Health Policy and Planning, 35, 2020, ii22–ii34
doi: 10.1093/heapol/czaa121
Supplement Article
Team-based primary health care for
non-communicable diseases:
complexities in South India
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Dorothy Lall 1,*, Nora Engel2, Narayanan Devadasan1,
Klasien Horstman2 and Bart Criel3
1
Institute of Public Health, 3009, II-A Main, 17th Cross, KR Rd, Siddanna Layout, Banashankari Stage II,
Banashankari, Bengaluru, Karnataka, 560070 India
2
Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, PO Box 616, 6200 MD
Maastricht, The Netherlands
3
Institute of Tropical Medicine, Nationalestraat 155, Antwerpen 2000, Belgium
*Corresponding author. Institute of Public Health, 3009, II-A Main, 17th Cross, KR Rd, Siddanna Layout, Banashankari
Stage II, Banashankari, Bengaluru, Karnataka 560070, India. E-mail: dorothylall@gmail.com
Accepted on 3 September 2020
Abstract
Chronic non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases,
have reached epidemic proportions worldwide. Health systems, especially those in low- and
middle-income countries, such as India, struggle to deliver quality chronic care. A reorganization of
healthcare service delivery is needed to strengthen care for chronic conditions. In this study, we
evaluated the implementation of a package of tailored interventions to reorganize care, which were
identified following a detailed analysis of gaps in delivering quality NCD care at the primary care
level in India. Interventions included a redesign of the workflow at primary care clinics, a redistribution of tasks, the introduction of patient information records and the involvement of community
health workers in the follow-up of patients with NCDs. An experimental case study design was
chosen to study the implementation of the quality improvement measures. Three public primary
care facilities in rural South India were selected. Qualitative methods were used to gain an in-depth
understanding of the implementation process and outcomes of implementation. Observations,
field notes and semi-structured interviews with staff at these facilities (n ¼ 15) were thematically
analysed to identify contextual factors that influenced implementation. Only one of the primary
health centres implemented all components of the intervention by the end of 9 months. The main
barriers to implementation were hierarchical arrangements that inhibited team-based care, the
amount of time required for counselling and staff transfers. Team cohesion, additional staff and
staff motivation seem to have facilitated implementation. This quality improvement research highlights the importance of building relational leadership to enable team-based care at primary care
clinics in India. Redesigned organization of care and task redistribution is important solutions to deliver quality chronic care. However, implementing these will require capacity building of local primary care teams.
Keywords: Teamwork, primary care, non-communicable diseases, implementation, quality improvement
Introduction
In the last few decades, the burden of chronic non-communicable diseases (NCDs), such as diabetes and cardiovascular diseases, has
increased, especially in low- and middle-income countries (LMICs),
including India (Dandona et al., 2017). India is heralded as the diabetes
capital of the world, with an estimated 72 million persons living with
C The Author(s) 2020. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.
V
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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Health Policy and Planning, 2020, Vol. 35, Suppl. 2
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KEY MESSAGES
•
•
•
•
diabetes in 2017 (International Diabetes Federation, 2017).
Hypertension, a leading risk factor for cardiovascular disease, has also
steadily increased. In 2017, there were an estimated 207 million persons
living with increased blood pressure in India (Gupta et al., 2018).
Traditionally designed to deliver care for acute diseases, health
systems in India are struggling to provide care for chronic conditions
(Samb et al., 2010; Gabert, 2017). Despite a national programme
launched by the government of India in 2009 for the control of
NCDs, focusing on diabetes, stroke, cancer and cardiovascular diseases (Ministry of Health & Family Welfare and Government of
India, 2010), the outcomes of care for these conditions are abysmally poor (Mohan et al., 2014; Unnikrishnan et al., 2014). Primary
care is best suited for managing chronic NCDs (Rothman and
Wagner, 2003; World Health Organization, 2008), but the services
specified in the national programme are limited to screening, continuation of medication and providing health-promoting messages.
Strengthening primary care to deliver continuous, comprehensive
and coordinated care for persons with chronic conditions is necessary (Das et al., 2015; Sinha and Pati, 2017). Any improvements in
the design of services require evidence about the system changes
needed to produce better care (Wagner et al., 2001).
Quality improvement (QI) research studies the design, development and evaluation of interventions to provide evidence for relevant redesign of health systems (Eccles et al., 2003; Peters et al.,
2013). There is a paucity of literature from India with regard to
such QI initiatives, especially at the primary care level, that could inform the design and guide the implementation of interventions
meant to improve care for chronic conditions.
We conducted QI research to improve care for chronic NCDs,
specifically diabetes and hypertension, at public primary health
centres (PHCs) in a rural district in South India. The interventions to
improve quality of services for diabetes and hypertension care were
developed to address specific gaps identified through a situational
analysis in the same setting as reported previously (Lall et al., 2019).
In this paper, we present the implementation process, including
the development of interventions. We critically analyse the implementation process using implementation and QI frameworks to
identify contextual factors that may have resulted in the differential
uptake of interventions at the different PHCs. The insights we
gained are important to consider while redesigning the delivery of
services and may have implications on the implementation of the
current national programme for NCDs.
