https://orcid.org/0000-0001-8894-3692
Figures
Abstract
Background
Community and retail pharmacies are essential to primary healthcare delivery in Pakistan; however, significant disparities in workforce distribution, medicine availability, and service quality persist between urban and rural settings. The absence of standardized performance monitoring systems limits the ability to identify and address these inequities.
Objective
To design, develop, and validate a key performance indicators (KPI) dashboard for monitoring equity in community and retail pharmacy service delivery in Pakistan.
Methods
A multi-phase methodological study was conducted. Phase I involved qualitative needs assessment using semi-structured interviews with pharmacists, technicians, and administrators (n = 28) to identify service gaps. Phase II employed a modified Delphi technique with expert panel consensus to refine KPIs. Phase III included dashboard development using Microsoft Power BI. Phase IV comprised validation through content validity index (CVI) assessment and usability testing using the System Usability Scale (SUS). Quantitative data were analyzed using descriptive statistics, while qualitative data were analyzed thematically.
Results
Eleven KPIs across workforce, efficiency, quality, safety, availability, and equity domains were finalized. Significant disparities were observed between urban and rural pharmacies, including higher stock-out duration (13.1 vs 6.2 days), lower counseling rates (55% vs 78%), and poorer workforce ratios (1:120 vs 1:65). The dashboard demonstrated high usability (SUS score: 82.5) and strong content validity (S-CVI/Ave: 0.89).
Citation: Hammad M, Arif R, Khan AZ, Nasir A (2026) Design and validation of a key performance indicator dashboard for equity in community and retail pharmacy services in Pakistan. PLoS One 21(7): e0349972. https://doi.org/10.1371/journal.pone.0349972
Editor: Ibrahim Jahun, SKYDA Health Nigeria, NIGERIA
Received: May 7, 2026; Accepted: June 24, 2026; Published: July 10, 2026
Copyright: © 2026 Hammad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The minimal data set [and accompanying code, where generated] is available at figshare via Doi: https://doi.org/10.6084/m9.figshare.32690772.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: KPI, Key Performance Indicator; CVI, Content Validity Index; S-CVI, Scale Content Validity Index; I-CVI, Item Content Validity Index; SUS, System Usability Scale; LMIC, Low- and Middle-Income Countries; Power BI, Microsoft Power Business Intelligence; DAX, Data Analysis Expressions; WHO, World Health Organization; FIP, International Pharmaceutical Federation; UHC, Universal Health Coverage
Introduction
Community and retail pharmacies play a pivotal role in ensuring safe, effective, and accessible medication use within primary healthcare systems, particularly in low- and middle-income countries (LMICs) [1]. In regional and rural settings, these pharmacies serve as the primary point of contact for medication dispensing, patient counselling, and essential medicine supply management [2]. However, significant disparities in workforce distribution, medicine availability, and service quality persist between urban and rural community pharmacies, contributing to inequitable health outcomes and inconsistent pharmaceutical care delivery. The absence of standardized performance monitoring systems further limits the ability of health managers to identify gaps and implement targeted improvements [3].
Globally, Key Performance Indicators (KPIs) are widely used to evaluate healthcare service performance, including dimensions of efficiency, quality, safety, and access [4]. In pharmacy practice, KPIs commonly encompass medication availability, dispensing accuracy, counselling provision, and medication safety outcomes [5]. Several pharmacy KPI frameworks have been implemented internationally, including the Canadian Community Pharmacy Key Performance Indicators (cpKPIs) and quality indicator frameworks developed by the Pharmaceutical Care Network Europe (PCNE) [6–7]. These frameworks have demonstrated effectiveness in monitoring service quality and patient outcomes in high-income settings. While such frameworks have demonstrated utility in high-income settings, most existing models are not directly transferable to LMIC contexts, where rural pharmacies often face structural constraints such as workforce shortages, fragmented supply chains, limited digital infrastructure, and high patient demand [8]. Furthermore, many existing frameworks emphasize clinical and operational performance but inadequately capture geographic and equity-related disparities that are particularly relevant in resource-constrained settings [9–10]. These contextual differences necessitate the development of locally relevant, equity-focused performance measurement tools.
