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Data usage of drgrouper

Mobile app data ussage: use of health apps in health management

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Data usage of drgrouper

  1. 1. Use of mobile apps in public health and management – The first data for drGrouper app usage Dr. Mihai Negrea, Dr. Iulia Grancea
  2. 2. Why? • Today we know that internet and technology get in every aspect of our life personal and professional • Why not make our jobs easier with technology? • If we can offer good products and make our health better why shouldn`t be doing it? • Romanian health system data is closed for outside researchers, developers, entrepreneurs, only a hand few of people have acces less than 10 • We plan to give public acces to our data
  3. 3. What`s DRG • Diagnosis Related Groups • It`s a financing system used in Europe, USA and some countries of Asia(China, Korea, UAE, etc) Australia • It`s based on the fact that similar pathology are using the similar resources so they need to paied the same.
  4. 4. How • We created at Reea the app available on mobile devices – iOS and Android systems • It can be only used by registration • It`s free to download to smartphones or tablet • We ask information about user – name, email, profession, specialization or ward, hospital, city, county • When use the grouper we can associate the patient cases – diagnosis, procedures, sex, age, weight, length of stay and discharge and the result of the grouper
  5. 5. What do we have at the moment • ~310 active users • 2600+ grouped cases • 1436 Medical cases • 648 Surgical Cases • 22 Others Cases • 1.0997 – Case Mix in app
  6. 6. So what I did? • I took the 3 of the most frequent medical groups in DRG report for 2015 • And associated the group with my database • So I know what is the primary diagnosis, what are the most frequent associate pathologies • what`s the average age, length of stay • What`s type of the outcome – discharge, transfer, death
  7. 7. F3032 – Heart failure and shock without catastrophic complications • 32 cases - 22 males – 10 females • 65.62% i50.0 – congestive hearth failure, 25% i11.0 – hypertension cardiopathy with congestive failure , 9.38% i50.1 – Left Ventricle Failure • Associated diagnosis i10 – Blood Hypertension 40.62% • N18.x and n17.x– renal disfunction 21.87% • Average length of stay 5.78 Days min 4 days max 12 days • All cases discharged
  8. 8. I3081 – non surgical perturbation of the spine • 5 cases all males • Main diagnosis 3 of m54.4 Lumbago with sciatics and 2 m47.xx spondylosis • Every case has associated at least a form of gastic affection k76.x, k30.x, k21.x,k62.x • 4 out of 5 have at least 1 urinal affection and hypercolestrolemia • Average length of stay 5.2 day , minim 2 max 9 • All cases discharged
  9. 9. E3061 • 8 cases – all males • Main diagnosis j44.x – a form of Chronic Obstructive Lung Disease • Associated diagnosis – 6 acute respiratory insufficiency • 4 have a form of pneumonia • 4 have heart or circulatory conditions also • 2 have diabeties
  10. 10. Discussions • Of course these data are not relevant to take medical actions at the moment we have 4.2 million patients admitted every year • Of course they could be better collected but we`re still developing the app and the data management system • But it`s the first in the Romania`s history when these datas are publicly available – anyone can ask for them we`ll give them we present them • There are many software proivders that have these datas but they don`t make them available for research and also don`t public statistics • Also the Romanian School of Public Health and National Insurance Service has them but they are not publicly available for research
  11. 11. Conclusion • We can say we have some data but we need many more • We can say we can model some patterns of public health indicators • There are some pathological patterns that we can analyse further • We consider we have an alpha model, proof of concept that we can develop further
  12. 12. Futher development • Better data collection • Better data organizing and data mining system • Attract more active users I estimate that in Romania are around 10 000 MDs – whole market
  13. 13. Thank You

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Mobile app data ussage: use of health apps in health management

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