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Ward Medication Management takes falls risk reduction to dizzying heights - updated 29/05/17

Through our multi-dimensional approach to assessing falls risk, we aim to offer tailored medications plans to those at most risk of falling.

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Who is your idea designed for and how does it enable older adults to live their best possible life by preventing falls?

Our idea is designed for older adults who are taking medications that may be inadvertently elevating their risk of falling. As a team of pharmacists, our idea is not based solely on medication use but also a host of other factors which may increase the risk of falls. The concept involves a multi-dimensional analysis to identify ways in which these factors can directly and indirectly predispose an older person to falling, or whereby the individual may be at risk of adverse outcomes after a fall.

The Problem

It is well known that many medications have the potential to increase the risk of falls. These risks are particularly apparent in older adults who are often sensitive to the adverse effects of medications. There are a variety of complex mechanisms by which medications and other factors can contribute to falls including effects on cognition, blood pressure, posture, muscle strength and eyesight. The World Health Organisation reports 30-50% of residents in long-term care will experience at least one fall each year and of those who suffer a hip fracture from falling, 20% will die within 1 year. Beyond the immediate impacts, there may be long lasting implications for those who suffer from falls. Detrimental effects to confidence and quality of life may occur and many individuals find themselves forced to shift to a higher level of care following a fall. 

Our solution

By analysing pharmacoepidemiological data gathered from thousands of comprehensive medication reviews, we can quantitatively assess and stratify falls risk. Using this method, we can assign a level of falls risk based on a combination of factors including age, gender, genomics, medications, pathology and medical conditions. We are currently developing a system to assess these variables and this will enable us to produce specific, tailored medication regimens for the elderly. We envisage that our approach will be able to highlight for prescribers, situations whereby their chosen approach to the management of an individual may confer extra risk of a serious adverse outcome such as a fall. The key to our approach is anticipating risk in advance and delivering proactive advice to prevent adverse outcomes before they occur. As well as delivering better clinical outcomes, we feel that this will be reflected in improved quality of life, reduced health care costs and diminished medicolegal risk.

Market Opportunity

We believe that our multi-dimensional approach to providing highly specific medication recommendations is unique in the market. Recommendations offered by current prescribing software are often not user specific and typically only assess direct medication-medication interactions. By analysing multiple different variables, our system will provide evidence-based, age-specific recommendations which are tailored to each individual patient. 

App Journey

Version 1 - Cloud based app built for pharmacoepidemiological data 

Version 2 - Cloud database used for business analytics 

Version 3 (current phase) - Auto-notification enabler aka "rules" engine built, DNA genotyping and pathology markers added

Version 4 (future phase) - Prescribing decision support with machine learning capability 

Web-based App Flow Diagram

User Journey Map

http://0bb.ad7.myftpupload.com/wp-content/uploads/2017/05/Jericho-System-Flow-Diagram-v1-1.pdf

About Us

'Ward Medication Management is the largest provider of clinical pharmacy services in the Australian aged care setting, and we are experts in medication analysis.’

http://wardmm.com.au

Accomplishments

Ward Medication Management is part of the Texas Medical Center (TMCx) Accelerator Digital Health 

http://medcitynews.com/2017/02/texas-medical-center-accelerators-giant-digital-health-cohort-includes-australian-contingent/ 

I understand that the following is what the TMCx is looking for from the startups in its cohort:

Companies that meet the following requirements should apply for consideration:

- You have at least one full-time founder 

- You have a working prototype 

- We have a preference for pre-revenue companies with previous pilots or early-revenue companies, but it is not required.

“We are in TMCx to validate, refine our system design and formulate a go-to market strategy in the USA with the hope of creating a global footprint for our company,” said Stuart Ward, CEO, Ward Medication Management.

Feedback and Questions

1. Would this be a situation where the patient takes a genetic test and using your tool they receive personalized advice on multiple medication?

Genomic testing allows us to understand an individual’s expression of certain hepatic enzymes which are responsible for the metabolism and therapeutic effects of many medications. By testing this variable, we can predict the response and risk of adverse effects from some medications and offered tailored advice specific to that person.

