成人头条

Skip to main content
Download PDF
  • Research
  • Published:

Impact of the family doctor system on medication adherence among type 2 diabetes patients in China: a difference-in-differences analysis

成人头条 volume听25, Article听number:听404 (2025) Cite this article

Abstract

Background

Nonadherence to medication is a prevalent issue among patients with type 2 diabetes mellitus (T2DM). The family doctor system promotes continuous, integrated, and personalized primary care, which may improve medication adherence. However, more evidence is needed regarding causal association between family doctor system and medication adherence. This study is to assess the impact of the family doctor system on medication adherence among T2DM patients.

Methods

This cohort study utilized data between 2014 and 2019 from three separate administrative databases of an eastern city in China. Adult patients with T2DM who continuously registered with family doctors from 2015 to 2019 (n鈥�=鈥�18,841) were assigned to the intervention group, while those who never registered during this period (n鈥�=鈥�1,429) were classified as the control group. A difference-in-differences design was employed to compare medication adherence between registered and unregistered T2DM patients after the first stage of family doctor system in 2015 and the second stage in 2018. Propensity score matching was applied to ensure the robustness. The mean proportion of days covered (PDC), and proportion of patients with good adherence (PDC鈥夆墺鈥�80%) were the outcomes of interest. All recommended T2DM medications were included to calculate PDC.

Results

Compared to the unregistered group, PDC across all institutions for registered patients increased by 5.0% (p鈥�<鈥�0.001) after the first stage of family doctor system, and by 5.9% (p鈥�<鈥�0.001) after the second stage. The proportion of patients with good adherence increased by 9.5% (p鈥�<鈥�0.001) and by 11.8% (p鈥�<鈥�0.001) after two stages, respectively. The adherence improvement was more pronounced in community health centers. However, the overall good adherence rate among registered patients in 2019 remained relatively low, reaching only 59.77%.

Conclusions

The family doctor system significantly improved medication adherence among T2DM patients by providing patient-centered, continuous, and integrated primary services, especially in community health centers. Nevertheless, further efforts should be made to enhance medication adherence.

Peer Review reports

Introduction

Diabetes remains a major public health challenge worldwide, contributing to a significant burden of disease [1, 2]. In 2021, an estimated 529听million people were diagnosed with diabetes, 96% of whom had type 2 diabetes mellitus (T2DM), with global diabetes-related expenditures reaching US$966 billion [1, 3]. In China, diabetes prevalence rose markedly from 10.9% in 2013 to 12.4% in 2018, while only 50.1% of treated patients achieving adequate control [2]. This inadequate control is particularly concerning, as diabetes is significantly associated with increased risk of both all-cause and cardiovascular disease mortality [4].

Long-term adherence to medication is critical for diabetes management. Numerous studies have demonstrated that higher adherence is associated with decreased hospitalization and mortality among diabetes patients [5, 6]. However, nonadherence to medication remains a widespread challenge globally [7, 8], approximately one in three T2DM patients failing to adhere to their prescribed regimen [7, 9]. The rates of nonadherence are even higher in China, approaching 50% [10,11,12]. Therefore, targeted interventions are urgently needed to improve medication adherence in China, enabling patients to fully benefit from prescribed therapies [13].

China introduced the family doctor system in 2016, followed by a series of policies to support its development [14]. Under this system, citizens voluntarily register with family doctor teams at nearby community health centers (CHCs) on an annual basis [15]. Registered individuals receive continuous, integrated, and personalized primary medical care, public health services, and health management from their family doctor teams [16]. Standardized management and follow-up of patients with chronic diseases represent a core responsibility of family doctor teams. Family doctors should contact all registered patients with diabetes or hypertension at least once every three months. Although specific measures may vary across cities, registered residents typically benefit from four key areas. First, registered individuals have access to more convenient services, including full-cycle care, home visits, and other forms of support. Second, patients in need can receive priority referrals and hospitalization. Third, family doctors have the discretion to extend the amount of medication dispensed per visit for registered patients with chronic conditions and provide prescription refills for those referred to CHCs. Fourth, patients referred for hospitalization who meet the criteria can have their deductible calculated continuously. Registered individuals are entitled to a higher proportion of medical insurance reimbursement when seeking care at CHCs.

