The determinants of patient perceptions of integrated care: Evidence from tightly-knit county medical community in China

doi:10.21203/rs.3.rs-4189296/v1

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Research Article

The determinants of patient perceptions of integrated care: Evidence from tightly-knit county medical community in China

https://doi.org/10.21203/rs.3.rs-4189296/v1

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Purpose

Integrated care services have been initiated in China for several years, yet there remains a notable dearth of substantial evidence and research elucidating the service’s efficacy. This study assesses the efficacy of integrated care services, particularly from the patients’ vantage point. We aim to identify the key influencing factors and pathways, providing invaluable insights into integrated service. Additionally, we aspire to delineate strategies for enhancing healthcare delivery systems’ quality, efficiency, and continuity.

Methods

The Patient Perceptions of Integrated Care (PPIC) and European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L) scales were employed to gather information on patients’ perceptions of integrated care and their self-rated health status. A total of 1093 respondents from two pilot areas were selected for data collection. T-tests and one-way analysis of variance (ANOVA) were, additionally, the study utilized multiple linear regression models to examine the specific impact of various factors on the effectiveness of integrated care services.

Results

The average score for the effectiveness of integrated healthcare services from the patients’ perspective was 67.72 (SD = 14.443), indicating a discrepancy between patient expectations and the actual delivery of care. The individual health status and socioeconomic factors significantly influence patients’ perceptions. As individual health status (B = -0.073, P = 0.024) declines, so does the perception of service effectiveness. Furthermore, health intervention factors, including intervention duration (B = 3.244, P < 0.001) and frequency (B = 5.346, p < 0.001), had a pronounced impact on patients with elevated health demands. Notably, age (B = 1.298, P = 0.009), marital status (B = 1.623, p = 0.002), and occupational category (B = -7.546, P = 0.002), also exert a nuanced influence on patients’ perceptions of integrated services.

Conclusions

This study identified a significant disparity between patients’ perceptions and expectations of integrated services, underscoring the imperative of patient-centered care in integrating services, and emphasizing the need for personalized health services tailored to individual needs. Furthermore, priority should be given to residents with chronic diseases or comorbidities. Additionally, there is a call for establishing more robust communication and management mechanisms to foster collaboration among healthcare teams.

Integrated care services

Effectiveness evaluation

Patient perception

The ongoing progression of China’s aging population, the rise in chronic non-communicable diseases, and increasing healthcare expenditures have exerted immense pressure on the primary healthcare system[1–3]. This escalating demand for social health and medical expenditures poses unprecedented risks to the healthcare service system [4]. Therefore, the adoption of Diagnosis-Related Group (DRG) healthcare payments under the per capita prepaid system has commenced. Integrating the primary healthcare system has been prioritized to address these challenges[5]. A paradigm shift from a treatment-centric approach to a health-centric approach in healthcare service is now underway.

Since the late 1990s, integrated care, has been considered a “burgeoning field”[6] and has been widely discussed on a global scale for an extended period[7]. The definition of Integrated care (IC) varies among different backgrounds and stakeholders. At the same time, there are common themes in its philosophy and content. First, it revolves around a patient-centric philosophy, focusing on individuals and providing patients with more continuous, effective, coordinated, and economically efficient high-quality medical services based on their health conditions[8, 9]. Second, integrated services encompass various aspects, typically including organizational integration, functional integration, personnel integration, standard integration, clinical integration, and system integration[10, 11]. Third, it emphasizes coordination and continuity in the service process, considering the appropriateness and effectiveness of individual services and the connection and coherence between various services, services at different time sequences and different life stages[12].

Until 2015, the World Health Organization (WHO) defined integrated care as follows: “an approach to strengthen patient-centered health systems through the promotion of the comprehensive delivery of quality services across the life-course, designed according to the multidimensional needs of the population and the individual and delivered by a coordinated multidisciplinary team of providers working across settings and levels of care”[13]. Furthermore, due to divergent institutional frameworks and economic development models, the operational mechanisms of integrated care exhibit notable variations among different countries[14]. In Germany, integrated health services are primarily driven by government authorities through the formulation of disease management plans. A market-driven approach was adopted in the United States, advocating for strategies such as mergers and collaborative partnerships to consolidate diverse medical and insurance institutions across various regions and levels[15].