2. How would you identify patients suitable for the tool especially in the context of fall prevention?

Any person taking 5 or more medications is usually a good starting point for considering a medication review. For every medication which is added to a regimen, the risk of drug interactions and adverse effects increases exponentially. In relation to identifying those particularly at risk of falls we can specifically look at known risk factors and target these patients. There are many complex mechanisms by which medications can contribute to falls and our goal is to identify these and add them into our algorithms for detecting adverse events.

3. Have you thought about how the information from the tool could be communicated from the pharmacist to the older adult/caregiver?

Our primary goal is to proactively alert prescribers to medication risks and offer prescribing decision point in a primary prevention setting. Our app would also aim to provide the patient or carer with a simplified version of the doctor's report/recommendations.

4. Is the customer the pharmacist or the older adult/caregiver?

The customer of our app is the doctor.

5. Would your medication tool keep medical lists for older adults current and deal with the ‘lag’ in documenting up-to-date medication lists?

Our app would be able to store medication lists for patients and these lists would be accessible to the patient via a patient interface on the app.


6. Is Ward Medication Management specific for fall prevention or for multiple physical side effects from medication?

Ward Medication Management aims to prevent all types of medication related harm with falls prevention making up an important component of our work.


7. How do pharmacists currently give fall prevention advice to patients taking multiple medications?

In our specific field, we provide falls prevention advice directly to the doctor in the form of medication recommendations in our comprehensive medication reviews. We also provide education sessions to nursing staff which can help to reduce the incidence of medication-related adverse effects.

What early, lightweight experiment might you try out in your own community to find out if the idea will meet your expectations?

Our experiment would involve collecting data relating to the incidence of falls and correlating this with a variety of influencing factors including age, gender, medications, pathology, medical conditions and genomics. Using this data, we could then quantify and stratify an individual's risk of falling and use the result to proactively highlight the risks to prescribers. Implemented actions could then be followed up over a period of time to assess the impact on the incidence of falls.

What skills, input, or guidance from the OpenIDEO community would be most helpful in building out or refining your idea?

The OpenIDEO community would be instrumental in helping our team to refine and scale our idea to produce a commercially viable product that could be used to assist prescribers around the world. The larger the number of older adults we can apply this methodology for, the more powerful the evidence we can assemble to demonstrate the effect of the interventions.

How long has your idea existed?

  • Over 1 year

This idea emerged from

  • A group brainstorm

Tell us about your work experience:

Myself and our team of clinical pharmacists work collaboratively with other health professionals conducting medication reviews in the community and aged care sector. Our team has extensive experience in being able to identify and minimise the risk of medication misadventure in older adults.

How would you describe this idea while in an elevator with someone?

Imagine that there was a tool that could calculate, with ease, the potential for serious medication-related adverse outcomes based on any given combination of set patient characteristics (age, weight, kidney function etc). Imagine that this system was widely available and accessible to doctors everywhere and could generate highly specific medication recommendations with the touch of a button.

How does your idea demonstrate our Criteria of Affordability?

For a GP to be able to plug in online the conditions, medications and biological profile to ascertain precision medication management, the cost of this analysis is only $10 a record using AI. We envisage that our tool will greatly improve prescribing efficiency, reduce inappropriate medication use and minimise potential harm to the patient.

How does your idea demonstrate or plan to demonstrate scalability?

We plan on using an online, web based application accessible from almost anywhere which can also serve as an electronic medical record holder and can be plugged into any system with API.

How do you plan to measure the impact of your idea?

To measure the impact of our idea we plan on assessing the number of medicines de-prescribed and recommendations followed by the doctor. This data could then be studied in relation to the incidence of adverse effects ie falls. We also have the capacity for our data to be published in medical journals for critique and the feedback then used to further refine and improve our "rules" engine.

What are your immediate next steps after the challenge?

After the challenge we plan on building the algorithm "rules" engine and adding auto notifications and data visualisations as we move towards version 4 of our web-based app.

Attachments (1)

Wardmm App Flow Diagram.pdf

Prescriber Decision Support Web-based App

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