Literature DB >> 24244581

Perceived quality of care for common childhood illnesses: facility versus community based providers in Uganda.

Agnes Nanyonjo1, Fredrick Makumbi, Patrick Etou, Göran Tomson, Karin Källander.   

Abstract

OBJECTIVE: To compare caretakers' perceived quality of care (PQC) for under-fives treated for malaria, pneumonia and diarrhoea by community health workers (CHWs) and primary health facility workers (PHFWs).
METHODS: Caretaker rated PQC for children aged (2-59) months treated by either CHWs or PHFWs for a bought of malaria, pneumonia or diarrhoea was cross-sectionally compared in quality domains of accessibility, continuity, comprehensiveness, integration, clinical interaction, interpersonal treatment and trust. Child samples were randomly drawn from CHW (419) and clinic (399) records from eight Midwestern Uganda districts. An overall PQC score was predicted through factor analysis. PQC scores were compared for CHWs and PHFWs using Wilcoxon rank-sum test. Multinomial logistic regression models were used to specify the association between categorized PQC and service providers for each quality domain. Finally, overall PQC was dichotomized into "high" and "low" based on median score and relative risks (RR) for PQC-service provider association were modeled in a "modified" Poisson regression model.
RESULTS: Mean (SD) overall PQC was significantly higher for CHWs 0.58 (0 .66) compared to PHFWs -0.58 (0.94), p<0.0001. In "modified" Poisson regression, the proportion of caretakers reporting high PQC was higher for CHWS compared to PHFWs, RR=3.1, 95%CI(2.5-3.8). In multinomial models PQC was significantly higher for CHWs compared to PHFWs in all domains except for continuity.
CONCLUSION: PQC was significantly higher for CHWs compared to PHFWs in this resource constrained setting. CHWs should be tapped human resources for universal health coverage while scaling up basic child intervention as PQC might improve intervention utilization.

Entities:  

Mesh:

Year:  2013        PMID: 24244581      PMCID: PMC3820538          DOI: 10.1371/journal.pone.0079943

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

In order to address childhood mortality, scarcity of human resources for health and inequalities in access to health care, approaches like the integrated community case management of childhood illnesses (iCCM) have been recommended by the World Health Organisation [1,2,3]. iCCM entails use of community health workers (CHWs) in the management of uncomplicated childhood illnesses including malaria, pneumonia, diarrhoea and newborn referral [3,4,5]. Despite the ability of community based interventions to improve access to life saving interventions, improvement is still needed in the quality of health care delivered to sick children, highlighting the dire need to strengthen health systems [6,7,8]. Many health initiatives today are faced with questionable ability to be scaled up with quality [9], making quality an important aspect of programme evaluation. Literature on the quality of health care concept has previously emphasised the association between health infrastructure and quality received but more attention is needed in applying this concept to individual users [10]. This is crucial because the effectiveness of quality of health care is a factor of both clinical and interpersonal care effectiveness. Factors not counting as infrastructure, such as poor performance of health workers, affect quality received [11]. Total quality assessment requires structure, process and outcome measure evaluation [10,12,13,14]. Structure refers to the availability and well organisation of resources (infrastructure, material and human) acting as channels through which care is delivered. Process reflects the actual process undergone during a clinical interaction encounter. Outcomes are the changes in the receiver’s health status or any desired outcomes occurring as a consequence of health provider-receiver interaction [10,12]. It is not possible to bridge health inequities by merely improving access [15,16]. User perception of quality of health care is known to drive utilization of health interventions [17,18,19]. In the context of user satisfaction, technical improvements and continuity of care alone are known to improve the ratings of perceived quality of care (PQC) [18,20,21]. In Uganda, basic primary health care for children is obtained from CHWs and primary health facility workers (PHFWs). Previously the quality of primary health care for children has been evaluated in both integrated management of childhood illnesses provided at health facilities and iCCM provided in the communities [22,23,24,25,26]. This evaluation was however limited in that it was hinged on structural and provider assessments and not PQC at the user level. The PQC received from CHWs has not been established previously. Evaluation of PQC is important since it affects caregiver demand and utilization of CHW services, which subsequently could improve health outcomes in sick children through more prompt care for uncomplicated cases and increased care quality for more complicated cases at health facilities through decreased staff workload [27]. Furthermore the private sector has been the largest provider of health care for sick children in Uganda followed by the formal sector [28]. In order for iCCM to be embraced by the communities as an alternative source of care, its PQC must be comparable to that of the standard care in the formal sector. This study reports on a cross-sectional comparison of the PQC among caretakers of children treated for malaria, pneumonia and diarrhoea by CHWs and by primary health facility workers (PFHWs).

Methods

Ethics statement

Ethical approval for the study was obtained from the Institutional Review Board of Makerere University School of Public Health and the Uganda National Council of Science and Technology (HS 958). Written consent was obtained from all caretakers before conducting the interviews.

