Adherence og persistence til behandling med medicinsk teknologi - Er det muligt at forudsige ud fra patienters baseline data i et klinisk studie?

Abstract

Resume Introduktion: WHO antager at kun 50 % af kroniske patienter er adherente til langvarig behandling, hvilket resulterer i dårligere sundheds outcome og stigende sundhedsudgifter. Evaluering af teknologianvendelse bør inkludere oplysninger om patienters adherence og persistence. I dette projekt undersøges, hvordan adherence og persistence kan kvantificeres i et eksisterende klinisk studie, og hvorvidt det er muligt at forudsige adherence og persistence ud fra forsøgspersoners baseline data. Metode: Der udføres en retrospektiv analyse af 100 KOL patienters baseline data samt anvendelse af medicinsk teknologi i et etårigt RCT studie. Adherence og persistence evalueres gennem objektive monitorerings data. Patienterne klassificeres som adherente/non-adherente ud fra en grænseværdi på > 80 % anvendelse ift. det rekommanderede antal timer/dag. Grænsen for persistence sættes ved gennemført studie uden afbrydelse af behandling. Der testes for forskel mellem subgruppernes baselinedata ved independent t-test, Mann-Whitney U-test og Chi-square test for at finde mulige prædiktorer for adherence og persistence. Resultater: Ud fra de fastsatte grænseværdier blev 52 % klassificeret som adherente mens 50 % var persistente til behandlingen. 9/50 (18%) afbrød behandlingen indenfor den første måned og 34/50 (68 %) indenfor 6 mdr. Resultaterne viste, at patienterne ud fra baseline data som fx rygestatus, sygdomshistorik og demografiske data lignede hinanden ved inklusion i studiet. De indsamlede baseline karakteristika kan derfor ikke stå alene om at forudsige, hvilke patienter der bliver eller har potentiale til at være adherente eller persistente til behandling med den medicinske teknologi. Diskussion: En 80 % grænseværdi vurderes anvendelig til kvantificering af adherence. En sammenfattende evaluering, som estimerer anvendelsen gennem hele studiet, skildrer ikke tendenser til ændringer i anvendelsen gennem de forskellige faser i adherence-processen, og giver dermed et mere usikkert estimat af patienternes adherence. En løbende monitorering af patienters anvendelse kunne bidrage med viden om den dynamiske proces. Et prospektivt studiedesign med systematisk indsamling af både subjektive og objektive monitoreringsdata kan anbefales i fremtidige studier. Konklusion: Det er ikke muligt alene ud fra patienters baseline data at forudsige deres adherence og persistence til behandling. En evaluering af teknologi anvendelse bør inkludere flere aspekter og perspektiver.

Abstract Introduction: Adherence among patients suffering chronic diseases averages only 50% according to WHO which causes poor health outcomes and increased health care costs. Evaluation of technology use should include information about patient adherence and persistence. In this project, it is investigated how adherence and persistence can be quantified in an existing clinical study and whether it is possible to predict adherence and persistence based on subjects' baseline data. Method: A retrospective analysis of 100 COPD patients baseline data and their use of medical technology in a one-year RCT study is performed. Adherence and persistence are evaluated through objective measurements. Patients are classified as adherent /non-adherent from a cut-point of > 80% of the recommended use. The cut-point for persistence equals completed study without interruption of treatment. To find possible predictors of adherence and persistence, Independent t-test, Mann-Whitney U test and Chi-square test are performed to test for differences between subgroups baseline data. Results: Based on the decided cut-points, 52% were classified as adherent while 50% were persistent to treatment. 9/50 (18%) discontinued treatment within the first month and 34/50 (68%) within 6 months. Results indicated that patients from baseline data e.g. smoking status, history of disease and demographic data were comparable by time of inclusion. Therefore, the collected baseline characteristics cannot stand alone to predict which patients are or have the potential to be adherent or persistent for treatment with the medical technology. Discussion: A cut-point of 80% is considered useful for quantification of adherence. Summary evaluations, that are estimated over an aggregate period of time, does not portray trends of technology use through the different phases of the adherence process, thus providing a more uncertain estimate of patient adherence. Continuous monitoring of technology use could contribute with knowledge of the dynamic process. A prospective study design with systematic collection of both subjective and objective monitoring data can be recommended in future studies. Conclusion: It is not possible from patient's baseline data alone, to predict their adherence and persistence to treatment. An evaluation of technology use should include additional aspects and perspectives.

A master thesis from Aalborg University

Adherence og persistence til behandling med medicinsk teknologi - Er det muligt at forudsige ud fra patienters baseline data i et klinisk studie?

[Treatment adherence and persistence to medical technology - is it possible to predict based on patients baseline data?]