Volume 6.
Number 1, 2025 https://ijble.
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php/journal/index Morning Briefing Meetings as a Strategy to Improve Healtcare Workforce and Service Quality Management at the Puskesmas Pembantu Lubang Buaya Jakarta Timur Hermina Nurmalita Sari1.
Supriyadi2.
Zaharuddin3 Program Studi Magister Manajeman.
Universitas Mitra Bangsa Jakarta, 2Prodi Pendidikan Ekonomi.
Universitas Pancasakti Bekasi lt_sari@yahoo.
2supriyadi@panca-sakti.
3zaharuddin@umiba.
ABSTRACT
This study evaluates the impact of morning briefing meetings on communication effectiveness, job satisfaction, and service quality at the Lubang Buaya Health Center.
Using a quantitative descriptive-analytical method, data were collected from five health workers through structured questionnaires and analyzed with SPSS Version 20.
The findings reveal that while morning briefings moderately improved team communication effectiveness .
ean = 19.
, their effect on job satisfaction and service quality was not statistically significant.
Regression analysis showed that morning briefings accounted for 34% of the variability in job satisfaction but failed to significantly influence service quality or workforce improvement .
> 0.
Normality tests confirmed the dataAos suitability for parametric Despite positive correlations, the results suggest that morning briefings alone are insufficient to significantly enhance healthcare outcomes, emphasizing the need for additional strategies to improve health worker performance and service delivery.
Keywords:
Morning Briefing.
Improve Healthcare Workforce.
Service Quality Management INTRODUCTION Sub-health centers play an important role in providing basic health services to the community.
However, challenges such as ineffective team coordination, low job satisfaction, and suboptimal service quality are still often encountered (Ministry of Health, 2.
Morning briefing meetings are known as one of the management strategies to improve communication, align team goals and ensure service quality.
The effectiveness of communication in health services is very important to ensure that information is conveyed clearly and understood by all parties involved.
(Wijaya, 2.
Analyzes the effectiveness of interpersonal communication between nurses and patients, emphasizing the importance of good communication in improving the quality of health services.
(Haryadi, 2.
Examining communication patterns in health services in hospitals, found that effective communication between health workers and patients increases patient satisfaction.
(Sari, 2.
Discusses effective communication strategies in improving health services, highlighting the importance of feedback in communication between health workers and patients.
(Putri, 2.
Examining the effectiveness of health communication through digital media, found that the use of short videos can improve patient understanding of health procedures.
(Nugroho, 2.
Analyzing the role of digital communication in health services, concluding that digital communication can accelerate the dissemination of information among health workers and improve services.
Daily briefings improve team communication by 30% through improved information delivery and discussion of service issues.
Health worker job satisfaction is influenced by various factors, including working conditions, incentives, and relationships between coworkers.
(Wafiq, 2.
Analyzing Volume 6.
Number 1, 2025 https://ijble.
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php/journal/index the job satisfaction of health workers in hospitals, found that conducive working conditions and appropriate incentives have a significant effect on job satisfaction.
(Suryani, 2.
Examining the relationship between job satisfaction and work motivation in health workers, found that job satisfaction is significantly related to work (Pratsama, 2.
Analyzing the satisfaction of health workers in improving performance, found that job satisfaction has a positive effect on the performance of health workers.
(Lailatul, 2.
Discussing the motivation and job satisfaction of health workers in health centers, highlighting the importance of a supportive work environment in increasing job satisfaction.
(Handayani, 2.
Examining the influence of internal factors on job satisfaction in health facilities, found that factors such as rewards and recognition play an important role in increasing job satisfaction.
The quality of health services is determined by various aspects, including the effectiveness of communication and job satisfaction of health workers.
(Priyanti, 2.
Discussing the quality of health services from a customer perspective, emphasizing the importance of customer perceptions in assessing service quality.
(Sari, 2.
Analyzing the quality of health services in health centers, found that tangible aspects play an important role in improving health services.
(Fajriah, 2.
Discussing the quality of health services in Indonesia, highlighting the need to improve infrastructure and personnel quality to improve services.
Increased service quality by 15% with the implementation of daily briefings.
(Putra, 2.
Examining the quality of health services according to consumer perceptions, found that customer satisfaction is the main indicator of service quality.
(Handayani, 2.