Study design

A comparative cross-sectional survey of caretakers of children visiting CHWs and PHFWs for management of malaria, pneumonia and diarrhea.

Study settings and context

Between August and September 2011, a survey was undertaken in eight Midwestern Uganda districts. The districts were estimated to have a population of 2.2 million people of which 18% were children under five. Health seeking behaviour of the people in the study areas ranges from treatments at home to formal and informal health providers outside the home, including drug shops, clinics, health facilities and traditional healers. In one study it was documented that 62.5% of children seeking care outside the home were first managed by a drug shop or private clinic [28]. During the study period approximately 6674 CHWs trained on iCCM were operating in an area which was served by 192 government owned, 51 private not for profit and 33 private health centres (HCs). In Uganda’s health system hierarchy (Figure 1), the lowest HC operating at the village level (HC-I) is the CHW who works from home [29]. The first HC with a physical structure is at the parish level (HC-II), followed by HC III at the sub-county level and HC-IV at the county level. Hospitals operate at district level. Majority of the HCs with a physical structure in the study area were level II and III. The HCs from level II-IV are herein referred to as primary health facilities.
Figure 1

A diagrammatic depiction of the health system hierarchy in Uganda.

Under Uganda’s village health team (VHT) strategy, 5-6 CHWs are trained to carry out health promotion and education activities, including follow-ups for pregnant women and sick newborn referrals. Two CHWs in each village are additionally trained on iCCM. A typical CHW is trained on iCCM for six days, oversees 20-30 households and is responsible for diagnosing and treating children suffering from uncomplicated malaria, pneumonia and diarrhoea, as well as referral of newborns with danger signs. CHWs are provided with colour coded Artemether/Lumefantrine combination to treat children aged 4 -59 months confirmed to have uncomplicated malaria through a rapid diagnostic test ; amoxicillin to treat uncomplicated pneumonia among children aged 2 -59 months and zinc and oral rehydration salts to treat uncomplicated diarrhoea in children aged 2 -59 months. Children showing danger signs are referred to the nearest health facility. Pre-referral rectal Artesunate is administered to children with danger signs attributable to severe malaria and pre-referral amoxicillin is provided to children with signs of severe pneumonia. The CHWs are supervised by staff from the nearest primary health facility. The PHFWs receive refresher courses on IMCI as part of their orientation to train and supervise the CHWs. HC-II’s and HC-III’s mainly constitute the primary health facilities in Uganda. A HC-III provides basic preventive, promotive and curative care and provides support supervision for the community and HC-IIs under its jurisdiction with a team consisting of a clinical officer and nurses. With respect to malaria, pneumonia and diarrhoea among under-fives, basic laboratory services are available for diagnosis of the three diseases. HC-IIIs are recommended to treat uncomplicated malaria with Artemether/Lumefantrine combination, uncomplicated pneumonia with vitamin A and either amoxicillin or a combination of cotrimoxazole and procaine penicillin forte if necessary. Watery diarrhoea is treated with ORS and zinc at this level. The HC-IIs provide the first level of interaction between the formal health sector and the communities. HC-IIs only provide outpatient care through an enrolled comprehensive nurse who also acts as a supervisor for CHWs. HC-IIs are required to treat uncomplicated malaria with Artemether/Lumefantrine combination, uncomplicated pneumonia with vitamin A and amoxicillin and watery diarrhoea with ORS and zinc. Study participants were caretakers of children aged 4-59 months who had received treatment for malaria from a CHW or PHFW and children aged 2-59 months who had received treatment for pneumonia or diarrhoea from either CHWs or PHFWs in sub-counties served by both CHWs and PHFWs. Caretakers were mainly parents and grandparents of the sick children.

Sample size estimation

Assuming an average PQC of 2.7 and standard deviation 0.82 for PHFWs (satisfaction with quality of health care for patients attending the outpatient clinic in Mulago hospital Uganda from Nabbuye-Sekandi et al [21]); a sample size of 158 participants were required in order to detect a 30% difference in mean PQC for CHWs and PHFWs with 90% power at 5% significance. In order to adjust for a cluster effect of 2 and a loss to follow up of 10%, a sample of 348 participants was required in each group.

Sampling method

Using computerised random sampling 30% of the 72 sub-counties with CHWs trained on iCCM were sampled (for logistical purposes). Using cluster sampling with probability proportionate to cluster size, 98 villages were selected from the sub-counties. All CHWs and their supporting primary health facility units for the selected villages were included in the study. Among the children treated by each selected CHW within 2 weeks of interview, a maximum of 3 were sampled by a trained research assistant through systematic random sampling of the register. Samples from the primary health facility units were drawn through systematic sampling from a list compiled from the outpatient register including only children with uncomplicated malaria, pneumonia and or diarrhoea seen in the past two weeks. The children sampled from the registers were restricted to ages 2-59 months for diarrhoea and pneumonia and 4-59 months for malaria. Equal numbers of children were sampled from the CHWs and PHFWs working in the primary health facility units of the same catchment area. Prior to data collection, out-patient department staff were asked to record contact information for caretakers of all under fives who did not mind having a follow up interview at home. The caretakers of children sampled from the records were then traced and interviewed.

