Open Access

A structured assessment of emergency and acute care providers in Afghanistan during the current conflict

  • Leeda Rashid1Email author,
  • Edris Afzali2,
  • Ross Donaldson3,
  • Paul Lazar1,
  • Raghnild Bundesmann1 and
  • Samra Rashid1
International Journal of Emergency Medicine20158:21

https://doi.org/10.1186/s12245-015-0069-0

Received: 2 March 2015

Accepted: 28 May 2015

Published: 4 July 2015

Abstract

Background

Afghanistan has struggled with several decades of well-documented conflict, increasing the importance of providing emergency services to its citizens. However, little is known about the country’s capacity to provide such care.

Methods

Three native-speaking Afghan-American physicians performed an assessment of emergency care via combined quantitative and qualitative survey tools. Hospitals in Kabul, Afghanistan were selected based on probability proportional to size methodology, in which size was derived from prior work in the country and permission granted by the administering agency and the Ministry of Health. A written survey was given to physicians and nurses, followed by structured focus groups, and multiple days of observation per facility. A descriptive analysis was performed and data analyzed through a combination of variables in eight overarching categories relevant to emergency care.

Results

One hundred twenty-five surveys were completed from 9 hospitals. One third of respondents (32.8 %) worked full time in the emergency departments, with another 28.8 % working there at least three quarters of the time. Over 63 % of providers believed that the greatest delay for care in emergencies was in the prehospital setting. Differences were noted among the various types of facilities when looking at specific components of emergency care such as skill level of workers, frequencies of assaults in the hospitals, and other domains of service provision. Sum of squares between the different facility types were highest for areas of skill (SS = 210.3; p = .001), confidence in the system (SS = 156.5; p < .005), assault (SS = 487.6; p < .005), and feeling safe in the emergency departments (SS = 193.1, p < .005). Confidence negatively correlated to frequency of assaults (Pearson r = −.33; p < .005) but positively correlated with feeling safe (Pearson r = .51; p < .005) and reliability of equipment (Pearson r = .48; p < .005). The only correlation for access to services was prehospital care (Pearson r = .72, p < .005).

Conclusions

There is a significant need to provide emergency care services in Afghanistan, specifically prehospital care. High variability exists among facility-type in various components of emergency services provision.

Background

In early 2002, the Ministry of Public Health (MoPH) of Afghanistan and the major donor organizations for the country, including the World Bank, the United States Agency for International Development, and the European Commission, created a Basic Package of Health Services (BPHS) for Afghanistan [1]. The BPHS was a multilateral approach to help address the most pressing health issues in the country and was the first time a low-income nation implemented such a comprehensive package while in the midst of conflict [2]. The Essential Package of Hospital Services (EPHS) followed suit to standardize how hospitals were to be staffed, organized, and equipped for care and as referral centers for the BPHS [3].

The World Bank has advocated for designing essential packages of health services based on country-specific burden of disease for some time [4]. Afghanistan’s package aimed in part to alleviate the uncoordinated and often separate objectives of health care delivery by non-governmental organizations (NGOs), a problem exacerbated by the more than 30 years of conflict in the country [5]. Both the BPHS and EPHS created a universal set of health services to be delivered, focusing heavily on maternal and child mortality [6]. It additionally gave leadership of the BPHS/EPHS to the MoPH, while allowing for health service delivery to be contracted out to international NGOs that were already established and providing care [7]. Since its implementation, the BPHS/EPHS has generally thought to be effective in both capacity building and service delivery, with Afghanistan’s performance measure scorecard showing its citizens receiving more health services since its implementation in 2002 [8, 9].

However, despite improvements in general and preventive health outcomes [10, 11], tertiary and specialty hospitals still only receive 26 % of the total funds allocated to the MoPH from government [12]. This leaves most of the tertiary hospitals with poor facility infrastructure, an inadequate workforce, and lack of necessary supplies [13]. It is also noteworthy that Afghanistan’s health system is largely dependant on foreign aid and a large portion of health services provisions are contracted out to NGO’s [14].

Afghanistan’s general health structure since the implementation of the BPHS/EPHS contains little recommendations regarding the establishment of emergency and acute care for the country [15]. This is despite the analysis showing that acute illness and injuries rank among the highest causes of death and disability adjusted life-years (DALYs) lost in low- and middle-income countries [16]. Given the long history of conflict in Afghanistan, emergency systems of care are arguably even more important in this context. Given the lack of a formal emergency system, the paucity of research about acute care, and ongoing conflict in the country, little is known about the current provision of emergency care in Afghanistan. We therefore designed and implemented a survey to analyze knowledge, attitudes, and practice among clinicians providing emergency-related care in the country.

Methods

Data gathering

We chose a convenience sampling of hospital physicians, nurses and medical residents in training to survey in Kabul, Afghanistan. All hospitals were either public, private, or run by the Afghan military. Approval was granted from the McLaren IRB/Ethics Review Board for exemption status and the Ministry of Health of Afghanistan. For each chosen hospital, we provided a written survey to providers that were on duty on sequential days. Provider inclusion criteria were physicians, residents, or nurses trained in Afghanistan, employed by the institutions and willing to answer our written survey.

