Table 3 Types of optimisation

Order	Types of optimisation	Definition or Example	Coded	Frequency (%)*
1	Increasing efficiency	Had four categories: 1) General; 2) Making workflow more efficient; 3) Minimising time spent with EHR and 4) Presenting right data at right time during the care (e.g. showing potassium lab results and renal function when a physician places a potassium order)	111	27.5
2	Smarter decision support	Refining clinical reminders, integrated in workflow, outcome-focused	45	11.2
3	Improving patient care quality	For example, decreasing sepsis mortality by building a MEWS system within an EHR system	33	8.2
4	Realising ROI, value, cost-savings	Efforts maximising benefits of EHR systems in financial perspective	29	7.2
5	Optimising practice/process/workflow	Process improvement, for example, improving business process of getting payers’ authorisation for expensive imaging studies, thus, reducing denials and consequently, increasing revenue and satisfaction among all stakeholders	27	6.7
6	Effectively tracking metrics	For example, tracking ED patient flow metrics	22	5.5
7	Improving outcomes	For example, ensuring foot exam for diabetic patients	21	5.2
8	Increasing patient safety	For example, screening allergies and drug–drug interactions	20	5.0
9	Using data in EHR	Using reporting function, business intelligence and analytics, research	20	5.0
10	Meeting regulatory requirements	Joint Commission, Meaningful Use, etc.	17	4.2
11	Improving documentation	Reducing/refining templates, simplifying nursing flow sheets	14	3.5
12	Upgrading and implementing/building new features/modules	For example, implementing anaesthesia application after going live with an operation room system	14	3.5
13	Stabilising the implemented EHR	Ensuring stable and reliable function of EHR	10	2.5
14	Maximising ‘model’ or ‘foundation’ system	A vendor-specific term, meaning utilising vendor-provided basic system as much as possible	7	1.7
15	Thoughtful change management	Controlling and coordinating change in EHR	7	1.7
16	Improving physician/user adoption of EHR	Driving adoption of EHR specifically among physicians and clinicians	6	1.5
	Total = 16		403	100