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Analysis of factors influencing the frequency of primary care visits among diabetic patients in two provinces in China.

ABSTRACT: BACKGROUND:Community health services have played an important role in the prevention and control of diabetes in China. The aims of this study were to examine the frequency of visits to community clinics for diabetic care services, to assess factors correlated with infrequent primary care visits and to identify barriers to regular follow-up visits for urban and rural patients. METHODS:Between October 2014 and November 2014, data were collected from 17 communities in two cities and four townships located in Shandong and Jiangsu Provinces in China. A total of 1598 diabetic patients aged 18?years or older who were registered with a primary health station in local communities were selected by simple random sampling. Each participant was required to complete an interviewer-led questionnaire. Univariate and multivariate analyses were used to identify significant factors for infrequent visitor status using multivariable logistic regression analysis. RESULTS:After being clearly informed of the study protocol, 1508/1598 (94.4%) patients agreed to participate in this survey. Among the 1508 subjects (mean age 64.4?±?10.6), 683 (45.3%) were classified as infrequent visitors. The following were significant factors determining infrequent visitor status: urban residence, lack of health insurance, per-capita household income

SUBMITTER: Wang J

PROVIDER: S-EPMC6743148 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Analysis of factors influencing the frequency of primary care visits among diabetic patients in two provinces in China.

Wang Jinwen J Zuo Huijuan H Chen Xiaorong X Hou Lei L Ma Jixiang J

BMC public health 20190913 1

<h4>Background</h4>Community health services have played an important role in the prevention and control of diabetes in China. The aims of this study were to examine the frequency of visits to community clinics for diabetic care services, to assess factors correlated with infrequent primary care visits and to identify barriers to regular follow-up visits for urban and rural patients.<h4>Methods</h4>Between October 2014 and November 2014, data were collected from 17 communities in two cities and ...[more]

PMID: 31519162

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Project description:ImportanceMaintaining a healthy physician workforce includes the routine use of primary care physician (PCP) services; however, physicians may face barriers to attaining formal care.ObjectiveTo analyze access to and frequency of visits to PCPs among physicians compared with nonphysicians.Design, setting, and participantsThis population-based, retrospective cohort study used registration data from the College of Physicians and Surgeons of Ontario, Canada, from January 1, 1990, to March 31, 2018. Data for all newly practicing physicians as of March 31, 2018, were linked to Ontario health administrative databases. Data were analyzed from August 25, 2020, to August 6, 2021.Main outcomes and measuresThe main outcomes were enrollment in a PCP practice and visits with a PCP. Generalized estimating equations compared primary care visits between physicians and nonphysicians, matched 1:5 based on age, sex, neighborhood income quintile, and health region.ResultsAmong 19 581 physicians (mean [SD] age, 43.99 [8.94] years; 53.27% male) matched to 97 905 nonphysicians, physicians were less likely to be enrolled with a PCP than were nonphysicians (81.8% vs 86.4%; absolute difference, 4.6%; adjusted odds ratio [OR], 0.75; 95% CI, 0.72-0.79) and had fewer primary care visits during the preceding 2 years (median [IQR], 2 [0-4] vs 4 [1-7]; adjusted relative rate ratio [RRR], 0.59; 95% CI, 0.58-0.60). Physicians aged 40 years or older and male physicians were less likely to be rostered (ages 40-44 years: OR, 0.70 [95% CI, 0.64-0.77]; male: OR, 0.60 [95% CI, 0.57-0.63]) and more likely to have a lower frequency of PCP visits (ages 40-44 years: RRR, 0.53 [95% CI, 0.51-0.56]; male: RRR, 0.50 [95% CI, 0.50-0.51]) compared with nonphysicians.Conclusions and relevanceIn this retrospective cohort study, enrollment with a PCP practice and frequency of visits were lower among physicians compared with a matched general population of nonphysicians. Individual, system, and medical cultural factors associated with these results need to be better understood so that physicians can take better care of themselves and their patients.

