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Related Concept Videos

Parkinson's Disease: Overview01:15

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Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is...
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Neurodegenerative disorders, such as Parkinson's Disease (PD), involve the gradual and irreversible destruction of neurons in particular brain areas. These disorders exhibit standard features like proteinopathies, selective vulnerability of some neurons, and an interaction of intrinsic properties, genetics, and environmental influences in neural injury.
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The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study.

Brett J Peterson1, Walter A Rocca1,2, James H Bower2

  • 1Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Clinical Parkinsonism & Related Disorders
|June 24, 2021
PubMed
Summary

Using administrative diagnostic codes alone to identify Parkinson's disease (PD) cases over-counts incidence by 73% and is not recommended. Further research is needed for accurate PD case-finding algorithms.

Keywords:
Diagnostic codeHealth administrative dataIncidenceParkinson’s diseaseValidation

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Area of Science:

  • Neurology
  • Epidemiology
  • Health Informatics

Background:

  • Administrative databases with diagnostic codes offer cost-effective research data.
  • Validating diagnostic codes for disease identification is crucial for research integrity.

Purpose of the Study:

  • To assess the accuracy of using administrative diagnostic codes for identifying incident Parkinson's disease (PD) cases.
  • To compare diagnostic code-based case ascertainment with a gold standard clinical diagnosis.

Main Methods:

  • Incident PD cases were identified using administrative diagnostic codes from the Rochester Epidemiology Project (REP).
  • A standard clinical diagnosis by movement disorder specialists, based on medical record review, served as the comparison.
  • Validity was measured using positive predictive value (PPV) and sensitivity.

Main Results:

  • The diagnostic code method over-counted incident PD cases by 73% (804 vs. 464).
  • Sensitivity was 80% (95% CI [76%, 84%]), but positive predictive value (PPV) was only 46% (95% CI [34%, 50%]).
  • Misclassification, including non-PD or parkinsonism diagnoses, accounted for two-thirds of falsely identified cases.

Conclusions:

  • Reliance solely on administrative diagnostic codes is not recommended for identifying incident PD cases in this setting.
  • The current method significantly overestimates PD incidence and trends.
  • Development of more accurate algorithms is necessary for valid research using diagnostic codes.