Theoretical background
The quality of care delivered through the health infrastructure is of
great concern to health care providers and patients. The National
Academy of Medicine (previously Institute of Medicine) landmark
report on crossing the quality chasm catalysed discussions on delivering and measuring quality in health care organizations (Institute of
Medicine, 2001). Arguably, improving the quality of services is an
everyday task and an obligation of service providers (Hirschhorn
et al., 2018), but systematically studying the effect of changes to the
delivery process on outcomes of care can inform choices that providers make. Thus, QI research is characterized as a type of implementation research (Peters et al., 2013). Interventions in QI research
are usually complex, and their success often depends on how the approach is tailored to address a problem in a given context
(Ramaswamy et al., 2018). Contextual influences include all factors
other than the intervention that influence implementation and outcomes of QI (Damschroder et al., 2009; Wells et al., 2012). A systematic review of contextual factors in 47 QI studies revealed that
organizational characteristics of the health facilities (e.g. size, ownership), leadership of the QI and management teams, organizational
culture, number of years involved in QI, data infrastructure and information systems and resources available are associated with implementation outcomes. Several theoretical frameworks have
attempted to categorize these contextual factors and are useful, as
they allow a systematic assessment of context in a wide range of settings (Greenhalgh and MacFarlane, 2005; Johnson and May, 2015;
May et al., 2016). In this analysis, we draw on two such theoretical
frameworks, the Consolidated Framework for Implementation
Research (CFIR) (Damschroder et al., 2009) and the Model for
Understanding Success in Quality (MUSIQ) (Kaplan et al., 2012), to
analyse factors that may have influenced implementation in our setting and context.
The CFIR is a meta-theoretical framework that identifies five
major domains that impact implementation: FEFFthe intervention,
inner and outer settings, the individuals involved and the process by
which implementation is accomplished. The intervention is conceptualized as having core components and elements that can and
should be adapted to the setting. The inner settings relate to the economic, political and social context within which the organization
resides, and the outer settings to the structural, political and cultural
contexts through which the implementation process proceeds. The
individual is viewed as the carrier of cultural, organizational, professional and individual mindsets, norms, interests and affiliations with
predictable or unpredictable consequences for implementation.
Finally, the implementation process itself involves an active change
process aiming to achieve use of the interventions as designed
(Damschroder et al., 2009). This framework provides useful categorization and definitions of the factors affecting implementation
that have been reported in implementation literature.
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Implementing changes in the workflow, redistributing tasks to members of primary care teams, recording patient information and
involving community health workers in the follow-up of patients in primary care settings in India is a challenge with respect to the
local context.
We found that the implementation of quality improvements was negatively impacted by the hierarchy within the team, inhibiting
team-based care, whereas team cohesion and motivation from implementing the interventions facilitated the implementation process.
We argue that there is a need to nurture participatory leadership at primary care facilities in India and similar settings to build an environment that overcomes hierarchies to facilitate team-based care.
This study also highlights the need for more research regarding organizational behaviour at primary care facilities in India to strengthen primary health care.
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Health Policy and Planning, 2020, Vol. 35, Suppl. 2
also had a care coordinator (CC) with a non-health background.
The CC was appointed to coordinate another pilot project to create
digital records of persons in the PHC catchment area. PHCs 1 and 2
were similar to respect to the average number of patients, and the
average number of persons with diabetes and hypertension receiving
treatment. PHC 3 had a larger catchment area population but relatively fewer patients with diabetes and hypertension under treatment
at the PHC.
Methods
Intervention development
To study the process of implementation and identify influential factors, we chose the case experimental design (Peters et al., 2013;
Toulany et al., 2013) including both observation and the implementation of interventions to improve quality. The interventions were
not static, but changed as they were adapted in the course of implementation relevant to the context of the individual setting.
We developed the interventions based on the results of an analysis of
the quality of service delivery for diabetes and hypertension at PHCs
in Kolar district that we reported elsewhere (Lall et al., 2019).
Doctor-centred care processes, lack of information to maintain continuity of care, fragmented care processes, poor support for selfmanagement and decision-making that was not evidence-based or
patient-centred were identified as factors impacting the quality of
care for NCDs (Lall et al., 2019). We presented these findings to the
DHO and programme managers of the NPCDCS in Kolar district to
identify possible interventions to address the gaps. The interventions
were then discussed with other co-authors who had relevant experience in improving quality of care in similar settings. A package of
interventions (Figure 1) was arrived at and further refined based on
the recommendations of the WHO, such as the package of essential
NCD interventions (WHO, 2010) and the innovative care for chronic conditions framework (World Health Organization, 2001). These
interventions were also supported by evidence of effectiveness in the
literature regarding QI for NCDs at the primary care level. The proposed interventions were a redesign of the workflow for patients
with diabetes and hypertension and identification of tasks to be
completed in the care of these patients (Knox and Branch, 2015;
Panattoni et al., 2017); (Unertl et al., 2009); allocation and redistribution of tasks among the staff at the PHC (Joshi et al., 2014;
Gyamfi et al., 2017); record patient information at the health facility
(Wagner et al., 2001; Unertl et al., 2009) and involve ASHAs to
follow-up with patients in the community (Gilmore and McAuliffe,
2013; Jacobs et al., 2015).
