Primary health care : open access最新文献

{"title":"Depression and Health Risk Behaviors: Towards Optimizing Primary Care Service Strategies for Addressing Risk.","authors":"Joan Rosenbaum Asarnow,&nbsp;Luis Roberto Zeledon,&nbsp;Elizabeth D'Amico,&nbsp;Anne LaBorde,&nbsp;Martin Anderson,&nbsp;Claudia Avina,&nbsp;Talin Arslanian,&nbsp;Minh-Chau Do,&nbsp;Jessica Harwood,&nbsp;Steven Shoptaw","doi":"10.4172/2167-1079.1000152","DOIUrl":"https://doi.org/10.4172/2167-1079.1000152","url":null,"abstract":"<p><strong>Purpose: </strong>Depression and health risk behaviors in adolescents are leading causes of preventable morbidity and mortality. Primary care visits provide prime opportunities to screen and provide preventive services addressing risk behaviors/conditions. This study evaluated the co-occurrence of depression and health risk behaviors (focusing on smoking, drug and alcohol misuse, risky sexual behavior, and obesity-risk) with the goal of informing preventive service strategies.</p><p><strong>Methods: </strong>Consecutive primary care patients (n=217), ages 13 to 18 years, selected to over-sample for depression, completed a Health Risk Behavior Survey and the Diagnostic Interview Schedule for Children and Adolescents (DISC) depression module.</p><p><strong>Results: </strong>Youths with DISC-defined past-year depression were significantly more likely to report risk across multiple risk-areas, Wald X²(1)=14.39, p<.001, and to have significantly higher rates of past-month smoking, X²(1)=5.86, p=.02, substance misuse, X²(1)=15.12, p<.001, risky sex, X² (1) =5.04, p=.03, but not obesity-risk, X² (1) =0.19, p=.66. Cross-sectional predictors of risk behaviors across risk areas were similar. Statistically significant predictors across all risk domains included: youths' expectancies about future risk behavior; attitudes regarding the risk behavior; and risk behaviors in peers/others in their environments.</p><p><strong>Conclusions: </strong>Depression in adolescents is associated with a cluster of health risk behaviors that likely contribute to the high morbidity and mortality associated with both depression and health risk behaviors. Consistent with the United States National Prevention Strategy (2011) and the focus on integrated behavioral and medical health care, results suggest the value of screening and preventive services using combination strategies that target depression and multiple areas of associated health risk.</p>","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"4 1","pages":"152"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2167-1079.1000152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32741610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing Web-based with Mail Survey Administration of the Consumer Assessment of Healthcare Providers and Systems (CAHPS^®) Clinician and Group Survey.","authors":"Steven C Bergeson,&nbsp;Janiece Gray,&nbsp;Lynn A Ehrmantraut,&nbsp;Tracy Laibson,&nbsp;Ron D Hays","doi":"10.4172/2167-1079.1000132","DOIUrl":"https://doi.org/10.4172/2167-1079.1000132","url":null,"abstract":"<p><strong>Context: </strong>The CAHPS^® survey instruments are widely used to assess patient experiences with care but there is limited information about web-based data collection with them.</p><p><strong>Objective: </strong>To compare web-based data collection with standard mail survey mode of collection of CAHPS^® Clinician and Group survey data.</p><p><strong>Design setting and patients: </strong>We randomized mode of data collection (web versus mail) of the CAHPS^® Clinician and Group Survey to patients who had visited one of six clinics over a four-month period in Minnesota. A total of 410 patients responded to the web-based survey (14% response rate) and 982 patients responded to the mail survey (33% response rate).</p><p><strong>Main outcome measures: </strong>Responses to CAHPS^® survey dimensions and individual question responses, response rates, and participant characteristics.</p><p><strong>Results: </strong>There were no significant differences in CAHPS^® survey composites and individual question responses by mode, except for those addressing access. Those responding via the web reported less positive experiences with access to an appointment for urgent care as soon as needed, getting an appointment for routine care as soon as needed, getting answers to medical questions as soon as needed, and follow-up on test results (t's=-3.64, -7.15, -2.58, -2.23; p's=0.0003, <0.0001, 0.01, 0.03, respectively). Web respondents had more positive experiences about office wait time for the most recent visit (t = 2.32, p=0.021). Those who participated in the study tended to be older than those that did not (ƛ²=247.51, df=8, p<0.0001 for mail; ƛ²= 4.56, df=8, p<0.0001 for the web). Females were significantly more likely than males to respond to the survey overall (24% vs. 18%, ƛ²=6.45, 1 df, p=0.011) and relatively more likely than males to respond to web (15% vs. 13%, ƛ²=1.32, 1 df, p=0.25) than mail (34% vs. 30%, ƛ²=5.42, 1 df, p=0.02). Mail respondents were more likely than web respondents to be male (28% versus 18%, ƛ²=16.27, 1 df, p<0.0001) and older (27% of the mail respondents and 19% of the web respondents were 65 or older, ƛ²=10.88, 1 df, p=0.001). Costs of web-based surveys were less than mailed surveys and were returned more quickly than mailed surveys. The correlations between reports and ratings of clinicians and clinics by mode were unreliable because of the relatively small number of web responses.</p><p><strong>Conclusion: </strong>Web-based surveys yielded comparable results to mail (except for questions addressing access) more quickly at lower costs. The low response rates in this study are a concern although this was not intended as a test of increasing response rates. Strategies to increase response rates will be a key element of web-based data collection. The differences in costs will be an incentive for o","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2167-1079.1000132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31769345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age-related Differential Item Functioning for the Patient-Reported Outcomes Information System (PROMIS®) Physical Functioning Items.","authors":"Sylvia H Paz,&nbsp;Karen L Spritzer,&nbsp;Leo S Morales,&nbsp;Ron D Hays","doi":"10.4172/2167-1079.1000131","DOIUrl":"https://doi.org/10.4172/2167-1079.1000131","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the equivalence of the PROMIS® wave 1 physical functioning item bank, by age (50 years or older versus 18-49).