Low-touch, team-based care for co-morbidity management in cancer patients: the ONE TEAM randomized controlled trial.

BACKGROUND: As treatments for cancer have improved, more people are surviving cancer. However, compared to people without a history of cancer, cancer survivors are more likely to die of cardiovascular disease (CVD). Increased risk for CVD-related mortality among cancer survivors is partially due to lack of medication adherence and problems that exist in care coordination between cancer specialists, primary care physicians, and cardiologists. METHODS/DESIGN: The Onco-primary care networking to support TEAM-based care (ONE TEAM) study is an 18-month cluster-randomized controlled trial with clustering at the primary care clinic level. ONE TEAM compares the provision of the iGuide intervention to patients and primary care providers versus an education-only control. For phase 1, at the patient level, the intervention includes video vignettes and a live webinar; provider-level interventions include electronic health records-based communication and case-based webinars. Participants will be enrolled from across North Carolina one of their first visits with a cancer specialist (e.g., surgeon, radiation or medical oncologist). We use a sequential multiple assignment randomized trial (SMART) design. Outcomes (measured at the patient level) will include Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of management of three CVD comorbidities using laboratory testing (glycated hemoglobin [A1c], lipid profile) and blood pressure measurements; (2) medication adherence assessed pharmacy refill data using Proportion of Days Covered (PDC); and (3) patient-provider communication (Patient-Centered Communication in Cancer Care, PCC-Ca-36). Primary care clinics in the intervention arm will be considered non-responders if 90% or more of their participating patients do not meet the modified HEDIS quality metrics at the 6-month measurement, assessed once the first enrollee from each practice reaches the 12-month mark. Non-responders will be re-randomized to either continue to receive the iGuide 1 intervention, or to receive the iGuide 2 intervention, which includes tailored videos for participants and specialist consults with primary care providers. DISCUSSION: As the population of cancer survivors grows, ONE TEAM will contribute to closing the CVD outcomes gap among cancer survivors by optimizing and integrating cancer care and primary care teams. ONE TEAM is designed so that it will be possible for others to emulate and implement at scale. TRIAL REGISTRATION: This study (NCT04258813) was registered in clinicaltrals.gov on February 6, 2020.

Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge.

PURPOSE: Timely outpatient follow-up has been promoted as a key strategy to reduce hospital readmissions, though one-half of patients readmitted within 30 days of hospital discharge do not have follow-up before the readmission. Guidance is needed to identify the optimal timing of hospital follow-up for patients with conditions of varying complexity. METHODS: Using North Carolina Medicaid claims data for hospital-discharged patients from April 2012 through March 2013, we constructed variables indicating whether patients received follow-up visits within successive intervals and whether these patients were readmitted within 30 days. We constructed 7 clinical risk strata based on 3M Clinical Risk Groups (CRGs) and determined expected readmission rates within each CRG. We applied survival modeling to identify groups that appear to benefit from outpatient follow-up within 3, 7, 14, 21, and 30 days after discharge. RESULTS: The final study sample included 44,473 Medicaid recipients with 65,085 qualifying discharges. The benefit of early follow-up varied according to baseline readmission risk. For example, follow-up within 14 days after discharge was associated with 1.5%-point reduction in readmissions in the lowest risk strata (P <.001) and a 19.1%-point reduction in the highest risk strata (P <.001). Follow-up within 7 days was associated with meaningful reductions in readmission risk for patients with multiple chronic conditions and a greater than 20% baseline risk of readmission, a group that represented 24% of discharged patients. CONCLUSIONS: Most patients do not meaningfully benefit from early outpatient follow-up. Transitional care resources would be best allocated toward ensuring that highest risk patients receive follow-up within 7 days.

Adherence to cardiovascular disease risk factor medications among patients with cancer: a systematic review.

PURPOSE: The most common cause of mortality for many cancer survivors is cardiovascular disease (CVD). This requires a shift in thinking where control of CVD risk factor-related comorbidity is paramount. Our objective was to provide an understanding of adherence to medications for the management of CVD risk factor-related comorbidities among cancer survivors. METHODS: We systematically searched for articles indexed in MEDLINE (via PubMed), Embase, Cochrane (Wiley), PsycINFO, and Scopus (via Elsevier) for articles published from inception to October 31, 2019, and updated the search on June 7, 2021. English language, original research that assessed medication adherence to common CVD risk factor-related comorbidities among cancer survivors was included. We assessed risk of bias using the Mixed Methods Appraisal Tool. RESULTS: Of the 21 studies included, 57% focused on multiple cancer types. Seventy-one percent used pharmacy-based adherence measures. Two were prospective. Adherence was variable across cancer types and CVD risk factor-related comorbidities. Among the studies that examined changes in comorbid medication adherence, most noted a decline in adherence following cancer diagnosis and throughout cancer treatment. There was a focus on breast cancer populations. CONCLUSIONS: CVD risk factor-related medication adherence is low among cancer survivors and declines over time. Given the risk for CVD-mortality among cancer survivors, testing of interventions aimed at improving adherence to non-cancer medications is critically needed. IMPLICATIONS FOR CANCER SURVIVORS: For many cancer survivors, regularly taking medications to manage CVD risk is important for longevity. Engaging with primary care throughout the cancer care trajectory may be important to support cardiovascular health.

Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record.

PURPOSE: Outcomes for patients with metastatic breast cancer (MBC) are continually improving as more effective treatments become available. Granular data sets of this unique population are lacking, and the standard method for data collection relies largely on chart review. Therefore, using electronic health records (EHR) collected at a tertiary hospital system, we developed and evaluated a computational phenotype designed to identify all patients with MBC, and we compared the effectiveness of this algorithm against the gold standard, clinical chart review. METHODS: A cohort of patients with breast cancer were identified according to International Classification of Diseases codes, the institutional tumor registry, and SNOMED codes. Chart review was performed to determine whether distant metastases had occurred. We developed a computational phenotype, on the basis of SNOMED concept IDs, which was applied to the EHR to identify patients with MBC. Contingency tables were used to aggregate and compare results. RESULTS: A total of 1,741 patients with breast cancer were identified using data from International Classification of Diseases codes, the tumor registry, and/or SNOMED concept identifiers. Chart review of all patients classified each patient as having MBC (n = 416; 23.9%) versus not (n = 1,325; 75.9%). The final computational phenotype successfully classified 1,646 patients (95% accuracy; 82% sensitivity; 99% specificity). CONCLUSION: Hospital systems with robust EHRs and reliable mapping to SNOMED have the ability to use standard codes to derive computational phenotypes. These algorithms perform reasonably well and have the added ability to be run at disparate health care facilities. Better tooling to navigate the polyhierarchical structure of SNOMED ontology could yield better-performing computational phenotypes.

Evaluating the Effectiveness of Community and Hospital Medical Record Integration on Management of Behavioral Health in the Emergency Department.

This study evaluated the correlation of an emergency department embedded care coordinator with access to community and medical records in decreasing hospital and emergency department use in patients with behavioral health issues. This retrospective cohort study presents a 6-month pre-post analysis on patients seen by the care coordinator (n=524). Looking at all-cause healthcare utilization, care coordination was associated with a significant median decrease of one emergency department visit per patient (p < 0.001) and a decrease of 9.5 h in emergency department length of stay per average visit per patient (p<0.001). There was no significant effect on the number of hospitalizations or hospital length of stay. This intervention demonstrated a correlation with reducing emergency department use in patients with behavioral health issues, but no correlation with reducing hospital utilization. This under-researched approach of integrating medical records at point-of-care could serve as a model for better emergency department management of behavioral health patients.

Mobile health devices: will patients actually use them?

Although mobile health (mHealth) devices offer a unique opportunity to capture patient health data remotely, it is unclear whether patients will consistently use multiple devices simultaneously and/or if chronic disease affects adherence. Three healthy and three chronically ill participants were recruited to provide data on 11 health indicators via four devices and a diet app. The healthy participants averaged overall weekly use of 76%, compared to 16% for those with chronic illnesses. Device adherence declined across all participants during the study. Patients with chronic illnesses, with arguably the most to benefit from advanced (or increased) monitoring, may be less likely to adopt and use these devices compared to healthy individuals. Results suggest device fatigue may be a significant problem. Use of mobile technologies may have the potential to transform care delivery across populations and within individuals over time. However, devices may need to be tailored to meet the specific patient needs.

A rat model reproducing key pathological responses of alcoholic chronic pancreatitis.

Although alcohol abuse is the major cause of chronic pancreatitis, the pathogenesis of alcoholic chronic pancreatitis (ACP) remains obscure. A critical obstacle to understanding the mechanism of ACP is lack of animal models. Our objective was to develop one such model. Rats were pair-fed for 8 wk ethanol or control Lieber-DeCarli liquid diet. For the last 2 wk, they received cyclosporin A (CsA; 20 mg/kg once daily) or vehicle. After 1 wk on CsA, one episode of acute pancreatitis was induced by four 20 microg/kg injections of cerulein (Cer); controls received saline. Pancreas was analyzed 1 wk after the acute pancreatitis. CsA or Cer treatments alone did not result in pancreatic injury in either control (C)- or ethanol (E)-fed rats. We found, however, that alcohol dramatically aggravated pathological effect of the combined CsA+Cer treatment on pancreas, resulting in massive loss of acinar cells, persistent inflammatory infiltration, and fibrosis. Macrophages were prominent in the inflammatory infiltrate. Compared with control-fed C+CsA+Cer rats, their ethanol-fed E+CsA+Cer counterparts showed marked increases in pancreatic NF-kappaB activation and cytokine/chemokine mRNA expression, collagen and fibronectin, the expression and activities of matrix metalloproteinase-2 and -9, and activation of pancreatic stellate cells. Thus we have developed a model of alcohol-mediated postacute pancreatitis that reproduces three key responses of human ACP: loss of parenchyma, sustained inflammation, and fibrosis. The results indicate that alcohol impairs recovery from acute pancreatitis, suggesting a mechanism by which alcohol sensitizes pancreas to chronic injury.