Patients freely choose healthcare providers in China. These benefits encourage more registered individuals to initially seek health services from their family doctors, thereby establishing a continuous patient-provider relationship. This relationship can enhance adherence by creating conditions that foster better support for individuals in understanding and managing their conditions [17]. Additionally, the World Health Organization (WHO) asserts that primary health care plays a crucial role in chronic disease management [18]. The family doctor system, as a flexible gatekeeper in primary care, provides registered T2DM patients with patient-centered services and consistent follow-up, which may facilitate self-management and improve medication adherence [13, 17]. Previous studies have demonstrated a positive association between patient-centered primary care and improved medication adherence across different countries. For example, in the United States, medication adherence among chronic disease patients receiving care in patient-centered medical homes was significantly 2.2% higher than that of patients receiving care from general primary care providers in the same area [19]. In South Korea, medication adherence rates among participants in the Control and Prevention Community-based Registration and Management for Hypertension and Diabetes Mellitus Project increased more rapidly after enrollment compared to the control groups, with these improvements sustained throughout the follow-up period [20].

Existing research in China has investigated medication adherence among T2DM patients [12] and identified various factors associated with adherence, including perceived satisfaction with community health services, beliefs about medications [10, 21,22,23]. Only a few studies have focused on the impact of interventions, such as online health education programs and pharmacist-led initiatives, on medication adherence among T2DM patients [11, 24]. Overall, evidence on the causal relationship between the family doctor system and medication adherence remains scarce. The goal of this study was to estimate the impact of family doctor system on medication adherence. We hypothesized that the family doctor system in China significantly promotes medication adherence among patients with T2DM.

Methods

Setting

City A is a developed urban center located in eastern China, with a resident population of 9.81听million at the end of 2018. In the same year, the city鈥檚 per capita Gross Domestic Product was 140,180 CNY (approximately US$21,184 based on the average exchange rate). By the end of 2018, City A had 5,377 medical and health institutions of various types, including 1,304 CHCs.

City A has been a pioneer in implementing the family doctor system. The development of its family doctor system can be divided into two stages. In 2015, the city first established the family doctor system to provide integrated medical, nursing, and caregiving services for residents, with a particular focus on seniors and individuals with chronic diseases. During this period, family doctors delivered health management services, primary care, referral services, home-based care, remote health monitoring services, and physical examination for registered residents. After 2018, the city developed the family doctor system, expanding the range of health services. One example is a long-term prescription policy, allowing participants with chronic diseases to receive prescriptions lasting from four to twelve weeks. The progression of the family doctor system in City A is detailed in Fig.听1.

Fig. 1
figure 1

Services provided by the family doctor system across two stages

Full size image

Continuous refinement has led to the development of a well-established family doctor system in City A, comprising over 2,000 family doctor service teams. The number of participants in City A increased from 0.51听million in 2015 to 3.04听million in 2019, covering approximately 30% of the city鈥檚 population, with nearly 70% of participants being elderly or individuals with chronic diseases [16].

Data source

This cohort study utilized data from three distinct databases, which can be linked using anonymized unique patient identifiers. First, chronic disease management data from the Health Commission of City A, covering January 2014 to December 2019, was used to identify patients with T2DM. Their sociodemographic information for 2014, 2016, and 2019 was also extracted. Second, the family doctor registration database from 2014 to 2019, managed by the Healthcare Security Administration of City A, was linked with chronic disease management data using patient identifiers to determine registration status. This linkage established groups of registered and unregistered patients. Third, prescription records from 2014, 2016, and 2019 for the study population were retrieved from the medical insurance claims database and integrated with the other two databases to assess medication adherence. There are no missing data. The Ethics Review Committee of the School of Public Health, Fudan University approved our study (IRB#2023-TYSQ-02-261) to ensure compliance with local regulations. Although patient identifiers were used for linking databases in this study, the informed consent process was waived, as the identifiers have been desensitized, the research involves minimal risk, and the data is used solely for analysis, as determined by the Committee.

Study population

The study identified all patients diagnosed with T2DM in City A before January 2015 according to ICD-10. Inclusion criteria for enrollment were as follows: (1) patients diagnosed with T2DM (ICD-10 code E11) before January 2015; (2) patients aged more than eighteen years old; (3) patients who continuously registered with family doctors for the entire 5-year period from 2015 to 2019, and those who were not registered at any point during this period; (4) patients with social medical insurance, either urban employee basic medical insurance (UEBMI) or urban-rural resident basic medical insurance (URRBMI); (5) patients who had prescriptions for diabetes each year in 2014, 2016, and 2019. Participants were classified into the registered group or the unregistered group based on their enrollment status in the family doctor system.

