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Focus on Chronic Disease through Different Lenses of Expertise: Towards Implementation of Patient-Focused Decision Support Preventing Disability: The Example of Early Rheumatoid Arthritis
Linköpings universitet, Institutionen för beteendevetenskap och lärande. Linköpings universitet, Filosofiska fakulteten.ORCID-id: 0000-0002-1551-1722
2009 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)Alternativ titel
Fokus på expertis inom kronisk sjukdom : Implementering av prognostiskt beslutsstöd med exempel från reumatoid artrit (Svenska)
Abstract [en]

Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory disease. Treatment strategies emphasize early multi-professional interventions to reduce disease activity and to prevent disability, but there is a lack of knowledge on how optimal treatment can be provided to each individual patient.

Aim: To elucidate how clinical manifestations of early RA are associated to disease and disability outcomes, to strive for greater potential to establish prognosis in early RA, and to facilitate implementation of decision support through analyses of the decision-making environment in chronic care.

Methods: Multivariate statistics and mathematical modelling, as well as field observations and focus group interviews.

Results: Decision support: A prognostic tree that predicted patients with a poor prognosis (moderate or high levels of DAS-28) at one year after diagnosis had a performance of 25% sensitivity, 90% specificity and a positive predictive value of 76%. Implementation of a decision support application at a rheumatology unit should include taking into account incentive structures, workflow and awareness, as well as informal communication structures. Prognosis: A considerable part of the variance in disease activity at one year after diagnosis could be explained by disease progression during the first three months after diagnosis. Using different types of knowledge – different expertise – prior to standardized data mining methods was found to be a promising when mining (clinical) data for new patterns that elicit new knowledge. Disease and disability: Women report more fatigue than men in early RA, although the difference is not consistently significant. Fatigue in early RA is closely and rather consistently related to disease activity, pain and activity limitation, as well as to mental health and sleep disturbance.

Conclusion: A decision tree was designed to identify patients at risk of poor prognosis at one year after the diagnosis of RA. When constructing prediction rules for good or poor prognosis, including more measures of disease and disability progressions showed promise. Using different types of knowledge – different lenses of expertise – prior to standardized data mining methods was also a promising method when mining (clinical) data for new patterns that elicit new knowledge.

Abstract [en]

Introduktion: Reumatoid artrit (RA) är en kronisk inflammatorisk sjukdom. Dagens behandlingsstrategi bygger på tidiga multiprofessionella insatser för att reducera sjukdomsaktivitet och minska risken för framtida funktionshinder. Idag finns stora datamängder tillgängliga gällande medicinering och utfall vid RA. Dessa data erbjuder möjligheter att generera ny kunskap som kan användas för att forma beslutsstöd.

Syfte: Att undersöka hur olika kliniska manifestationer vid tidig RA samvarierar med funktionshinder och sjukdomsaktivitet, att pröva metoder att ställa prognos vid tidig RA, och att analysera en kontext för beslutsfattande inom vård av kroniskt sjuka.

Metod: Multivariat statistik och matematisk modellering, samt observationsstudier och fokusgruppsintervjuer.

Resultat: Beslutsstöd: Ett beslutsträd utformades för att bestämma vilka patienter som har dålig prognos (måttlig eller hög DAS-28) ett år efter diagnos. Beslutsträdet hade 25 % sensitivitet, 90 % specificitet och ett positivt prediktivt värde på 76 %. Vid införande av beslutsstöd på en reumatologisk klinik befanns det nödvändigt att hänsyn tas till incitamentsstrukturer, arbetsflöde och samarbetsformer. Informella kommunikationsstrukturer kan också ha stort inflytande på klinisk praxis. Prognos: En betydande del av variansen i sjukdomsaktivitet ett år efter diagnos kan förklaras av sjukdomsprogression första tre månaderna efter diagnos. Att formalisera olika experters erfarenheter före standardiserade ”data mining” metoder är en lovande ansats när man letar efter mönster i (kliniska) databaser. Funktionshinder och sjukdomsaktivitet: Kvinnor rapporterar mer trötthet än män vid tidig RA, men skillnaden är inte konsistent över tid. Trötthet vid tidig RA är nära relaterat till sjukdomsaktivitet, smärta och aktivitets begränsningar, men också till mental hälsa och sömnstörningar.