Study instruments

Drawing from Donabedian’s criteria for quality assessment [12] a last visit based quality of healthcare assessment tool (available from first author on request) was used. The tool was adapted from the primary care assessment survey (available on request at ) and the Uganda service provision assessment survey [30,31] and was administered to the caretakers by trained research assistants. Primary care assessment survey and a similar tool known as the primary care assessment tool have previously been tested for validity and reliability [30,32,33,34]. The tool was translated into the native languages before pilot testing. The tool measured quality domains (table 1) using weighted scale items assumed to have equal relationship to the quality concept (summary scales) being measured. Each summary scale had a set of items (2-8) that prompted participants to rate their experiences with quality of health care. The rating scales varied from a minimum of 0-2 to a maximum of 0-10.
Table 1

Domains, summary scales and scale items used in measurement of perceived quality of care on the last visit to the health worker.

Domain AreaDefinitionDomain summary scaleScale item/content
Structure of the health careHealth system organisational factors that act as conduit through which care is offeredFinancial accessMeasure of the amount of money spent on treatment including user fees during an illness episode
Organizational accessAvailability of staff and services and convenience of location of the health structure
Longitudinal continuityDuration of contact between the health provider and user
Visit based continuityOngoing care for the same episode of illness
ProcessProcesses refers to what is done to the user during a health care delivery and receipt relationshippatient competence (comprehensiveness)Provider knowledge of the patient
Preventive Counselling (comprehensiveness)Discussion of preventive measures with the user
Integration of health servicesProviders role in coordinating referral and receiving feedback in from referred patients/caretakers
communicationAbility to probe for symptoms give feedback and assist in making treatment decisions
Physical examThoroughness of the physical examination
Interpersonal treatmentPatience, friendliness , respect and giving quality time to patient
TrustIntegrity , patience and role of health provider as patient’s agent
OutcomeOutcomes are occurrences arising as a result of health care received and are aimed at maximizing benefits according to the user’s needsMeasures of outcome
Satisfaction
Health statusChange in health status and quality of life attributable to health service provided
Enablement feltEmpowerment to have behavioural change.

Statistical analysis

The overall objective of the analysis was to compare PQC scores for caretakers of children who received treatment from CHWs to those received treatment from PHFWs. Using the primary care assessment survey scoring guidelines (available on request at ) reverse coding was done for scale items with questions asked in a negative way to achieve consistency in directionality. Items with higher rating score values were recalibrated to ensure equal weights for all items contributing to the same summary scale. Recalibration ensured that equal total scale score variance contribution assumptions underlying valid linear summated rating scales are fulfilled. Raw scale scores were calculated for each scale by summing across scale items for participants responding to over 50% summary scale items. In case of missing values and a response rate above 50% scale items, the median was used to impute data before raw scale score calculation. Raw scale scores were converted into transformed scale scores on a scale of 0-100 using the formula recommended by the primary care assessment survey scoring guidelines. Domain summary scale scores with adequate sample size in both groups (9/11) were used to predict an overall PQC score through factor analysis. The two excluded items included integration and longitudinal continuity. Chi-square tests were used to a) compare socio-demographic characteristics and categorical summary scale items between the two groups and b) compare categorical treatment outcomes between the two groups. PQC for each summary scale, the overall predicted quality scores, and stated overall satisfaction were compared between the two groups using Wilcoxon rank-sum test as data were highly skewed. The lower, median (middle two) and upper quartiles of each summary scale score were categorised as low, medium and high-quality, respectively. Multinomial logistic regression for categorical outcomes was used to assess the association between PQC for each summary scale and service providers while controlling for potential confounders. Robust standard errors with adjustment for clustering at the village and primary health facility levels were used to account for possible correlation between caretakers of children visiting the same health worker. Given the fact that independent multinomial models yielded high relative risks and consistent directions of association between PQC and service providers among the three quality categories, the overall predicted quality scores were dichotomised into “high quality” and “low quality” using a median split. A modified Poisson regression model was then used to adjust for these high relative risk ratios and establish the association between the overall predicted PQC and service providers. The modified Poisson regression model with a sandwich error term can be used to estimate relative risks with efficiency and consistency. The model uses a logarithm link and hence the estimates are robust to omitted covariates [35,36,37]. Questions on ownership of household items, household construction materials, sanitation infrastructure and means of transportation were used to create a single indicator representing household wealth through principal components analysis. The wealth indicator of individual households ranked from lowest to highest was divided into the upper, middle and lower terciles which represent the socioeconomic status. The individual indicators that weighted heaviest in the analysis were house construction materials (roof, walls and floor material) and type of toilet facility used. All analysis was done in STATA version 12.

