scholarly journals Comparing health insurance data and health interview survey data for ascertaining chronic disease prevalence in Belgium

2020 ◽  
Author(s):  
Finaba Berete ◽  
Stefaan Demarest ◽  
Rana Charafeddine ◽  
Olivier Bruyère ◽  
Johan Van der Heyden
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Health Insurance ◽  
Health Status ◽  
Administrative Data ◽  
Predictive Value ◽  
Kappa Statistic ◽  
Data Sources ◽  
Thyroid Disorders ◽  
Interview Survey

Abstract BackgroundHealth administrative data were increasingly used for chronic diseases (CDs) surveillance purposes. This cross sectional study explored the agreement between Belgian compulsory health insurance (BCHI) data and Belgian health interview survey (BHIS) data for asserting CDs.MethodsIndividual BHIS 2013 data were linked with BCHI data using the unique national register number. The study population included all participants of the BHIS 2013 aged 15 years and older. Linkage was possible for 93% of BHIS-participants, resulting in a study sample of 8474 individuals. For seven CDs disease status was available both through self-reported information from the BHIS and algorithms based on ATC-codes of disease-specific medication, developed on demand of the National Institute for Health and Disability Insurance (NIHDI). CD prevalence rates from both data sources were compared. Agreement was measured using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) assuming BHIS data as gold standard. Kappa statistic was also calculated. Participants’ sociodemographic and health status characteristics associated with agreement were tested using logistic regression for each CD.ResultsPrevalence from BCHI data was significantly higher for CVDs but significantly lower for COPD and asthma. No significant difference was found between the two data sources for the remaining CDs. Sensitivity was 83% for CVDs, 78% for diabetes and ranged from 27% to 67% for the other CDs. Specificity was excellent for all CDs (above 98%) except for CVDs. The highest PPV was found for Parkinson’s disease (83%) and ranged from 41% to 75% for the remaining CDs. Irrespective of the CDs, the NPV was excellent. Kappa statistic was good for diabetes, CVDs, Parkinson’s disease and thyroid disorders, moderate for epilepsy and fair for COPD and asthma. Agreement between BHIS and BCHI data is affected by individual sociodemographic characteristics and health status, although these effects varied across CDs.ConclusionsNHIDI’s CDs case definitions are an acceptable alternative to identify cases of diabetes, CVDs, Parkinson's disease and thyroid disorders but yield in a significant underestimated number of patients suffering from asthma and COPD. Further research is needed to refine the definitions of CDs from administrative data.

scholarly journals Comparing health insurance data and health interview survey data for ascertaining chronic disease prevalence in Belgium

2020 ◽  
Vol 78 (1) ◽  
Author(s):  
Finaba Berete ◽  
Stefaan Demarest ◽  
Rana Charafeddine ◽  
Olivier Bruyère ◽  
Johan Van der Heyden
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Health Insurance ◽  
Health Status ◽  
Administrative Data ◽  
Predictive Value ◽  
Kappa Statistic ◽  
Data Sources ◽  
Thyroid Disorders ◽  
Interview Survey

Abstract Background Health administrative data were increasingly used for chronic diseases (CDs) surveillance purposes. This cross sectional study explored the agreement between Belgian compulsory health insurance (BCHI) data and Belgian health interview survey (BHIS) data for asserting CDs. Methods Individual BHIS 2013 data were linked with BCHI data using the unique national register number. The study population included all participants of the BHIS 2013 aged 15 years and older. Linkage was possible for 93% of BHIS-participants, resulting in a study sample of 8474 individuals. For seven CDs disease status was available both through self-reported information from the BHIS and algorithms based on ATC-codes of disease-specific medication, developed on demand of the National Institute for Health and Disability Insurance (NIHDI). CD prevalence rates from both data sources were compared. Agreement was measured using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) assuming BHIS data as gold standard. Kappa statistic was also calculated. Participants’ sociodemographic and health status characteristics associated with agreement were tested using logistic regression for each CD. Results Prevalence from BCHI data was significantly higher for CVDs but significantly lower for COPD and asthma. No significant difference was found between the two data sources for the remaining CDs. Sensitivity was 83% for CVDs, 78% for diabetes and ranged from 27 to 67% for the other CDs. Specificity was excellent for all CDs (above 98%) except for CVDs. The highest PPV was found for Parkinson’s disease (83%) and ranged from 41 to 75% for the remaining CDs. Irrespective of the CDs, the NPV was excellent. Kappa statistic was good for diabetes, CVDs, Parkinson’s disease and thyroid disorders, moderate for epilepsy and fair for COPD and asthma. Agreement between BHIS and BCHI data is affected by individual sociodemographic characteristics and health status, although these effects varied across CDs. Conclusions NHIDI’s CDs case definitions are an acceptable alternative to identify cases of diabetes, CVDs, Parkinson’s disease and thyroid disorders but yield in a significant underestimated number of patients suffering from asthma and COPD. Further research is needed to refine the definitions of CDs from administrative data.

