Colonoscopy Outreach for Rural Communities (CORC): A study protocol of a pragmatic randomized controlled trial of a patient navigation program to improve colonoscopy completion for colorectal cancer screening

BACKGROUND

Colonoscopy is one of the primary methods of screening for colorectal cancer (CRC), a leading cause of cancer mortality in the United States. However, up to half of patients referred to colonoscopy fail to complete the procedure, and rates of adherence are lower in rural areas.

OBJECTIVES

Colonoscopy Outreach for Rural Communities (CORC) is a randomized controlled trial to test the effectiveness of a centralized patient navigation program provided remotely by a community-based organization to six geographically distant primary care organizations serving rural patients, to improve colonoscopy completion for CRC.

METHODS

CORC is a type 1 hybrid implementation-effectiveness trial. Participants aged 45-76 from six primary care organizations serving rural populations in the northwestern United States are randomized 1:1 to patient navigation or standard of care control. The patient navigation is delivered remotely by a trained lay-person from a community-based organization. The primary effectiveness outcome is completion of colonoscopy within one year of referral to colonoscopy. Secondary outcomes are colonoscopy completion within 6 and 9 months, time to completion, adequacy of patient bowel preparation, and achievement of cecal intubation. Analyses will be stratified by primary care organization.

DISCUSSION

Trial results will add to our understanding about the effectiveness of patient navigation programs to improve colonoscopy for CRC in rural communities. The protocol includes pragmatic adaptations to meet the needs of rural communities and findings may inform approaches for future studies and programs.

TRIAL REGISTRATION

National Clinical Trial Identifier: NCT05453630.

TRIAL REGISTRATION

ClinicalTrials.gov. Identifier: NCT05453630. Registered July 6, 2022.

Identifying patients with opioid use disorder using International Classification of Diseases (ICD) codes: Challenges and opportunities

BACKGROUND AND AIMS

International Classification of Diseases (ICD) diagnosis codes are often used in research to identify patients with opioid use disorder (OUD), but their accuracy for this purpose is not fully evaluated. This study describes application of ICD-10 diagnosis codes for opioid use, dependence and abuse from an electronic health record (EHR) data extraction using data from the clinics' OUD patient registries and clinician/staff EHR entries.

DESIGN

Cross-sectional observational study.

SETTING

Four rural primary care clinics in Washington and Idaho, USA.

PARTICIPANTS

307 patients.

MEASUREMENTS

This study used three data sources from each clinic: (1) a limited dataset extracted from the EHR, (2) a clinic-based registry of patients with OUD and (3) the clinician/staff interface of the EHR (e.g. progress notes, problem list). Data source one included records with six commonly applied ICD-10 codes for opioid use, dependence and abuse: F11.10 (opioid abuse, uncomplicated), F11.20 (opioid dependence, uncomplicated), F11.21 (opioid dependence, in remission), F11.23 (opioid dependence with withdrawal), F11.90 (opioid use, unspecified, uncomplicated) and F11.99 (opioid use, unspecified with unspecified opioid-induced disorder). Care coordinators used data sources two and three to categorize each patient identified in data source one: (1) confirmed OUD diagnosis, (2) may have OUD but no confirmed OUD diagnosis, (3) chronic pain with no evidence of OUD and (4) no evidence for OUD or chronic pain.

FINDINGS

F11.10, F11.21 and F11.99 were applied most frequently to patients who had clinical diagnoses of OUD (64%, 89% and 79%, respectively). F11.20, F11.23 and F11.90 were applied to patients who had a diagnostic mix of OUD and chronic pain without OUD. The four clinics applied codes inconsistently.

CONCLUSIONS

Lack of uniform application of ICD diagnosis codes make it challenging to use diagnosis code data from EHR to identify a research population of persons with opioid use disorder.

Stakeholder perspectives on a telemedicine referral and coordination model to expand medication treatment for opioid use disorder in rural primary care clinics

INTRODUCTION

Opioid overdose deaths are increasing rapidly in the United States. Medications for opioid use disorder (MOUD) are effective and can be delivered in primary care, but uptake has been limited in rural communities. Referral to and coordination with an external telemedicine (TM) vendor by rural primary care clinics for MOUD (TM-MOUD) may increase MOUD access for rural patients, but we know little about perspectives on this model among key stakeholders. As part of a TM-MOUD feasibility study, we explored TM-MOUD acceptability and feasibility among personnel and patients from seven rural primary care clinics and a TM-MOUD vendor.

