Dawn Dowding PhD RN VNSNY Professor of Nursing Supporting Evidence Based Decision Making in Practice: Contextual and Organizational Factors in Developing Decision Support Dawn Dowding PhD RN VNSNY Professor of Nursing

What is Decision Support? Integration of evidence with characteristics from individual patients to provide advice or guidance during decision making Can be in a variety of formats Can support different ‘types’ of decision integrate evidence (ideally from high-quality research) with the characteristics of individual patients, in order to provide health care professionals (including nurses) with advice during decision-making can provide information and advice in a variety of formats, including paper-based guidance, more structured formulations such as decision algorithms and computerized systems Note that it is NOT providing facilities for clinicians to search for information online

Considerations when designing decision support The type of decision being taken Who is making the decision The organizational context

Types of decision

Diagnosis (Visualdx http://www.visualdx.com/features/) Diagnostic systems (of which this is an example) Normally work by prompting the clinician to input patient information, signs and symptoms This is then used to identify probably diagnoses from the systems database Always – looks at probability and possible diagnoses – gives estimates of likelihood Clinician still has to use clinical judgement Benefit that it ensures clinicians have considered all possible explanations/reasons for a patients signs and symptoms (helps to try and avoid the biases associated with diagnostic reasoning) (Visualdx http://www.visualdx.com/features/)

Reminder Systems Reminder systems: Often used at population level to collate and send out reminders for preventive health care interventions such as screening and vaccinations Now also used to send out text message reminders to patients (for things like doctors appointments etc). Normally offers facility for health care provider to select group of patients who will receive reminder, and format of that reminder. http://www.doh.wa.gov/Portals/1/Documents/Pubs/348-266-ReminderRecallStrategies.pdf

Disease Management Mann DM, Lin JJ. Increasing efficacy of primary care-based counseling for diabetes prevention: Rationale and design of the ADAPT (Avoiding Diabetes Thru Action Plan Targeting) trial. Implementation Science 2012; 7:6. Disease management Often incorporate evidence based guidance/guidelines into care processes to support disease management Normally for chronic conditions such as hypertension, diabetes Provide prompts to care givers to carry out certain activities, can also provide prompts to patients, may encourage patients to enter data onto a system, which clinicians then use to provide health care advice This particular example is a system for managing diabetes – where behaviour change interventions are supported through the EHR – examples include an action plan and behaviour change prescription at the clinical encounter – then supported by emails, advice and guidance and online tracking

Medications Management Elements include: assistance with prescribing (ensuring that clinicians are prescribing drugs at right dose, considering interactions etc) Assistance with drug dispensing and administration – so ensuring the right drug is given to the right patient, in the right dose, at the right time A system of alerts to ensure that the above two elements operate effectively – so alerts if physician tries to prescribe the wrong dose of a drug, if they prescribe something that interacts with another drug, if the nurse is trying to give a drug to the wrong patient). For drugs such as warfarin, the decision support would take a patients blood test result (INR) and calculate the right dose of warfarin – so does drug calculations

A framework for decision making to inform decision support design One of the first things you need to consider when either designing a decision support system, or if you want to introduce one, is what decisions you intend to support and why. Decision making is a complex clinical activity and you can’t just introduce a system without first understanding how the system might benefit or affect the decision process. This is an example of a simple decision making framework we developed for a tool that planned to assist with both the assessment and management of pain in patients with dementia in an acute care setting. The types of support that are required are different if you want to support the judgement process (making an assessment or diagnosis) or the decision process (choosing an intervention). In this case we wanted to support both elements but often decision support interventions support one thing or another – so they may provide guidance on what information to collect to inform a judgement or diagnosis (this is what diagnostic systems do), or alternatively assume that you know what is wrong with the patient and provide guidance on what the best treatment option is (this is often what medicines management and disease management systems do). Dowding et al. Using sense-making theory to aid understanding of the recognition, assessment and management of pain in patients with dementia in acute hospital settings. International Journal of Nursing Studies, 53:152-162. 2016

The decision maker

Who is using your system? Another factor you need to consider is who is going to use the system. More experienced or expert clinicians tend to make decisions in a different way to less experienced clinicians (explain here about expert vs novice and characteristics of their decision making) – and that it is context specific Key – are you trying to get everyone up to a level of competence or is it a more advanced task or a decision which it is vitally important that no-one makes a mistake on…

The potential for ‘mis-match’ ‘Rule’-based decision support targeted at ‘expert’ clinicians Lack of flexibility in the system – leads to workarounds Expert clinicians with expertise in using the system* Use of the system to ‘confirm’ a decision Manipulation of the system to provide the ‘right’ answer Use changes with system experience - more expert users less likely to follow the guidance – leading to overriding of recommendations Dowding D et al. Experience and nurses’ use of computerized decision support systems. Studies in Health Technology and Informatics: 146;505-510. 2009.

Experience/expertise and decision support So you’ve got an idea how you’re going to dose them and you run it through [the system] and you think, oh yeah, that agrees with me and it kind of boosts your confidence to know that you’re thinking along the right lines. “I end up almost engineering the answers, because you think ‘oh I can’t put that because it’s going to say” Nurses select algorithms, or predict what it is going to say, based on their knowledge of the system Dowding et al Nurses' use of computerised clinical decision support systems: a case site analysis 2009 Journal of Clinical Nursing, 18, 1159–1167

Experience/expertise and decision support “when you start doing the job, you do tend to rely on that more for guidance, you know, but as you get more experienced, that lessens.” “But we have to use our clinical judgment because there could be some different reason than what it says on the computer, the software” Variation in use of decision support depending on experience, with the system and/or patient condition

The Organizational Context

The Context Other factors are equally important: The organisational resources available to you – the majority of the work I have been involved in in the UK has developed paper based systems for supporting decision making. This is challenging as this often requires either asking nurses to fill out an additional bit of documentation OR replacing their existing documentation with your documentation – both of which have issues in terms of clinical acceptability. Organisations that have good electronic systems have the potential to develop or introduce computer based decision support – but there are still issues that you need to consider in terms of who will use it, how it fits with workflow. Basic issues such as where the clinical interactions take place, what equipment individuals may need, have you the resources to support changes in decisions taken….

The system and the environment Organizational context affects: How decisions are taken Who takes the decisions How CDS is implemented How CDS is used Dowding et al. Using sense-making theory to aid understanding of the recognition, assessment and management of pain in patients with dementia in acute hospital settings. International Journal of Nursing Studies, 53:152-162. 2016.

Conclusion Decision support offers the potential for using clinical data collected at point of care to inform decision making – ‘real time’ decision support, using a ‘learning’ system When designing decision support you need to consider: How to support decision processes over time and across individuals/organizations Does decision support need to be used by everybody? Should it be targeted at specific users/decision makers? How do you effectively integrate CDS into workflow and organizational systems?