Equity is a central pillar of Universal Health Coverage (UHC), emphasizing fair access to essential health services regardless of geographic or socioeconomic status [11]. In Pakistan, rural populations frequently experience reduced access to qualified pharmacy personnel, higher medicine stock-out rates, and weaker pharmaceutical care infrastructure compared to urban settings [12]. National assessments have reported uneven distribution of registered pharmacists, lower regulatory compliance, and limited adoption of computerized pharmacy systems in rural and peripheral regions, further widening disparities in pharmaceutical service delivery [13–14]. These systemic inequities underscore the need for tools that not only measure pharmacy performance but also explicitly quantify disparities in service delivery across different healthcare settings.
Recent equity-focused implementation frameworks suggest that healthcare performance assessment should consider both service effectiveness and equitable distribution of healthcare resources. Gustafson et al. (2023) highlighted the importance of incorporating equity considerations into implementation frameworks to identify structural barriers and reduce healthcare disparities. Guided by this perspective, the present study conceptualized pharmacy performance across four domains: service accessibility, workforce capacity, medicine availability, and quality of pharmaceutical care. Together, these domains provide a framework for assessing equity in pharmacy service delivery across regional and rural settings [15].
Digital dashboards have emerged as effective tools for health system monitoring by integrating multiple indicators into visual, real-time platforms that support data-driven decision-making. In pharmacy practice, such dashboards can enhance transparency, facilitate performance tracking, and enable rapid identification of service gaps. Despite their growing adoption in hospital and health system management globally, there is a lack of standardized, equity-oriented pharmacy KPI dashboards designed specifically for community and retail pharmacy settings [16]. Moreover, currently available dashboard systems primarily focus on operational monitoring and often lack mechanisms to evaluate disparities in service delivery between different geographic and socioeconomic settings [17–18].
To address this gap, this study aimed to design, develop, and validate a community and retail pharmacy KPI dashboard to monitor service performance and assess equity in regional and rural settings in Pakistan. A rigorous multi-phase methodological approach was employed, including qualitative needs assessment, Delphi-based expert consensus for KPI refinement, dashboard development using Microsoft Power BI, and validation through the System Usability Scale (SUS) and content validity index (CVI) assessment.
By developing an evidence-based, equity-oriented performance monitoring tool, this study contributes to strengthening pharmacy management systems, improving accountability, and supporting equitable pharmaceutical care delivery. The resulting dashboard provides a practical mechanism for pharmacists, hospital administrators, and policymakers to identify service disparities, optimize resource allocation, and enhance decision-making within community and retail pharmacy systems in Pakistan.
Study objectives
Primary objective
To design and develop a validated community and retail pharmacy KPI dashboard for monitoring performance and assessing equity in service delivery across regional and rural settings in Pakistan.
Secondary objectives
- To identify key performance gaps and priority indicators through qualitative needs assessment in community and retail pharmacies.
- To achieve structured expert consensus on essential pharmacy KPIs using a modified Delphi technique.
- To develop a functional and user-friendly KPI dashboard using Microsoft Power BI.
- To evaluate the usability of the dashboard using the System Usability Scale (SUS).
- To assess content validity of selected KPIs using expert agreement and CVI analysis.
- To propose a framework for potential integration of the dashboard into routine pharmacy management systems.
Methodology
Study design
This study employed a multi-phase methodological design to develop and validate a community pharmacy key performance indicators (KPI) dashboard aimed at assessing and improving equitable pharmaceutical service delivery across community and retail pharmacy settings in Pakistan. The methodological framework consisted of four sequential phases: (i) qualitative needs assessment to explore system-level gaps and equity-related challenges in community and retail pharmacy practice, (ii) KPI generation and prioritization using a modified Delphi consensus process, (iii) iterative design and development of a digital performance dashboard, and (iv) content validity assessment and usability testing of the final system. This mixed-methods developmental approach ensured methodological triangulation and enhanced both construct validity and practical applicability of the final tool.
