Patient waiting time for healthcare services is identified by the World Health Organization (WHO) as one of the key measurements of a responsive health system. Patient waiting time is the amount of time for patients seeking care at healthcare units before being attended for consultation and treatment [1, 2]. The United States (US) Institute of Medicine’s report “Crossing the Quality Chasm” outlines a framework of six guiding principles to staying ahead in a more competitive healthcare delivery system. One of these principles is the ability to provide timely care and to reduce harmful delays [3]. The Patient’s Charter of the United Kingdom (UK) Government sets a series of standards which state that all patients must be seen within 30 min of their appointment time [4]. It is globally agreed that a well-designed healthcare service management system should not have patients to wait long time for appointment and consultation.

Lengthy waiting time has long been considered frustrating to patients and thus appears to be a consistent and significant potential cause of patient dissatisfaction. A strong inverse relationship between patient satisfaction and waiting time has been demonstrated by many studies [5–10]. As healthcare solutions become more personalized and consumer-driven, the need to provide overall patient satisfaction is becoming more important [11].

The outstanding waiting time problem in the Chinese health systems lies in two aspects, one is long waiting time at the registration and admission windows. This is mainly due to that most Chinese hospitals used not to schedule the appointment, patients get registered upon arrival to hospitals at the service window, thus the unplanned patient flow clogged in hospitals. A straightforward and easy appointment-scheduling process is the first step for patients’ timely access to healthcare services. Multiple appointment-scheduling methods (including web-, landline-, smart phone-, and automatic teller machine “ATM”-based methods) have been used to replace the traditional process where patients were asked to make the appointment physically inside hospitals [12–14].

The other aspect of the problem is the long waiting time between the appointment time and the time patients are attended by doctors. Findings from the 2015 China National Patient Survey [15] from 136 public tertiary hospitals showed that outpatient users of ambulatory services were least satisfied with long waiting times for consultations. The key reason behind this is that the increasing of patient demand is faster than that of the health care resources. Although the number of public tertiary hospitals in China doubled during the past 10 years (from 946 in 2005 to 1972 in 2015), the annual number of outpatient visits increased nearly four times (from 397 million to 1.5 billion) during the same time period [16]. The increasing patient turnover may have implications for the overall quality of care, such as insufficiencies in patient safety and increased tensions between doctors and patients [17–19]. Therefore, the rapidly increasing demand and limited health care resources require health services must rely on improved flow control and better capacity allocation to minimize the negative effect of patient long waiting time. Organizational and structural changes must be introduced with purposeful planning and demand-oriented scheduling of outpatient care.

This study focus on the waiting times for consultations and filling prescriptions (Chinese health care system does not separate prescription from dispensing, hospitals run their own pharmacies to serve outpatients, and majority of outpatients fill prescriptions from the hospital pharmacies).

Many interventions aiming to reduce waiting times for consultation, tests and filling prescriptions have been implemented in the Chinese public tertiary hospitals [20–22]. Few interventions were well-documented and intervention impact was rarely measured with robust method. This study takes one provincial hospital as a typical example of a Chinese public tertiary hospital in southern China. It is on the top of the three-tiered public health service delivery system (community health center/station and township health center/village clinics as primary level, city secondary hospitals and county hospitals as the secondary level, and tertiary hospitals mainly located in urban areas), and public facilities dominate the overall health service delivery systems. We comprehensively document the studied hospital’s efforts to achieve the organizational and structural changes in order to reduce waiting times for consultations and filling prescriptions. The study also used longitudinal data series before and after the intervention which deliver robust results, quantitatively presents the amount that waiting time was reduced, and to what extent such efforts helped to improve the outpatient satisfaction.

The monthly average waiting times for consultations and for filling prescriptions before and after the respective interventions are presented in Appendix 1. The waiting times for consultations ranged between 20.88–23.92 min during October 2014–August 2015, which reduced to a range between 15.83–20.32 min during September 2015–February 2017; and the waiting times for filling prescriptions ranged between 24.91–42.52 min during March 2015–January 2016, which went down to a range of 14.99–28.77 min during February 2016–February 2017. Appendix 2 shows the monthly average satisfaction scores towards consulting doctors and pharmacy services. From February 2016 to February 2017, the monthly average satisfaction scores towards consulting doctors ranged from the lowest of 82.78 to the highest of 93.44; which for filling prescriptions ranged from the lowest of 59.33 to the highest of 89.52.

As presented in Table 1 and Figs. 1 and 2, the segmented regression analysis results indicate that, prior to the interventions on waiting time for consultations in September 2015, the trend of the monthly average length of waiting time for consultations declined slightly (P = 0.37). In September 2015, the month that consultation interventions were introduced, there was an immediate decrease in average length of waiting time for consultations of 3.49 min (95% CI: -5.38 – -1.61; P = 0.003). This decreasing trend continued after September 2015 through the end of the study period in February 2017, although the results were not statistically significant (P = 0.07).

Outcome variable	Coefficient		95% CI	P-value
Waiting time for consultation	Intercept	23.05	/	/
	Baseline trend	−0.09	−0.31 ~ 0.12	0.37
	Level change	−3.49	−5.38 ~ −1.61	0.003
	Trend change	−0.12	−0.24 ~ −0.03	0.07
Waiting time for filling prescription	Intercept	32.88 0.479	/	/
	Baseline trend		−0.39 ~ 1.35	0.26
	Level change	−8.70 −1.09	−16.12 ~ −1.29	0.02
	Trend change		−1.76 ~ −0.42	0.003
Outpatient satisfaction score towards consulting doctors	Intercept	4.41	/	/
	Trend change	0.01	−0.005 ~ 0.03	0.17
Outpatient satisfaction score towards pharmacy services	Intercept	3.91	/	/
	Trend change	0.05	0.03 ~ 0.07	0.000

Bold signifies statistically significant coefficient (P < 0.05)

For the waiting time of filling prescriptions, the trend steadily increased (P = 0.26) before the interventions in February 2016. There was an immediate decrease in average length of waiting time of 8.70 min (95% CI: -16.12 – -1.29; P = 0.02) in February 2016, when the interventions were introduced. There was a significant decreasing trend in average waiting time from February 2016 through the end of the study period in February 2017 (P = 0.003).

