Leveraging structured and unstructured electronic health record data to detect reasons for suboptimal statin therapy use in patients with atherosclerotic cardiovascular disease

Objective: To determine whether natural language processing (NLP) of unstructured medical text can improve identification of ASCVD patients not using high-intensity statin therapy (HIST) due to statin-associated side effects (SASEs) and other reasons.Methods: Reviewers annotated reasons for not prescribing HIST in notes of 1152 randomly selected patients from across the VA healthcare system treated for ASCVD but not receiving HIST. Developers used reviewer annotations to train the Canary NLP tool to detect and extract notes containing one or more of these reasons. Negative predictive value (NPV), sensitivity, specificity and Area Under the Curve (AUC) were used to assess accuracy at detecting documents containing reasons when using structured data, NLP-extracted unstructured data, or both data sources combined.Results: At least one documented reason for not prescribing HIST occurred in 47% of notes. The most frequent reasons were SASEs (41%) and general intolerance (20%). When identifying notes containing any documented reason for not using HIST, adding NLP-extracted, unstructured data significantly (p\u3c0.05) increased sensitivity (0.69 (95% confidence interval [CI] 0.60-0.76) to 0.89 (95% CI 0.81-0.93)), NPV (0.90 (95% CI 0.87 to 0.93) to 0.96 (95% CI 0.93-0.98)), and AUC (0.84 (95% confidence interval [CI] 0.81-0.88) to 0.91 (95% CI 0.90-0.93)) compared to structured data alone.Conclusions: NLP extraction of data from unstructured text can improve identification of reasons for patients not being on HIST over structured data alone. The additional information provided through NLP of unstructured free text should help in tailoring and implementing system-level interventions to improve HIST use in patients with ASCVD

Understanding prescribing practices and patient experiences with renin angiotensin system inhibitors use in chronic kidney disease: A qualitative study

Introduction: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) improve outcomes but are underutilized in patients with chronic kidney disease (CKD). Little is known about reasons for discontinuation and lack of reinitiating these medications. We aimed to explore clinicians\u27 and patients\u27 experiences and perceptions of ACEI/ARB use in CKD.Methods: A multi-profession sample of health care clinicians and patients with documented ACEI/ARB-associated side effects in the past 6 months. Participants were recruited from 2 Veterans Affairs healthcare systems in Texas and Tennessee. A total of 15 clinicians and 10 patients completed interviews. We used inductive and deductive qualitative data analysis approaches to identify themes related to clinician and patient experiences with ACEI/ARB. Thematic analysis focused on prescribing decisions and practices, clinical guidelines, and perception of side effects. Data were analyzed as they amassed, and recruitment was stopped at the point of thematic saturation.Results: Clinicians prescribe ACEI/ARB for blood pressure control and kidney protection and underscored the importance of these medications in patients with diabetes. While clinicians described providing comprehensive patient education about ACEI/ARB in CKD, patient interviews revealed significant knowledge gaps about CKD and ACEI/ARB use. Many patients were unaware of their CKD status, and some did not know why they were prescribed ACEI/ARB. Clinicians\u27 drug management strategies varied widely, as did their understanding of prescribing guidelines. They identified structural and patient-level barriers to prescribing and many endorsed the development of a decision support tool to facilitate ACEI/ARB prescribing and management.Discussion/conclusion: Our qualitative study of clinicians and providers identified key target areas for improvement to increase ACEI/ARB utilization in patients with CKD with the goal to improve long-term outcomes in high-risk patients. These findings will also inform the development of a decision support tool to assist with prescribing ACEI/ARBs for patients with CKD

The use of structured data elements to identify ASCVD patients with statin-associated side effects: Insights from the Department of Veterans Affairs

Background: Accurate identification of patients with statin-associated side effects (SASEs) is critical for health care systems to institute strategies to improve guideline-concordant statin use.Objective: The objective of this study was to determine whether adverse drug reaction (ADR) entry by clinicians in the electronic medical record can accurately identify SASEs.Methods: We identified 1,248,214 atherosclerotic cardiovascular disease (ASCVD) patients seeking care in the Department of Veterans Affairs. Using an ADR data repository, we identified SASEs in 15 major symptom categories. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed using a chart review of 256 ASCVD patients with identified SASEs, who were not on high-intensity statin therapy.Results: We identified 171,189 patients (13.71%) with documented SASEs over a 15-year period (9.9%, 2.7%, and 1.1% to 1, 2, or \u3e2 statins, respectively). Statin use, high-intensity statin use, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol levels were 72%, 28.1%, 99 mg/dL, and 129 mg/dL among those with vs 81%, 31.1%, 84 mg/dL, and 111 mg/dL among those without SASEs. Progressively lower statin and high-intensity statin use, and higher low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol levels were noted among those with SASEs to 1, 2, or \u3e2 statins. Two-thirds of SASEs were related to muscle symptoms. Sensitivity, specificity, PPV, NPV compared with manual chart review were 63.4%, 100%, 100%, and 85.3%, respectively.Conclusion: A strategy of using ADR entry in the electronic medical record is feasible to identify SASEs with modest sensitivity and NPV but high specificity and PPV. Health care systems can use this strategy to identify ASCVD patients with SASEs and operationalize efforts to improve guideline-concordant lipid-lowering therapy use in such patients. The sensitivity of this approach can be further enhanced by the use of unstructured text data