China has long grappled with the polarizing effects of healthcare resource distribution, leading to imbalanced development where “the large get larger, and the small get smaller.” This issue is evident in the imbalance of healthcare resources across various country regions and the disparity between urban and rural areas[16]. The necessity of implementing an integrated care service strategies has become increasingly pressing. In fact, as part of the healthcare service delivery model reform, the capitation prepayment medical insurance payment initiative has been implemented Since 2020. Simultaneously, tightly-knit county medical community and numerous integrated care service teams were initiated to optimize the integration of medical resources and reinforce interorganizational collaboration.

Under the unified planning of health administration, tertiary and secondary hospitals, as well as community health service institutions, are seamlessly interwoven, entailing the horizontal or vertical integration of resources among healthcare institutions at various echelons. Integrated health care service teams comprising multiple professional disciplines, including general medicine, traditional Chinese medicine, nursing, public health, and pharmacy, among others. Such a Chinese version of the integrated care services model is currently underway in selected pilot areas, endeavoring to pioneer a scalable solution to address the multifaceted challenges confronting the health care system effectively.

This study selected two representative regions in Henan Province, where is one of the most populous and largest agricultural provinces in China[17]. The selected region collectively covers a population of 5.4 million people, including 12 urban medical alliances and integrated county-level medical communities. Simultaneously, 1644 healthcare service teams were formed. However, the actual service outcomes following healthcare service integration still need to be clarified, especially concerning exploring integrated service levels from the patient’s perspective, which has received limited attention. This scarcity highlights a significant gap in this field.

Therefore, this study aimed to explore the effects of integrated services from the patient’s perspective through questionnaire surveys and patient interviews. This study seeks to elucidate how demographic differences impact the perceived effectiveness of integrated care services. Moreover, this research explores the influence of population health levels on the perception of integrated services, aiming to provide insights for more targeted health integration services. In summary, this research examines the effectiveness of healthcare services in the region and aims to fill some existing gaps.

This study conducted a questionnaire survey targeting pilot areas for data collection. The questionnaire consisted of three main sections: patient demographics, the Patient Perceptions of Integrated Care scale, and the European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L) scale. These sections aimed to capture patients’ basic information, perceptions of integrated services, and self-perceived health status.

The Scale of Patient Perceptions of Integrated Care (PPIC)

To evaluate the effectiveness of integrated care services for chronic diseases from patients’ perspective, this study introduced the Patient Perceptions of Integrated Care (PPIC) developed and validated by Professor Singer’s research team in the United States[18]. The PPIC scale, specifically designed to investigate the integrated care experiences of chronic patients, has undergone rigorous validation to ensure the accuracy and reliability of its content, as well as its structural validity and internal consistency. Following cross-cultural validation across various contexts, including the Netherland, and Spain, among other regions, the scale has demonstrated robust cultural applicability[19]. The scale’s adaptation and refinement were rigorously conducted per the guidelines for cross-cultural adaptation of international scales. A version tailored to the Chinese cultural context was developed, which includes 37 items.

A total of 520 questionnaires were collected to conduct reliability and validity tests. In addition, exploratory factor analysis (EFA) was employed to assess the structural validity of the scale. The analysis revealed a Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy value of 0.895 and a significant Bartlett’s sphericity test statistic of 6723.760 (df = 351, P<0.001), confirming that the scale met the prerequisites for factor analysis. Following rotation using the maximum variance method, Cronbach’s α coefficient for the scale was determined to be 0.901. A total of 6 common factors were extracted, aligning with the dimensions proposed by the scale’s developers, demonstrating the solid structural validity of the translated version.

Additionally, the examination results revealed that the six dimensions explained a cumulative percentage of the total variance of 69.283%. Cronbach’s α coefficients for each dimension ranged between 0.754 and 0.930, exhibiting strong internal consistency. Furthermore, the study employed AMOS 26.0 to conduct confirmatory factor analysis. The average variance extracted (AVE) values for factor loadings in each dimension were all above 0.5, and the composite reliability (CR) values were all above 0.8, indicating that the construct validity of the scale passed basic tests for convergent validity. The results of the discriminant validity test for the baseline model revealed favorable fit indices (χ²/df = 2.003, CFI = 0.961, RMSEA = 0.044, TLI = 0.952, IFI = 0.962), meeting the adaptation requirements and demonstrating good discriminant validity among the variables[20].