The interventions were then locally adapted and co-designed
with the health care teams at each of the three PHCs during the
course of the study. Co-designing practically entailed iterative discussions with the staff to determine the exact details of the intervention bundle. An average of four such discussions or planning
meetings was conducted at each PHC with the staff before we began
implementing the interventions. This participatory approach was
inspired by the action research methodology (Whyte, 1991) relevant
to QI initiatives, and is known to increase ownership of such initiatives (Wolstenholme et al., 2017). Our role as a research team was
to facilitate the discussions. In response to practical problems that
the teams faced, minor changes were made to the interventions during implementation. Consequently, the interventions were slightly
different at each of the PHCs, even if broadly similar.
The study received ethical approval from the ethics committees
of the Institute of Tropical Medicine, Antwerp (ref 1186/17), the
University of Antwerp (ref 17/47/527) and the Institute of Public
Health, Bengaluru (ref IEC-FR/02/2017). We also obtained permission from the State Ministry of Health and the Kolar District Health
Office to conduct this research.
Setting
The study was conducted at three publicly funded primary care
facilities in Kolar, a rural district in Karnataka state in South India
with a population of 1 536 401 (Office of the Registrar General and
Census Commissioner India, 2011). In India, health care is ordered
in a three-tiered system of primary, secondary and tertiary care provided by both the public and private sectors. >70% of care for
chronic conditions is provided by the private sector, and the public
sector mainly provides services for those who are unable to afford
care elsewhere (Balarajan et al., 2011).
Primary care is delivered by the public sector at PHCs, which are
the first point of contact with a medical doctor, and through a network of sub-centres where an auxiliary nurse midwife and community health workers [accredited social health activists (ASHAs)] are
available for a population of 5000 and 1000, respectively.
Kolar district has 60 PHCs that, in principle, cater to a maximum population of 30 000 persons in a defined catchment area of
surrounding villages (Directorate General of Health Services, 2012).
The usual team at a PHC includes the medical doctor, two staff
nurses, a lab technician and a pharmacist. Services provided at the
PHC are largely structured through ‘vertical’ disease control programmes to fight-specific diseases or disorders, e.g. tuberculosis,
blindness and malaria. The National Program for Control of
Diabetes, Cancers and Stroke (NPCDCS) is the NCD programme
specifying a package of services be delivered at the PHC that
includes screening for diabetes and hypertension, referral to a secondary level hospital for diagnosis, and continuation of medication
for those diagnosed (Ministry of Health & Family Welfare, 2016).
Kolar district has been implementing this programme since 2009.
The doctors in charge of PHCs are responsible for the centre’s
performance.
Selection of PHCs
As the QI initiative sought to improve the quality of care for diabetes and hypertension, we considered the average number of
patients with diabetes and hypertension being treated at the PHC
and the presence of basic infrastructure, including medicines and
health professional staff, to create a list of 25 PHCs that were eligible as ‘cases’ for the study. The list was then discussed with the district health officer (DHO) and 10 of the PHCs shortlisted. Finally,
three PHCs were selected from this list based on the willingness of
the medical doctor to participate.
All three PHCs had a doctor, two nurses, a lab technician and a
pharmacist at the time of inclusion in the study (Table 1). PHC 2
Capacity building
The primary author and a research associate conducted training for
the staff regarding NCDs, risk factors and their control relevant to
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The second framework was more specific to understanding the
context of QI in health care. The MUSIQ identifies external environment, organization (including QI leadership), microsystem (including data infrastructure) and QI team (including physician
involvement) as broad categories of factors that influence implementation. Though the CFIR also mentions these categories, the MUSIQ
provides a model for understanding how these categories interact to
affect implementation (Kaplan et al., 2012).
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
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Table 1 Description of the selected PHCs
Characteristic
PHC 1
PHC 2
PHC 3
Location from the closest town
area
Team at PHC
Close
Remote
Close
MO, 2 nurses, lab technician,
pharmacist
16 000
120
MO, 2 nurses, lab technician,
pharmacist, CC
12 000
100
MO, 2 nurses, lab technician,
pharmacist
31 000
60
Population in the catchment area
Average daily number of patients
seen in OPD
Average monthly number of persons with DM or HTN
20
40
18
Table 2 Team at each PHC
PHC
Interviewee
Label
Age range
(years)
Number of years
at PHC
1
Nurse 1
Nurse 2
Medical officer
Lab technician
Pharmacist
Nurse 1
Nurse 2
Medical doctor
Lab technician
Pharmacist
CC
Nurse 1
Nurse 2
Lab technician
Medical doctor
Pharmacist
N1a
N1b
M1
L1
P1
N2a
N2b
M2
L2
P2
CC2
N3a
N3b
L3
-
30–40
20–30
20–30
40–50
50–60
20–30
30–40
20–30
30–40
40–50
20–30
30–40
20–30
30–40
30–40
30–40
5–10
<1
1–5
15–20
10–15
1–5
1–5
1–5
10–15
10–15
<1
5–10
<1
1–5
1–5
5–10
2
3
the roles of counsellor, lab technician, pharmacist and physician
when the staff expressed a lack of skills, such as counselling, that
were necessary to fulfil the tasks they volunteered to complete. The
Indian guidelines for the standard treatment of diabetes and hypertension (National Centre for Disease Control, MOHFW and GOI,
2017) and the NPCDCS operational guidelines (Ministry of Health
& Family Welfare and Government of India, 2010) were used as reference documents.
