Managerial capacity among district health managers and its association with district performance: A comparative descriptive study of six districts in the Eastern Region of Ghana.

INTRODUCTION: District health managers play a pivotal role in the delivery of basic health services in many countries, including Ghana, as they are responsible for converting inputs and resources such as, staff, supplies and equipment into effective services that are responsive to population needs. Weak management capacity among local health managers has been suggested as a major obstacle for responsive health service delivery. However, evidence on district health managers' competencies and its association with health system performance is scarce. AIM: To examine managerial capacity among district health managers and its association with health system performance in six districts in the Eastern Region of Ghana.
METHODS: Fifty-nine district health managers' in six different performing districts in the Eastern Region of Ghana completed a self-administered questionnaire measuring their management competencies and skills. In addition, the participants provided information on their socio-demographic background; previous management experience and training; the extent of available management support systems, and the dynamics within their district health management teams. A non-parametric one-way analysis was applied to test the association between management capacity and district performance, which was measured by 17 health indicators.
RESULTS: Shortcomings within different aspects of district management were identified, however there were no significant differences observed in the availability of support systems, characteristics and qualifications of district health managers across the different performing districts. Overall management capacity among district health managers were significantly higher in high performing districts compared with lower performing districts (p = 0.02). Furthermore, district health managers in better performing districts reported a higher extent of teamwork (p = 0.02), communication within their teams (p<0.01) and organizational commitment (p<0.01) compared with lower performing districts.
CONCLUSION: The findings demonstrate individual and institutional capacity needs, and highlights the importance of developing management competencies and skills as well as positive team dynamics among health managers at district level.

Introduction

Decentralization of health care, where authority and responsibilities for service delivery are transferred from higher levels (e.g. central, federal or national) to lower levels (e.g. state, regional, district, sub-district), is frequently perceived as a way to improve health system performance as local authorities are better able to make informed decisions regarding local conditions [1-3]. However, in order to improve performance, individual capacity among local health managers are needed [1, 4–6]. Moreover institutional capacities, such as functional support systems and enabling work environments, including an appropriate level of autonomy for the managers’, must be in place [7].

This study focuses on district health managers (DHMs) working within District Health Management Teams (DHMTs) in Ghana. In Ghana, the DHMTs follow administrative directives issued by Ghana Health Service (GHS), the central level public health sector agency. The DHMTs have narrow decision-space with limited political and fiscal decentralization [8]. Nevertheless, they are mandated to convert inputs and resources, such as finance, staff, supplies, equipment and infrastructure into effective services that are responsive to the population needs [7, 9–11]. This mandate demands management capacity among the DHMs, defined as them having the abilities to keep the system functioning [12-14]; they must have the abilities to organize themselves effectively within the DHMTs in terms of encouraging teamwork, tackling problems collectively, spreading motivation and positive staff attitudes [15]. Moreover, they must have the abilities to manage health services (i.e. planning, supervising, monitoring quality and coverage), resources (i.e. staff, budgets, drugs, equipment, buildings and information), and stakeholders (external relations, partners, community members, service users and intersectoral stakeholders) [4, 16, 17]. Literature suggests weak management and leadership capacities among local health managers globally [7, 18–22]. However, a lack of tools for assessing management capacity among DHMs, results in limited knowledge about their actual competencies and qualifications [9, 18, 23].

Several studies suggest a positive association between district-level management capacity and health system performance [4, 24–30]. However, the study of Fetene et al in Ethiopia (2019) is to our knowledge the only in a lower income setting that has applied a quantifiable and precise measurement of management capacity at district level. Moreover, Fetene et al’s study appear to be the first to investigate the association between district level management capacity and health system performance measured by a wider set of public health indicators [4]. Further research is thus called for.

To enhance current knowledge on management capacity at district level and its association with health system performance in LMICs, this study aims to (1) explore qualifications and management competencies among DHMT members in Ghana, including characteristics of the DHMs and the systems they work in; and (2) to examine whether management capacity among DHMs is associated with health system performance.

Findings from this study can inform policy-makers and the global health community on areas in need of improvement for effective district health management in Ghana and other LMICs. Moreover, it can shed light on the importance of strengthening management capacity among local health managers in order to improve health system performance.

Methods

Ethics statement

This study was carried out as an integral part of the project PERFORM2Scale (P2S) under the lead of the Liverpool School of Tropical Medicine (LSTM). Ethical clearance was obtained from the Research Ethics Committee of LSTM (ID No.: 17–046) and the GHS Ethics Review Committee (ID No.: GHS-ERC:009/12/17). Additionally, permission was obtained from the Eastern Regional Health Administration. Written informed consent was obtained from all study participants and personal data were anonymized prior to analysis.

Study design

This cross-sectional study, consisting of a self-administered survey, took place as part of the baseline assessment of the P2S project aiming to scale up a piloted district management strengthening intervention [31].

Study setting

The survey took place in February and March 2018 in 6 of the 26 districts in the Eastern Region of Ghana. The study included the same districts as those in the P2S project. The districts were selected based on the following inclusion criteria: 1) willingness to participate in P2S, 2) them being clustered close to each other, 3) them representing different degrees of performance and (4) geographic entities (urban and rural). Characteristics of the study districts are available in Table 1.

Table 1

Characteristics of the six study districts.

	District 1	District 2	District 3	District 4	District 5	District 6
Population	165.271	85.810	108.053	130.295	104.888	114.409
Sub-districts	7	7	9	7	6	7
Geographical setting	Semi-Urban	Rural	Semi-Urban	Rural	Urban	Semi-urban
Health Facilities	60	47	32	40	62	50
District Hospitals	1	1	1	1	-	2
Health Centers	6	5	5	2	13	9
Maternity home	2	2	0	2	3	2
CHPS	47	39	26	35	46	37
District Performance*	43.0	47.0	52.0	52.25	56.50	61.50
Burden of Disease**	Malaria; Upper Respiratory Tract Infections;Anaemia	Malaria; Rheumatism and other joint pains; Upper Respiratory Tract Infections	Malaria; Diarrhea; Upper Respiratory Tract Infection	Malaria; Upper Respiratory Tract Infections; Rheumatism & other Joint pains	Malaria; Upper Respiratory Tract Infections; Rheumatism and other joint pains	Malaria; Upper Respiratory Tract Infections; Skin Diseases

*Based on the League of District Performance,

**Based on OPD attendance

Study population

Inclusion criteria for participation in the study were 1) being employed as a DHMT member in one of the P2S study districts at the time of the study; and 2) having supervisory, administrative and management responsibilities within the study district.

