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1.
J Am Board Fam Med ; 33(1): 27-33, 2020.
Article in English | MEDLINE | ID: mdl-31907243

ABSTRACT

BACKGROUND: The literature on results from primary care-based opioid-prescribing protocols is small and results have been mixed. To advance this field, we evaluated whether opioid prescribing changed after a comprehensive protocol was implemented and whether change was associated with the number and type of risk reduction tools adopted. METHODS: Electronic medical record data were obtained for 2607 patients. Demographics, Patient Health Questionnaire-9 scores, body mass index, and utilization levels of protocol elements were measured for 24 months prior and 18 months post implementation of an opioid-prescribing protocol within a federally qualified health center. χ2 and t-tests were computed to estimate change in opioid prescribing, morphine-equivalent dose, comedication prescribing, and number and type of protocol elements utilized. RESULTS: The opioid protocol was associated with an increase in urine drug screens from 18.3% to 26.8% from pre to postimplementation (P < .0001). There was no significant increase in opioid treatment agreements. Tramadol (21.4% to 16.8%, P = .0006) and antidepressant (56.0% to 51.6%, P = .012) prescribing significantly decreased. Total opioid prescriptions and maximum morphine-equivalent doses were similar from pre to postimplementation. Protocol elements were more often used when patients had a higher opioid dose and were receiving benzodiazepines. CONCLUSIONS: Implementing a multi-faceted opioid-prescribing protocol was not associated with change in number or dose of opioid prescriptions but was associated with greater use of urine drug screens, and risk reduction tools were used more often in high-risk patients. Implementation research is needed to identify barriers to maximizing adherence to opioid protocols.


Subject(s)
Analgesics, Opioid/administration & dosage , Chronic Pain/therapy , Opioid-Related Disorders/prevention & control , Pain Management/methods , Practice Patterns, Physicians'/statistics & numerical data , Adult , Chronic Pain/drug therapy , Female , Humans , Male , Middle Aged , Opioid-Related Disorders/urine , Practice Patterns, Physicians'/organization & administration , Primary Health Care/organization & administration , Retrospective Studies , Risk Assessment/methods , Surveys and Questionnaires
2.
Am Fam Physician ; 96(10): 640-646, 2017 Nov 15.
Article in English | MEDLINE | ID: mdl-29431384

ABSTRACT

The definition and classification of cardiomyopathy have evolved considerably in recent years. Cardiomyopathy can be separated into primary (genetic, mixed, or acquired) and secondary categories, which result in varied phenotypes including dilated, hypertrophic, and restrictive patterns. Hypertrophic cardiomyopathy is the most common primary cardiomyopathy and can cause exertional dyspnea, presyncope, atypical chest pain, heart failure, and sudden cardiac death. Dilated cardiomyopathy can be genetic or acquired and typically presents with classic symptoms of heart failure with reduced ejection fraction. Restrictive cardiomyopathy is much less common and often associated with systemic disease. Family physicians should be alert for acquired variants of cardiomyopathy, including peripartum and stress-induced cardiomyopathy, as well as rare variants, such as arrhythmogenic right ventricular dysplasia and left ventricular noncompaction. In addition to history and physical examination, diagnosis of cardiomyopathy includes electrocardiography and echocardiography testing. Treatment may include appropriately staged therapy for heart failure, appropriate activity restriction, evaluation for implantable cardioverter-defibrillator placement, and consideration of heart transplantation in refractory cases. Genetic testing of families is an emerging modality with some potential to augment traditional screening performed by family physicians.


Subject(s)
Cardiomyopathies/diagnosis , Cardiomyopathies/etiology , Cardiomyopathies/therapy , Diagnosis, Differential , Heart/physiopathology , Humans , Risk Factors
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