The scale of the European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L)

To determine the respondents’ health status, the European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L) were incorporated into the questionnaire. The instrument is widely employed as a health status detector[21], offering efficiency with minimal cognitive demands. It includes a concise, descriptive system questionnaire and a EuroQol-visual analog scale (EQ-VAS). It was Originally introduced by the EuroQol Group in 2009, and covers five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension comprises five response options: no problems, slight problems, moderate problems, severe problems and extreme problems. Compared to the 3D-3L version, it offers enhanced sensitivity and lower ceiling effects by increasing the number of severity levels[22, 23]. Additionally, the visual analog scale (EQ-VAS) could serve as a straightforward self-assessment tool, which provides a scale anchored from 0 (The worst health you can imagine) to 100 (The best health you can imagine) for respondents to express their health status. With its simplicity, versatility, and capacity to generate quantifiable health data, the EQ-5D-5L has proven to be a valuable instrument for evaluating and comparing health-related quality of life in various contexts[24, 25].

Data collection

Two pilot cities were selected from Henan province, from which two community health service centers and four township health clinics were randomly chosen in each city. All participants provided informed consent prior to their involvement in the study. Several respondents’ selection criteria were established for our respondents: (1) Respondents had to be beneficiaries of integrated care services in the last 6months (2) Respondents needed to be at least 18 years old. (3) Respondents should have a comprehensive understanding of the survey questions. (4) Respondents should be able to express their viewpoints accurately and clearly. In addition, considering most of our study participants were older individuals with chronic conditions, we utilized paper-based or electronic questionnaires and personalized one-on-one data input assistance. It guaranteed that the gathered information was based on the respondents’ intentions, thus elevating the data quality. In the study’s first phase in 2023, 1125 respondents who fulfilled all the inclusion criteria were randomly recruited. Additionally, samples were excluded with missing, ambiguous, or logically inconsistent, including invalid questionnaires where more than 80% of the selected options were identical or where there were evident contradictions between responses across questions. Finally, 1093 (97.16%) qualified samples were applied in this study.

Following the guidelines set forth by the Consumer Assessment of Healthcare Providers and Systems (CAHPS), the PPIC scoring criteria can be divided into three primary types. The specific breakdown of these criteria is detailed in the Table 1 below. Moreover, the total score for the scale amounts to 130 points, enabling classification into four distinct tiers, thereby facilitating the assessment of the respondents’ perceptions across various levels of integrated care service. A higher score indicates better quality of services from the perspective of patients. When respondents choose to skip questions within the scale, all sub-items under the main item are assigned a score of 0 points. Additionally, to ensure authentic feedback from respondents, questions 20 and 21 are designed for reverse scoring.

Table 1

The scoring criteria of the PPIC scale
Category	1 Point	2 Point	3 Point	4 Point
Binary scoring	No	Yes	-^a	-
Ternary scoring	Never	sometimes	always	-
Quaternary scoring	Never	sometimes	often	always
^aN/A: not applicable.

Data analysis

This study employed a comprehensive approach to data analysis, combining descriptive statistical analysis with inferential statistical analysis methods. Demographic information was utilized to categorize patients logically according to their health status. Comparative analyses across different patient groups were conducted using t-tests and one-way analysis of variance (ANOVA) to discern significant differences in the effectiveness of integrated care services. Furthermore, the study utilized multiple linear regression models to investigate the specific impact of various factors on the effectiveness of integrated care services. This approach enabled a more detailed examination of how different factors influenced the outcomes related to integrated care services. Statistical analyses were conducted using SPSS version 20 software. Statistical significance was defined as 0.05.

1 Demographic information

The study was conducted in a relatively disadvantaged region of China, with respondents predominantly sourced from communities and rural areas. As illustrated in Supplementary Table 1. Notably, most respondents were aged 31 and above, making up approximately 94.64% of the sample. Among this respondent group, females constitute 64.73%, while 77.09% of respondents have an educational background of junior high school or lower, with a minority holding a college degree or higher. Furthermore, approximately 81% of the respondents are permanent rural residents, and 67.18% were primarily engaged in farming. This occupational distribution closely corresponds to the proportion of individuals in the low-income category (Below 1000 RMB per month), which stands at 54.64%.

Additionally, the collected data provides insights into respondents’ overall health status and critical information about integrated care services. For example, 41.54% of respondents reported having chronic diseases. Within the respondent group, 954 individuals had received integrated services for more than three years, constituting 87.28% of the sample. Approximately 63.40% of respondents proactively sought guidance from medical groups across healthcare areas, encompassing preventive measures, disease diagnosis, treatment, and rehabilitation. In summary, the fundamental data collected portrays the overall conditions of respondents in the pilot area, offering an objective depiction of their living and health standards.

