Scoping review + SOCI: to assess DHIS2 applicability for NCD
Hi there!
I am Oleg, graduated student from Belgarde University. It is my thesis work and I am looking for community assesment.
With research team from the University of Belgrade. We are conducting a scoping review on the use of DHIS2 and DHIS2-based health information systems for non-communicable diseases (NCDs).
OSF LINK [ OSF | Applicability of DHIS2 software platform for monitoring non-communicable diseases in Serbia and Southeast Europe: Scoping Review].
Now I will explain how I imagine to combine SOCI Serbia and DHIS2 scoping review. Please assess this approach:
As an example we took 19 articles. We extracted barriers and facilitators from each article and coded them according to the five main SOCI domains. From this coding, I decided to create two simple indicators for each domain.
The first is **prevalence (**how common a problems across studies): the proportion of studies that report at least one barrier or facilitator.
The second is intensity: the average, across studies, of the share of all barrier (or facilitator) statements within each study that are attributed to a given domain.
To intergarte Serbian context, I decided to use SOCI 2024 maturity level. Each criterion is rated from 1 to 5, normalized to a 0-1 scale.
From this constructed two parametrs:
The Priority index combines the prevalence of barriers with the readiness deficit , that is, how much more the country has to do in this area. Both are multiplied, not added, because a field can be considered high priority only if both criteria are met: in literature it is defined as a widespread problem and the country is not yet ready for it. Otherwise, priority is automatically lowered if one of the criteria is weak.
The Opportunity index is the exact opposite: it combines both the prevalence of facilitators and readiness. If the literature highlights positive experiences and the country has a decent basis to start with, it is considered a domain with high opportunity, which means quick wins can be possible.
Finally, I calculated an overall applicability indicator. In each domain, we looked at two things: whether the evidence is mostly from facilitators or barriers (depending on intensity), and whether Serbia’s SOCI score meets the midpoint of the scale.
Domains where both are favourable were rated Met. Domains where the picture is mixed were rated Partly met. Domains where both are unfavourable would be rated Unmet. Each rating was converted to a simple score (2, 1, or 0), and the sum across all five domains, divided by the maximum possible, gave us an overall applicability percentage of 70%, indicating moderate-to-high applicability of DHIS2 for NCD surveillance in Serbia.
I have next Questions
1. Threshold selection Assuming that 2.5 is the middle of the SOCI scale, I used it as a threshold. Is this valid?
2. Interpreting Opportunity vs. Priority I am examining various ways to interpret the correlation between the Opportunity and Priority indices
Should I keep both parameters and interpret them independently? Or Is it better to combine them into a single metric, like Net Balance (Opportunity - Priority), and pay attention to the difference?
In addition, would it be reasonable to interpret based on rules, for instance: Similar values = system is balanced (no immediate intervention needed) Opportunity > Priority = focus on scaling strengths Priority > Opportunity = prioritize fixing gaps
- I would be grateful if you could evaluate my approach and the formulas I used. It is important for me to receive comprehensive and honest feedback, including any critical remarks. Thank you in advance to everyone who takes the time to share their thoughts.
** Example of All formulas and tables are provided Below**
1. Study-level totals (per study i)
1.1 Total number of barriers in study (i) based on SOCI Domains.
\text{Bar}{\text{total}}(i) = \text{Bar}{\text{LandG}}(i) + \text{Bar}{\text{MandW}}(i) + \text{Bar}{\text{ICT}}(i) + \text{Bar}{\text{SandI}}(i) + \text{Bar}{\text{DQandU}}(i)
Explanation: Bar_total(i) is the sum of all barrier statements in study i across the five SOCI domains (Leadership and Governance, Management and Workforce, ICT Infrastructure, Standards and Interoperability, Data Quality and Use).
Example (Study #5 from raw data): Study #5 has 3 L and G barriers, 2 M and W barriers, 1 ICT barrier, 0 S and I barriers, and 8 DQ and U barriers.
Bar_total(5) = 3 + 2 + 1 + 0 + 8 = 14
1.2 Total number of facilitators in study (i)
\text{Fac}{\text{total}}(i) = \text{Fac}{\text{LandG}}(i) + \text{Fac}{\text{MandW}}(i) + \text{Fac}{\text{ICT}}(i) + \text{Fac}{\text{SandI}}(i) + \text{Fac}{\text{DQandU}}(i)
Explanation:Fac_total(i) is the sum of all facilitator statements in study (i) across the five SOCI domains .
2. Prevalence per SOCI domain d
2.1 Barrier prevalence(d)
Formula:Barrier Prevalence(d) = Number of studies with ≥1 barrier in domain d / Total number of studies (19 )
Explanation:This is the proportion of included studies that report at least one barrier in a given domain. If 15 out of 19 studies have a DQ and U barrier, the barrier prevalence for DQ and U is 15/1 9.