The written survey was an 87-item questionnaire in Likert-scale focusing on personnel background and training, hospital background, emergency room services, emergency personnel, transportation, and prehospital questions (Additional file 1). It combined elements from two previously validated tools: an emergency medicine assessment used in Iraq by Donaldson et al. [17] and the World Health Organization’s Tool for Situational Analysis to Assess Emergency and Surgical Care [18].

After completion of the written survey, we held focus group discussions with approximately ten providers at each of the hospitals. The oral questions (Additional file 2) were open-ended and emergency written.

To maintain a heterogeneity of opinions, we opted to interview groups of physicians, nurses, and resident physicians.

Finally, we spent around 7 days visiting each hospital to observe the triage and emergency care systems in practice. During each visit, we spoke with key informants, including administrative officials, chiefs of staff, and hospital executives. These observations were either recorded in audio or via written notes.

Analysis

After collection, the data was coded and entered into SPSS software. Quality checks were performed on every tenth entry. We used PASW 18 Statistical Package (PASW Statistics 18, www.spss.com) for data analysis.

After completing initial descriptive analysis, we coded the written survey questions into eight overarching categories relevant to the practice of emergency medicine in the country (Additional file 3).

We then used these categories to compare differences in responses between government, NGO, and Public hospitals’ personnel using a two-way ANOVA. We did this because we could not control for the myriad of other factors such as location within the city, popularity of the facility, and ease of access to the facility.

To elucidate correlations between the summary measures, we used Kendall’s Tau-b method, since some of the data were not normally distributed. We additionally ran Pearson’s correlations on the same data and the results confirmed similar and significance levels.

Results

There were 125 surveys returned: 62 (49.6 %) from government hospitals, 42 (33.6 %) from military hospitals, 17 (13.6 %) from NGO hospitals, and 4 (3.2%) not specified (Table 1). More than half of the respondents were physicians and another quarter were nurses. Of our 125 respondents, 34.7 % stated they worked in an emergency room-type area full time, 88.7 % said they had some form of life support training, and 55.4 % said they had ACLS training.
Table 1

Frequency table for baseline descriptives

 

# (%) Respondents

Professional category

No answer

1 (0.8)

Doctor

83 (66.4)

Nurse

28 (22.4)

Resident

13 (10.4)

Total

125

Do you currently work only in emergency section

Yes

89 (71.2)

No

31 (24.8)

What percentage of your current clinical practice do you spend in the emergency section?

No answer

1 (0.8)

1–10 %

10 (8)

11–25 %

14 (11.2)

26–50 %

16 (12.8)

51–75 %

28 (22.4)

76–99 %

8 (6.4)

100 %

41 (32.8)

What type of hospital

Government non teaching

37 (29.6)

Private non teaching

12 (9.6)

Government teaching hospital

57 (45.6)

Private teaching hospital

14 (11.2)

Where do you see the greatest delay for care in emergencies?

Prehospital

79 (63.2)

Waiting room

6 (4.8)

In the emergency section waiting for room

14 (11.2)

On the medicine/surgery floors

1 (0.8)

Do you feel emergency care should be included in the BPHS/EPHS

No answer

2 (1.6)

Yes

57 (45.6)

No

53 (42.4)

Necessary equipment is immediately available for use during emergencies

Strongly agree

71 (56.8)

Agree

43 (34.4)

Neutral

1 (0.8)

Strongly disagree

1 (0.8)

Improve nurse training

No

61 (48.8)

Yes

52 (41.6)

What is average time to get to hospital in emergency

<5 min

2 (1.6)

5–30 min

23 (18.4)

31 to 60 min

46 (36.8)

61–120 min

14 (11.2)

121–180 min

11 (8.8)

>3 h

14 (11.2)

Is there a universal phone number to call to get an ambulance in your area?

Yes

104 (83.2)

No

9 (7.2)

No answer

2 (1.6)

If you called this phone number, how long on average does it take an ambulance to arrive?

<5 min

2 (1.6)

5–30 min

51 (40.8)

31 to 60 min

44 (35.2)

61–120 min

11 (8.8)

>3 h

1 (0.8)

If a family member became seriously ill at home, how would you seek medical care?

Keep comfortable treat at home

3 (2.4)

Wait for doc to arrive at home

1 (0.8)

Carry to hospital

43 (34.4)

Transport via private car or taxi

40 (32)

Call for ambulance

29 (23.2)

If a family member became seriously ill outside the home, how would you seek medical care?

Keep comfortable treat at home

2 (1.6)

Wait for doc to arrive at home

4 (3.2)

Carry to hospital

66 (52.8)

Transport via private car or taxi

28 (22.4)

Call for ambulance

14 (11.2)

There is a need for emergency med as specialty

Strongly agree

73 (58.4)

Agree

48 (38.4)

Neutral

3 (2.4)

Where do you see the greatest delay for care in emergencies?