METHODS

We conducted virtual interviews or focus groups with clinic administrators (n = 7 interviews), clinic primary care and behavioral health providers (8 groups, n = 30), other clinic staff (9 groups, n = 37), patients receiving MOUD (n = 16 interviews), TM-MOUD vendor staff (n = 4 interviews), and vendor-affiliated behavioral health and prescribing providers (n = 17 interviews). We asked about experiences with and acceptability of MOUD (primarily buprenorphine) and telemedicine (TM) and a TM-MOUD referral and coordination model. We conducted content analysis to identify themes and participants quantitatively rated acceptability of TM-MOUD elements on a 4-item scale.

RESULTS

Perceived benefits of vendor-based TM-MOUD included reduced logistical barriers, more privacy and less stigma, and access to services not available locally (e.g., counseling, pain management). Barriers included lack of internet or poor connectivity in patients' homes, limited communication and trust between TM-MOUD and clinic providers, and questions about the value to the clinic of TM-MOUD referral to external vendor. Acceptability ratings for TM-MOUD were generally high; they were lowest among frontline staff.

CONCLUSIONS

Rural primary care clinic personnel, TM-MOUD vendor personnel, and patients generally perceived referral from primary care to a TM-MOUD vendor to hold potential for increasing access to MOUD in rural communities. Increasing TM-MOUD uptake requires buy-in and understanding among staff of the TM-MOUD workflow, TM services offered, requirements for patients, advantages over clinic-based or TM services from clinic providers, and identification of appropriate patients. Poverty, along with patient hesitation to initiate treatment, creates substantial barriers to MOUD treatment generally; insufficient internet availability creates a substantial barrier to TM-MOUD.

Care coordination between rural primary care and telemedicine to expand medication treatment for opioid use disorder: Results from a single-arm, multisite feasibility study

PURPOSE

The use of telemedicine (TM) has accelerated in recent years, yet research on the implementation and effectiveness of TM-delivered medication treatment for opioid use disorder (MOUD) has been limited. This study investigated the feasibility of implementing a care coordination model involving MOUD delivered via an external TM provider for the purpose of expanding access to MOUD for patients in rural settings.

METHODS

The study tested a care coordination model in 6 rural primary care sites by establishing referral and coordination between the clinic and a TM company for MOUD. The intervention spanned approximately 6 months from July/August 2020 to January 2021, coinciding with the peak of the COVID-19 pandemic. Each clinic tracked patients with OUD in a registry during the intervention period. A pre-/post-intervention design (N = 6) was used to assess the clinic-level outcome as patient-days on MOUD based on patient electronic health records.

FINDINGS

All clinics implemented critical components of the intervention, with an overall TM referral rate of 11.7% among patients in the registry. Five of the 6 sites showed an increase in patient-days on MOUD during the intervention period compared to the 6-month period before the intervention (mean increase per 1,000 patients: 132 days, P = .08, Cohen's d = 0.55). The largest increases occurred in clinics that lacked MOUD capacity or had a greater number of patients initiating MOUD during the intervention period.

CONCLUSIONS

To expand access to MOUD in rural settings, the care coordination model is most effective when implemented in clinics that have negligible or limited MOUD capacity.

Personal health information management among healthy older adults: Varying needs and approaches

OBJECTIVE

With age, older adults experience a greater number of chronic diseases and medical visits, and an increased need to manage their health information. Technological advances in consumer health information technologies (HITs) help patients gather, track, and organize their health information within and outside of clinical settings. However, HITs have not focused on the needs of older adults and their caregivers. The goal of the SOARING (Studying Older Adults and Researching their Information Needs and Goals) Project was to understand older adult personal health information management (PHIM) needs and practices to inform the design of HITs that support older adults.

MATERIALS AND METHODS

Drawing on the Work System Model, we took an ecological approach to investigate PHIM needs and practices of older adults in different residential settings. We conducted in-depth interviews and surveys with adults 60 years of age and older.

RESULTS

We performed on-site in-person interview sessions with 88 generally healthy older adults in various settings including independent housing, retirement communities, assisted living, and homelessness. Our analysis revealed 5 key PHIM activities that older adults engage in: seeking, tracking, organizing, sharing health information, and emergency planning. We identified 3 major themes influencing older adults' practice of PHIM: (1) older adults are most concerned with maintaining health and preventing illness, (2) older adults frequently involve others in PHIM activities, and (3) older adults' approach to PHIM is situational and context-dependent.

DISCUSSION

Older adults' approaches to PHIM are dynamic and sensitive to changes in health, social networks, personal habits, motivations, and goals.

CONCLUSIONS

PHIM tools that meet the needs of older adults should accommodate the dynamic nature of aging and variations in individual, organizational, and social contexts.

