Health Perceptions of Primary Care Patients and the Influence on Health Care Utilization

Medical Care ◽  
1989 ◽  
Vol 27 (Supplement) ◽  
pp. S99-S109 ◽  
Author(s):  
Julia E. Connelly ◽  
John T. Philbrick ◽  
G Richard Smith ◽  
Donald L. Kaiser ◽  
Antoinette Wymer
2008 ◽  
Vol 21 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Melissa A. Polusny ◽  
Barry J. Ries ◽  
Jessica R. Schultz ◽  
Patrick Calhoun ◽  
Lisa Clemensen ◽  
...  

1997 ◽  
Vol 42 (9) ◽  
pp. 966-973 ◽  
Author(s):  
Michael S Klinkman ◽  
Thomas L Schwenk ◽  
James C Coyne

Objective: To explore the relationships between detection, treatment, and outcome of depression in the primary care setting, based upon results from the Michigan Depression Project (MDP). Methods: A weighted sample of 425 adult family practice patients completed a comprehensive battery of questionnaires exploring stress, social support, overall health, health care utilization, treatment attitudes, self-rated levels of stress and depression, along with the Center for Epidemiologic Studies Depression Scale (CES-D), the Hamilton Rating Scale for Depression (HAM-D), and the Structured Clinical Interview for DSM-III (SCID), which served as the criterion standard for diagnosis. A comparison sample of 123 depressed psychiatric outpatients received the same assessment battery. Family practice patients received repeated assessment of depressive symptoms, stress, social support, and health care utilization over a period of up to 60 months of longitudinal follow-up. Results: The central MDP findings confirm that significant differences in past history, severity, and impairment exist between depressed psychiatric and family practice patients, that detection rates are significantly higher for severely depressed primary care patients, and that clinicians use clinical cues such as past history, distress, and severity of symptoms to “detect” depression in patients at intermediate and mild levels of severity. As well, there is a lack of association between detection and improved outcome in primary care patients. Conclusion: These results call into question the assumption that “depression is depression” irrespective of the setting and physician, and they are consistent with a model of depressive disorder as a subacute or chronic condition characterized by clinical parameters of severity, staging, and comorbidity, similar to asthma. This new model can guide further investigation into the epidemiology and management of mood disorders in the primary care setting.


2021 ◽  
Vol 8 (3) ◽  
pp. 239-247
Author(s):  
Tamara K Oser ◽  
Siddhartha Roy ◽  
Jessica Parascando ◽  
Rebecca Mullen ◽  
Julie Radico ◽  
...  

2001 ◽  
Vol 28 (4) ◽  
pp. 378-399 ◽  
Author(s):  
Michael R. Polen ◽  
Carla A. Green ◽  
Donald K. Freeborn ◽  
John P. Mullooly ◽  
Frances Lynch

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
E. Rydwik ◽  
R. Lindqvist ◽  
C. Willers ◽  
L. Carlsson ◽  
G. H. Nilsson ◽  
...  

Abstract Background This study is the first part of a register-based research program with the overall aim to increase the knowledge of the health status among geriatric patients and to identify risk factors for readmission in this population. The aim of this study was two-fold: 1) to evaluate the validity of the study cohorts in terms of health care utilization in relation to regional cohorts; 2) to describe the study cohorts in terms of health status and health care utilization after discharge. Methods The project consist of two cohorts with data from patient records of geriatric in-hospital stays, health care utilization data from Stockholm Regional Healthcare Data Warehouse 6 months after discharge, socioeconomic data from Statistics Sweden. The 2012 cohort include 6710 patients and the 2016 cohort, 8091 patients; 64% are women, mean age is 84 (SD 8). Results Mean days to first visit in primary care was 12 (23) and 10 (19) in the 2012 and 2016 cohort, respectively. Readmissions to hospital was 38% in 2012 and 39% in 2016. The validity of the study cohorts was evaluated by comparing them with regional cohorts. The study cohorts were comparable in most cases but there were some significant differences between the study cohorts and the regional cohorts, especially regarding amount and type of primary care. Conclusion The study cohorts seem valid in terms of health care utilization compared to the regional cohorts regarding hospital care, but less so regarding primary care. This will be considered in the analyses and when interpreting data in future studies based on these study cohorts. Future studies will explore factors associated with health status and re-admissions in a population with multi-morbidity and disability.


2022 ◽  
Vol 2 (1) ◽  
pp. es0358
Author(s):  
Daphne Hui ◽  
Bert Dolcine ◽  
Hannah Loshak

A literature search informed this Environmental Scan and identified 11 evaluations of virtual care in primary care health settings and 7 publications alluding to methods, standards, and guidelines (referred to as evaluation guidance documents in this report) being used in various countries to evaluate virtual care in primary care health settings. The majority of included literature was from Australia, the US, and the UK, with 2 evaluation guidance documents published by the Heart and Stroke Foundation of Canada. Evaluation guidance documents recommended using measurements that assess the effectiveness and quality of clinical care including safety outcomes, time and travel, financial and operational impact, participation, health care utilization, technology experience including feasibility, user satisfaction, and barriers and facilitators or measures of health equity. Evaluation guidance documents specified that the following key decisions and considerations should be integrated into the planning of a virtual care evaluation: refining the scope of virtual care services; selecting an appropriate meaningful comparator; and identifying opportune timing and duration for the evaluation to ensure the evaluation is reflective of real-world practice, allows for adequate measurement of outcomes, and is comprehensive, timely, feasible, non-complex, and non–resource-intensive. Evaluation guidance documents highlighted that evaluations should be systematic, performed regularly, and reflect the stage of virtual care implementation to encompass the specific considerations associated with each stage. Additionally, evaluations should assess individual virtual care sessions and the virtual care program as a whole. Regarding economic components of virtual care evaluations, the evaluation guidance documents noted that costs or savings are not limited to monetary or financial measures but can also be represented with time. Cost analyses such as cost-benefit and cost-utility estimates should be performed with a specific emphasis on selecting an appropriate perspective (e.g., patient or provider), as that influences the benefits, effects, and how the outcome is interpreted. Two identified evaluations assessed economic outcomes through cost analyses in the perspective of the patient and provider. Evidence suggests that, in some circumstances, virtual care may be more cost-effective and reduces the cost per episode and patient expenses (e.g., travel and parking costs) compared to in-person care. However, virtual care may increase the number of individuals treated, which would increase overall health care spending. Four identified evaluations assessed health care utilization. The evidence suggests that virtual care reduces the duration of appointments and may be more time-efficient compared to in-person care. However, it is unclear if virtual care reduces the use of medical resources and the need for follow-up appointments, hospital admissions, and emergency department visits compared to in-person care. Five identified evaluations assessed participation outcomes. Evidence was variable, with some evidence reporting that virtual care reduced attendance (e.g., reduced attendance rates) and other evidence noting improved attendance (e.g., increased completion rate and decreased cancellations and no-show rates) compared to in-person care. Three identified evaluations assessed clinical outcomes in various health contexts. Some evidence suggested that virtual care improves clinical outcomes (e.g., in primary care with integrated mental health services, symptom severity decreased) or has a similar effect on clinical outcomes compared to in-person care (e.g., use of virtual care in depression elicited similar results with in-person care). Three identified evaluations assessed the appropriateness of prescribing. Some studies suggested that virtual care improves appropriateness by increasing guideline-based or guideline-concordant antibiotic management, or elicits no difference with in-person care.


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