Data collection

Each DHM completed a self-administered questionnaire assessing their management competencies and skills, cf. S1 File. The questionnaire included 132 closed—and open-ended items divided into seven sections; 1) socio-demographic background; 2) management experience and exposure to management training; 3) functional management support structures and systems (i.e. for planning and budgeting, procurement of drugs and other commodities, data and human resource management); 4) general management competencies (i.e. interpersonal skills; leadership and conflict handling skills; time planning); 5) specific health system management competencies (oversight and coordination; human resource management; resource management; financial management; information management; service delivery and community involvement); 6) overall management performance; and lastly 7) being part of a DHMT (teamwork, communication, organizational commitment, job motivation and satisfaction among DHMs).

The DHMs rated their overall management capacity on a five-point Likert scale ranging from 1 (very poor) to 5 (excellent). The remaining items relating to competencies and being part of the DHMT were rated from 1 (“Strongly Disagree”) to 5 (“Strongly agree”), while the availability of management support systems and structures were rated from 1 (“To a small extent”) to 5 (“To a high extent”).

A paper-based version of the questionnaire was distributed to DHMT members by members of the P2S research team. Prior to doing so, the aim of the survey was explained to the respondents and they were given the opportunity to ask questions for clarity.

Validity of the questionnaire

The survey measuring managerial capacity among DHMs were developed by the authors due to absence of an existing assessment tool at the time of the study. The survey was developed based on a 1) literature review on what facilitates good management at district level in LMICs, and 2) on in-depth interviews conducted as part of the P2S initial context analysis, with DHMs, as well as with their supervisors (Regional Health Administrators) and peers (NGOs working within the study districts). To further ensure face and content validity, the questionnaire was developed and reviewed in an iterative process with five experts from the P2S consortium, including professionals from Ghana to ensure the appropriateness for a Ghanaian context. A total of 109 items were specifically developed for this study, while 22 were existing validated indexes.

The questionnaire was validated through five separate cognitive interviews with five DHMs’ in two non-study districts in the Eastern Region, a similar approach to other studies [32, 33]. The interviewees were asked to think loud when completing the questionnaire and explain why they responded as they did in order to identify questions that may elicit response error. The questionnaire was adjusted based on the five first interviews, and followed by five additional cognitive interviews with five other DHMs in the non-study districts.

Data analysis

District performance

The dependent variable in our analysis is district performance. District performance is stated in Table 1, with District 1 having the lowest performance score and District 6 the highest performance score. Each of the study districts’ performance was extracted from the Ghana League Table of District Performance (TDP), which includes data from the District Health Information Management System (DHIMS2) on 17 public health indicators, cf. Box 1, S2 File. The TDP ranks the 26 districts in the Eastern Region according to their aggregated annual performance score (average of four quarters). In 2017, the average annual score across the 26 districts ranged from 41.75 to 70.0 on a scale of 100.

Box 1: District performance health indicators included in the Ghana League Table of District Performance

(1) Outpatient Department Visits per capita, (2) Percentage of teenage pregnancies among ANC registrants, (3) Family planning Acceptor rate; (4) Percentage skilled deliveries, (5) Measles-Rubella-2 coverage, (6) Under 5 Malaria Case Fatality Rate, (7) % Pregnant women tested HIV positive, (8) Penta 3 coverage, (9) Isoniazid Preventive Therapy, (10) Antenatal Coverage, (11) Authorisation completeness, (12) Authorisation Timeliness, (13) Integrated Disease Surveillance and Response (IDSR) Weekly Timeliness, (14) IDSR Monthly Completeness, (15) Non Polio AFP rate, (16) Data Entry Completeness, (17) Data Entry Timeliness.

Independent variables

Characteristics of the DHMs, i.e. their sex, age, educational background, previous management experience and training, as well as systemic factors, i.e. the number of DHMs in each DHMT and available management support systems and structures were included as independent variables.

The primary independent variable, namely the DHMs’ management capacity, was measured by the item “Overall, how would you rate your management and leadership skills and competencies?”. In addition, sum variables measuring the DHMs’ general management and leadership skills were included, i.e. their conflict handling and interpersonal skills (e.g. “I ensure that staff under my supervision feel their contributions are valued and appreciated“) (3 items), leadership skills (i.e. “I am confident in my abilities to direct and motivate people I work with”) (5 items), and time planning skills (“I plan my workload by setting up daily/weekly/monthly to-do-lists”) (3 items). Moreover sum variables were included on the DHMs’ competencies related to health system management, i.e. oversight and coordination (4 items), problem analysis (6 items), planning (7 items), implementation and monitoring (3 items) and reporting (2 items), as well as their skills within human resource management (11 items), resource management (4 items), information management (3 items), financial management (3 items) and service delivery and community involvement (3 items). The internal consistency of the sum scales were tested by the Cronbach alpha to ensure a reliability coefficient of 0.7 or higher [34, 35].

Lastly, validated scales were included measuring the DHMs’ ability to organize themselves effectively within their DHMTs, i.e. their teamwork (7 items) [36], job satisfaction (6 items) [37], motivation (3 items)[38] and organizational commitment in terms on their desire to stay (3 items) [37]. Moreover, an adapted and shortened version of Hoegl et al. items on communication within the DHMT (4 items) were included [39].

Statistical analysis

Bivariate analyses were performed to evaluate differences across the different performing districts in DHM characteristics and available management support systems and structures. Non-parametric one-way analyses were applied, namely Fisher’s exact test for categorical variables and Kruskal Wallis test for continuous variables.

In order to test the hypothesis that management capacity among DHMs was positively associated with health system performance, we used a non-parametric test for trend across ordered groups [40]. In light of the relatively low number of DHMs in each district, a multivariable regression model was not developed due to concerns about the reliability of the model.

All statistical analyses were performed with the statistical software Stata (Stata 14; StataCorp LP, College Station, TX, USA).

Results

A total of 61 DHMs were invited to participate in the study. Hereof 59 completed the questionnaire (96.7% response rate). Non-respondents were caused by DHMs opting not to respond due to their busy schedule (n = 2). Six DHMs could not be included in the study as they were on maternity or sick leave (n = 4) or absent during the research teams’ site visit (n = 2).

