Effect of Implementing an Informatization Case Management Model on the Management of Chronic Respiratory Diseases in a General Hospital: Retrospective Controlled Study

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Abstract

Background

The use of chronic disease information systems in hospitals and communities plays a significant role in disease prevention, control, and monitoring. However, there are several limitations to these systems, including that the platforms are generally isolated, the patient health information and medical resources are not effectively integrated, and the “Internet Plus Healthcare” technology model is not implemented throughout the patient consultation process.

Objective

The aim of this study was to evaluate the efficiency of the application of a hospital case management information system in a general hospital in the context of chronic respiratory diseases as a model case.

Methods

A chronic disease management information system was developed for use in general hospitals based on internet technology, a chronic disease case management model, and an overall quality management model. Using this system, the case managers provided sophisticated inpatient, outpatient, and home medical services for patients with chronic respiratory diseases. Chronic respiratory disease case management quality indicators (number of managed cases, number of patients accepting routine follow-up services, follow-up visit rate, pulmonary function test rate, admission rate for acute exacerbations, chronic respiratory diseases knowledge awareness rate, and patient satisfaction) were evaluated before (2019‐2020) and after (2021‐2022) implementation of the chronic disease management information system.

Results

Before implementation of the chronic disease management information system, 1808 cases were managed in the general hospital, and an average of 603 (SD 137) people were provided with routine follow-up services. After use of the information system, 5868 cases were managed and 2056 (SD 211) patients were routinely followed-up, representing a significant increase of 3.2 and 3.4 times the respective values before use ( U=342.779; P<.001). With respect to the quality of case management, compared to the indicators measured before use, the achievement rate of follow-up examination increased by 50.2%, the achievement rate of the pulmonary function test increased by 26.2%, the awareness rate of chronic respiratory disease knowledge increased by 20.1%, the retention rate increased by 16.3%, and the patient satisfaction rate increased by 9.6% (all P<.001), while the admission rate of acute exacerbation decreased by 42.4% (P<.001) after use of the chronic disease management information system.

Conclusions

Use of a chronic disease management information system improves the quality of chronic respiratory disease case management and reduces the admission rate of patients owing to acute exacerbations of their diseases.

Related collections

Most cited references 23

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Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease.

Catherine McCabe, Margaret McCann, Anne Marie Brady (2017)

Chronic obstructive pulmonary disease (COPD) is characterised by airflow obstruction due to an abnormal inflammatory response of the lungs to noxious particles or gases, for example, cigarette smoke. The pattern of care for people with moderate to very severe COPD often involves regular lengthy hospital admissions, which result in high healthcare costs and an undesirable effect on quality of life. Research over the past decade has focused on innovative methods for developing enabling and assistive technologies that facilitate patient self-management.

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Specialty COPD care during COVID-19: patient and clinician perspectives on remote delivery

Frances Wu, Jenni Burt, Teena Chowdhury … (2021)

Introduction The COVID-19 pandemic has impacted specialty chronic obstructive pulmonary disease (COPD) care. We examined the degree to which care has moved to remote approaches, eliciting clinician and patient perspectives on what is appropriate for ongoing remote delivery. Methods Using an online research platform, we conducted a survey and consensus-building process involving clinicians and patients with COPD. Results Fifty-five clinicians and 19 patients responded. The majority of clinicians felt able to assess symptom severity (n=52, 95%), reinforce smoking cessation (n=46, 84%) and signpost to other healthcare resources (n=44, 80%). Patients reported that assessing COPD severity and starting new medications were being addressed through remote care. Forty-three and 31 respondents participated in the first and second consensus-building rounds, respectively. When asked to rate the appropriateness of using remote delivery for specific care activities, respondents reached consensus on 5 of 14 items: collecting information about COPD and overall health status (77%), providing COPD education and developing a self-management plan (74%), reinforcing smoking cessation (81%), deciding whether patients should seek in-person care (72%) and initiating a rescue pack (76%). Conclusion Adoption of remote care delivery appears high, with many care activities partially or completely delivered remotely. Our work identifies strengths and limitations of remote care delivery.

