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Few evidence-based tools exist to support identification of older community dwelling adults at risk for unwanted transitions in living environment leading to missed opportunities to modify care plans to support aging-in-place and/or establish end-of-life care goals. An interpretable and actionable tool for assessing a person's risk of experiencing a transition is introduced. Logistic regression analysis of 14,772 transition opportunities (i.e. 12-month periods) for 4,431 respondents to the National Health and Aging Trends Study (NHATS) rounds 1-7. Results were visualized in a nomogram. Unmarried males of increasing age with chronic disease, greater functional dependence, overnight hospitalizations, not living in a single-family home, and limited social network, have elevated risk of experiencing a transition in living environment in a 12-month period. Homecare nurses are uniquely qualified to identify social determinants of health and can use this evidence-based tool to identify individuals who may benefit from transitional care assistance.

Integrating behavioral health into primary care can increase patient access to treatments for behavioral health disorders, especially in rural areas. The first step of integrated care implementations is the need to identify at-risk patients and effectively communicate patient screening results to the care team. The use of technology can facilitate patient screening and incorporate screening data into electronic health records. This paper describes the development of a tablet-based screening system to facilitate behavioral health integration in a rural primary care clinic, discusses the preliminary impact of digital screening on workflows, and provides recommendations for the use of technology for screening. A tablet-based assessment was developed to screen patients for behavioral health concerns and was implemented within a rural primary care clinic. The system was created using the Visual Signature Capture system, which integrates directly with the electronic health record. Following the initial assessment, patients are screened as frequently as every 30 days with a mini-screen assessment, consisting of multiple screening tools for mental health and substance use. The tablet-based screening system had a positive impact on clinician workflows and the overall effectiveness of clinic operations. This system supports providers in addressing the behavioral health needs of patients that often go unrecognized in primary care., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Precision health initiatives for end-of-life planning require robust methods for identifying patient risk for decline and mortality. The Outcome and Assessment Information Set (OASIS) surprise question (SQ; M1034 Overall Status) is the primary tool for evaluating risks in homebound older adults. However, the OASIS-D, Released in 2019, eliminates this question. This study examines the prognostic ability of 12- and 24-month mortality risk reflected in the OASIS-SQ and develops an alternative approach for classifying mortality risk to support decision-making in the absence of the OASIS-SQ., Design: Retrospective secondary data analysis., Setting/participants: A nationally representative sample of 69 097 OASIS-C assessments (2012) linked to the Master Beneficiary Summary file (2012 and 2013)., Measurements: Survival analysis, k-means clustering, and Cohen κ coefficient with Z test., Results: The OASIS-SQ predicts mortality (35% at 12 and 45% at 24 months; P < .001). Cluster analysis identified 2 risk groups: OASIS activity of daily living "ADL total scores" >15 = (lower risk) and ≤15 = (higher risk) for 24-month mortality. Model agreement is weak for both cluster 1 and cluster 2, the OASIS-SQ κ = 0.20, 95% confidence interval (CI) = .19 to .21, and "alive/not alive" κ = .17, 95% CI = .16 to .18., Conclusion: The OASIS-SQ and "ADL total score" are almost equally likely to predict 24-month mortality; therefore, it was reasonable to use the "ADL total score" as a substitute for the OASIS-SQ. Removal of the OASIS-SQ leaves home care providers with few clear options for risk screening resulting in missed opportunities to refer to palliative or hospice services.

This study uses observational causal inference to evaluate the impact of different combinations of home care services (nursing, therapies, social work, home aides) on end-of-episode disposition for individuals with chronic diseases associated with the circulatory, endocrine, and musculoskeletal systems. The potential to generate actionable recommendations for personalizing home care services, or treatment plans, from limited clinical and care needs data is demonstrated. For patients with chronic disease in the circulatory or musculoskeletal systems, a 2.91% and 3.38% decrease, respectively, in acute care hospitalization rates could be obtained by providing patients with therapy and nursing services, rather than therapy services alone.

Objective: Demonstrate how observational causal inference methods can generate insights into the impact of chronic disease combinations on patients' 30-day hospital readmissions., Materials and Methods: Causal effect estimation was used to quantify the impact of each risk factor scenario (ie, chronic disease combination) associated with chronic kidney disease and heart failure (HF) for adult Medicaid beneficiaries with initial hospitalizations in 2 New York State counties. The experimental protocol: (1) created matched risk factor and comparator groups, (2) assessed covariate balance in the matched groups, and (3) estimated causal effects and their statistical significance. Causality lattices summarized the impact of chronic disease comorbidities on readmissions., Results: Chronic disease combinations were ordered with respect to their causal impact on readmissions. Of disease combinations associated with HF, the combination of HF, coronary artery disease, and tobacco abuse (in that order) had the highest causal effect on readmission rate (+22.3%); of disease combinations associated with chronic kidney disease, the combination of chronic kidney disease, coronary artery disease, and diabetes had the highest effect (+9.5%)., Discussion: Multi-hypothesis causal analysis reveals the effects of chronic disease comorbidities on health outcomes. Understanding these effects will guide the development of health care programs that address unique care needs of different patient subpopulations. Additionally, these insights bring new attention to individuals at high risk for readmission based on chronic disease comorbidities, allowing for more personalized attention and prioritization of care., Conclusion: Multi-hypothesis causal analysis, a new methodological tool, generates meaningful insights from health care claims data, guiding the design of care and intervention programs.