Setting
Study was conducted in community and retail pharmacy settings across Punjab, Pakistan, including both urban and rural locations from 20-April-2021–18- February 2024. Participants (n = 28) were purposively recruited from these settings to capture variability in infrastructure, staffing patterns, medication availability, patient volume, and operational workflows. This diversity provided a robust contextual foundation for identifying service delivery gaps and developing equity-oriented performance indicators for community and retail pharmacy practice. Participants were selected using purposive sampling to ensure inclusion of individuals with relevant expertise and experience in community and retail pharmacy settings. The final sample size was determined by thematic saturation, with interviews conducted until additional data ceased to yield novel themes or meaningful insights. Saturation was reached after 28 interviews, at which point data collection was concluded.
Phase I: Needs assessment
Sampling and participants.
A purposive sampling strategy was used to recruit key stakeholders directly engaged in community and retail pharmacy service delivery. Potential participants were identified through professional pharmacy networks, local pharmacy associations, and institutional contacts across participating pharmacies. Eligible individuals were contacted via email or telephone and invited to participate. Of 34 individuals approached, 28 agreed to participate, yielding a response rate of 82.4%. Participants included community and retail pharmacists (n = 12), pharmacy technicians (n = 10), and pharmacy administrators (n = 6). Inclusion criteria required a minimum of one year of professional experience in community or retail pharmacy practice and active involvement in medication dispensing, inventory management, and patient counseling activities.
Data collection.
Data were collected through semi-structured, in-depth interviews designed to explore operational workflows, service delivery challenges, and equity-related disparities in community and retail pharmacy settings. Prior to formal data collection, the interview guide was pilot-tested with three pharmacists to evaluate the clarity, relevance, and comprehensiveness of the questions. Minor revisions were subsequently made to improve wording and ensure consistency in data collection. The final interview guide encompassed key domains including medicine availability, dispensing practices, staffing challenges, patient access barriers, workflow inefficiencies, and perceived differences in service provision between urban and rural pharmacies. Interviews were conducted either face-to-face or via secure online platforms according to participant preference and availability, with each session lasting approximately 20–30 minutes. All interviews were audio-recorded with prior informed consent and transcribed verbatim for analysis. Data collection and analysis were undertaken concurrently, allowing emerging findings to inform subsequent interviews. Recruitment continued until thematic saturation was achieved, defined as the point at which no new themes or meaningful insights emerged from additional interviews.
Phase II: KPI selection using modified Delphi method
Expert panel.
A multidisciplinary expert panel comprising twelve members was formed for the Delphi process [19]. The panel included senior community pharmacists, academic pharmacy faculty, health systems researchers, and pharmacy administrators with oversight experience in community and retail pharmacy operations. This ensured contextual relevance and methodological rigor in KPI selection.
Delphi rounds.
A modified Delphi technique was conducted over two to three iterative rounds to achieve consensus on KPI selection [20]. In each round, experts evaluated proposed indicators based on relevance, feasibility, measurability, and importance in ensuring equitable pharmacy service delivery. A four-point Likert scale was used for scoring. Indicators achieving a mean score ≥3.5 and an item-level content validity index (I-CVI) ≥0.78 were retained. Feedback between rounds was summarized and used to refine and stabilize expert consensus.
The final KPI framework was categorized into four domains:
- Accessibility (i.e., pharmacist-to-patient ratio, medicine availability, patient waiting time)
- Quality of care (i.e., patient counseling rate, medication error reporting frequency)
- Operational efficiency (i.e., dispensing time, stock-out duration)
- Equity (i.e., rural–urban performance differentials, medicine availability disparity index)
Phase III: Dashboard development
Software and tools.
Dashboard was developed using Microsoft Power BI as the primary analytics and visualization platform. Data integration was performed using Microsoft Excel and CSV datasets. Data transformation and KPI computation were executed using Data Analysis Expressions (DAX) to enable dynamic calculations and interactive reporting.
Dashboard architecture.