Comparative analysis of district health managers’ in different performing districts

Shortages of core administrative managers were observed in District 2, 4 and 6 (Table 2). All districts had a DHM within the technical areas of disease control, nutrition and health information, yet two districts were missing a Health Promotion Manager (4 and 5) and a Public Health Nurse (1 and 3). In terms of operational managers, half the districts were missing a HR Officer as well as a Supply Officer. Finance officers were present in all districts, except District 1.

Table 2

Members of the district health management teams across study districts.

	District 1	District 2	District 3	District 4	District 5	District 6
Administrative managers	3	2	3	1	3	1
Director of Health Services	***1	1	1	1	1	1
Administrator	1	1	1	-	1	-
Dep. Dir. of Nursing Services	1	-	1	-	1	-
Technical managers	5	6	5	6	6	7
Public Health Nurse	-	×1	-	1	2	*1
Disease Control Officer	2	2	2	2	2	2
Health Information Officer	***1	1	1	2	1	1
Nutrition Officer	1	×1	1	1	1	1
Health Promotion Officer	1	1	1	-	-	**2
Operational managers	2	1	2	3	1	2
Finance Officer	-	1	1	1	1	1
Supply/Procurement Officer	1	-	1	1	-	-
Human Resource Officer	1	-	-	1	-	1
Other	2	1	1	-	3	1
Pharmacist	1	-	-	-	-	-
Mental Health Officer/Psychiatry Nurse	-	1	1	-	**2	-
Principal Nursing Officer/CHN	1	-	-	-	*1	-
Quality Assurance Officer	-	-	-	-	-	*1
Total (n = 67)	12	10	11	10	13	11
Active DHMT members (n = 63)	12	10	11	10	11	9
Responded to survey (n = 59)	10	8	11	10	11	9

CHN: Community Health Nurse,

*Sick/maternity leave;

**1 missing due to sick leave;

***Absent;

×Non-respondents

There were no significant differences in the demographic and educational characteristics of the DHMs across the six districts (Table 3). Most of the DHMs’ had a clinical background (20.3%) or a background in public health (35.4%). The most frequent highest educational qualification was a bachelor degree (44.1%) followed by a certificate/diploma (42.4%). More than one third of the respondents (34.5%) had less than 1 year of management experience prior to their current position. Moreover, less than half of the respondents (41.1%) had received formal training in management and leadership, i.e. degrees, certificate or diplomas. More than half (64.8%) had received informal management training within the last 12 months, i.e. mentoring, in-service training, non-certified programs.

Table 3

Characteristics of study participants across different performing district.

	D1 (n = 10)	D2 (n = 8)	D3 (n = 11)	D4 (n = 10)	D5 (n = 11)	D6 (n = 9)	Total (n = 59)	*p
	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
Sex								0.98
Male	5 (50.0)	5 (62.5)	6 (54.5)	5 (50.0)	5 (45.5)	4 (44.4)	30 (50.9)
Female	5 (50.0)	3 (37.5)	5 (45.5)	5 (50.0)	6 (54.5)	5 (55.6)	29 (49.1)
Age								**0.37
Mean (range)	39.1 (29–57)	39.5 (32–54)	41.6 (30–58)	35.6 (30–54)	42 (33–57)	36.8 (27–55)	39.2 (27–58)
Educational background								0.99
Public Health	3 (30.0)	3 (37.5)	5 (45.4)	3 (30.0)	3 (27.7)	4 (44.4)	21 (35.6)
Medical Doctor /Nursing/Midwife	2 (20.0)	3 (37.5)	1 (9.1)	2 (20.0)	3 (27.7)	1 (11.1)	12 (20.3)
Accounting/Financing	0	1 (12.5)	1 (9.1)	2 (20.0)	1 (9.1)	1 (11.1)	6 (10.2)
Human Resource Management	1 (10.0)	0	1 (9.1)	1 (10.0)	0	0	3 (5.1)
Nutrition	1 (10.0)	0	1 (9.1)	1 (10.0)	1 (9.1)	1 (11.1)	5 (8.5)
Other	3 (30.0)	1 (12.5)	2 (18.2)	1 (10.0)	3 (27.3)	2 (22.2)	12 (20.3)
Highest educational qualification								0.97
Certificate/Diploma	4 (40.0)	4 (50.0)	6 (54.6)	3 (30.0)	4 (36.4)	4 (44.4)	25 (42.4)
Bachelor	5 (50.0)	2 (25.0)	4 (36.4)	5 (50.0)	6 (54.5)	4 (44.4)	26 (44.1)
Master/PhD	1 (10.0)	2 (25.0)	1 (9.1)	2 (20.0)	1 (9.1)	1 (11.1)	8 (13.6)
Years in current position								0.52
<5	6 (60.0)	3 (37.5)	3 (27.3)	7 (70.0)	7 (63.6)	4 (44.4)	30 (50.9)
5–10	3 (30.0)	4 (50.0)	6 (54.6)	2 (20.0)	2 (18.2)	5 (55.6)	22 (37.3)
>10	1 (10.0)	1 (12.5)	2 (18.2)	1 (10.0)	2 (18.2)	0	7 (11.9)
Previous management experience								0.88
<1yrs	5 (50.0)	3 (37.5)	3 (30.0)	3 (30.0)	2 (18.2)	4 (44.4)	20 (34.5)
1-5yrs	2 (20.0)	2 (25.0)	2 (20.0)	6 (60.0)	5 (45.5)	3 (33.3)	20 (34.5)
5+ yrs	3 (30.0)	3 (37.5)	5 (50.0)	1 (10.0)	4 (36.4)	2 (22.2)	18 (31.0)
Experience from other DHMTs								0.48
Experience	4 (40.0)	6 (75.0)	6 (54.5)	4 (40.0)	4 (36.4)	6 (66.7)	30 (50.9)
No experience	6 (60.0)	2 (25.0)	5 (45.5)	6 (60.0)	7 (63.6)	3 (33.3)	29 (49.2)
Formal Management & Leadership training								0.40
Formal training	4 (44.4)	2 (28.6)	4 (40.0)	7 (70.0)	4 (36.4)	2 (22.2)	23 (41.1)
No formal training	5 (55.6)	5 (71.4)	6 (60.0)	3 (30.0)	7 (63.6)	7 (77.8)	33 (58.9)
Informal Management and Leadership training within the 12 months								0.44
Informal training	7 (77.8)	6 (85.7)	6 (54.5)	7 (78.8)	5 (45.5)	5 (45.5)	35 (64.8)
No informal training	2 (22.2)	1 (14.3)	5 (45.5)	2 (22.2)	6 (54.5)	6 (54.5)	19 (35.2)

