Diagnostic and clinical decision support systems for antenatal care: is mHealth the future in low-resource settings?
Abejirinde, I.O.
2018
document version
Publisher's PDF, also known as Version of record
Link to publication in VU Research Portal
citation for published version (APA)
Abejirinde, I. O. (2018). Diagnostic and clinical decision support systems for antenatal care: is mHealth the future in low-resource settings?.
General rights
Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ?
Take down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
E-mail address:
vuresearchportal.ub@vu.nl
1 Usability Questionnaire
2 Search Strategy, Scoping Review
3 Search strategy for different databases, Scoping Review
4 Detailed profile of reviewed studies
5 Review Terms, Search Strategy and Exclusion Criteria, Realist Review
6 Realist review: Framework in progress
7 Data collection activities and Respondents
8 Facility checklist for ANC service provision
9 Characteristics of B4M users and Usability survey scores
10 Question Guide Client Exit Interviews
11 Question Guide In-depth Interviews, Bliss4Midwives (B4M)
users
Disagree Neither Agree
STATEMENT -2 -1 0 +1 +2
1 I think using B4M has made me more effective in my job.
(Probe: In what aspects of your job are you now more effective? Do you think it is the device that caused that?) 2 I think using B4M made it possible for me to attend to
conduct ANC quickly.
(Probe: Is it important to you that you can quickly attend to clients? Why?)
3 Using B4M increased my workload
(Probe: How? All the time or only sometimes?) 4 With B4M, I am now able to do more things
(Probe: i.e. productivity. In what way? e.g. see more women, conduct tests and diagnose immediately, keep patient records easily. Do you feel you were less productive without B4M??)
5 With B4M I am now able to test patients properly for Anaemia, Pre-Eclampsia and Gestational Diabetes (Probe: How did women get tested for PE, Anaemia &
GDm before?)
6 It is easier to do ANC consultations now that I use B4M (Probe: What aspect of ANC services did you find difficult when you were not using B4M? Which part of B4M do you feel makes your work easier- px history, diagnosis, risk classification or px counselling?)
7 I think more pregnant women are coming for ANC now that we use B4M in the Health Facility
(Probe: Why do you think women were not coming for ANC before? How do you feel B4M solves that problem?) 8 I think that the pregnant women follow my advice more
now that I use B4M for consultation.
(Probe: Why do you think they comply more now?)
Date of Interview ………... Location ………...……… Interviewer Initials .………...…...
Health Facility: Name ………...……….. District ….……...………...
Initials of Midwife/CHN …………...…....………. Assigned Project Code .……...……….
Confirmation of Consent:(Yes/No) ...….………. Type of Consent: (Verbal/Written) …...…....………
Appendix 1 - Usability Questionnaire
BLISS4MIDWIVES (B4M): QUESTIONNAIRE ON PERCEIVED USEFULNESS
& EASE OF USE
(Bring out printed color-coded sheet for likert scale and explain the colors to respondent. Ask respondent to point to which square/color applies for each statement that you make. Tick the appropriate box in the survey sheet.
Following responses, probe further before moving to the next question)
A
Disagree Neither Agree
STATEMENT -2 -1 0 +1 +2
9 I do not trust the diagnosis that I get from the B4M device.
(Probe: Why do you trust the diagnosis? What type of tests would you prefer?)
10 It is now easier for me to refer women that I identify as being at risk for Anaemia, Pre-Eclampsia and Gestational Diabetes.
(Probe: Was this a difficulty in the past? In what way?) 11 I am not satisfied with using B4M for ANC consultations 12 Using B4M improves my performance as a Health care
worker
(Probe: Can you give an example of when you felt your performance improved?)
13 Operating the B4M system is easy for me
(Probe: What aspects of the device do your find difficult (e.g. typing, using the diagnostic sets, reading the traffic lights etc.))
14 The system is too complex for me to use
(Probe: Are there any parts that you find easy or the entire system is complex?)
15 I am confident in my ability to use B4M
(Probe: Do you think you are able to teach a new member of staff that has not been trained on how to use it?) 16 I think I need more training on how to use B4M
(Probe: Do you want training on every aspect of the system or just some specific things?)
17 I like the traffic light signalling function of the decision- support
(Probe: Show picture of the traffic lights. Ask midwife to tell you what the colours mean. What exactly does she like (or not like) about the lights function?)
18 The results and recommendations of the B4M confuses me (Probe: Can you remember a time when the system confused you? Give specific example.)
19 I find it easy to update information in the patients file using B4M
20 It is difficult for me to do the Haemoglobin test using B4M 21 It is easy for me to take blood pressure using B4M 22 The urine glucose and protein tests are easy for me to do 23 I usually need someone to assist me when I want to use
the B4M system
(Probe: Who usually assists you when you need help?) 24 It is easier for me to use the usual system of ANC than
with B4M
(Probe: What (if any) are the advantages of the standard system in your opinion?)
