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1.
J Gen Intern Med ; 38(4): 1054-1058, 2023 03.
Article in English | MEDLINE | ID: mdl-36414802

ABSTRACT

Reliable systems that track the continuation, progression, or resolution of a patient's symptoms over time are essential for reliable diagnosis and ensuring that patients harboring more worrisome diagnoses are safely followed up. Given their first-contact role and increasing stresses on busy primary care clinicians and practices, new processes that make these tasks easier rather than creating more work for busy clinicians are especially needed.Some symptoms are sufficiently worrisome that they demand an urgent diagnosis and treatment while others result in a differential that can be more safely explored over time, or less differentiated and worrisome that they are best managed with the "test of time" to see if they resolve, worsen, or evolve into symptoms that are more worrisome. Regardless, it is essential that clinicians are able to reliably track symptoms over time, yet this capacity is rarely available or explicit. Working with systems engineers, we are developing prototypes for such systems and are working on their implementation and evaluation. In this commentary, we describe approaches to this essential, but underappreciated, problem in primary care.


Subject(s)
Primary Health Care , Symptom Assessment , Humans
2.
J Patient Saf ; 18(8): e1142-e1149, 2022 12 01.
Article in English | MEDLINE | ID: mdl-35617623

ABSTRACT

OBJECTIVES: Opioid misuse has resulted in significant morbidity and mortality in the United States, and safer opioid use represents an important challenge in the primary care setting. This article describes a research collaborative of health service researchers, systems engineers, and clinicians seeking to improve processes for safer chronic opioid therapy management in an academic primary care center. We present implementation results and lessons learned along with an intervention toolkit that others may consider using within their organization. METHODS: Using iterative improvement lifecycles and systems engineering principles, we developed a risk-based workflow model for patients on chronic opioids. Two key safe opioid use process metrics-percent of patients with recent opioid treatment agreements and urine drug tests-were identified, and processes to improve these measures were designed, tested, and implemented. Focus groups were conducted after the conclusion of implementation, with barriers and lessons learned identified via thematic analysis. RESULTS: Initial surveys revealed a lack of knowledge regarding resources available to patients and prescribers in the primary care clinic. In addition, 18 clinicians (69%) reported largely "inheriting" (rather than initiating) their chronic opioid therapy patients. We tracked 68 patients over a 4-year period. Although process measures improved, full adherence was not achieved for the entire population. Barriers included team structure, the evolving opioid environment, and surveillance challenges, along with disruptions resulting from the 2019 novel coronavirus. CONCLUSIONS: Safe primary care opioid prescribing requires ongoing monitoring and management in a complex environment. The application of a risk-based approach is possible but requires adaptability and redundancies to be reliable.


Subject(s)
COVID-19 , Chronic Pain , Opioid-Related Disorders , Humans , United States , Analgesics, Opioid/adverse effects , Chronic Pain/drug therapy , Chronic Pain/chemically induced , Practice Patterns, Physicians' , Opioid-Related Disorders/epidemiology , Opioid-Related Disorders/prevention & control , Opioid-Related Disorders/drug therapy
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