Enhancing Elderly Care Services: A Comprehensive Internet+ Community Home Indicator System

doi:10.21203/rs.3.rs-3588988/v1

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Research Article

Enhancing Elderly Care Services: A Comprehensive Internet+ Community Home Indicator System

https://doi.org/10.21203/rs.3.rs-3588988/v1

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Background

In the context of the smart city and aging trends, Internet + community home-based care offers a novel approach to elderly care in China. However, limited research has focused on developing a comprehensive indicator system to address the diverse needs of elderly individuals residing at home. Based on existence needs, relationship needs and growth needs abbreviated as "ERG" demand theory. In response, this study leverages the ERG demand theory as a functional framework to establish a demand-oriented Internet + community home-based elderly service indicator system.

Methods

In this study, we adopt the ERG demand theory as the conceptual framework and employ a combination of the Delphi method and Analytic Hierarchy Process (AHP), thereby integrating both qualitative and quantitative research techniques to develop and assign weightings to the demand-orientated indicator system for Internet-based community home healthcare services for the elderly. Our research methodology is based on comprehensive literature reviews and collaborative group meetings.

Results

The study developed a demand-orientated Internet + community home healthy elderly service indicator system, comprising three primary indicators, 10 secondary indicators, and 46 tertiary indicators. These top-level indicators, ranked in descending order of importance, are medical and nursing services (0.493), living care services (0.311), and psychosocial/spiritual support services (0.196).

Conclusion

The indicator system serves the purpose of comprehending the health status and care requirements of elderly individuals confined to their homes while offering personalized services. In addition to addressing the fundamental needs of homebound older people through individualized care and expert medical guidance, this program places a significant emphasis on the spiritual and psychological well-being of these individuals to ensure a holistic approach to their physical and mental needs. This research posits that the indicator system can aid community healthcare workers in discerning the demand distribution for elderly services and optimizing resource allocation. By continuously evaluating and monitoring the indicators, this approach facilitates the enhancement of service quality and the fine-tuning of strategies, ultimately delivering efficient, safe, and high-quality elderly care services.

Internet+

Community home-based elderly care

Index system

Delphi consultation

Analytic hierarchy process (AHP)

A significant sociodemographic trend in the contemporary era is the global aging population [1]. Notably, China has witnessed a substantial rise in its elderly population since 2000, with more than 7% of its citizens aged 65 years or older. By 2021, China had reached the status of a highly aged society, with more than 14% of its population falling into the elderly category, indicating a rapid surge in the aging demographic [2]. China’s aging population possesses distinctive characteristics, including a swifter aging process, a more pronounced dependency burden, and aging preceding economic prosperity, which distinguish it from developed nations in Europe and the United States [3]. The acceleration of population aging presents escalating demands and challenges in the field of elderly care services. The conventional elderly care model struggles to meet the diverse and personalized needs of the elderly, thereby constraining their overall health and well-being. In response to this backdrop, the fusion of the Internet + technology and community-based home care services has emerged as a pivotal avenue for innovating and enhancing elderly care services [4]. Internet + community home care involves the integration of Internet technology with modern community care services, using online platforms and smart devices to deliver care services, and effectively integrating the necessary care resources and services for the elderly. This approach aims to achieve "menu-type demand" and "precise supply", thereby broadening the channels for providing pension services and optimizing the use of social resources. It signifies an extension and expansion of the traditional pension model in the context of the new economic landscape [5]. The "Internet+" community home care model not only introduces Internet technology to the elderly care industry but also deeply integrates professional information technology and platforms into the sector [6]. This integration serves two primary purposes: first, leveraging the strengths and characteristics of both industries to address deficiencies and foster mutual development, and second, comprehensively infusing technology to drive the overall progress of the elderly care sector [7].

China is actively promoting the implementation of Internet + community-based aging at home, with relevant government departments introducing a range of policies and support measures. These initiatives encourage enterprises to innovate elderly care service models, facilitate the development of Internet + community-based elderly care platforms, and enhance the digital literacy of the elderly population [8–11]. Various regions in China have proactively embraced and advanced the practice of Internet + community aging at home, yielding positive outcomes. However, they also encounter challenges such as limited adoption of technology and inconsistent service standards [12–14]. There is a pressing need for enhanced policy support and standardized guidance to improve the accessibility and quality of elderly care services. The integration of China’s Internet industry has caused a comprehensive social elderly care service system encompassing home-based, community-based, and institution-supported services. Consequently, a critical priority for enhancing China's social care service system lies in effectively addressing the home care service needs of the elderly and enhancing the provision of community home care services [15].