No format was available to record patient information at the
PHCs. Therefore, the primary author and a research associate consulted with the staff to create a format (Supplementary 1). The development of the tool required four iterations to balance the main
concern of the staff regarding the time it would take to record the information and identify the necessary information required for treatment decisions.
(January–September 2018) of the implementation (Table 2). In addition to the doctor, nurse, lab technician and pharmacist, at PHC 2
we also interviewed the CC. At PHC 3, we were not able to interview the doctor or the pharmacist, as they had been posted
elsewhere.
The objective of the interviews was to understand how the staff
viewed the interventions and their implementation. The interviews
included questions to explore the working environment, their ability
to make changes, the challenges they faced and their motivation to
implement the interventions. The interview guides were pilot-tested
and refined prior to the interviews (Supplementary 2). All of the
interviews were conducted at the PHC at a time convenient for the
respondents that did not interfere with their daily work schedule.
Each of the interviews was conducted with due attention to privacy,
and consent was obtained individually before the interviews.
Interviews lasted an average of 30 min. During the interviews, interpretations were checked with the participants (member validation)
to improve the internal validity of the data.
Data collection
Positionality of researchers
The primary author and research associate made an average of 14
visits to each PHC to monitor the interventions during the 9 months
of implementation. At each visit, observations were conducted and
extensive field notes taken, specifically including information related
to the care for NCDs. We also conducted semi-structured, in-depth
interviews with the teams at the three PHCs (n ¼ 15) after 9 months
Although the primary author and research associate were considered
external to the PHC team, in the initial months they were invited on
4–5 occasions to participate in some of the tasks, such as recording
patient information and directing patients to follow the new workflow. In the initial few months, we also had to remind the team at
each PHC to complete the records on 2–3 occasions. However, we
Figure 1 Elements of the intervention package
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CC, care coordinator; DM, diabetes mellitus; HTN, hypertension; MO, medical officer; OPD, outpatient department.
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maintained an outsider position throughout the research and were
reflexive, especially as our backgrounds as health care professionals
could have influenced the interpretations. The outsider position
enabled an objective as possible assessment of the implementation
process.
Data analysis
Results
The workflows at the three PHCs were similar before the start
of the intervention (Figure 2). Most tasks, such as examination,
counselling and prescribing, were done by the doctor. Notably,
no foot examination was done and, although the doctor was
counselling patients, it was inconsistent and limited due to time
constraints.
PHC 1
We conducted four planning meetings at this PHC during the first
3 months of the study (January–March 2018). The doctor decided
which members of the team would attend; each meeting was
attended by two members in addition to the doctor, and at no
meeting were all four members present. The discussions were interactive, but the allocation of tasks and decisions regarding changes
were made by the doctor.
The first QI measure we discussed was the flow of patients and
identification of tasks. Members of the team charted the prevalent
flow of a patient diagnosed with an NCD and suggested changes
from a patient’s perspective (Table 3). A new task identified was
measurement of fasting blood sugar, but this was met with resistance by the doctor who felt that it would alter the routine of the
PHC and be unacceptable to patients.
No . . . it’s [testing fasting blood glucose before 9AM] not a tradition here . . . even if you call the patients also . . . they will come at
11:30 or so . . . (D1).
The workflow was implemented as planned for 2 months but
changed after 6 months, and at the end of 9 months the workflow
was almost similar to the pre-intervention period (Table 3). The doctor felt this was because of the large number of patients and the inability of patients to adjust to the new workflow.
Patient flow, usually it will look nice for only 2 to 3 months,
again the patients will follow what they are used to, they will
come to the doctor they will see, they will take medicine . . . the
[new] flow will be difficult when the crowd is more . . . (D1).
The second QI included the distribution of tasks among team
members, such as measurement of blood pressure and counselling
by the nurse, foot examination by the doctor, measurement of
blood glucose by the lab technician, and dispensation of medicine
by the pharmacist. The third QI, recording patient information,
was to be done by all members relevant to the task they complete.
The implementation of the second and third improvements followed a pattern similar to the workflow and, by 9 months, most of
the tasks and recording were being conducted by the doctor
(Table 3). Consequently, even though >100 patients were seen by
the end of 9 months, only 52 records had been initiated. A lack of
time was identified as the reason for not implementing the
interventions.
The patients are large in number, nobody has time to sit with
each of them and talk to them (N1a).
We thought of . . . giving a specific work for a specific people but
it didn’t work really . . . because staff nurse is busy in pricking
[injections] . . . and the pharmacist is busy, only thing is a doctor
is free in this (D1).