25 What is the most positive aspect(s) of using B4M?
(audio recorded)
26 What is the most negative aspect(s) of using B4M? (audio recorded)
Return to section 7 of the interview guide
Appendix 2 - Search Strategy, Scoping Review Concept Syntax
mobile health
Telemedicine[mh] OR telenursing[mh] OR User-Computer Interface[mh] OR cell phones[mh] OR public health informatics[mh] OR medical informatics[mh] OR nursing informatics[mh] OR computers, handheld[mh] OR internet[mh] OR Mobile Applications[mh] OR mobile health*[tiab] OR mHealth*[tiab] OR m-health*[tiab] OR ehealth*[tiab] OR e-health*[tiab] OR mobile health[tiab] OR digital health[tiab] OR app[tiab] OR apps[tiab] OR smartphone*[tiab] OR phone application[tiab] OR phone applications[tiab] OR cellphone application[tiab] OR cellphone applications[tiab]
OR telephone application[tiab] OR telephone applications[tiab] OR mobile application[tiab] OR mobile applications[tiab] OR mobile technolog*[tiab] OR health technolog*[tiab] OR health application[tiab] OR health applications[tiab] OR internet[tiab] OR iPad[tiab] OR sms[tiab] OR text messag*[tiab] OR USSD[tiab] OR pda[tiab] OR laptop*[tiab] OR palmtop*[tiab] OR palm-top*[tiab] OR Personal Digital Assistant*[tiab] OR computer*[tiab] OR cell phone*[tiab] OR cellular phone*[tiab]
OR smart phone*[tiab]
Decision- making
OR
Quality of care
Decision-making[mh] OR decision-making, computer-assisted[mh] OR evidence-based medicine[mh] OR evidence-based nursing[mh] OR decision support techniques[mh] OR decision support systems, clinical[mh] OR guideline adherence[mh] OR health care quality, access, and evaluation[mh] OR quality of health care[mh] OR workflow[mh] OR patient care[mh] OR delivery of health care[mh] OR health services[mh] OR patient care management[mh] OR decision- making[tiab] OR decision support[tiab] OR Evidence-based[tiab] OR decision aid*[tiab] OR guideline*[tiab] OR decision process*[tiab] OR decision tool*[tiab]
OR health service*[tiab] OR health care quality[tiab] OR healthcare quality[tiab] OR health outcome*[tiab] OR quality of health[tiab] OR quality of care[tiab] OR quality care[tiab] OR competen*[tiab] OR best practic*[tiab] OR patient care[tiab]
Health care workers
Health personnel[mh] OR nurse[tiab] OR nurses[tiab] OR physician[tiab] OR physicians[tiab] OR health provider[tiab] OR health providers[tiab] OR health care provider[tiab] OR health care providers[tiab] OR healthcare provider[tiab]
OR healthcare providers[tiab] OR health worker[tiab] OR health workers[tiab]
OR midwife[tiab] OR midwives[tiab] OR health care worker[tiab] OR health care workers[tiab] OR healthcare worker[tiab] OR healthcare workers[tiab]
OR community health worker[tiab] OR community health workers[tiab] OR practitioner[tiab] OR practitioners[tiab] OR clinician[tiab] OR clinicians[tiab] OR doctor[tiab] OR doctors[tiab] OR clinical officer[tiab] OR clinical officers[tiab] OR medical personnel[tiab] OR health professional[tiab] OR health professionals[tiab]
OR frontline provider[tiab] OR frontline providers[tiab] OR frontline worker[tiab] OR frontline workers[tiab] OR traditional birth attend*[tiab] OR front line provider*[tiab]
OR front line worker*[tiab]
Africa Africa[mh] OR africa[tiab] OR Cameroon[tiab] OR Central African Republic[tiab] OR Chad[tiab] OR Congo[tiab] OR Democratic Republic of the Congo[tiab] OR Equatorial Guinea[tiab] OR Gabon[tiab] OR Burundi[tiab] OR Djibouti[tiab] OR Eritrea[tiab] OR Ethiopia[tiab] OR Kenya[tiab] OR Rwanda[tiab] OR Somalia[tiab] OR Sudan[tiab] OR Tanzania[tiab] OR Burundi[tiab] OR Djibouti[tiab] OR Uganda[tiab] OR Angola[tiab]
OR Botswana[tiab] OR Lesotho[tiab] OR Malawi[tiab] OR Mozambique[tiab]
OR Namibia[tiab] OR South Africa[tiab] OR Swaziland[tiab] OR Zambia[tiab] OR Zimbabwe[tiab] OR Benin[tiab] OR Burkina Faso[tiab] OR Cape Verde[tiab] OR Ivory Coast[tiab] OR Cote d’Ivoire[tiab] OR Gambia[tiab] OR Ghana[tiab] OR Guinea[tiab]
OR Guinea-Bissau[tiab] OR Liberia[tiab] OR Mali[tiab] OR Mauritania[tiab] OR Niger[tiab] OR Nigeria[tiab] OR Senegal[tiab] OR Sierra Leone[tiab] OR Togo[tiab]
OR Algeria[tiab] OR Egypt[tiab] OR Libya[tiab] OR Morocco[tiab] OR Tunisia[tiab]
A
Appendix 3 - Search strategy for different databases, Scoping Review PubMed (25
thDecember 2015)
Search Query
#6 Search #1 AND #2 AND #3 AND #4 Sort by: Relevance Filters: English
#5 Search #1 AND #2 AND #3 AND #4
#4 Search (Africa[mh] OR africa[tiab] OR Cameroon[tiab] OR Central African Republic[tiab]
OR Chad[tiab] OR Congo[tiab] OR Democratic Republic of the Congo[tiab] OR Equatorial Guinea[tiab] OR Gabon[tiab] OR Burundi[tiab] OR Djibouti[tiab] OR Eritrea[tiab] OR Ethiopia[tiab] OR Kenya[tiab] OR Rwanda[tiab] OR Somalia[tiab] OR Sudan[tiab] OR Tanzania[tiab] OR Burundi[tiab] OR Djibouti[tiab] OR Uganda[tiab] OR Angola[tiab] OR Botswana[tiab] OR Lesotho[tiab] OR Malawi[tiab] OR Mozambique[tiab]
OR Namibia[tiab] OR South Africa[tiab] OR Swaziland[tiab] OR Zambia[tiab] OR Zimbabwe[tiab] OR Benin[tiab] OR Burkina Faso[tiab] OR Cape Verde[tiab] OR Ivory Coast[tiab] OR Cote d’Ivoire[tiab] OR Gambia[tiab] OR Ghana[tiab] OR Guinea[tiab] OR Guinea-Bissau[tiab] OR Liberia[tiab] OR Mali[tiab] OR Mauritania[tiab] OR Niger[tiab] OR Nigeria[tiab] OR Senegal[tiab] OR Sierra Leone[tiab] OR Togo[tiab] OR Algeria[tiab] OR Egypt[tiab] OR Libya[tiab] OR Morocco[tiab] OR Tunisia[tiab])
#3 Search (Health personnel[mh] OR nurse[tiab] OR nurses[tiab] OR physician[tiab]
OR physicians[tiab] OR health provider[tiab] OR health providers[tiab] OR health care provider[tiab] OR health care providers[tiab] OR healthcare provider[tiab]
OR healthcare providers[tiab] OR health worker[tiab] OR health workers[tiab]
OR midwife[tiab] OR midwives[tiab] OR health care worker[tiab] OR health care workers[tiab] OR healthcare worker[tiab] OR healthcare workers[tiab] OR community health worker[tiab] OR community health workers[tiab] OR practitioner[tiab] OR practitioners[tiab] OR clinician[tiab] OR clinicians[tiab] OR doctor[tiab] OR doctors[tiab]
OR clinical officer[tiab] OR clinical officers[tiab] OR medical personnel[tiab] OR health professional[tiab] OR health professionals[tiab] OR frontline provider[tiab] OR frontline providers[tiab] OR frontline worker[tiab] OR frontline workers[tiab] OR traditional birth attend*[tiab] OR front line provider*[tiab] OR front line worker*[tiab])
#2 Search (Decision Making[mh] OR decision making, computer-assisted[mh] OR evidence-based medicine[mh] OR evidence-based nursing[mh] OR decision support techniques[mh] OR decision support systems, clinical[mh] OR guideline adherence[mh]
OR health care quality, access, and evaluation[mh] OR quality of health care[mh]
OR workflow[mh] OR patient care[mh] OR delivery of health care[mh] OR health services[mh] OR patient care management[mh] OR decision making[tiab] OR decision support[tiab] OR Evidence-based[tiab] OR decision aid*[tiab] OR guideline*[tiab] OR decision process*[tiab] OR decision tool*[tiab] OR health service*[tiab] OR health care quality[tiab] OR healthcare quality[tiab] OR health outcome*[tiab] OR quality of health[tiab] OR quality of care[tiab] OR quality care[tiab] OR competen*[tiab] OR best practic*[tiab] OR patient care[tiab])