Analyzing the quality of health services in health centers, emphasizing the importance of effective communication in improving service quality.
The purpose of this study was to analyze the effect of morning briefing meetings on communication effectiveness.
In addition, analyzing the influence of morning briefing meetings on the job satisfaction of health workers.
And analyzing the influence of morning briefing meetings on the quality of health services.
METHOD
This study uses a quantitative method with a descriptive-analytical design.
The population of the study was all health workers at Lubang Buaya Health Center.
The sample used a saturated sample involving all members of the population, namely 5 health workers (Doctor.
The research instrument used was a structured questionnaire with proven validity and reliability.
The research variables include .
Communication effectiveness .
, .
Job satisfaction .
, .
Quality of health services .
Data were analyzed using SPSS Version 20 with descriptive tests and simple linear regression to see the effect of each variable on the performance of health workers and quality of service.
RESULTS AND DISCUSSION
The results of this study are expected to show a significant influence between morning briefing on Improve Healthcare Workforce and Service Quality Management at Lubang Buaya Sub-Health Center.
East Jakarta.
And can be implemented well and become a basis for thinking in the medical world to improve the quality of service.
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php/journal/index Results Descriptives Table: I Descriptives Morning Briefing Improve Healthcare Workforce Service Quality Management Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std.
Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std.
Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis Mean 95% Confidence Interval for Mean 5% Trimmed Mean Median Variance Std.
Deviation Minimum
Maximum
Range Interquartile Range Skewness Kurtosis Lower Bound
Upper Bound
Lower Bound
Upper Bound
Lower Bound
Upper Bound
Statistic 19,2000 14,6888 23,7112 19,2222 20,0000 13,200 3,63318 14,00 24,00 10,00 6,00 -,267 1,074 17,0000 13,4880 20,5120 17,0000 18,0000 8,000 2,82843 14,00 20,00 6,00 5,50 -,331 -2,922 18,6000 16,3444 20,8556 18,5556
18,0000
3,300
1,81659
17,00
21,00
4,00
3,50
,567
-2,231
Std.
Error
1,62481
,913
2,000
1,26491
,913
2,000
,81240
,913
2,000
From the descriptive results above, it can be interpreted that:
The Morning Briefing variable (X) has a Mean value of 19.
Confidence Interval .
%): The confidence interval shows that the actual average is estimated to be 6888 and 23.
The Median value is 20, indicating that half of the data is above this value and half is below it.
With a Standard Deviation value of 3.
63318, it shows that there is a fairly significant spread of data.
The skewness value of -0.
indicates that the distribution is slightly skewed to the left .
, but is close to The kurtosis value of 1.
074 indicates that the distribution has a sharper peak than the normal distribution.
Volume 6.
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php/journal/index The Improve Healthcare Workforce variable (Y.
has a Mean value of 17.
which is lower than Morning Briefing.
Confidence Interval .
%): The confidence interval shows the true mean is estimated to be between 13.
4880 and 20.
The Median value is 18, slightly higher than the mean, indicating the data distribution may be slightly skewed to the left.
With the Standard Deviation value: The value of 2.
shows the data spread is smaller than Morning Briefing.
The skewness value of -0.
shows the distribution is slightly skewed to the left.
The kurtosis value of -2.
922 shows a very flat distribution or wider than a normal distribution.
The Service Quality Management variable (Y.
has a Mean value of 18.
6, between the mean values of Morning Briefing and Improve Healthcare Workforce.
Confidence Interval .
%): The confidence interval shows the true mean is between 16.
3444 and 20.
The Median value is 18.
0, slightly lower than the mean.
With Standard Deviation: A value 81659 indicates that the data has a small spread compared to other variables.
skewness value of 0.
567 indicates that the distribution is slightly skewed to the right.
A kurtosis value of -2.
231 indicates that the distribution is flatter than the normal Normality Test Table: II Tests of Normality Kolmogorov-Smirnova Statistic Sig.
,213
,200*
Morning Briefing Improve Healthcare ,256 Workforce Service Quality ,229 Management This is a lower bound of the true significance.
Lilliefors Significance Correction Shapiro-Wilk Statistic ,963 Sig.
,826
,200*
,843
,174
,200*
,867
,254
The normality test table shows the results of two statistical tests, namely Kolmogorov-Smirnov (KS) and Shapiro-Wilk (SW), for three variables: Morning Briefing.
