An Approach to Selecting Single or Multiple Social Risk Factors for Clinic-Based Screening.
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ABSTRACT:
SUBMITTER: Steiner JF
PROVIDER: S-EPMC8858361 | biostudies-literature | 2022 Feb
REPOSITORIES: biostudies-literature
Publications
An Approach to Selecting Single or Multiple Social Risk Factors for Clinic-Based Screening.
Steiner John F JF Goodrich Glenn K GK Moore Kelly R KR Manson Spero M SM Gottlieb Laura M LM Kelly Cheryl C Schroeder Emily B EB
Journal of general internal medicine 20210329 3
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Project description:ImportanceProviding person-centered dermatologic care includes consideration of social risk factors, such as housing instability and unreliable transportation, that may affect clinical management. Patients' perspectives on social risk screening and documentation in dermatology clinics have not yet been evaluated.ObjectiveTo understand patients' perspectives on social risk screening and documentation in a dermatology clinic.Design, setting, and participantsThis mixed-methods study used a survey and semistructured interviews and was conducted in a general dermatology clinic at a large urban public hospital. Patients at the clinic were eligible to complete the survey if they were 18 years or older; able to speak and read English, Spanish, or Cantonese; and comfortable using a computer tablet. Survey participants who preferred to use English were eligible for interviews. The survey included social risk screening questions, measures of acceptability, and questions on social risk factors associated with patient acceptability. Semistructured interviews were conducted to explore attitudes and beliefs about social risk screening and documentation. Survey and interview findings were integrated during data analysis through development of themes and joint display. Data were analyzed from December 2021 to April 2023.Main outcomes and measuresThere were 2 outcome measures of acceptability: appropriateness of screening in a dermatology clinic and comfort with documentation of social risk in the electronic health record (EHR).ResultsA total of 135 participants (including 73 males [54.1%]) answered both measures of acceptability in the survey. Of these participants, 116 (85.9%) reported that social risk screening in their dermatology clinic was very or somewhat appropriate and 85 (63.0%) reported being completely or somewhat comfortable with having their social risks documented in the EHR. Themes that were developed from surveys and interviews were the (1) role of interpersonal factors in willingness to disclose social risks, (2) implications of institutional trust for willingness to disclose and comfort with documentation, and (3) relevance of screening in a dermatology clinic.Conclusions and relevanceResults of this study showed that most participants found social risk screening to be appropriate in a dermatology clinic, although a smaller proportion of participants were comfortable with EHR documentation of their social risks. Optimizing patients' trust in their physicians and the medical system, while addressing privacy and discrimination concerns, may help facilitate disclosure of social risks.
| S-EPMC10600715 | biostudies-literature
Project description:BackgroundA key aspect of randomized trial design is the choice of risk group. Some trials include patients from the entire at-risk population, others accrue only patients deemed to be at increased risk. We present a simple statistical approach for choosing between these approaches. The method is easily adapted to determine which of several competing definitions of high risk is optimal.MethodWe treat eligibility criteria for a trial, such as a smoking history, as a prediction rule associated with a certain sensitivity (the number of patients who have the event and who are classified as high risk divided by the total number patients who have an event) and specificity (the number of patients who do not have an event and who do not meet criteria for high risk divided by the total number of patients who do not have an event). We then derive simple formulae to determine the proportion of patients receiving intervention, and the proportion who experience an event, where either all patients or only those at high risk are treated. We assume that the relative risk associated with intervention is the same over all choices of risk group. The proportion of events and interventions are combined using a net benefit approach and net benefit compared between strategies.ResultsWe applied our method to design a trial of adjuvant therapy after prostatectomy. We were able to demonstrate that treating a high risk group was superior to treating all patients; choose the optimal definition of high risk; test the robustness of our results by sensitivity analysis. Our results had a ready clinical interpretation that could immediately aid trial design.ConclusionThe choice of risk group in randomized trials is usually based on rather informal methods. Our simple method demonstrates that this decision can be informed by simple statistical analyses.
| S-EPMC1609186 | biostudies-literature
Project description:BackgroundHospitals are increasingly screening patients for social risk factors to help improve patient and population health. Intelligence gained from such screening can be used to inform social need interventions, the development of hospital-community collaborations, and community investment decisions.ObjectiveWe evaluated the frequency of admitted patients' social risk factors and examined whether these factors differed between hospitals within a health system. A central goal was to determine if community-level social need interventions can be similar across hospitals.Design and participantsWe described the development, implementation, and results from Northwell Health's social risk factor screening module. The statistical sample included patients admitted to 12 New York City/Long Island hospitals (except for maternity/pediatrics) who were clinically screened for social risk factors at admission from June 25, 2019, to January 24, 2020.Main measuresWe calculated frequencies of patients' social needs across all hospitals and for each hospital. We used chi-square and Friedman tests to evaluate whether the hospital-level frequency and rank order of social risk factors differed across hospitals.ResultsPatients who screened positive for any social need (n = 5196; 6.6% of unique patients) had, on average, 2.3 of 13 evaluated social risk factors. Among these patients, the most documented social risk factor was challenges paying bills (29.4%). The frequency of 12 of the 13 social risk factors statistically differed across hospitals. Furthermore, a statistically significant variance in rank orders between the hospitals was identified (Friedman test statistic 30.8 > 19.6: χ2 critical, p = 0.05). However, the hospitals' social need rank orders within their respective New York City/Long Island regions were similar in two of the three regions.ConclusionsHospital patients' social needs differed between hospitals within a metropolitan area. Patients at different hospitals have different needs. Local considerations are essential in formulating social need interventions and in developing hospital-community partnerships to address these needs.
