elevated.

BackgroundMedicare claims data may be a fruitful data source for research or quality measurement in mammography. However, it is uncertain whether claims data can accurately distinguish screening from diagnostic mammograms, particularly when claims are not linked with cancer registry data.ObjectivesTo validate claims-based algorithms that can identify screening mammograms with high positive predictive value (PPV) in claims data with and without cancer registry linkage.Research designDevelopment of claims-derived algorithms using classification and regression tree analyses within a random half-sample of bilateral mammogram claims with validation in the remaining half-sample.SubjectsFemale fee-for-service Medicare enrollees aged 66 years and older, who underwent bilateral mammography from 1999 to 2005 within Breast Cancer Surveillance Consortium (BCSC) registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=383,730 mammograms obtained from 146,346 women).MeasuresSensitivity, specificity, and PPV of algorithmic designation of a "screening" purpose of the mammogram using a BCSC-derived reference standard.ResultsIn claims data without cancer registry linkage, a 3-step claims-derived algorithm identified screening mammograms with 97.1% sensitivity, 69.4% specificity, and a PPV of 94.9%. In claims that are linked to cancer registry data, a similar 3-step algorithm had higher sensitivity (99.7%), similar specificity (62.7%), and higher PPV (97.4%).ConclusionsSimple algorithms can identify Medicare claims for screening mammography with high predictive values in Medicare claims alone and in claims linked with cancer registry data.

Background Screening has become one of our best tools for early detection and prevention of cancer. The group-randomized trial is the most rigorous experimental design for evaluating multilevel interventions. However, identifying the proper sample size for a group-randomized trial requires reliable estimates of intraclass correlation (ICC) for screening outcomes, which are not available to researchers. We present crude and adjusted ICC estimates for cancer screening outcomes for various levels of aggregation (physician, clinic, and county) and provide an example of how these ICC estimates may be used in the design of a future trial. Methods Investigators working in the area of cancer screening were contacted and asked to provide crude and adjusted ICC estimates using the analysis of variance method estimator. Results Of the 29 investigators identified, estimates were obtained from 10 investigators who had relevant data. ICC estimates were calculated from 13 different studies, with more than half of the studies collecting information on colorectal screening. In the majority of cases, ICC estimates could be adjusted for age, education, and other demographic characteristics, leading to a reduction in the ICC. ICC estimates varied considerably by cancer site and level of aggregation of the groups. Conclusions Previously, only two articles had published ICCs for cancer screening outcomes. We have complied more than 130 crude and adjusted ICC estimates covering breast, cervical, colon, and prostate screening and have detailed them by level of aggregation, screening measure, and study characteristics. We have also demonstrated their use in planning a future trial and the need for the evaluation of the proposed interval estimator for binary outcomes under conditions typically seen in GRTs.