2 Descriptive analyses of PPIC scores and Health Status

Analysis of the PPIC total score and sub-dimensions

Based on the analysis of the 1093 samples collected in this study, the average PPIC score was 67.72 (SD = 14.44), with a range spanning from 27 to 117 (total score of 130). These scores are categorized into four tiers: poor (< 40), fair (41–70), good (71–100), and excellent (100–130). The “fair” level constitutes the most significant proportion, with a cumulative count of 576 individuals (52.70%), a majority representation within the sample. Moreover, 477 individuals (43.64%) achieved scores of ‘Good’ or higher (> 70), showcasing a notable portion of participants who perceived integrated care positively. Conversely, individuals scoring below 40, totaling 40 individuals (3.66%), are indicative of experiencing poor service quality, highlighting the need for remedial actions in care delivery.

Across various scoring dimensions, Dimension 4 (familiarity with the patient over time) and Dimension 6 (patient-centeredness) achieved total scores of 12 and 16, respectively. However, their mean scores were 8.55 (SD = 2.295) and 13.75 (SD = 2.518), indicating a relatively high overall evaluation level for these two dimensions. In addition, Dimension 2 (coordination across care teams) and Dimension 5 (proactive and responsive action between visits) demonstrated acceptable evaluation results, with total scores of 10 and 30, and mean scores of 6.31, (SD = 2.105) and 20.20 (SD = 6.956), respectively. However, Dimension 1 (Coordination within the Care Team) and Dimension 3 (coordination between Care Teams and Community Resources) exhibited significantly lower scores. Despite their total scores of 40 and 20, respectively, their mean scores were only 12.93 (SD = 5.333) and 5.96 (SD = 2.972), placing them at the first quartile level.

Self-rated health status of respondents

The study investigated the physical health status of the respondents using the EQ-5D-5L scale. The results revealed that the average self-rated health status of the 1093 participants was 87.79 (n = 1093, SD = 12.479), indicating a generally high level of self-rated health among the respondents. Additionally, the study identified a notable decline in self-rated health with advancing age among the respondents, as depicted in the accompanying Fig. 1. The line graph illustrates the trends of self-assessed health and PPIC evaluation scores among respondents about age. Respondents’ average self-assessed health score was 87.79 (n = 1093, SD = 12.479). Notably, there was a discernible downward trend in self-assessed health with increasing age, while the average PPIC score was 67.72 (n = 1093, SD = 14.443), demonstrating a gradual upward trend with age. The study further employed Pearson correlation analysis to explore the relationship between health status and respondents perceived PPIC levels to clarify the correlation between these two dimensions. The results revealed a statistically significant negative correlation between the two indicators (r = -0.092, P = 0.002).

Figure 1 Comparison between health status and effectiveness of PPIC across different age categories

As shown in Table 2, which evaluates five dimensions of health, respondents mostly rated their health status as either “No problems” or “Slight problems." Notably, except for the “Pain/Discomfort” dimension, over 86.27% of respondents reported no issues across all health dimensions. This observation reflects a prevailing optimistic outlook among respondents regarding their health. Additionally, none of the respondents reported experiencing “Extreme problems” in the “Anxiety/Depression” dimension. The presence of “slight problems” was mainly noted in the “mobility” and pain/discomfort” dimensions, with the vast majority of respondents (P = 95.15%, n = 1040) indicating no issues in the “self-care” dimension. In summary, this analysis sheds light on respondents’ overall positive perception of health status, with minor issues predominantly observed in the mobility and pain/discomfort dimensions.

Table 2

Self-rated health status based on the EQ-5D-5L scale (n = 1093)
Severity	Mobility	Usual activities	Self-care	Pain/ Discomfort	Anxiety/ Depression
No problems	943	990	1040	763	988
Slight problems	114	74	38	256	91
Moderate problems	25	22	9	65	12
Severe problems	7	4	5	8	2
Extreme problems	4	3	1	1	0

Furthermore, the study revealed a significant impact of chronic diseases on patients’ self-rated health. Of the 1093 individuals surveyed, 454 had been diagnosed with chronic diseases. Data analysis revealed that individuals with a single chronic disease achieved an average PPIC score of 70.99 (n = 294, SD = 13.267). In contrast, those with two chronic diseases scored 73.12 (n = 113, SD = 15.243), and individuals with three chronic diseases(those with diseases above three were excluded due to limited quantity)with an averaged a score of 78.80 (n = 35, SD = 13.299).

