Computational Time Series Analysis of Patient Referrals to a Primary Percutaneous Coronary Intervention Service

Aleeha Iftikhar, RR Bond, V. E. McGilligan, Stephen James Leslie, Anne McShane, Charles Knoery, Khaled Rjoob, Aaron Peace

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Abstract

This article retrospectively analyses a primary percutaneous coronary intervention dataset comprising patient referrals that were accepted for percutaneous coronary intervention and those who were turned down between January 2015 and December 2018 at Altnagelvin Hospital (United Kingdom). Time series analysis of these referrals was undertaken for analysing the referral rates per year, month, day and per hour. The overall referrals have 70 per cent (n = 1466, p < 0.001) males. Of total referrals, 65 per cent (p < 0.001) of referrals were ‘out of hours’. Seasonality decomposition shows a peak in referrals on average every 3 months (standard deviation = 0.83). No significant correlation (R = 0.03, p = 0.86; R = −0.11, p = 0.62) was found between the referral numbers and turndown rate. Being female increased the probability of being out of hour in all the groups. The 30-day mortality was higher in the turndown group. The time series of all the referrals depict variation over the months or days which is not the same each year. The average age of the patients in the turndown group is higher. The number of referrals does not impact on the turndown rate and clinical decision making. Most patients are being referred out of hours, especially females. This analysis leads to the emphasis on the importance of working 24/7 CathLab service.

Original languageEnglish
Number of pages15
JournalHealth Informatics Journal
Early online date24 Jan 2020
DOIs
Publication statusE-pub ahead of print - 24 Jan 2020

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Keywords

  • PPCI
  • time series analysis
  • health data analysis
  • pathway analysis
  • heart attacks
  • cathlab
  • CathLab
  • primary percutaneous coronary intervention
  • ST-segment elevation myocardial infarction
  • patient referrals

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