Using open source at the Christie and how it supports agile software development; projects completed...

Post on 25-Jun-2015

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Dr Rhidian BramleyChief Clinical Information Officer

Director of Radiology

Using open source at the Christie

CCIO Open Source Conference

Dr Jac LivseyClinical Outcomes Unit Lead Consultant Clinical Oncologist

and how it supports agile software developmentprojects completed to date and current portal developments

Open Source at the Christie

Christie Clinical Portals

Christie Clinical Web Forms

Christie Clinical Web Forms• Clinical noting• Nursing & AHP assessments• Clinical observations and results• Care plans and actions• Order communications• Clinical referrals• Discharge letters and TTOs• Clinical outcomes• MDT meetings• Clinical audit• Clinical research• Staff & patient surveys

Christie Clinical Web Forms

Form Status Total

Concept 12

Design 73

Test QA 78

Live 162

Retired 23

Christie Clinical Web Forms

Structured clinical dataReal time clinical coding

Secure role based accessRecord locking, audit and version control

Clinical workflowClinician and patient worklists

Simple and flexible designForm and field templatesBuild reusable questions and tables

Performance & analyticsData quality reports and charting

NotificationsMessages and reminders

Set rules logicDynamic on data entryShow/hide questionsCalculate risk Customise care plansShow alerts

Custom data modelLoad and persist patient data

Clinical safetyRisk assessment scoringPoint of care decision support

Data display optionsTables, charts, journal, timeline

Easy and intuitive to useForms designed by cliniciansLogical relevant questions. Click and select

Medical care

• Provide patient care• Record care given

And now…• Collect clinical outcomes data

Dilemma

• Who has time to collect the data?

• Who is able to collect meaningful accurate data?

Solution

• Integrate data collection so completely into the workflow that it becomes part of the workflow not extra to it.

• Making data collection replace the previous normal record of patient care

• Designing intelligent, intuitive, clinically relevant processes

Clinician completes disease specific web forms

Recording Clinical Tumour Stage

• Christie (2011) 41%• Christie (2014) 90%

Overall survival by other factors

Electronic nursing

Previous nursing process1. Admit patients, formulate care plans and complete care plans on paper2. Some data (CQUINS) entered electronically3. Some data used for paper referrals4. Some data collected by regular “walk arounds” and spot checks

Electronic nursing

Problems• Data collected up to 4 times• Much of the data collection is distinct from patient

care• Almost all the data recorded is not usable for analysis• No real time data• Very labour intensive• Perceived as ‘box ticking’ waste of time by staff

Electronic nursing pilotFeb 2014

49 nursing assessment forms created for pilot• Forms were easy to use• Saved time overall• Increased time spent with patients• Helped clinical decision making• Improved data quality• Allowed real time data capture

Electronic nursing pilotQuotes

Nurse: “Fewer interruptions when completing with patients” (compared to completing at a screen were people can ask you to do other things and you get distracted).Nurse: “We don’t want to go back to the old way”.Nurse: “I want to give the patient as much information as possible, now I can’t forget anything as I’m prompted on screen”.Nurse: ”(We’ve) come back to the days where we know our patient”.Nurse: “There’s more patient involvement”.

Patient: ”The nurse told me so much more” (compared to a previous appointment at the hospital, the patient felt that the nurse told them more information and had more time to speak to them).

MDT data capture

Pathway

MDT Referral

• Patient and provisional diagnosis• Clinical details for rad and path review

MDT Meeting

• Confirm information• Confirm diagnosis, staging and treatment

Clinic• Review patient• Agree management and treat

Conclusions

• Develop a system that allows the users to directly interact and dictate design

• Work closely together to refine and improve

• Produce a tailored, user friendly, efficient system that both improves patient care and seamlessly collects the evidence to prove it