It consisted of a three-layer framework comprising (i) a data source layer, (ii) a data processing and analytics layer, and (iii) a visualization layer. Data source layer incorporated structured pharmacy datasets obtained from Excel and CSV files. Processing layer utilized Microsoft Power BI and Data Analysis Expressions (DAX) to perform data cleaning, transformation, KPI computation, and aggregation. The visualization layer generated interactive dashboards, KPI scorecards, trend analyses, and equity comparison modules. Relationships among datasets were established through a relational data model to enable automated KPI updates and real-time filtering across pharmacy settings, geographic locations, and reporting periods.
Dashboard features.
Dashboard incorporated interactive and real-time visualization features to support performance monitoring across community and retail pharmacy settings. Key features included color-coded performance indicators (red = poor, yellow = moderate, green = optimal), dynamic filtering by geography, pharmacy type, and time period, and multiple visualization formats such as bar charts, line graphs, and gauge indicators. The dashboard also included KPI summary cards, an equity comparison module, and automated alerts to highlight underperforming indicators requiring managerial attention.
Data model.
A structured relational data model was developed to support KPI computation. Key derived indicators included stock-out rate (proportion of days a medicine was unavailable), counseling coverage (proportion of patients receiving documented counseling), and disparity ratio (rural-to-urban KPI performance comparison). These measures enabled standardized and comparable assessment of performance across community and retail pharmacy settings.
Data verification.
To ensure data quality, operational records used for dashboard development were cross-checked against pharmacy inventory logs, dispensing registers, and administrative records where available. Where computerized pharmacy management systems were available, operational records were extracted directly from electronic databases. In pharmacies without computerized systems, data were obtained from paper-based dispensing and inventory records and subsequently verified through administrative review. Data completeness and consistency were reviewed before dashboard integration. Any discrepancies identified during verification were resolved through consultation with participating pharmacy personnel.
Phase IV: Validation and usability testing
Content validity.
Content validity of the KPI framework and dashboard components was assessed through expert panel review. Item-level content validity index (I-CVI) and scale-level content validity index (S-CVI) were calculated to quantify agreement among experts. A threshold of ≥0.80 was considered acceptable, ensuring that retained indicators were methodologically robust and contextually appropriate for community and retail pharmacy practice.
Usability testing.
Usability evaluation was conducted among 20 end-users, comprising practicing community pharmacists and retail pharmacy administrators. Participants were recruited through purposive sampling to ensure representation of key stakeholder groups expected to use the dashboard in routine pharmacy practice. The System Usability Scale (SUS) was employed to assess perceived usability and ease of use of the dashboard. SUS scores were interpreted according to established benchmarks, with scores ≥80 indicating excellent usability, scores around 68 reflecting acceptable usability, and lower scores suggesting areas requiring further refinement.
Data analysis.
Data analysis was conducted using a structured, sequential approach aligned with the multi-phase design of the study. Initially, qualitative data from Phase I (needs assessment interviews conducted in community and retail pharmacy settings) were analyzed using Braun and Clarke’s six-step thematic analysis framework [21]. Two researchers independently reviewed and coded the interview transcripts, with discrepancies resolved through discussion and consensus. An iterative codebook was developed and refined throughout the analysis. Codes were subsequently grouped into broader themes reflecting operational challenges, service delivery gaps, and equity-related disparities in pharmacy practice. To enhance trustworthiness, investigator triangulation was employed, whereby a third researcher with expertise in pharmacy practice and qualitative methods reviewed the coding framework and emerging themes. Representative quotations were retained to support interpretation of the findings. The resulting themes informed the development of an initial pool of candidate key performance indicators (KPIs), which served as the foundation for the subsequent Delphi validation phase.
In Phase II, quantitative data obtained from the modified Delphi process were analyzed using descriptive statistical techniques. For each proposed KPI, measures of central tendency and dispersion, including mean scores and standard deviations, were calculated based on expert ratings. The level of expert agreement was assessed using the item-level content validity index (I-CVI) and scale-level content validity index (S-CVI). Predefined inclusion criteria (mean score ≥3.5 and I-CVI ≥ 0.78) were applied to determine the final set of KPIs. The degree of consensus across Delphi rounds was evaluated by examining changes in agreement scores and stability of responses between iterations.