Project description:BackgroundDengue fever (DF) is a common mosquito-borne viral infectious disease in the world, and increasingly severe DF epidemics in China have seriously affected people's health in recent years. Thus, investigating spatiotemporal patterns and potential influencing factors of DF epidemics in typical regions is critical to consolidate effective prevention and control measures for these regional epidemics.MethodsA generalized additive model (GAM) was used to identify potential contributing factors that influence spatiotemporal epidemic patterns in typical DF epidemic regions of China (e.g., the Pearl River Delta [PRD] and the Border of Yunnan and Myanmar [BYM]). In terms of influencing factors, environmental factors including the normalized difference vegetation index (NDVI), temperature, precipitation, and humidity, in conjunction with socioeconomic factors, such as population density (Pop), road density, land-use, and gross domestic product, were employed.ResultsDF epidemics in the PRD and BYM exhibit prominent spatial variations at 4 km and 3 km grid scales, characterized by significant spatial clustering over the Guangzhou-Foshan, Dehong, and Xishuangbanna areas. The GAM that integrated the Pop-urban land ratio (ULR)-NDVI-humidity-temperature factors for the PRD and the ULR-Road density-NDVI-temperature-water land ratio-precipitation factors for the BYM performed well in terms of overall accuracy, with Akaike Information Criterion values of 61 859.89 and 826.65, explaining a total variance of 83.4 and 97.3%, respectively. As indicated, socioeconomic factors have a stronger influence on DF epidemics than environmental factors in the study area. Among these factors, Pop (PRD) and ULR (BYM) were the socioeconomic factors explaining the largest variance in regional epidemics, whereas NDVI was the environmental factor explaining the largest variance in both regions. In addition, the common factors (ULR, NDVI, and temperature) in these two regions exhibited different effects on regional epidemics.ConclusionsThe spatiotemporal patterns of DF in the PRD and BYM are influenced by environmental and socioeconomic factors, the socioeconomic factors may play a significant role in DF epidemics in cases where environmental factors are suitable and differ only slightly throughout an area. Thus, prevention and control resources should be fully allocated by referring to the spatial patterns of primary influencing factors to better consolidate the prevention and control measures for DF epidemics.

Project description:BackgroundPrimary care practitioners (PCPs) play a key role in cancer screening decisions for older adults (≥ 65 years), but recommendations vary by cancer type and jurisdiction.PurposeTo examine the factors influencing PCPs' recommendations for breast, cervical, prostate, and colorectal cancer screening for older adults.Data sourcesMEDLINE, Pre-Medline, EMBASE, PsycINFO, and CINAHL, searched from 1 January 2000 to July 2021, and citation searching in July 2022.Study selectionAssessed factors influencing PCPs' breast, prostate, colorectal, or cervical cancer screening decisions for older adults' (defined either as ≥ 65 years or < 10-year life expectancy).Data extractionTwo authors independently conducted data extraction and quality appraisal. Decisions were crosschecked and discussed where necessary.Data synthesisFrom 1926 records, 30 studies met inclusion criteria. Twenty were quantitative, nine were qualitative, and one used a mixed method design. Twenty-nine were conducted in the USA, and one in the UK. Factors were synthesized into six categories: patient demographic characteristics, patient health characteristics, patient and clinician psycho-social factors, clinician characteristics, and health system factors. Patient preference was most reported as influential across both quantitative and qualitative studies. Age, health status, and life expectancy were also commonly influential, but PCPs held nuanced views about life expectancy. Weighing benefits/harms was also commonly reported with variation across cancer screening types. Other factors included patient screening history, clinician attitudes/personal experiences, patient/provider relationship, guidelines, reminders, and time.LimitationsWe could not conduct a meta-analysis due to variability in study designs and measurement. The vast majority of included studies were conducted in the USA.ConclusionsAlthough PCPs play a role in individualizing cancer screening for older adults, multi-level interventions are needed to improve these decisions. Decision support should continue to be developed and implemented to support informed choice for older adults and assist PCPs to consistently provide evidence-based recommendations.RegistrationPROSPERO CRD42021268219.Funding sourceNHMRC APP1113532.

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Analysis of factors influencing the frequency of primary care visits among diabetic patients in two provinces in China.

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Analysis of factors influencing the frequency of primary care visits among diabetic patients in two provinces in China.

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