Association of patient, provider and facility related characteristics with statin associated side effects and statin use: Insight from the Veteran\u27s Affairs healthcare system

Background: Statin associated side effects (SASE) are a leading cause of statin discontinuation.Objective: We evaluated patient, provider, and facility characteristics associated with SASEs and whether these characteristics impact statin utilization.Methods: Patients with atherosclerotic cardiovascular disease (ASCVD) receiving care across the Veterans Affairs healthcare system from October 1, 2014 to September 30, 2015 were included. Multivariable logistic regression analyses were performed to determine (a) factors associated with SASE and (b) factors associated with statin use in those with SASE.Results: Our cohort included 1,225,576 patients with ASCVD. Of these, 171,189 (13.7%) had at least 1 reported SASE since year 2000. The most significant odds for SASEs were observed with female sex (odds ratio [OR] 1.40, 95% confidence interval [CI] 1.36, 1.45), White race (OR 1.43, 95% CI 1.41, 1.45), hypertension (OR 1.37, 95% CI 1.33, 1.41) and ischemic heart disease (IHD: OR 1.45, 95% CI 1.43, 1.47). Lower odds were noted with care at a teaching facility (OR 0.89, 95% CI 0.88, 0.90). Factors most associated with being on a statin among patients with SASE included having diabetes (OR 1.18, 95% CI 1.15, 1.20), IHD (OR 1.39, 95% CI 1.35, 1.43) and a higher number of cardiology visits (OR 1.08, 95% CI 1.07, 1.09), while female sex was associated with lower odds (OR 0.65, 95% CI 0.61, 0.69)Conclusion: There are significant disparities in statin use by sex, ASCVD type, and comorbidities among secondary prevention patients with SASE, which represent areas for improvement in optimizing statin utilization

Facility-level variation in reported statin-associated side effects among patients with atherosclerotic cardiovascular disease-perspective from the veterans affair healthcare system

Purpose: Statin-associated side effects (SASEs) can limit statin adherence and present a potential barrier to optimal statin utilization. How standardized reporting of SASEs varies across medical facilities has not been well characterized.Methods: We assessed facility-level variation in SASE reporting among patients with atherosclerotic cardiovascular disease receiving care across the Veterans Affairs (VA) healthcare system from October 1, 2014, to September 30, 2015. The facility rates for SASE reporting were expressed as cases per 1000 patients with ASCVD. Facility-level variation was determined using hierarchical regression analysis to calculate median rate ratios (MRR [95% confidence interval]) by first using an unadjusted model and then adjusting for patient, provider, and facility characteristics.Results: Of the 1,248,158 patients with ASCVD included in our study across 130 facilities, 13.7% had at least one SASE reported. Individuals with a history of SASE were less likely to be on a statin at follow-up compared with those without SASE (72.0% vs 80.8%, p \u3c 0.01). The median (interquartile range) facility rate of SASE reported was 140.5 (109.4-167.7) cases per 1000 patients with ASCVD. Significant facility-level variation in the rate of SASE reported was observed: MRR 1.38 (1.33-1.44) in the unadjusted model and MRR 1.56 (1.47-1.65) in the adjusted model.Conclusion: Significant facility-level variation in SASE reporting was found within the VA healthcare system suggesting room for improvement in standardized documentation of SASEs among medical facilities. This has the potential to lead to improvement in statin utilization

Documented adverse drug reactions and discontinuation of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers in chronic kidney disease

Introduction: Angiotensin-converting enzyme inhibitors (ACEis) and angiotensin receptor blockers (ARBs) are frequently discontinued in patients with chronic kidney disease (CKD). Documented adverse drug reactions (ADRs) in medical records may provide insight into the reasons for treatment discontinuation.Methods: In this retrospective cohort of US veterans from 2005 to 2019, we identified individuals with CKD and a current prescription for an ACEi or ARB (current user group) or a discontinued prescription within the preceding 5 years (discontinued group). Documented ADRs in structured datasets associated with an ACEi or ARB were categorized into 17 pre-specified groups. Logistic regression assessed associations of documented ADRs with treatment discontinuation.Results: There were 882,441 (73.0%) individuals in the current user group and 326,794 (27.0%) in the discontinued group. There were 26,434 documented ADRs, with at least one documented ADR in 7,520 (0.9%) current users and 9,569 (2.9%) of the discontinued group. ADR presence was associated with treatment discontinuation, aOR 4.16 (95% CI: 4.03, 4.29). The most common documented ADRs were cough (37.3%), angioedema (14.2%), and allergic reaction (10.4%). ADRs related to angioedema (aOR 3.81, 95% CI: 3.47, 4.17), hyperkalemia (aOR 2.03, 95% CI: 1.84, 2.24), peripheral edema (aOR 1.53, 95% CI: 1.33, 1.77), or acute kidney injury (aOR 1.32, 95% CI: 1.15, 1.51) were associated with treatment discontinuation.Conclusion: ADRs leading to drug discontinuation were infrequently documented. ADR types were differentially associated with treatment discontinuation. An understanding of which ADRs lead to treatment discontinuation provides an opportunity to address them at a healthcare system level