Example (Data Quality and Use):In the Excel file, 18 out of 19 studies have at least one DQ and U barrier. Barrier Prevalence (DQ and U) = 18 / 19 = 0.947 (94.7%).
**
2.2 Facilitator prevalence(d)**
Formula:Facilitator Prevalence(d) = Number of studies with ≥1 facilitator in domain d / Total number of studies (19) Explanation:This is the proportion of studies that mention at least one facilitator in a given domain.
3. Within-study shares (per study i and domain d)
3.1 Barrier share in domain d within study i
\text{Barrier}{\text{Share}}(i, d) = \frac{\text{Bar}{d}(i)}{\text{Bar}_{\text{total}}(i)}
Explanation:This is the fraction of all barriers in study i that belong to domain d. It tells us how important the domain is within that study. Example (Study #5, DQ and U): Study #5: 8 DQ and U barriers out of 14 total barriers- Barrier Share (5, DQ and U) = 8 / 14 = 0.571 (57.1%).
**
3.2 Facilitator share in domain d within study i**
\text{Facilitator}{\text{Share}}(i, d) = \frac{\text{Fac}{d}(i)}{\text{Fac}_{\text{total}}(i)}
Explanation:This is the fraction of all facilitators in study i that belong to domain d.
4. Intensities per domain d
4.1 Barrier intensity(d)
Barrier Intensity(d) = Average of Barrier Share(i, d) across all studies with ≥1 barrier in domain d
Explanation: We first compute Barrier Share(i, d) for each study. Then we take the simple average across studies that actually have at least one barrier in that domain. Each study contributes equally to this average.
Example (Data Quality and Use): The Excel summary shows Barrier Intensity (DQ and U) = 45.0%. This means that, on average across studies that have DQ and U barriers, about 45% of all their barriers belong to DQ and U
**
4.2 Facilitator intensity(d)**
Facilitator Intensity(d) = Average of Facilitator Share(i, d) across all studies with ≥1 facilitator in domain d
Example (Data Quality and Use): The Excel summary shows Facilitator Intensity(DQ and U) = 23.4%. This means that facilitators in DQ and U form about 23.4% of all facilitators within these studies, on average.
5. Net balance per domain d
\text{Net}{\text{Balance}}(d) = \text{Facilitator}{\text{Intensity}}(d) - \text{Barrier}_{\text{Intensity}}(d)
Explanation:If the result is positive, facilitators dominate barriers in that domain. If negative, barriers dominate.
Example (Data Quality and Use):Facilitator Intensity(DQ and U) = 23.4%, Barrier Intensity(DQ and U) = 45.0%.
Net Balance (DQ and U) = 23.4 − 45.0 = −21.6 percentage points (barriers dominate).
6. Readiness from SOCI score
\text{Readiness}(d) = \frac{\text{SOCI}(d) - 1}{4}
Explanation:SOCI(d) is the HIS maturity score for domain d on a 1–5 scale. Readiness(d) rescales this to a 0–1 scale: 1 becomes 0, 5 becomes 1, and values in between are linearly in between.
Example (Data Quality and Use): SOCI(DQ and U) = 2.6. Then Readiness (DQ and U) = (2.6 − 1) / 4 = 1.6 / 4 = 0.4 (40%).
7. Priority and Opportunity indices per domain d
7.1 Priority index(d)
\text{Priority}(d) = 100 \times \text{Barrier}_{\text{Prevalence}}(d) \times \bigl(1 - \text{Readiness}(d)\bigr)
Explanation:Priority is higher when barriers are reported in many studies and when national readiness in that domain is low. The factor 100 simply scales the value to a 0–100 range.
Example (Data Quality and Use): Barrier Prevalence(DQ and U) = 0.947, Readiness(DQ and U) = 0.4.
Priority (DQ and U) = 100 × 0.947 × (1 − 0.4) = 100 × 0.947 × 0.6 = 56.8.
**
7.2 Opportunity index(d) **
\text{Opportunity}(d) = 100 \times \text{Facilitator}_{\text{Prevalence}}(d) \times \text{Readiness}(d)
Explanation:Opportunity is higher when facilitators are common in the literature and national readiness is already relatively high.
Example (Data Quality and Use):Facilitator Prevalence(DQ and U) = 0.947, Readiness(DQ and U) = 0.4.
Opportunity (DQ and U) = 100 × 0.947 × 0.4 = 37.9.
8. Domain judgments and overall applicability
8.1 Domain score J(d)
Rule :
· Met- J(d) = 2 (evidence favourable and readiness at least moderate ).
· Partly met -J(d) = 1 (mixed picture: one input favourable, one less favourabl e).
· Unmet-J(d) = 0 (both evidence and readiness unfavourab le).