This study on Internet + community aging at home leverages information technology to centralize aging-related information on an external platform, creating a vital connection between the demand and supply sides. This platform gathers information from those seeking services and consolidates untapped societal resources. Using the power of the Internet and other information technologies, it delivers a multi-tiered array of diversified services [16]. This platform transcends spatial and temporal limitations, leveraging information technology and social platforms to harmonize the efforts of the government, society, markets, and families. It seamlessly integrates healthcare, artificial intelligence, social organizations, and other resources to jointly provide the elderly with life care, safety management, medical support, rehabilitation, and healthcare services, ultimately meeting the elderly’s aging-related needs and enhancing their overall health and quality of life. This effort not only bolsters the social pension service system but also contributes to the growth of the aging information industry [16]. Building upon the intelligent home care service model facilitated by 5G technology in Jinzhou City, Liaoning Province, the initiative establishes service areas, information repositories, and professional teams. Regardless of the specific senior care model chosen by the elderly, they can access "self-help and menu-type" senior care services through online applications and offline service provision. The Internet + community-based home care service providers encompass a diverse, high-quality, and professional workforce, including medical and nursing professionals, information technology experts, managers, housekeeping personnel, volunteers, and others. Moreover, these services encompass elderly care service robots, smart home devices, wearable technology, and other advanced tools. These not only offer professional and intelligent services but also leverage cutting-edge technical equipment and network information systems to reduce labor intensity and time requirements, thereby addressing human resource shortages in the elderly care industry.

Elderly individuals have multifaceted health needs that encompass both physical and mental aspects [17]. Empirical research has highlighted key areas of demand, including community-assisted meals, leisure and recreational activities, home assistance, rehabilitation training, minor healthcare, and elderly day care [4]. Based on a survey addressing the needs of a diverse elderly population, a broad spectrum of in-home services has been developed to cater to their care requirements. These services span long-term assistance for essential daily activities, and primary or hospital-level medical care delivered in the comfort of their homes [18]. The 2018 China Longitudinal Health and Life Survey (CLHLS) categorizes services into four main groups, each containing two subcategories: medical services, which encompass home visits and health education; daily life care services, including personal care and grocery shopping; mental and cultural services, consisting of social and recreational activities and psychological counseling; and mediation services, which include legal assistance and neighborhood relations [19]. Over the decade from 2008 to 2018, medical services emerged as the second-most important among the four categories, albeit with limited availability of home visits and health education due to constraints on primary care resources [20, 21]. Nevertheless, concerns such as "cognitive disorientation", "lack of family support", "self-restraint", and "unmet emotional and spiritual needs" still warrant attention [22]. However, providing humanistic care, mental health support, and addressing the spiritual aspects relevant to these concerns remains ambiguous [22, 23]. Alderfer [24], from Yale University in the United States, introduced the ERG needs theory, identifying three core needs: survival, interrelationships, and growth and development. This study classifies elderly needs based on the ERG theory into survival, relationship, growth, and development needs. Prior research has predominantly focused on service content, particularly medical care services, leaving a gap in understanding the elderly’s spiritual and social support needs, leading to a misalignment between services provided and actual needs.

To address the aforementioned gaps, this study integrates the Internet with elderly care services, harnessing the strengths of community-based home care services. The primary focus lies in introducing two specific service categories, namely daily care and psychosocial support, to construct a comprehensive Internet + community home care service indicator system that genuinely caters to the needs of elderly individuals at home. Simultaneously, the methodology, underpinned by the ERG demand theory, Delphi method, and hierarchical analysis, ensures the scientific rigor of the indicator system. Consequently, this study establishes a solid scientific foundation for evaluating the demand for community-based home care services and the rational allocation of medical service resources.

Theoretical Framework

The ERG theory of needs, introduced by Alderfer in 1969 in his work “An Empirical Test of a New Theory of Human Needs"[24], categorizes human needs into three primary groups. First, survival needs to encompass the fundamental requirements for individual material survival, including clothing, food, housing, transportation, income, benefits, and allowances, analogous to the physiological and safety needs in Maslow’s hierarchy of needs theory. Second, relationship needs pertain to the necessity for interpersonal connections, seeking satisfaction through interactions with others in both work and personal life, corresponding to the external aspect of social and self-esteem needs in Maslow’s hierarchy of needs theory. Third, growth needs revolve around an individual’s intrinsic aspiration for self-improvement and development, which is achievable through the realization of personal potential and capabilities, including the intrinsic part of self-esteem needs and the need for self-actualization in Maslow’s hierarchy. Internet + community home care can address the multifaceted needs of the elderly, spanning life care and medical health, which fall at the base of Maslow’s hierarchy of needs. However, the traditional elderly care model often struggles to adequately satisfy these requirements, let alone the need for respect and self-actualization among the elderly. This study is based on the Internet + community home care platform, which transcends spatial and temporal constraints, aligns government, society, markets, and families, and integrates healthcare, artificial intelligence, and social organizations’ resources to collectively provide the elderly with services such as life care, safety management, medical support, and rehabilitation and healthcare, ultimately catering to the authentic needs of the elderly and enhancing their health and quality of life.