#1 Search (Telemedicine[mh] OR telenursing[mh] OR User-Computer Interface[mh] OR cell phones[mh] OR public health informatics[mh] OR medical informatics[mh] OR nursing informatics[mh] OR computers, handheld[mh] OR internet[mh] OR Mobile Applications[mh] OR mobile health*[tiab] OR mhealth*[tiab] OR m-health*[tiab] OR ehealth*[tiab] OR e-health*[tiab] OR mobile health[tiab] OR digital health[tiab] OR app[tiab] OR apps[tiab] OR smartphone*[tiab] OR phone application[tiab] OR phone applications[tiab] OR cellphone application[tiab] OR cellphone applications[tiab] OR telephone application[tiab] OR telephone applications[tiab] OR mobile application[tiab]
OR mobile applications[tiab] OR mobile technolog*[tiab] OR health technolog*[tiab]
OR health application[tiab] OR health applications[tiab] OR internet[tiab] OR iPad[tiab]
OR sms[tiab] OR text messag*[tiab] OR USSD[tiab] OR pda[tiab] OR laptop*[tiab]
OR palmtop*[tiab] OR palm-top*[tiab] OR Personal Digital Assistant*[tiab] OR
computer*[tiab] OR cell phone*[tiab] OR cellular phone*[tiab] OR smart phone*[tiab])
A
Cochrane (24th December 2015) Search Query
#1 MeSH descriptor: [Telemedicine] explode all tress
#2 MeSH descriptor: [Telenursing] explode all trees
#3 MeSH descriptor: [User-Computer Interface] explode all tress
#4 MeSH descriptor: [Cell Phones] explode all tress
#5 MeSH descriptor: [Public Health Informatics] explode all tress
#6 MeSH descriptor: [Medical Informatics] explode all tress
#7 MeSH descriptor: [Nursing Informatics] explode all tress
#7 MeSH descriptor: [Computers, Handheld] explode all tress
#9 MeSH descriptor: [Internet] explode all tress
#10 MeSH descriptor: [Mobile Applications] explode all tress
#11 #1 or #2 or #3 or #4 or #5 or #6 or #7 or #8 or #9 or #10
#12 (#11) or (“mobile health*” or mhealth* or “m-health*” or ehealth* or “e-health*” or “digital health”
or app or apps or smartphone* or “phone application” or “phone applications” or “cellphone application” or “cellphone applications” or “telephone application” or “telephone applications” or
“mobile application” or “mobile applications” or “mobile technolog*” or “health technolog*” or
“health application” or “health applications” or internet or iPad or sms or “text messag*” or USSD or pda or laptop* or palmtop* or “palm-top*” or “Personal Digital Assistant*” or computer* or “cell phone*” or “cellular phone*” or “smart phone*”):ab,ti,kw
#13 MeSH descriptor: [Africa] explode all tress
#14 (#13) or (Africa or Cameroon or “Central African Republic” or Chad or Congo or “Equatorial Guinea” or Gabon or Burundi or Djibouti or Eritrea or Ethiopia or Kenya or Rwanda or Somalia or Sudan or Tanzania or Burundi or Djibouti or Uganda or Angola or Botswana or Lesotho or Malawi or Mozambique or Namibia or “South Africa” or Swaziland or Zambia or Zimbabwe or Benin or
“Burkina Faso” or “Cape Verde” or “Ivory Coast” or “Cote d’Ivoire” or Gambia or Ghana or Guinea or “Guinea-Bissau” or Liberia or Mali or Mauritania or Niger or Nigeria or Senegal or “Sierra Leone”
or Togo or Algeria or Egypt or Libya or Morocco or Tunisia):ab,ti,kw
#15 MeSH descriptor: [Health Personnel] explode all trees
#16 (#15) or (nurse or nurses or physician or physicians or “health provider” or “health providers” or
“health care provider” or “health care providers” or “healthcare provider” or “healthcare providers”
or “health worker” or “health workers” or midwife or midwives or “health care worker” or “health care workers” or “healthcare worker” or “healthcare workers” or “community health worker” or
“community health workers” or practitioner or practitioners or clinician or clinicians or doctor or doctors or “clinical officer” or “clinical officers” or “medical personnel” or “health professional” or
“health professionals” or “frontline provider” or “frontline providers” or “frontline worker” or “frontline workers” or “traditional birth attend*” or “front line provider*” or “front line worker*”):ab,ti,kw
#17 MeSH descriptor: [Decision Making] explode all trees
#18 MeSH descriptor: [Evidence-Based Medicine] explode all trees
#19 MeSH descriptor: [Decision Making, Computer-Assisted] explode all trees
#20 MeSH descriptor: [Evidence-Based Nursing] explode all trees
#21 MeSH descriptor: [Decision Support Techniques] explode all trees
#22 MeSH descriptor: [Decision Support Systems, Clinical] explode all trees
#23 MeSH descriptor: [Guideline Adherence] explode all trees
#24 MeSH descriptor: [Health Care Quality, Access, and Evaluation] explode all trees
#25 MeSH descriptor: [Workflow] explode all trees
#26 MeSH descriptor: [Patient Care] explode all trees
#27 MeSH descriptor: [Health Services] explode all trees
#28 MeSH descriptor: [Patient Care Management] explode all trees
#29 #17 or #18 or #19 or #20 or #21 or #22 or #23 or #24 or #25 or #26 or #27 or #28
#30 (#29) or (“decision making” or “decision support” or “Evidence-based” or “decision aid*” or guideline*
or “decision process*” or “decision tool*” or “health service*” or “health care quality” or “healthcare quality” or “health outcome*” or “quality of health” or “quality of care” or “quality care” or competen*
or “best practic*” or “patient care”):ab,ti,kw
#31 #12 and #30 and #16 and #14
Web of Science Core Collection (24th December 2015) Search Query
# 6 (#1 AND #2 AND #3 AND #4) AND LANGUAGE: (English) Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
# 5 #1 AND #2 AND #3 AND #4
Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
# 4 TS=(Africa or Cameroon or “Central African Republic” or Chad or Congo or “Equatorial Guinea” or Gabon or Burundi or Djibouti or Eritrea or Ethiopia or Kenya or Rwanda or Somalia or Sudan or Tanzania or Burundi or Djibouti or Uganda or Angola or Botswana or Lesotho or Malawi or Mozambique or Namibia or “South Africa” or Swaziland or Zambia or Zimbabwe or Benin or “Burkina Faso” or “Cape Verde” or “Ivory Coast” or
“Cote d’Ivoire” or Gambia or Ghana or Guinea or “Guinea-Bissau” or Liberia or Mali or Mauritania or Niger or Nigeria or Senegal or “Sierra Leone” or Togo or Algeria or Egypt or Libya or Morocco or Tunisia)
Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
# 3 TS=(nurse or nurses or physician or physicians or “health provider” or “health providers” or “health care provider” or “health care providers” or “healthcare provider”
or “healthcare providers” or “health worker” or “health workers” or midwife or midwives or “health care worker” or “health care workers” or “healthcare worker” or
“healthcare workers” or “community health worker” or “community health workers” or practitioner or practitioners or clinician or clinicians or doctor or doctors or “clinical officer” or “clinical officers” or “medical personnel” or “health professional” or “health professionals” or “frontline provider” or “frontline providers” or “frontline worker” or