Outcomes

The primary outcome was the change in medication adherence for each eligible registered T2DM patient. The proportion of days covered (PDC) was calculated as the number of days with medication on hand divided by the number of days in the specified time interval [25], which was applied to assess the medication adherence [23, 26, 27]. To measure PDC, we first generated outpatient prescription doses for each type of diabetes drug based on specifications and volume. Second, the sum of days covered by each type of diabetes drug was calculated according to defined daily dose (DDD) obtained from the WHO. Third, the number of days a patient was covered by at least one diabetes drug was counted based on prescription date and days of supply. Specifically, we focused on the medication that provided the longest coverage during the prescription period. For refills, the start date for the days supplied was deferred until the supply from the previous prescription was fully exhausted, in order to account for any overlap between prescriptions [28]. Finally, PDC is calculated as PDC = (Sum of days covered in one year) / (days in one year) [29]. PDC was used as both a continuous (primary outcome) and binary categorical measure of adherence, with PDC above a threshold of 80% considered optimal [30].

Our study included 9 types of diabetes medications recommended by clinical guidelines, including metformin, sulfonylurea, 伪-glucosidase inhibitor, thiazolidinedione (TZD), meglitinides, dipeptidyl peptidase鈥�4 inhibitor (DPP4i), glucagon-like peptide-1 receptor agonist (GLP-1RA), sodium-dependent glucose transporters 2 inhibitor (SGLT2i), and insulin [31].

Covariates

We combined several covariates in our analysis to control the sociodemographic characteristics and health status of patients, including age, gender, comorbidities (n鈥�=鈥�0 or n鈥�=鈥�1 or n鈥夆墺鈥�2), type of medical insurance (UEBMI or URRBMI), and body mass index (BMI). The BMI of patients was considered in three levels: normal (18.5听kg/m2鈥夆墹鈥塀MI鈥夆墹鈥�23.9听kg/m2), above normal (BMI鈥�>鈥�23.9听kg/ m2), and below normal (BMI鈥�<鈥�18.5听kg/m2). All of these covariates were incorporated into each model.

Statistical analysis

A difference-in-differences (DID) approach was employed to assess the impacts of two stages of the family doctor system on medication adherence among diabetes patients in City A by comparing adherence in 2016 with 2014 and 2019 with 2014. The models included a dummy variable representing groups that was equal to 1 if the patient had registered with a family doctor, and a dummy variable for time that was equal to 1 for implementation of either the family doctor system or its developed version in 2016 or 2019. The outcome variables were both continuous and dichotomous measures of PDC. Age, gender, comorbidities, insurance types, and BMI class were the controlled individual characteristics. The primary parameter of interest, the DID estimator, represented the interaction effect, capturing the impact of either the family doctor system or its developed version on medication adherence.

Propensity score matching

The DID approach requires meeting the parallel trend assumption. However, since we only had data for one year prior to the intervention, a formal parallel trends test could not be conducted. To address this limitation, propensity score matching (PSM) was employed to increase the likelihood that the registered and unregistered groups exhibited similar adherence trends during the pre-intervention period [32]. To ensure the robustness of results, additional DID estimates were established with a 1:1 PSM using nearest neighbor estimation with replacement. Five variables were adopted to match patients in the registered group with the unregistered group, including age, gender, comorbidity class, insurance types, and baseline BMI class.

Results

Among the 20,270 T2DM patients included in this cohort study, 18,841 (92.95%) patients who had registered with family doctor teams for 5 years were assigned to the registered group, while 1,429 (7.05%) patients who had not registered were placed in the unregistered group. The average age of the cohort was 67.75 years, and 44.64% of the cohort were male. Most patients were enrolled in the UEBMI, with normal or below-normal baseline BMI. The majority of patients had a single comorbidity, with 91.35% of them having hyperlipidemia and hypertension (eTable听1 in Supplement). A comprehensive description of the sociodemographic characteristics by group is provided in Table听1. After PSM, no significant differences were observed in age, gender, type of medical insurance, or BMI. Only the number of comorbidities remains different between the groups (eTable听2 in Supplement). There was sufficient overlap in the propensity score distributions between the registered and unregistered groups (eFigure 1 in Supplement).

Table 1 Baseline characteristics of patients in each group
Full size table

Proportion of days covered

PDC displayed a sustained improvement during the observation year. The PDC of outpatient T2DM medications in all health institutions rose from 62.07% in 2014 to 73.22% in 2016 and 76.85% in 2019. Similarly, the PDC in CHCs also showed an upward trend, increasing from 54.76% in 2014 to 69.21% in 2016 and 74.07% in 2019.