Results

Data were drawn from caretakers of children with complete data and whose last visit was with a PHFWs (376/399; 94.2%) or CHWs (377/419; 90.0%). Of the complete observations, 3.0% had at least one summary scale item value imputed and exclusion of these results would not significantly affect the sample size. All study participants were recruited from 98 villages in 24 sub-counties. The group of caretakers who last visited CHWs had significantly more missing overall predicted quality scores (10.0%) relative to the group that last visited PHFWs (5.8%, p=0.02). Majority (82%) of caretakers visiting CHWs had historical contact with the PHFWs in the last month, while only 54.5% of caretakers visiting PHFWs had been to a CHW with a sick child (p<0.001). Overall there were no observed differences in age and sex between caretakers visiting CHWs or PHFWs (table 2). Caretakers visiting the CHWs had a significantly higher socioeconomic status compared to those visiting the PHFWs .The caretakers of children managed by PHFWs were also more likely to have education levels beyond primary education. The proportion of children with diarrhoea was significantly higher in children visiting PHFWs, while no significant differences were observed for malaria and pneumonia. They also often had overall predicted quality scores falling in the high or medium category compared to low (table 2). With respect to PHFWs, higher proportions of overall predicted quality scores fell in the medium category for HC-IIs and HC-IIIs (60.7% and 45%) respectively, while more fell in the low category for HC-IVs (79.5%; p<0.001).
Table 2

Distribution of basic characteristics and overall perceived quality scores between caretakers of children treated by PHFWs and CHWs.

CharacteristicPHFWs Number (%)CHWs Number (%)Total % p-value
Sex0.402
Female359 (90.9)383 (92.5)742 (91.7)
Male36 (9.1)31 (7.5)67 (8.3)
total395414 809
Age0.792
0-1938 (9.7)33 (8.0)71 (8.8)
20-29306 (78.5)328 (79.4)634 (79.0)
40+46 (1.8)52 (12.6)88 (12.2)
total390 413803
education level0.032*
None 69 (17.3) 61(14.6) 130 (15.9)
Primary 240 (60.1) 288 (68.7) 528 (64.5)
Secondary and beyond 90 (22.6) 70 (16.7) 160 (19.6)
Total 399 419 818
social economic status0.020*
Lower (1/3)150 (37.6)123 (29.4)273 (33.4)
Middle (1/3)132 (33.1)141 (33.6)273 (33.4)
Upper (1/3)117 (29.3)155 (37.0)272 (33.2)
Total399419818
malaria diagnosis0.073
No104 (26.1)85 (20.7)189 (23.4)
Yes295 (73.9)325 (79.3)620 (76.6)
Total399 410 809
pneumonia 0.089
No280 (70.2)311 (75.5)591 (72.9)
Yes119 (29.8)101 (25.5)220 (27.1)
total399 412 811
diarrhoea0.013*
No299 (75.0)344 (82.1)643 (78.6)
Yes100 (25.0)67 (17.9)175 (21.4)
total399419818
Quality category<0.001*
low171 (45.5)18 (4.8)189 (25.1)
medium179 (47.6)196 (52.0)375 (49.8)
high26 (6.9)163 (43.2)189 (25.1)
Total376377753

Significant p-value

Significant p-value Summary scales for organisational and financial access varied greatly between PHFWs and CHWs due to differences in constituent items summarised in table 3. Organisational access was generally perceived to be higher among caretakers of children treated by CHWs compared to those treated by PHFWs as explained by shorter travel distances, waiting times and better access hours. Financial access scores were lower for the PHFWs with higher proportions of caretakers contemplating cancelling treatment visits and skipping medications due to expenses involved.
Table 3

Association between access measurements and service providers.

