Module 6, IT in pharmacy practice Flashcards

1
Q

What does LASA stand for?

A
  • look-alike sound-alike automated screening application
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What are some health initiatives that are directly relevant to pharmacy practice?

A
  • clinical decision support rules in computer systems
    • prediction using artificial intelligence (=dynamic modelling, machine learning, adaptive algorithms), accessing single or mulitple sources of data to guide management decisions
    • PainCheck- pain detection through facial recognitions
      • dementia, or crying babies
    • ScalaMed- blockchain prescription exchange system drawing on clinical and genomics data to alert the patient to interactions, warnings or need for dose adjustment
    • stock management & ordering using sales data to predict:
      • seasonal changes
      • wastage due to expired stock
    • clinical prompts and guidance for medication selection, dosing & adjustments
    • sentimental analysis to adapt machine responses to match a persons emotion
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

How does IT prevent clincial errors?

A
  • automated alerts detecting
    • duplicate medication classes
    • drug interactions
    • multiple routes of administration
    • out-of-range doses
    • allergies to medicines
    • potential for confusion between medicine names or routes
  • caution realert fatigue (densensitisation)
    • excessive alerts are generally false-positive
    • however, ignoring alerts can be a significant patient saftey hazard
    • recommendations
      • tiers of alerts
      • restrict alerts to most significant issues
      • apply human factors in design of alerts (appearance, sound)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

We need IT systems that:

A
  • reduce our ‘faith’ in the machine
    • human logic & cognitive processes still required
  • prevent silent errors e.g. wrong selection from lists
  • support rather than replace communication
  • help manage interruptions in work flow
  • recognise non-linear work flows e.g. dispensary technician handing over to pharmacist mis-dispensing
  • offer more efficient incident reporting (in real time)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Describe how health consumers engage with IT?

A
  • health apps
  • medavisor
  • healthengine: Dr appointments
  • Freestyle libre blood glucose scanning to replace finger prick tests
    • detects falls
    • link to medical data
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Applications of health technologies…

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is a health professionals role with IT?

A
  • keep abreast of technological developments
    • beyond awareness
    • beyond simply adopting and responding to new technologies when released
  • pharmacists should be able to operate:
    • as engaged health professionals
    • within an evolving technology universe
    • within the framework of government policy
    • with a vision for connectivity and paperless healthc care
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is the pharmacists role with IT?

A
  • to maintain the pharmacys digital presence (website, blog to assist in recognition by Google, e commerce, social media)–> professionalism and regular updates are key
  • manage ‘Dr Google’ searches/ downloads by consumers
  • interpret consumer-monitored health data e.g. BP readings and understanf the:
    • validity & reliability of data
    • limitations of apps (lack or artificial intelligence to interpret trends and out of range readings)
  • interpret medication adherance data (MedicineWise, TerryWhite Chemmart)
  • potentially receive al-generated predictions and warnings about health risks e.g. risk of fall, heart attack
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are some challenges & risks for IT?

A
  • managaing multiple data sources; self generated by health consumer, populated in MHR from various health professionals, predicted by Al, population/ societal averages vs healthy data ranges- which data are trustworthy?
  • data security (hacking)
  • uncertainty in decision making
  • incomplete data
  • outdated data
How well did you know this?
1
Not at all
2
3
4
5
Perfectly