No answer

1 (0.8)

Prehospital

79 (63.2)

Waiting room

6 (4.8)

In the emergency section waiting for room

14 (11.2)

Total

100 (80)

Table 1 reveals the general makeup of the health workers in our survey and their attitudes toward various components of emergency care. 76.8 % of our respondents were either physicians or physicians in training. 61.6 % of respondents worked half to full time in the ED. The majority worked at government teaching and non teaching hospitals. Overall, our respondents agreed that the greatest obstacle/delay to getting health in an emergency situation was prehospital care (63.2 %). The majority of respondents noted it would take between 30 and 60 min to wait for the arrival of an ambulance and to get to the hospital. Close to two-thirds of our respondents noted that if family members were to get ill, it was best to bring them via private car or even carry them, instead of calling an ambulance. Eighty-three percent admitted that there was a reliable number to call for help; however, despite this, respondents consistently noted that they would rather take their loved ones by private car or taxi. Over 96 % surveyed agreed that emergency medicine needs to be prioritized as a specialty.

We then coded remaining questions into the following overarching emergency care relevant, aggregated variables:
  1. 1.

    Emergency procedural skills

     
  2. 2.

    Confidence in hospital emergency care

     
  3. 3.

    ED safety

     
  4. 4.

    Assault on personnel in the ED

     
  5. 5.

    Staffing issues

     
  6. 6.

    Equipment and supplies

     
  7. 7.

    Access to emergency care

     
  8. 8.

    Prehospital care and transport time

     
A comparison of the means for the aggregated categories (Table 2) showed that the highest skill level was in the NGO hospitals; military hospitals had the second best skill level and the MoPH had the lowest skill level. For adequacy of staffing, the NGOs again were the best staffed, the military was second, and the MoPH again had the lowest staffing.
Table 2

Comparison of means between hospital types

Descriptive statistics

What type of hospital

N

Minimum

Maximum

Mean

Std. deviation

Statistic

Statistic

Statistic

Statistic

Statistic

Military

Assault

39

4

16

7.97

3.483

Confidence

40

9

15

12.7

1.488

Access

33

6

29

9.48

4.258

Equipment

40

6

10

8.03

1.165

Feel safe

39

12

20

15.31

1.962

Prehospital

35

4

11

6.23

2.03

Skill

34

9

20

15.24

3.542

Staff

39

4

10

6.64

1.98

Valid N (listwise)

27

    

NGO

Assault

17

4

15

5.71

3.46

Confidence

16

10

15

13

1.265

Access

14

6

13

9.14

1.916

Equipment

17

6

10

7.82

1.131

Feel Safe

16

13

20

16.75

2.145

Prehospital

14

4

9

6.14

1.406

Skill

16

9

20

16.31

3.049

Staff

17

5

10

7.65

1.057

Valid N (listwise)

12

    

MOPH

Assault

49

4

22

11.33

4.819

Confidence

53

6

15

10.4

2.133

Access

45

5

13

8.84

1.918

Equipment

52

2

8

6.5

1.502

Feel Safe

51

4

17

13.2

2.417

Prehospital

49

3

9

6.04

1.485

Skill

47

6

20

12.72

4.025

Staff

55

2

8

5.51

1.597

Valid N (listwise)

35

    

The military hospital felt their equipment was most adequate, followed by NGOs, then the MoPH Hospitals. In the feeling safe component, the NGOs felt they were the safest, while the military ranked second and the MoPH hospitals rated lowest. Assaults were also most common in the MoPH hospitals, least in the NGO’s and the military again ranked in the middle.

When we used two-way ANOVA on these summary measures, to understand if the differences between the facilities for each measure were significant, we found statistically significant differences among the facilities with regard to each summary measure we had defined as being core components of emergency care; concluding that differences of opinion were not likely random. The only summary measures that were not statistically significantly different among the various facilities were access and prehospital care (Table 3). Since some of our data was dichotomous, some might argue that we did not meet assumptions, but we felt differently because we have the means of mixed data. However, to confirm these findings, we also ran the nonparametric equivalent, Kruskal-Wallis analysis, and the results largely coincided (Table 4).
Table 3

Analysis of variance among summary measures

ANOVA

 

Sum of squares

df

Mean square

F

Sig.

Staff

Between groups

69.308

2

34.654

12.287

0

Within groups

304.602

108

2.82

  

Total

373.91

110

   

Access

Between groups

7.817

2

3.908

0.44

0.645

Within groups

789.868

89

8.875

  

Total

797.685

91

   

Prehospital

Between groups

0.727

2

0.363

0.127

0.881

Within groups

271.804

95

2.861

  

Total

272.531

97

   

Equipment

Between groups

58.839

2

29.419

16.548

0

Within groups

188.446

106

1.778

  

Total

247.284

108

   

Feel safe

Between groups

193.144

2

96.572

19.606

0

Within groups

507.347

103

4.926

  

Total

700.491

105

   

Assault

Between groups

487.635

2

243.818

14.072

0

Within groups

1767.279

102

17.326

  

Total

2254.914

104

   

Confidence

Between groups

156.499

2

78.249

23.898

0

Within groups

347.079

106

3.274

  

Total

503.578

108

   

Skill

Between groups

210.319

2

105.159

7.61

0.001

Within groups

1298.959

94

13.819

  

Total

1509.278

96

   
Table 4

Post hoc tests (nonparametric Kruskal-Wallis)

 

Multiple comparisons

Tukey HSD

 

Dependent variable

(I) What type of hospital

(J) What type of hospital

Mean difference (I-J)

Sig.