CharacteristicPHFWs Number (%)CHWs Number (%)Total (%) P-Value
Organizational access
Travel time
Less than 30 min151 (37.9)328 (78.3)479 (58.6)<0.001*
0.5-1 hours117 (29.4)71 (16.9)188( 23.0)
1 - 2 hours86 (21.6)17 (4.1)103(12.6)
More than 2 hours44 (11.1)3 (0.7)47 (5.7)
Total 398419817
More opening hours needed
Early in the morning No227 (61.8)353 (84.2)580 (73.8)<0.001*
Yes140 (38.1)66 (15.7)206 (26.2)
Total367419786
In the evenings No313 (91.2)390 (93.1)703 (92.4)0.420
Yes29 (8.4)29 (6.9)59 (7.6)
Total342419761
On weekends No270 (76.3)413 (98.6)683(88.4)<0.001*
Yes84 (23.7)6 (1.4)90 (11.6)
Total354419773
None No236 (66.7)105 (25.1)<0.001*
Yes118 (33.3)313 (74.9)
Total354418772
Waiting time
≤ 5 min 142 (35.7)396 (94.5) 538 (65.8)< 0.001*
6 -30 min107 (26.9)20 (4.8)127 (15.5)
31 -60 min21 ( 5.3)1 (0.2)22 (2.7)
> 60 min128 (32.2)2 (0.5)130 (15.9)
Total398419817
Financial access
Visit costs expensive No358 (89.7)414 (98.8)772 (94.4)<0.001*
Yes41(10.3)5 (1.2)46 (5.6)
Total399419818
Drugs skipped due to cost No41 (10.3)13 (3.1)54 (6.6)<0.001*
Yes356 (89.7)406 (96.9)762 (93.4)
Total397419816

Significant p-value

Significant p-value There were differences in PQC scores for the two groups, both for the overall predicted score and for individual summary scale items or domains (table 4). Overall, CHWs’ ratings were significantly higher than PHFWs ratings in the areas of clinical interaction, patient competence, preventive counselling, examination, communication and interpersonal treatment. Although children treated by CHWs were more likely to see the same person on different visits for the same illness episode the continuity of care was rated low. Additionally children treated by PHFWs were more likely to have had the same provider for longer durations compared to those treated by CHWs. The proportion of children referred to seek treatment from a higher level facility was significantly higher for CHWs (14.3%) compared to the PHFWs (2.0%, p<0.0001) but no significant differences existed in perceived integration of health services.
Table 4

Difference in perceived quality of care between caretakers of children visiting community health workers and primary health facilities.

DOMAIN ITEMPHFWsCHWs
StructureMean (SD)Median (IQR)Mean (SD)Median (IQR)Ranksum p-value
Organizational access52.4 (21.8)53.3 (40.0- 66.7)81.2 (14.8)80.0 (73.3-3.3)<0.0001*
Visit based continuity38.3 (21.3)40 (20.0-40.0)17.2(17.8)20.0 (0.0-20.0)<0.0001*
Longitudinal continuity64.6 (35.6)75.0 (25.0-100)42.0 (26.4)50.0 (25.0-50.0)<0.0001*
Financial access66.5 (23.9)60.0 (50.0-80.0)85.0 (17.9)90.0 (80.0-100)<0.0001*
Process-comprehensiveness
Patient competence52.4 (22.2)53.7 (33.7-68.7)70.3 (17.2)72.5 (58.7-83.7)<0.0001*
preventive counselling51.8(38.4)60.8 (21.6-100)76.5 (30.4)80.4 (60.8-100)<0.0001*
Process-clinical interaction
physical examination61.9 (23.9)60.0 (60.0-80.0)80.8 (16.2)80.0 (80.0-100)<0.0001*
Communication60.7 (18.1)63.3 (53.3-70.0)76.7 (13.0)76.7 (66.7-86.7)<0.0001*
Interpersonal treatment61.3 (21.2)60.0 (48.0-80.0)80.7 (15.2)80.0 (68.0-96.0)<0.0001*
Trust69.6 (17.1)67.8 (57.1-82.1)79.4 (13.2)78.6 (71.4-89.3)<0.0001*
Process- integration
Integration57.7 (23.4)58.3 (46.7-73.3)57.6 (22.4)53.3 (40.0-73.3)0.2820
overall quality score-0.58 ( 0.94)-0.50 ( -3.77- 1.82)0.58 (0 .66)0.65 ( -1.66- 1.79)<0.0001*
Satisfaction (outcome) 24.4 (16.9)16.7 (16.7-33.3)14.5 (11.4) 16.7 (0.0-16.7)<0.0001*

Significant p-value

Significant p-value With regards to visit outcomes, mean stated satisfaction with the entire visit was higher for PHFWs visits compared to CHWs visits (table 4). Caretakers of children treated by CHWs registered higher cure prevalence and behavioural change as a result of advice provided on the last visit, compared to caretakers visiting PHFWs (table 5).
Table 5

Distribution of visit outcomes between CHWs and PHFWs.

