CHIA E Flashcards
3 perspectives or frames of reference via which information systems can be viewed
technological, informational, and social
The informational frame
Informational frames can be described as cognitive models concerning the assumptions, expectations and knowledge individuals use to understand and manage information.
Ontology, data archicture, management frameworks, qualtiy management frameworks
The technological frame
Technological frames concern the “assumptions, expectations, and knowledge that people use to understand technology” (Huvila et al., 2021).
Orlikowski and Gash presented three generalised technological frames:
1. The nature of technology – which technologies are used in organizations, and for what?
2. Technology strategy – why these technologies were implemented, what expectations they were introduced to satisfy, and their desired impacts (aligned to organisational goals).
3. Technology-in-use – how these technologies are used to generate organisational changes and the conditions and consequences associated with these changes.
The social frame
Viewing information systems in terms of the social frame requires a detailed understanding of formal, informal and fluid organisational processes, focusing on the networks of organisations, people, and technological and social (sub-) systems that collectively shape design, development, implementation, and use. Social frames:
• Recognise that system design, implementation, and use are extended, socially-shaped and political processes.
• Take account of the multi-stakeholder needs of the enterprise, users and those affected by the use of an information system.
• Emphasise system design criteria that prioritise adaptability through local control and the building of environments that recognise and harness the creative capacities of people.
• Recognise and prioritise social support systems that encourage desired behaviours.
Common problem solving methods
- PDSA
- Root cause analysis
- Rapid Problem Resolution
- DMAIC (defince measure, analyse, improve, control
- 8D (pan, define, develop interim, analyse, agree, implement corrective, implement preventative, close)
- OODA (observe, orient, decide, act)
- GROW (goal, reality, obstacles, way forward)
- Creative problem solving
characteristics of wicked problems (
• They are difficult to define clearly.
• They have many interdependencies and are often multi-causal.
• Addressing wicked problems often leads to unforeseen consequences, often in unexpected places.
• They are often unstable. Frequently, wicked problems and the constraints or evidence involved in understanding them evolve simultaneously. They are ‘moving targets’”.
• They usually have no clear solution. Problem-solving often ends when deadlines are met or dictated by other resource constraints rather than when the best solution is identified. Solutions to wicked problems are not verifiably ‘right’ or ‘wrong’ but rather ‘better’, ‘worse’ or ‘good enough’.
• Wicked problems are socially complex, and it is social complexity rather than their technical complexity that makes resolution difficult.
• They hardly ever sit conveniently within the responsibility of any one organisation and require action at multiple levels.
• Solutions to many wicked problems involve changing the behaviours and/or gaining the commitment of individual citizens.
Tackling wicked problems seems to require at least
• Holistic, rather than partial or linear thinking – i.e. considering the interrelationships between the full range of causal factors and understanding the problem from the perspectives of multiple stakeholders.
• Innovative and flexible approaches and ongoing learning.
• Working across organisational, stakeholder, and other boundaries and setting governance arrangements aligned with this.
• Effective stakeholders and citizen engagement. Because wicked problems are often imperfectly understood and require sustained behaviour changes, they must be widely discussed by all relevant stakeholders to understand their complexity and interconnections fully.
• Tolerance of uncertainty and acceptance of the need for a long-term focus: there are usually no quick fixes.
Challenges contributing to the difficulties in interpreting legislation include:
• Legislation in Australia is written in English, and English is an imprecise language. As a result, English text is not always interpreted the same way by everybody.
• “The diversity of human conduct means that drafters [of legislation and regulations] have to try to deal with and am foreseeably wide range of future possibilities” (McLeod, as cited in Hall & Macken, 2021, p.3).
• Legislation and regulations, like everything else, exist within a context. This context includes other legal instruments, case law (previous interpretations accepted or denied by courts), societal expectations, and so on.
five principles upon which to interpret statutes within legistlation
- “The modern approach to statutory interpretation requires consideration of context and purpose, rather than a literal approach to the interpretation of the words of a statute”.
- “Consideration of context and purpose may sometimes require that the words of a statute are interpreted differently to their literal or grammatical meaning”.