Improve Healthcare Workforce, and Service Quality Management.
Interpretation of this table can be done as follows :
Decision Making Criteria.
Hypothesis: H0 (Null Hypothesi.
: Data is normally H1 (Alternative Hypothesi.
: Data is not normally distributed.
Significance (Sig.
): If the Sig.
value > 0.
05, then accept H0 .
ata is normally distribute.
If the Sig.
value O 0.
05, then reject H0 .
ata is not normally distribute.
Interpretation Per Variable : In the Morning Briefing variable (X).
KolmogorovSmirnov Value (Sig.
): 0.
200* .
reater than 0.
In Shapiro-Wilk (Sig.
): 0.
reater Based on both tests, the data is normally distributed.
Improve Healthcare Workforce variable (Y.
Kolmogorov-Smirnov value (Sig.
): 0.
200* .
reater than 0.
In Shapiro-Wilk (Sig.
): 0.
reater than 0.
So based on both tests, the data is normally distributed.
Service Quality Management variable (Y.
Kolmogorov-Smirnov value (Sig.
): 0.
200* .
reater than 0.
In Shapiro-Wilk (Sig.
): 0.
reater than So based on both tests, the data is normally distributed.
Based on the results of the normality test with Kolmogorov-Smirnov and Shapiro-Wilk, all variables (Morning Briefing.
Improve Healthcare Workforce, and Service Quality Managemen.
have a significance value greater than 0.
Therefore, the data from the three variables can be considered normally distributed.
Volume 6.
Number 1, 2025 https://ijble.
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php/journal/index This normal distribution is important for determining the statistical analysis method to be used next, such as parametric tests .
ANOVA or t-tes.
Hypothesis Test Table: i Regression coefficient between X --> Y1 Model Coefficientsa Unstandardized Coefficients Std.
Error (Constan.
8,273 7,106 Morning Briefing ,455 ,365 Dependent Variable: Improve Healthcare Workforce Standardized Coefficients Beta
,584
Sig.
1,164
1,246
,328
,301
From the coefficient table above, the constant b0 = 8.
Regression coefficient b1 = 0.
So the multiple linear regression equation is YAo = 8.
Hypothesis A0:b1 From the results of the analysis as summarized in the table, it shows the statistical price for the X coefficient, namely t count = 1.
246 and p value = 0.
301/2 =
1505> 0.
05 or H0 is accepted, meaning that the implementation of morning briefing has no positive effect on Improve Healthcare Workforce.
Table: IV Regression coefficient between X --> Y2 Model Coefficientsa Unstandardized Coefficients Std.
Error (Constan.
11,909 4,031 Morning Briefing ,348 ,207 Dependent Variable: Service Quality Management Standardized Coefficients Beta
,697
Sig.
2,954
1,683
,060
,191
From the coefficient table above, the constant b0 = 11.
Regression coefficient b1 = 0.
So the multiple linear regression equation is YAo = 11.
Hypothesis A0:b1 From the results of the analysis as summarized in the table shows the statistical price for the X coefficient, namely t count = 1.
683 and p value = 0.
191/2 = 0.
05 or H0 is accepted, meaning that the implementation of morning briefing has no positive effect on Service quality management.
TABLE: V ANOVA X --> Y1
Model
ANOVAa
Sum of Mean Square Squares Regression 10,909 10,909 Residual 21,091 7,030 Total
32,000
Dependent Variable: Improve Healthcare Workforce Predictors: (Constan.
Morning Briefing 1,552 Sig.
,301b From the results of the analysis summarized in the ANOVA table above, the F statistic value is obtained, namely F count = 1.
552 and p value = 0.
301> 0.
05 or this means that H0 is accepted, meaning that the variable of morning briefing implementation does not have a positive effect on Improve Healthcare Workforce.
This Volume 6.
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php/journal/index also means that there is no simultaneous and joint relationship between the implementation of morning briefing and Improve Healthcare Workforce Table: VI ANOVA X --> Y2
ANOVAa
Model
Sum of Mean Square Squares Regression 6,412 6,412 Residual 6,788 2,263 Total
13,200
Dependent Variable: Service Quality Management Predictors: (Constan.
Morning Briefing Sig.