Slutsats: Ett beslutsträd har utformats för att predicera patienter med dålig prognos inom tidig RA. Studier av fler mått på sjukdoms- och funktionshindersprogression behövs vid konstruktion av prediktionsregler för god eller dålig prognos framledes. Att använda sig av kunskap från olika experter – olika experters glasögon – vid sökandet efter mönster i stora datamängder för att generera ny kunskap är en lovande metodik. Implementering av beslutsstöd bör göras under övervägande av incitamentsstrukturer, arbetsflöde och samarbetsformer.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press , 2009. , s. 126
Serie
Linköping Studies in Arts and Science, ISSN 0282-9800 ; 481Studies from the Swedish Institute for Disability Research, ISSN 1650-1128 ; 29
Nyckelord [en]
Clinical Decision Support, Rheumatology, Prognosis, Disability, Fatigue, Knowledge Engineering
Nyckelord [sv]
Kliniskt beslutsstöd, reumatologi, prognos, funktionshinder, trötthet, kunskapsmodellering
Nationell ämneskategori
Socialt arbete
Identifikatorer
URN: urn:nbn:se:liu:diva-18112ISBN: 978-91-7393-613-2 (tryckt)OAI: oai:DiVA.org:liu-18112DiVA, id: diva2:214774
Disputation
2009-05-29, Key 1, Hus Key, Campus Valla, Linköpings universitet, Linköping, 13:00 (Svenska)
Opponent
Handledare
Tillgänglig från: 2009-05-06 Skapad: 2009-05-06 Senast uppdaterad: 2018-04-07Bibliografiskt granskad
Delarbeten
1. Prognostic components and predictive modelling of prognosis in early RA
Öppna denna publikation i ny flik eller fönster >>Prognostic components and predictive modelling of prognosis in early RA
(Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
Abstract [en]

Introduction: There is a need for tools that are easy to use in clinical practice supporting decision making upon treatment in early rheumatoid arthritis (RA). Aim: The aim was to identify components of prognosticators in early RA and to identify individual patients with a poor prognosis as early as possible.

Methods: Two cohorts from the Swedish TIRA project including 320+408 patients with recent onset RA were included in the study. Disease activity was measured by C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and the 28-joint count disease activity score (DAS-28), and by the physicians’ global assessment of disease activity (PGA). Disability was assessed as activity limitation by the Swedish version of the Health Assessment Questionnaire (HAQ) and impairment was reported by pain on a visual analogue scale of 0–100 mm. Serological markers were rheumatoid factor (RF) and anti-CCP. RF was measured at the time for diagnosis, and anti-CCP at the time of diagnosis or at one or some of the follow-ups. If at least one anti-CCP test was positive, the patient was judged to be anti-CCP-positive. Assuming different clinical practice in the different cohorts, two different treatment strategies were assumed based on clinical practice in real-world settings. Principal Component Analysis and Multiple Linear Regression Analysis were used to identify prognosticators. Prediction rules were identified by data-driven approach, controlling for different treatment strategies.

Results: Progression of disease and disability measures and inflammation measures the first three months after inclusion predicted a considerable part of DAS-28 at the 1-year follow-up. Serological markers had a larger explanatory power for men than for women. Anti-CCP was a significant predictor for men, but not for women. Two versions of rules, one for women and one for men, predicting good or poor prognosis at one year after inclusion were produced by using measures of disability (Health Assessment Questionnaire), DAS-28, relative change in DAS-28 during first three months, sex, and test of anti-CCP. The rules demanded high prognostic specificity but the prognostic sensitivity was moderate.

Conclusion: A considerable part of DAS-28 at one year after inclusion could be explained by the first 3 months’ progression of disease, disability and inflammation. Anti-CCP was predictive for men but not for women, and needs further investigation. A decision tree predicting poor prognosis among individual early RA-patients showed high specificity and moderate sensitivity on a validationcohort. The medical informatics approach used, controlling for different treatment strategies, yields promising results and further studies will control for more specific differences in treatment strategies, e.g. different DMARDs initiated.

Nationell ämneskategori
Socialt arbete
Identifikatorer
urn:nbn:se:liu:diva-18104 (URN)
Tillgänglig från: 2009-05-06 Skapad: 2009-05-06 Senast uppdaterad: 2018-04-07Bibliografiskt granskad
2. A simple method for heuristic modeling of expert knowledge in chronic disease: identification of prognostic subgroups in rheumatology
Öppna denna publikation i ny flik eller fönster >>A simple method for heuristic modeling of expert knowledge in chronic disease: identification of prognostic subgroups in rheumatology
Visa övriga...
2008 (Engelska)Ingår i: eHealth Beyond the Horizon – Get IT There, IOS Press, 2008, Vol. 136, s. 157-162Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Identification of prognostic subgroups is of key clinical interest at the early stages of chronic disease. The aim of this study is to examine whether representation of physicians' expert knowledge in a simple heuristic model can improve data mining methods in prognostic assessments of patients with rheumatoid arthritis (RA). Five rheumatology consultants' experiences of clinical data patterns among RA patients, as distinguished from healthy reference populations, were formally represented in a simple heuristic model. The model was used in K-mean-clustering to determine prognostic subgroups. Cross-sectional validation using physician's global assessment scores indicated that the simple heuristic model performed better than crude data made in identification of prognostic subgroups of RA patients. A simple heuristic model of experts' knowledge was found useful for semi-automatic data mining in the chronic disease setting. Further studies using categorical baseline data and prospective outcome variables are warranted and will be examined in the Swedish TIRA-program.