outcomePHFWsCHWsTotal P-value
Number (%)Number (%)Number (%)
Child recovered<0.001*
Yes 254 (71.7)346 (85.2)600 (78.9)
No100 (28.2)60 (14.8)160 (21.0)
Total354 406 760
Required extra treatment0.362
Yes25 (7.2)32 (9.1)57 (8.1)
No 322 (92.8)320 (90.9)642 (91.8)
Total347352 699
Child died0 (0)0 (0)0N/A
Had complications0.302
Yes6 (1.7)3 (0.9)9 (1.3)
No338 (98.3)347 (99.1)685 (98.7)
Total344 350 694
Still on treatment0.184
Yes30 (7.5)22 (5.2)52 (6.4)
No369 (92.5)397 (94.7)766 (93.6)
Total399419818
Behavioural change following treatment
Sleeping under a net
Yes265 (66.7)330 (79.3)595 (73.2) <0.001*
No132 (33.2)86 (20.6)218 (26.8)
Total397416813
Drinking clean water
Yes242 (60.8)310 (74.7)552 (67.9)<0.001*
No156 (39.2)105 (25.3)261 (32.1)
Total398415813
Feeding the sick child
Yes266 (67.0)330 (79.1)596 (73.2)<0.001*
No131 (33.0)87 (20.9)218 ( 26.8)
Total397417814

Significant p-value

Significant p-value In multinomial regression models for the separate quality domains where potential confounders were adjusted for (table 6), the model for organizational access had the highest relative risk ratios for quality compared to the models for other summary scales (domains). In the “modified” Poisson regression model (table 7), adjusting for potential confounding factors with overall PQC categorised as “high” and “low”,the proportion of caretakers reporting high PQC was higher for CHWS compared to PHFWs, RR=3.1 (95%CI(2.5-3.8).
Table 6

Multinomial logistic regression model of association between categorised perceived quality of care and service provider for the overall perceived quality score and for each domain (N= 753).

Domain/Scale itemQuality categoryCHWs versus PHFWs (unadjusted)CHWs vs PHFWs (unadjusted)
Financial accessLow quality1.01.0
Medium quality4.6 (3.17-6.85)5.2 (3.5-8.01)
High quality7.3 (4.94-10.88)7.8(5.27-11.01)
Organizational accessMedium versus low 17.1(10.17-28.93)19.2 (10.88-33.80)
High versus low78.5 (38.97-158.34)87.5 (41.60-184.03)
Visit based continuityMedium versus low0.2 (0.14-0.31)0.2 (0.13-0.31)
High versus low0.0 (0.02-0.09)0.4 (0.03-0.10)
Patient competenceMedium versus low4.9 (3.18-7.49)4.7 (3.02-7.50)
High versus low10.9 (5.96-20.01)9.1 ( 5.35-15.63)
Preventive counsellingMedium versus low3.2 (2.14-4.72)2.5 (1.70-3.98)
High versus low4.7 (3.13-7.02)3.6 (2.37-5.73)
Physical examinationMedium versus low4.4 (2.87-6.86)4.7(3.31-6.80)
High versus low7.4 (4.39-12.62)8.2 (5.25-12.87)
communicationMedium versus low4.9 (3.28-7.28)4.8 (3.08-7.47)
High versus low11.5(6.88-18.08)16.4 (9.61-28.04)
Interpersonal treatmentMedium versus low4.7 (3.27-6.74)5.0 (3.42-7.41)
High versus low12.3 (7.66-19.87)12.3 (7.38-20.41)
TrustMedium versus low3.1 (2.10-4.52)3.1 (2.07-4.82)
High versus low5.4 ( 3.55-8.13)4.5 (2.84-7.01)

The reference category for service provider is PHFWs; the reference category for perceived quality of care is low quality and is always equal to one.

Models for integration and longitudinal continuity were excluded because of sample size violation.

Other covariates included in each of the models were socio-economic status, previous visit to a CHW or PHFW, education level, type of disease and duration between the interview and the health provider visit.

Table 7

Modified Poisson regression models for the association the between the predicted quality score and both service providers and visit outcomes (N= 753).

Predicted perceived quality unadjusted quality IRRp-valueadjusted quality IRRp-value
CHWs versus PHFWs3.3 (2.73-4.02)<0.0013.10 (2.53-3.81)<0.001*
Child recovered versus not1.70 (1.37- 2.10)<0.0011.56 (1.26-1.93)<0.001*
Needed more treatment versus not0.90 (0.66-1.23)0.5121.52 (1.01-2.28)0.043*
Still on treatment versus not0.72 (0 .50-1.06)0.0891.15 (0.75-1.77)0.513

Significant p-value

Other covariates included in each of the models were socio-economic status, previous visit to CHW or PHFW, education level, type of disease and duration between the interview and the health provider visit.

The reference category for service provider is PHFWs; the reference category for perceived quality of care is low quality and is always equal to one. Models for integration and longitudinal continuity were excluded because of sample size violation. Other covariates included in each of the models were socio-economic status, previous visit to a CHW or PHFW, education level, type of disease and duration between the interview and the health provider visit. Significant p-value Other covariates included in each of the models were socio-economic status, previous visit to CHW or PHFW, education level, type of disease and duration between the interview and the health provider visit.