“frontline workers” or “traditional birth attend*” or “front line provider*” or “front line worker*”)
Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
# 2 TS=(decision making or decision support or Evidence based or “decision aid*” or guideline* or “decision process*” or “decision tool*” or “health service*” or “health care quality” or “healthcare quality” or “health outcome*” or “quality of health” or
“quality of care” or “quality care” or competen* or “best practic*” or “patient care”) Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
# 1 TS=(“mobile health*” or mhealth* or “m-health*” or ehealth* or “e-health*” or “digital health” or app or apps or smartphone* or “phone application” or “phone applications”
or “cellphone application” or “cellphone applications” or “telephone application” or
“telephone applications” or “mobile application” or “mobile applications” or “mobile technolog*” or “health technolog*” or “health application” or “health applications” or internet or iPad or sms or “text messag*” or USSD or pda or laptop* or palmtop* or
“palm-top*” or “Personal Digital Assistant*” or computer* or “cell phone*” or “cellular phone*” or “smart phone*”)
Indexes=SCI-EXPANDED, SSCI, A&HCI, ESCI Timespan=All years
A
CINAHL (24th December 2015) Search Query
S5 S1 AND S2 AND S3 AND S4 (English Language)
S4 (MH “Africa+”) OR TI (Africa or Cameroon or “Central African Republic” or Chad or Congo or
“Equatorial Guinea” or Gabon or Burundi or Djibouti or Eritrea or Ethiopia or Kenya or Rwanda or Somalia or Sudan or Tanzania or Burundi or Djibouti or Uganda or Angola or Botswana or Lesotho or Malawi or Mozambique or Namibia or “South Africa” or Swaziland or Zambia or Zimbabwe or Benin or “Burkina Faso” or “Cape Verde” or “Ivory Coast” or “Cote d’Ivoire” or Gambia or Ghana or Guinea or “Guinea-Bissau” or Liberia or Mali or Mauritania or Niger or Nigeria or Senegal or “Sierra Leone”
or Togo or Algeria or Egypt or Libya or Morocco or Tunisia) OR AB (Africa or Cameroon or “Central African Republic” or Chad or Congo or “Equatorial Guinea” or Gabon or Burundi or Djibouti or Eritrea or Ethiopia or Kenya or Rwanda or Somalia or Sudan or Tanzania or Burundi or Djibouti or Uganda or Angola or Botswana or Lesotho or Malawi or Mozambique or Namibia or “South Africa” or Swaziland or Zambia or Zimbabwe or Benin or “Burkina Faso” or “Cape Verde” or “Ivory Coast” or “Cote d’Ivoire”
or Gambia or Ghana or Guinea or “Guinea-Bissau” or Liberia or Mali or Mauritania or Niger or Nigeria or Senegal or “Sierra Leone” or Togo or Algeria or Egypt or Libya or Morocco or Tunisia)
S3 (MH “Health Personnel+”) OR TI (nurse or nurses or physician or physicians or “health provider”
or “health providers” or “health care provider” or “health care providers” or “healthcare provider”
or “healthcare providers” or “health worker” or “health workers” or midwife or midwives or “health care worker” or “health care workers” or “healthcare worker” or “healthcare workers” or “community health worker” or “community health workers” or practitioner or practitioners or clinician or clinicians or doctor or doctors or “clinical officer” or “clinical officers” or “medical personnel” or “health professional” or “health professionals” or “frontline provider” or “frontline providers” or “frontline worker” or “frontline workers” or “traditional birth attend*” or “front line provider*” or “front line worker*”) OR AB (nurse or nurses or physician or physicians or “health provider” or “health providers”
or “health care provider” or “health care providers” or “healthcare provider” or “healthcare providers”
or “health worker” or “health workers” or midwife or midwives or “health care worker” or “health care workers” or “healthcare worker” or “healthcare workers” or “community health worker” or
“community health workers” or practitioner or practitioners or clinician or clinicians or doctor or doctors or “clinical officer” or “clinical officers” or “medical personnel” or “health professional” or
“health professionals” or “frontline provider” or “frontline providers” or “frontline worker” or “frontline workers” or “traditional birth attend*” or “front line provider*” or “front line worker*”)
S2 (MH “Decision Making+”) OR (MH “Professional Practice, Evidence-Based+”) OR (MH “Decision Support Techniques+”) OR (MH “Decision Support Systems, Clinical”) OR (MH “Guideline Adherence”) OR (MH “Quality of Health Care+”) OR (MH “Patient Care+”) OR (MH “Health Care Delivery+”) OR (MH
“Health Services+”) OR (MH “Patient Care Plans+”) OR TI (“decision making” OR “decision support”
OR “Evidence-based” OR “decision aid*” OR guideline* OR “decision process*” OR “decision tool*”
OR “health service*” OR “health care quality” OR “healthcare quality” OR “health outcome*” OR
“quality of health” OR “quality of care” OR “quality care” OR competen* OR “best practic*” OR “patient care”) OR AB (“decision making” OR “decision support” OR “Evidence-based” OR “decision aid*” OR guideline* OR “decision process*” OR “decision tool*” OR “health service*” OR “health care quality”
OR “healthcare quality” OR “health outcome*” OR “quality of health” OR “quality of care” OR “quality care” OR competen* OR “best practic*” OR “patient care”)
S1 (MH “Telemedicine+”) OR (MH “User-Computer Interface+”) OR (MH “Cellular Phone+”) OR (MH
“Health Informatics+”) OR (MH “Computers, Hand-Held+”) OR (MH “Internet+”) OR (MH “Mobile Applications”) OR TI (“mobile health*” OR mhealth* OR “m-health*” OR ehealth* OR “e-health*” OR
“digital health” OR app OR apps OR smartphone* OR “phone application” OR “phone applications”
OR “cellphone application” OR “cellphone applications” OR “telephone application” OR “telephone applications” OR “mobile application” OR “mobile applications” OR “mobile technolog*” OR “health technolog*” OR “health application” OR “health applications” OR internet OR iPad OR sms OR
“text messag*” OR USSD OR pda OR laptop* OR palmtop* OR “palm-top*” OR “Personal Digital Assistant*” OR computer* OR “cell phone*” OR “cellular phone*” OR “smart phone*”) OR AB (“mobile health*” OR mhealth* OR “m-health*” OR ehealth* OR “e-health*” OR “digital health” OR app OR apps OR smartphone* OR “phone application” OR “phone applications” OR “cellphone application”
OR “cellphone applications” OR “telephone application” OR “telephone applications” OR “mobile application” OR “mobile applications” OR “mobile technolog*” OR “health technolog*” OR “health application” OR “health applications” OR internet OR iPad OR sms OR “text messag*” OR USSD OR pda OR laptop* OR palmtop* OR “palm-top*” OR “Personal Digital Assistant*” OR computer* OR
“cell phone*” OR “cellular phone*” OR “smart phone*”)
mHealth Evidence Knowledge 4 Health Database (24th December 2015)
Search String: “decision support” followed by manually combining “decision
support” and Tunisia (or Africa or Botswana i.e. country name or continent
name) individually for all 60 possibilities.