Staff

Military

NGO

−1.006

0.103

MOPH

1.132*

0.005

NGO

Military

1.006

0.103

MOPH

2.138*

0

MOPH

Military

−1.132*

0.005

NGO

−2.138*

0

Access

Military

NGO

0.342

0.931

MOPH

0.64

0.618

NGO

Military

−0.342

0.931

MOPH

0.298

0.943

MOPH

Military

−0.64

0.618

NGO

−0.298

0.943

Prehospital

Military

NGO

0.086

0.986

MOPH

0.188

0.871

NGO

Military

−0.086

0.986

MOPH

0.102

0.978

MOPH

Military

−0.188

0.871

NGO

−0.102

0.978

Equipment

Military

NGO

0.201

0.861

MOPH

1.525*

0

NGO

Military

−0.201

0.861

MOPH

1.324*

0.002

MOPH

Military

−1.525*

0

NGO

−1.324*

0.002

Feel safe

Military

NGO

−1.442

0.078

MOPH

2.112*

0

NGO

Military

1.442

0.078

MOPH

3.554*

0

MOPH

Military

−2.112*

0

NGO

−3.554*

0

Assault

Military

NGO

2.268

0.151

MOPH

−3.352*

0.001

NGO

Military

−2.268

0.151

MOPH

−5.621*

0

MOPH

Military

3.352*

0.001

NGO

5.621*

0

Confidence

Military

NGO

−0.3

0.841

MOPH

2.304*

0

NGO

Military

0.3

0.841

MOPH

2.604*

0

MOPH

Military

−2.304*

0

NGO

−2.604*

0

Skill

Military

NGO

−1.077

0.606

MOPH

2.512*

0.01

NGO

Military

1.077

0.606

MOPH

3.589*

0.003

MOPH

Military

−2.512*

0.01

NGO

−3.589*

0.003

*The mean difference is significant at the 0.05 level

To understand if there was any correlations among our summary measures, we ran both Kendall Tau B correlations and Pearson’s correlations between the summary measures (two-tailed) and some of our measures were significant at the .01 to .05 level.

Skill level was significantly correlated to the type of hospital, confidence in the benefit of emergency care, feeling safe while practicing, and having sufficient supplies (Tables 5 and 6).
Table 5

Correlations (Pearson’s)

Correlations

 

Confident

Assault

Feel safe

Equipment

Prehospital

Access

Staffing

Skill

What type of hospital

Confidence

Pearson Correlation

1

–0.336**

0.515**

0.481**

−0.1

−0.058

0.322**

0.469**

0.260**

 

Sig. (two-tailed)

 

0

0

0

0.326

0.581

0.001

0

0.007

 

Sum of squares and cross-products

504.124

−320.365

277.077

156.783

−33.694

−31.29

136.622

362.787

62.972

 

Covariance

4.501

−3.11

2.69

1.493

−0.347

−0.34

1.242

3.901

0.589

 

N

113

104

104

106

98

93

111

94

108

Assault

Pearson correlation

−0.336**

1

−0.547**

−0.438**

0.087

−0.02

−0.312**

−0.069

−0.221*

 

Sig. (two-tailed)

0

 

0

0

0.398

0.851

0.001

0.52

0.024

 

Sum of squares and cross-products

−320.365

2308.807

−676.874

−315.514

64.608

−24.446

−284.557

−99.622

−109.077

 

Covariance

−3.11

21.378

−6.636

−3.034

0.673

−0.269

−2.71

−1.119

−1.059

 

N

104

109

103

105

97

92

106

90

104

Feel safe

Pearson correlation

0.515**

−0.547**

1

0.716**

−0.271**

−0.205

0.415**

0.258*

0.207*

 

Sig. (two-tailed)

0

0

 

0

0.007

0.05

0

0.014

0.035

 

Sum of squares and cross-products

277.077

−676.874

706.972

299.157

−114.371

−145.304

210.896

220.798

56.952

 

Covariance

2.69

−6.636

6.546

2.796

−1.191

−1.597

2.009

2.509

0.553

 

N

104

103

109

108

97

92

106

89

104

Equipment

Pearson correlation

0.481**

−0.438**

0.716**

1

−0.18

−0.125

0.324**

0.220*

0.111

 

Sig. (two-tailed)

0

0

0

 

0.076

0.231

0.001

0.035

0.256

 

Sum of squares and cross-products

156.783

−315.514

299.157

248.857

−43.837

−51.723

96.843

111.011

18.093

 

Covariance

1.493

−3.034

2.796

2.242

−0.452

−0.556

0.905

1.22

0.171

 

N

106

105

108

112

98

94

108

92

107

Prehospital

Pearson correlation

−0.1

0.087

−0.271**

−0.18

1

0.719**

−0.211*

−0.097

0.007

 

Sig. (two-tailed)

0.326

0.398

0.007

0.076

 

0

0.036

0.372

0.947

 

Sum of squares and cross-products

−33.694

64.608

−114.371

−43.837

298.912

336.747

−68.061

−55.605

1.155

 