Ort, förlag, år, upplaga, sidor
IOS Press, 2008
Serie
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; Vol. 136
Nyckelord
Knowledge engineering, Clinical Decision Support Systems, Semiautomated Data Mining, Rheumatoid Arthritis, Mathematical models in medicine
Nationell ämneskategori
Socialt arbete
Identifikatorer
urn:nbn:se:liu:diva-18106 (URN)000274308700026 ()18487724 (PubMedID)978-1-58603-864-9 (ISBN)978-1-60750-333-0 (ISBN)
Konferens
21st International Congress of the European-Federation-for-Medical-Informatic (MIE2008), Gothenburg, Sweden, MAY 25-28, 2008
Tillgänglig från: 2009-05-06 Skapad: 2009-05-06 Senast uppdaterad: 2018-04-07Bibliografiskt granskad
3. Factors related to fatigue in women and men with early rheumatoid arthritis: The Swedish TIRA study
Öppna denna publikation i ny flik eller fönster >>Factors related to fatigue in women and men with early rheumatoid arthritis: The Swedish TIRA study
2009 (Engelska)Ingår i: Journal of Rehabilitation Medicine, ISSN 1650-1977, E-ISSN 1651-2081, Vol. 41, nr 11, s. 904-912Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Objective: To study whether there are differences between women and men, with regard to the reported level of fatigue, and to explore the strength of the relations between fatigue and disease activity, pain, sleep disturbance, mental health, and activity limitation in early rheumatoid arthritis, and also to explore the consistency of such findings.

Design: Analyses and comparisons of cross-sectional data.

Subjects. 276 patients, 191 women and 85 men, with early rheumatoid arthritis were included.

Method: Patients were examined with respect to 28-joint count disease activity score, and disability variables reflecting pain, sleep disturbance, fatigue, mental health, and activity limitation, at follow-ups at one, two and three years after diagnosis.

Results: Women reported somewhat more fatigue than men. Fatigue was closely and rather consistently related to disease activity, pain and activity limitation, and also to mental health and sleep disturbance.

Conclusion: Although this study does not permit conclusions about causal directions, statistical relationships may be related to clinical conceptions about causation: When disease activity can be significantly reduced by pharmacological treatment, this may have a positive effect on fatigue. Specific treatment with respect to the mentioned disability aspects that are related to fatigue is also a clinically reasonable strategy.

Ort, förlag, år, upplaga, sidor
Uppsala, Sweden: FOUNDATION REHABILITATION INFORMATION, 2009
Nyckelord
Early rheumatoid arthritis, fatigue, sleep disturbance, sex
Nationell ämneskategori
Socialt arbete
Identifikatorer
urn:nbn:se:liu:diva-18108 (URN)10.2340/16501977-0444 (DOI)000271102800008 ()19841842 (PubMedID)
Tillgänglig från: 2009-05-06 Skapad: 2009-05-06 Senast uppdaterad: 2018-04-07Bibliografiskt granskad
4. Designing a decision support system for existing clinical organizational structures: Considerations from a rheumatology clinic
Öppna denna publikation i ny flik eller fönster >>Designing a decision support system for existing clinical organizational structures: Considerations from a rheumatology clinic
Visa övriga...
2006 (Engelska)Ingår i: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 30, nr 5, s. 325-331Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The aim of this study was to identify the social and organizational requirements for a decision support system (DSS) to be implemented in a clinical rheumatology setting, utilizing data-mining techniques. Field observations and focus group interviews were used for data collection. The decision-making was found to be situated, patient-focused, and long-term in nature. At the same time, the main part of peer-to-peer communication was informal. Patient records were involved in almost every decision. The conclusion is that the main challenges, when introducing a DSS at a rheumatology unit, are adapting the system to informal communication structures and integrating it with patient records. Considering incentive structures, understanding workflow and incorporating awareness are relevant issues when addressing these issues in future studies.

Nationell ämneskategori
Socialt arbete
Identifikatorer
urn:nbn:se:liu:diva-18111 (URN)10.1007/s10916-005-9000-1 (DOI)17068995 (PubMedID)
Tillgänglig från: 2009-05-06 Skapad: 2009-05-06 Senast uppdaterad: 2018-04-07Bibliografiskt granskad

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