scholarly journals Impact of Multimorbidity Subgroups on the Health Care Use and Clinical Outcomes of Patients With Tuberculosis: A Population-Based Cohort Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Qin Chen ◽  
Yang Che ◽  
Yue Xiao ◽  
Feng Jiang ◽  
Yanfei Chen ◽  
...  
Keyword(s):  
Health Care ◽  
Chronic Conditions ◽  
Chronic Condition ◽  
Latent Class ◽  
Care Delivery ◽  
Cohort Analysis ◽  
Health Care Use ◽  
Cardiovascular Morbidity ◽  
Respiratory Morbidity ◽  
Regional Health Care

Background: Multimorbidity is defined as the existence of two or more chronic health conditions in the same individual. While patients with tuberculosis commonly have multiple conditions at diagnosis, such as HIV, diabetes, and depression, to the authors' knowledge, there is limited information on the patterns of multimorbidity, and how the types and combinations of conditions could impact the healthcare utilization, expenditure, and TB outcomes.Methods: An observational cohort study of adult patients diagnosed with tuberculosis was conducted using the Chinese Center for Disease Control and Prevention (CDC)'s National TB Information System (NTBIS) linked to the Ningbo Regional Health Care Database (NRHCD) (2015–2020). Latent class analysis was used to identify comorbidity groups among the subset with ≥2 conditions including TB. Group-level health care use, expenditure, and treatment outcomes were compared with patients without chronic conditions using multivariate regression models.Results: A total of 9,651 patients with TB were identified, of whom approximately 61.4% had no chronic conditions, 17.4% had 1 chronic condition, and 21.3% had ≥2 chronic conditions. Among those with ≥1 chronic condition other than TB, 4 groups emerged: (1) general morbidity (54.4%); (2) cardiovascular morbidity without complications (34.7%); (3) cardiovascular morbidity with complications (5.0%); (4) respiratory morbidity (5.9%). The respiratory morbidity group experienced the highest expenditures, at 16,360 CNY more overall (95% CI, CNY 12,615–21,215) after adjustment compared with TB patients without chronic conditions. The respiratory morbidity and cardiovascular morbidity with complications group also had the lowest odds of favorable TB outcomes [adjusted odds ratio (aOR), 0.68; 95% CI, 0.49–0.93] and (aOR 0.59, 95% CI 0.42–0.83), respectively. The cardiovascular morbidity without complications group had the highest odds of successful TB treatment (aOR, 1.40; 95% CI, 1.15–1.71).Conclusions: Multimorbidity is common among patients with TB. The current study identified four distinct comorbidity subgroups, all of which experienced high, yet differential, rates of health care use. These findings highlight the need for urgent reforms to transform current fragmented TB care delivery and improve access to other specialists and financial assistance.

scholarly journals Learning from and Leveraging Multi-Level Changes in Responses to the COVID 19 Pandemic to Facilitate Breast Cancer Prevention Efforts

2021 ◽  
Vol 18 (13) ◽  
pp. 6999
Author(s):  
Deborah J. Bowen ◽  
Kelly E. Rentscher ◽  
Amy Wu ◽  
Gwen Darien ◽  
Helen Ghirmai Haile ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Health Care ◽  
Cancer Prevention ◽  
Care Delivery ◽  
Breast Cancer Prevention ◽  
Health Care Use ◽  
Economic Life ◽  
Future Research ◽  
Multi Level ◽  
And Shifts

The coronavirus pandemic (COVID-19) has had multilevel effects on non-COVID-19 health and health care, including deferral of routine cancer prevention and screening and delays in surgical and other procedures. Health and health care use has also been affected by pandemic-related loss of employer-based health insurance, food and housing disruptions, and heightened stress, sleep disruptions and social isolation. These disruptions are projected to contribute to excess non-COVID-19 deaths over the coming decades. At the same time municipalities, health systems and individuals are making changes in response to the pandemic, including modifications in the environmental to promote health, implementation of telehealth platforms, and shifts towards greater self-care and using remote platforms to maintain social connections. We used a multi-level biopsychosocial model to examine the available literature on the relationship between COVID-19-related changes and breast cancer prevention to identify current gaps in knowledge and identify potential opportunities for future research. We found that COVID-19 has impacted several aspects of social and economic life, through a variety of mechanisms, including unemployment, changes in health care delivery, changes in eating and activity, and changes in mental health. Some of these changes should be reduced, while others should be explored and enhanced.

