Lithuanian
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
JMIR public health and surveillance 2020-Jan

Medical Conditions Predictive of Self-Reported Poor Health: Retrospective Cohort Study.

Straipsnius versti gali tik registruoti vartotojai
Prisijungti Registracija
Nuoroda įrašoma į mainų sritį
M Cepeda
Jenna Reps
David Kern
Paul Stang

Raktažodžiai

Santrauka

Identifying the medical conditions that are associated with poor health is crucial to prioritize decisions for future research and organizing care. However, assessing the burden of disease in the general population is complex, lengthy, and expensive. Claims databases that include self-reported health status can be used to assess the impact of medical conditions on the health in a population.This study aimed to identify medical conditions that are highly predictive of poor health status using claims databases.To determine the medical conditions most highly predictive of poor health status, we used a retrospective cohort study using 2 US claims databases. Subjects were commercially insured patients. Health status was measured using a self-report health status response. All medical conditions were included in a least absolute shrinkage and selection operator regression model to assess which conditions were associated with poor versus excellent health.A total of 1,186,871 subjects were included; 61.64% (731,587/1,186,871) reported having excellent or very good health. The leading medical conditions associated with poor health were cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), sleep disorders, seizures, male reproductive tract infections, chronic obstructive pulmonary disease, cardiomyopathy, dementia, and headaches.Understanding the impact of disease in a commercially insured population is critical to identify subjects who may be at risk for reduced productivity and job loss. Claims database studies can measure the impact of medical conditions on the health status in a population and to assess changes overtime and could limit the need to collect prospective collection of information, which is slow and expensive, to assess disease burden. Leading medical conditions associated with poor health in a commercially insured population were the ones associated with high burden of disease such as cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), infections, chronic obstructive pulmonary disease, cardiomyopathy, and dementia. However, sleep disorders, seizures, male reproductive tract infections, and headaches were also part of the leading medical conditions associated with poor health that had not been identified before as being associated with poor health and deserve more attention.

Prisijunkite prie mūsų
„Facebook“ puslapio

Išsamiausia vaistinių žolelių duomenų bazė, paremta mokslu

  • Dirba 55 kalbomis
  • Žolelių gydymas, paremtas mokslu
  • Vaistažolių atpažinimas pagal vaizdą
  • Interaktyvus GPS žemėlapis - pažymėkite vaistažoles vietoje (netrukus)
  • Skaitykite mokslines publikacijas, susijusias su jūsų paieška
  • Ieškokite vaistinių žolelių pagal jų poveikį
  • Susitvarkykite savo interesus ir sekite naujienas, klinikinius tyrimus ir patentus

Įveskite simptomą ar ligą ir perskaitykite apie žoleles, kurios gali padėti, įveskite žolę ir pamatykite ligas bei simptomus, nuo kurių ji naudojama.
* Visa informacija pagrįsta paskelbtais moksliniais tyrimais

Google Play badgeApp Store badge