Longitudinal Healthcare Utilization and Costs in Parkinson's Disease: Pre-Diagnosis to 9 Years After

Systematic Review of the Cost of Illness of Parkinson's Disease from a Societal Perspective

Previous reviews on the cost of illness (COI) of Parkinson's disease (PD) have often focused on health-care costs due to PD, underestimating its effects on other sectors. This systematic review determines the COI of PD from a societal perspective. The protocol was registered in PROSPERO (ID: CRD42023428937). Embase, Medline, and EconLit were searched up to October 12, 2023, for studies determining the COI of PD from a societal perspective. From 2812 abstracts, 17 studies were included. The COI of PD averaged €20,911.37 per patient per year, increasing to almost €100,000 in the most severely affected patients. Health-care costs accounted for 46.1% of total costs, followed by productivity loss (37.4%) and costs to patient and family (16.4%). The COI of PD strongly varied between different geographical regions, with costs in North America 3.6 times higher compared to Asia. This study is the first to identify the relative importance of different cost items. Most important were reduced employment, government benefits, informal care, medication, nursing homes, and hospital admission. There was strong variety in the cost items that were included, with 55.2% of cost items measured in fewer than half of articles. Our review shows that PD-COI is high and appears in various cost sectors, with strong variety in the cost items included in different studies. Therefore, a guideline for the measurement of COI in PD should be developed to harmonize this. This article provides a first step toward the development of such a tool by identifying which cost items are most relevant. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Trends in Physiotherapy Interventions and Medical Costs for Parkinson's Disease in South Korea, 2011-2020

OBJECTIVE

Physiotherapy (PT), which is an effective strategy for managing Parkinson's disease (PD), can influence health care utilization. We analyzed trends in health care utilization, PT interventions, and medical costs among patients with PD.

METHODS

Using data from the Korean National Health Insurance Service from 2011 to 2020, we analyzed the number of patients with PD and their health care utilization and assessed the odds ratio (OR) for receiving regular PTs.

RESULTS

Over 10 years, 169,613 patients with PD were included in the analysis. The number of patients with PD increased annually from 49,417 in 2011 to 91,841 in 2020. The number of patients with PD receiving PT increased from 4,847 (9.81%) in 2011 to 13,163 (14.33%) in 2020, and the number of PT prescriptions increased from 81,220 in 2011 to 377,651 in 2019. Medical costs per patient with PD increased from 1,686 United States dollars (USD) in 2011 to 3,202 USD in 2020. The medical expenses for each patient with PD receiving PT increased from 6,582 USD in 2011 to 13,475 USD in 2020. Moreover, regular PTs were administered to 31,782 patients (18.74%) and were administered only through hospitalization. Those patients in their 50s with disabilities demonstrated a high OR for regular PTs, whereas those aged 80 years or older and residing outside of Seoul had a low OR.

CONCLUSION

The PD burden increased in South Korea between 2011 and 2020, as did health care utilization and medical costs. A significant increase in medical expenses can be associated with increased PD incidence and PT interventions. Regular PT applications remain restricted and have barriers to access.

Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics

Neurodegenerative conditions significantly impact patient quality of life. Many conditions do not have a cure, but with appropriate and timely treatment the advance of the disease could be diminished. However, many patients only seek a diagnosis once the condition progresses to a point at which the quality of life is significantly impacted. Effective non-invasive and readily accessible methods for early diagnosis can considerably enhance the quality of life of patients affected by neurodegenerative conditions. This work explores the potential of convolutional neural networks (CNNs) for patient gain freezing associated with Parkinson's disease. Sensor data collected from wearable gyroscopes located at the sole of the patient's shoe record walking patterns. These patterns are further analyzed using convolutional networks to accurately detect abnormal walking patterns. The suggested method is assessed on a public real-world dataset collected from parents affected by Parkinson's as well as individuals from a control group. To improve the accuracy of the classification, an altered variant of the recent crayfish optimization algorithm is introduced and compared to contemporary optimization metaheuristics. Our findings reveal that the modified algorithm (MSCHO) significantly outperforms other methods in accuracy, demonstrated by low error rates and high Cohen's Kappa, precision, sensitivity, and F1-measures across three datasets. These results suggest the potential of CNNs, combined with advanced optimization techniques, for early, non-invasive diagnosis of neurodegenerative conditions, offering a path to improve patient quality of life.