Figure 2 Pre-intervention workflow and task distribution at the PHCs. BP, blood pressure; Lab Tech, laboratory technician; RBS, random blood sugar
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Data from the observations, interviews and field notes were uploaded
to NVivo (QSR International Pty Ltd., version 11, 2015). Coding was
done by the primary author using codes identified a priori from relevant constructs of the CFIR and MUSIQ. New codes were assigned to
data that did not fit the a priori codes. Codes, such as culture of the
PHC, implementation climate, attitude to intervention and motivation of staff, were used to categorize the data. Both inductive and deductive approaches were used in the analysis of text. Repetitive
reading of the data and comparisons with the constructs in the frameworks were performed to refine the codes. Coding was discussed with
the other authors to develop a coding tree.
We analysed the data to understand how much of what was
planned was implemented at each of the PHCs over the 9 months. A
thematic analysis was then conducted to identify the themes of contextual factors that may have impacted the implementation process.
The differences in context at the three PHCs were compared with
identify possible explanations for the findings. Participant observation data were used independently to triangulate the data from the
interviews. We found no inconsistencies or contradictions in the
data.
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
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Table 3 Patient flow and tasks at PHC 1 during the course of implementation
PHC 1
Intervention
9 months
BP, blood pressure; FBS, fasting blood sugar; Lab Tech, laboratory technician; PPBS, post prandial blood sugar.
We observed that the doctor did not take the initiative to involve
members of the team:
Since the doctor sees the patient and prescribes the tablets, he
will only maintain the record, rather he explaining us how to do,
he is only writing it (LT1).
The fourth QI to involve ASHAs in the follow-up was initiated
in one meeting where they were sensitized to their role in follow-up
and to support lifestyle modification. This was attended by most of
the ASHAs (15 of 20). The doctor also conducted one meeting,
where he used the clinical record to identify patients in each ASHA’s
area. However, there was no follow-up meeting to continue this
element of the intervention.
PHC 2
Four planning meetings were conducted at this PHC, and each was
attended by all of the staff. The members of the team waited for
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6 months
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
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First, they used to go to the doctor, and then come to me get
sugar levels checked, and then go to the doctor, and if doctor
says, they come back and get their BP checked. Now it is not like
that, first they get their cards from CC and get their tests done
then visit the doctor (LT2).
Changes to the task distribution were made at monthly meetings,
where staff had an opportunity to discuss the challenges they faced.
The task of dispensing drugs was initially the responsibility of the
pharmacist, but during the course of implementation, it was taken
on by the nurse for efficiency (Table 4). Similarly, counselling was
initially taken up by the nurse, but as the lab technician had more
time and was interested in counselling, she volunteered to do this
task. The counselling was done when patients had their blood sugar
tested, and each session lasted 5–20 min. Counselling included advice regarding lifestyle modifications and often became an opportunity for patients to discuss challenges in their lives, including
family circumstances.
When we counsel about walking, food habits, to avoid drinks
and betel nut leaves, they sit and listen. By doing all these, they
can avoid problems, so they sit and listen (LT2).
Fasting blood glucose testing was a challenge and could not be
implemented initially because it required the lab technician to be
available earlier than the regular time. However, the night shift
nurse volunteered to take on this task and, by 9 months, this it was
implemented. However, ASHAs were not involved because the CC
took on the task of making phone calls and reminding patients
about follow-up.
PHC 3
At this PHC, we conducted five planning meetings attended by all of
the staff. The doctor at this PHC assumed the lead responsibility,
but the discussions were interactive and the staff participated in
decision-making regarding the workflow and responsibilities. At
6 months, most of the QI interventions had been implemented as
planned by the team (Table 5).
The nurse expressed challenges, especially with the counselling,
as she could not cope with the time it required. On two occasions,
the time she took to counsel led to the patients waiting outside
becoming restless, and they demanded to be seen faster. This was
discussed at a follow-up meeting and the lab technician volunteered
to do this task when she tested patients’ blood sugar levels.
We can do the counselling, Madam, but we do not have time, we
cannot spend the time with one patient, some patients will speak
less, and some will bring the history of their family and tell us,
my children are not taking care of us, and some start crying, in
that situation we have to give them some time and other patients
will be waiting for us (N3a).
However, 6 months after starting the implementation, the
pharmacist was transferred to another PHC. Soon after, the senior
nurse was transferred and the doctor received a new assignment.
Table 4 Patient flow and tasks at PHC 2 during the course of implementation
PHC 2
Intervention
6 months
9 months
BP, blood pressure; CC, care coordinator; FBS, fasting blood sugar; Lab Tech; lab technician; PPBS, post prandial blood sugar.
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each other to finish their work, and these meetings were conducted
during the lunch break. Even though the doctor assumed the lead
role and gave instructions, there was room for the staff to express
their opinions and make suggestions with respect to specific QIs.
Discussions began with charting the prevalent workflow and tasks,
followed by redesigning and redistributing tasks from a patient’s
perspective.
The workflow design, task distribution and recording of patient
information were implemented at the end of 9 months (Table 4).
A total of 210 patients had clinical information recorded and
used for treatment decisions. Coincidentally, 1 month after the start
of the implementation, a new staff member, a CC, was posted at the
PHC as part of another district health project. The CC took on the
role of coordinating the workflow and guiding patients. The CC became the holder of patient records and was responsible for registering new patients and identifying cards for repeat patients. This was
not a role the team had envisioned at the start, but it enabled implementation of the workflow:
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
ii29
Table 5 Patient flow and tasks at PHC 3 during the course of implementation
PHC 3
Intervention
6 months
BP, blood pressure; FBS, fasting blood sugar; Lab Tech, laboratory technician; PPBS, post prandial blood sugar; RBS, random blood sugar.
