EP3553786A1

Patient risk assessment based on data from multiple sources in a healthcare facility

Abstract

Apparatus for assessing medical risks of a patient includes an analytics engine and equipment that provides data to the analytics engine. The equipment includes a patient support apparatus such as a patient bed, a nurse call computer, a physiological monitor, a patient lift, a locating computer of a locating system, and an incontinence detection pad. The analytics engine analyzes the data from the equipment to determine a sepsis risk score, a falls risk score, and a pressure injury score. The apparatus further include displays that are communicatively coupled to the analytics engine and that display the sepsis, falls, and pressure injury risk scores. The displays include a status board display located at a master nurse station, an in-room display provided by a room station of a nurse call system, an electronic medical records (EMR) display of an EMR computer, and a mobile device display of a mobile device of a caregiver assigned to the patient.

EP3553786A1, drawing sheet 1
Sheet 1 of 16

Term

12.5 yearsto projected expiry

Projected expiry 9 April 2039, counted from filing; an application has no term until it is granted.

  1. Priority and filed
  2. Published
  3. Today
  4. Projected expiry

15 claims: 11 independent, 4 dependent

  1. 1
    A system for use in a healthcare facility, the system comprising an analytics engine, a plurality of equipment providing data to the analytics engine, the data pertaining to a patient in the healthcare facility, the plurality of equipment including at least one of the following:a patient support apparatus, a nurse call computer, a physiological monitor, a patient lift, a locating computer of a locating system, or an incontinence detection pad, wherein the analytics engine analyzes the data from the plurality of equipment to determine in substantially real time at least one of the following: a first score relating to a risk of the patient developing sepsis, a second score relating to a risk of the patient falling, and a third score relating to a risk of the patient developing a pressure injury, and a computer coupled to the analytics engine and coordinating a caregiver rounding interval at which at least one caregiver assigned to the patient is required to check in on the patient, wherein the computer automatically decreases the caregiver rounding interval in response to the at least one of the first, second, or third scores increasing from a first value to a second value and wherein the computer automatically increases the caregiver rounding interval in response to the at least one of the first, second, or third scores decreasing from the second value to the first value.
  2. 4
    The system of any preceding claim, wherein each of the first, second, and third scores is normalized by the analytics engine so as to have a minimum value and a maximum value that is common to each of the other first, second, and third scores.
  3. 6
    The system of any preceding claim, wherein the analytics engine communicates the at least two first, second, and third scores to at least one piece of equipment of the plurality of equipment.
  4. 8
    The system of any preceding claim, wherein data from the patient support apparatus includes at least one patient vital sign sensed by at least one vital sign sensor integrated into the patient support apparatus, and/or wherein data from the patient support apparatus further includes patient weight, and/or wherein data from the patient support apparatus includes a position of the patient on the patient support apparatus, and/or wherein data from the patient support apparatus further includes data indicative of an amount of motion by the patient while supported on the patient support apparatus, and/or wherein data from the physiological monitor includes one or more of the following:heart rate data, electrocardiograph (EKG) data, respiration rate data, patient temperature data, pulse oximetry data, and blood pressure data.
  5. 9
    The system of any preceding claim, wherein the first score is at or near a maximum value if the following criteria exist:i) the patient's temperature is greater than about 38.3° Celsius (C) (about 101° Fahrenheit (F)) or less than about 35.6° C (about 96° F.), ii) the patient's heart rate is greater than 90 beats per minute;and iii) the patient's respiration rate is greater than 20 respirations per minute.
  6. 10
    The system of any preceding claim, wherein the analytics engine initiates a message to a mobile device of the at least one caregiver assigned to the patient if the first, second, or third score increases from a previous value, or reaches a threshold value.
  7. 11
    The system of any preceding claim, wherein the analytics engine also receives additional data from an international pressure ulcer prevalence (IPUP) survey for the patient and analyzes the additional data in connection with determining at least one of the first, second, and third scores, and/or wherein the analytics engine also receives additional data relating to at least one wound of the patient and analyzes the additional data in connection with determining at least one of the first, second, and third scores, and/or wherein the analytics engine also receives additional data relating to at least one of the following:fluid input and output, cardiac output, comorbidities, and bloodwork, and wherein the analytics engine analyzes the additional data in connection with determining at least one of the first, second, and third scores.
  8. 12
    The system of any preceding claim, wherein the physiological monitor comprises at least one of the following:a wireless patch sensor attached to the patient, an ambulatory cardiac monitor, an EKG, a respiration rate monitor, a blood pressure monitor, a pulse oximeter, and a thermometer.
  9. 13
    The system of any preceding claim, wherein the analytics engine is configured to receive patient demographics data of the patient including at least one of age, race, and weight; wherein the analytics engine is configured to receive comorbidity data of the patient including data indicating that the patient has at least one of the following medical conditions:acquired immunodeficiency syndrome (AIDS), anemia, chronic congestive heart failure, asthma, cancer, chronic obstructive pulmonary disease (COPD), coronary artery disease, cystic fibrosis, dementia, emphysema, alcohol or drug abuse, stroke, pulmonary emboli, a history of sepsis, type 1 diabetes, morbid obesity, neuromuscular disease, prior intubation, scoliosis, smoker, delirium, asplenic, bone marrow transplant, cirrhosis, dialysis, diverticulosis, heart valve disorders, inflammatory bowel disease, joint replacement, leukopenia, malignancy, neoplasm, organ transplant, peripheral vascular disease, renal disease, pressure injury, recent abortion, recent childbirth, seizures, sickle cell anemia, or terminal illness;wherein the analytics engine is configured to receive physiological data measured by a physiological monitor having at least one sensor coupled to, or in communication with, the patient, the physiological data being dynamic and changing over time while the patient is being monitored by the physiological monitor;and wherein the analytics engine is configured to calculate a risk score of the patient in substantially real time based on the patient demographics data, the comorbidity data, and the physiological data.
  10. 14
    The system of any preceding claim, wherein the analytics engine is configured to:receive dynamic clinical variables and vital signs information of the patient, use the vital signs information to develop prior vital signs patterns and current vital signs patterns, compare the prior vital signs patterns with the current vital signs patterns, receive one or more of the following: static variables of the patient, subjective complaints of the patient, prior healthcare utilization patterns of the patient, or social determinants of health data of the patient, and use the dynamic clinical variables, the vital signs information, the results of the comparison of the prior vital signs patterns with the current vital signs patterns, and the one or more of the static variables, the subjective complaints, the healthcare utilization patterns, or the social determinants of health data in an algorithm to detect or predict that the patient has sepsis or is likely to develop sepsis.
  11. 15
    The system of any preceding claim, wherein a risk determination is made or one or more of the first, second, or third scores is calculated based on one or more of the data elements listed in Table 11.