Journal of Advances in Medical and Pharmaceutical Sciences

Integrating Clinical, Operational, and Financial Data to Improve Project Outcomes in Digital Health Programs: A Critical Review

Bashiru Ibrahim, Jane Sharon Akinyemi — Mon, 10 Aug 2026 00:00:00 +0000

Digital health programmes are commonly monitored through separate clinical, operational and financial reporting systems. This fragmentation obscures whether a programme that is technically delivered and operationally adopted also improves patient outcomes, distributes benefits equitably and produces affordable, sustainable value. This critical narrative review examines how integrated use of the three data domains can strengthen project governance, implementation learning and benefits realisation. Literature published from 1 January 2005 to 1 June 2026 was identified through accessible scholarly indexes, citation searching and verification against authoritative bibliographic records. Evidence from learning health systems, health informatics, process mining, implementation science, economic evaluation and project governance was appraised and synthesised thematically. The evidence indicates that integration improves observability: it can connect workflow changes, resource use and clinical consequences, expose bottlenecks and unintended effects, and support earlier corrective action. Interoperability standards, common data models and integrated repositories are enabling conditions, but technical linkage alone does not produce decision-ready evidence. Reliable interpretation also requires aligned denominators and time windows, traceable provenance, explicit causal assumptions, baseline or counterfactual comparisons, benefit ownership and governance capable of reconciling conflicting objectives. Clinical measures are often incomplete or weakly attributable; operational measures may reward throughput without reflecting outcomes; and financial measures frequently omit implementation burden, opportunity costs, maintenance and the distribution of costs and benefits. Consequently, evidence that integrated data directly cause superior long-term programme outcomes remains limited, despite stronger evidence for improved measurement, learning and operational control. An evidence-informed programme model is proposed in which technical outputs are linked sequentially to implementation outcomes, clinical and service outcomes, financial value, equity and sustainability. Future research should test this model prospectively across multiple sites using standardised measures, patient- or episode-level cost-outcome linkage, causal evaluation designs and explicit assessment of equity and organisational burden.

Governance and Performance Dashboards for Managing Healthcare Analytics and Artificial Intelligence Implementation Projects in Hospital Systems: A Critical Review

Ododoade Idowu Adewuyi, Moshood Khairah Olayinka — Tue, 18 Aug 2026 00:00:00 +0000

Hospital systems are adopting predictive analytics and artificial intelligence at a pace that has outstripped the development of the organisational machinery required to supervise them. Two bodies of scholarship have grown in parallel to address this problem. The first proposes governance frameworks that specify principles, lifecycle stages, decision points and oversight bodies for artificial intelligence adoption. The second, considerably older, examines performance dashboards as instruments for making clinical and operational performance visible and actionable within hospitals. These literatures rarely engage with one another, and the practical consequence is that governance frameworks specify what ought to be overseen without establishing how oversight is instrumented, while the dashboard literature describes display and feedback mechanisms without addressing the distinctive properties of algorithmic systems that degrade silently, distribute performance unevenly across patient subgroups and depend on outcome labels that arrive long after predictions are made. This critical review examines the intersection of these fields, drawing on peer-reviewed literature identified through structured searching of bibliographic metadata registries and biomedical indexes to 1 June 2026. Five arguments are developed. Governance frameworks remain concentrated at the level of principles, with oversight mechanisms the least frequently specified component. The indicator base for algorithmic performance is dominated by discrimination metrics whose selection is seldom justified and which are poorly aligned with the decisions that governance bodies actually make. Evidence that dashboards improve care is suggestive rather than conclusive, derives largely from non-algorithmic quality improvement contexts, and depends heavily on how feedback is designed and embedded in organisational routines. Post-deployment monitoring of deployed models is constrained by label latency, by the absence of agreed thresholds for action and by the cost of ground-truth ascertainment. Generative and ambient applications are stretching an oversight model constructed for discrete risk-scoring tools. Priorities for research include comparative evaluation of oversight architectures, development of decision-relevant indicator sets, and prospective study of dashboards as governance interventions rather than as reporting artefacts.