Appendix 4 - Detailed profile of reviewed studies
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
m4Change ANCa McNabb et al (2015) [25]
1
Quantitative pre/post- study
1 Nigeria
Maternal Health CHEW/HCWs
• Mobile phone and Tablet
• Guided decision support with algorithms for ANC and client data for registration and tracking
• Health education audio clips for client counselling
• Local language support
• Offline functionality
• Password protected
• Pre/Post study involving 152 CHEWs/HCWs and 20 supervisors in 10PHCs
• Health facility surveys, client exit interviews, monitoring reports and quality score assessment
• 1 year intervention period
• Effect on quality of ANC services
• Effect on client satisfaction
• Generally, quality score improved significantly by about 4 points (from 13.3 at baseline to 17.2 at endline)
• Not all specific elements of the score significantly improved
• Client satisfaction with ANC services significantly improved at end line.
DESIRE (Decision Support and Integrated Record- keeping) Vedanthan et al (2015) [26]
1 Qualitative usability / feasibility study
1 Kenya
Hypertension Nurses and Clinical Officers
• Tablet-based patient-specific clinical decision-support tool with branching logic algorithm, alerts and reminders
• Integrated with patient data and linked to a central medical records system
• Offline functionality
• Data security through user-authentication, automatic timeouts, encryption and secure transmission system
• Iterative usability and feasibility assessments involving 5 nurses using human-centred design.
• Think aloud exercises, mock patient encounters, focus group discussions and semi- structured interviews
• 4 months
• Identification of barriers and facilitators to implementing the DESIRE tool
• Technical and human barriers to implementation were identified.
• Feasibility themes included facilitators to implementation, provider or patient issues and additional feature requests
• Twenty-one unique critical incidents identified in usability testing.
CommCare Svoronos et al (2010) [27]
1 Qualitative and descriptive
1 Tanzania
Maternal Health CHWs
• Phone-based CommCare application including user- controlled guided decision support tool, checklist and follow-up reminders for quality improvement
• Use of patient data for referral support and monitoring
• Supervisory feedback and report-generation
• Offline functionality
• Password protected
• Iterative and participatory pilot study involving 5 CHWs
• Meetings, observation studies and focus group discussions
• 4 months
• Develop CommCare
module • Application was well received by CHWs and found to improve and standardize service delivery (identification, follow-up and referral)
• Ease and comfort of use reported after some training
• Use of tool declined post-implementation
mPneumonia Ginsburg et al (2015) [28]
1 Mixed methods usability &
feasibility testing
1 Ghana
Childhood Illnesses Lesser trained health care professionals
• Tablet-based tool with IMCI algorithm and decision- making protocol
• Coupled with “intelligent” electronic breath counter and paediatric pulse oximeter with visual, auditory, and vibratory feedback
• Offline functionality
• English language support
• Password protected
• Feasibility, usability and acceptability study involving 5 HCWs and one technician.
• Iterative design process
• No pre-study training of target users
• Qualitative and quantitative data collected through task-analysis, think-aloud exercises, interviews and usability rating.
• Design and development of mPneumonia to improve diagnostic accuracy and facilitate guideline adherence by HCWs.
• HCWs positively responded to the mCDSS and found it innovative and easy.
• HCWs preferred it to standard (paper) practice, anticipating accurate and easier care management
• Concerns about maintenance and theft
• Identified 17 critical and 9 noncritical usability issues
• Increased ease of use with repetition
• Suggested at least 2 days (16.3hours) of training
Bacis (Basic Antenatal Care Information System) Horner et al (2013) [29]
1 Before and after cohort study
1 South Africa
Maternal Health Nurses
• Electronic patient information system with clinical decision support for maternal health via protocols, checklists, and a rule and knowledge base with alerts and reminders
• Supports patient data entry for classification, follow-up and referral, with validation and completeness checks
• Utility assessment
• Before and after study to assess compliance to guidelines using two study cohorts
• Data collection via record reviews and interviews
• 2 years (development, implementation, evaluation)
• Usability and acceptability review of Bacis
• Compliance (i.e. completion and response) performance for maternity care protocols and the antenatal care checklist
• Improved compliance from 85% to 89% although not statistically significant
• Out of nine specific categories for measuring compliance, three (compliance at booking, patients
<18 years & booking patients after week 20) showed statistically significant results compared to standard practice using paper
• Better suited for younger computer literate workers
TB Tech Catalani et al (2014) [30]
1 Mixed methods human- centred design
1 Kenya
Tuberculosis
& HIV Clinicians
• Patient-specific clinical decision support for provider action, education and behaviour change.
• Integrates existing paper-based processes with an electronic medical record.
• Supported with educational and motivational information for HCW
• Additional intervention inputs including facility upgrades with staffing and hardware, supply chain management and provision of mobile radiology units and educational campaign for providers
• Qualitative (observation visits, interviews) and quantitative (usability survey and laboratory stimulation).
