Army-Baylor University Graduate Program in Health and Business Administration

 

 

 

 

 

 

 

 

 

 

 

 

 

The Effects of an Army-Baylor Masters in Health Care Administration on Retention of U.S. Army Medical Service Corps Officers

 

Presented to Dr. A. David Mangelsdorff

 

 

 

          

 

 

 

 

 

In partial fulfillment of the requirements for

HCA 5311, Health Care Research Methods: Design and Analysis

 

 

 

         

By

MAJ(P) Andrew Barr

MAJ Jon Edwards

CPT Alan Jones

 

 

 

       

Ft Sam Houston, TX

6 December 05

 

Introduction

A Masters of Health Care Administration (MHA) degree from the Army-Baylor University Graduate Program in Health Care and Business Administration (Baylor) confers with it many benefits. For the officer who obtains it, a Baylor degree leads to mastery of multiple leadership, educational, and professional competencies. For the Army, a Baylor graduate represents a highly trained and motivated officer who can further support and improve the Military Health System (MHS). In this important period of transition, the Army is focused on the retention of its most precious commodity: highly trained, skilled personnel. These facts lead us to our research question: does a Baylor degree lead to significantly higher retention among Army Medical Service Corps (MSC) officers?

Literature Review

            The current literature regarding Baylor is limited, but focuses on the effects of a Baylor education as they relate not only to the individual officer’s career, but also to the Army MHS in general. Mangelsdorff (2005b) demonstrated that a statistically significant positive correlation exists between promotion of Army MSC officers to Lieutenant Colonel (O5) and being a Baylor student; numerous studies conducted by students during their year at Baylor mirror these results. Mangelsdorff (2005a) also notes that Medical Treatment Facilities (MTFs) with Deputy Commanders for Administration (DCAs) who possess Baylor degrees score higher on Joint Commission for the Accreditation of Hospital Organization inspections and garner higher patient satisfaction scores than MTFs with DCAs who did not attend Baylor. The Army quantitatively benefits from the training provided by Baylor with 99% of students graduating over the past 30 years and 61% of students affiliating with a health care executive professional organization.

The military requires retention of well qualified individuals to support its organizational needs. According to Gilroy, Horne, and Smith (1991), retirement benefits have a major impact on retention behavior for soldiers in the second half of their career. Gilroy et al. (1991) also state that individuals enter the Army because of the training offered, but, as time goes by, become more difficult to retain due to their increased skill sets and civilian earnings potential; this is especially evident with Army dentist and physician losses after completion of primary active duty service obligations. However, McGaha (1997) found evidence that military physicians who performed Graduate Medical Education (GME) in military facilities had an increased incidence of retention when compared to those who received training in civilian facilities. Similarly, McClary (1999) found that dental officers receiving military dental specialty training are more likely to stay in the Army. It is in this spirit that the Army uses Baylor as a retention tool; the Baylor MHA program typically targets active duty MSC officers between eight and eleven years of service in an attempt to retain quality officers. We propose that Army MSC officers who attend Baylor are retained at a higher rate than non-Baylor MSC officers.

Method

Our study employed an exploratory model for theoretical analysis. From the historical population of Army MSC officers, a sample was selected which consisted of the 178 officers selected for promotion to Major (O4) in fiscal year (FY) 1990. This sample was selected because it provided data on a complete year group typically targeted by Baylor which could be followed with the most recent MSC Directory (2005) through selection to Colonel. Data was gathered from the MSC Directory, the Medical Operational Data Systems database, and the Baylor MSC database compiled and edited by Dr. A. David Mangelsdorff at Baylor. Of the 178 officers, six were excluded due to incomplete longitudinal data and 55 were excluded who did not qualify for Baylor due to Military Occupational Specialty (MOS); these exclusions yielded a final sample of 117 officers eligible to apply for Baylor. The dichotomous dependent variable, retirement, is operationally defined as actual retirement from active service or active federal service greater than 240 months if the officer is still serving on active duty coded as 1, 0 otherwise; 92% of the sample officers reached retirement. The independent variable of interest is attendance of Baylor; of the 117 officers in the sample, 23 attended Baylor (20%) and 22 of those reached retirement (96%). The remaining independent variables are gender, MOS Health Care Administrator 70A (70A), completion of Command and General Staff College (CGSC), promotion to O5, and Civilian Education Level (CEL). Table 1 outlines the types of independent variables utilized and their operational definitions. Of the 117 officers, 80% were male, 15% occupied the 70A MOS, 81% completed CGSC, and 56% were promoted to O5, and 79% had obtained a CEL of 3. Missing data were discovered for ten officers regarding CGSC. Upon comparing CGSC and MEL categories, it was discovered that eight of the missing CGSC officers had MEL scores of 4 meaning they had not attended CGSC; these officers were assigned a 0 for CGSC. The other two officers had missing data in both categories, but it was discovered that they both left the military without attaining the rank of O5; these officers were also assigned a 0 for CGSC.

The variables were analyzed using descriptive statistics, correlation, Chi-Square, analysis of variance (ANOVA), and linear regression to develop a predictive model for the dependent variable. An alpha level of p < .05 was established to determine statistical significance. The Statistical Program for the Social Sciences was utilized to analyze the data.