Alderfer’s theory posits that his survival needs align with Maslow’s physiological and safety needs, encompassing basic physical survival and existence. Consequently, two level 1 indicators, namely living care services and medical and nursing services, are defined by these survival needs. Moreover, Aldefer’s concept of relationship needs corresponds to the requirement for interpersonal relationships, mirroring the social and self-esteem needs in Maslow’s hierarchy, including aspects such as self-esteem and self-actualization. This connection underlines the definition of another level 1 indicator, psychosocial/spiritual support services, which is rooted in both relationship and growth needs. Consequently, the level 1 indicators serve the genuine needs of the elderly, offering a range of healthy aging services across the three distinct dimensions.

Research Group Discussion

The research team comprised two professors, one chief nursing officer, one doctoral student, and three master’s students. They convened a group meeting to deliberate on the feasibility of content design for Internet + community home-based elderly care services. Subsequently, I revised it and created the first official expert consultation questionnaire. The initial index system emerged from a comprehensive literature review and extensive research group discussions, encompassing three top-level indicators, 10 second-level indicators, and 57 third-level indicators.

Delphi Expert Consultation

Concurrently, the research team set the criteria for selecting indicators and employed the Delphi method to identify experts. Previous research recommended the involvement of 10–50 advisory experts [25]. In this instance, 22 experts from universities, hospitals, communities, and information management departments were specifically invited to participate in shaping the index system for Internet + community-based elderly care services. These selected experts possess profound knowledge of the Internet and the Internet of Things, along with extensive research experience in elderly care, assuring the credibility of the consultation results [26].

The questionnaire consists of four distinct sections: (1) fundamental information about the expert, (2) an indicator questionnaire based on the initial indicator system, (3) the expert’s familiarity with the subject, and (4) the basis for the expert’s judgment. Every item in the questionnaire was assessed on a five-point Likert scale, spanning from "unimportant" to "very important"[27].

Two rounds of expert consultation were conducted via email. In the initial round, following the completion of the questionnaires by the experts, the researcher analyzed their responses. To ensure dependable consultation outcomes and acknowledge expert authority, a minimum expert authority coefficient (Cr) of 0.7 was required, and Kendall consistency was employed to assess the alignment of experts' viewpoints. Criteria for retaining each item included an average score for item importance exceeding 3.5 and a coefficient of variation (CV) lower than 0.25, based on previous research guidelines [28]. The researcher validated the proposed modifications proposed by experts by thoroughly reviewing the literature before their acceptance. In the second round, the experts were provided with the second-round questionnaire and summaries of the feedback received from the first round. Following the completion of the questionnaire by all experts, the researcher re-evaluated their responses. The consultation process was concluded once the experts’ opinions converged during the second round.

AHP Weight Assessment

The index weight plays a crucial role in appraising the quality of Internet + community home-based elderly care services because it determines the relative significance of each index, directly influencing the accuracy of the results derived from the index system. The AHP proves to be an invaluable tool for translating subjective expert judgments regarding various evaluation factors into quantitative weights, especially in the context of intricate issues necessitating decomposition [29]. In this study, we leveraged the results from the second round of expert importance ratings to compute the indicator weights and determine their corresponding values [30].

We engaged 15 experts to employ the 1–9 scale method in creating the pair-wise comparison judgment matrix because it offers greater clarity and simplicity for experts in determining the importance value of each indicator. The study is divided into 14 matrices, structured around three primary indicators, 10 secondary indicators, and 46 tertiary indicators [31]. Weight coefficients for primary, secondary, and tertiary indicators were derived from the matrix analysis results, using the index weight coefficient to evaluate the significance of each indicator. MATLAB 2016a was employed to input the experts' assessments of first-level indicators and establish a matrix for acquiring and organizing weight coefficients, maximum eigenvalues (λ max), consistency index (CI), and random consistency ratio (CR) [32]. A consistency assessment was conducted using the computed values, and a CR value below 0.1 indicated a successful outcome. Consequently, the hierarchical analysis yielded consistent results, ensuring the logical assignment of weight coefficients [33].

Statistical Analysis

We employed Excel to input and organize the data, followed by an in-depth analysis conducted using SPSS 25.0 and MATLAB 2016a software. Measurement data are illustrated by mean values along with their corresponding standard deviations, whereas enumeration data are conveyed by frequencies and percentages. The return rate of the questionnaires served as a measure of positivity among the experts. To gauge the level of expert authority and agreement, we employed the authority coefficient (Cr) and the Kendall coefficient (W), respectively. Evaluating the experts' appraisals of item importance was done based on the mean item importance scores and the coefficient of variation (CV).

Basic Information about the Experts

Information about the experts is shown in Table 1.

