The problem
Clinical practice guidelines (CPGs) are used byhealth professionalstoguidebest practice, evidence-based care for specific health conditions, for example diabetes, hypertension, chronic heart failure and obesity.Since the early 2000s, guideline-based computerised platforms, have been developed tohelphealth professionals deliverthe best possiblecarebyenhancingclinical decision support systems (CDSSs),which make it easier to implement the guidelines in practice. However, there is a lack of standardization in formatting the computer-interpretable guidelines (CIGs) that underpin such systems. This can create conflicts and contradictionsbetween conditions ortreatment approachesand is aparticularissuewhen dealing with patients with multiple conditions or comorbidities.The management of multimorbid patients is complexanda key health challenge,accountingfor78% of all GP patient visitsand beingclosely associated with mortality and severe disability.Patients with multimorbidity receivemultiple treatment regimensand ifthese are not coordinated it can result inanincreased risk of adverse drug interactions and poor adherence to treatment and medication.
Professor Theodoros Arvanitis, Associate DirectorHDRUKMidlands Site,explains:“When these guidelinesare produced, theyusuallytend to review the evidence separately for each condition. In some cases, say with diabetes and cardiovascular disease,which are very much linked,the guidelinesand treatment pathstend to be more harmonised. But when youthenthrow in say arthritis and COPD[chronic obstructive pulmonary disease]intothatmix, it startsto get very complex,indeed.”
The solution
By developing a CDSS which applies CIG in practice,this project aimsto code guidelines in a way that is standardised, consistentand unambiguous. The aim of the Better Care project,led byProfessor Arvanitis, is todevelopastandardlanguagethat can executemultipleCIGsfor different conditions.It is based on an ontological approach, which is essentially a way ofdefiningvariousdiseases, their attributes or characteristicsas well as theirrelationshipswitheach other.
“The problem with guidelines is that they can become very rigid if they follow a very specific representation –soweareworkingtowardsdevelopingdynamic modellingfor CIGs. Here you don’t have static knowledge that simply shows basic relationships, but you have dynamic knowledge and temporal relationships, such asstart time, end time and duration.”
“Ultimately this is about how we supportclinicians and patientsto makedecisions andhelp themreconcilebest practiceguidelineswhich mayconflict. That doesn’tnecessarilymean convergence to a single complete solutionfor everyone,butrathera tailored approach tominimisethe riskfor each patient. For example,we might accepta degree ofrisk in terms of diabetesmanagementin ordertotreata very high risk of renal failure.”
Thesedynamicmodels willincorporateboth drug-disease,anddisease-disease interactionsalongsideallergies, drug intolerances, genetics and past treatment history.Initially, the team will work with groups of patients with multiple different conditionstodevelopspecific use cases.
Impact and outcomes
This project will developflexibleCDSSs and a supporting standard language.
The systemswill helpclinicians and patients to deviselong-term care planswithtreatment choices and goalstailored toindividualpatients, involving them in ashared decision-making processthat accommodates their preferences.Overall, this willhelptomaximisetreatmentadherenceand satisfaction with outcomes.
Professor Arvanitis comments:“Our aim is to translate this work into a practical decision support systemandwork with NICE[The National Institute for Health and Care Excellence]to addresscare planning of complex comorbidities.I believe this is an area where we can make a real differencegoing forward.Through the pandemic we’ve come to appreciate the complexity of COVID-19 and the many complications ofinfectionwhich will need to be managed alongside existingcomorbidities.This represents a key opportunity to apply these frameworks to help provide the best possible long-term care to the many millions of people affected by the pandemic.”