Health disparities in low-income populations complicate care for at-risk individuals or those diagnosed with lung cancer and may influence their patterns of healthcare utilization. The purpose of this study is to examine whether age, sex, provider's affiliation, Medicare dual eligibility, and number of comorbidities can predict healthcare utilization, as well as to examine factors influencing mortality in lung biopsy patients. A retrospective review of de-identified Medicaid claims of adults having a lung biopsy in 2013 resulted in classification into lung cancer and non-lung cancer cases based on a lung cancer diagnostic code within 30 days after biopsy. Biopsy cases were further divided by whether or not the provider's institution was accredited by the Commission on Cancer (CoC). Inpatient (IP), outpatient (OP), and emergency department (ED) utilization was followed from initial date of biopsy through 2015, or to the earliest date of death, disenrollment, or study end for both groups. The result of Cox proportional hazards regression model indicated that age and the number of comorbidities significantly predicted OP use and the number of comorbidities significantly predicted ED use in patients with lung cancer. However, for non-lung cancer patients, only the number of comorbidities significantly predicted IP and ED uses. Furthermore, for patients with lung cancer, the significant factors of mortality included IP use per month and the number of comorbidities. Patients with lung cancer who received a lung biopsy by a CoC-accredited organization had a longer time of survival from the biopsy event. Our findings suggest that understanding predictors of healthcare utilization and mortality may create opportunities to improve health and quality of life through better healthcare coordination.

Background: Failure to address social determinants of health (SDH) may contribute to the problem of readmissions in high-risk individuals. Comprehensive shared care plans (CSCP) may improve care continuity and health outcomes by communicating SDH risk factors across settings., Purpose: The purpose of this study to evaluate the state of knowledge for integrating SDH into a CSCP. Our scoping review of the literature considered 13,886 articles, of which seven met inclusion criteria., Results: Identified themes were: integrate health and social sectors; interoperability; standardizing ontologies and interventions; process implementation; professional tribalism; and patient centeredness., Discussion: There is an emerging interest in bridging the gap between health and social service sectors. Standardized ontologies and theoretical definitions need to be developed to facilitate communication, indexing, and data retrieval., Conclusions: We identified a gap in the literature that indicates that foundational work will be required to guide the development of a CSCP that includes SDH that can be shared across settings. The lack of studies published in the United States suggests that this is a critical area for future research and funding., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Context: Care continuity during transitions between the hospital and home requires reliable communication between providers and settings and an understanding of social determinants that influence recovery., Case Description: The coordinating transitions intervention uses real time alerts, delivered directly to the primary care practice for complex chronically ill patients discharged from an acute care setting, to facilitate nurse care coordinator led telephone outreach. The intervention incorporates claims-based risk stratification to prioritize patients for follow-up and an assessment of social determinants of health using the Patient-centered Assessment Method (PCAM). Results from transitional care are stored and transmitted to qualified healthcare providers across the continuum., Findings: Reliance on tools that incorporated interoperability standards facilitated exchange of health information between the hospital and primary care. The PCAM was incorporated into both the clinical and informational workflow through the collaboration of clinical, industry, and academic partners. Health outcomes improved at the study practice over their baseline and in comparison with control practices and the regional Medicaid population., Major Themes: Current research supports the potential impact of systems approaches to care coordination in improving utilization value after discharge. The project demonstrated that flexibility in developing the informational and clinical workflow was critical in developing a solution that improved continuity during transitions. There is additional work needed in developing managerial continuity across settings such as shared comprehensive care plans., Conclusions: New clinical and informational workflows which incorporate social determinant of health data into standard practice transformed clinical practice and improved outcomes for patients.

Economically disadvantaged individuals with chronic disease have high rates of in-patient (IP) readmission and emergency department (ED) utilization following initial hospitalization. The purpose of this study was to explore the relationships between chronic disease complexity, health system integration (admission to accountable care organization [ACO] hospital), availability of care management interventions (membership in managed care organization [MCO]), and 90-day post-discharge healthcare utilization. We used de-identified Medicaid claims data from two counties in western New York. The study population was 114,295 individuals who met inclusion criteria, of whom 7,179 had index hospital admissions in the first 9 months of 2013. Individuals were assigned to three disease complexity segments based on presence of 12 prevalent conditions. The 30-day inpatient (IP) readmission rates ranged from 6% in the non-chronic segment to 12% in the chronic disease complexity segment and 21% in the organ system failure complexity segment. Rehospitalization rates (both inpatient and emergency department [ED]) were lower for patients in MCOs and ACOs than for those in fee-for-service care. Complexity of chronic disease, initial hospitalization in a facility that was part of an ACO, MCO membership, female gender, and longer length of stay were associated with a significantly longer time to readmission in the first 90 days, that is, fewer readmissions. Our results add to evidence that high-value post-discharge utilization (fewer IP or ED rehospitalizations and early outpatient follow-up) require population-based transitional care strategies that improve continuity between settings and take into account the illness complexity of the Medicaid population. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)