Table 1

Basic information about the experts
Item	First round(n = 27)		Second round(n = 22)
Item	Number of People	Composition ration(%)	Number of People	Composition ration(%)
Age
≤ 40	1	3.7	0	0
41～50	3	11.1	3	13.6
51～60	17	63.0	16	72.8
≥ 61	6	22.2	3	13.6
Education level
PhD degree	9	33.3	8	36.4
Master's degree	13	48.2	11	50.0
Bachelor degree or below	5	18.5	3	13.6
Professional title
Full Senior Professor	22	81.5	18	81.8
Associate Senior Professor	2	7.4	2	9.1
Intermediate lecturer	3	11.1	2	9.1
Research areas
Nursing Education	10	37.1	10	45.6
Geriatric Nursing	7	25.9	4	18.2
Community Nursing	5	18.5	3	13.6
Clinical Nursing	2	7.4	2	9.1
Information Technology Management	1	3.7	1	4.5
Management of medical institutions	1	3.7	1	4.5
Nursing Management	1	3.7	1	4.5
Professional years
≤ 20	3	11.1	2	9.1
21～30	2	7.4	2	9.1
31～40	19	70.4	16	72.7
≥ 41	3	11.1	2	9.1

Enthusiasm of Experts and Degree of Experts Authority

The questionnaires were dispatched via email in both instances, yielding a 100% response rate for each. The initial round involved the dispatch of 27 questionnaires, all of which were completed and returned, and the second round involved the distribution of 22 questionnaires, all of which were duly completed and returned. During the first round, 22 experts proposed amendments, while the second round saw eight experts offering their insights. The effective response rate for both rounds was 100%, underscoring the profound enthusiasm and active engagement of the experts.

The expert authority coefficient (Cr) is computed based on the expert’s assessments of the indicator (Ca) and their familiarity with the consultation content (Cs). The formula for Cr is (Ca + Cs)/2, with a Cr value of ≥ 0.70 generally considered acceptable [34]. In this study, the expert authority coefficients for the two rounds of expert consultation were 0.852 and 0.868. These values indicate a significant level of expert authority within this consultation. Further details can be found in Table 2.

Table 2

Expert authority level
Item	Judgment Basis(Ca)	Familiarity(Cs)	Authority(Cr)
First round(n = 27)	0.937	0.767	0.852
Second round(n = 22)	0.945	0.791	0.868

Degree of Coordination of Expert Opinion

The degree of coordination among expert opinions is typically evaluated using the Kendall Harmony Coefficient [27]. The Kendall coordination coefficients (W) for the primary, secondary, and tertiary indicators are detailed in Table 3. These coefficients demonstrate statistical significance (p < 0.001), indicating a robust consensus and alignment among expert perspectives.

Table 3

Expert coordination coefficient
Hierarchical level	First round			Second round
Hierarchical level	Kendall's W	X²	P	Kendall's W	X²	P
First-level	0.325	17.543	＜0.001	0.431	18.949	＜0.001
Second-level	0.242	58.845	＜0.001	0.300	59.360	＜0.001
Third-level	0.198	277.362	＜0.001	0.226	228.286	＜0.001
Overall	0.202	353.699	＜0.001	0.264	342.500	＜0.001

Demand-oriented Internet + Community Home-based Elderly Service Indicator System

Results of the First Round of Delphi Expert Consultation

Following the initial round of expert consultation, the mean importance ratings of the first-level indicators ranged from 4.52–5.00, with coefficients of variation ranging from 0.00–0.14, leading to the retention of all first-level indicators. For the second-level indicators, the mean importance ratings fell within the range of 4.44–5.00, with coefficients of variation ranging from 0.00–0.18, prompting the retention of all secondary indicators. However, two of them were subject to revision to enhance their standardization after discussions within the research group and consultation with experts. For instance, "spiritual comfort service" was revised to "psychological support service", and "home care" was modified to "health problem care". In the case of the third-level indicators, the mean importance ratings varied from 3.25–5.00, with coefficients of variation ranging from 0.00–0.44. Among them, five items had mean values lower than 3.5 and coefficient of variation values exceeding 0.25. After group discussions and expert opinion, these five items were removed. They included "community platform management consultation", "elderly care market information consultation", "family doctor contract", "prevention and control of public health emergencies", and "preventive health care". Two items exhibited coefficient of variation values surpassing 0.25 and were subsequently deleted after deliberation, as they were deemed to overlap with previous items and lacked professional terminology. These two items were "excretory care" and "elderly home constipation care". Taking into account expert feedback and discussions, "Chinese medicine services" and "medication management" were consolidated into "Chinese and Western medicine health services"; while "fistula care" and "wound care (including pressure ulcer care)" were merged into "wound/stoma care".

Results of the Second Round of Delphi Expert Consultation

Following the second round of expert consultation, the first-level indicators displayed mean importance scores ranging from 4.18–5.00, with a coefficient of variation ranging from 0.00–0.16. The second-level indicators exhibited mean importance ratings within the range of 4.23–5.00, accompanied by a coefficient of variation that ranged from 0.00–0.22. Similarly, the third-level indicators demonstrated mean importance scores between 4.14 and 5.00, with a coefficient of variation ranging from 0.00–0.23. Following discussion within the research group and incorporating expert feedback, one adjustment was made, where "accompanying to get around" was merged with "assistance with dressing and undressing, moving in bed, getting in and out of bed, going up and down stairs, and getting around". No further modifications were made to the remaining items. The results of the second round of consultation are presented in Table 6.

