Potential Factors of Medical Specialist Allocation in a Private Hospital Network in Thailand: A Modified Delphi Study

OBJECTIVES: Medical specialist allocation is crucial for achieving equitable access to specialized care. Given the scarcity of data from the private sector, this study aimed to identify potential factors of medical specialist allocation within the largest private hospital network in Thailand. identified as potential factors of medical specialist allocation. Of the 35 factors, 6 potential factors were considered as the most affected potential factors of medical specialist allocation: 1) health need of the population, 2) organization’s mission, 3) organization’s Hoshin, 4) organization’s strategy, 5) complexity of the patients, and 6) severity of the patients. CONCLUSION: Six factors that might influence the allocation of medical specialists were identified and could be useful for medical allocation in a private hospital network.

A ccording to the World Health Organization (WHO) 1 in the year of 2010, the data showed that there has been a shortage and maldistribution of physicians in Thailand compared to other developed countries worldwide, particularly in the Southeast Asia region. Moreover, the shortage of medical specialists has been even more pronounced. 2,3 A good understanding of how medical specialists are distributed would promote the quality and efficiency of healthcare services. This is also very critical for medical specialist resource allocation between the private and public hospital network. However, the research data has been limited and not thoroughly explored so far.
For the public healthcare system, copious factors affect the demand for physician's services such as population dynamics (graying population, zero population growth), changes in types of public health services and technologies, changes in economic and social status (urbanization), epidemics and pandemics of diseases (HIV, Zika). All these lead to changes in response in the supply and distribution of physicians and physician specialists in particular.
For the private hospital healthcare system, the number of physicians required for each hospital depends on the missions and characteristics of each individual hospital 4, 5 such as hospital's level, size, facilities, and service plans, the number of inpatients and outpatients, the complexity and severity of the patients, the work hours per patient day (HPPD), the patient-physician relationship, and the Quality Assurance Services. 2,[4][5][6][7][8][9][10][11][12][13] Evidence on how medical specialists are allocated would be useful for achieving equitable access to specialized care. Due to limited data from the public sector, therefore, this study is designed to be the first consensus-based survey in Thailand. The purpose of this study was to find potential factors which will serve as a model for medical specialist allocation in a large private hospital network in Thailand.

Materials and Methods
This four-round modified Delphi survey 14 was done by using a questionnaire containing potential factors identified from reviewing published literature as well as interviewing the experts who had extensive experience with human resource management or hospital management in the public and private sectors. Executives who were part of BDMS management for 1 year or more were recruited from 32 hospitals. The respondents were chosen based upon their willingness to respond to the survey and if they met required criteria as follows: a) be in position assistant of director or above, b) have extensive experience with human resource management or hospital management for at least 3 years.

Questionnaire
The questionnaire for this study was developed from published literature review and was reviewed by the experts from both public and private sectors for face validity. For standardization and comparison, based on the identified key points in the questionnaire, all factors were derived by the modified four-round Delphi study.

Data Collection
The first round was conducted among 32 representative hospitals. Each nominated executive was emailed a cover letter outlining the objective of the study along with a six-page questionnaire. The questionnaire comprised two parts: Part 1: contains the demographic data (gender, age, education, job position, and administrative experience) of participants. Part 2: the participants are asked to rank 43 items and add on factors that will possibly influence the allocation of medical specialists in a free text response.
In round 2, each executive received a questionnaire survey comprising 46 items along with the responses from round 1. In round 3, each executive received a questionnaire survey, comprising all 46 items from round 2 with the participants' own response and the group's response from round 2. In round 4, executives were asked to reconsider their responses in the final round.

Data Analysis
Descriptive data were presented as absolute numbers and percentages. As the survey was conducted in four rounds, items with inconsistent values across the four rounds determined by the interquartile range (IQR) larger than 1.5, were considered unreliable and, therefore, were excluded. All items remaining after the fourth round were considered as potential factors; their means and standard deviations were presented.

Results
Forty-three top executives of BDMS hospital network were interviewed, 43 executives completed questionnaires in round 1 (100%), 41 of 43 completed questionnaires in round 2 (95.35%), 39 of 41 completed questionnaire in round 3 (95.12%) and 31of 39 (79.49%) completely participated in the fourth round of the survey. The characteristics of the executives in the first round and fourth round are shown in Table 1. The questionnaire for this study was developed based on 46 items identified from the reviews and interviews, 11 items were excluded because of inconsistent values and 35 factors were considered as potential factors of medical specialist allocation (

Eleven factors were excluded because of inconsistent values
Potential factors of medical specialist allocation were classified into 4 levels: 1. National: population structure, population health need, economic and social change, country policy, cause of death, and disease burden. 2. Regional: hospital network policy, mission, strategy, and Hoshin. 3. Hospital: hospital type, size, location, revenue, reputation, service offered, case mix index, bed occupancy, quality assurance, available medical technology, human resource management, and availability of doctors. 4. Personal: qualification and competency, personal behavior, network contribution attitude, patient complexity, patient severity, number of admissions, number of outpatient, number of inpatient, number of surgical cases, number of refer in cases, revenue, responsibility and discipline, and benefit and welfare (Table 3).
Focused on factors with a mean value of more than 4.5 and IQR less than 1.5, 6 out of 35 were considered as the most affected potential factors of medical specialist allocation: 1. Health need of population. 2. Organization's mission.

Discussion
This was the first survey undertaken in the largest private hospital network in Thailand to ascertain the potential factors of medical specialist allocation. The response rate of each round was more than 75%. We have modified a uniform study protocol used in previous studies. The questionnaire was modified after a series of email questions and answers using a modified Delphi technique. This process has been utilized widely in research which allows feedback and develops questions using a consensus-based approach. Therefore, all answers are based on frequency and type of response from this Delphi approach.
This study has identified 35 factors that determine the allocation of medical specialists. For factors with the mean value of more than 4.5 and IQR less than 1.5, a total of 6 factors are identified to significantly affect medical specialist allocation. They include health need of the population, organization's mission, organization's Hoshin, organization's strategy, severity and complexity of patients. Regarding severity and complexity of patients, these findings are consistent with the study of Kalisch, et al. 10 , which reported that case mix index and a measure for acuity of patient were associated with both hours per patient day (HPPD) and nurse-reported patient workloads. 15 In addition to the previous point, comparing outcomes of care by generalist and specialist, Smetana, et al. 16 found that most people preferred a specialist to a generalist. Therefore, the complexity of the patient may be one of the factors for the need of a specialized doctor. Of 11 factors, for example, gender, age, the residence of physicians showed inconsistent values and are not considered as potential factors of medical specialist allocation in our study. In contrast, Wibulpolprasert S. 7 found that gender, age, and residence are factors of medical distribution. These findings are similar to previous studies that identified gender, age, the residence of physicians, qualified staff, as a negative outcome with the inequity of medical doctor distribution or allocation. 6,[17][18][19][20]

Conclusion
The findings in this study could be used to plan appropriate strategies of medical specialist allocation. The questionnaire used in our study was specifically designed for the BDMS hospital network. For benchmarking purposes, the questionnaire used in our study is useful and should be adjusted for further research done in other hospital networks.
14. Location of hospital 15