Telemedicine, the effect of nurse-initiated telephone follow up, on health status and health-care utilization in COPD patients: A randomized trial

Respirology ◽  
2014 ◽  
Vol 20 (2) ◽  
pp. 279-285 ◽  
Author(s):  
Farida F. Berkhof ◽  
Jan W.K. van den Berg ◽  
Steven M. Uil ◽  
Huib A.M. Kerstjens
Keyword(s):  
Health Care ◽  
Health Status ◽  
Health Care Utilization ◽  
Randomized Trial ◽  
Care Utilization ◽  
Copd Patients

scholarly journals Associations Between Engagement With an Online Health Community and Changes in Patient Activation and Health Care Utilization: Longitudinal Web-Based Survey

10.2196/13477 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e13477 ◽  
Author(s):  
Ruth E Costello ◽  
Amrutha Anand ◽  
Matt Jameson Evans ◽  
William G Dixon
Keyword(s):  
Health Care ◽  
Health Status ◽  
Health Care Utilization ◽  
Patient Activation ◽  
Care Utilization ◽  
Chi Square ◽  
Web Based ◽  
Health Communities ◽  
Very High

Background Participation in online health communities (OHCs) is a popular trend in the United Kingdom. However, so far, no evidence exists to indicate an association between participation in OHCs and improved health outcomes. Objective This study aimed to (1) determine changes in patient activation over 3 months in new users of an OHC, (2) describe patterns of engagement with an OHC, (3) examine whether patients’ characteristics at baseline were associated with subsequent patterns of engagement, and (4) determine if patterns of engagement during the 3 months were associated with changes in patient activation, health care utilization, and health status. Methods Active new OHC users on HealthUnlocked (HU) were surveyed to measure demographics, levels of patient activation (describing a person’s confidence in managing their own health; scale 0-100 with 4 categories), health care utilization, and health status using a Web-based survey at baseline and 3 months. Patient activation at baseline and 3 months was compared (aim 1). Alongside, for a sample of HU users and survey responders, daily OHC website usage data were automatically captured. This was used to identify clusters of engagement with HU (aim 2). For survey responders, baseline characteristics, patient activation, health care utilization, and health status were compared at baseline and 3 months, overall, and between engagement clusters using t tests and chi-square tests (aims 3 and 4). Results In 329 people who completed both surveys, baseline activation was most frequently level 3, described as taking action but still lacking confidence. At follow-up, a change of 2.6 points was seen, with the greatest change seen in those at lowest baseline activation levels. In addition, 4 clusters of engagement were identified: low, medium, high, and very high, who were active on HU for a mean of 4, 12, 29, and 59 days, respectively. Survey responders were more commonly high or very high engagers. Baseline activation was highest in low and very high engagers. Overall activation increased over time in all engagement groups. Very high engagers had the greatest improvement in activation (5 points), although the average change was not above what is considered clinically meaningful for any group. Fewer accident and emergency visits were seen at follow-up in those with higher engagement, although this trend was not seen for other health care utilization measures. There was no change in health status at 3 months. Conclusions This observational study provides some insight into how patterns of engagement with OHCs are associated with changes in patient activation, health care utilization, and health status. Over 3 months, overall, the change in activation was not clinically significant, and there were some indications that OHCs may be of benefit to particular groups. However, the study limitations prevent firm conclusions about causal relationships.

scholarly journals Associations Between Engagement With an Online Health Community and Changes in Patient Activation and Health Care Utilization: Longitudinal Web-Based Survey (Preprint)

2019 ◽  
Author(s):  
Ruth E Costello ◽  
Amrutha Anand ◽  
Matt Jameson Evans ◽  
William G Dixon
Keyword(s):  
Health Care ◽  
Health Status ◽  
Health Care Utilization ◽  
Patient Activation ◽  
Care Utilization ◽  
Chi Square ◽  
Web Based ◽  
Health Communities ◽  
Very High

BACKGROUND Participation in online health communities (OHCs) is a popular trend in the United Kingdom. However, so far, no evidence exists to indicate an association between participation in OHCs and improved health outcomes. OBJECTIVE This study aimed to (1) determine changes in patient activation over 3 months in new users of an OHC, (2) describe patterns of engagement with an OHC, (3) examine whether patients’ characteristics at baseline were associated with subsequent patterns of engagement, and (4) determine if patterns of engagement during the 3 months were associated with changes in patient activation, health care utilization, and health status. METHODS Active new OHC users on HealthUnlocked (HU) were surveyed to measure demographics, levels of patient activation (describing a person’s confidence in managing their own health; scale 0-100 with 4 categories), health care utilization, and health status using a Web-based survey at baseline and 3 months. Patient activation at baseline and 3 months was compared (aim 1). Alongside, for a sample of HU users and survey responders, daily OHC website usage data were automatically captured. This was used to identify clusters of engagement with HU (aim 2). For survey responders, baseline characteristics, patient activation, health care utilization, and health status were compared at baseline and 3 months, overall, and between engagement clusters using t tests and chi-square tests (aims 3 and 4). RESULTS In 329 people who completed both surveys, baseline activation was most frequently level 3, described as taking action but still lacking confidence. At follow-up, a change of 2.6 points was seen, with the greatest change seen in those at lowest baseline activation levels. In addition, 4 clusters of engagement were identified: low, medium, high, and very high, who were active on HU for a mean of 4, 12, 29, and 59 days, respectively. Survey responders were more commonly high or very high engagers. Baseline activation was highest in low and very high engagers. Overall activation increased over time in all engagement groups. Very high engagers had the greatest improvement in activation (5 points), although the average change was not above what is considered clinically meaningful for any group. Fewer accident and emergency visits were seen at follow-up in those with higher engagement, although this trend was not seen for other health care utilization measures. There was no change in health status at 3 months. CONCLUSIONS This observational study provides some insight into how patterns of engagement with OHCs are associated with changes in patient activation, health care utilization, and health status. Over 3 months, overall, the change in activation was not clinically significant, and there were some indications that OHCs may be of benefit to particular groups. However, the study limitations prevent firm conclusions about causal relationships.

scholarly journals Health status and health care utilization after discharge from geriatric in-hospital stay – description of a register-based study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
E. Rydwik ◽  
R. Lindqvist ◽  
C. Willers ◽  
L. Carlsson ◽  
G. H. Nilsson ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Health Status ◽  
Health Care Utilization ◽  
Care Utilization ◽  
Future Studies ◽  
Healthcare Data ◽  
Utilization Data ◽  
Hospital Stays ◽  
Socioeconomic Data

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.

scholarly journals Health Status, Health Insurance, and Health Care Utilization Patterns of Immigrant Black Men

2003 ◽  
Vol 93 (10) ◽  
pp. 1740-1747 ◽  
Author(s):  
Jacqueline W. Lucas ◽  
Daheia J. Barr-Anderson ◽  
Raynard S. Kington
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Health Status ◽  
Health Care Utilization ◽  
Black Men ◽  
Care Utilization ◽  
Utilization Patterns

scholarly journals A Meta-Analysis of Health Status, Health Behaviors, and Health Care Utilization Outcomes of the Chronic Disease Self-Management Program

2013 ◽  
Vol 10 ◽  
Author(s):  
Teresa J. Brady ◽  
Louise Murphy ◽  
Benita J. O’Colmain ◽  
Danielle Beauchesne ◽  
Brandy Daniels ◽  
...  
Keyword(s):  
Health Care ◽  
Chronic Disease ◽  
Health Status ◽  
Health Care Utilization ◽  
Health Behaviors ◽  
Meta Analysis ◽  
Management Program ◽  
Self Management ◽  
Care Utilization
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