Postoperative electrocardiography changes: To worry or not to worry.

Abnormal postoperative electrocardiograms are not uncommon, oftentimes leading to further cardiac workup especially when the findings are new and not easily explainable. A forty-year-old woman, with a history of left breast cancer status post bilateral mastectomies and reconstructions, presented for robot-assisted low-anterior resection secondary to rectal cancer. Postoperative electrocardiogram showed poor R wave progression, biphasic T waves in V2-4, and possible anterior wall ischemia. Her electrocardiogram from 6 years ago was normal. No recent electrocardiogram was available for comparison. Initially, the abnormal postoperative electrocardiogram appeared worrisome. However, the patient was completely asymptomatic, and all vital signs were normal. Cardiac point-of-care ultrasound showed normal parasternal long and short axis views. The biphasic T waves in V2-4 were suggestive of Wellens syndrome, but the accompanying poor R wave progression was not consistent with the diagnostic criteria. The anesthesiologist then remembered the patient's history of the presence of a left breast implant and suspected it might have caused the changes on the electrocardiogram. A literature search did find one publication that shows approximately 45% of patients with breast implants present with electrocardiogram changes, including poor R wave progression and negative T waves. Therefore, no further cardiac workup was ordered for our patient. She was discharged home 3 days later. Breast implants and electrocardiogram changes are a lesser-known topic. Obtaining a pre-operative electrocardiogram should be considered in patients with previous breast implants, to serve as a baseline for comparison if the patient were to need another electrocardiogram in the future.

Screening for Individuals at Risk for Hereditary Breast and Ovarian Cancer: A Statewide Initiative, Georgia, 2012-2020.

Georgia implemented a statewide family history screening program for hereditary breast and ovarian cancer. From November 2012 through December 2020, 29 090 individuals were screened, 16 679 of whom (57.3%) self-identified as a racial/ethnic minority. Of the 4% (1172/29 090) of individuals who screened as high risk, more than half underwent genetic consultation (793/1172; 67.7%) and testing (416/589; 70.6%). Compared with White women, Black and Hispanic women had higher uptake rates of genetic consultation. Public health settings serving racial minorities are well suited to address disparities in genetic service access. (Am J Public Health. 2022;112(9):1249-1252. https://doi.org/10.2105/AJPH.2022.306932).

'It's like you don't have a roadmap really': using an antiracism framework to analyze patients' encounters in the cancer system.

Background: Cancer patients can experience healthcare system-related challenges during the course of their treatment. Yet, little is known about how these challenges might affect the quality and completion of cancer treatment for all patients, and particularly for patients of color. Accountability for Cancer Care through Undoing Racism and Equity is a multi-component, community-based participatory research intervention to reduce Black-White cancer care disparities. This formative work aimed to understand patients' cancer center experiences, explore racial differences in experiences, and inform systems-level interventions.Methods: Twenty-seven breast and lung cancer patients at two cancer centers participated in focus groups, grouped by race and cancer type. Participants were asked about what they found empowering and disempowering regarding their cancer care experiences. The community-guided analysis used a racial equity approach to identify racial differences in care experiences.Results: For Black and White patients, fear, uncertainty, and incomplete knowledge were disempowering; trust in providers and a sense of control were empowering. Although participants denied differential treatment due to race, analysis revealed implicit Black-White differences in care.Conclusions: Most of the challenges participants faced were related to lack of transparency, such that improvements in communication, particularly two-way communication could greatly improve patients' interaction with the system. Pathways for accountability can also be built into a system that allows patients to find solutions for their problems with the system itself. Participants' insights suggest the need for patient-centered, systems-level interventions to improve care experiences and reduce disparities.

Characterizing phenotypes and outcomes of drug-associated liver injury using electronic medical record data.

