Spirometry is necessary to diagnose chronic obstructive pulmonary disease (COPD), yet a large proportion of patients are diagnosed and treated without having received testing. This study explored whether the effects of interventions using the electronic health record (EHR) to target patients diagnosed with COPD without confirmatory spirometry impacted the incidence rates of spirometry referrals and completions. This retrospective before and after study assessed the impact of provider-facing clinical decision support that identified patients who had a diagnosis of COPD but had not received spirometry.
View Article and Find Full Text PDFIntroduction: There is mounting interest in the use of risk prediction models to guide lung cancer screening. Electronic health records (EHRs) could facilitate such an approach, but smoking exposure documentation is notoriously inaccurate. While the negative impact of inaccurate EHR data on screening practices reliant on dichotomized age and smoking exposure-based criteria has been demonstrated, less is known regarding its impact on the performance of model-based screening.
View Article and Find Full Text PDFBackground: Perinatal exposure to hepatitis C virus (HCV) is a major public health issue, and poor testing rates leave many children with infection unidentified. We sought to use the electronic health record (EHR) to promote guideline-directed HCV testing among infants born to mothers with HCV infection in an urban, safety-net hospital system.
Methods: Our study population was identified using our EHR database, Epic.
Background: Hepatitis C virus (HCV) infection is a major public health burden, affecting over 4 million people. The Centers for Disease Control and Prevention and the US Preventive Services Task Force guidelines recommend screening everyone born between 1945 and 1965, but screening rates remain low.
Objective: To determine whether bulk ordering and electronic messaging to patients improves guideline-based HCV screening rates.
J Am Med Inform Assoc
November 2017
All default electronic health record and drug reference database vendor drug-dose alerting recommendations (single dose, daily dose, dose frequency, and dose duration) were silently turned on in inpatient, outpatient, and emergency department areas for pediatric-only and nonpediatric-only populations. Drug-dose alerts were evaluated during a 3-month period. Drug-dose alerts fired on 12% of orders (104 098/834 911).
View Article and Find Full Text PDFBackground: Code status (CS) of a patient (part of their end-of-life wishes) can be critical information in healthcare delivery, which can change over time, especially at transitions of care. Although electronic health record (EHR) tools exist for medication reconciliation across transitions of care, much less attention is given to CS, and standard EHR tools have not been implemented for CS reconciliation (CSR). Lack of CSR creates significant potential patient safety and quality of life issues.
View Article and Find Full Text PDFAim: Taking a detailed family history is an inexpensive way for healthcare providers to screen patients for increased risk of various chronic conditions. Documentation of family history, however, has been shown to be incomplete in the majority of patient charts. The current study examines when family history is collected within the context of the development and diagnosis of chronic conditions in paediatrics, using hypertension and overweight/obesity as examples.
View Article and Find Full Text PDFAlthough it is widely recognized that diagnosis plays a central role in clinical medicine, in recent years the primacy of diagnosis has come under attack from several sources. 1. "Billable terms" are replacing traditional medical diagnoses.
View Article and Find Full Text PDFBackground: Electronic medical records (EMRs) have the potential to facilitate the design of large cluster-randomized trials (CRTs).
Objective: To describe the design of a CRT of clinical decision support to improve diabetes care and outcomes.
Methods: In the Diabetes Improvement Group-Intervention Trial (DIG-IT), we identified and balanced preassignment characteristics of 12,675 diabetic patients cared for by 147 physicians in 24 practices of 2 systems using the same vendor's EMR.