At all stages related to care, information systems showcase errors since healthcare quality is vigilantly implemented and diligently pursued to minimize the impact associated with information mismatch.
Nature of Personal Information
Health information systems mostly manage information of personal nature. Most of the data transfer between different healthcare entities involves real and possible risk of information landing in the wrong hands. This perception of compromised privacy makes information exchange in health become extremely convoluted.
Regulators and Competition Influence
All patient data in healthcare is subject to regulatory policies. Providers of information and communications technology (ICT) based solutions experience additional complexities when organizations exploit the advantages of their offering. This makes it more complex to realize ICT-driven innovations within healthcare.
Professionalism and Hierarchy
Powerful stakeholders such as the hierarchical nature and professionals driving the health care organizations often resist technology, creating barriers to fully exploit the potentials associated with health information systems.
Although ICT faces multiple barriers in healthcare, there is an overall unity in the usage of HCISs. This is because of most of the healthcare services are interdisciplinary in nature. This heterogeneity of disciplines in healthcare makes using ICT very complex – forcing an approach that makes the information system different from the simple classification system usually followed in other industries.
Implementation, Learning and Adaptation
Within the delivery of healthcare, there is an ongoing tension between the need for order on one hand and the need for sensitivity on the other. Because of this tension, the importance of effective learning and adaptation surrounding the implementation of HCISs increases. The acuteness of the situation can be estimated from the fact that solutions working well in one specific context in healthcare does not necessarily work in others.
Information systems in healthcare are processes that involve all key stakeholders in an organization’s goals, including the project, business unit and the company’s overall management. This mandates transparent decision-making in the governance process of the enterprise architecture ensuring that organizational changes move in the desired direction, while also implementing objectives and goals. Such ownership processes may include enforced or clearly spelled rules or may be broadly defined IT principles. Apart from allowing an organization to achieve IT objectives, Information systems help in creating and enforcing accountability. Given the complexity and specificity of the healthcare information systems market, we can only expect funding and interest to increase in the coming years.
The most basic part of any HealthKit data point is a unit, which are essentially units of measure for the health data collected via HealthKit. You can collect numbers from your users to no end but they will have little meaning without a unit. In HealthKit, the class representing units is called
HKUnit. Units are fairly straightforward and many units are already builtin to HealthKit and have helper methods to quickly create the unit you need. Or if there is no helper method to create your unit, the easiest way is to create the unit with what is called a unit string
HKUnit *gram = [HKUnit gramUnit]; HKUnit *mgPerdL = [HKUnit unitFromString:@"mg/dL"];
Your units should be chosen appropriately for the type of data being collected. For example, you wouldn’t choose grams when measuring temperature and its unlikely you would choose Kelvin when measuring temperature either. The two most appropriate choices for temperature would be either Fahrenheit or Celsius. This choice is up to personal preference as HealthKit does not prefer one or the other. There are a number of APIs within HealthKit that aid in converting units between US standard units and the metric system but those are beyond the scope of this blog post.