Covariance

−0.347

0.673

−1.191

−0.452

2.96

3.582

−0.694

−0.654

0.012

 

N

98

97

97

98

102

95

99

86

97

Access

Pearson correlation

−0.058

−0.02

−0.205

−0.125

0.719**

1

−0.104

−0.163

0.119

 

Sig. (two-tailed)

0.581

0.851

0.05

0.231

0

 

0.323

0.139

0.266

 

Sum of squares and cross-products

−31.29

−24.446

−145.304

−51.723

336.747

820.905

−54.462

−112.095

32.222

 

Covariance

−0.34

−0.269

−1.597

−0.556

3.582

8.733

−0.592

−1.351

0.362

 

N

93

92

92

94

95

95

93

84

90

Staffing

Pearson correlation

0.322**

−0.312**

0.415**

0.324**

−0.211*

−0.104

1

0.106

0.272**

 

Sig. (two-tailed)

0.001

0.001

0

0.001

0.036

0.323

 

0.313

0.004

 

Sum of squares and cross-products

136.622

−284.557

210.896

96.843

−68.061

−54.462

393.183

73

57.273

 

Covariance

1.242

−2.71

2.009

0.905

−0.694

−0.592

3.449

0.793

0.525

 

N

111

106

106

108

99

93

115

93

110

Skill

Pearson correlation

0.469**

−0.069

0.258*

0.220*

−0.097

−0.163

0.106

1

0.068

 

Sig. (two-tailed)

0

0.52

0.014

0.035

0.372

0.139

0.313

 

0.51

 

Sum of squares and cross-products

362.787

−99.622

220.798

111.011

−55.605

−112.095

73

1510.634

26.667

 

Covariance

3.901

−1.119

2.509

1.22

−0.654

−1.351

0.793

15.106

0.281

 

N

94

90

89

92

86

84

93

101

96

What type of hospital

Pearson correlation

0.260**

−0.221*

0.207*

0.111

0.007

0.119

.272**

0.068

1

 

Sig. (two-tailed)

0.007

0.024

0.035

0.256

0.947

0.266

0.004

0.51

 
 

Sum of squares and cross-products

62.972

−109.077

56.952

18.093

1.155

32.222

57.273

26.667

130.8

 

Covariance

0.589

−1.059

0.553

0.171

0.012

0.362

0.525

0.281

1.099

 

N

108

104

104

107

97

90

110

96

120

*Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (two-tailed)

Table 6

Nonparametric correlations (Kendall Tau)

Correlations

 

Confidence

Assault

Feel Safe

Equipment

Prehospital

Access

Staff

Skill

What type of hospital

Kendall’s tau_

Confidence

Correlation coefficient

1

−0.248**

0.390**

0.416**

−0.085

−0.086

0.253**

0.387**

0.170*

Sig. (two-tailed)

 

0.001

0

0

0.28

0.283

0.001

0

0.032

N

113

104

104

106

98

93

111

94

108

Assault

Correlation coefficient

−0.248**

1

−0.471**

−0.313**

0.056

0.023

−0.249**

−0.046

−0.192*

Sig. (two-tailed)

0.001

 

0

0

0.468

0.763

0.001

0.549

0.014

N

104

109

103

105

97

92

106

90

104

Feel safe

Correlation coefficient

0.390**

−0.471**

1

0.547**

−0.189*

−0.225**

0.311**

0.151

0.202*

Sig. (two-tailed)

0

0

 

0

0.017

0.005

0

0.059

0.012

N

104

103

109

108

97

92

106

89

104

Equipment

Correlation coefficient

0.416**

−0.313**

0.547**

1

−0.171*

−0.183*

0.224**

0.183*

0.097

Sig. (two-tailed)

0

0

0

 

0.041

0.029

0.006

0.027

0.247

N

106

105

108

112

98

94

108

92

107

Prehospital

Correlation coefficient

−0.085

0.056

−0.189*

−0.171*

1

0.835**

−0.145

−0.072

0.008

Sig. (two-tailed)

0.28

0.468

0.017

0.041

 

0

0.071

0.374

0.923

N

98

97

97

98

102

95

99

86

97

Access

Correlation coefficient

−0.086

0.023

−0.225**

−0.183*

0.835**

1

−0.156

−0.111

0.028

Sig. (two-tailed)

0.283

0.763

0.005

0.029

0

 

0.055

0.17

0.743

N

93

92

92

94

95

95

93

84

90

Staffing

Correlation coefficient

0.253**

−0.249**

0.311**

0.224**

−0.145

−0.156

1

0.082

0.244**

Sig. (two-tailed)

0.001

0.001

0

0.006

0.071

0.055

 

0.301

0.002

N

111

106

106

108

99

93

115

93

110

Skill

Correlation coefficient

0.387**

−0.046

0.151

0.183*

−0.072

−0.111

0.082

1

0.049

Sig. (two-tailed)

0

0.549

0.059

0.027

0.374

0.17

0.301

 

0.547

N

94

90

89

92

86

84

93

101

96

What type of hospital

Correlation coefficient

0.170*

−0.192*

0.202*

0.097

0.008

0.028

0.244**

0.049

1

Sig. (two-tailed)

0.032

0.014

0.012

0.247

0.923

0.743

0.002

0.547

 

N

108

104

104

107

97

90

110

96

120

*Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (two-tailed)

Confidence in the particular health system was negatively correlated to frequency of assaults, and positively correlated with feeling safe in that particular system and in the adequacy of supplies/equipment, the amount of hospital staffing and in the skill level of the workers (Table 6).