In Phase III, operational pharmacy data from community and retail settings were cleaned, coded, and structured for integration into Microsoft Power BI. The operational data used during dashboard development and testing were derived from pilot pharmacy datasets collected from participating community and retail pharmacies and were not hypothetical datasets. Data transformation procedures were performed using Excel and Data Analysis Expressions (DAX) to compute standardized performance indicators. Key derived variables included stock-out rate, calculated as the proportion of days a medicine was unavailable; counseling coverage, defined as the proportion of patients receiving documented counseling; and other efficiency and accessibility metrics. These indicators were standardized to ensure comparability across diverse community and retail pharmacy settings.
In Phase IV, quantitative validation and usability data were analyzed using SPSS version 26. System Usability Scale (SUS) scores were computed according to established scoring guidelines and summarized using means and standard deviations to assess perceived usability and user satisfaction. Content validity indices (I-CVI and S-CVI) were re-evaluated at the final stage to confirm consistency of expert agreement on KPI relevance and dashboard structure. Descriptive analyses were also performed to examine equity-related indicators, including rural–urban disparity ratios in pharmacy service performance across community and retail settings.
Finally, qualitative feedback obtained during usability testing was analyzed using conventional content analysis to identify recurring themes related to usability, interpretability, workflow integration, and system feasibility. Quantitative and qualitative findings were triangulated to provide a comprehensive evaluation of the dashboard’s performance, ensuring methodological rigor and strengthening the validity, usability, and implementation readiness of the developed KPI system for community and retail pharmacy practice.
Ethical considerations
Ethical approval for the study was obtained from ethics review committee of AI-Shifa Trust Eye Hospital Rawalpindi (Reference no: ERC-115/AST-21; Dated: 15-04-2021) prior to data collection. Written informed consent was obtained from all participants involved in interviews and usability testing. No patient-level or identifiable clinical data were collected during the study. All collected data were stored securely, and confidentiality of participants was strictly maintained throughout the research process.
Results
Participant characteristics
A total of 28 participants were included in the qualitative needs assessment phase, comprising community pharmacists (42.9%), pharmacy technicians (35.7%), and pharmacy administrators (21.4%). Participants were equally distributed across urban and rural community pharmacy settings (50.0% each), ensuring balanced representation of diverse practice environments. The mean years of professional experience varied across groups, with administrators demonstrating the highest experience (10.5 ± 3.4 years), followed by pharmacists (6.8 ± 2.1 years) and technicians (4.3 ± 1.9 years). These characteristics reflect a multidisciplinary and experienced sample suitable for identifying system-level challenges in pharmacy practice as shown in Table 1.
Needs assessment findings
Thematic analysis identified four major domains influencing pharmacy service delivery: workforce capacity and access, medicine availability, quality of service delivery, and operational efficiency. Workforce-related challenges included staffing shortages, unequal distribution favoring urban settings, and increased workload in rural pharmacies. Medicine availability issues were characterized by frequent stock-outs, supply chain delays, and budget constraints, particularly in rural settings.
Quality-related concerns included inadequate patient counselling, poor documentation practices, and lack of follow-up systems. Operational inefficiencies were reflected in longer dispensing times, workflow bottlenecks, and the absence of digital systems. These findings highlight systemic disparities between urban and rural community pharmacies and informed the initial development of candidate KPIs as mentioned in Table 2.
Delphi round 1: Initial KPI screening
In the first Delphi round, 29 candidate KPIs were evaluated across six domains. Key indicators such as pharmacist-to-patient ratio (mean = 4.6, I-CVI = 0.92), stock-out frequency (mean = 4.5, I-CVI = 0.96), and stock-out duration (mean = 4.4, I-CVI = 0.92) demonstrated strong consensus and were retained for further evaluation. Medication error reporting showed borderline agreement (I-CVI = 0.78) but was retained due to its relevance to patient safety as shown in Table 3.
