The narrative that AI instantly saves lives is dangerously pushing IT leaders into a costly trap of rushed, poorly planned technology deployments. Learn why successful clinical AI implementations require leaders to move past the hype and demand strict organizational change management.

The narrative that AI instantly saves lives is dangerously pushing IT leaders into a costly trap of rushed, poorly planned technology deployments. Learn why successful clinical AI implementations require leaders to move past the hype and demand strict organizational change management.

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By Robin Roberts (PointClickCare), Vice Chair, EHR Association AI Workgroup, and Lukasz Kowalczyk, MD (Provation), Member, HIMSS Physician Committee This is the first of a 5-part joint blog series …

Healthcare can record every detail and still lose the plot. Before we buy more AI, we should ask why our systems keep forgetting what they already know. “Is there an economic or operational impact that’s going to translate to dollars?” — Nassib Chamoun, founder and CEO of the Health Data Analytics Institute, at the HIMSS AI in Healthcare Forum…

Alexandra Wright of HIMSS told the eHealth Commission that organizations with higher digital maturity tend to get better quality, safety and patient‑experience results, but Colorado shows wide variation and many providers lack readiness for safe AI adoption.

The HIMSS27 conference invites healthcare leaders to Chicago from April 5-8, 2027, to explore critical issues like AI and health equity.

AI needs rigorous oversight to protect patients from harm and to protect physicians from liability, says Dr. Fahad Razak, who is speaking at the HIMSS AI in Healthcare Forum.

AI needs rigorous oversight to protect patients from harm and to protect physicians from liability, says Dr. Fahad Razak, who is speaking at the HIMSS AI in Healthcare Forum.

Background: Hospitals continue to invest heavily to increase their level of digitalization. While advanced digital maturity is assumed to improve hospital performance, empirical evidence remains mixed. This tension is mirrored by the productivity paradox of IT, whereby investments in digital technologies do not consistently translate into observable performance gains. Objective: This study aims to examine the relationship between the Healthcare Information and Management Systems Society (HIMSS) Electronic Medical Record Adoption Model (EMRAM) score and hospitals’ financial, operational, and workforce-related indicators. Methods: This longitudinal observational study used routinely collected hospital-level annual report data from the Dutch National Annual Healthcare Reports Database (CIBG) for Dutch hospitals from 2017 to 2023. Hospital-year records were linked at the institutional level to publicly available HIMSS EMRAM stage 6 or 7 certification information and operationalized dichotomously (stage 6 or 7 vs ≤5). The sample included 66 to 74 hospitals per year (mean 70.4, SD 2.8), corresponding to up to 498 hospital-year observations. Outcome measures were financial (profit margins, return on assets, asset-turnover ratio, and personnel-expense ratio), operational (length of stay and number of patients treated), and workforce (absenteeism) performance indicators. Linear mixed-effects models were estimated while controlling for hospital size, teaching status, staff-to-patient ratio, time trends, and COVID-19 effects. Results: Advanced digital maturity was not significantly associated with improved financial, operational, or workforce performance after adjustment for multiple testing. For financial outcomes, high digital maturity showed no significant association with profit margin, return on assets, personnel-expense ratio, or asset-turnover ratio. Digitally mature hospitals initially appeared to treat more patients annually (β=31,664.318; 95% CI 8392.095-54,936.540; P=.008), but this association was not statistically significant after Holm-Bonferroni correction (adjusted P=.44). No significant associations were observed for length of stay or absenteeism. Conclusions: In a highly digitalized health system with near-universal electronic health record adoption, advanced technical digital maturity alone was not associated with measurable improvements in aggregated hospital-level financial, operational, or workforce performance. These findings provide longitudinal empirical support for the IT productivity paradox in hospital digitalization, suggesting that technical maturity is a necessary but insufficient condition for performance gains. Trial Registration:

Background: Controlled substances require strict life cycle management, but manual workflows can lead to documentation errors, traceability gaps, and delays in empty-ampoule recovery. Objective: This study aimed to construct a quantifiable 3D closed-loop framework integrating technology, process redesign, and organizational accountability and to examine whether implementation was temporally associated with changes in controlled substance process indicators. Methods: A single-center pre-post quality improvement study was conducted in a #healthcare Information and Management Systems Society (HIMSS) Electronic #medical Record Adoption Model (EMRAM) stage 7 hospital. The preintervention period was September 2024 to November 2024, and the postintervention period was December 2024 to February 2025. The intervention combined unique drug identifiers, personal #digital assistant (PDA)–based bedside verification, smart medication cabinets, predispensing prescription review rules, batch-number traceability, daily reconciliation, tiered alerts, staff training, and anomaly-handling standard operating procedures (SOPs). Outcomes were prescription dispensing record compliance, batch-number management noncompliance, failure to complete empty-ampoule recovery and electronic documentation within 24 hours, and implementation fidelity. Proportions were reported with Wilson 95% CIs. Between-period absolute differences and 95% CIs were calculated using the Wald normal approximation for independent proportions. Comparisons used the chi-square test or Fisher exact test, as appropriate. Results: The analysis included 3264 prescription dispensing records before implementation and 3311 prescription dispensing records after implementation. Prescription dispensing record compliance increased from 94.82% (3095/3264) to 98.7% (3268/3311). Batch-number management noncompliance decreased from 2.4% (24/1000) to 0.6% (6/1000). The rate of failure to complete empty-ampoule recovery and electronic documentation within 24 hours decreased from 5.61% (68/1213) to 0.78% (10/1274). Implementation fidelity indicators generated from operational logs were high across system stability, scanning execution, and anomaly closure. Conclusions: Implementation of the 3D closed-loop framework was temporally associated with improvements in controlled substance process indicators in a #digitally mature hospital. The implementation parameters may serve as a reference for local feasibility testing in other wards or institutions, but transferability remains to be evaluated. Multicenter studies are still needed to confirm sustainability and transferability.

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At HIMSS 2026, we showed that the most useful place to apply clinical intelligence is often not in a separate app or side window, but at the cursor, in the...

Malaysia's Institut Jantung Negara hit HIMSS EMRAM Stage 7, using that data foundation to predict patient outcomes and healthcare costs. The cardiac hospital now forecasts length of stay, readmission risk, and procedure-level expenses for individual patients.