Time to the ED/prehospital time was heavily correlated to the levels of access in each facility.

The type of hospital was significantly correlated to the number of assaults experienced by respondents and negatively correlated to confidence in the system, feeling safe, adequacy of staffing, and supplies.

From our observations, medical training and adequate equipment was a large barrier in providing services. Many public facilities were often so crowded that we could not safely get in through the hospital doors and we met many patients waiting hours for basic life support mechanisms such as oxygen tanks or an EKG. Physicians were very eager to learn, and requested support for medical education and greater training. User fees were collected at one of the NGO sites, whereas all other facilities collected intermittently for medical supplies, blood products, and other equipment that were not immediately available within the facility itself.

Discussion

The Afghan health care system is limited in its capacity to provide in-and-out-of-hospital emergency care. Our data and analysis shows wide variation in emergency services provided in Kabul, with much of the variability dependent on the type of hospital facility.

We found that medical training at the military hospital had some, although limited focus on emergency medical training, but this was not persistent in the public sector system. Resident physicians often noted that they were left to deal with emergencies that came to the hospital, regardless of whether they had prior training in certain clinical scenarios. During focus groups and in our observations, limitations highlighted were not always due to resources constraints but also to a lack of organizational structure and processes in place to prioritize and triage cases.

Although the public hospitals see a disproportionately large number of patients, they trended toward having less capacity, supply, and resources. These issues were highlighted in their level of confidence, skill and staffing issues corroborated by our quantitative analyses. They were also more subject to frequent assaults and disaster scenarios, further creating barriers to consistent staffing of the emergency departments. From our own observations, their medical and equipment supply, including items as simple as oxygen supplementation, did not meet the demands of the volume of patients treated daily.

From our observations, the military hospitals were not open for civilian care unless injuries were the direct result of combat. Our focus groups highlighted that most patients, despite being from remote areas of the provinces, knew of the existence of public facilities and were either referred to or directly came to public facilities much more readily than the NGO hospitals or other private facilities. There was also a sense that public sector hospitals were always free, whereas NGO facilities would charge a fee, even though only one of the NGO facilities we visited had begun a process of user fee collection on a very limited basis.

From our summary measures and correlations data, we found that NGO’s consistently had the better trained staff compared to the public and military hospital. We found that confidence in emergency medicine skills, such as intubation were much better in NGO and military hospitals as compared to the Public system. Even when we split the data based on occupation (nurse or physician), we found that differences among the facilities persisted in their level of skill.

Skill was also an outstanding variable that was positively correlated to the type of hospital (public, NGO, or military), confidence in the emergency care system, feeling safe while practicing, and having sufficient supplies. It is a possibility that the skilled workforce migrates to higher paying, better supplied, and safer working conditions.

Our assessment demonstrated that there is a high need for ongoing investment in the skills based training of physicians, nurses, residents, and other emergency personnel especially in the public sector hospitals.

Tables 5 and 6 show that the type of hospital was significantly correlated to the number of assaults experienced by respondents and negatively correlated to confidence in the system, feeling safe, and adequacy of staffing and supplies.

As part of the current debate on a national salary policy, adequate compensation, and incentives for health workers should be addressed to maintain adequate staffing for the care of emergency patients in light of such safety issues. Its also noteworthy that the reality of Kabul still purports a more secure work environment in comparison to other provinces and in particular rural areas where corruption will more likely be a contributing factor given fewer civil services and the paucity of security forces.

Time to the ED and prehospital time was heavily correlated to the levels of access in each facility. Whether this implied that more efficient prehospital care, as provided for example in places like the military, also allows for quicker and more effective initial entry and triage via the ambulance system cannot be determined by our quantitative data alone, but this was corroborated repeatedly by our focus group discussions and our qualitative analyses. Our own observations of seeing patients brought in by local taxis to the public hospitals also begged the question of whether more focus on the development of the prehospital system is a key to increasing access for all citizens. Time to ED undoubtedly differs in urban centers like Kabul, versus rural Afghanistan, but we cannot make any specific conclusions at this time.

Since most admitted knowing colleagues who were assaulted or having been assaulted themselves during the highly emotional moments that medical emergencies provoke, the addition of further security measures for workers in the hospitals, especially within the public sector hospitals, would allow physicians to feel safer committing more time to emergency sections, such as taking night shifts. Studies in Iraq have found that within the Emergency Department alone, over 80 % of physicians were victims of assault at least once [19]. Correlations found regarding safety do not again prove causality, but does confirm that workers within conflict zones are being threatened regularly, but in fact may be more willing to commit to night shifts and other less than ideal working conditions if they at least feel safe while there.