</p><p><strong>Materials and methods: </strong>A total of 114 physical functioning items with 5 response choices were administered to English- (n=1504) and Spanish-language (n=640) adults. Item frequencies, means and standard deviations, item-scale correlations, and internal consistency reliability were estimated. Differential Item Functioning (DIF) by age was evaluated.</p><p><strong>Results: </strong>Thirty of the 114 items were fagged for DIF based on an R-squared of 0.02 or above criterion. The expected total score was higher for those respondents who were 18-49 than those who were 50 or older.</p><p><strong>Conclusions: </strong>Those who were 50 years or older versus 18-49 years old with the same level of physical functioning responded differently to 30 of the 114 items in the PROMIS® physical functioning item bank. This study yields essential information about the equivalence of the physical functioning items in older versus younger individuals.</p>","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"3 131","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2167-1079.1000131","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31748293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Academic-Industry Collaboration to Develop an EHR Module for Primary Care.","authors":"Jacqueline Halladay,&nbsp;Christopher M Shea,&nbsp;David Reed,&nbsp;Timothy P Daaleman","doi":"10.4172/phcoa.1000111","DOIUrl":"https://doi.org/10.4172/phcoa.1000111","url":null,"abstract":"","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"2 111","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3771108/pdf/nihms481822.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31736393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Academic-Industry Collaboration to Develop an EHR Module for Primary Care.","authors":"Jacqueline R. Halladay, C. Shea, David Reed, T. Daaleman","doi":"10.4172/2167-1079.1000111","DOIUrl":"https://doi.org/10.4172/2167-1079.1000111","url":null,"abstract":"Introduction:By forging partnerships among academia, industry and other stakeholders in health care IT, it is hoped that more user-friendly and efficient HIT solutions will become available soon. Although this shared stakeholders approach appears effective and synergistic, there has been minimal prior work that describes such collaborations.Understanding this collaboration is particularly important due to the different perspectives and priorities of academic and commercial stakeholders. In this report we share our collaborative experience of developing and delivering the Geriatric Enhancement Module (GEM), a software application comprised of a 7-item questionnaire designed to generate discussions among staff, providers and patients regarding quality of life issues. \u0000Methods:Our academic-industry collaborators worked cooperatively to select and recruit three practices for the study, iteratively developed the GEM questions and available responses, and devised the method of delivering the questions within our pilot practices by participating jointly in a series of face to face meetings and conference calls during 12 months out of the two year study period. \u0000Findings: One of the most important lessons learned is that despite the vendor’s computer programming aimed at delivering the module in a specific way for a particular set of patients, practices figured out ways to control the delivery of the module or tailor it for their own purposes in ways that certain automated features, such as “popping” up for all patients aged 50 or over, were not being used in the way that the vendor had thought. Therefore, we experimented with free-text software as an alternative method for delivery.","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"181 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73168716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using the Electronic Medical Record to Examine Racial and Ethnic Differences in Depression Diagnosis and Treatment in a Primary Care Population.","authors":"Nhi-Ha T Trinh, Rachel Larocca, Susan Regan, Trina E Chang, Stephen E Gilman, Maurizio Fava, Albert Yeung","doi":"10.4172/2167-1079.1000106","DOIUrl":"10.4172/2167-1079.1000106","url":null,"abstract":"<p><strong>Objective: </strong>We assessed racial and ethnic differences in depression diagnosis and treatment in a primary care population.</p><p><strong>Methods: </strong>A sample of primary care outpatients in 2007 was generated using the electronic medical record (EMR). Patients were considered depressed if their providers billed for depression-related codes; they were considered prescribed antidepressants if any antidepressants were on their medication list. Rates of diagnosis and medication prescription were estimated using a generalized linear model with a Poisson distribution, adjusting for covariates.</p><p><strong>Results: </strong>In the resulting sample (n=85,790), all minority groups were less likely to be diagnosed with depression as compared to Whites (p<0.05); 11.36% of Whites had a depression diagnosis, as compared to 6.44% of Asian Americans, 7.55% of African Americans, and 10.18% of Latino Americans. Among those with a depression diagnosis (n=11,096), 54.07% of African Americans were prescribed antidepressant medications, as compared to 63.19% Whites (p<0.05); Asian Americans and Latino Americans showed a trend of being less likely to be prescribed antidepressant medications.</p><p><strong>Conclusions: </strong>Our study illustrates differences in diagnosis and treatment for minority primary care patients, and is innovative in using the EMR to probe these differences. Further research is needed to understand the underlying reasons for these observed differences.</p>","PeriodicalId":90040,"journal":{"name":"Primary health care : open access","volume":"1 ","pages":"1000106"},"PeriodicalIF":0.0,"publicationDate":"2012-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32115583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}