Ensuring Data Accuracy

One of the major challenges is ensuring that accurate and complete data are collected. There are opportunities to audit information to enhance the reliability of the measurements.

  • Using Incidence to Help Determine Case Ascertainment:

    One way to determine whether you have been able to collect all the cardiac arrest cases that have occurred in your geography is to calculate incidence figures. Cardiac arrest incidence is a measure of the risk of developing cardiac arrest within a specified period of time, generally a year. It is commonly expressed as a proportion or a rate per 100,000 population.

    Incidence for SCA has been considered to fluctuate slightly around 55 cases per 100,000 population.

    • For example, the incidence reported in the Resuscitation Consortium agencies in 2008 was 52 per 100,000. (Nichol G, Calloway TE, Hedges J: Regional variation in out-of-hospital cardiac arrest incidence and outcome. JAMA 2008 Sep 24;300(12):1423-31.)
    • The most reasonable way to measure incidence in this case is to use EMS-treated out of hospital cardiac arrests.
    • If your EMS system serves a population of 100,000, and you have record of 55 cardiac arrests that year, your incidence is 55/100,000.
    • If in that same system of 100,000 population, only 25 arrests are recorded, the incidence of 25/100,000 would alert you that you are likely missing many cases in your reporting.
  • Case Ascertainment:

    All cases must be accounted for when tracking SCA survival rates. Patients who may be defibrillated once and awaken quickly are sometimes missed in data collection systems. Often, identifying victims who die early is easier than tracking survivors. However, every effort should be used to ensure that there is an outcome (Alive/Dead at hospital discharge) for each individual in the database. Several resources available on the Internet allow such searches including the Social Security Death Index.

  • Effect of Missing Data

    • If survivors are missed, the calculated survival rate will be falsely low.
    • If there are many cases missing outcomes, an accurate survival rate cannot be calculated.