It is also worthwhile to discuss our two summary measures that were consistently not significantly different among facility type; access and prehospital care. Neither of these components proved to be different among the various facility types throughout our analyses. This may be indicative of the fact that most respondents were in agreement regarding the landscape of prehospital care and access issues. Therefore, when we tried to decipher if respondents felt differently about these particular issues based on their facility type, our conclusions were never statistically different.

Conclusions

The challenges of providing care in Afghanistan combine those of a developing nation, an intra-conflict nation and a combat zone [20]. Our conclusions are that Afghanistan’s system of emergency and acute care is exposed to all of these challenges. Given the significant reliance on foreign aid, resource utilization, the limitations of unsustainable contracting mechanisms [21], and evidence based priority setting in service provision is paramount to delivering care.

Our survey combined with the focus group conclusions and our own first hand witness of the emergency system in Kabul, Afghanistan reveals critical lack of resources, capacity, and safety while providing initial care. Additionally, there is a widely accepted opinion that although an emergency call number exists, there is no consistent and reliable predhospital system.

There are frequent shortages of lifesaving medications, a lack of functioning medical equipment, and a paucity of opportunity for continuing training and medical education.

There are also few incentives for clinicians to provide emergency care. Neither the national health service primary package, the BPHS, or the hospital wide quality initiatives of the EPHS focus much detail on initial point of care guidelines or resources [12, 22]. At the hospital level, there appears to be little organizational structure for the triage of emergency patients. This places a high demand on physicians in other specialties who do not feel confident in the system, especially in the public sector. Clinicians providing emergency care are not comfortable if they have not had formal training in emergency services and are not confident in their skills toward some procedures, and they have to do their job in an environment with poorly functioning equipment and scarce medications. Combined with disincentives such as violence at work and poor pay by the public system, it is understandable that many providers choose not to make emergency care a priority.

In a country plagued by decades of war and unrest, a comprehensive and effective prehospital and emergency care system is paramount to saving lives, meeting critical health care needs, and providing a reliable safety net for the population.

Despite documented success in indicators as maternal mortality rates and infant mortality rates [23], much more needs to be done in meeting the needs of basic emergency services in a country that sees such acute events almost daily. Our data supports the need for focused efforts to improve prehospital and hospital-based care in Afghanistan, starting with the inclusion of emergency services training and organizational structures as a part of the expansion of basic health services in the country.

Limitations

The major limitation in this study is that although the hospitals were randomly sampled, we used a convenience sampling of health workers present in the hospitals during our data collection period. The experience and opinions of the health workers present may not reflect those of their hospital overall throughout the full year.

Additionally, our study was limited to Kabul. Although a majority of resources are concentrated in Kabul, it is unclear if this survey is generalizable to other urban centers and the more remote areas of Afghanistan. As of 2012, there are still only 26 hospitals in the entire country that implement the quality initiatives and standards of the EPHS, therefore data on the capacity of emergency care in all hospitals as a whole may not be fully reflected at our chosen sites [12]. Kabul also has only one of its major hospitals implementing the EPHS that is funded and managed by the MoPH. The current contracts that support emergency services through the MoPH are also not in Kabul province, and therefore our results may not be generalizable to MoPH facilities providing acute care.

It is possible that our survey was influenced by cultural bias, since many health workers may fear job loss in an ongoing insecure labor market, due to retribution if respondents were honest about the shortcomings of the system. We maintained that all surveys were completely confidential, but this limitation is still a possibility. Also, though we did not ask directly about corruption and theft as a factor during open-ended focus groups, it is likely that out of fear of retribution or cultural nuances, these issues were not discussed.

In our focus groups, we avoided asking direct response questions and instead opted for more open-ended questions. However, it is a well-known limitation of focus groups that surveyors asking questions may indirectly elucidate responses already programmed through a society’s own belief system and systems of hierarchy (Maxwell) [24]. Focus groups were held in the most culturally appropriate way so as to elicit a sense of mutual respect and understanding for the goals of the project, thereby obtaining more critical thinking and obtaining increasing accuracy of information. However, this limitation must be considered regardless.

Declarations

Acknowledgements

The authors would like to acknowledge the efforts of Her Excellency, Dr Suraya Dalil, the Minister of Health of Afghanistan, Dr Khaled Ibn Amin (Director of Monitoring and Evaluation at the Ministry of Health), Dr. Nooragha Akramzada (Director at Wazir Akbar Khan Hospital), and Dr Ahmad Jawad Osmani (Director of International Relations).

We would also like to thank our language editors, Ms. Suraya Rashid and Dr Sayed Shefayee for substantial contribution in the revision and final draft of the survey.