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Integrated Telehealth and Telecare for Monitoring Frail Elderly with Chronic Disease

Hulya Gokalp, Joost de Folter, Vivek Verma … (2018)

Abstract Objective: To investigate the potential of an integrated care system that acquires vital clinical signs and habits data to support independent living for elderly people with chronic disease. Materials and Methods: We developed an IEEE 11073 standards-based telemonitoring platform for monitoring vital signs and activity data of elderly living alone in their home. The platform has important features for monitoring the elderly: unobtrusive, simple, elderly-friendly, plug and play interoperable, and self-integration of sensors. Thirty-six (36) patients in a primary care practice in the United Kingdom (mean [standard deviation] age, 82 [10] years) with congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) were provided with clinical sensors to measure the vital signs for their disease (blood pressure [BP] and weight for CHF, and oxygen saturation for COPD) and one passive infrared (PIR) motion sensor and/or a chair/bed sensor were installed in a patient's home to obtain their activity data. The patients were asked to take one measurement each day of their vital signs in the morning before breakfast. All data were automatically transmitted wirelessly to the remote server and displayed on a clinical portal for clinicians to monitor each patient. An alert algorithm detected outliers in the data and indicated alerts on the portal. Patient data have been analyzed retrospectively following hospital admission, emergency room visit or death, to determine whether the data could predict the event. Results: Data of patients who were monitored for a long period and had interventions were analyzed to identify useful parameters and develop algorithms to define alert rules. Twenty of the 36 participants had a clinical referral during the time of monitoring; 16 of them received some type of intervention. The most common reason for intervention was due to low oxygen levels for patients with COPD and high BP levels for CHF. Activity data were found to contain information on the well-being of patients, in particular for those with COPD. During exacerbation the activity level from PIR sensors increased slightly, and there was a decrease in bed occupancy. One subject with CHF who felt unwell spent most of the day in the bedroom. Conclusions: Our results suggest that integrated care monitoring technologies have a potential for providing improved care and can have positive impact on well-being of the elderly by enabling timely intervention. Long-term BP and pulse oximetry data could indicate exacerbation and lead to effective intervention; physical activity data provided important information on the well-being of patients. However, there remains a need for better understanding of long-term variations in vital signs and activity data to establish intervention protocols for improved disease management.

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Author and article information

Contributors

Yi-Zhen Xiao:

ORCID: http://orcid.org/0009-0004-0087-6288

Xiao-Jia Chen:

ORCID: http://orcid.org/0009-0001-1325-593X

Xiao-Ling Sun:

ORCID: http://orcid.org/0009-0005-2633-4230

Huan Chen:

ORCID: http://orcid.org/0009-0005-9304-2107

Yu-Xia Luo:

ORCID: http://orcid.org/0009-0000-5185-5285

Yuan Chen:

ORCID: http://orcid.org/0009-0004-8732-0652

Ye-Mei Liang:

ORCID: http://orcid.org/0009-0001-0016-9872

Journal

Journal ID (nlm-ta): JMIR Med Inform

Journal ID (iso-abbrev): JMIR Med Inform

Journal ID (hwp): JMI

Journal ID (publisher-id): medinform

Journal ID (index): 7

Title: JMIR Medical Informatics

Publisher: JMIR Medical Informatics

ISSN (Electronic): 2291-9694

Publication date Collection: 2024

Publication date (Electronic): 19 June 2024

Volume: 12

Electronic Location Identifier: e49978

Affiliations

[1 ]departmentDepartment of Pulmonary and Critical Care Medicine , Yulin First People’s Hospital , Yulin, China

[2 ]departmentDepartment of Nursing , Yulin First People’s Hospital , Yulin, China

Author notes

Ye-MeiLiangMM, Department of Nursing, Yulin First People’s Hospital, 495 Middle Education Road, Yuzhou District, Yulin, 537000, China, 86 0775-2683224; liangyemeilym8@ 123456126.com

None declared.

Author information

Yi-Zhen Xiao http://orcid.org/0009-0004-0087-6288

Xiao-Jia Chen http://orcid.org/0009-0001-1325-593X

Xiao-Ling Sun http://orcid.org/0009-0005-2633-4230

Huan Chen http://orcid.org/0009-0005-9304-2107

Yu-Xia Luo http://orcid.org/0009-0000-5185-5285

Yuan Chen http://orcid.org/0009-0004-8732-0652

Ye-Mei Liang http://orcid.org/0009-0001-0016-9872

Article

Publisher ID: 49978

DOI: 10.2196/49978

PMC ID: 11199924

PubMed ID: 38904478

SO-VID: d46a16ed-d312-4278-bdc9-ff459b0bd34c

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 15 June 2023

Date revision received : 14 April 2024

Date accepted : 17 April 2024

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