The registered group exhibited greater increases in PDC compared to the unregistered group following both stages of the family doctor system implementation. Over 50% of the medications for diabetes patients were obtained from CHCs, with this proportion being higher among individuals enrolled in the family doctor system (Table听2).

Table 2 Medication adherence of outpatient T2DM medications in 2014, 2016, and 2019 (%)
Full size table

Medication adherence level

An increasing proportion of T2DM patients demonstrated good medication adherence (PDC鈥夆墺鈥�80%). The proportion of good adherence patients in all institutions was 32.99% in 2014, 49.79% in 2016, and 58.78% in 2019. Similarly, the proportion of patients with good adherence in CHCs increased from 25.87% in 2014 to 44.93% in 2016, and 56.07% in 2019. The proportion of good adherence patients in the registered group increased more rapidly than in the unregistered group.

DID estimation

Two-stage family doctor system significantly improved PDC in both all health institutions and CHCs, with a more pronounced improvement observed in CHCs. After adjusting for covariates, the PDC in all institutions among registered patients increased by 5.0% (p鈥�<鈥�0.001), while the PDC in CHCs increased by 5.5% (p鈥�=鈥�0.003) during the first stage, compared to unregistered patients. In the second stage, the PDC across all institutions among registered patients increased by 5.9% (p鈥�<鈥�0.001), and by 8.1% (p鈥�<鈥�0.001) in CHCs (Table听3).

Table 3 Adherence before and after family doctor, DID estimates
Full size table

Similarly, the family doctor system also enhanced the proportion of patients demonstrating good adherence. Following registration with family doctors, the proportion of registered patients with good adherence to T2DM medications increased by 9.5% (p鈥�<鈥�0.001) across all institutions, and by 11.9% (p鈥�<鈥�0.001) in CHCs. Furthermore, the second-stage family doctor system led to additional improvements in adherence in both overall institutions and CHCs. The proportion of patients with good adherence to T2DM medications in all institutions in the registered group increased by 11.8% (p鈥�<鈥�0.001), while at CHCs, it increased by 19.3% (p鈥�<鈥�0.001).The PSM-DID results were consistent with the DID analysis, demonstrating the credibility of our findings (eTable 3 in Supplement).

Discussion

This study established a large cohort of 20,270 T2DM patients from 2014 to 2019, including all recommended medications for T2DM, to evaluate the long-term impact of the family doctor system on medication adherence. To the best of our knowledge, this study represents a significant contribution to the existing literature, as it is the first to demonstrate the positive impact of the family doctor system in an eastern Chinese city on medication adherence, particularly within CHCs. We also observed that the proportion of registered patients with good medication adherence in 2019 was still only 59.77%, which remained relatively low compared to developed countries.

Following the implementation of both stages of family doctor system in City A, the PDC and good adherence rate among registered patients showed significant improvement. These findings are consistent with relevant international studies. A South Korean study showed that implementing a chronic disease management program in primary clinics enhanced adherence by 6.10% and the cumulative persistence rate by 10.80% in patients with diabetes. The increase in adherence was even more significant for patients who consistently visited the same clinic [33]. Similarly, an Italian study revealed that family physician participation in a local diabetes management program improved patient adherence and positively impacted patient health outcomes and health service utilization [34].

Discontinuous and decentralized healthcare are key factors associated with medication nonadherence. Discontinuous services are always related to weak doctor-patient relationships characterized by inadequate communication [35]. This can result in doctors prescribing medications that are not appropriate for patients鈥� comprehensive health condition, or their social and financial circumstances [36]. Fostering good communication between patients and doctors has proven to be an effective strategy to improve adherence [37]. Registration with family doctors encourages long-term, stable doctor-patient relationships, allowing doctors to follow up on patients鈥� health status and provide them with safe, convenient, effective, continuous, cost-effective, and personalized health management [38]. Additionally, insufficient communication among providers in decentralized healthcare systems also exacerbates nonadherence [39, 40]. In City A, residents register with a family doctor team rather than with an individual family doctor. The family doctor teams is primarily composed of family doctors, and may also include community nurses, public health doctors, specialists, and other healthcare professionals. This team-based structure facilitates the delivery of integrated medical-caregiving services. Moreover, the family doctor system in City A seeks to promote the establishment of a hierarchical healthcare system. By addressing issues of discontinuity and decentralization, the family doctor system effectively improved medication adherence among T2DM patients, providing valuable insights for other developing countries.