Determination of Weight Coefficient For Each Index in the Indicator System

Based on expert assessments, the significance of each dimension indicator was evaluated to derive an evaluation matrix. The foundational criteria for the evaluation are presented in Table 4.

Table 4

AHP numerical scale evaluation matrix
Numerical Value (aij)	Interpretation
1	The former is of equal importance to the latter.
3	The former is moderately more important than the latter.
5	The former is strongly more important than the latter.
7	The former is very strongly more important than the latter.
9	The former is extremely more important than the latter.
2,4,6,8	Intermediate values of the above judgements, adopted for compromising.
The Reciprocal of the above value	The importance of indicator i, indicator j, is aij. The importance of indicator j relative to indicator i is then 1/aij.

First, the geometric mean of each row of the judgement matrix was calculated using the product square root method, in which “aij” denotes the element of the i-th row and j-th column of the primitive judgement matrix, and “n” denotes the quantity of indicators. The geometric mean of each line is normalized to obtain the feature vector, which is the weight coefficient of each indicator. Next, the consistency test of the judgement matrix is conducted: by calculating the maximum eigenvalue of the judgement matrix as:\({\lambda }_{max}=\frac{1}{n}{\sum }_{i=1}^{n}\frac{{\sum }_{j=1}^{n}\text{a}\text{i}\text{j}\text{w}\text{j}}{wi}\) ; calculating the consistency index (CI) with the following formula:\(CI=\frac{{\lambda }_{max}-n}{n-1}\);calculating the consistency ratio (CR) as:\(CR=\frac{CI}{RI}\) .RI is the average random consistency index, and its value depends on “n” and is the average consistency index of randomly generated reciprocal matrices.

Using the judgment matrix and weight solution for the first-level index, as exemplified in Table 5, the analytic hierarchy process was employed to determine the weight of the index. The process involves constructing the judgment matrix and computing the maximum characteristic root \({\lambda }_{max}=0.30536\)of the judgment matrix using MATLAB2016a. To evaluate the consistency of the judgment matrix, the consistency index (CI) was computed as follows:\(CI=\frac{0.30536-3}{3-1}=0.0268\); while the random consistency index (RI)=0.52; Consequently, the consistency ratio (CR) was computed as follows:\(CR=\frac{0.0268}{0.52}=0.0516\); which falls below 0.1, indicating a successful consistency test. This implies that the results obtained through the AHP exhibit satisfactory consistency, affirming the rationality of the weight allocation. Accordingly, the AHP was used to establish the weight coefficients for indicators at all levels, with the three first-level indicators, ranked from highest to lowest as follows: medical and nursing services (0.493), living care services (0.311), and psychosocial/spiritual support services (0.196). The weights for each index are detailed in Table 6.

Table 5

Judgment matrix
Indicators	1	2	3	Weights
1	1	1/2	2	31.1%
2	2	1	2	49.3%
3	1/2	1/2	1	19.6%