Diagnostic windows in non-neoplastic diseases: a systematic review

BACKGROUND

Investigating changes in prediagnostic healthcare utilisation can help identify how much earlier conditions could be diagnosed. Such 'diagnostic windows' are established for cancer but remain relatively unexplored for non-neoplastic conditions.

AIM

To extract evidence on the presence and length of diagnostic windows for non-neoplastic conditions.

DESIGN AND SETTING

A systematic review of studies of prediagnostic healthcare utilisation was carried out.

METHOD

A search strategy was developed to identify relevant studies from PubMed and Connected Papers. Data were extracted on prediagnostic healthcare use, and evidence of diagnostic window presence and length was assessed.

RESULTS

Of 4340 studies screened, 27 were included, covering 17 non-neoplastic conditions, including both chronic (for example, Parkinson's disease) and acute conditions (for example, stroke). Prediagnostic healthcare events included primary care encounters and presentations with relevant symptoms. For 10 conditions, sufficient evidence to determine diagnostic window presence and length was available, ranging from 28 days (herpes simplex encephalitis) to 9 years (ulcerative colitis). For the remaining conditions, diagnostic windows were likely to be present, but insufficient study duration was often a barrier to robustly determining their length, meaning that diagnostic window length may exceed 10 years for coeliac disease, for example.

CONCLUSION

Evidence of changing healthcare use before diagnosis exists for many non-neoplastic conditions, establishing that early diagnosis is possible, in principle. In particular, some conditions may be detectable many years earlier than they are currently diagnosed. Further research is required to accurately estimate diagnostic windows and to determine how much earlier diagnosis may be possible, and how this might be achieved.

Objective measurement versus clinician-based assessment for Parkinson's disease

INTRODUCTION

Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients.

AREAS COVERED

The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management.

EXPERT OPINION

In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.

Causes, factors, and complications associated with hospital admissions among patients with Parkinson's disease

Introduction

Patients with Parkinson's disease (PD) are at a higher risk of hospital admissions compared to the general population. We studied the causes and factors associated with admissions among patients with PD over 6 years.

Methods

We included all PD admissions between 1 January 2016 and 31 December 2021. Other causes of parkinsonism were excluded. Causes of admissions were divided into PD-related (direct or indirect) or non-PD-related. The type of admission was categorized into emergency or elective.

Results

We identified 605 hospital admissions (259 patients with PD); 345 (57.0%) were PD-related and 260 (43%) were non-PD-related. Emergency PD admissions contributed to 50.4% of all admissions, most commonly from respiratory infection (23%). PD admissions in comparison to non-PD admissions were associated with worse disease severity (HY ≥ 3; p < 0.001), longer disease duration [8.71 (SD 6.23) vs. 6.60 (SD 5.39) years; p < 0.001], and longer hospital stay [7.70 (SD 5.89) vs. 6.42 (SD 7.63) days; p = 0.020]. Non-PD admissions were associated with more comorbidities (97.3%; p = 0.013). There were 124 (20.5%) complications and 31 deaths (5.1%). A total of 29 deaths were due to respiratory infection and 3 deaths were due to COVID-19 pneumonia. Emergency admission (PD- and non-PD-related; p = 0.001) and respiratory-related causes (p < 0.001) were predictors of unfavorable hospital admission outcomes (death and complications).

Conclusion

Respiratory infection was the leading cause of hospital admission and a significant independent predictor of unfavorable hospital admission outcomes (death and complications). PD-related admissions were associated with disease severity and led to more complications and longer hospital stays. Non-PD-related admissions were associated with comorbidities.