The medication adherence level of our cohort was similar to that of other domestic studies, but lower than that of some international studies. In this study, the PDC of T2DM patients in all health institutions ranged from 62% to 77%, with the proportion of patients with good medication adherence between 33% and 59%. The proportion of high PDC in another Chinese cohort was concentrated around 50鈥�60% across different diabetes drug classes, similar to our findings [12]. However, studies conducted in the United States and Canada have reported that the average PDC for diabetes patients ranged from 61鈥�87% [41,42,43], and the overall range of good medication adherence was 58鈥�81% [44,45,46,47]. In contrast, the medication adherence level among patients with T2DM in this study was lower. Several factors likely contribute to this discrepancy, including medication costs, follow-up rates, and health literacy [48,49,50]. Although some innovative drugs, such as SGLT2i and GLP-1RAs, were included in social medical insurance after 2019, their high costs during the study period may have contributed to the financial barriers to medication adherence. Moreover, the family doctor system in China functions more as a soft constraint rather than a strict gatekeeper. Patients are not required to consult their family doctors before visiting a specialist. Consequently, the relationship between family doctors and patients remains relatively weak, leading to inadequate patient follow-up. In addition, a previous investigation in China found that patients, particularly seniors, still exhibit poor health literacy, which is associated with lower adherence [50]. To improve medication adherence within the Chinese family doctor system, policy frameworks should be refined to foster a stronger relationship between patients and their family doctors. Furthermore, family doctors could offer more comprehensive health education to patients through the integration of advanced technologies. Strengthening continuity and integration in primary care could optimize patient-centered chronic disease management and improve adherence.

This study has several limitations. First, the volume of drugs purchased from pharmacies was not included in this study, which caused underestimation of the PDC and the proportion of patients with good adherence. Second, the DDD offered by the WHO was an average at the clinical level, which was unable to reflect specific medications among patients. Third, the city included in this study is one of the most developed in China, with a more advanced healthcare system, wealthier and better-educated citizens, and a more effective policy design and implementation. Therefore, the results of this study may not be generalizable to other cities in China. Fourth, the observation period after the second stage of family doctor system in City A was limited, and it is important to continue to follow up in the future. Fifth, due to the limited observation time, parallel trend test cannot be conducted. However, we have mitigated this limitation by establishing PSM-DID models to ensure the reliability of our results. Sixth, as registration with family doctor was voluntary, this may introduce selection bias. Seventh, the study obtained prescription records of only the study population, limiting the ability to conduct sensitivity analyses based on a larger cohort of patients registered for 1鈥�4 years.

Conclusion

This study demonstrates that family doctor system and its developed version significantly improves the adherence to medication among type 2 diabetes patients, especially in CHCs. The continuity and integration of healthcare facilitated by the family doctor system are crucial factors that enhance adherence. Nevertheless, medication adherence in China remains relatively low compared to that in developed countries. To improve medication adherence, further efforts should be made to optimize continuous primary care, with an emphasis on fostering stronger relationships between patients and their family doctors, as well as providing more high-quality chronic disease management.

Data availability

The data that support the findings of this study are available from the Healthcare Security Administration and Health Commission of City A, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Healthcare Security Administration and Health Commission of City A.

Abbreviations

BMI:

body mass index

CHCs:

community health centers

DDD:

defined daily dose

DID:

difference-in-differences

顿笔笔鈥�4颈:

dipeptidyl peptidase鈥�4 inhibitor

GLP-1RA:

glucagon-like peptide-1 receptor agonist

PDC:

proportion of days covered

PSM:

propensity score matching

SGLT2i:

sodium-dependent glucose transporters 2 inhibitor

T2DM:

type 2 diabetes mellitus

TZD:

thiazolidinedione

UEBMI:

urban employee basic medical insurance

URRBMI:

urban-rural resident basic medical insurance

WHO:

World Health Organization

References

  1. GBD 2021 Diabetes Collaborators. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the global burden of Disease Study 2021. Lancet. 2023;402(10397):203鈥�34.

    听 听

  2. Wang L, Peng W, Zhao Z, Zhang M, Shi Z, Song Z, et al. Prevalence and treatment of diabetes in China, 2013鈥�2018. JAMA. 2021;326(24):2498鈥�506.

    听 听 听 听

  3. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.

