Care studies in open care Tino Sanandaji Erik

Care studies in open care Tino Sanandaji Erik Lakomaa

Introduction Data Reform Empirical strategy Results Evaluation of community-based projects Conclusions § Cases of open care heterogenous in type and focus, ranging from evasive entreprenureship in communities to profit IT-aps. Some are directly in health care provision and others in broader health or in providing health infrastructure § Community based traditional care § Often requires common ideology or subculture § Evasive entrepreneurship, evade regulation. High legitimacy when providing care § Rare where formal health function well, often response to failure § Hard to scale up without subculture or ideology to overcome collective action § Data aggregation and collective intelligence § Symptoms, side-effect, genetic data, rating doctors, use social media to track epidemics § Facilitated by IT, allows for sufficient number of cases across countries to share symptoms, side effect and other data even for rare health problems § Advantageous even when formal care functions well § High potential to scale up and be influenced by best practice 2

Introduction Data Reform Range of case studies Empirical strategy Results Conclusions § Health provision itself therapeutic § Mental care, programs for disabled, addiction care § Peer-to-peer, provision part of health, participating itself valuable aside outcome § Advantageous even when formal care functions well § Fairly high potential to scale up § Health infrastructure § Open Health-IT solutions, health-technology, prosthetics § Avoid or evade high price and monopoly rent of IP § IT programs that link or support existing home-care or support voluntary efforts § Increasing number of initiatives in recent years § Fairly high potential to scale up 3

Introduction Data Reform Examples of open care Empirical strategy Results Conclusions § Geel community (Family-based mental care) § First Person (self-managed associations mental health) § Care. Zapp (support for home care providers) § Health. Unlocked (peer-to-peer support network) § Patients. Like. Me (social patient communication platform) § Praxis. Platform (connects patients and providers) § Asperger. Forum (chat, support and information) § Link. Age (elderly peer-to-peer socialization) § Rare. Connect (platform for rare disease communication) § Geneix (data aggregator on drug interaction and side affect) 4

Introduction Data Policy lessons Reform Empirical strategy Results Conclusions § Community care has low cost of experimentation whereas public health system risk averse. Many failures, but low cost of failure, value of a few successful outweighs § Traditional hospital care is rarely community based if formal care functions well. Often requires subculture or ideology. § Community care particularly advantageous in mental health and addiction care § More examples if health is defined broadly § Open care common in health infrastructure, such as open source software § Many sucessful examples if open care in IT-based information aggregation (symptoms, side affects, peer-to-peer support, genetic data, rating doctors), high potential to scale up or spead best case. § Public sector can facilitate community initiativets with guidelines § Use IT to support and connect existing community care § Interesting and innovative applications of collective intelligence in using social media such as twitter in tracking epidemics. 5

Introduction Data Reform Qualtrics survey outline Empirical strategy Results Conclusions 6