Table 6

Demand-oriented Internet + Community Home Healthy Elderly Service Indicator System and Weight Values for Each Indicator
Indicators	Importance rating (x̄ ± s)	Coefficient of variation	Value of weight
1 Living care services	5.00 ± 0.00	0.00	0.311
1.1 Daily life care services	4.95 ± 0.21	0.04	0.449
1.1.1 Head and face cleansing care: hair washing, combing, cutting, facial cleansing, and beard trimming.	5.00 ± 0.00	0.00	0.068
1.1.2 Trunk cleaning care: limbs and body cleaning and, nail trimming	4.91 ± 0.29	0.06	0.060
1.1.3 Oral cleaning care	5.00 ± 0.00	0.00	0.097
1.1.4 Assistance with feeding and drinking	5.00 ± 0.00	0.00	0.367
1.1.5 Urination and defecation care	5.00 ± 0.00	0.00	0.236
1.1.6 Assistance with dressing, bed mobility, and mobility: Assistance with dressing and undressing, moving in and out of bed, navigating stairs, and general mobility.	4.95 ± 0.21	0.04	0.144
1.1.7 Makeup bed units: cleaning and replacing bedding	4.73 ± 0.46	0.10	0.028
1.2 Agency services	4.45 ± 0.74	0.17	0.139
1.2.1 Meal assistance services: private doorstep ordering, home delivery, and centralized meal supply	4.77 ± 0.43	0.09	0.467
1.2.2 Housekeeping and cleaning services: cleaning the living environment, laundry, and tending flower gardens	5.00 ± 0.00	0.00	0.278
1.2.3 Daily maintenance services: maintenance of electrical appliances household goods, and living facilities.	4.73 ± 0.46	0.10	0.095
1.2.4 Agency X services: procurement and receipt of items, fee payment, and handling of procedures on behalf of others.	4.82 ± 0.40	0.08	0.160
1.3 Security services	4.95 ± 0.21	0.04	0.287
1.3.1 Smart services: remote health monitoring, intelligent alarms, safety reminders, timed positioning, and intelligent companionship	4.45 ± 0.80	0.18	0.571
1.3.2 Safety and security services: regular door-to-door inspection, rental, and use of daily living AIDS, environmental renovation, and dissemination of safety and anti-fraud information	4.77 ± 0.43	0.09	0.286
1.3.3 Rights protection services: legal advisory, legal aid, and resolution of neighborhood disputes	4.36 ± 0.95	0.22	0.143
1.4 Advisory services	4.45 ± 0.80	0.18	0.126
1.4.1 Consultation on the functions of the elderly care service platform and surrounding available resources	5.00 ± 0.00	0.00	0.222
1.4.2 Consultation on the fees for old-age care services	4.91 ± 0.43	0.09	0.667
1.4.3 Consultation on policies related to old age	4.77 ± 0.43	0.09	0.111
2 Medical and nursing services	4.55 ± 0.51	0.11	0.493
2.1 Medical services	4.95 ± 0.21	0.04	0.540
2.1.1 Online appointment registration, accompanied by outpatient examinations and follow-up services	4.23 ± 0.87	0.21	0.103
2.1.2 Remote or mobile Online diagnosis and treatment of common, chronic, and frequently-occurring diseases	4.32 ± 0.95	0.22	0.164
2.1.3 Door-to-door emergency care	4.36 ± 0.95	0.22	0.371
2.1.4 Critical illness green referral services	4.14 ± 0.89	0.21	0.248
2.1.5 Chinese and Western medicine health services	4.86 ± 0.35	0.07	0.069
2.1.6 Infectious disease management	4.95 ± 0.21	0.04	0.045
2.2 Nursing for health problems	5.00 ± 0.00	0.00	0.297
2.2.1 Measurement of vital signs, disease observation, and treatment	4.95 ± 0.21	0.04	0.017
2.2.2 Safe medication and nursing: oral medication, sublingual medication, rectal administration, intravenous injection, subcutaneous injection, intramuscular injection, atomization inhalation, and percutaneous administration	4.95 ± 0.21	0.04	0.039
2.2.3 Indwelling tube nursing: nasogastric tube nursing, catheter nursing, and other drainage tube nursing	4.86 ± 0.35	0.07	0.218
2.2.4 Nursing of pain	5.00 ± 0.00	0.00	0.110
2.2.5 Nursing of sleep disorders	4.95 ± 0.21	0.04	0.294
2.2.6 Nursing of nutritional problems	4.95 ± 0.21	0.04	0.151
2.2.7 Nursing of the stoma	4.91 ± 0.29	0.06	0.052
2.2.8 Nursing for pressure injury	4.82 ± 0.50	0.10	0.070
2.2.9 Aspiration of phlegm and oxygen	4.91 ± 0.43	0.09	0.027
2.2.10 Evaluation of physical function and mental state	5.00 ± 0.00	0.00	0.020
2.3 Health management	4.82 ± 0.40	0.08	0.163
2.3.1 Establishment and management of personal health records, including psychological services	4.82 ± 0.50	0.10	0.163
2.3.2 Health screening services	4.91 ± 0.29	0.06	0.475
2.3.3 Health education services	5.00 ± 0.00	0.00	0.255
2.3.4 Rehabilitation and health services	4.91 ± 0.29	0.06	0.107
3 Psychosocial/Spiritual support services	4.18 ± 0.66	0.16	0.196
3.1 Psychological support services	4.95 ± 0.21	0.04	0.540
3.1.1 Emotional communication and emotional counseling	4.95 ± 0.21	0.04	0.238
3.1.2 Psychological technical support: psychological counseling and crisis intervention	5.00 ± 0.00	0.00	0.625
3.1.3 Establishment of spiritual cultivation courses: yoga, mindfulness meditation, and more	4.82 ± 0.40	0.08	0.136
3.2 Cultural and entertainment services	4.23 ± 0.87	0.21	0.163
3.2.1 Provide recreational and gymnastic facilities, platforms, and equipment	4.82 ± 0.50	0.10	0.122
3.2.2 Coordinating sporting, activities, cultural, and intellectual events	4.91 ± 0.29	0.06	0.320
3.2.3 Building social support networks	4.95 ± 0.21	0.04	0.558
3.3 Self-actualization services	4.23 ± 0.92	0.22	0.297
3.3.1 Organize college study and skills training for the elderly	4.86 ± 0.35	0.07	0.648
3.3.2 Establish an integrated re-employment service platform for the elderly that offers employment consultation, job referral, and employment monitoring services	4.82 ± 0.40	0.08	0.230
3.3.3 Introduce a "time bank" incentive program to encourage elderly people’s involvement in voluntary services and reward them with points for participation.	4.41 ± 0.50	0.11	0.122