PURPOSE: To evaluate the incidence, phenotypes, and outcomes of drug-associated liver injury identified in electronic medical record (EMR) data using standardized criteria for drug-induced liver injury (DILI). METHODS: This retrospective cohort study used EMR data from a large integrated healthcare system. Study inclusion required 18 years of age or older, ≥1 prescription fill for any of 14 medications associated with hepatotoxicity between 1 January 2003 and 30 June 2009, and ≥12 months of membership prior to the drug exposure. Patients with underlying non-drug causes of liver injury were excluded to minimize capture of liver injury events unrelated to drugs. Drug-associated liver injuries were identified by liver chemistry elevations temporally associated with drug use based on standardized criteria for DILI. Cases were classified by clinical pattern and severity. Outcomes of liver transplant and all-cause and liver-related death were examined. RESULTS: A total of 1 053 979 drug exposures were identified in 601 125 patients. We identified 265 drug-associated liver injuries (32.8 per 100 000 persons) occurring in 250 patients. Isoniazid exhibited the highest incidence rate of 606 per 100 000 persons. Of the 265 cases, 41% were mild; 12% exhibited moderate drug-associated liver injury (with concomitant ALT ≥ 5× ULN and bilirubin ≥2× ULN); and 17% exhibited coagulopathy, ascites, encephalopathy, or other organ failure. Last, seven cases (3%) were associated with death, and there were no liver transplants. CONCLUSIONS: Study results align with earlier prospective studies, supporting the value of standardized methodology to identify drug-associated liver injury in the EMR. These methods can potentially enhance safety and clinical outcomes.

The impact of the iPLEDGE program on isotretinoin fetal exposure in an integrated health care system.

BACKGROUND: Preventing fetal exposure to isotretinoin is widely acknowledged as an important safety issue. The iPLEDGE program is the latest in a series of Food and Drug Administration-mandated risk management programs designed to prevent pregnancies in female patients of childbearing potential (FCBP) taking isotretinoin. OBJECTIVE: We sought to evaluate the effect of iPLEDGE relative to the prior risk management program (system to manage Accutane-related teratogenicity [SMART]) on the risk of isotretinoin fetal exposure in FCBP in a managed care setting. METHODS: All FCBP at Kaiser Permanente Southern and Northern California who filled at least one prescription for isotretinoin during a 4-year period (March 1, 2004, to February 29, 2008) were included in this retrospective cohort study (n = 8344). Chart review was performed to confirm fetal exposures and outcomes. A Cox proportional hazards model was used to estimate the hazard ratio and 95% confidence intervals. RESULTS: There were a total of 29 fetal exposures and 9912 isotretinoin treatment courses. After iPLEDGE was implemented, the unadjusted rate of fetal exposure decreased from 3.11 to 2.67 per 1000 treatment courses (P = .69). The hazard ratio = 0.76 (95% confidence interval 0.36-1.61) for fetal exposures to isotretinoin during treatment courses filled after iPLEDGE implementation compared with SMART. LIMITATIONS: Limitations include limited generalizability of results, small sample size (n = 29 total documented fetal exposures), and potential uncontrolled confounders. CONCLUSION: Evaluating the impact of iPLEDGE on isotretinoin fetal exposures is important in understanding the full risks and benefits of isotretinoin treatment. We found no evidence that iPLEDGE significantly decreased the risk of fetal exposure in FCBP compared to the SMART program.

Primary nonadherence to statin medications in a managed care organization.

BACKGROUND: Primary nonadherence to a medication occurs when a drug is prescribed but the patient fails to pick the prescription up from the pharmacy. Managed care organizations that provide integrated care using electronic medical records (EMR) are an ideal setting to study primary nonadherence.  OBJECTIVE: To identify patient and provider characteristics that are significantly associated with primary nonadherence to statin medications compared with a population of patients who picked up their first statin order.   METHODS: This was a retrospective cohort study of patients with a new statin prescription. Patients with a new order for a statin prescription between December 1, 2009, and February 28, 2010, were eligible. A statin order was considered new if the patient had no statin prescriptions in the previous 12 months. Study participants were 24 years and older with 12 months of continuous membership prior to the statin order. Patients were defined as primary nonadherent if they did not pick up their new prescription within 90 days. Descriptive and multivariate (conditional logistic regression) analyses of patients who did and did not pick up their new statin prescriptions were performed using demographic and socioeconomic information, health care utilization, health conditions, medical benefits, and prescriber characteristics.   RESULTS: A total of 19,826 patients with a new statin order that met all of the inclusion and exclusion criteria was identified. Of these, 3,049 patients (15.4%) did not pick up their statin prescriptions within 90 days of the order date. Primary nonadherent patients tended to be younger (55 vs. 57 years, P less than 0.001) and healthier, with fewer comorbid conditions (Charlson Comorbidity Index ≥ 1, 42.2% vs. 52.3%, P less than 0.001), lower rates of hospitalizations (7.2% vs. 12.0%, P less than 0.001), fewer concurrent prescriptions (3 vs. 4, P less than 0.001) and fewer clinic (4 vs. 5, P less than 0.001) and emergency department visits (18.2% vs. 24.6%, P less than 0.001) in the prior year than adherent patients. Although the multivariate model agreed well with the observed data, the characteristics included had a poor ability to predict primary nonadherence (c-statistic = 0.603).   CONCLUSION: Primary nonadherence has been recognized as a significant problem for many years, and electronic health records are allowing researchers to investigate the extent of the problem. In this study, almost 1 in 6 patients (15.4%) failed to pick up their new statin order within 90 days. However, clinical and demographic information available in electronic health care data may not be useful in predicting primary nonadherence. New methods and interventions need to be developed to improve primary adherence.  