Severe Maternal Morbidity: A Comparison of Definitions and Data Sources

2021 ◽  
Author(s):  
Jonathan M Snowden ◽  
Audrey Lyndon ◽  
Peiyi Kan ◽  
Alison El Ayadi ◽  
Elliott Main ◽  
...  
Keyword(s):  
Administrative Data ◽  
Maternal Morbidity ◽  
Claims Data ◽  
Birth Certificate ◽  
Population Level ◽  
Kappa Statistic ◽  
Data Sources ◽  
Severe Maternal Morbidity ◽  
Fine Grained ◽  
Control And Prevention

Abstract Severe maternal morbidity (SMM) is a composite outcome measure that indicates serious, potentially life-threatening maternal health problems. There is great interest in defining SMM using administrative data for surveillance and research. In the US, one common way of defining SMM at the population level is an index developed by the Centers for Disease Control and Prevention. Modifications have been proposed to this index (e.g., excluding maternal transfusion); some research defines SMM using an index introduced by Bateman et al. Birth certificate data are also increasingly being used to define SMM. We compared commonly used US definitions of SMM to each other among all California births, 2007-2012, using the Kappa statistic and other measures. We also evaluated agreement between maternal morbidity fields on the birth certificate compared to claims data. Concordance was generally low between the 7 definitions of SMM analyzed (i.e., κ < 0.4 for 13 of 21 two-way comparisons), Low concordance was particularly driven by presence/absence of transfusion and claims data versus birth certificate definitions. Low agreement between administrative data-based definitions of SMM highlights that results can be expected to differ between them. Further research is needed on validity of SMM definitions, using more fine-grained data sources.

scholarly journals Rehabilitation Therapy Utilization in Patients with Parkinson’s Disease in Korea

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Han Gil Seo ◽  
Sang Jun Park ◽  
Jiah Seo ◽  
Seong Jun Byun ◽  
Byung-Mo Oh
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Health Insurance ◽  
Clinical Practice ◽  
Patient Characteristics ◽  
National Sample ◽  
Present Evidence ◽  
Rehabilitation Therapy ◽  
Swallowing Therapy ◽  
Over Time

Objective. Although evidence and guidelines recommend appropriate rehabilitation from the beginning of diagnosis in patients with Parkinson’s disease (PD), there is a lack of data addressing the utilization of rehabilitation therapies for these patients in practice. The aim of this study is to investigate the rate of rehabilitation therapy utilization over time in patients with PD using a nationwide cohort in Korea. Methods. Patients were identified using the registration code for PD in the program for rare, intractable disease from the National Health Insurance Service-National Sample Cohort database, which consists of 979,390 Korean residents. Data were divided into four periods: 2004–2006, 2007–2009, 2010–2012, and 2013–2015. We assessed the utilization of rehabilitation therapies and the associated patient characteristics. Results. The numbers of patients with PD were 384 in 2004, 855 in 2007, 1,023 in 2010, and 1,222 in 2013. The numbers of physiatrist visits per person were 0.58, 0.96, 1.97, and 2.91, in the respective periods. Among the patients, 35–40% had claims for physical therapy, 16–19% for occupational therapy, and 4–6% for swallowing therapy. There were no remarkable differences between these rates between the study periods. Sex, age, income, disability, and levodopa-equivalent dose were significantly associated with the utilization of rehabilitation therapy. Conclusion. This study demonstrated that the rate of rehabilitation therapy utilization did not change remarkably in patients with PD from 2004 to 2015 in Korea although the number of physiatrist visits increased dramatically. The present evidence and guidelines may have not been adequately integrated into clinical practice during the period of study. Additional efforts may be warranted to provide adequate rehabilitation therapies in clinical practice for patients with PD.