| S-EPMC9086091 | biostudies-literature
Project description:ObjectiveScaling evidence-based interventions (EBIs) from pilot phase remains a pressing challenge in efforts to address health-related social needs (HRSN) and improve population health. This study describes an innovative approach to sustaining and further spreading DULCE (Developmental Understanding and Legal Collaboration for Everyone), a universal EBI that supports pediatric clinics to implement the American Academy of Pediatrics' Bright Futures™ guidelines for infants' well-child visits (WCVs) and introduces a new quality measure of families' HRSN resource use.MethodsBetween August 2018 and December 2019, seven teams in four communities in three states implemented DULCE: four teams that had been implementing DULCE since 2016 and three new teams. Teams received monthly data reports and individualized continuous quality improvement (CQI) coaching for six months, followed by lighter-touch support via quarterly group calls (peer-to-peer learning and coaching). Run charts were used to study outcome (percent of infants that received all WCVs on time) and process measures (percent of families screened for HRSN and connected to resources).ResultsIntegrating three new sites was associated with an initial regression of outcome: 41% of infants received all WCVs on time, followed by improvement to 48%. Process performance was sustained or improved: among 989 participating families, 84% (831) received 1-month WCVs on time; 96% (946) were screened for seven HRSN, 54% (508) had HRSN, and 87% (444) used HRSN resources.ConclusionAn innovative, lighter-touch CQI approach to a second phase of scale-up resulted in sustainment or improvements in most processes and outcomes. Outcomes-oriented CQI measures (family receipt of resources) are an important addition to more traditional process-oriented indicators.
| S-EPMC10012656 | biostudies-literature
Project description:Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model's confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmacophore models were proposed. Both approaches to some extent correspond to commonly used consensus approaches like the common hit approach or the one based on a logical OR operation uniting hit lists of individual models. Unlike some known approaches, the proposed ones can rank compounds retrieved by multiple models. These approaches were benchmarked on multiple ChEMBL datasets used for ligand-based pharmacophore modeling and externally validated on corresponding DUD-E datasets. The influence of complexity of pharmacophores and their performance on a calibration set on results of virtual screening was analyzed. It was shown that Max and Mean approaches have superior early enrichment to the commonly used approaches. Thus, a well-performing, easy-to-implement, and probabilistic alternative to existing approaches for pharmacophore-based virtual screening was proposed.
| S-EPMC7024325 | biostudies-literature
Project description:BackgroundIndividuals often report concurrent social risk factors such as food insecurity, unstable housing, and transportation barriers. Comparing relative changes between pairs of social risk factors may identify those that are more resistant to change.ObjectiveThe objective of this study was to develop a method to describe relative changes in pairs of social risk factors.Research designThis was a prospective cohort study.SubjectsParticipants in a randomized controlled trial of hypertension care in an Urban Indian Health Organization.MeasuresWe measured 7 social risk factors (housing, transportation, food, clothing, health care, utilities, and debts) at enrollment, 6, and 12 months among 295 participants in the trial. We hypothesized that pairwise comparisons could identify social risk factors that were less likely to change over time. We used conditional odds ratios (ORs) with 95% confidence intervals (CIs) to rank each pair.ResultsFood, clothing, health care, utilities, and debts had more changes between 0 and 6 months relative to housing (OR=2.3, 3.4, 4.7, 3.5, and 3.4, respectively; all 95% CI excluded 1.0). These same social risk factors also had more changes between baseline and 6 months relative to transportation (OR=2.8, 3.4, 4.9, 4.7, and 4.1, respectively; all 95% CI excluded 1.0). Changes in housing and transportation risk factors were comparable (OR=0.7, 95% CI: 0.4-1.4). Relative changes between 6 and 12 months were similar.ConclusionsHousing and transportation exhibited fewer relative changes than other social risk factors and might be more resistant to change. Awareness of the relationships between social risk factors can help define priorities for intervention.
| S-EPMC9140194 | biostudies-literature
Project description:BackgroundExtensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate. We use 64 two-dimensional speckle tracking echocardiography (2D-STE) features and seven clinical features to predict whether one has CHD.MethodsWe develop a machine learning approach that integrates a number of popular classification methods together by model stacking, and generalize the traditional stacking method to a two-step stacking method to improve the diagnostic performance.ResultsBy borrowing strengths from multiple classification models through the proposed method, we improve the CHD classification accuracy from around 70-87.7% on the testing set. The sensitivity of the proposed method is 0.903 and the specificity is 0.843, with an AUC of 0.904, which is significantly higher than those of the individual classification models.ConclusionOur work lays a foundation for the deployment of speckle tracking echocardiography-based screening tools for coronary heart disease.