2,834
,191b From the results of the analysis summarized in the ANOVA table above, the F statistic value is obtained, namely F count = 2.
834 and p value = 0.
191> 0.
05 or this means that H0 is accepted, meaning that the variable of morning briefing implementation does not have a positive effect on Service quality management.
This also means that there is no simultaneous and joint relationship between the implementation of morning briefing and Service quality management.
Table: VII Model Summary Std.
Error Change Statistics of the R Square Estimate Change Change ,584a ,341 ,121 2,65147 ,341 1,552 Predictors: (Constan.
Morning Briefing Mod Adjusted R Square Square Sig.
Change ,301 The significance test of the multiple correlation coefficient is obtained from the model summary table above for variables X and Y1.
It can be seen that the multiple correlation coefficient RY1 = 0.
584 and F count = 1.
552 and p value = 0.
301> 0.
05 or H0 is accepted, thus the multiple correlation coefficient between X and Y1 is not significant, while the determination coefficient is shown by R Square = 0.
341 which means that 34% of the variability of the variable.
Improve Health Care Workforce (Y.
can be explained by Morning briefing (X), so it can be concluded that the relationship between morning briefing in Improve Health Care Workforce in the Work Environment is 34%.
Partial Correlation Coefficient Significance Test Correlation between Morning Briefing and Improve Healthcare Workforce.
Table: Vi Pearson Correlation Sig.
-taile.
Correlations Improve Healthcare Morning Briefing Workforce Improve Healthcare Workforce 1,000 ,584 Morning Briefing ,584 1,000 Improve Healthcare Workforce ,151 Morning Briefing ,151 Improve Healthcare Workforce Morning Briefing Volume 6.
Number 1, 2025 https://ijble.
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php/journal/index From the analysis results in the table above, ry1 = 0.
584 and p value = 0.
05 or H0 is accepted, thus the correlation coefficient between Morning Briefing and Improve Healthcare Workforce is significant.
Correlation between Morning Briefing and Service quality management Table: VI Correlations Service Quality Management Service Quality Pearson Correlation Management Morning Briefing Service Quality Management Sig.
-taile.
Morning Briefing Service Quality Management Morning Briefing Morning Briefing 1,000 ,697 ,697 1,000 ,095 ,095 From the analysis results in the table above, it was obtained that ry2 = 0.
and p value = 0.
095 > 0.
05 or H0 is accepted, thus the correlation coefficient between Morning briefing and Service quality management is significant.
Discussion The implementation of morning briefing has no positive effect on Improve Healthcare Workforce.
The implementation of morning briefing has no positive effect on Service quality management.
The variable of the implementation of morning briefing has no positive effect on Improve Healthcare Workforce.
This also means that there is no simultaneous and simultaneous relationship between the implementation of morning briefing, on Improve Healthcare Workforce.
While the variable of the implementation of morning briefing has no positive effect on Service quality management.
This also means that there is no simultaneous and simultaneous relationship between the implementation of morning briefing, on Service quality management.
On the Relationship of Morning Briefing in Improve Healthcare Workforce in the Work Environment by 34% While on the Relationship of Morning Briefing in Service Quality Management in the Work Environment by 48%.
These results support previous research showing that daily briefings can improve the effectiveness of team communication (Covey, 2015.
Robbins & Judge.
Morning briefings also increase job satisfaction by strengthening communication between colleagues and management support (Herzberg, 1.
Better service quality is caused by regular planning and evaluation during briefings, as supported by Donabedian's theory .
CONCLUSION
All variables analyzed (Morning Briefing.
Improve Healthcare Workforce, and Service Quality Managemen.
have normal data distribution, as evidenced by the significance value of the Kolmogorov-Smirnov and Shapiro-Wilk normality tests which are greater than 0.
This allows the use of parametric test methods in further statistical analysis.
Volume 6.
Number 1, 2025 https://ijble.
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php/journal/index The implementation of Morning Briefing did not show a significant positive effect either individually or simultaneously on Improve Healthcare Workforce or Service Quality Management.
Although there is a moderate relationship between Morning Briefing and both variables, this relationship is not statistically significant enough to conclude a strong positive effect.
Acknowledgments Thank you for the assistance from colleagues who have been willing to be respondents, as well as the supervisors who have been willing to give their time in sharing knowledge for the completion of this research.
Reference