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Monitoring and Anomaly Characterization

Monitoring and Anomaly Characterization. Protocols. Prioritization at all levels Resources Time people Perceived utility History Level of data Season. “Common” Steps. System runs Identify signal/anomaly Look for underlying data problems (i.e. dupes, data dropout)

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Monitoring and Anomaly Characterization

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  1. Monitoring and Anomaly Characterization

  2. Protocols • Prioritization at all levels • Resources • Time • people • Perceived utility • History • Level of data • Season

  3. “Common” Steps • System runs • Identify signal/anomaly • Look for underlying data problems (i.e. dupes, data dropout) • Primary – signal details • Secondary – further analyses • Tertiary – provider information

  4. Necessary information • Indicator variables • Syndrome variable (chief complaint/diagnosis code) • Demographic variables (age, gender) • Time variable (hour, date) • Geographic variable (zip code, hospital) • Analysis variable (ratio, count)

  5. Anomaly Indicators • Magnitude • In a demographic population of significance or public health importance • Clustering in any of the indicator variables that deviates from natural history (baseline, seasonality) or is interesting based on domain knowledge

  6. Beyond System Capacity • Clinical information • Confirmed laboratory tests • Physician notes/consultation • Epidemiological information • Exposure history • Event • Food • Travel

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