3 Statistical analyses

This study conducted a comparative analysis of patients’ perceived effectiveness using both the t- test and ANOVA. Significant disparities emerged among respondents across various demographic categories, such as age, education level, income, and health status, underscoring the multifaceted nature of their perceptions. However, no significant differences were observed based on pilot city, residential location, or gender. There were substantial differences in the perception of integrated services between respondents with chronic diseases and those without chronic diseases (t = 8.838, P < 0.001).

To further understand the factors influencing patients’ PPIC perception levels, the study categorized the research subjects into groups based on demographic information and health status across various dimensions (such as activity level and illness condition). Subsequently, as illustrated in Table 3. (In the end of this manuscript) One-way analysis of variance (ANOVA) was recruited to examine the differences among these groups. Intergroup differences in occupation (F = 4.147, P < 0.001), income level (F = 6.327, P = 0.002), and education level (F = 9.942, P < 0.001) were found for patients’ evaluations of integrated service effectiveness.

Table 3

ANOVA of patient perceptions of integrated care services based on demographic information and health-related factors (n = 1093)
Measures	M ± SD	F/F’	P-value
Age		15.999	< 0.001
18–30	61.60 ± 14.42
31–45	61.94 ± 15.94
46–60	67.06 ± 13.80
61–75	71.03 ± 13.35
> 75	69.69 ± 13.31
Occupation		4.147	< 0.001
Farmer	68.29 ± 14.54
Self-employed	68.12 ± 11.87
Industrial/Commercial/Service	64.67 ± 12.93
Government/Institution/Enterprise	55.53 ± 20.25
Professional/Technical	63.38 ± 13.66
Retired	70.33 ± 11.46
Other	66.82 ± 14.39
Education		9.942	< 0.001
Primary school or below	70.08 ± 12.67
Junior high school	66.37 ± 15.18
High school	67.36 ± 14.65
Bachelor or above	62.05 ± 16.98
Health status		4.036	0.004
Poor	76.71 ± 17.10
Fair	68.31 ± 16.18
Good	65.61 ± 14.42
Very good	67.51 ± 12.86
Excellent	68.97 ± 13.45
Economic income level		6.327	0.002
Below 1000 RMB	68.05 ± 13.61
1001–3000 RMB	68.39 ± 15.26
3001–5000 RMB	66.92 ± 14.90
Above 5000 RMB	56.94 ± 15.29
Frequency of smoking		6.503	0.002
Never smokers	67.57 ± 14.38
Current smokers	66.15 ± 13.76
Ex-smokers	73.47 ± 15.69
Frequency of drinking		3.356	0.035
Never drinkers	67.83 ± 14.11
Current drinkers	66.02 ± 14.85
Ex-drinkers	71.63 ± 17.31
Frequency of patient inquiry		48.581	< 0.001
Never	52.80 ± 16.68
Rarely	57.98 ± 14.95
Sometimes	63.92 ± 13.65
Often	69.63 ± 11.89
Always	75.80 ± 13.20
Health services duration		27.913	< 0.001
Less than one year	46.45 ± 16.66
1–2 years	62.35 ± 16.32
2–3 years	69.85 ± 15.83
Three years and above	68.92 ± 13.30

Furthermore, the intergroup variances of health-related factors, such as health status (F = 4.036, P = 0.004), duration of chronic diseases (F = 23.725, P < 0.001), frequency of patients’ health inquiries (F = 45.581, P < 0.001), frequency of drinking (F = 23.725, P = 0.002) and smoking (F = 6.503, P = 0.002), were validated through statistical analysis, which revealed significant intergroup differences. Despite a marginal upward trend in PPIC scores observed with increasing chronic diseases, the differential analysis conducted by grouping chronic diseases did not yield statistically significant results.

Multiple linear regression analysis

A multiple linear regression model was recruited to explore the critical factors that influence patients’ perceptions of integrated care services. Demographic characteristics and health-related factors, which may influence patients’ perceptions, were all considered. The residuals indicated approximate independence, with an adjusted R-squared value of 0.296 for the model. Subsequently, as shown in Table 4 below, the research identified nine covariates as statistically significant and were integrated into the model (F = 22.876, P < 0.001).