*Fisher’s exact,

**Kruskal Wallis test,

1) Master of Science in Pharmacy (n = 1), Bachelor in Health Service Administration (n = 1), Diplomas in Management, Health Promotion and Disease Control (n = 3), 2) Masters in Disease Control and Prevention (n = 1), a Bachelor in Health Administration (n = 1) and a Bachelor in Business Administration (n = 1), 3) Bachelor’s in Health Management (n = 1), Masters in General Management (n = 1), Diploma in Purchasing and Supply (n = 1), Master of Philosophy in Leadership (n = 1)

Differences in system factors across different performing districts

Table 4 demonstrates whether management structures and systems were in place to support DHMs in carrying out their role. There were no significant differences across the districts. All DHMs reported having received job descriptions specifying their respective tasks. However, the majority (88.1%) reported that they to a moderate/large extent took on additional roles and responsibilities that were not stated in their job description. All DHMs, except from in two districts (4 and 6), reported having access to relevant national and/or regional guidelines within the different work areas (i.e. on disease surveillance and response for disease control officer, postings of health workers for HR officers, budgeting for finance officers). Regular team meetings (weekly) took place to a moderate (20.3%) or large extent (79.7%) in all districts, and records of team meetings were available (96.1%). In regards to supportive supervision, feedback and monitoring from supervisors, 10.3% reported receiving no or little supervision. Over half of the respondent reported inadequate funds (69.5%), logistics and infrastructure (55.9%) for carrying out their planned activities.

Table 4

Functional support systems across different performing district.

	D1 (n = 10)	D2 (n = 8)	D3 (n = 11)	D4 (n = 10)	D5 (n = 11)	D6 (n = 9)	Total (n = 59)	p*
	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
Additional responsibilities besides what is stated in job description								0.59
Not at all/Small extent	2 (20)	0	2 (18.2)	0	2 (18.2)	1 (11.8)	7 (11.8)
To a moderate/large extent	8 (80)	8 (100)	9 (81.8)	10 (100)	9 (81.8)	8 (88.9)	52 (88.1)
Access to relevant national and/or regional guidelines within your work area								0.18
Not at all/Small extent	2 (20)	0	2 (18.2)	0	0	0	4 (6.9)
To a moderate/large extent	8 (80)	7 (100)	9 (81.8)	10 (100)	11 (100)	9 (100)	54 (93.1)
Regular team meetings								0.87
To a moderate extent	2 (20.0)	2 (25.0)	2 (18.2)	2 (20.0)	1 (9.1)	3 (33.3)	12 (20.3)
To a large extent	8 (80.0)	6 (75.0)	9 (81.8)	8 (80.0)	10 (90.9)	6 (66.7)	47 (79.7)
Available records of team meetings								0.93
Not at all/Small extent	0	0	0	1 (10.0)	1 (9.1)	0	2 (3.4)
To a moderate/large extent	10 (100)	8 (100)	11 (100)	9 (90.0)	10 (90.9)	9 (100)	57 (96.1)
Supportive supervision, feedback and mentoring from your supervisor								0.12
Not at all/Small extent	0	1 (12.5)	2 (18.2)	3 (30.0)	0	0	6 (10.3)
To a moderate/large extent	10 (100)	7 (87.5)	9 (81.8)	7 (70.0)	11 (100)	8 (100)	52 (89.7)
Adequate funds to carry out planned activities								0.59
Not at all/Small extent	7 (70.0)	6 (75.0)	9 (81.8)	7 (70.0)	5 (45.5)	7 (77.8)	41 (69.5)
To a moderate/large extent	3 (30.0)	2 (25.0)	2 (18.2)	3 (30.0)	6 (54.6)	2 (22.2)	18 (30.5)
Adequate logistics and infrastructure to carry out planned activities								0.42
Not at all/Small extent	5 (50.0)	4. (50.0)	8 (72.7)	5 (50.0)	4 (36.4)	7 (77.8)	33 (55.9)
To a moderate/large extent	5 (50.0)	4 (50.0)	3 (27.3)	5 (50.0)	7 (63.6)	2 (22.2)	26 (44.1)
Are there systems and structures in place to support within the following areas?
Planning and budgeting								0.89
Not at all/Small extent	2 (22.2)	1 (9.1)	3 (30.0)	2 (18.3)	2 (25.0)	1 (14.3)	11 (19.6)
To a moderate/large extent	7 (77.9)	10 (90.9)	7 (70.0)	9 (81.8)	6 (75.0)	6 (85.7)	45 (80.4)
Procurement of drugs and other commodities								0.42
Not at all/Small extent	2 (25.0)	2 (20.0)	1 (14.3)	0	1 (12.5)	0	6 (11.5)
To a moderate/large extent	6 (75.0)	8 (80.0)	6 (85.7)	9 (100)	7 (87.5)	10 (100)	46 (88.5)
Data management								0.68
Not at all/Small extent	0	0	1 (11.1)	2 (18.2)	1 (12.5)	1 (10.0)	5 (8.6)
To a moderate/large extent	9 (100.0)	11 (100.0)	8 (88.9)	9 (81.8)	7 (87.5)	9 (90.0)	53 (91.4)
Human resource management								0.98
Not at all/Small extent	1 (12.5)	1 (10.0)	1 (12.5)	2 (20.0)	1 (12.5)	0	6 (12.2)
To a moderate/large extent	7 (87.5)	9 (90.0)	7 (87.5)	8 (80.0)	7 (87.5)	5 (100)	43 (87.8)
Community-level structures or groups that enable community involvement								0.14
Not at all/Small extent	3 (42.9)	1 (10.0)	1 (11.1)	5 (50.0)	1 (12.5)	1 (12.5)	12 (23.1)
To a moderate/large extent	4 (57.1)	9 (90.0)	8 (88.9)	5 (50.0)	7 (87.5)	7 (87.5)	40 (76.9)

*Fisher’s exact t-test

The majority of respondents rated support systems to be in place to a moderate or large extent, particularly in regards to data management (91.4%), procurement of drugs and other commodities (88.5%) and HR management (87.8%). The largest inadequacies were observed in terms of systems for planning and budgeting (19.6%), as well as for engaging communities (23.1%).

