Concepts

Here is a taster of the dictionary  of concepts we have under development. Reality is that those concepts can mean a different thing for any different person. Under those circumstances communication and teamwork become if not impossible at least hopelessly inefficient. By having a common conceptual dictionary we mitigate a major risk in any project or BAU activity. It usually takes more than just reading it. It takes understanding and building that understanding from ground up by hands on transfers of skills and conceptual transfer.

 

IT Concepts dictionary

Data mapping	Each organisation uses different systems and different labels for describing and capturing data needed for managing their business processes. A solution that we implement for integrating data from different systems will need data mapping. We have experience in doing this and therefore enhancing the quality, availability and meaning of the data that an organisation holds
Data processing	Data processing has many aspects to it but generally is a highly technical issue involving capturing it, validating it, cleaning it and presenting it in a way which is efficient and useful to the people managing and delivering care to the patients. All the aspects concerning this highly technical process are presented and taken care of in our implemented solutions. After implementation the solutions can be taken over by the organisation itself and managed, changed and maintained as the organisation wishes or can be left with ourselves to manage and maintain
Data import	The importing of data from different systems imposes on an organisation many challenges in terms of processing power, programming skills, scalability, data compatibility, and data transformation. All these aspects are highly technical and sometimes time consuming for an organisation that has operational deadlines to meet and therefore they seem not to be done in the most efficient manner. We can fill that gap of resources using our experience in data migration issues. Another aspect would be that of migrating existent data into a new system and preserving logical links and rules from an old system into a new system. We can advise on, mitigate and implement the risk that a data migration process presents for an organisation
Data cleaning	Data cleaning is a concept often subjected to misunderstanding and misinterpretation. We can put this right and then take the necessary steps to obtain for an organisation the cleanest data possible and therefore a more realistic basis for management, measurements and decision making. Three aspects are important from a data cleaning perspective: Completeness, Consistency, Logical compliance. All those need first to be checked using specific and efficient tools which we poses or we can build. Then we ca check for consistency and logical compliance and take the necessary steps to perform deliver you an enhanced data set that is more complete, consistent and logically true. That is a basis for analysing processes with your organisation and implement required changes as well as for adjusting and maintaining a healthy data set for patient care management.
Data warehouse	Most of the data integration, cleaning and delivery is packaged in a data warehouse solution. The data warehouse solution can be as complex or as simple as needed by the organisation and as agreed to implement with the available resources. Our previous implementations provide an efficient platform for delivering a customised solution to your organisation. The way this solution is built would be presented in a way in which resources within your organisation will be able to understand it and if needed to take it over for management and enhancement after our initial implementation
Data stores	Just as a goods warehouse is made of different stores (textiles, food, metal, tools, etc) our warehouse is made of stores (inpatients episodes, outpatient appointments, referrals, etc) Those data stores have many concepts in common and we uncover those before implementation therefore being able to preserve them all the way to the deliverable stage. Organising a data warehouse like this gives us a more elegant way, far more transparent than usual, to present the data to those who needed in raw form or in enhanced for (reports, summaries, etc)
Data enhancers	These are programs that we have already or that we can build to run automatically to enhance the meaning and the accessibility of data. They will present the data in a format that is a lot more accessible to the way we think and communicate in our day to day life. For example instead of using codes we will translate the codes and present the user with the meaning in English because that’s how we function and communicate through words and not through codes
To be continued when we start working together