• Lab simulation involved mock patients
• Iterative prototype development using human- centred design
• Develop, design and pilot test TBTech using a human-centred design approach
• Positive disposition of clinicians to medical record and decision support system –Concerns regarding accuracy and actionability of recommendations
• Health system challenges such as unavailability of tests, low staffing and supplies resulted in delayed action and some unactionable recommendations.
txt2MEDLINE Armstrong et al (2012) [31]
1 Pre-Post utility evaluation
1 Botswana
Multiple domains Clinicians of varying cadres
• Mobile phone-based two-way Short Messaging Service (SMS) of clinical guidelines, with MEDLINE/PubMed query function.
• 76 HCWs used and evaluated system.
• Pre-usage survey was followed by training
• Post-intervention data acquired through a mixed questions survey
• One-month
• Usability and usefulness
of intervention • Although pre-intervention study recorded high
intention to use, this declined during the one-month
trial
A
Appendix 4 - Detailed profile of reviewed studies
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
m4Change ANCa McNabb et al (2015) [25]
1
Quantitative pre/post- study
1 Nigeria
Maternal Health CHEW/HCWs
• Mobile phone and Tablet
• Guided decision support with algorithms for ANC and client data for registration and tracking
• Health education audio clips for client counselling
• Local language support
• Offline functionality
• Password protected
• Pre/Post study involving 152 CHEWs/HCWs and 20 supervisors in 10PHCs
• Health facility surveys, client exit interviews, monitoring reports and quality score assessment
• 1 year intervention period
• Effect on quality of ANC services
• Effect on client satisfaction
• Generally, quality score improved significantly by about 4 points (from 13.3 at baseline to 17.2 at endline)
• Not all specific elements of the score significantly improved
• Client satisfaction with ANC services significantly improved at end line.
DESIRE (Decision Support and Integrated Record- keeping) Vedanthan et al (2015) [26]
1 Qualitative usability / feasibility study
1 Kenya
Hypertension Nurses and Clinical Officers
• Tablet-based patient-specific clinical decision-support tool with branching logic algorithm, alerts and reminders
• Integrated with patient data and linked to a central medical records system
• Offline functionality
• Data security through user-authentication, automatic timeouts, encryption and secure transmission system
• Iterative usability and feasibility assessments involving 5 nurses using human-centred design.
• Think aloud exercises, mock patient encounters, focus group discussions and semi- structured interviews
• 4 months
• Identification of barriers and facilitators to implementing the DESIRE tool
• Technical and human barriers to implementation were identified.
• Feasibility themes included facilitators to implementation, provider or patient issues and additional feature requests
• Twenty-one unique critical incidents identified in usability testing.
CommCare Svoronos et al (2010) [27]
1 Qualitative and descriptive
1 Tanzania
Maternal Health CHWs
• Phone-based CommCare application including user- controlled guided decision support tool, checklist and follow-up reminders for quality improvement
• Use of patient data for referral support and monitoring
• Supervisory feedback and report-generation
• Offline functionality
• Password protected
• Iterative and participatory pilot study involving 5 CHWs
• Meetings, observation studies and focus group discussions
• 4 months
• Develop CommCare
module • Application was well received by CHWs and found to improve and standardize service delivery (identification, follow-up and referral)
• Ease and comfort of use reported after some training
• Use of tool declined post-implementation
mPneumonia Ginsburg et al (2015) [28]
1 Mixed methods usability &
feasibility testing
1 Ghana
Childhood Illnesses Lesser trained health care professionals
• Tablet-based tool with IMCI algorithm and decision- making protocol
• Coupled with “intelligent” electronic breath counter and paediatric pulse oximeter with visual, auditory, and vibratory feedback
• Offline functionality
• English language support
• Password protected
• Feasibility, usability and acceptability study involving 5 HCWs and one technician.
• Iterative design process
• No pre-study training of target users
• Qualitative and quantitative data collected through task-analysis, think-aloud exercises, interviews and usability rating.
• Design and development of mPneumonia to improve diagnostic accuracy and facilitate guideline adherence by HCWs.
• HCWs positively responded to the mCDSS and found it innovative and easy.
• HCWs preferred it to standard (paper) practice, anticipating accurate and easier care management
• Concerns about maintenance and theft
• Identified 17 critical and 9 noncritical usability issues
• Increased ease of use with repetition
• Suggested at least 2 days (16.3hours) of training
Bacis (Basic Antenatal Care Information System) Horner et al (2013) [29]
1 Before and after cohort study
1 South Africa
Maternal Health Nurses
• Electronic patient information system with clinical decision support for maternal health via protocols, checklists, and a rule and knowledge base with alerts and reminders
• Supports patient data entry for classification, follow-up and referral, with validation and completeness checks
• Utility assessment
• Before and after study to assess compliance to guidelines using two study cohorts
• Data collection via record reviews and interviews
• 2 years (development, implementation, evaluation)
• Usability and acceptability review of Bacis
• Compliance (i.e.
completion and response) performance for maternity care protocols and the antenatal care checklist
• Improved compliance from 85% to 89% although not statistically significant
• Out of nine specific categories for measuring compliance, three (compliance at booking, patients
<18 years & booking patients after week 20) showed statistically significant results compared to standard practice using paper
• Better suited for younger computer literate workers
TB Tech Catalani et al (2014) [30]
1 Mixed methods human- centred design
1 Kenya
Tuberculosis
& HIV Clinicians
• Patient-specific clinical decision support for provider action, education and behaviour change.
• Integrates existing paper-based processes with an electronic medical record.
• Supported with educational and motivational information for HCW
• Additional intervention inputs including facility upgrades with staffing and hardware, supply chain management and provision of mobile radiology units and educational campaign for providers
• Qualitative (observation visits, interviews) and quantitative (usability survey and laboratory stimulation).
• Lab simulation involved mock patients
• Iterative prototype development using human- centred design
• Develop, design and pilot test TBTech using a human-centred design approach
• Positive disposition of clinicians to medical record and decision support system –Concerns regarding accuracy and actionability of recommendations
• Health system challenges such as unavailability of tests, low staffing and supplies resulted in delayed action and some unactionable recommendations.
txt2MEDLINE Armstrong et al (2012) [31]
1 Pre-Post utility evaluation
1 Botswana
Multiple domains Clinicians of varying cadres
• Mobile phone-based two-way Short Messaging Service (SMS) of clinical guidelines, with MEDLINE/PubMed query function.
• 76 HCWs used and evaluated system.