Table 4

Multiple linear regression analysis on the patient perceptions of integrated care services based on Demographic information factors and Health-related factors (n = 1093)
Categories	Items	B	SE	t	P-value
Demographic information factors	Constant term	30.945	5.351	5.783	< 0.001
	Age (years)	1.298	0.496	2.615	0.009
	Occupation
	Farming	Ref
	Government/Institution/Enterprise	-7.546	2.393	-3.153	0.002
	Retired	3.462	1.474	2.349	0.019
	Marital status
	Single/Widow/Divorced	Ref
	Married/In a relationship	1.623	0.534	3.037	0.002
	Educational level
	Primary school	Ref
	Junior high school level	-1.818	0.974	-1.866	0.062
Health-related factors	Self-rated health score	-0.073	0.032	-2.260	0.024
	Duration of chronic disease	1.247	0.231	5.403	< 0.001
	Duration of integrated health service	3.244	0.549	5.904	< 0.001
	Frequency of health interactions	5.346	0.371	14.419	< 0.001

Notably, several factors within the model positively affected the evaluation of integrated services. Age (B = 1.298, P = 0.009) positively correlated with service evaluation, indicating that older individuals tended to rate the services more favorably. Conversely, self-rated health status (B = -0.073, P = 0.024) negatively influenced personal perceived service effectiveness, indicating that individuals with better health status prefer to rate the integrated service lower. On the other hand, health-related factors, such as the duration of Integrated health service (B = 3.244, P < 0.001) and the duration of chronic disease (B = 1.247, P < 0.001), both demonstrated a supportive effect on the evaluation outcomes. Specifically, the frequency of active consultation the doctors (B = 5.346, P < 0.001) provided the most decisive beneficial influence on service perception.

Additionally, we categorized marital status, employment status, and education level as dummy variables. It was found that being married or in a relationship (B = 1.623, P = 0.002) was associated with more favorable evaluation of service perceptions than being widowed or single. Respondents in government or other public service roles (B = -7.546, P = 0.002) tended to evaluate the services less favorably than did those employed in farming occupations. However, the retired group (B = 3.462, P = 0.019) reported higher satisfaction with the service outcome.

1 Perceptions and reflections on integrated services effectiveness

In this study, comprehensive patient interviews and surveys were conducted in the sampled area. The average score of integrated care services effectiveness from the patients’ perspective was 67.72 points, which is moderate, indicating a significant scope for further enhancement in service efficacy. Various factors, such as socioeconomic development levels and healthcare service orientations, influence the effectiveness of integrated care services. Challenges in integration stem from system complexity, weak interconnections among professionals and organizations, insufficient funding incentives for collaborative efforts, and bureaucratic management styles. These findings are consistent with previous research conducted in Canada[26]. These obstacles hinder seamless coordination and collaboration, which are essential for delivering comprehensive and patient-centered care.

Furthermore, the scores across various dimensions of the PPIC scale revealed that patient-centered care principles have garnered commendable levels of patient satisfaction. On the one hand, collaborative efforts among diverse healthcare service teams facilitated through training, guidance, and mutual support have contributed significantly to elevated patient satisfaction level. Such progress is closely intertwined with governmental initiatives and incentives to foster the integration of medical services. On the other hand, general practitioners typically reside within contracted areas, maintaining favorable interactions with residents, fostering long-standing relationships built on trust with patients, and facilitating the delivery of health services by the team, mainly contributing to the high scores observed in the subdimensions of patient familiarity and patient-centeredness. This finding has been validated by Baxter et al.[27, 28]. Furthermore, enhancing the accessibilityof healthcare services[28] could hold substantial significance in meeting the escalating health needs and boosting patient satisfaction.

There may need to be more than structural integration to deliver care perceived as integrated by patients[29, 30]. Diverse integration approaches can lead to varied perceptions among populations, as seen in England’s pilot programs [14], which utilize different strategies for integrating care for specific target groups. While some patients’ experiences improved, others saw no change or worsened outcomes. Respondents’ assessments of “internal coordination” and “interaction and collaboration with local communities” within the integrated service teams were relatively subdued. Notably, integrated care teams have yet to optimally leverage their members’ diverse skill sets and expertise, with coordination within medical teams predominantly led by general practitioners, thereby underutilizing the potential contributions of other team members, such as nurses and public health professionals.

Conspicuous deficiencies in personnel allocation within medical service teams, particularly in teams operating below the township level, have been observed. Personnel within these teams often find themselves stretched across multiple roles, leading to compromised delivery of primary health services. This disparity highlights an inadequate integration of service capabilities, further exacerbated by a need for more specialized professionals in public health and traditional Chinese medicine. These findings align with concerns raised by Li regarding the potential forthcoming shortage of village doctors, as the aging and turnover of village doctors could seriously threaten the primary healthcare workforce [16]. Addressing this disparity is imperative for enhancing integration with local community resources and elevating coordination between care teams and community resources, which currently needs to catch up to optimal levels[31].