    听 听 听

  4. Tian Y, Qiu Z, Wang F, Deng S, Wang Y, Wang Z, et al. Associations of diabetes and prediabetes with mortality and life expectancy in China: a national study. Diabetes Care. 2024;47(11):1969鈥�77.

  5. Ho PM, Rumsfeld JS, Masoudi FA, McClure DL, Plomondon ME, Steiner JF, et al. Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Arch Intern Med. 2006;166(17):1836鈥�41.

    听 听 听

  6. Shani M, Lustman A, Comaneshter D, Schonmann Y. Overall medication adherence as an Indicator for Health outcomes among Elderly patients with hypertension and diabetes. Am J Med. 2024;137(8):736鈥�41.

    听 听 听

  7. Kirkman MS, Rowan-Martin MT, Levin R, Fonseca VA, Schmittdiel JA, Herman WH, et al. Determinants of adherence to diabetes medications: findings from a large pharmacy claims database. Diabetes Care. 2015;38(4):604鈥�9.

    听 听 听 听

  8. American Diabetes Association. Standards of Care in Diabetes-2023 abridged for primary care providers. Clin Diabetes. 2022;41(1):4鈥�31.

    听 听 听

  9. Capoccia K, Odegard PS, Letassy N. Medication adherence with diabetes medication: a systematic review of the literature. Diabetes Educ. 2016;42(1):34鈥�71.

    听 听 听

  10. Yao J, Wang H, Shao D, Yin J, Guo X, Yin X, et al. Association between availability of glucose-lowering drugs in primary health institutions and diabetes patients鈥� medication adherence: a cross-sectional study in Shandong Province, China. Global Health J. 2021;5(2):83鈥�9.

    听 听

  11. Wu M, Xu X, Zhao R, Bai X, Zhu B, Zhao Z. Effect of pharmacist-led interventions on Medication Adherence and Glycemic Control in type 2 Diabetic patients: a study from the Chinese Population. Patient Prefer Adherence. 2023;17:119鈥�29.

    听 听 听 听

  12. Chong E, Wang H, King-Shier KM, Quan H, Rabi DM, Khan NA. Prescribing patterns and adherence to medication among South-Asian, Chinese and white people with type 2 diabetes mellitus: a population-based cohort study. Diabet Med. 2014;31(12):1586鈥�93.

    听 CAS听 听 听

  13. World Health Organization. Adherence to long-term therapies: evidence for action: World Health Organization. Available at: . Accessed September 26, 2024.

  14. Chen Y, Huang F, Zhou Q. Equality of public health service and family doctor contract service utilisation among migrants in China. Soc Sci Med. 2023;333:116148.

    听 听 听

  15. Zheng Q, Shi L, Pang T, Leung W. Utilization of community health care centers and family doctor contracts services among community residents: a community-based analysis in Shenzhen, China. 成人头条 Fam Pract. 2021;22(1):100.

    听 听 听 听

  16. Liu X, Zhang L, Chen W. Impact of the family doctor system on the continuity of care for diabetics in urban China: a difference-in-difference analysis. BMJ Open. 2023;13(2):e065612.

    听 听 听 听

  17. World Health Organization. Continuity and Coordination of Care: A Practice Brief to Support Implementation of the WHO Framework on Integrated People-Centred Health Services. Available at: . Accessed September 26, 2024.

  18. World Health Organization. Preventing chronic diseases: a vital investment: WHO global report. Available at: . Accessed September 26, 2024.

  19. Lauffenburger JC, Shrank WH, Bitton A, Franklin JM, Glynn RJ, Krumme AA, et al. Association between Patient-Centered Medical Homes and Adherence to Chronic Disease medications: a Cohort Study. Ann Intern Med. 2017;166(2):81鈥�8.

    听 听 听

  20. Choi YJ, Kim YT, Yi HS, Lee SY, Lee WY. Effects of community-based interventions on medication adherence and hospitalization for elderly patients with type 2 diabetes at primary care clinics in South Korea. Int J Environ Res Public Health. 2021;18(7):3396.

  21. Wei L, Champman S, Li X, Li X, Li S, Chen R, et al. Beliefs about medicines and non-adherence in patients with stroke, diabetes mellitus and rheumatoid arthritis: a cross-sectional study in China. BMJ Open. 2017;7(10):e017293.

    听 听 听 听

  22. Wu Y, Xiong S, Zhu G, Chen X, Zhang M, Gong E, et al. Patient, family, and community factors associated with medication adherence among people with hypertension or diabetes: a cross-sectional analysis. Explor Res Clin Soc Pharm. 2024;15:100482.