Moreover, 18 KPIs were removed or merged due to redundancy, limited feasibility, or lack of standardized measurement in community and retail pharmacy settings. These included advanced digital indicators, complex equity measures, and sub-indicators overlapping with broader KPI constructs as given in Table 4.
Delphi Round 2: Final KPI consensus
Following iterative refinement, 11 KPIs were finalized across six domains: workforce, efficiency, quality, safety, availability, and equity. Indicators such as pharmacist-to-patient ratio (mean = 4.8, I-CVI = 0.92), stock-out frequency (mean = 4.6, I-CVI = 0.96), and essential medicine availability (mean = 4.5, I-CVI = 0.89) demonstrated strong expert agreement. The inclusion of the inter-facility disparity index reflects the study’s emphasis on equity measurement as mentioned in Table 5.
Final KPI framework for dashboard
The finalized KPIs were operationalized into a structured framework, with clearly defined formulas and measurement approaches. These indicators collectively capture workforce capacity, service efficiency, quality of care, patient safety, medicine availability, and equity in service provision. This framework formed the basis for dashboard development and real-time performance monitoring as shown in Table 6.
Dashboard design and features
The developed dashboard incorporated multiple functional components as given in Table 7, including KPI summary cards, interactive filters, dynamic visualizations, and an equity comparison panel. These features enable users to monitor performance trends, compare urban and rural settings, and identify areas requiring intervention. Automated alert systems further enhance decision-making by highlighting underperforming indicators.
Usability evaluation
Usability testing demonstrated high acceptability of the dashboard among all user groups as mentioned in Table 8. The overall System Usability Scale (SUS) score was 82.5 ± 6.1, indicating excellent usability. Community pharmacists reported the highest usability scores (84.1 ± 5.8), followed by administrators and technicians. These findings suggest that the dashboard is intuitive and suitable for routine use in pharmacy settings.
Subgroup comparison by profession
Table 9 summarizes subgroup differences across professional roles in terms of usability, KPI appraisal, and qualitative focus. SUS scores were consistently high across all groups, with pharmacists reporting slightly higher usability than administrators and technicians. Delphi KPI ratings were derived from a unified expert panel and therefore were not stratified by profession. Qualitative findings indicated role-specific emphases, with pharmacists focusing on clinical workflow and patient counselling, technicians on dispensing and operational workload, and administrators on system-level resource and staffing management.
Qualitative usability feedback
Qualitative feedback reinforced the quantitative usability findings as mentioned in Table 10. Participants highlighted ease of navigation and visual clarity as key strengths, particularly the use of color-coded indicators. The dashboard was also perceived as a valuable decision-support tool for identifying rural service gaps. However, respondents emphasized the need for training, especially for staff in rural settings.
Content validity of KPIs
Content validity analysis demonstrated strong agreement among experts, with an overall S-CVI/Ave of 0.89, indicating excellent validity of the KPI framework. Individual indicators showed high I-CVI values, particularly for stock-out duration (0.96) and pharmacist-to-patient ratio (0.92), confirming their relevance and applicability as shown in Table 11.
Equity analysis: Urban vs rural comparison
Significant disparities were observed between urban and rural community pharmacies across multiple indicators as shown in Table 12. Rural settings showed higher stock-out duration (13.1 vs 6.2 days), lower counselling rates (55% vs 78%), and poorer pharmacist-to-patient ratios (1:120 vs 1:65). Documentation completeness and essential medicine availability were also lower in rural pharmacies. These findings highlight substantial inequities in pharmaceutical service delivery.
System performance evaluation
Dashboard demonstrated strong technical performance as mentioned in Table 13, with optimal data refresh rates, fast load times (1.8 seconds), and zero system errors. User interaction metrics indicated efficient navigation, requiring an average of only two clicks to access core KPIs. High mobile responsiveness further supports its applicability in diverse practice settings.