• Pre-usage survey was followed by training
• Post-intervention data acquired through a mixed questions survey
• One-month
• Usability and usefulness
of intervention • Although pre-intervention study recorded high
intention to use, this declined during the one-month
trial
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
ALMANACH Shao et al (2015); Shao et al (2015) [32,33]
2 Controlled non- inferiority trial and qualitative study
2 Tanzania
Childhood Illnesses Clinicians
• Smartphone or tablet
• Electronic medical record system with modified version of IMCI algorithm
• Supported by point-of-care tests and simple clinical assessments
• Case-controlled non- inferiority trial comparing ALMANACH use with standard practice
• Observation on initial patient visit and follow-ups (day 7 and 14) with in-depth interviews
• Supervision, training and algorithm use in 2 intervention facilities
• One month pilot
• Primary outcomes: proportion of children cured at day 7 and proportion of children who received antibiotics on day zero
• Secondary outcomes: proportion of children who were admitted secondarily or who died, and proportion of children who received antibiotics during the study period
• Barriers and facilitators to uptake of algorithm and differences between tablets and phones
• Antibiotic prescription reduced by 80% and study reported better clinical outcomes due to increased compliance to guidelines compared to usual practice
• Ease and comfort of use, with sustained rational judgment despite certain recommendations by the system
• HCWs reported that it made their work efficient and effective compared to usual practice, but raised concerns about increased consultation time and lack of financial incentives for using the service
• Patients trust in service delivery improved, although health system constraints hindered completion of the actions and was demotivating
eIMCI Mitchell et al (2012);
Mitchell et al (2013);
DeRenzi et al (2008) [34-36]
3 Mixed methods before- after cluster trial
3 Tanzania
Childhood Illnesses Health care professionals
• Personal Digital Assistant with guided decision support using Electronic IMCI protocols for stepwise examination, diagnosis and management.
• Algorithm included prompts based on data input.
• Language support in English and Swahili
• Quantitative before-after cluster trial
• HCW received one day of technical training
• Iterative modification of prototype design in pre- study stage
• Semi-structured interviews with HCW and patients’ care givers
• Perceptions of HCW and caretakers to eIMCI compared to standard paper formats
• Adherence to eIMCI guidelines compared to paper formats
• Impact of mHealth on quality of IMCI implementation (measured as complete assessment on the 15 critical items of the IMCI)
• HCWs were positively predisposed to using the eIMCI; finding it faster and easier, and appreciating the stepwise guidance
• Caretakers reported improved assessment of their children and perceived that the eIMCI enhanced provider knowledge and skill
• Increased trust and confidence of caretakers in care provided.
• Some HCWs reported challenges with eIMCI recommendations that contradicted their preferred course of management
• Protocol adherence using eIMCI showed statistically significant improvement from 61%-98% in paper format, to 92%-100%.
• Completeness of assessment improved from 21% in the paper format to 71%, and was consistent across study clinics.
• Consultation time was not significantly different between the paper system (8.98minutes) and the eIMCI (9.06minutes)
Text Messaging of Malaria Guidelines Jones et al (2012);
Zurovac et al (2012);
Zurovac et al (2011) [37-39]
3 Cluster randomised controlled trial
3 Kenya
Malaria Health workers
• One way SMS guidelines for outpatient management of malaria, supported by unique motivational messages
• English Language
• Cluster-randomised control trial
• Intervention period of about 6 months. 2 messages delivered daily 5 days a week.
• Qualitative study (interviews)
• Health facility surveys
• Cost-effectiveness study
• HCW perceptions, experiences and drivers of change of intervention
• Improved and maintained adherence guidelines for outpatient paediatric malaria
• Correct management with artemether- lumefantrine and effective counselling
• 24% improvement in correct management, which was sustained (25%) up to 6 months later
• Major improvements in tasks related to dispensing and counselling
• HCW responded to the intervention with enthusiasm, perceiving it as innovative, relevant and useful
• Most HCW were happy with content, frequency and timing of messages with a few concerns about repetition and monotony
• Intervention cost amounted to about USD 19,000,
most (45%) of which was for development and pre-
testing. Cost per additional child correctly managed
was USD 0.50
A
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
ALMANACH Shao et al (2015); Shao et al (2015) [32,33]
2 Controlled non- inferiority trial and qualitative study
2 Tanzania
Childhood Illnesses Clinicians
• Smartphone or tablet
• Electronic medical record system with modified version of IMCI algorithm
• Supported by point-of-care tests and simple clinical assessments
• Case-controlled non- inferiority trial comparing ALMANACH use with standard practice
• Observation on initial patient visit and follow-ups (day 7 and 14) with in-depth interviews
• Supervision, training and algorithm use in 2 intervention facilities
• One month pilot
• Primary outcomes:
proportion of children cured at day 7 and proportion of children who received antibiotics on day zero
• Secondary outcomes:
proportion of children who were admitted secondarily or who died, and proportion of children who received antibiotics during the study period
• Barriers and facilitators to uptake of algorithm and differences between tablets and phones
• Antibiotic prescription reduced by 80% and study reported better clinical outcomes due to increased compliance to guidelines compared to usual practice
• Ease and comfort of use, with sustained rational judgment despite certain recommendations by the system
• HCWs reported that it made their work efficient and effective compared to usual practice, but raised concerns about increased consultation time and lack of financial incentives for using the service
• Patients trust in service delivery improved, although health system constraints hindered completion of the actions and was demotivating
eIMCI Mitchell et al (2012);
Mitchell et al (2013);
DeRenzi et al (2008) [34-36]
3 Mixed methods before- after cluster trial
3 Tanzania
Childhood Illnesses Health care professionals
• Personal Digital Assistant with guided decision support using Electronic IMCI protocols for stepwise examination, diagnosis and management.
• Algorithm included prompts based on data input.
• Language support in English and Swahili
• Quantitative before-after cluster trial
• HCW received one day of technical training
• Iterative modification of prototype design in pre- study stage
• Semi-structured interviews with HCW and patients’ care givers
• Perceptions of HCW and caretakers to eIMCI compared to standard paper formats
• Adherence to eIMCI guidelines compared to paper formats
• Impact of mHealth on quality of IMCI implementation (measured as complete assessment on the 15 critical items of the IMCI)
• HCWs were positively predisposed to using the eIMCI;
finding it faster and easier, and appreciating the stepwise guidance
• Caretakers reported improved assessment of their children and perceived that the eIMCI enhanced provider knowledge and skill
• Increased trust and confidence of caretakers in care provided.
• Some HCWs reported challenges with eIMCI recommendations that contradicted their preferred course of management
• Protocol adherence using eIMCI showed statistically significant improvement from 61%-98% in paper format, to 92%-100%.