Primary nonadherence to medications in an integrated healthcare setting.

OBJECTIVES: To measure primary nonadherence (PNA) rates for 10 therapeutic drug groups and identify factors associated with PNA to chronic and acute medications. STUDY DESIGN: Retrospective cohort study. METHODS: New prescriptions written in an integrated healthcare system for study drugs were identified between December 1, 2009, and February 28, 2010. PNA was defined as the failure to fill a prescription within 14 days of when it was written. PNA rates were calculated by drug group and descriptive statistics were performed. Multivariable logistic regression was used to identify significant patient, provider, and prescription characteristics associated with PNA. Results were stratified by acute versus chronic treatment. RESULTS: A total of 569,095 new prescriptions were written during the 3-month period. Across all drug groups, the PNA rate was 9.8%. PNA rates for individual drug groups varied and were highest for osteoporosis medications (22.4%) and antihyperlipidemics (22.3%). Patients who filled at least 1 prescription in the prior year (odds ratio [OR], 95% confidence interval [CI] for acute = 0.06 [0.06-0.07], for chronic = 0.11 [0.10-0.12]) or had a prescription for a symptomatic disease (OR = 0.51 [0.48-0.53]) were more likely to fill their prescription. Patients were more likely to be primary nonadherent if they were black (OR acute = 1.30 [1.25-1.36], chronic = 1.26 [1.18-1.33]) or treatment-naive to therapy (OR acute = 2.52 [2.36-2.7], chronic=1.07 [1.03-1.12]). CONCLUSIONS: Overall PNA was 9.8% but individual PNA rates varied by therapeutic drug group. Factors of PNA were mostly consistent across drug groups, but some depended on whether the treatment was acute or chronic.

Economic burden associated with patients diagnosed with hepatitis C.

BACKGROUND: New therapies for Hepatitis C virus (HCV) are under development that will augment pegylated interferon-alpha plus ribavirin to improve patient outcomes. Data documenting the incremental economic and health burden of patients with HCV relative to those who are not infected with HCV will be required to evaluate the comparative effectiveness of these new therapies. OBJECTIVE: The objective of this study was to estimate the incremental impact of HCV infection on health care costs and risk of adverse health events. METHODS: Paid claims data for commercially insured patients in the United States were used to identify 2 matched cohorts of 8861 patients with and without HCV infection. Propensity score matching was used to adjust for patient demographics, diagnostic mix, prior use, and drug profile. Patients with prior cirrhosis, liver cancer, or liver transplantation were excluded. Differences in the first postindex year associated with the diagnosis of an HCV infection were estimated for adverse event risk (logistic regression), costs (ordinary least square regression), and utilization counts (generalized linear models), controlling for patient demographics, prior use, comorbidity profile, and prescription drug profile. RESULTS: The costs of treating patients infected with HCV and a matched sample not infected with HCV were $37,390 and $13,575, respectively. The incremental cost of HCV infection was estimated at +$23,406, primarily because of higher costs for ambulatory care (+$6531), hospital services (+$1827), and prescription drugs (+$6935). The presence of HCV was associated with a significantly higher risk of hospitalization (odds ratio [OR] = 2.5) and number of hospital admissions (+186%); depression (OR = 2.2); cirrhosis (OR = 65.8); hepatic cancer (OR = 28.1), and liver transplantation (OR = 46.1; P < 0.0001 for all estimates). CONCLUSIONS: A diagnosis of HCV infection was correlated significantly with increased adverse event risk and increased health care costs. New alternative treatments are needed that are more efficacious and less burdensome for the patient. Limitations of this study are that only 1 year was used to screen for preexisting conditions and events and that paid claims data do not capture indirect HCV infection costs such as time lost from work.