The regression results of respective monthly average outpatient satisfaction scores during January 2016 – February 2017 indicate that satisfaction towards consulting doctors slightly increased (P = 0.17), and satisfaction towards filling prescriptions significantly increased (P < 0.05).

The Pearson correlation analysis results indicate that the strength of negative correlation between the waiting time of filling prescriptions and outpatient satisfaction score towards pharmacy services (r = −0.71, P = 0.004) is stronger than that between the waiting time of consultations and outpatient satisfaction score towards consulting doctor (r = −0.39, P = 0.17).

Huang [25] found that outpatients were reasonably satisfied if they waited no more than 37 min when arriving on time. Our results are in line with this finding. The waiting time for consultations in the studied hospital did not exceed this threshold, though the waiting times for filling prescriptions far exceeded this limit, before interventions were introduced. Outpatients were less satisfied with pharmacy services. There were negative correlations between waiting times and outpatient satisfaction scores. Such correlations between waiting time for filling prescriptions and outpatient satisfaction score towards pharmacy services was stronger than that between waiting time for consultations and outpatient satisfaction score towards consulting doctors. It is likely that patients see the filling of a prescription as more of process and therefore strongly influenced by time, whereas there are different expectations of the doctor consultation.

The regression analysis shows the effectiveness of the interventions on reducing waiting times for consultation and for filling prescriptions in the studied hospital. There were statistically significant immediate intervention effects on reduction of waiting time for consultations. Statistically significant long term reduction effects on waiting time for consultations was also shown, implying that waiting time reduction interventions in the studied hospital were not a one-time campaign but continuous efforts. Such continuous efforts are essential for quality of healthcare improvements. Findings provide evidence in support of the effectiveness of the interventions. By the end of February 2017, all the waiting times were below the threshold set by the Patient’s Charter of the UK Government.

Many studies proved that, process matters in healthcare, a process improvement team approach for evaluating and redesigning the patient care system can be successful in reducing waiting times and raising patient satisfactions [26–28]. Similar findings were also concluded by many studies in the Chinese tertiary hospitals [29–31]. As an example of Chinese tertiary public hospitals, who has been trying to address the waiting time problem, the studied hospital provides a good example of carrying out continuous quality of healthcare improvements in optimizing the process management in outpatient care with the support of relevant evidence. Firstly, a multidisciplinary taskforce empowered by the top hospital manager with supreme authority to design interventions, to appraise the performance of the targeted players, and to link the appraisal results with financial penalties, such process-improvement approach with major sustained support from top-level hospital administrators is fundamental for quality improvement. Secondly, they selected the problem of waiting times and clearly defined it. This enabled the interventions to be carried out with clear objectives and targets. Thirdly, they identified the potential cause of the problem, collected and analyzed data related to the problem, generated solutions to address the root causes of the problem, and gained support from the top hospital manager to secure the credibility. Fourthly, they implemented the solutions on a trial of waiting time for consultations, and expanded to waiting time for filling prescriptions, which secured steady push forward of the interventions step by step. Fifthly, they evaluated the results and gathered and analyzed the data on the solutions, which made evidence based solution adjustment possible. Finally, the integrated information system was shown to be indispensable for implementing the above problem solving process efficiently.

It is a pity that the outpatient satisfaction survey started after the interventions on waiting time for consultations, and just one month before the introduction of the interventions on waiting time for filling prescriptions. We were not able to measure the changes of the outpatient satisfaction scores corresponding to the changes of the waiting times for both consultations and filling prescriptions. The upward trends of the monthly average outpatient satisfaction scores towards both consultations and filling prescriptions already support the effective effects of interventions on waiting times, and the positive impacts of waiting time reductions on raising the outpatient satisfaction scores. However, as literatures also proved that time spent with the physician is a stronger predictor of patient satisfaction than is the time spent in the waiting room [32], the increased patient satisfaction might not be brought by shorter waiting time but longer consulting time due to process improvement. The daily outpatient satisfaction survey carried out by the studied hospital only asks the outpatients’ satisfactions with consulting doctors instead of waiting time for consultations. This is also the case for the outpatients’ satisfaction with pharmacy services, which does not specifically target patients’ satisfaction towards waiting time for filling prescriptions. Although waiting time is an important factor influencing the outpatient satisfaction, there are still many other critical factors affecting the outpatient satisfaction with consulting doctors. Previous studies have found that interpersonal relationships are very important in patient satisfaction, and therefore patients who had to wait but then had a good experience with their doctor are still likely to be satisfied [33]. Ideally we would be able to analyze both the waiting time and the outpatient satisfaction time series data with the segmented regression analysis, which would generate strong evidence of correlation between waiting time reduction and outpatient satisfaction improvement, as a further proof of the Pearson correlation analysis. However, due to the absence of the outpatient satisfaction data before 2016 (the hospital outpatient satisfaction survey started in January 2016), we can only show the trend of outpatient satisfaction after interventions.

The evidence generated by robust method proved that the studied hospital used its integrated health information system to support a well-designed and carefully arranged quality improvement in reducing waiting time and raising patient satisfaction. This typical case set up an example for the other Chinese public tertiary hospitals, as well as the overloaded public hospitals in other settings to implement organizational and structural changes in order to address the waiting time issue.