| S-EPMC8196502 | biostudies-literature
Project description:Introduction/objectivesHealth-related social needs (HRSN) screening efforts have reported high rates of identified social needs. Little is known if efforts to conduct HRSN screening in resource-constrained federally-qualified health centers (FQHC) successfully captures a representative patient population.MethodsThis cross-sectional study extracted EMR data from 2016 to 2020 for 4731 screened patients from 7 affiliated clinics of a FQHC. Unscreened patients were pulled as a random sample from the study period. A multivariable logistic regression was used to identify sociodemographic traits, chronic disease diagnoses and burden, and clinic visit type and frequency associated with being screened for HRSN.ResultsBHC screened 4731 unique patients or <1% of the total clinic population. Screened patients had a median of 3.3 (±2.5) unmet HRSN. Medicaid patients had higher odds of being screened (aOR = 1.38, CI 1.19-1.61) relative to Medicare patients. The odds of being screened for social needs increased with more provider visits per year: compared to fewer than 1 visit per year, patients with 1 to 3 provider visits (aOR = 2.06, CI 1.73-2.32), 4 to 6 provider visits (aOR = 3.34, CI 2.89-3.87), and more than 6 provider visits (aOR = 5.16, CI 4.35-6.12) all had higher odds of social needs screening. Patients with a higher comorbid disease burden (>2 conditions, aOR = 2.80, CI 2.07-3.79) had higher odds of screening.ConclusionsOur findings demonstrate an increased likelihood to screen patients who visit outpatient services more often and have a higher comorbid disease burden. To meet state-level Medicaid requirements, resource-constrained FQHCs that implement clinic wide HRSN screening may be well served to identify a priori strategies to ensure representative and equitable screening across the patient population.
| S-EPMC9393584 | biostudies-literature
Project description:BackgroundThis study developed a new lung cancer risk prediction model for the Korean population and evaluated the performance, compared to the previously reported risk models developed in Western countries.MethodsAmong the 6,811,893 people who received health examinations from the Korean National Health Insurance Service, 969,351 ever-smokers (40-79 years) were included. Performance of Bach, Lung Cancer Risk Models for Screening, PLCOM2012, Pittsburgh, and Liverpool Lung Project models were evaluated. The ever-smokers were divided into the training and validation datasets by random sampling. The lung cancer risk model was developed and validated in the Korean population. The efficiency of model-based selection for lung cancer screening was compared with the eligible criteria of the National Lung Screening Trial (NLST).ResultsThe Korean lung cancer risk model showed the area under the curve and expected/observed (E/O) ratio of 0.816 and 0.983 in the training dataset and 0.816 and 0.988 in the validation dataset. The Korean lung cancer risk model included age-mean of age, square of age-mean of age, sex, square root of pack-years of smoking, years since cessation, physical activity, alcohol consumption, body mass index, and medical history of chronic pulmonary obstructive disease, emphysema, pneumoconiosis, and interstitial pulmonary disease. Compared with the NLST criteria, the Korean lung cancer risk model's cut-off criteria (>2.1%) had more improved sensitivity (61.4% vs. 44.3%) and positive predictive value (4.1% vs. 2.9%). The Korean lung cancer risk model showed better discrimination and calibration than previously developed models in Western population.ConclusionsThe Korean lung cancer risk model can select eligible population for low-dose computed tomography screening among the Asian population. The efficiency of risk model-based selection for lung cancer screening is superior to that of fixed criteria-based selection.
| S-EPMC8743515 | biostudies-literature
Project description:BackgroundCOVID-19 has changed healthcare access and delivery, especially impacting older adults. The Community Paramedicine at Clinic (CP@clinic) program is a chronic disease prevention, management, and health promotion program for community-dwelling low-income older adults. We investigated a telephone-based CP@clinic program adaptation during the pandemic.MethodsCommunity paramedics delivered CP@clinic via telephone to residents of 36 social housing buildings. They conducted screening for COVID-19, emergency preparedness, and social health factors. Community paramedics provided education on staying safe, self-isolating, self-monitoring, and preparing for pandemics using governmental infographics. Descriptive analysis was conducted on assessments completed between March and June 2020. Paramedic documentation was thematically analyzed to identify common themes.ResultsAll 191 participants had ≥ 1 telephone visit and 34.6% had ≥ 2 telephone visits, 82.8% were aged 65 years and older, 30.9% had internet access, and 57.9% had cable TV (limiting exposure to COVID-19 information). The CP@clinic program infrastructure provided a platform for paramedics to swiftly contact many vulnerable older adults to screen for COVID-19, educate on safe practices, and facilitate healthcare access. One-quarter of participants screened positive for social isolation. Thematic analysis described participants' experiences adapting to daily life in the pandemic, emotional experience during the pandemic, and paramedics supporting participants during the pandemic.ConclusionsPublic health interventions are needed for low-income or hard-to-reach older adults, especially during pandemics. Community paramedics were able to support vulnerable older adults living in social housing through the unique CP@clinic adaptation. This innovative program delivery increased vulnerable populations' access to public health services and information at a time of great health need.
| S-EPMC11603842 | biostudies-literature