scholarly journals Visual illusions in Parkinson's disease: an interview survey of symptomatology

2021 ◽  
Author(s):  
Chinami Sasaki ◽  
Kayoko Yokoi ◽  
Hiroto Takahashi ◽  
Tomoyuki Hatakeyama ◽  
Koji Obara ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Visual Illusions ◽  
Interview Survey

Deep brain stimulation and cognitive decline in Parkinson’s disease: The predictive value of electroencephalography

2015 ◽  
Vol 262 (10) ◽  
pp. 2275-2284 ◽  
Author(s):  
A. Markser ◽  
Franziska Maier ◽  
C. J. Lewis ◽  
T. A. Dembek ◽  
D. Pedrosa ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Cognitive Decline ◽  
Brain Stimulation ◽  
Predictive Value ◽  
Deep Brain

scholarly journals Assistive HCI-Serious Games Co-design Insights: The Case Study of i-PROGNOSIS Personalized Game Suite for Parkinson’s Disease

2021 ◽  
Vol 11 ◽  
Author(s):  
Sofia Balula Dias ◽  
José Alves Diniz ◽  
Evdokimos Konstantinidis ◽  
Theodore Savvidis ◽  
Vicky Zilidou ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Health Status ◽  
Game Design ◽  
Serious Games ◽  
Linear Regression Analysis ◽  
Real Life ◽  
Design Parameters ◽  
Online Questionnaire ◽  
Design Elements

Human-Computer Interaction (HCI) and games set a new domain in understanding people’s motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people’s health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson’s Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients’ quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

scholarly journals Acoustic analysis of swallowing as an auxiliary method for assessing dysphagia in Parkinson's disease

2021 ◽  
Vol 10 (16) ◽  
pp. e323101623298
Author(s):  
Glauce Souza da Silva ◽  
Ana Clara Gonçalves de Figueiredo ◽  
Bianca Simone Zeigelboim ◽  
Cristiano Miranda de Araújo ◽  
José Stechmann Neto ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Predictive Value ◽  
Acoustic Analysis ◽  
Screening Method ◽  
Oropharyngeal Dysphagia ◽  
Accuracy Study ◽  
Swallow Study ◽  
Videofluoroscopic Swallow Study ◽  
Tracheal Aspiration

Objective: To measure the accuracy of DeglutiSom as an auxiliary method to assess swallowing in patients with Parkinson's disease (PD). Methodology: Accuracy study. Among 248 individuals, 91 participants met the inclusion criteria, with a mean age of 64.9 years (SD 7.7), 53.8% male and 46.2% female, with a mean disease duration of 12.6 years (SD 3.8 years). Two instrumental studies were performed: An acoustic analysis with Sonar Doppler via the DeglutiSom Software, and a videofluoroscopic swallow study. Three judges analyzed the swallowing sounds in the DeglutiSom software and the instrumental examination findings. Results: The inter-rater reliability was 90.1%, with 4.4% degree of partial agreement and 5.5% disagreement. Sensitivity resulted in 90.0% and specificity in 90.0%. A sensitivity of 97.0% and specificity of 91.0% are indicators of a high validity for the dysphagia screening method, with predictive value (+) of 97.0% and predictive value (-) of 91.0%, with an accuracy method of 96.0%. The validity indicator values for screening aspiration were also high, with a sensitivity of 90.0%, specificity of 90.0%, predictive value (+) of 82.0%, predictive value (-) of 95% , 0% and 90.0% accuracy. Conclusion: The method proposed is considered appropriate for oropharyngeal dysphagia and tracheal aspiration screening in patients with Parkinson's Disease.

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