Findings

Descriptive and inferential statistics, ANOVA, and regression data are summarized in Tables 2-4. Attendance of Baylor was not correlated to retention, φ = .06, χ2 (1) = .45, p = .50, and was found to be statistically insignificant as a predictor of retirement. Of the other independent variables, completion of CGSC, φ = .44, χ2 (1) = 22.21, p < .001, CEL, φ = .28,      χ2 (1) = 14.69, p = .001, and promotion to O5, φ = .26, χ2 (1) = 7.80, p = .005, correlated significantly with retention. ANOVA for the regression model was significant, F (6,110) = 4.97, p < .001. The shared variance for the model was r2 = 21%. Using linear regression, the following equation was formulated to predict retirement; only CGSC showed significance as a predictor for retention:

Retirement = .57 + .08(70A) + .07(Gender) – .02(Baylor) + .02(CEL) + .25(CGSC) + .04(O5)

Discussion

Our study suggests that attendance of Baylor does not significantly lead to increased retention for Army MSC officers compared to their non-Baylor colleagues; although a greater percentage of Baylor MSC officers (96%) than non-Baylor MSC officers (92%) remained in the Army until retirement, the difference is statistically insignificant. This analysis, however, should not be viewed negatively. As 96% of the Baylor MSCs did retire, the Army enjoyed above average retention of these officers and excellent return on its investment; the reason for this can simply not be significantly attributed to Baylor based on the data alone.

During the study, we discovered numerous limitations in our methods. As the only significant predictive factor of our model was completion of CGSC, our study yielded the tautology that the longer an officer stays in the Army, the higher his chance of retiring. Complete as a snapshot in time, our data was quite limited as a longitudinal sample due to its small size. The sample should be expanded to include Army MSC Captains, investigate the impact of non-Baylor master’s degrees, include all MSC MOSs, and include multiple year groups; these steps will provide a richer data set and account for important retention decisions that occur earlier in an officer’s career. Another confounder is the fact that 30 officers retired with less than 240 months of active federal service most likely due to early retirement programs or medical retirements. 

Conclusion

Although our data shows insignificant correlation and predictive value of a Baylor degree on retention, its value to the Army is certainly significant. Further in-depth and longitudinal study of this issue should be undertaken to fully investigate Baylor’s impact on Army MSC officer retention.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

Gilroy, C. L., Horne, D. K., & Smith, D. A. (Eds.). (1991). Military compensation and personnel retention: Models and evidence. United States Army Research Institute for the Behavioral and Social Sciences.

Mangelsdorff, A. D. (2005a). Evidence based outcomes. U.S. Army Medical Department Journal, PB 8-05-1/2/3, 14-17.

Mangelsdorff, A. D. (2005b). Factors affecting selection for promotion to Lieutenant Colonel (O5). U.S. Army Medical Department Journal, PB 8-05-1/2/3, 21-23.

McClary, M. (1999). Predictors of recruitment & retention factors to aid in the management of turnover in the Army Dental Corps. (Available from the U.S. Army-Baylor Graduate  Program in Health Care Administration, 3151 Stanley Road, Fort Sam Houston, TX 78234)

McGaha, J. F. (1997). Medical readiness training, retention, and cost efficiency: The future of DOD’s graduate medical education program. Army War College, Carlisle Barracks, Pennsylvania.

 

 

 

 

 

 

 

 

Table 1

Types of and Operational Definitions for Independent Variables

Independent Variable

Type

Operational Definition

Attended Baylor (Baylor)

Dichotomous

1 = Attended Baylor

0 = Did not attend Baylor

Gender

Dichotomous

1 = Male

0 = Female

MOS = 70A (70A)

Dichotomous

1 = 70A

0 = Other

Command and General Staff College (CGSC)

Dichotomous

1 = Completed CGSC

0 = Did not complete CGSC

Promotion to O5 (O5)

Dichotomous

1 = Promoted to O5

0 = Not promoted to O5

Civilian Education Level (CEL)

Ordinal

1 = Associate degree

2 = Bachelor’s degree

3 = Master’s degree

4 = Professional degree

5 = Doctorate degree

Note. CAS3 = Combined Arms and Services Staff School

 

 

 

 

 

Table 2

Group

n

Mean

SD

φ

df

χ2

p

Baylor

117

.20

.40

.06

1

.45

.50

Gender

117

.79

.41

.09

1

.98

.32

70A

117

.15

.35

.12

1

1.66

.20

CGSC

117

.81

.39

.44

1

22.21

<.001

O5

117

.56

.50

.26

1

7.80

.005

CEL

117

2.88

.56

.28

1

14.69

.001

Descriptive and Inferential Statistics for Independent Variables

 

Table 3

Analysis of Variance for Regression Model

Source

SS

df

MS

F

Significance

r2

Regression

1.77

6

.30

4.97

<.001

.21

Residual

6.54

110

.06

 

 

 

Total

8.31

116

 

 

 

 

 

Table 4

Group

B

SD

t

p

Constant

.57

.13

4.35

<.001

Baylor

-.02

.08

-.29

.78

Gender

.07

.06

1.20

.23

70A

.08

.09

.91

.37

CGSC

.25

.07

3.42

.001

O5

.04

.05

.78

.44

CEL

.02

.05

.50

.62

Regression Data for Dependent Variable “Retirement”

 

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