Improving patient-provider communication about chronic pain: development and feasibility testing of a shared decision-making tool

BACKGROUND: Chronic pain has emerged as a disease in itself, affecting a growing number of people. Effective patient-provider communication is central to good pain management because pain can only be understood from the patient\u27s perspective. We aimed to develop a user-centered tool to improve patient-provider communication about chronic pain and assess its feasibility in real-world settings in preparation for further evaluation and distribution. METHODS: To identify and prioritize patient treatment goals for chronic pain, strategies to improve patient-provider communication about chronic pain, and facilitate implementation of the tool, we conducted nominal group technique meetings and card sorting with patients with chronic pain and experienced providers (n = 12). These findings informed the design of the PainAPP tool. Usability and beta-testing with patients (n = 38) and their providers refined the tool and assessed its feasibility, acceptability, and preliminary impact. RESULTS: Formative work revealed that patients felt neither respected nor trusted by their providers and focused on transforming providers\u27 negative attitudes towards them, whereas providers focused on gathering patient information. PainAPP incorporated areas prioritized by patients and providers: assessing patient treatment goals and preferences, functional abilities and pain, and providing patients tailored education and an overall summary that patients can share with providers. Beta-testing involved 38 patients and their providers. Half of PainAPP users shared their summaries with their providers. Patients rated PainAPP highly in all areas. All users would recommend it to others with chronic pain; nearly all trusted the information and said it helped them think about my treatment goals (94%), understand my chronic pain (82%), make the most of my next doctor\u27s visit (82%), and not want to use opioids (73%). Beta-testing revealed challenges delivering the tool and summary report to patients and providers in a timely manner and obtaining provider feedback. CONCLUSIONS: PainAPP appears feasible for use, but further adaptation and testing is needed to assess its impact on patients and providers. TRIAL REGISTRATION: This study was approved by the University of New England Independent Review Board for the Protection of Human Subjects in Research (012616-019) and was registered with ClinicalTrials.gov (protocol ID: NCT03425266) prior to enrollment. The trial was prospectively registered and was approved on February 7, 2018

Implementation of substance use screening in rural federally-qualified health center clinics identified high rates of unhealthy alcohol and cannabis use among adult primary care patients

Abstract Background Screening for substance use in rural primary care clinics faces unique challenges due to limited resources, high patient volumes, and multiple demands on providers. To explore the potential for electronic health record (EHR)-integrated screening in this context, we conducted an implementation feasibility study with a rural federally-qualified health center (FQHC) in Maine. This was an ancillary study to a NIDA Clinical Trials Network study of screening in urban primary care clinics (CTN-0062). Methods Researchers worked with stakeholders from three FQHC clinics to define and implement their optimal screening approach. Clinics used the Tobacco, Alcohol, Prescription Medication, and Other Substance (TAPS) Tool, completed on tablet computers in the waiting room, and results were immediately recorded in the EHR. Adult patients presenting for annual preventive care visits, but not those with other visit types, were eligible for screening. Data were analyzed for the first 12 months following implementation at each clinic to assess screening rates and prevalence of reported unhealthy substance use, and documentation of counseling using an EHR-integrated clinical decision support tool, for patients screening positive for moderate-high risk alcohol or drug use. Results Screening was completed by 3749 patients, representing 93.4% of those with screening-eligible annual preventive care visits, and 18.5% of adult patients presenting for any type of primary care visit. Screening was self-administered in 92.9% of cases. The prevalence of moderate-high risk substance use detected on screening was 14.6% for tobacco, 30.4% for alcohol, 10.8% for cannabis, 0.3% for illicit drugs, and 0.6% for non-medical use of prescription drugs. Brief substance use counseling was documented for 17.4% of patients with any moderate-high risk alcohol or drug use. Conclusions Self-administered EHR-integrated screening was feasible to implement, and detected substantial alcohol, cannabis, and tobacco use in rural FQHC clinics. Counseling was documented for a minority of patients with moderate-high risk use, possibly indicating a need for better support of primary care providers in addressing substance use. There is potential to broaden the reach of screening by offering it at routine medical visits rather than restricting to annual preventive care visits, within these and other rural primary care clinics

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, Cohens 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

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\u27s 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