These transfers were without replacement; therefore, at 9 months
none of the QIs were implemented. The workflow became redundant, as a doctor was not available for consultations and
prescriptions.
The involvement of ASHAs in the follow-up of patients was also
not implemented 9 months into the implementation phase. The
ASHAs were invited to the PHC for one meeting, where their roles
in follow-up and lifestyle modification were discussed. The meeting
was attended by most of the ASHAs (18 of 25), and they mentioned
that they were already giving lifestyle advice but were not systematically following up with patients. However, further involvement did
not materialize because the doctor was not available.
The QIs were implemented the least at PHC 1 and most at PHC
2. The implementation at PHC 3 started successfully, but when the
team dissolved at 6 months, the implementation process came to an
end.
The local context of implementing QI
We analysed the data to identify locally relevant contextual factors
at each of the PHCs. Major themes that emerged from this analysis
related to the challenge of team-based care and the inability of staff
to make changes within the strong hierarchal arrangement of the
team. Team cohesion and motivation to implement the interventions
also emerged as important themes.
Hierarchical arrangements and team-based care
The doctors are responsible for achieving the target indicators for
their PHC. They have traditionally been placed at the apex of strong
hierarchal arrangements among health professionals in India.
At PHC 1, the doctor did not often seek the opinion of his team
in decision-making regarding the functioning of the PHC. The following quote from the interview with the lab technician illustrates
how the doctor asserts authority and resists suggestions from staff.
It is not possible to give any suggestions to our doctor. You know
our doctor; no, he will not listen to anybody . . . he has repeatedly
told in the past that he is the doctor and I am not the doctor, so I
cannot suggest anything (L1).
Even when the staff had suggestions or wanted to make changes
in their areas of work, they were often not allowed to do so unless
the doctor gave directions.
Change means, whatever Sir says I will do like that, I cannot say,
‘I want to do this (L1).
The doctor at PHC 2 was different in that he sought the opinions
of his staff with regard to managerial decisions.
All of us will discuss first, and if we feel this is correct and we
can bring in the change we will go to Sir and tell him, he will
bring the change (N2b).
The team members, such as the lab technician and pharmacist,
seemed to be able to make changes in their areas of work at the
PHC.
We can do, there is no restriction, we can do, we have to inform
Sir, that we are doing this change and we can do (N2b).
At PHC 3, the doctor did not seek the opinions of all staff equally regarding managerial decisions, as the opinion of the lab technician seemed to be valued more than the others. This may have been
because the lab technician was well-qualified and had worked at the
district hospital previously. Well-qualified staff flattened the hierarchical structure and enabled participation. The lab technician
described how she was able to negotiate change with the doctor by
virtue of being an ‘expert’ in her area of work:
So me and madam [doctor] discussed and decided to have the
ANC clinic on one day and NCD clinic on one day. We decided
to have NCD clinic on Fridays every week and have started this
(L3).
We also observed that staff training and clear responsibilities
empowered them to make decisions and participate in patient care.
The nurse described the initial inhibition to make decisions independently and how this changed after roles were specified:
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9 months
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
ii30
Earlier, we used to say that Madam [doctor] has to write. Only if
Madam writes we do sugar test, we were afraid that we have no
permission to do. Now we have no fear if patients come, we do
the tests (N3a).
Interestingly, counselling had the greatest impact on personal motivation and satisfaction at the PHCs.
At PHC 1, the staff felt that the follow-up was better, as they
now had records for each patient at the PHC.
Team cohesion
The team members had specific roles related to their training, but all
of the teams reported sharing each other’s work if possible and supporting each other, especially during absences due to leave. This was
especially important, as we observed that the teams at all of the
PHCs rarely had all members present on all days, due to leave, deputation for training, or supervisory visits from the district or state
health authorities that demanded their attention.
The team at PHC 1 was the least cohesive of the three. They had
no shared activities in which they participated. The pharmacist, in
particular, was often not involved in the meetings or in causal discussions. However, they did help each other, especially when on
leave, as illustrated by the lab technician:
Very few patients were coming regularly for follow-up visits,
they used to come casually, take tablets and go, but now they
come correctly once in a month (N1b).
We observed the most cohesion between team members at PHC
2. They would wait for each other during the lunch break to eat
together:
Our PHC is like a home, very little time we fight or else we are
all one, especially during lunch time we are all one. I have
worked in several other places, but here is the best, there they
used to be on their own, but here everybody’s work we share and
do (LT2).
We also observed that tasks were redistributed by mutual agreement during the course of implementation when a member
expressed an inability to complete the task due to a lack of time.
At PHC 3, the team was supportive of each other and helped
each other with their work. We observed the team getting together
during their break time on some days. However, the transfer of three
members of the team limited our understanding of cohesion in this
team.
Here they are very supportive, if suppose we have to do FBS, but
I come late, sisters here said no problem we will do it till you
come (LT3).