scholarly journals Rapid establishment of a COVID ‐19 convalescent plasma program in a regional health care delivery network

Transfusion ◽  
2020 ◽  
Vol 60 (10) ◽  
pp. 2203-2209
Author(s):  
Douglas Blackall ◽  
Shephali Wulff ◽  
Timothy Roettger ◽  
Lauren Jacobs ◽  
Alexandre Lacasse ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Delivery ◽  
Care Delivery ◽  
Regional Health ◽  
Regional Health Care ◽  
Delivery Network

scholarly journals An Innovative Approach to Health Care Delivery for Patients with Chronic Conditions

2017 ◽  
Vol 20 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Janice L. Clarke ◽  
Scott Bourn ◽  
Alexis Skoufalos ◽  
Eric H. Beck ◽  
Daniel J. Castillo
Keyword(s):  
Health Care ◽  
Health Care Delivery ◽  
Chronic Conditions ◽  
Care Delivery ◽  
Innovative Approach

scholarly journals Access to primary care and other health care use among western Canadians with chronic conditions: a population-based survey

CMAJ Open ◽  
2014 ◽  
Vol 2 (1) ◽  
pp. E27-E34 ◽  
Author(s):  
R. G. Weaver ◽  
B. J. Manns ◽  
M. Tonelli ◽  
C. Sanmartin ◽  
D. J. T. Campbell ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Chronic Conditions ◽  
Population Based ◽  
Health Care Use ◽  
Access To Primary Care ◽  
Population Based Survey

scholarly journals Development and Implementation of a Person-Centered, Technology-Enhanced Care Model For Managing Chronic Conditions: Cohort Study (Preprint)

2018 ◽  
Author(s):  
Curtis L Petersen ◽  
William B Weeks ◽  
Olof Norin ◽  
James N Weinstein
Keyword(s):  
Health Care ◽  
Chronic Conditions ◽  
Chronic Condition ◽  
Health Care Systems ◽  
Health Care Expenditures ◽  
Health Behavior Change ◽  
Care Model ◽  
Health Technologies ◽  
Care Systems ◽  
Per Capita

BACKGROUND Caring for individuals with chronic conditions is labor intensive, requiring ongoing appointments, treatments, and support. The growing number of individuals with chronic conditions makes this support model unsustainably burdensome on health care systems globally. Mobile health technologies are increasingly being used throughout health care to facilitate communication, track disease, and provide educational support to patients. Such technologies show promise, yet they are not being used to their full extent within US health care systems. OBJECTIVE The purpose of this study was to examine the use of staff and costs of a remote monitoring care model in persons with and without a chronic condition. METHODS At Dartmouth-Hitchcock Health, 2894 employees volunteered to monitor their health, transmit data for analysis, and communicate digitally with a care team. Volunteers received Bluetooth-connected consumer-grade devices that were paired to a mobile phone app that facilitated digital communication with nursing and health behavior change staff. Health data were collected and automatically analyzed, and behavioral support communications were generated based on those analyses. Care support staff were automatically alerted according to purpose-developed algorithms. In a subgroup of participants and matched controls, we used difference-in-difference techniques to examine changes in per capita expenditures. RESULTS Participants averaged 41 years of age; 72.70% (2104/2894) were female and 12.99% (376/2894) had at least one chronic condition. On average each month, participants submitted 23 vital sign measurements, engaged in 1.96 conversations, and received 0.25 automated messages. Persons with chronic conditions accounted for 39.74% (8587/21,607) of all staff conversations, with higher per capita conversation rates for all shifts compared to those without chronic conditions (P<.001). Additionally, persons with chronic conditions engaged nursing staff more than those without chronic conditions (1.40 and 0.19 per capita conversations, respectively, P<.001). When compared to the same period in the prior year, per capita health care expenditures for persons with chronic conditions dropped by 15% (P=.06) more than did those for matched controls. CONCLUSIONS The technology-based chronic condition management care model was frequently used and demonstrated potential for cost savings among participants with chronic conditions. While further studies are necessary, this model appears to be a promising solution to efficiently provide patients with personalized care, when and where they need it.