• Completeness of assessment improved from 21% in the paper format to 71%, and was consistent across study clinics.
• Consultation time was not significantly different between the paper system (8.98minutes) and the eIMCI (9.06minutes)
Text Messaging of Malaria Guidelines Jones et al (2012);
Zurovac et al (2012);
Zurovac et al (2011) [37-39]
3 Cluster randomised controlled trial
3 Kenya
Malaria Health workers
• One way SMS guidelines for outpatient management of malaria, supported by unique motivational messages
• English Language
• Cluster-randomised control trial
• Intervention period of about 6 months. 2 messages delivered daily 5 days a week.
• Qualitative study (interviews)
• Health facility surveys
• Cost-effectiveness study
• HCW perceptions, experiences and drivers of change of intervention
• Improved and maintained adherence guidelines for outpatient paediatric malaria
• Correct management with artemether- lumefantrine and effective counselling
• 24% improvement in correct management, which was sustained (25%) up to 6 months later
• Major improvements in tasks related to dispensing and counselling
• HCW responded to the intervention with enthusiasm, perceiving it as innovative, relevant and useful
• Most HCW were happy with content, frequency and timing of messages with a few concerns about repetition and monotony
• Intervention cost amounted to about USD 19,000,
most (45%) of which was for development and pre-
testing. Cost per additional child correctly managed
was USD 0.50
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
QUALMAT (Quality of Maternal and Prenatal Care) Blank et al (2013); Dalaba et al (2014);
Dalaba et al (2015);
Mensah et al (2015);
Saronga et al (2015); Zakane et al (2014);
Duysburgh et al (2016) [40-46]
7 Mixed methods quasi- experimental study
7 Tanzania,
Ghana and Burkina Faso Maternal and Prenatal Health Health professionals (non- physicians)
• Guided computer-based decision support system integrated with patient data and algorithmic function for care management (antenatal till early postnatal care) and monitoring.
• Includes educational training materials for health workers and an electronic partograph.
• Additional intervention components included solar power, regular technical supervision, and performance- based incentives (PBI)
• Case control study
• Pre- and post-
intervention assessments of quality of care using structured checklists and questionnaires.
• Monthly monitoring reports
• Multi-stakeholder involvement in design and development
• Pre-intervention training of target users.
• Implementation period of 14months. (3 years for development and pre- implementation)
• Usability, acceptance and impact study
• Assessment of effect on workflow
• Improved quality of care through improved competence and motivation of HCW
General Findings
• No clear difference between pre- and post- intervention quality scores and scores at non- intervention facilities.
• Some variables were inconsistently statistically significant (e.g. in only one study arm, being pre-or post-intervention or intervention, non-intervention).
• Post-intervention history taking, monitoring of mother, total technical and inter-personal performance scores were significantly better but remained unsatisfactory.
• Between intervention and non-intervention quality scores, only care and examination of the newborn scored significantly better
• Use of mCDSS was acceptable and feasible
• Combination of mCDSS and PBI did not improve quality of antenatal care
Ghana
• Decreased proportion of delivery complications (from 10.7% to 9.6%) and reduced number of maternal deaths (from 4 to 1).
• Total financial cost of implementation was about USD 23,000, 48% of which was for pre-intervention expenses
• None significant increase in consultation time for ANC compared to control sites
Tanzania
• Total financial cost of implementation was about USD185,000, 77% of which was for pre-intervention expenses.
• No significant increase in consultation time for ANC in intervention sites compared to control sites
Burkina Faso
• HCW perceived the mCDSS enthusiastically, expecting it to improve their skill and over-reliance on referring patients.
• However providers also resisted due to perceived increased workload and complexity of using the system
a
While this study also used the CommCare app, we decided to treat them as independent studies because the interventions were only similar on a technical level and not part of an integrated multi-country study.
Abbreviations
CHEWs - Community Health Extension Workers HCWs - Health care Workers
ANC - Antenatal Care
PHCs - Primary Healthcare Centre’s CHWs - Community Health Workers
IMCI - Integrated Management of Childhood Illness
mCDSS - mobile clinical decision support system
A
Name of Intervention Authors (Year)
Number of Articles / Type of Paper(s)
Number of Articles
Country Health Domain Target Group
Type of CDSS and Characteristics Study Design and Process Expected Outcome Reported Outcome
QUALMAT (Quality of Maternal and Prenatal Care) Blank et al (2013); Dalaba et al (2014);
Dalaba et al (2015);
Mensah et al (2015);
Saronga et al (2015); Zakane et al (2014);
Duysburgh et al (2016) [40-46]
7 Mixed methods quasi- experimental study
7 Tanzania,
Ghana and Burkina Faso Maternal and Prenatal Health Health professionals (non- physicians)
• Guided computer-based decision support system integrated with patient data and algorithmic function for care management (antenatal till early postnatal care) and monitoring.
• Includes educational training materials for health workers and an electronic partograph.
• Additional intervention components included solar power, regular technical supervision, and performance- based incentives (PBI)
• Case control study
• Pre- and post-
intervention assessments of quality of care using structured checklists and questionnaires.
• Monthly monitoring reports
• Multi-stakeholder involvement in design and development
• Pre-intervention training of target users.
• Implementation period of 14months. (3 years for development and pre- implementation)
• Usability, acceptance and impact study
• Assessment of effect on workflow
• Improved quality of care through improved competence and motivation of HCW
General Findings
• No clear difference between pre- and post- intervention quality scores and scores at non- intervention facilities.
• Some variables were inconsistently statistically significant (e.g. in only one study arm, being pre-or post-intervention or intervention, non-intervention).
• Post-intervention history taking, monitoring of mother, total technical and inter-personal performance scores were significantly better but remained unsatisfactory.
• Between intervention and non-intervention quality scores, only care and examination of the newborn scored significantly better
• Use of mCDSS was acceptable and feasible
• Combination of mCDSS and PBI did not improve quality of antenatal care
Ghana
• Decreased proportion of delivery complications (from 10.7% to 9.6%) and reduced number of maternal deaths (from 4 to 1).
• Total financial cost of implementation was about USD 23,000, 48% of which was for pre-intervention expenses
• None significant increase in consultation time for ANC compared to control sites
Tanzania
• Total financial cost of implementation was about USD185,000, 77% of which was for pre-intervention expenses.
• No significant increase in consultation time for ANC in intervention sites compared to control sites
Burkina Faso
• HCW perceived the mCDSS enthusiastically, expecting it to improve their skill and over-reliance on referring patients.
• However providers also resisted due to perceived increased workload and complexity of using the system
a