Discussion

Results from this study show higher ratings for PQC received from CHWs compared to care received from PHFWs in all quality domains, except for continuity. The association between quality of health care received and health provider choice has been previously debated [38,39,40]. Campbell argues that quality is best applied to the individual user who accesses the health structure, interacts with health providers and receives holistic care [10]. This same concept has been used to explain the differences in scores observed in this study. In terms of structure, iCCM is inherently associated with improved financial and geographical access as it uses CHWs who provide free health services [2,27]. Previous studies have shown that accessibility, affordability, and free medicines are all associated with better PQC [39,41]. Although both PHFWs and CHWs offer free services, differences in costs are likely to occur due to some differences in financing mechanisms used. For example a study on user satisfaction with quality of health care in Uganda reported on unexpected health costs incurred by patients at the hospitals in the form of unforeseen investigations [21]. Corruption in form of under the table user-fees is also well documented among PHFWs in Uganda and other low income countries [42,43,44]. Organisational access differs with respect to flexibility in working hours whereby the home based CHWs are more likely to be flexible compared to PHFWs, a characteristic which is valued by caretakers [27]. In Uganda staff absenteeism in health facilities is well documented, leading to facilities being unmanned during opening hours a phenomenon that has been termed as “the quiet corruption” by the World Bank (The World Bank, 2010). Longitudinal continuity was rated lower for CHWs than for PHFWs, probably because iCCM was inaugurated in Uganda as late as June 2010, while primary health facility units might have had the same staff for longer durations. Some studies have argued that visit based continuity can improve PQC through the establishment of provider-user relationships [14,20]. It is therefore not clear why CHWs were rated lower than PHFWs despite implied higher continuity. It is possible that CHWs’ inability to treat a child who gets worse on treatment (as they are advised to refer) might be a contributing factor. CHWs operate within their own community and are therefore more likely to behave as expected by the community members and to have established trusting relationships with caretakers [27,45]. They are more likely to communicate better with their already known subjects during a clinical interaction session leading to higher scores for process measures of quality. Trust is also known to have a role in health seeking behaviour with respect to provider choice [10,20,46]. Satisfaction with health provider as an outcome was rated higher among the PHFWs. It is possible that caretakers are more comfortable with the education level and professional skills of PHFWs. It is also likely that they appreciate getting several opinions from different health workers between illness episodes. However, there is a need to dig deeper into the low satisfaction despite high PQC. Study limitations and methodological considerations included recall bias which was minimized through use of a two week period between provider visits and interview. Quality ratings vary with the interval between the interview and the visit to the health provider [47]. Data obtained from cluster samples have been criticized for lack of representability compared to individual samples [48], however cluster robust standard errors were used to adjust for clustering at health worker level. The study tool was previously validated in non-African contexts and efforts were made to adapt the questionnaire through comparison with questions from the Uganda service provision survey. The self-selection of individuals receiving care from health facilities and CHWs in the study might have created an unavoidable bias as PHFWs might be seeing sicker children however attempts were made to recruit children with similar diseases. There was an inevitable possibility of caretakers perceiving quality as high for CHWs due to mere friendship. The study was also not able to capture the cadre of staff at the primary health facility level where more often than not several cadres of staff exist.

Conclusion

In an ‘ideal’ world of universal health coverage (UHC), access to the best clinical and interpersonal quality of care is everyone’s right. In this resource constrained setting, caretakers’ PQC was significantly higher for CHWs compared to PHFWs. This finding suggests that it is viable to improve access to care for sick children through use of CHWs as their services are well perceived. CHWs could thus play an important interim role in achieving UHC by addressing quality gaps in the areas of access to health care and patient- provider interactions where they score highly. Since PHFWs supervise CHWs and manage referred children, strategies that improve the health provider and patient relationship should be of concern in health system strengthening.
  42 in total

1.  Maternal and child health services in rural Nepal: does access or quality matter more?

Authors:  L B Acharya; J Cleland
Journal:  Health Policy Plan       Date:  2000-06       Impact factor: 3.344

2.  Defining quality of care.

Authors:  S M Campbell; M O Roland; S A Buetow
Journal:  Soc Sci Med       Date:  2000-12       Impact factor: 4.634

3.  Reducing child mortality: can public health deliver?

Authors:  Jennifer Bryce; Shams el Arifeen; George Pariyo; ClaudioF Lanata; Davidson Gwatkin; Jean-Pierre Habicht
Journal:  Lancet       Date:  2003-07-12       Impact factor: 79.321

Review 4.  Model-based estimation of relative risks and other epidemiologic measures in studies of common outcomes and in case-control studies.