scholarly journals A Web-Based eHealth Intervention to Improve the Quality of Life of Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial

10.2196/25175 ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. e25175
Author(s):  
David H Gustafson Sr ◽  
Marie-Louise Mares ◽  
Darcie C Johnston ◽  
Jane E Mahoney ◽  
Randall T Brown ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Primary Care ◽  
Health Care ◽  
Chronic Conditions ◽  
Health Care Use ◽  
Multiple Chronic Conditions ◽  
Secondary Outcomes ◽  
Ehealth Intervention

Background Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients’ lives. Objective This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. Methods In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. Results Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. Conclusions With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. Trial Registration ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. International Registered Report Identifier (IRRID) DERR1-10.2196/25175

scholarly journals Health Care Visits During the COVID-19 Pandemic: A Spatial and Temporal Analysis of Mobile Device Data

2021 ◽  
Author(s):  
Jueyu Wang ◽  
Noreen McDonald
Keyword(s):  
Health Care ◽  
Health Care Delivery ◽  
Mobile Device ◽  
Care Delivery ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Health Care Use ◽  
Spatial Characteristics ◽  
Demographic Groups ◽  
Medical Visits

Transportation disruptions caused by COVID-19 have exacerbated difficulties in health care delivery and access, which may lead to changes in health care use. This study uses mobile device data from SafeGraph to explore the temporal patterns of visits to health care points of interest (POIs) during 2020 and examines how these patterns are associated with socio-demographic and spatial characteristics at the block group level in North Carolina. Specifically, using the k-medoid time-series clustering method, we identify three distinct types of temporal patterns of visits to health care POI. Furthermore, by estimating the multinomial logit models, we find that socio-demographic and spatial characteristics are strongly correlated with both the intensity and trend of medical visits during the pandemic. The results suggest that the ability to conduct in-person medical visits during the pandemic has been unequally distributed, which highlights the importance of tailoring policy strategies for specific socio-demographic groups to ensure health care delivery and access in a timely, equitable, and safe manner.

How Do We Align Health Services Research and Quality Improvement?

2020 ◽  
pp. 282-291
Author(s):  
Devika Das ◽  
Lalan Wilfong ◽  
Katherine Enright ◽  
Gabrielle Rocque
Keyword(s):  
Health Care ◽  
Quality Improvement ◽  
Health Services Research ◽  
Health Services ◽  
Health Care Quality ◽  
Care Delivery ◽  
Care Quality ◽  
Health Care Use ◽  
Semistructured Interview ◽  
Services Research

Quality improvement (QI) initiatives and health services research (HSR) are commonly used to target health care quality. These disciplines are increasingly important because of the movement toward value-based health care as alternative payment and care delivery models drive institutions and investigators to focus on reducing unnecessary health care use and improving care coordination. QI efforts frequently target medical error and/or efficiency of care through the Plan-Do-Study-Act methodology. Within the QI framework, strategies for data display (e.g., Pareto charts, run charts, histograms, scatter plots) are leveraged to identify opportunities for intervention and improvement. HSR is a multidisciplinary field of study that seeks to identify the most effective way to organize, deliver, and finance health care to maximize the quality and value of care at both the individual and population levels. HSR uses a diverse set of quantitative and qualitative methodologies, such as case-control studies, cohort studies, randomized control trials, and semistructured interview/focus group evaluations. This manuscript provides examples of methodologic approaches for QI and HSR, discusses potential challenges associated with concurrent quality efforts, and identifies strategies to successfully leverage the strengths of each discipline in care delivery.

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