The association between management capacity and district performance

As shown in Table 5, the DHMs overall rating of their management capacity was significantly associated with district performance; the self-assessed management capacity tended to increase from the low to high performing districts (p = 0.017).

Table 5

Management capacity across different performing districts.

District	District 1	District 2	District 3	District 4	District 5	District 6	Total	p*
Overall Management Capacity	n = 10	n = 8	n = 11	n = 10	n = 11	n = 9	n = 59
Mean (SD)	3.5 (1.0)	3.9 (0.6)	4.1 (0.3)	4.2 (0.6)	4.3 (0.5)	4.1 (0.3)	4.0 (0.6)	0.02
Oversight and Coordination	n = 10	n = 8	n = 11	n = 10	n = 11	n = 9	n = 59
Situational analysis1	4.4 (0.6)	4.3 (0.5)	4.5 (0.5)	4.5 (0.6)	4.5 (0.6)	4.4 (0.6)	4.4 (0.5)	0.47
Problem analysis2	4.1 (0.7)	4.5 (0.5)	4.4 (0.5)	4.4 (0.5)	4.4 (0.7)	4.5 (0.6)	4.4 (0.6)	0.25
Planning3	4.0 (0.9)	4.4 (0.7)	4.0 (0.7)	3.9 (0.8)	4.2 (0.8)	4.3 (0.7)	4.1 (0.8)	0.63
Implementation and Monitoring4	4.1 (0.7)	4.5 (0.8)	4.1 (0.7)	4.4 (0.7)	4.4 (0.7)	4.3 (0.7)	4.3 (0.7)	0.78
Reporting5	4.6 (0.7)	4.6 (0.6)	4.5 (0.5)	4.5 (0.7)	4.7 (0.5)	4.5 (0.5)	4.6 (0.5)	0.84
Human Resource Management6	n = 7	n = 7	n = 9	n = 9	n = 10	n = 6	n = 48
Mean (SD)	4.5 (0.5)	4.2 (0.6)	4.1 (0.6)	3.9 (0.9)	4.3 (1.0)	4.2 (0.8)	4.2 (0.7)	0.91
Resource Management7	n = 9	n = 7	n = 8	n = 10	n = 10	n = 9	n = 53
Mean (SD)	4.1 (0.8)	4.5 (0.4)	4.3 (0.6)	3.7 (1.2)	4.5 (0.5)	3.8 (0.6)	4.1 (0.8)	0.18
Financial Management8	n = 8	n = 8	n = 10	n = 9	n = 10	n = 8	n = 53
Mean (SD)	3.9 (0.6)	4.2 (1.1)	4.2 (0.6)	3.5 (1.2)	4.1 (1.3)	3.8 (1.2)	3.9 (1.0)	0.74
Information Management9	n = 9	n = 8	n = 10	n = 9	n = 9	n = 8	n = 54
Mean (SD)	4.4 (0.9)	4.6 (0.9)	4.5 (0.5)	4.6 (0.5)	4.7 (0.4)	4.2 (0.6)	4.5 (0.7)	0.22
Service Delivery & Community Involvement10	n = 9	n = 6	n = 8	n = 7	n = 7	n = 7	n = 44
Mean (SD)	4.4 (0.5)	4.7 (0.5)	4.5 (0.5)	4.5 (0.5)	4.2 (0.7)	4.0 (0.6)	4.4 (0.6)	0.17
Dynamics within the DHMT	n = 10	n = 8	n = 11	n = 10	n = 11	n = 9	n = 59
Teamwork	3.8 (0.8)	4.1 (0.7)	4.4 (0.4)	4.2 (0.6)	4.3 (0.5)	4.5 (0.4)	4.2 (0.6)	0.01
Communication	3.8 (0.7)	4.1 (0.8)	4.5 (0.5)	4.0 (0.8)	4.6 (0.5)	4.7 (0.4)	4.3 (0.7)	<0.01
Motivation	3.1 (0.9)	3.3 (0.7)	3.9 (0.7)	4.0 (0.7)	3.3 (0.5)	3.7 (0.7)	3.6 (0.7)	0.12
Job satisfaction	3.5 (0.4)	3.4 (0.6)	3.5 (0.4)	3.5 (0.7)	3.6 (0.5)	3.8 (0.5)	3.5 (0.5)	0.11
Organizational commitment	3.7 (0.5)	3.6 (0.9)	4.5 (0.6)	4.0 (1.1)	4.3 (0.7)	4.6 (0.8)	4.1 (0.8)	<0.01

*Oneway non-parametric test for trend (nptrend);

Sum-scales mean score:

1) 4 items, Cronbach alpha 0.76,

2) 6 items, Cronbach alpha 0.88,

3) 7 items, Cronbach alpha 0.92,

4) 3 items, Cronbach alpha 0.92,

5) 2 items, Cronbach alpha 0.83,

6) 11 items, Cronbach alpha 0.95

7) 4 items, Cronbach alpha 0.93

8) 3 items, Cronbach alpha 0.84

9) 3 items, Cronbach alpha 0.93

10) 3 items, Cronbach alpha 0.73

The difference across district groups in general management and leadership competencies was not significant (Fig 1). However, as shown in Fig 1, there is an evident tendency among DHMs in the lower performing districts to rate their interpersonal, leadership and conflict handling skills more negatively than the DHMs in the higher performing districts.

Fig 1

General management and leadership competencies among district health managers in high, mid and low performing districts.

Red: Lowest performing districts (District 1 & 2), Yellow: Mid performing districts (District 3 & 4), Green: Highest performing districts (District 5 & 6). No statistical significant difference (p>0.05, oneway non-parametric test for trend); Interpersonal Skills: 2 items, Cronbach alpha 0.88, Time Planning Skills: 3 items, Cronbach alpha 0.86, Leadership Skills: 5 items, Cronbach alpha 0.9, Conflict Handling: 1 item.

Competencies within the various health system management domains did not differ significantly between the districts (Table 5). District health managers’ across all districts appeared to be confident in their skills related to reporting and carrying out situational and problem analyses, yet less confident in their planning, implementation and monitoring skills. Competencies within management of human resources, resources and finances were rated less positively compared with information management, service delivery and community involvement.