Authors:  Sander Greenland
Journal:  Am J Epidemiol       Date:  2004-08-15       Impact factor: 4.897

5.  Overcoming health-systems constraints to achieve the Millennium Development Goals.

Authors:  Phyllida Travis; Sara Bennett; Andy Haines; Tikki Pang; Zulfiqar Bhutta; Adnan A Hyder; Nancy R Pielemeier; Anne Mills; Timothy Evans
Journal:  Lancet       Date:  2004 Sep 4-10       Impact factor: 79.321

6.  A modified poisson regression approach to prospective studies with binary data.

Authors:  Guangyong Zou
Journal:  Am J Epidemiol       Date:  2004-04-01       Impact factor: 4.897

7.  Effect of an IMCI intervention on quality of care across four districts in Cape Town, South Africa.

Authors:  M Chopra; S Patel; K Cloete; D Sanders; S Peterson
Journal:  Arch Dis Child       Date:  2005-04       Impact factor: 3.791

8.  Perceived quality of care of primary health care services in Burkina Faso.

Authors:  R M P M Baltussen; Y Yé; S Haddad; R S Sauerborn
Journal:  Health Policy Plan       Date:  2002-03       Impact factor: 3.344

9.  Management of severely ill children at first-level health facilities in sub-Saharan Africa when referral is difficult.

Authors:  Eric A F Simoes; Stefan Peterson; Youssouf Gamatie; Felix S Kisanga; Gelasius Mukasa; Jesca Nsungwa-Sabiiti; M Wilson Were; Martin W Weber
Journal:  Bull World Health Organ       Date:  2003-09-03       Impact factor: 9.408

Review 10.  How many child deaths can we prevent this year?

Authors:  Gareth Jones; Richard W Steketee; Robert E Black; Zulfiqar A Bhutta; Saul S Morris
Journal:  Lancet       Date:  2003-07-05       Impact factor: 79.321

View more
  8 in total

1.  Perceived Quality of Care of Community Health Worker and Facility-Based Health Worker Management of Pneumonia in Children Under 5 Years in Western Kenya: A Cross-Sectional Multidimensional Study.

Authors:  Brian I Shaw; Elijah Asadhi; Kevin Owuor; Peter Okoth; Mohammed Abdi; Craig R Cohen; Maricianah Onono
Journal:  Am J Trop Med Hyg       Date:  2016-03-14       Impact factor: 2.345

2.  Determinants of Utilization and Community Experiences with Community Health Volunteers for Treatment of Childhood Illnesses in Rural Sierra Leone.

Authors:  Aisha I Yansaneh; Asha S George; Alyssa Sharkey; William R Brieger; Lawrence H Moulton; Fatu Yumkella; Peter Bangura; Augustin Kabano; Theresa Diaz
Journal:  J Community Health       Date:  2016-04

Review 3.  Towards eliminating malaria in high endemic countries: the roles of community health workers and related cadres and their challenges in integrated community case management for malaria: a systematic review.

Authors:  Bruno F Sunguya; Linda B Mlunde; Rakesh Ayer; Masamine Jimba
Journal:  Malar J       Date:  2017-01-03       Impact factor: 2.979

4.  Integrated community case management in a peri-urban setting: a qualitative evaluation in Wakiso District, Uganda.

Authors:  Robin Altaras; Mark Montague; Kirstie Graham; Clare E Strachan; Laura Senyonjo; Rebecca King; Helen Counihan; Denis Mubiru; Karin Källander; Sylvia Meek; James Tibenderana
Journal:  BMC Health Serv Res       Date:  2017-11-28       Impact factor: 2.655

5.  Facility type and primary care performance in sub-district health promotion hospitals in Northern Thailand.

Authors:  Nithra Kitreerawutiwong; Sue Jordan; David Hughes
Journal:  PLoS One       Date:  2017-03-24       Impact factor: 3.240

6.  Under 10 mortality patterns, risk factors, and mechanisms in low resource settings of Eastern Uganda: An analysis of event history demographic and verbal social autopsy data.

Authors:  Rornald Muhumuza Kananura; Tiziana Leone; Tryphena Nareeba; Dan Kajungu; Peter Waiswa; Arjan Gjonca
Journal:  PLoS One       Date:  2020-06-11       Impact factor: 3.240

7.  Estimating the cost of referral and willingness to pay for referral to higher-level health facilities: a case series study from an integrated community case management programme in Uganda.

Authors:  Agnes Nanyonjo; Benson Bagorogoza; Frida Kasteng; Godfrey Ayebale; Fredrick Makumbi; Göran Tomson; Karin Källander
Journal:  BMC Health Serv Res       Date:  2015-08-28       Impact factor: 2.655

8.  How Do Patients and Health Workers Interact around Malaria Rapid Diagnostic Testing, and How Are the Tests Experienced by Patients in Practice? A Qualitative Study in Western Uganda.

Authors:  Robin Altaras; Anthony Nuwa; Bosco Agaba; Elizabeth Streat; James K Tibenderana; Sandrine Martin; Clare E Strachan
Journal:  PLoS One       Date:  2016-08-05       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.