    听 听 听

  23. McGovern A, Tippu Z, Hinton W, Munro N, Whyte M, de Lusignan S. Comparison of medication adherence and persistence in type 2 diabetes: a systematic review and meta-analysis. Diabetes Obes Metab. 2018;20(4):1040鈥�3.

    听 CAS听 听 听

  24. Zhang B, Kalampakorn S, Powwattana A, Sillabutra J, Liu G. A Transtheoretical Model-based online intervention to improve medication adherence for Chinese adults newly diagnosed with type 2 diabetes: a mixed-method study. J Prim Care Community Health. 2024;15:21501319241263657.

    听 听 听 听

  25. Peterson AM, Nau DP, Cramer JA, Benner J, Gwadry-Sridhar F, Nichol M. A checklist for medication compliance and persistence studies using retrospective databases. Value Health. 2007;10(1):3鈥�12.

    听 听 听

  26. Claxton AJ, Cramer J, Pierce C. A systematic review of the associations between dose regimens and medication compliance. Clin Ther. 2001;23(8):1296鈥�310.

    听 CAS听 听 听

  27. Gellad WF, Grenard JL, Marcum ZA. A systematic review of barriers to medication adherence in the elderly: looking beyond cost and regimen complexity. Am J Geriatr Pharmacother. 2011;9(1):11鈥�23.

    听 听 听 听

  28. Yeaw J, Benner JS, Walt JG, Sian S, Smith DB. Comparing adherence and persistence across 6 chronic medication classes. J Manag Care Pharm. 2009;15(9):728鈥�40.

    听 听

  29. DeClercq J, Choi L. Statistical considerations for medication adherence research. Curr Med Res Opin. 2020;36(9):1549鈥�57.

    听 听 听 听

  30. Asamoah-Boaheng M, Osei Bonsu K, Farrell J, Oyet A, Midodzi WK. Measuring Medication Adherence in a Population-based Asthma Administrative Pharmacy Database: a systematic review and Meta-analysis. Clin Epidemiol. 2021;13:981鈥�1010.

    听 听 听 听

  31. Chinese Diabetes Society, National Office for Primary Diabetes Care. National guidelines for the prevention and control of diabetes in primary care (2022). Chin J Intern Med. 2022;61(3):249鈥�62.

    听

  32. Stuart EA, Huskamp HA, Duckworth K, Simmons J, Song Z, Chernew M, et al. Using propensity scores in difference-in-differences models to estimate the effects of a policy change. Health Serv Outcomes Res Methodol. 2014;14(4):166鈥�82.

    听 听 听 听

  33. Kim JA, Kim ES, Lee EK. Evaluation of the chronic disease management program for appropriateness of medication adherence and persistence in hypertension and type-2 diabetes patients in Korea. Med (Baltim). 2017;96(14):e6577.

    听 听

  34. Ugolini C, Lippi Bruni M, Leucci AC, Fiorentini G, Berti E, Nobilio L, et al. Disease management in diabetes care: when involving GPs improves patient compliance and health outcomes. Health Policy. 2019;123(10):955鈥�62.

    听 听 听

  35. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005;353(5):487鈥�97.

    听 CAS听 听 听

  36. Brown MT, Bussell JK. Medication adherence: WHO cares? Mayo Clin Proc. 2011;86(4):304鈥撯��14.

  37. Qureshi NN, Hatcher J, Chaturvedi N, Jafar TH. Effect of general practitioner education on adherence to antihypertensive drugs: cluster randomised controlled trial. BMJ. 2007;335(7628):1030.

    听 听 听 听

  38. State Council of China. Opinions on reforming and improving the incentives to train and employ general practitioners. Available at: . Accessed September 26, 2024.

  39. Gordon K, Smith F, Dhillon S. Effective chronic disease management: patients鈥� perspectives on medication-related problems. Patient Educ Couns. 2007;65(3):407鈥�15.

    听 听 听

  40. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831鈥�41.

    听 CAS听 听 听

  41. Yoon J, Wu F, Chang E. Impact of primary care intensive management on medication adherence and adjustments. Am J Manag Care. 2020;26(8):e239鈥�45.

    听 听 听

  42. Hawley CE, Lauffenburger JC, Paik JM, Wexler DJ, Kim SC, Patorno E. Three sides to the story: adherence trajectories during the First Year of SGLT2 inhibitor therapy among Medicare beneficiaries. Diabetes Care. 2022;45(3):604鈥�13.