Glucagon in Endocrine and Metabolic Practice: A Critical Narrative Review of Stimulation Testing, Diagnostic Cut-points and Therapeutic Use in Children, Adolescents and Adults

Wed, 19 Aug 2026 00:00:00 +0000

Glucagon occupies an unusual position in clinical endocrinology. The same 29-amino-acid peptide serves as a provocative agent for pituitary function testing, as an emergency treatment for severe hypoglycaemia, as a continuous infusion in hyperinsulinaemic states of infancy, and, through receptor co-agonism, as a component of the newest generation of cardiometabolic drugs. These applications have developed in parallel, largely within separate literatures, and the assumptions that underpin them have rarely been examined together. This review evaluates the evidence accumulated over approximately a quarter of a century on the glucagon stimulation test and on therapeutic glucagon across the paediatric and adult lifespan, with particular attention to the derivation, transportability and validity of diagnostic cut-points. Evidence was identified through structured searching of biomedical and bibliographic sources and appraised for design adequacy, reference-standard quality, sample size, assay dependence and generalisability. Three findings dominate the synthesis. First, the growth hormone cut-point for the glucagon stimulation test is not a fixed biological threshold but a function of dose regimen, adiposity, glucose tolerance, age and assay calibration; the widely used threshold of 3 µg/L overdiagnoses deficiency in overweight adults, and the proposed alternative of 1 µg/L rests on small validation cohorts. Second, the corticotroph read-out from the same test performs considerably less well than the somatotroph read-out, and several independent series show a broad indeterminate zone in which the test cannot classify patients reliably. Third, therapeutic glucagon has been transformed by stable ready-to-use formulations and by the analogue dasiglucagon, with randomised evidence in severe hypoglycaemia, congenital hyperinsulinism and post-bariatric hypoglycaemia, although comparative effectiveness data and long-term paediatric safety data remain sparse. Priorities include multicentre cut-point validation stratified by body mass index and assay platform, harmonised cortisol thresholds, and adequately powered comparisons between glucagon formulations in real-world hypoglycaemia.

Osteogenesis Imperfecta from Historical Nosology to Gene-directed Therapy: A Critical Narrative Review of Mechanism, Evidence and Translational Uncertainty

Stefan Bittmann, Elisabeth Luchter, Elena Moschüring-Alieva — Wed, 26 Aug 2026 00:00:00 +0000

Osteogenesis imperfecta is the prototypical heritable disorder of bone fragility, and the last three decades have transformed it from a clinically defined syndrome into a molecularly stratified group of conditions involving more than twenty genes. That transformation has not been matched by comparable progress in classification, outcome measurement or therapeutic evidence, and the resulting mismatch is the central concern of this review. The purpose of the article is to evaluate critically how historical nosology, molecular pathology and emerging gene-directed interventions relate to one another, and to determine which conclusions the accessible evidence can currently sustain. Literature was identified through open scholarly databases, citation searching and a clinical trials registry, with appraisal directed at study design, cohort ascertainment, endpoint selection and the distance between mechanistic plausibility and demonstrated clinical benefit. Three critical findings emerge. First, competing nosological frameworks now coexist without prospective validation against clinical outcomes, so classification supports communication more than it supports prognosis or treatment selection. Second, the dominant-negative mechanism that accounts for most disease produces a hypermineralised yet mechanically inferior matrix, which explains why densitometric gains have repeatedly failed to translate into proportionate fracture reduction and why surrogate endpoints have misdirected therapeutic expectation. Third, cell and gene therapy remain overwhelmingly preclinical or exploratory: published editing work is largely confined to cell models and rodent studies, mesenchymal stromal cell evidence rests on small uncontrolled series, and no completed clinical gene therapy trial for this condition was identified. Major unresolved questions concern the qualification of surrogate endpoints, the penetrance of pathogenic variants in unselected populations, allele-specific correction of private dominant-negative variants, and durable delivery to skeletal progenitors in a growing skeleton. Progress will depend less on new mechanistic detail than on trial designs and outcome measures capable of detecting clinically meaningful change in a rare, heterogeneous and slowly evolving disorder.

Reducing False Positives and False Negatives in Artificial Intelligence-assisted Imaging Screening: A Critical Review of Accuracy, Error Mechanisms and Clinical Translation