Scientific and Reliable Nature of the Demand-oriented Internet + Community Home-based Elderly Service Indicator System

To address the increasing demand for healthy aging and the fragmented state of China’s medical and elderly care systems, the country has proposed an internet-based elderly care model. This approach focuses on the integration of medical resources at the community level, offering home care services to the elderly, thereby addressing the current challenges in elderly care in China.[35]. Based on this framework, this research developed an index system for Internet + community home-based elderly care services. Guided by the healthcare requirements of elderly individuals in homes, and using the ERG needs theory as a structural framework, the study employed the Delphi method and the AHP analytic hierarchy process as its primary research methodologies. This index system serves as a valuable complement to the existing long-term care system for elderly individuals residing at home, allowing for an in-depth, comprehensive, and dynamic evaluation of their healthcare and care-related needs. It facilitates the provision of tailored services that align with local conditions, making it a logical and rational approach [36]. The research engaged 22 experts, each with substantial expertise in the relevant field, representing various provinces and institutions. These diverse and representative groups achieved a 100% effective response rate in both questionnaire rounds. The experts exhibited a high level of authority, as indicated by the authority coefficients of 0.852 and 0.868. Furthermore, Kendall’s coordination coefficient (W) for the second round of expert correspondence increased to 0.264, surpassing the first round’s coefficient of 0.202.

Comprehensive and Practical Indicator System for Demand-oriented Internet + Community Home-based Elderly Services

Focusing on the genuine needs of elderly individuals living at home within the community, this study actively constructed an Internet + community home-based elderly care services index system that encompasses three essential aspects: living care services, medical and nursing services, and psychosocial/spiritual support services. The indicator construction results reveal that the highest weight among the first-level indicators belongs to medical and nursing services (0.493), followed by living care services (0.311) and psychosocial/spiritual support services (0.196). These differing weight values emphasize the varied needs of elderly individuals living at home in the context of China’s aging population. Previous research [37] has consistently indicated that elderly individuals residing at home often have a heightened demand for medical and nursing services because of a range of subjective and objective factors, including limited physical activity [38], a high prevalence of chronic diseases [39], and disparities in the distribution of primary medical and healthcare resources [40].

At a subjective level, the elderly prioritize the satisfaction of their two primary needs, specifically, life care and health, as they age. At an objective level, the aim is to efficiently allocate community public pension service resources and guarantee the elderly’s willingness to access these services within the community. In pursuit of this goal, we categorize the elderly into three distinct groups based on their assessment of elderly care needs in Jinzhou: those receiving care from their own families, those receiving care within the community, and those receiving care within institutional settings. The first approach involves using community health service centers or nursing stations to provide daily care, clinical support, and specialized services. The second approach involves utilizing community health service centers to provide long-term contracted medical services to elderly individuals living at home. Furthermore, efforts are being made to strengthen collaboration with regional medical institutions and establish an efficient process for elderly individuals in need of hospitalization or medical treatment while residing in elderly care facilities.

As the elderly population living alone or with disabilities increases [41], alongside a high prevalence of chronic diseases, there is a surging occurrence of diverse psychological challenges [42]. In the absence of professional home care and psychological support within the community, the essential healthcare needs of the elderly remain unaddressed. We are committed to providing precise in-home care services that cover personal daily care, support, and safety, including clothing, food, housing, and transportation. We thoroughly assessed the living conditions and distinctive features of the local elderly population at home. Notably, we empower the elderly by involving them in decision-making through psychological assistance, cultural and recreational activities, and self-realization initiatives. This approach enhances their independence and self-esteem while easing the responsibilities of caregivers [43]. Consequently, community-based elderly care providers must prioritize the psychological and social well-being of the elderly living at home. By challenging stereotypes associated with aging and disability, offering tailored services, and promoting mental health and active social engagement, we can enhance their overall well-being and integration into society.

The index system for Internet + community home-based elderly care services offers a comprehensive and practical approach, covering a wide array of factors crucial for the effective care of the elderly population living at home. This extensive system considers diverse aspects, including healthcare, social support, personal assistance, and technological integration. Concerning healthcare, the index system underscores the importance of accessible and responsive medical services, ensuring that elderly individuals have convenient access to healthcare facilities, regular check-ups, and timely medical interventions. Thereby, it addresses prevalent chronic diseases and enables early detection and prevention of potential health issues. In addition, the system acknowledges the significance of social support for the well-being of the elderly, advocating for the establishment of community resources and networks that encourage social interaction, companionship, and emotional support, mitigating feelings of loneliness and isolation experienced by elderly individuals living at home. Personalized assistance is another crucial aspect covered, emphasizing tailored care services that address the specific needs of each elderly individual, including assistance with daily activities such as personal hygiene, meal preparation, and household chores, significantly enhancing their quality of life. Finally, the index system recognizes the role of technology in enhancing the delivery of home-based elderly care services, promoting the integration of innovative technologies such as telemedicine, smart home systems, and wearable devices to monitor the health status of the elderly, facilitate remote consultations, and ensure their safety and security.