Is telemedicine the answer to rural expansion of medication treatment for opioid use disorder? Early experiences in the feasibility study phase of a National Drug Abuse Treatment Clinical Trials Network Trial

Telemedicine (TM) enabled by digital health technologies to provide medical services has been considered a key solution to increasing health care access in rural communities. With the immediate need for remote care due to the COVID-19 pandemic, many health care systems have rapidly incorporated digital technologies to support the delivery of remote care options, including medication treatment for individuals with opioid use disorder (OUD). In responding to the opioid crisis and the COVID-19 pandemic, public health officials and scientific communities strongly support and advocate for greater use of TM-based medication treatment for opioid use disorder (MOUD) to improve access to care and have suggested that broad use of TM during the pandemic should be sustained. Nevertheless, research on the implementation and effectiveness of TM-based MOUD has been limited. To address this knowledge gap, the National Drug Abuse Treatment Clinical Trials Network (CTN) funded (via the NIH HEAL Initiative) a study on Rural Expansion of Medication Treatment for Opioid Use Disorder (Rural MOUD; CTN-0102) to investigate the implementation and effectiveness of adding TM-based MOUD to rural primary care for expanding access to MOUD. In preparation for this large-scale, randomized controlled trial incorporating TM in rural primary care, a feasibility study is being conducted to develop and pilot test implementation procedures. In this commentary, we share some of our experiences, which include several challenges, during the initial two-month period of the feasibility study phase. While these challenges could be due, at least in part, to adjusting to the COVID-19 pandemic and new workflows to accommodate the study, they are notable and could have a substantial impact on the larger, planned pragmatic trial and on TM-based MOUD more broadly. Challenges include low rates of identification of risk for OUD from screening, low rates of referral to TM, digital device and internet access issues, workflow and capacity barriers, and insurance coverage. These challenges also highlight the lack of empirical guidance for best TM practice and quality remote care models. With TM expanding rapidly, understanding implementation and demonstrating what TM approaches are effective are critical for ensuring the best care for persons with OUD.

Examining the Needs of Patient Stakeholders as Research Partners in Health Data Networks for Translational Research

Patient stakeholders are getting increasingly involved in research health data networks, particularly as research partners. However, tools do not exist to help effectively orient, educate, and engage patient stakeholders as they take on these roles. Using a human centered design approach, we conducted a patient stakeholder needs assessment qualitative study to identify key user needs to drive design recommendations for development of an online education and engagement tool for research health data networks. We found three key needs related to multiple role identities, motivations and expectations for participation on research teams, and patient journeys. Design recommendations derived from the needs assessment are discussed that can support future tool design and testing.

A Closer Look at Health Information Seeking by Older Adults and Involved Family and Friends: Design Considerations for Health Information Technologies

Older adults are the largest consumers of healthcare. As part of a broader study of personal health information management (PHIM), we interviewed older adults in King County, Washington, and their involved family and friends (FF), regarding health information (HI) sources they seek and utilize. Analysis of interview transcripts revealed four main themes: 1) older adults and FF consider healthcare providers the foundational source of HI; 2) older adults utilize FF for seeking, sharing, and interpreting HI, while FF serve as surrogate seekers and experience-based experts; 3) online searching is common for older adults and FF, but confidence in assessing the quality of online HI is often lacking; 4) a smorgasbord approach is frequently utilized by older adults and FF for gathering and clarifying HI. Design considerations include: facilitating access to quality provider-vetted HI, incorporating older adults and FF in the design process, and creating shared spaces for communication of HI among older adults, FF, and providers.

Monitoring for change: the role of family and friends in helping older adults manage personal health information

Objective

Although family and friends (FF) often play a significant support role in the health of older adults (OA), we know little about their role in personal health information management (PHIM). To address this gap and inform the design of PHIM tools, we describe the work, needs, and barriers of FF in the context of PHIM for OAs.

Methods

We conducted semi-structured telephone interviews with 52 FF identified by OA as being important in their health and PHIM. We analyzed interview transcripts for themes about FF information work, barriers, and support needs.

Results

FF play a supportive role in OA health maintenance, medical encounters, decision making, and daily activities. Monitoring, the ongoing process of seeking information related to the OA status, emerged as a key activity comprised of 3 phases: detection, interpretation, and action. Barriers to monitoring included OA choices and constraints, FF constraints, and difficulty with technological tools, resources, health information exchange between providers, social network dynamics, and physical distance.

Conclusions

FF frequently monitor for change in OA well-being, seeking up-to-date information to facilitate support of OA PHIM. Health information technology tools designed for FF can support all phases of monitoring by providing: (1) timely and granular levels of access to OA health information as the OA ages; (2) tailored health education for FF that is based on OA clinical data; and (3) networking platforms that integrate delegation, volunteering, and relevant resources, along with tools to facilitate support of OA appointment calendars and medication management. Such tools could reduce the burden of PHIM for OA and their loved ones.