To minimize the potential of missing data, patients who missed their appointment were contacted a new follow up appointment was set up. This is a self- completed questionnaire evaluating the disease activity parameters, functional ability as well as quality of life. Prior to baseline examination in the clinic and every follow-up appointment, each patient completed a patient reported outcome measures (PROMs) questionnaire. Patients with past history of cancer or hepatitis, HIV or any other contraindication to DMARDs therapy. Patients taking oral steroids for non-arthritic/ other medical causes.ģ. Patients with history of RA, urogenital, intestinal or other forms of infection.Ģ. Results: PsA patients who had higher incidence of comorbid condition and were at high risk of hospitalization were men, with older age at disease onset, high BMI (p 6 weeks, or remittent pain involving any finger and/or toe for 3 months. Internal and external validation were carried out. A weighted index that was developed in a cohort of 1707 PsA patients. Outcomes of interest included functional ability, quality of life, medications induced complications, hospitalization/death. Methods: This was a retrospective multicenter cohort analysis of PsA patients in a rheumatology clinical registry, assessing the effect of different comorbidities measured at patients’ visits over 10-years period. 2.develop and validate a prospectively applicable comorbidity index for classifying PsA patients according to their comorbid conditions. identify comorbidities with greatest impact on PsA patients’ health status. Compared with the original score, it has similar performance in predicting readmission in a population of United States commercially insured individuals.Objective: 1. We propose an ICD-10-CM version of the combined comorbidity score that includes codes identified by ICD-10-CA and GEMs. The algorithm based on ICD-10-CA codes had the most similar discrimination for readmission to the ICD-9-CM version (c, 0.646 95% CI, 0.639-0.653), but combining all identified ICD-10-CM codes had the highest c-statistic (c, 0.651 95% CI, 0.644-0.657). We used logistic regression models to predict 30-day hospital readmission for the original score in the ICD-9-CM cohort and for each ICD-10-CM algorithm in the ICD-10-CM cohort.ĭistributions of each version of the score were similar. The ICD-9-CM cohort comprised patients who had a hospitalization between Januand March 1, 2015. The ICD-10-CM cohort comprised patients who had a hospitalization between Januand March 1, 2016. We used claims data from the Clinfomatics Data Mart to identify 2 cohorts. The objective of this study is to examine different coding algorithms for the ICD-10-CM combined comorbidity score and compare their performance to the original ICD-9-CM score.įour ICD-10-CM coding algorithms were defined: 2 using General Equivalence Mappings (GEMs), one based on ICD-10-CA (Canadian modification) codes for Charlson and Elixhauser measures, and one including codes from all 3 algorithms. In October 2015, the United States adopted the 10th revision (ICD-10-CM).
The combined comorbidity score, which merges the Charlson and Elixhauser comorbidity indices, uses the ninth revision of the International Classification of Diseases, Clinical Modification (ICD-9-CM).
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