Dynamics among the DHMs, i.e. teamwork, communication and organizational commitment, differed across the districts (Table 5), with a tendency of higher ratings in the higher performing districts. The highest performing district group scored best on all measures, except motivation where District 3 had a higher average score.

A total of 55.2% of the respondents stated that they did not reach their objectives set in their Annual Appraisal Form for the previous year, and 94.9% stated a desire to improve their management competencies within certain areas (results not shown). The areas mentioned included financial management (n = 7), information management (n = 5), HR management (n = 2), general management and leadership skills (n = 12), conflict management (n = 4), time planning (n = 3), communication (n = 2), report writing (n = 3), how to involve community members (n = 2), advocacy and lobbying (n = 3) and supervision skills (n = 3). Lastly, seven people mentioned that they would like to improve specific competencies, i.e. research, reproductive and child health, malaria control and information management (i.e. gathering, analyzing and reporting information from facilities, stakeholders and communities to improve health services).

Discussion

No systematic differences were observed across the different performing districts in terms of DHMT characteristics, functional support systems and specific management competencies. Nevertheless, differences were found in overall perceived management capacity, organizational commitment, teamwork and communication within the DHMTs. Management capacity and DHMT dynamics were positively correlated with health system performance.

District health managers and the system they work in

Despite not being able to explain the differences in health system performance by systematic differences in the characteristics of DHMs and available functional management support systems, our findings contribute to health system research by identifying areas in which district health systems can be strengthened [9, 18, 23].

The WHO Leadership and Management Strengthening framework lists an adequate number of DHMs as an important element in having a robust health system [7]. We observed shortcomings in the number of core managers, converging with other studies in LMICs [7, 41, 42]. When staff shortages exist, current DHMs have to take on additional roles, which leaves them with a higher workload and tasks they do not have the appropriate competencies for. This will consequently affect their output [43], and may be the reason why more than half of the DHMs in this study did not reach their annual objectives. The DHMTs do not have authority to hire additional staff members, and thus depend on higher levels to recruit an adequate number of DHMs. This can be challenging in settings with a scare workforce, yet it is essential in order to have a well-functioning decentralized health system.

In our study, almost half of the DHMs had received formal management training. In Ghana, the District Directors of Health Services who lead the DHMTs, are strongly encouraged to undergo a certified management training course at the Ghana Institute of Management and Public Administration to prepare them for their role [44]. Thus, Ghana seems to be advancing in terms of competent DHMs compared to other countries, where DHMs often are described as clinical staff that have been promoted to management positions with little or no structured management training [12, 30, 43, 45, 46]. However, there is still improvement potential; more than one third of DHMs in this study had less than one year of management experience before entering their current role, and the majority had a bachelor degree or lower as highest educational qualification. Moreover, the majority of the respondents stated a desire to develop their competencies in order to carry out their job.

Additional areas with room for improvement include the extent of supervision provided to DHMs. Supervision plays a critical role in creating an enabling work environment where DHMs are appraised and incentivized to perform better [47-49]. Moreover, regular meetings and structures to enable community involvement should be present to a larger extent. Regular meetings have been described as an effective strategy to improve performance as they create a forum for addressing pressing issues, reflecting on progress and sharing information [6, 23, 43]. Community engagement can be helpful to identify needs and gain feedback from the community, in addition to enhancing accountability of health workers, and is thus an important component to train and empower DHMs in [46, 50].

This study demonstrates that DHMs perceive funds, logistics and infrastructure to be inadequate for carrying out planned activities. Irregularity in budgetary transfers in Ghana [50, 51], as well as in other countries [43, 52], results in DHMTs not having money to buy fuel and maintain vehicles. This affects their motivation negatively and prohibits them in carrying out essential supervision tasks [41, 51]. Apart from ensuring that resources are received by districts in a timely manner, DHMs’ competencies in managing resources (financial, material and human) should be enhanced. Moreover, user-friendly systems for effective planning and budgeting should be in place.

District management capacity and its association with health system performance

Overall, management competencies were positively rated by the DHMs in this study. However, potential for improvement was identified within certain areas, i.e. time planning, conflict handling and resource management (financial, material and human), converging with other studies on district health management [46, 49, 53]. Further research should look into the most effective ways to enhance such skills. Filerman suggest that essential management competencies are learned most effectively if the training takes place where the managers’ work, within the team and it addresses existing challenges [22]. Gholipour et al describes that the academic credibility of the instructors are important, and that meeting and sharing experiences with peers from other districts also can be an effective approach to strengthen district management [45].

A positive association was identified between the DHMs’ overall management capacity and district health performance. Moreover, higher ratings of general management and leadership skills were observed among DHMs in the higher performing districts. The relatively small sample may have prevented the detection of a statistical significant association.

There was no association observed between district performance and the DHMs assessment of competencies within the specific health system domains. Moreover, the specific management competencies were generally rated more positively than the overall managerial capacity. The discrepancy may be caused by the fact that a subgroup of the DHMs responded to the items within the various domains, namely those involved in carrying out tasks related to the specific areas. These may thus have been particularly competent within their defined area of responsibility.

The higher ratings may also reflect areas, which frequently are targeted by management training, i.e. information management, reporting, implementation and monitoring. Technical skills relating to these areas are essential, yet do not necessarily improve the DHMs abilities to organize themselves effectively within the DHMTs, in terms of encouraging teamwork, tackling problems collectively, spreading motivation and positive staff attitudes. The DHMs assessments of communication, teamwork and organizational commitment were associated with their assessment of their overall managerial capacity, as well as with district performance. In alignment, Seims et al found that strengthening leadership and management skills among DHMs in Kenya through a team-based approach led to significant increases in health-service delivery [24]. The importance of building abilities among DHMs to work effectively within teams has been confirmed by other studies as well [5, 10, 23, 43, 54], and an emphasis on this should thus be ensured in district level management strengthening efforts.