Motivation and perceived effect of the interventions
At all three PHCs, the staff perceived some changes due to the interventions, resulting in increased motivation among some of the staff.
When we counsel a patient about the dos and don’ts for his diabetes, which they will not be knowing, and they listen to us, we
will feel satisfied (LT 2).
The lab technician at PHC 3 also expressed similar motivation
and satisfaction after counselling patients:
Just doing the tests, anybody can do that, but the counselling I
have done and they have followed my instructions, and they have
made use of it, that gives me a satisfaction that even I have contributed something (LT 3).
The lab technicians at PHC 2 and PHC 3 had volunteered to
complete this task because the nurse did not have time during the
course of implementation. The lab technicians were accepted by
patients and found it fulfilling to participate in this manner.
Comparing the local context and the outcomes of
implementation at the different PHCs
Although the PHCs are similar to respect to their roles, team structure and available infrastructure available, we found differences in
team behaviour that may have affected the way the team came together to implement the interventions. The success of implementation at PHC 2 can be related to relatively more cohesive and
participatory team dynamics. Another significant contextual factor
at PHC 2 was the presence of the CC, which positively influenced
the outcome of the intervention (Table 6).
The CC was able to facilitate the workflow, follow-up with
patients and serve as the focal point for the changes introduced:
If one person is there to coordinate, it is helpful, or else just me
to do everything will be difficult. We have care coordinator so he
is the person and we are monitoring the cards (D2).
From the analysis, it appears that a team leader (medical doctor)
who is willing to include other members of the team in making decisions regarding functioning of the PHC and a cohesive team are
Table 6 Comparison of implementation across PHCs
Success of implementation
oWorkflow
oTask distribution
oRecord
oCHW F/U
Hierarchy within team
Team cohesion
Motivation
Main facilitators
Main barriers
PHC 1
PHC 2
PHC 3
þ
6
þ
6
Doctor’s interest
Time, patient load
1
þ
þ
þ
6
6
þ
þ
CC
Time, patient load
6
6
6
6
6
6
þ
þ
Team interest
Team dispersed
, indicates absence; 6, indicates sometimes present; þ, indicates presence.
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If I am on leave, and I am not available also, they will manage, if
I give some work for them and ask them to do it on my behalf,
and tell them that I am on leave, they will do it, like filling the
details, everybody will support in our staff (LT1).
At PHC 2, the effect of counselling was also a motivating factor,
as illustrated by the lab technician, who was doing the counselling
for patients:
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
important contextual ingredients for the implementation of QIs in
primary care facilities. The presence of a CC who is able to facilitate
the implementation of these changes can also be important.
Discussion
Theoretical reflections
We found the CFIR framework to be a good guide for our study, as
it helped define constructs, such as context and setting. We found
that hierarchical structures influenced team-based care and impacted
implementation related to the inner settings. We confirmed that centralizing or concentrating decision-making negatively impacts implementation. Similarly, team cohesion relates to the construct of social
capital, defined as the quality and extent of relationships within the
organization (Damschroder et al., 2009). The CFIR further proposes
that the bonding between members of the team influences implementation, and we found that this may have been a contributing factor to the relative success of implementation at PHC 2. The MUSIQ
model focuses much more on interactions at the micro level during
implementation processes (Kaplan et al., 2012). The model hypothesizes that the internal ecosystem at each primary care facility is
driven by the leader and directly impacts the implementation outcome. Leadership is an important theme in the MUSIQ model
(Kaplan et al., 2012) and all our findings (hierarchy, team cohesion,
motivation, staff attrition) can be related to leadership at the three
PHCs.
Relevance of the results
Across different settings in primary care, leadership influences day
to day functioning and impacts quality of care. Strong management
and leadership competencies, such as motivating the team, have
been identified as critical to enhancing health system performance
(de Savingy and Taghreed, 2009; Yellappa et al., 2016). Though
leadership and management are theoretically distinct, they overlap
in practice. Leadership is viewed as a process of enabling others to
work, and management as a set of tasks, such as planning, budgeting
and organizing (Daire et al., 2014). It is this view of leadership that
we found lacking, especially at PHC 1. Many studies have shown
that team-based care, in which all members of the team play an integral role in providing patient care, is an effective tool in delivering
high quality patient-centred care (Wen and Schulman, 2014;
Wagner et al., 2017; World Health Organization, 2018). However,
strong enabling leadership is required to facilitate team-based care.
Leadership that is relational, combining a vision and sensitivity
to the views of others, is considered to be more effective in bringing
about QIs (Cleary et al., 2018). Authoritative and hierarchical styles
of leadership are associated with poor staff motivation, inability to
work as a team and poor outcomes for patients (Jackson et al.,
2017). The WHO and the Alliance for Health Systems, in its flagship report, define participatory leadership as the ability to empower
teams and engage communities to achieve better health outcomes
(Report, 2016). This type of participatory leadership needs to be
developed at all levels of the health system, but particularly at the
primary care level and in the context of an LMIC. However, developing leaders that facilitate team-based care is especially challenging
in countries like India, where doctors have traditionally been the
sole providers of care.