Respondents expressed dissatisfaction with the internal coordination of service teams, while highly rating the collaboration between different health service teams. Suggesting that health service teams at different levels collaborate through various means, such as skill training and business guidance, supporting each other in providing services to contracted residents. Such collaboration is closely intertwined with government initiatives promoting integration and incentivizing collaborative efforts within medical communities. Therefore, it is crucial to consistently prioritize patient-centeredness and expedite the training and deployment of skilled professionals to ensure the uniform proficiency of service teams[32]. Enhancing the integration of healthcare service teams with local community resources will significantly elevate patients’ perceptions of integrated services, thus fostering a heightened sense of health attainment among residents[33].

2 The impact of social and personal health factors on perceptions of integrated care

Research has unveiled nuanced relationships between patient demographics and perceptions of integrated care, highlighting a complex interplay between social factors, personal health, and service evaluations. Occupation, education, and income are pivotal social determinants that dictate access to health care and influence the affordability and perceptions of integrated care. Similarly, an individual’s health status and access to healthcare resources are critical in shaping their views on integrated care services[34–36].

An exciting finding is the more positive evaluations from older participants, which likely stems from the alignment of integrated services with their escalating healthcare needs due to aging. Contrary to expectations, a subtle negative correlation exists between respondents’ positive health self-assessments and their evaluations of integrated care’s effectiveness. This suggests that those with poorer health perceptions are more inclined to appreciate the value of integrated care. While integrated care teams have successfully addressed a wide range of health needs—garnering positive feedback—individuals in better health or with higher socioeconomic status exhibit more critical perspectives. This divergence appears to be driven by a mismatch between the expectations of these individuals and the primary health interventions typically offered by integrated care teams, leading to diminished satisfaction levels[37]. The underlying causes of this phenomenon likely align with findings from a cross-racial study, which revealed that Black and Hispanic beneficiaries perceived higher levels of integrated care compared to White beneficiaries[38]. Such disparity is closely associated with patients’ socioeconomic status and accessibility to health services among different demographic groups.

Moreover, the research indicates that a patient’s acceptance of health interventions is influenced by the duration of the illness and the frequency and duration. An increase in these factors correlates with improved perceptions of care, underscoring evaluations based on tangible health benefits derived from integrated care. Nevertheless, if integrated care service effects are imperceptible or fail to meet patient needs adequately, satisfaction will likely wane. Thus, to address these varied outcomes, medical providers must holistically consider patients’ health statuses and specific needs for health services, which is essential for optimizing service delivery and enhancing patient satisfaction[39].

Integrated services should focus more on populations with greater health needs, such as chronic disease patients whose lives are significantly affected by illness. Our study revealed that patients diagnosed with chronic diseases generally provided more positive feedback regarding the effectiveness of integrated care services than did those without chronic conditions. This underscores the significant impact of integrated care interventions on enhancing the perceived health outcomes among chronic disease patients, thereby addressing their specific healthcare needs more effectively[40]. Additionally, there was a noticeable trend within the chronic disease patient population: as the number of chronic comorbidities increased, patients tended to report higher levels of satisfaction with integrated services. This may indicate that comorbidity groups are eager for greater health demands, which aligns perfectly with the original intention of the scale authors: “Theoretically they were the most likely to benefit from improved integration, patients with higher needs perceived more, rather than less, integrated care”[41].

It was found that patients have expressed concerns over challenging navigation systems, frustration due to services not aligning with their individual needs, and a noticeable absence of support to boost their health literacy[42]. It is vital to customize services based on the unique health requirements of different patient groups. For example, residents who were widowed, primarily older individuals, provided poorer overall feedback on integrated services. Widowhood is considered one of the most distressing transitions experienced by older adults. Considering that widowed individuals lack effective ways to receive the life care, social support, and emotional solace typically provided by a spouse, this may be attributed to complex emotional reasons[43–45]. Previous research has shown that marital status significantly influences residents, while our study found that integrated care services have yet to satisfy this demographic substantially. By prioritizing patient-centered care and offering tailored health interventions, healthcare delivery can be optimized to address the complex needs of patients better, ultimately leading to improved effectiveness and patient satisfaction[28]. Thus, attention should be given to individuals newly diagnosed with diseases, gradually increasing their self-health intervention capabilities to alleviate their initial anxiety and tension associated with the diagnosis. Simultaneously, for healthy, people who generally have good health status and do not require extensive health interventions, services such as medication guidance and follow-ups can be provided, with a focus on health testing and disease prevention, thus saving more human and material resources and reducing healthcare inequality[46].