It is important to note that management capacity among DHMs only is one of many factors that may affect district performance. Firstly, regardless of management competencies and skills, management practices may be constrained by the DHMs lack of authority to make decisions. Priorities at higher levels determine how DHMs carry out their responsibilities, which limits them in responding to the needs of their district [42, 51]. Secondly, district health system performance is affected by a myriad of other factors than district management, which were not adjusted for in current study. These include the economic status of a district, household economic conditions and poverty, general infrastructure, degree of urbanization, health facility management, social, religious affiliations and traditional beliefs that may render healthcare utilization [4, 55, 56]. Nevertheless, the positive association between district management and health system performance is confirmed in adjusted analyses performed in Fetene et al’s study in Ethiopia. Their findings suggest that stronger management among district health officers magnify the positive effects of strong management at health facility level. Being the first point of primary care, management at health facilities play an important role in Ghana too [57], and future studies is suggested to explore management at health facility level and its synergy with management at district level.

Measures of management capacity and health system performance

Management capacity is a complex concept to measure. This study measured it through a self-administered survey, which is an approach that has been used in other studies [45, 58–61]. The self-assessment methodology is founded on the concept of self-efficacy that posits that individuals who feels greater confidence in their ability to perform is more likely to successfully perform [30]. However, it is important to be aware of the fact that differences may exist between self-reported management behavior and actual behavior as observed by subordinates, superiors and peers [62]. Managers’ self-ratings tend to be inflated, which most likely also is the case in this study, where positive ratings in general were observed despite previous research suggesting a lack of capacity among DHMs. This study is to our knowledge the first study to measure management capacity through a questionnaire that were thoughtfully developed to assess management competencies among DHMs in a time and cost efficient way; validity and reliability was sought through expert review and cognitive interviews, which have been described to be effective when exploring new or poorly described concepts [32]. The identified correlation between self-reported managerial capacity and the objective measure of district performance, may be an indicator of criterion-related validity [63]. Nevertheless, further reliability and validity measures may enhance the effectiveness of the questionnaire; internal validity can be improved by including observations and additional assessments of the DHMs capacity from their superiors (Regional Health Administration), subordinates (health facilities) and peers (NGOs and other stakeholders) [64].

The outcome variable, district performance, is based on data from DHIMS2, and the analyses were thus carried out under the assumption that DHIMS2 data in Ghana is reliable [65]. However, it should be noted that inconsistencies can occur in DHMIS2, i.e. late or non-reporting from some health facilities, which could introduce misclassification bias of the exposure. Lastly, quality of care, which is an essential aspect of health system performance [66], was not reflected by the seventeen TDP indicators. Future research concerning health system performance should take this into consideration.

Study limitations

The causal relationship between management capacity and performance cannot be established due to the cross-sectional study design; high performing districts may for instance have attracted highly competent DHMs or the confidence of DHMs self-assessment may have been affected by them being aware of the ranking of their districts’ performance. If the district performance has affected the DHMs perception of their competencies, there may be differential misclassification and thus a biased measure of association. Moreover, the test of significance may have been influenced by the relatively small sample size; an effect that failed to be significant (p<0.05) could prove significant in a larger samples. Further exploration of this research topic would benefit from longitudinal studies, as well as from larger studies with more statistical power and greater generalizability.

Due to the sample size, adjusted analyses could not be performed, and the confounding effect of mentioned factors affecting health system performance have not been established. Future studies may, if their sample size allows, eliminate confounding factors by running adjusted analyses, or by comparing performance between similar districts in regards to socio-demographic district characteristics. The latter was attempted in current study where there were no major differences across the districts in terms of DHM characteristics (Table 3) and availability of functional support systems (Table 4). Moreover, all study districts were located in the same region, governed by the same Regional Health Administration, and thus similar in terms of the DHMs level of authority, regional guidelines and procedures, climate and disease burden, cf. Table 1.

The inclusion of different performing, urban and rural districts makes current study findings generalizable to districts within the Eastern Region, yet to ensure external validity the questionnaire has to be tested in other settings.

Conclusion

The complexity of district management and its association with health system performance is difficult to capture. However, despite the study limitations, our findings indicate a strong association between self-reported management capacity and health system performance at district level in Ghana, which should be researched further. Moreover, this study identified areas within district health management that should be improved through policy making, i.e. inadequate supervision, funds and logistics available to DHMs, and targeted efforts, i.e. the DHMs motivation, specific management competencies and lack of management support systems.

Questionnaire, district health managers’ self-assessed management capacity.

(DOCX)

Click here for additional data file.

District performance tables.

(PDF)

Click here for additional data file.

3 Sep 2019

PONE-D-19-20019

District Health Management and its association with District Performance: A comparative descriptive study of six districts in the Eastern Region of Ghana

PLOS ONE

Dear Miss Heerdegen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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The reviewers find the work of merit but have requested some additions and revisions, In addition to the items raised by the reviewers, please address the following points:

Clarify the concept of “District Health Management” in introduction and also modify it in method and title to avoid misunderstandings. In some case District Health Management means a structure of management and in your case it means the head managers of this structure not the management as a mechanism and structure.

Clarify whether you consider the role and capabilities of district health managers as district health management role and capabilities in discussion and limitation section.

You can find new references instead of old one. I recommend you discuss and compare your findings with the result of a series of paper we published in relation to district health management as a similar setting in a developing country. In this project we investigate the district health management environment in a developing country (Managerial barriers and challenges in Iran public health system: East Azerbaijan health managers' perspective. J Pak Med Assoc) after that develop management training program (Developing management capacity building package to district health manager in northwest of iran: a sequential mixed method study. J Pak Med Assoc), then design a management performance framework (A framework to assess management performance in district health systems: a qualitative and quantitative case study in Iran. Cadernos de saude publica) and finally implement and evaluate training programme (Evaluation of the district health management fellowship training programme: a case study in Iran. BMJ open).

Clarify the table topics,  such a “high”, “low”, “A”, “B”,… without any directive explanation.

Provide self-administered questionnaire, study protocol, informed consent as appendix.

Describe the self-administered questionnaire validation process in detail (how many expert, Validation methods, Analysis, …).

Describe cutoff point for Cronbach’s alpha coefficient and the result of your study.

Provide detailed information in relation to District Health Information Management System (DHIMS2) analysis method and process as appendix.

Consider confounding factor in your analysis and provide more detail in relation to controlling their in Statistical analysis section.

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Reviewer #1: This is a descriptive study to assess the relationship between management capacity and district performance in the Eastern Region of Ghana. First, I would like to commend the authors for a comprehensive effort to assess public health/health management capacity in a LMIC context as well as for a well-written manuscript.