Discussion
This study developed an equity-focused KPI dashboard for community pharmacies in Pakistan using Delphi consensus and usability testing. Eleven KPIs across six domains were finalized, highlighting workforce shortages, rural medicine stock-outs, poor counselling rates, and operational inefficiencies. Strong urban–rural disparities were evident, particularly in stock-out duration and pharmacist availability. Content validity was high (S-CVI/Ave = 0.89), and usability testing showed excellent acceptability (SUS = 82.5). Overall, the dashboard demonstrated feasibility as a structured tool for monitoring pharmacy performance and equity in resource-limited settings. The findings of this study align strongly with existing global literature emphasizing persistent inequities in community pharmacy services, particularly in low- and middle-income countries (LMICs) [22–24]. Workforce maldistribution observed in this study, with significantly lower pharmacist-to-patient ratios in rural areas, reflects similar patterns reported by the International Pharmaceutical Federation (FIP) [25] and World Health Organization (WHO) report [26], where rural areas consistently face shortages of trained pharmacy personnel. These structural imbalances have been associated with reduced patient counseling time and compromised pharmaceutical care quality.
Medicine availability issues identified in this study, including frequent stock-outs and longer stock-out durations in rural pharmacies, are also consistent with evidence from Kenya, Bangladesh, and Pakistan, where fragmented supply chains and weak inventory systems limit access to essential medicines [27–29]. The magnitude of rural-urban disparity observed reinforces prior findings that supply chain inefficiencies disproportionately affect underserved regions. Whereas, quality-related gaps, particularly low counseling rates and incomplete documentation, mirror studies from South Asia that link poor pharmacy service quality to high workload and lack of standardized protocols [30]. Similarly, operational inefficiencies such as prolonged dispensing times and reliance on manual systems reflect broader LMIC health system limitations in digital infrastructure adoption [31].
Importantly, this study extends existing literature by integrating equity as a measurable KPI dimension within a real-time dashboard. While most prior frameworks focus on efficiency and quality, the inclusion of disparity indices provides a more holistic health system perspective [32–33]. High usability findings further align with global digital health evidence demonstrating that intuitive system design facilitates adoption within clinical workflows. Collectively, the results reinforce established systemic challenges in pharmacy practice while advancing an equity-oriented, data-driven approach to performance monitoring in pharmacy systems. However, implementation of the proposed dashboard in low-resource rural settings may be constrained by limited digital infrastructure, workforce shortages, and inconsistent internet connectivity [34]. These constraints may affect real-time data entry and system responsiveness in peripheral pharmacies. However, the use of a lightweight platform such as Microsoft Power BI, combined with standardized KPI reporting, provides a scalable and cost-effective approach [16] that can function within existing resource limitations. Long-term sustainability will depend on integration with provincial pharmacy regulatory frameworks, establishment of routine data reporting mechanisms [35], and continuous stakeholder engagement. Strengthening governance structures, particularly those related to data quality assurance, performance monitoring, and accountability, will be essential to ensure sustained adoption and meaningful use of the dashboard in routine pharmacy practice.
A key strength of this study is the rigorous development of an equity-oriented KPI dashboard using a mixed-methods design, combining qualitative needs assessment with Delphi consensus and validated through CVI and SUS, ensuring methodological robustness and contextual relevance. The explicit inclusion of equity indicators extends conventional pharmacy performance frameworks. However, limitations include reliance on structured rather than real-time operational data, a geographically limited sample, and small usability testing cohort, which may affect generalizability. Despite this, the dashboard offers a scalable decision-support tool for LMICs to improve pharmacy performance, address rural-urban disparities, and support data-driven health system strengthening.
Conclusion
This study developed and validated a comprehensive KPI dashboard for community and retail pharmacy settings in Pakistan, revealing significant urban-rural disparities in workforce distribution, medicine availability, service quality, and operational efficiency. The finalized 11-KPI framework, supported by strong expert consensus and high usability scores, provides a practical tool for real-time performance monitoring and equity assessment. Its integration of multidimensional indicators makes it a scalable solution for improving pharmacy services. The dashboard holds strong potential to support data-driven decision-making and strengthen equitable pharmaceutical care in LMIC health systems.
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