In the future, fundamental reforms of integrated services in pilot areas should be undertaken in several key areas. First, effective communication between healthcare providers and patients must be enhanced to build stronger, long-lasting trust[47]. Additionally, information technology could be applied to enhance organizational management capabilities and promote collaboration among teams. Finally, expanding incentives to attract more skilled professionals and clarifying individual responsibilities would significantly foster stronger teamwork. These measures collectively aim to elevate the quality of integrated care services, ultimately ensuring that patients receive better holistic medical care.

Limitations

While this study has illuminated several issues within the field, it is essential to acknowledge its limitations. First, our sample was cross-sectional, constraining our ability to infer causation. Moreover, the issues identified in this study may only partially reflect the situation in the pilot areas. Future research could address this limitation by extending the study’s duration and increasing the number of pilot sites, thereby gaining deeper insights into the effectiveness of integrated services. Second, our study primarily focused on assessing the effectiveness of integrated services from the patient’s perspective. However, existing research suggests that the structural characteristics of medical teams may have a limited impact on patients’ perceptions of integrated care[48, 49]. Given the unique context of healthcare reform and medical insurance payments in China, further investigation is warranted to explore whether the characteristics and overall service capabilities have specific effects on patients’ perceptions of integrated services.

This study highlights a notable discrepancy between patients’ perceptions and expectations regarding integrated services, emphasizing the critical importance of patient-centered care in the integration process. This underscores the necessity of personalized health services catering to individual needs. Specifically, greater attention should be directed towards residents with chronic diseases or comorbidities, ensuring that their unique health requirements are adequately addressed within integrated care frameworks. Moreover, there is a pressing need to develop more robust communication and management mechanisms to facilitate seamless collaboration among healthcare teams. By enhancing coordination and information sharing, healthcare professionals can optimize the delivery of integrated care services, improving patient outcomes and experiences.

In conclusion, prioritizing patient-centered approaches, tailoring services to individual health needs, and strengthening communication and management mechanisms are essential to maximizing the benefits of integrated health care. These efforts will contribute to providing comprehensive health services and ultimately enhance patients’ overall quality of care.

PPIC Patient Perception of Integrated Care

EQ-5D-5L European Quality of Life-5 Dimensions-5 Levels

EQ-VAS European Quality of Life-Visual Analog Scale

CAHPS Consumer Assessment of Healthcare Providers and System

Authors’ contributions

H.K., Y.G. and H.B. contributed to the design of this study. H.K. led the writing for the manuscript and drew all the figures and tables. H.K., Y.G. and X.Y. completed questionnaire translation and data collection. X.Y. performed the validation of questionnaire. H.B. supervised the project. All authors reviewed and revised the manuscript and agreed to the submission of the final manuscript.

Acknowledgements

We would like to thank the patients and all the integrated care team members who participated in this study.

Authors’ details

¹School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou district, Wuhan 430030, Hubei, China

²Research Center for Hospital Management and Development, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou district, Wuhan 430030, Hubei, China

Ethics approval and consent to participate

The study was conducted in accordance with the principles established in the Declaration of Helsinki. It primarily focused on patients’ perceptions of integrated care services, with participation being entirely voluntary and anonymous during data collection. Hence, formal approval from the ethical review authority was deemed unnecessary. We ensured that informed consent was obtained from all participants, and strict measures were taken to maintain the confidentiality of participant data throughout the research process. All surveys received approval from School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the National Natural Science Foundation of China, Grant No. 7207041637.

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No competing interests reported.

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The determinants of patient perceptions of integrated care: Evidence from tightly-knit county medical community in China

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Abstract

Purpose

Methods

Results

Conclusions

Figures

Background

Materials and Methods

The Scale of Patient Perceptions of Integrated Care (PPIC)

The scale of the European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L)

Data collection

Data analysis

Results

1 Demographic information

2 Descriptive analyses of PPIC scores and Health Status

Analysis of the PPIC total score and sub-dimensions

Self-rated health status of respondents

3 Statistical analyses

Multiple linear regression analysis

Discussion

1 Perceptions and reflections on integrated services effectiveness

2 The impact of social and personal health factors on perceptions of integrated care

Limitations

Conclusions

Abbreviations

Declarations

Authors’ contributions

Acknowledgements

Authors’ details

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

References

Additional Declarations

Supplementary Files

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