1. My primary concern relates to the generalizability of the study beyond those surveyed. The study was conducted in one region in the country. Further, in that region only 6 out 26 districts were assessed.

2. The authors conclude that there is an association between management capacity and district performance. While this is technically right (since they measured management capacity as perceived management capacity), all other objective measures of management competencies, included in this study, were not found to be associated with district performance. Thus, it is a bit hard for this reviewer to agree with the above-mentioned conclusion. Why was there a misalignment between the findings based on perceived management capacity and the objective measures of management competencies? Perhaps, (a) an association between self-reported capacity was observed primarily because the majority of the district managers in the low performing districts reported little prior management experience or training (as reported). Thus, these managers, because of the lack of training or experience viewed themselves as lacking in management skills, even though they may not have differed from other managers.

(b) There really was not enough variation in the performance measure to warrant the classification of three distinct groups (low medium, high). The cut-off points for these felt a bit arbitrary.

(c) Also it is possible that the lack of statistical significance across several of the indicators assessed may be due to a small sample size. I would love to see the authors discuss these above-mentioned issues a bit more.

3. Notably, what is a bit more apparent is the relationship between performance and work-place dynamics.

Minor

Abstract: Aim: May be missing "competencies" after "management"

Figure 1: Indicates (lines 234-237) that low performing districts have lower scores in time planning than mid-performing. The figure as shown indicates little difference between the two groups. Suggest that the authors exclude time planning from the list.

Reviewer #2: This is a study of the association between District Health Management and District Performance in six districts in the Eastern Region of Ghana. The benefit of this article is the deeper exploration than in previous studies, such as a self-administered questionnaire measuring the management capabilities and skills of district health managers. The downside is that this manuscript is very similar to the one by Fetene N et al (note the misspelling on line 74) who studied district-level health management and health system performance in Ethiopia.

Another problem is that, as the authors wrote in the study limitations, a causal relationship between the dependent variable and the independent variable cannot be established. The outcome variable, district performance, was not part of the questionnaire, rather it was extracted from aggregated data collected annually, so any association between the dependent and independent variables is questionable. Also, the authors did not investigate district health management implementers (such as doctors, nurses) and beneficiaries (such as patients), so the study was subjective and has no promotional value.

It is unclear how the authors actually assessed the outcome variables (high, medium, and low levels). In the methods section, the measurement standard cannot be found. What were the cut-points for high, medium and low and why were they chosen? In other words, the authors need to make a reasonable explanation for classifying the districts with scores of 61.5 and 56.5 into the high performance group, 52.3 and 52.0 into the middle performance group, and 47.0 and 43.0 into the low performance group.

The authors need to explain whether this is a random cluster sampling study or a convenience cluster sampling study. There is also no calculation of the sample size and exclusion criteria for the study in this manuscript.

Reviewer #3: The study is important in terms of management and health system performance in Ghana. The statistical analysis reflects the answers to the tasks set in the study. The author highlights the main problems but also reflects some limitations of the study which did not allow to fully elucidate the proposed goal.

Reviewer #4: I will suggest you revisit your statistical analysis, everything is wrong about it.

Why did you choose non-parametric test and not ANOVA parametric test?

Your data is two level hierarchical in nature where the 59 managers were nested in 6 district, you will need to account for this clustering in your analysis. SO therefore, I was thinking you should have applied some kind of multivariable logistic model while adjusting for clustering in 6 district.

Also, considering you categorized your outcome i.e. dependent variable into three level, you will need to applied multinomial logistic regression to this data.

That Table three is not right at all, you can not be applying kruskal-wallis test (for testing continuous variables) to categorical variables like sex, educational background, educational qualification, year in current position etc No you cant, this is slap on statistic face.

How on earth did you apply nptrend to ordered data when its not a time-series in nature? Why?

Your best bet:

Assuming you dont know how to do all I described above, please use ordinary CHI-SQUARE TEST, apply it to Table 3. Considering your sample size was low (n=59), please categorize, the performance outcome into two levels i.e. High vs mid/Low (combine Mid/Low together) then apply Chi-square test to EACH of the categorical variable. Then test Age (continuous variable using ANOVA) or you can categorize Age into 2 or 3 levels and then apply Chi-square test.

Then this will at least suffice.

But it will be better to apply Multivariable logistic regression/ Mixed effect logistic model to this data.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Ana Ciobanu

Reviewer #4: Yes: Dr. Babafela Awosile

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16 Oct 2019

The authors would like to sincerely thank the reviewers for their useful comments and suggestions, which enable us to improve the presentation of our study and the quality of our manuscript. Please find attached our point-by-point responses to the concerns raised by the reviewers and how we addressed these concerns.

Submitted filename: Response to reviewers, 14Oct.docx

Click here for additional data file.

6 Dec 2019

PONE-D-19-20019R1

Managerial capacity among District Health Managers and its association with District Performance: A comparative descriptive study of six districts in the Eastern Region of Ghana

PLOS ONE

Dear Miss Heerdegen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands.

1_ check that all statistic test values are included in your tables (e.g. chi square values etc.)

2_ The formatting in the reference list needs fixing -there is inconsistency in format of journal names (short or full) and in capitalization of titles

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We would appreciate receiving your revised manuscript by Jan 20 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Kamal Gholipour, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #4: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #4: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #4: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #4: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thank you for your answers and revisions. Personally, I think you have met the publishing requirements.

Reviewer #4: The review has improved the manuscript. I think the manuscript is better and the statistical analysis improved

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Reviewer #2: No

Reviewer #4: No

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20 Dec 2019

The authors would like to sincerely thank the reviewers for taking the time to provide useful comments and suggestions. These have enabled us to improve the presentation of our study and the quality of our manuscript.

Submitted filename: PLOS ONE, Letter to Editor, 10Dec19.docx

Click here for additional data file.

6 Jan 2020

Managerial capacity among District Health Managers and its association with District Performance: A comparative descriptive study of six districts in the Eastern Region of Ghana

PONE-D-19-20019R2

Dear Dr. Heerdegen,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Kamal Gholipour, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

13 Jan 2020

PONE-D-19-20019R2

Managerial Capacity among District Health Managers and its Association with District Performance: A Comparative Descriptive Study of Six Districts in the Eastern Region of Ghana

Dear Dr. Heerdegen:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Kamal Gholipour

Academic Editor

PLOS ONE