Case studies of leadership in primary care in 12 countries have
highlighted the role of training primary care leaders for effective
leadership (Flahault et al., 1986). In the Indian context, training and
sensitization to relational aspects of leadership is an important first
step. These skills are not part of the training in medical school;
therefore, training courses may be one way to create awareness.
Identifying role models and effective mentoring are other ways by
which this capacity can be built over time. This also calls for studies
of the complex interactions of leadership, context and system
change in the Indian context using relevant methods (Gilson and
Agyepong, 2018).
In this study, we experimented with task redistribution among
the team members at primary care level. Redistribution of tasks or
task shifting to members of the team other than the doctor is a viable, cost-effective solution to improving care for persons with
chronic conditions in primary care in LMICs (Joshi et al., 2014;
Seidman and Atun, 2017; World Health Organization, 2018). In
this study, the task of counselling was shifted from being the sole responsibility of the medical doctor to either the nurse or lab technician and the task of reminding patients to attend follow up at the
PHC shifted to the ASHA in the community. While the task of counselling was well taken up by the nurse or lab technician, it proved
difficult for ASHA workers to regularly follow up patients in their
homes. Clearly defined roles and appropriate capacity building are
recommended to enable task shifting (World Health Organization,
2007); in our study, we found this to be crucial in enabling the nurse
or lab technician to counsel patients.
The positive feedback from patients regarding lifestyle advice
received during counselling sessions motivated the nurse and lab
technician to perform this additional task and is likely to have contributed to the relative success of this task shifting arrangement. A
recent study of motivation and job satisfaction of health workers in
Indian PHCs report that training sessions and the opportunity to use
the acquired skills were important factors motivating health workers
(Peters et al., 2010).
The limited ability of ASHAs to follow up patients despite capacity building and clear role descriptions that we observed in this
study, may at least partly be due to the lack of specific financial
incentives. Indeed, ASHAs currently receive incentives from the
Ministry of Health, for each of the health care services they provide,
mainly related to maternal and child care. A recent study that evaluated the training of ASHAs for the control of hypertension also report that the lack of a financial incentive demotivates the ASHA
from incorporating additional tasks into her routine (Abdel-All
et al., 2018).
Recent reviews pertaining to the context of LMIC, support task
sharing and team-based care as a promising way forward to deliver
chronic care at the primary level but also point to the necessity of
supportive supervision (Anand et al., 2019). Regulatory frameworks, enhanced job descriptions and a clear policy framework at
the state level would be required to roll out task shifting at a wider
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We studied the implementation of QI interventions for NCDs at
three public PHCs in rural South India and qualitatively assessed the
implementation processes and outcomes. The three PHCs had different outcomes, as only one of the PHCs was able to make the changes
and were implementing them at the end of 9 months. Comparing the
local context at the three PHCs highlighted the role of hierarchical
arrangements in the team and the lack of a team-based approach,
which could be related to the different implementation outcomes.
We also found that workflow management by a CC, team cohesion
and motivation from feedback positively impacted the implementation process. These findings are not unique to the setting of rural
publicly funded PHCs in India and have been reported in other primary care settings for persons with diabetes and hypertension
(Khatib et al., 2014; Rushforth et al., 2016).
ii31
Health Policy and Planning, 2020, Vol. 35, Suppl. 2
ii32
(Twum-Danso et al., 2012). The findings of our study are in line
with these conclusions and this seems to be a way forward to
achieve QI in LMIC settings.
Delivery of high-quality care is the need of the hour, and requires
continuous QI initiatives with attention to leadership, capacity
building and genuine participation of all stakeholders.
Conclusion
We found that the prevailing hierarchical relationships in primary
care teams in India are a major barrier to team-based care and redistribution of clinical, organizational and managerial tasks at PHC
level. This study draws attention to the need for building capacity
and leadership to enable better implementation of public health programmes. Further research regarding the development of QI teams,
testing QI intervention packages and studying organizational behaviour at primary care settings in India, is required to strengthen the
delivery of primary health care for people with chronic NCDs.
Funding
The research was supported by the Institute of Tropical Medicine, Antwerp,
through a PhD scholarship to the first author. This article is part of the supplement ‘Innovations in Implementation Research in Low- and MiddleIncome Countries’, a collaboration of the Alliance for Health Policy and
Systems Research and Health Policy and Planning. The supplement and this
article were produced with financial support from the Alliance for Health
Policy and Systems Research. The Alliance is able to conduct its work thanks
to the commitment and support from a variety of funders. These include our
long-term core contributors from national governments and international
institutions, as well as designated funding for specific projects within our current priorities. For the full list of Alliance donors, please visit: https://www.
who.int/alliance-hpsr/partners/en/.
Supplementary data
Supplementary data are available at Health Policy and Planning online.
Conflict of interest statement. None declared.
Ethical approval. The study received ethical approval from the ethics committees of the Institute of Tropical Medicine, Antwerp (ref 1186/17), the
University of Antwerp (ref 17/47/527) and the Institute of Public Health,
Bengaluru (ref IEC-FR/02/2017). We also obtained permission from the State
Ministry of Health and the Kolar District Health Office to conduct this
research.
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Health Policy and Planning, 2020, Vol. 35, Suppl. 2