- “Context and purpose includes consideration of legislative history and extrinsic material”, as well as the purpose of the legislation. “However, the purpose of legislation is not the subjective intention of those who ‘promoted or passed’ the legislation”.
- Legislation should be interpreted “on the basis that it is intended to give effect to harmonious goals, and to operate coherently”.
- “Legislative provisions should not be read to exclude fundamental rights or to depart from the general system of law” unless this is specifically articulated.
patchwork of regulation affects the practice of health informatics and digital health in Australia, the major components are:
• Privacy legislation.
• Legislation about health identifiers.
• Legislation about the MyHealthRecord system.
• Legislation about health records more generally.
• Freedom of Information legislation.
• Legislation under which health services and the health system are administered.\
Australian Privacy Principles summarised (13)
Australian Privacy Principles Part 1 — Consideration of Personal Information Privacy
APP#1 — Concerns the open and transparent management of personal information.
APP#2 — Concerns anonymity and pseudonymity.
Australian Privacy Principles Part 2 — Collection of Personal Information
APP#3 — Concerns the collection of solicited personal information.
APP#4 — Deals with unsolicited personal information.
APP#5 — Concerns the notification of the collection of personal information.
Australian Privacy Principles Part 3 — Dealing with Personal Information
APP#6 — Concerns the use or disclosure of personal information
APP#7 — Concerns direct marketing
APP#8 — Concerns cross-border disclosure of personal information.
APP#9 — Concerns the adoption, use or disclosure of government related identifiers.
Australian Privacy Principles Part 4 — Integrity of Personal Information
APP#10 — Concerns the quality of personal information.
APP#11 — Concerns the security of personal information.
Australian Privacy Principles Part 5 — Access to and Correction of Personal Information
APP#12 — Concerns access to personal information
APP#13 — Concerns the correction of personal information
Privacy impact assessment will
• Describe the relevance and flow of personal information in a project/initiative/system.
• Analyse possible impacts on the privacy of individuals.
• Identify, analyse and recommend between options for eliminating or mitigating impacts.
• Encourage good privacy practice and risk management.
A variety of new information privacy issues are poised to confront health informaticians, including the sample below:
• Information privacy and the inference economy.
“Information privacy is in trouble. Contemporary information privacy protections emphasize individuals’ control over their personal information. But machine learning, the leading form of artificial intelligence, facilitates an inference economy that strains this protective approach past its breaking point” (Solow-Niederman, 2021).
Current information privacy protections tend to focus on individual control over personal information. This is increasingly problematic because:
o Insights about individuals can be derived by aggregating huge amounts of otherwise innocuous data.
o Aggregated personal data can train machine learning models to make predictions about other people. Unfortunately, those third parties can suffer the consequences (e.g., ‘push’ marketing) even though they did not contribute to the targeting datasets.
• Advances in biometrics
Privacy-related technologies are not inherently bad. Consider, for example, the potential of facial recognition in healthcare:
o Overcoming the ‘wrong patient’ risk.
o Identifying and administratively processing people entering an emergency department pre-triage (enabling greater focus on the clinical). Combine this with emotion-sensing in assisting triage.
However, societal concerns about the potential misuse of facial recognition technologies, including by law enforcement and intelligence communities, may circumvent the potential advantages in healthcare.
• Genetic Privacy
Persons being genetically tested are not the only ones with interest in the results.
“There is a growing concern that sharing and releasing genomic sequencing poses risks to genetic privacy, that is, privacy related to the identification of a human individual and/or confidential/sensitive information about his/her personal traits from anonymous genome sequences” (Shi & Wu, 2016).
Human-centred design is
an approach to systems design and development that aims to make interactive systems more usable by focusing on the use of the system and applying human factors/ergonomics and usability knowledge and techniques”
Benefits attributed to human-centred design include
• Products and services that meet consumers’ real underlying needs.
• Improved customer experiences.
• Cost-effectiveness – systems and services that meet people’s needs tend to require less support.
• Reduced risk.
• Greater buy-in and impact from stakeholders through involvement in design.
• Greater empathy for consumers/users amongst service delivery staff and system developers.