This study developed a demand-oriented Internet + community home-based elderly service indicator system by incorporating a literature review, expert consultation, and AHP hierarchical analysis. The indicator system is grounded in the ERG demand theory, which holds significant practical utility in delivering community-based healthy aging services to elderly individuals residing at home. It considers the diverse and multi-dimensional needs of the elderly, constructing scientific, comprehensive, and tailored indicator contents that offer valuable guidance and support for the delivery of top-notch, personalized community home-based elderly care services.

First, this approach enhances a better understanding of the health status, care needs, and living habits of elderly people living at home, thus facilitating the provision of personalized health and care services tailored to their specific needs. For instance, individuals suffering from stroke can receive customized rehabilitation care programs or professional medical guidance, which address their individual needs and enhance the relevance and effectiveness of services. Second, it aids community doctors and nurses in comprehending the characteristics of elderly needs and the temporal and spatial distribution of the demand for elderly services, allowing for more efficient resource allocation. By reasonably allocating human, material, and technical resources, service efficiency can be improved, costs reduced, and the diverse needs of various regions and elderly groups addressed. Finally, the quality of services can be enhanced through quantitative assessment and monitoring of the indicators of Internet + community-based home healthcare services. Community doctors and nurses can collect and analyze data, including elderly satisfaction and service feedback, to make timely adjustments to service strategies and enhance service procedures, ensuring the delivery of more efficient, safe, and high-quality elderly care services.

The demand-oriented Internet + community home-based elderly service indicator system offers several advantages. It enables the collection and analysis of data on elderly needs, facilitating quantitative and precise management of elderly services with a focus on delivering user-centric services. The system allows for a comprehensive assessment of indicators related to Internet + community home health care services, offering data support that empowers community doctors and nurses to make timely adjustments to service strategies and enhance service quality. Moreover, the indicator system aids service providers in understanding the demand patterns and temporal distribution of elderly care services, leading to the rational allocation of human, material, and technical resources. This, in turn, improves service efficiency and extends the reach of community services. However, it is worth noting that due to time and resource constraints, this study had limitations in terms of the number of consulting experts and their input. Future steps involve empirical research on the index system, further modification, and increased applicability. Additionally, addressing the variance in resource awareness among homebound elderly, especially those unfamiliar with the Internet and new types of elderly care, requires additional time and effort from community doctors and community nurses for training and communication. Senior care service providers must establish comprehensive quality standards and management systems, while ordinary service providers need to invest in skills development and service improvements to effectively utilize the indicator system and provide better services for the elderly.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without any restrictions or reservations.

Author Contributions

RZ designed the study protocol, conducted the study, and prepared the manuscript. Ms. H, My T, LW, Jx L, and Ql L were responsible for conducting the study, data collection, and statistical analysis. Hy L and RW provided research guidance and contributed to the critical review of the article for intellectual content.

Funding

This study received funding from the Liaoning Science and Technology Innovation Think Tank in 2023 (project number: LNKX2023FH17) and the first batch of the "Elderly Health Promotion Action (2021-2025)" screening project by the Chinese Society of Gerontology and Geriatrics (project number: 2021-04-01).

Acknowledgments

This study was approved and assisted by the person in charge of the Wei Sen Smar’t elderly care service platform in Jinzhou City. We extend our gratitude to the experts who participated in the Delphi process.

Ethics Declaration

This study was ratified by the Ethics Committee of Jinzhou Medical University (Ethical approval number: JZMULL2023080). At the commencement of the study, the participants were duly informed about the study’s objectives and their right to voluntarily participate. Written informed consent was obtained from all study participants, and all procedures were conducted according to relevant guidelines and regulations.

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Enhancing Elderly Care Services: A Comprehensive Internet+ Community Home Indicator System

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Abstract

Background

Methods

Results

Conclusion

Background

Methods

Theoretical Framework

Research Group Discussion

Delphi Expert Consultation

AHP Weight Assessment

Statistical Analysis

Results

Basic Information about the Experts

Enthusiasm of Experts and Degree of Experts Authority

Degree of Coordination of Expert Opinion

Demand-oriented Internet + Community Home-based Elderly Service Indicator System

Results of the First Round of Delphi Expert Consultation

Results of the Second Round of Delphi Expert Consultation

Determination of Weight Coefficient For Each Index in the Indicator System

Discussion

Scientific and Reliable Nature of the Demand-oriented Internet + Community Home-based Elderly Service Indicator System

Comprehensive and Practical Indicator System for Demand-oriented Internet + Community Home-based Elderly Services

Conclusion

Strength and Limitations

Declarations

References

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