8.2 Overall applicability
Formula: Applicability (0–1) = (J(L and G) + J(M and W) + J(ICT) + J(S and I) + J(DQ and U)) / ( 2 × 5)
In percentage:Applicability (%) = Applicabilit y × 100
Example (Serbia results): L and G = Met (2), M and W = Partly met (1), ICT = Met (2), S and I = Partly met (1), DQ and U = Partly met (1).
Sum = 2 + 1 + 2 + 1 + 1 = 7; maximum = 2 × 5 = 10; Applicability = 7 / 10 = 70%.
S ensitivity analysis
For each domain d and each scenario (Baseline, +0.3, +0.5, +1.0):
Increase the SOCI score by ΔSOCI.
Recalculate Readiness(d) = (SOCI(d) + ΔSOCI − 1) / 4.
Keep Barrier Prevalence(d) fixed (the literature does not change).
Recalculate Priority(d) = 100 × Barrier Prevalence(d) × (1 − Readiness(d)).
This shows how Priority scores decrease as SOCI (and therefore readiness) improves, and whether the ranking of domains remains stable when assume realistic improvements in HIS maturity
Scenario +0.3 (ΔSOCI = 0.3)
- New SOCI:
- SOCI_new = 2.6 + 0.3 = 2.9
- New Readiness:
- Readiness_new = (2.9 − 1) / 4 = 1.9 / 4 = 0.475
- New Priority:
1 − Readiness_new = 1 − 0.475 = 0.525
Priority_new = 100 × 0.947 × 0.525 = 49.7
Feasibility asswsment
| Column 1 | Column 2 | Column 3 | Column 4 | E | F | G | H | I | J |
|---|---|---|---|---|---|---|---|---|---|
| SOCI Domain (= Criterion) | SOCI 2024 (1–5) | Readiness (0–100%) | Barrier Prevalence | Facilitator Prevalence | Barrier Intensity | Facilitator Intensity | Net Balance (Fac−Bar) | Judgment | Score (0–2) |
| Leadership and Governance | 2,8 | 45% | 73.7% | 89.5% | 18.7% | 21.7% | +3.1% | Met | 2 |
| Management and Workforce | 2,3 | 32% | 78.9% | 84.2% | 23.6% | 25.4% | +1.8% | Partly met | 1 |
| ICT Infrastructure | 2,6 | 40% | 42.1% | 78.9% | 6.3% | 20.0% | +13.7% | Met | 2 |
| Standards and Interoperability | 2,3 | 32% | 42.1% | 57.9% | 6.5% | 9.6% | +3.0% | Partly met | 1 |
| Data Quality and Use | 2,6 | 40% | 94.7% | 94.7% | 45.0% | 23.4% | -21.6% | Partly met | 1 |
| TOTAL | Met: 2 Partly: 3 Unmet: 0 | 7/10 | |||||||
| JUDGMENT RULE: | |||||||||
| Met (2) | Net Balance ≥ 0 (facilitators dominate in scoping) AND SOCI ≥ 2.5 | ||||||||
| Partly met (1) | Net Balance ≥ 0 but SOCI < 2.5 (evidence positive, readiness low) OR Net Balance < 0 but SOCI ≥ 2.5 (readiness OK, evidence flags a gap) | ||||||||
| Unmet (0) | Net Balance < 0 AND SOCI < 2.5 (both evidence and readiness unfavorable) |
Priority and Opportunity Indices by SOCI Domain
| Column 1 | Column 2 | Column 3 | Column 4 | E | F | G | H |
|---|---|---|---|---|---|---|---|
| SOCI Domain | Barrier Prevalence | Readiness | Priority Index (0–100) | Priority Rank | Facilitator Prevalence | Opportunity Index (0–100) | Opportunity Rank |
| Leadership & Governance | 73.7% | 45% | 40,5 | 3 | 89.5% | 40,3 | 1 |
| Management & Workforce | 78.9% | 32% | 53,3 | 2 | 84.2% | 27,4 | 4 |
| ICT Infrastructure | 42.1% | 40% | 25,3 | 5 | 78.9% | 31,6 | 3 |
| Standards & Interoperability | 42.1% | 32% | 28,4 | 4 | 57.9% | 18,8 | 5 |
| Data Quality & Use | 94.7% | 40% | 56,8 | 1 | 94.7% | 37,9 | 2 |
| SENSITIVITY ANALYSIS | |||||||
| Scenario | ΔSOCI | Leadership | Management | ICT Infrastr | Standards | Data Quality | Mean |
| Baseline | 0 | 40,5 | 53,3 | 25,3 | 28,4 | 56,8 | 40,9 |
| +0.3 | 0,3 | 35 | 47,4 | 22,1 | 25,3 | 49,7 | 35,9 |
| +0.5 | 0,5 | 31,3 | 43,4 | 20 | 23,2 | 45 | 32,6 |
| +1.0 | 1 | 22,1 | 33,6 | 14,7 | 17,9 | 33,2 | 24,3 |
Thank you for your Attention!
Discussion in the ATmosphere