    听 CAS听 听 听 听

  43. Munshi KD, Amelung K, Carter CS, James R, Shah BR, Henderson RR. Impact of a diabetes remote monitoring program on medication adherence. J Manag Care Spec Pharm. 2021;27(6):724鈥�31.

    听 听

  44. Oung AB, Kosirog E, Chavez B, Brunner J, Saseen JJ. Evaluation of medication adherence in chronic disease at a federally qualified health center. Ther Adv Chronic Dis. 2017;8(8鈥�9):113鈥�20.

    听 听 听 听

  45. Ye M, Vena JE, Johnson JA, Shen-Tu G, Eurich DT. Anti-hyperglycemic Medication Adherence and Health Services Utilization in people with diabetes: a longitudinal study of Alberta鈥檚 tomorrow project. Patient Prefer Adherence. 2022;16:1457鈥�67.

    听 听 听 听

  46. Pednekar P, Heller DA, Peterson AM. Association of Medication Adherence with Hospital utilization and costs among Elderly with Diabetes enrolled in a State Pharmaceutical Assistance Program. J Manag Care Spec Pharm. 2020;26(9):1099鈥�108.

    听 听

  47. Lo-Ciganic WH, Donohue JM, Jones BL, Perera S, Thorpe JM, Thorpe CT, et al. Trajectories of diabetes medication adherence and hospitalization risk: a retrospective cohort study in a large state Medicaid Program. J Gen Intern Med. 2016;31(9):1052鈥�60.

    听 听 听 听

  48. Haff N, Sequist TD, Gibson TB, Benevent R, Sears ES, Chaguturu S, et al. Association between cost-saving prescription policy changes and adherence to Chronic Disease medications: an observational study. J Gen Intern Med. 2022;37(3):531鈥�8.

    听 听 听

  49. Gao W, Liu H, Ge C, Liu X, Jia H, Wu H, et al. A clinical prediction model of Medication Adherence in Hypertensive patients in a Chinese Community Hospital in Beijing. Am J Hypertens. 2020;33(11):1038鈥�46.

    听 CAS听 听 听

  50. Jia Q, Wang H, Wang L, Wang Y. Association of Health Literacy with Medication adherence mediated by cognitive function among the community-based Elders with Chronic Disease in Beijing of China. Front Public Health. 2022;10:824778.

    听 听 听 听

Acknowledgements

The authors acknowledge Xing Chen and Feifei Chen for their assistance with data cleaning.

Funding

This study was funded by the National Natural Science Foundation of China (grant No.72374049, 72342016). The funding body played no role in designing the study, in the analysis and interpretation of the data, or in writing the manuscript.

Author information

Author notes

  1. Xichen Tong and Haiyan Zou contributed equally to this work.

Authors and Affiliations

  1. School of Public Health, Fudan University, No.130 Dongan Road, Shanghai, 200032, China

    Xichen Tong,听Luying Zhang听&听Wen Chen

  2. Institutional Review Board, Huashan Hospital, Fudan University, Shanghai, 200040, China

    Haiyan Zou

Authors
  1. Xichen Tong

    You can also search for this author in 听

  2. Haiyan Zou

    You can also search for this author in 听

  3. Luying Zhang

    You can also search for this author in 听

  4. Wen Chen

    You can also search for this author in 听

Contributions

XT and HZ contributed equally. LZ conceptualized the study. XT and HZ designed the study, cleaned and analyzed the data, and wrote the first draft of the manuscript together. LZ and WC supervised the entire study and provided technical guidance. All authors contributed to the revision and approval of the final manuscript.

Corresponding author

Correspondence to Luying Zhang.

Ethics declarations

Ethics approval and consent to participate

As the administrative data used in this study were obtained from anonymized databases and did not influence patient health or outcomes, the requirement for informed consent was waived. The study was reviewed and approved by The Ethics Review Committee of the School of Public Health, Fudan University approved our study (IRB#2023-TYSQ-02-261).

Consent for publication

Not applicable.

Conflict of interest

The authors declare no conflicts of interest.

Additional information

Publisher鈥檚 note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article鈥檚 Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article鈥檚 Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit .

About this article

Cite this article

Tong, X., Zou, H., Zhang, L. et al. Impact of the family doctor system on medication adherence among type 2 diabetes patients in China: a difference-in-differences analysis. 成人头条 25, 404 (2025). https://doi.org/10.1186/s12889-025-21656-0

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-025-21656-0

Keywords

成人头条

ISSN: 1471-2458

Contact us