Thu, 27 Aug 2026 00:00:00 +0000

Imaging-based screening programmes are constrained by two opposing failures: false-positive results that generate unnecessary recall, anxiety, further imaging and biopsy, and false-negative results that permit disease to progress undetected until the next screening round or until symptoms appear. Artificial intelligence applied to medical images has been presented as a means of relaxing this constraint by improving detection without expanding the recalled population. This critical review evaluates whether that claim is supported, and under what conditions. Evidence was drawn from peer-reviewed studies identified through open scholarly indexes and citation searching, with emphasis on prospective, randomised and population-based evaluations across breast, lung, ophthalmic, prostate and tuberculosis screening. Three findings emerge. First, the strongest current evidence, from randomised and large prospective breast screening studies, indicates that artificial intelligence used as triage plus decision support within a double-reading programme increases cancer detection and sensitivity while leaving specificity unchanged and substantially reducing reading workload; the effect on interval cancer rate is at present consistent with non-inferiority rather than with demonstrated superiority. Second, gains are configuration-dependent rather than intrinsic to the algorithm: autonomous rule-out of low-risk examinations has produced both preserved and significantly increased recall in different prospective settings, and simulated reader replacement has reduced detection in at least one population-based cohort. Third, residual error is structured rather than random, arising from shortcut learning, distribution shift, model version change, uneven subgroup performance and reader-algorithm interaction effects such as automation bias. The evidence base remains geographically narrow, dominated by breast imaging, largely reliant on retrospective and simulated designs outside mammography, and weakly connected to patient-relevant endpoints such as mortality, overdiagnosis and stage shift. Priorities include randomised evaluation outside mammography, prespecified subgroup and threshold reporting, standardised post-deployment monitoring of version change, and explicit accounting of the harms attached to each error type.

Predictive ADMET Assessment and Molecular Docking Analysis of Fisetin for Its Immunomodulatory Potential

Rakesh Tirkey — Mon, 17 Aug 2026 00:00:00 +0000

Background: Immune-mediated diseases impose substantial clinical and socioeconomic burdens, while prolonged use of conventional immunosuppressive agents may be associated with serious adverse effects. Fisetin, a naturally occurring flavonoid, has demonstrated anti-inflammatory and immunomodulatory properties, but its interaction with FK506-binding protein 12 (FKBP12) remains insufficiently characterised.

Aim: This study aimed to evaluate the binding interaction of fisetin with FKBP12 and to assess its predicted absorption, distribution, metabolism, excretion, and toxicity properties in comparison with tacrolimus.

Method: The three-dimensional structure of FKBP12 was prepared for molecular docking, while fisetin and tacrolimus were selected as ligands. Docking analysis was performed using AutoDock version 4.2.6. Drug-likeness, pharmacokinetic behaviour, and toxicity-related parameters were predicted using SwissADME and pkCSM.

Results: Fisetin interacted with three FKBP12 binding sites, with predicted binding energies of −8.15, −7.92, and −5.62 kcal/mol. Tacrolimus showed corresponding binding energies of −10.29, −8.44, and −8.43 kcal/mol. Fisetin formed hydrogen-bond and hydrophobic interactions with several amino acid residues, including ARG18, GLU60, ALA64, PHE15, ARG13, and THR85. It showed no violation of Lipinski’s rule of five and had higher predicted gastrointestinal absorption than tacrolimus. No Ames toxicity, hERG inhibition, hepatotoxicity, or skin sensitisation was predicted for fisetin, although inhibition of CYP1A2, CYP2D6, and CYP3A4 was indicated.

Conclusion: Fisetin demonstrated plausible binding to FKBP12 and a comparatively favourable predicted ADMET profile. These findings provide preliminary computational support for further investigation, although biochemical, cellular, and in vivo validation is required before its immunomodulatory potential can be confirmed.

Development and Validation of New Analytical Method for Determination of Particle Size Distribution in Alogliptin Benzoate Drug Substance Using Laser-based Particle Size Analyzer

Tue, 18 Aug 2026 00:00:00 +0000

Particle size distribution (PSD) characterisation is important for pharmaceutical drug-substance quality because particle size can influence formulation-related performance. This study developed and validated a wet-dispersion laser-diffraction method for determining the PSD of Alogliptin Benzoate using the Malvern Mastersizer 3000 (Ultra Plus). Methanol, chloroform, and liquid paraffin light were evaluated during method development, and liquid paraffin light was selected as the dispersion medium. The optimised measurement conditions included a particle refractive index of 1.50, dispersant refractive index of 1.468, sample absorption value of 1.0, obscuration of 10–20%, stirrer speed of 2000 rpm, and sonication for 45 seconds. Method performance was assessed using Dᵥ10, Dᵥ50, and Dᵥ90 through precision, intermediate precision, and robustness studies. Method precision produced %RSD values of 3.00%, 2.47%, and 3.91% for D(0.1), D(0.5), and D(0.9), respectively. Intermediate precision gave corresponding %RSD values of 3.46%, 3.40%, and 8.77%. The cumulative %RSD values for method and intermediate precision were 3.21%, 3.30%, and 6.80%, respectively. Robustness was evaluated by deliberate changes in stirrer speed, obscuration range, and sonication time, with the reported results remaining within the stated acceptance criteria. The developed procedure therefore demonstrated consistent performance under the conditions evaluated and is suitable for routine particle size determination of Alogliptin Benzoate drug substance in quality control laboratories.