Authors’ Affiliations

(1)
Mclaren Regional Medical Center Department of Family Medicine, Michigan State University College of Human Medicine
(2)
Harbor-UCLA Medical Center, Division of Emergency Medicine
(3)
Department of Emergency Medicine, Michigan State University/Synergy Medical Education Alliance

References

  1. A basic package of health services for Afghanistan [Internet]. Kabul, Afghanistan: Ministry of Health of Afghanistan & USAID; 2003; cited October 2009]. Available from: http://apps.who.int/medicinedocs/documents/s21746en/s21746en.pdf.
  2. Lejars M. Health system in Afghanistan: problems and institutional perspectives. Med Trop (Mars). 2008;68(5):463–7.Google Scholar
  3. Belay T. Building on early gains in Afghanistan’s health, nutrition and population sector. Challenges and options. Washington, D.C: The World Bank; 2010.Google Scholar
  4. Gonzalez-Pier E, Gutierrez-Delgado C, Stevens G, Barraza-Llorens M, Porras-Condey R, Carvalho N, et al. Priority setting for health interventions in Mexico’s system of social protection in health. Salud Publica Mex. 2007;49 Suppl 1:S37–52.PubMedGoogle Scholar
  5. Building on early gains: The role and structure of government in further strengthening Afghanistan’s health sector- AAA concept note. Afghanistan: 2007.Google Scholar
  6. Edward A, Kumar B, Kakar F, Salehi AS, Burnham G, Peters DH. Configuring balanced scorecards for measuring health system performance: evidence from 5 years’ evaluation in Afghanistan. PLoS Med. 2011;8(7), e1001066.PubMed CentralPubMedView ArticleGoogle Scholar
  7. Siddiqi S, Masud TI, Sabri B. Contracting but not without caution: experience with outsourcing of health services in countries of the Eastern Mediterranean Region. Bull World Health Organ. 2006;84(11):867–75.PubMed CentralPubMedGoogle Scholar
  8. The essential package of health services for Afghanistan [Internet].: Management Sciences forHealth;2005.Availablefrom: http://moph.gov.af/Content/Media/Documents/EPHS-2005-FINAL29122010164126629.pdf.
  9. Hansen PM, Peters DH, Niayesh H, Singh LP, Dwivedi V, Burnham G. Measuring and managing progress in the establishment of basic health services: the Afghanistan health sector balanced scorecard. Int J Health Plann Manage. 2008;23(2):107–17.PubMedView ArticleGoogle Scholar
  10. Hodkinson PW, Wallis LA. Emergency medicine in the developing world: a Delphi study. Acad Emerg Med. 2010;17(7):765–74.PubMedView ArticleGoogle Scholar
  11. Peters DH, Noor AA, Singh LP, Kakar FK, Hansen PM, Burnham G. A balanced scorecard for health services in Afghanistan. Bull World Health Organ. 2007;85(2):146–51.PubMed CentralPubMedView ArticleGoogle Scholar
  12. Ministry of Public Health (Health Economics & Financing Directorate). Cost analysis of Afghanistan’s Essential Package of Hospital Services (EPHS). 2012. In press.Google Scholar
  13. Ministry of Pubic Health of Afghanistan (Consultative Group of Health & Nutrition, The Unit for Improving Quality in HealthCare, The Technical Advisory Group,) USAID, University Research Co. LLC. National strategy for improving quality in healthcare 2011–1015. 2011. In press.Google Scholar
  14. Acerra JR, Iskyan K, Qureshi ZA, Sharma RK. Rebuilding the health care system in Afghanistan: an overview of primary care and emergency services. Int J Emerg Med. 2009;2(2):77–82.PubMed CentralPubMedView ArticleGoogle Scholar
  15. Ministry of Health. Institutional analysis of the health sector in Afghanistan. Ministry of Health: Islamic Republic of Afghanistan; 2008.Google Scholar
  16. Razzak JA, Kellermann AL. Emergency medical care in developing countries: is it worthwhile? Bull World Health Organ. 2002;80(11):900–5.PubMed CentralPubMedGoogle Scholar
  17. Donaldson RI. IMC emergency medical care needs assessment toolkit. 2009. In press.Google Scholar
  18. WHO integrated management for emergency & essential surgical care. http://www.who.int/surgery/publications/imeesc/en/.
  19. Donaldson RI, Hasson T, Aziz S, Ansari W, Evans G. The development of civilian emergency medical care during an insurgency: current status and future outlook in Iraq. Ann Emerg Med. 2010;56(2):172–7.PubMedView ArticleGoogle Scholar
  20. NATO. Afghan national army medical education development program. NATO: Kabul, Afghanistan; 2009.Google Scholar
  21. Sabri B, Siddiqi S, Ahmed AM, Kakar FK, Perrot J. Towards sustainable delivery of health services in Afghanistan: options for the future. World Hosp Health Serv. 2007;43(3):10–6.PubMedGoogle Scholar
  22. Transitional Islamic Government of Afghanistan, Ministry of Health. A basic package of health services for Afghanistan. March 2003/1382. In press.Google Scholar
  23. Strong L, Wali A, Sondrop E. Health policy in Afghanistan: two years of rapid change. A review of the process from 2001–2003. London: European Commission Poverty Reduction Effectiveness Program (EC-PREP); 2005.Google Scholar
  24. Nelson BD, Dierberg K, Scepanovic M, Mitrovic M, Vuksanovic M, Milic L, et al. Integrating quantitative and qualitative methodologies for the assessment of health care systems: emergency medicine in post-conflict Serbia. BMC Health Serv Res. 2005;5(1):14.PubMed CentralPubMedView ArticleGoogle Scholar

Copyright

© Rashid et al. 2015

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