Validity of International Classification of Diseases (ICD)-10 Diagnosis Codes for Identification of Acute Heart Failure Hospitalization and Heart Failure with Reduced Versus Preserved Ejection Fraction in a National Medicare Sample.

BACKGROUND: Heart failure (HF) is a leading cause of hospitalization in older adults. Medicare data have been used to assess HF outcomes. However, the validity of ICD-10 diagnosis codes (used since 2015) to identify acute HF hospitalization or distinguish reduced (heart failure with reduced ejection fraction) versus preserved ejection fraction (HFpEF) is unknown in Medicare data. METHODS: Using Medicare data (2015-2017), we randomly sampled 200 HF hospitalizations with ICD-10 diagnosis codes for HF in the first/second claim position in a 1:1:2 ratio for systolic HF (I50.2), diastolic HF (I50.3), and other HF (I50.X). The primary gold standards included recorded HF diagnosis by a treating physician for HF hospitalization, ejection fraction (EF)≤50 for heart failure with reduced ejection fraction, and EF>50 for HFpEF. If the quantitative EF was not present, then qualitative descriptions of EF were used for heart failure with reduced ejection fraction/HFpEF gold standards. Multiple secondary gold standards were also tested. Gold standard data were extracted from medical records using standardized forms and adjudicated by cardiology fellows/staff. We calculated positive predictive values with 95% CIs. RESULTS: The 200-chart validation sample included 50 systolic, 50 diastolic, 47 combined dysfunction, and 53 unspecified HF patients. The positive predictive values of acute HF hospitalization was 98% [95% CI, 95-100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58-74] for first/second-position diagnosis. Quantitative EF was available for ≥80% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82-98] for EFs≤50% and 72% [95% CI, 60-85] for EFs≤40%. The positive predictive value was 92% [95% CI, 85-100] for HFpEF for EFs>50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF. CONCLUSIONS: ICD-10 principal diagnosis identified acute HF hospitalization with a high positive predictive value. Systolic and diastolic ICD-10 diagnoses reliably identified heart failure with reduced ejection fraction and HFpEF when EF 50% was used as the cutoff.

Verification of a Portable Motion Tracking System for Remote Management of Physical Rehabilitation of the Knee.

Rehabilitation following knee injury or surgery is critical for recovery of function and independence. However, patient non-adherence remains a significant barrier to success. Remote rehabilitation using mobile health (mHealth) technologies have potential for improving adherence to and execution of home exercise. We developed a remote rehabilitation management system combining two wireless inertial measurement units (IMUs) with an interactive mobile application and a web-based clinician portal (interACTION). However, in order to translate interACTION into the clinical setting, it was first necessary to verify the efficacy of measuring knee motion during rehabilitation exercises for physical therapy and determine if visual feedback significantly improves the participant's ability to perform the exercises correctly. Therefore, the aim of this study was to verify the accuracy of the IMU-based knee angle measurement system during three common physical therapy exercises, quantify the effect of visual feedback on exercise performance, and understand the qualitative experience of the user interface through survey data. A convenience sample of ten healthy control participants were recruited for an IRB-approved protocol. Using the interACTION application in a controlled laboratory environment, participants performed ten repetitions of three knee rehabilitation exercises: heel slides, short arc quadriceps contractions, and sit-to-stand. The heel slide exercise was completed without feedback from the mobile application, then all exercises were performed with visual feedback. Exercises were recorded simultaneously by the IMU motion tracking sensors and a video-based motion tracking system. Validation showed moderate to good agreement between the two systems for all exercises and accuracy was within three degrees. Based on custom usability survey results, interACTION was well received. Overall, this study demonstrated the potential of interACTION to measure range of motion during rehabilitation exercises for physical therapy and visual feedback significantly improved the participant's ability to perform the exercises correctly.