Skip to content
MarketScale
‹ Back to IndustriesHealthcare

Six Week Radiographic Comparison of HipGrid® Drone™ and PhantomMSK® Hip

OrthoGrid announces a new clinical whitepaper for review. A retrospective evaluation was conducted for a consecutive cohort of patients having undergone unilateral total hip arthroplasty via the direct anterior approach between January 2017 and January 2020. All procedures were performed at a single site, by a single, fellowship trained orthopedic surgeon. Intraoperative fluoroscopy was supplemented…

This story was produced through MarketScale. See how Healthcare teams put it to work with Executive Thought Leadership.

Share
Six Week Radiographic Comparison of HipGrid® Drone™ and PhantomMSK® Hip

Get featured

Want to get featured in MarketScale Healthcare?

Create a free MarketScale workspace and get your company's expertise featured across our Healthcare coverage. No credit card, no demo required.

Request an invite

OrthoGrid announces a new clinical whitepaper for review.

A retrospective evaluation was conducted for a consecutive cohort of patients having undergone unilateral total hip arthroplasty via the direct anterior approach between January 2017 and January 2020. All procedures were performed at a single site, by a single, fellowship trained orthopedic surgeon. Intraoperative fluoroscopy was supplemented by either the HipGrid®Drone™ (Drone) or PhantomMSK® Hip (Phantom) (OrthoGrid Systems Inc.

, Salt Lake City, UT, USA) to assist in the positioning of total hip arthroplasty components including cementless, short femoral stem and acetabular cup. The pre-defined target leg length discrepancy (LLD) and global hip offset (GHO) was less than 10mm and acetabular cup abduction angle (ABD) target was 45 degrees plus or minus 10 degrees for the Drone and 42 degrees plus or minus 10 degrees for the Phantom. Accuracy of component placement was evaluated on the six-week post-operative, weight bearing radiographs.

Fluoroscopy times were recorded directly from the c-arm imaging device and surgical times were defined as incision to wound closure. Percentages of patients achieving each component placement goal, as well as reaching all three accuracy goals, were also evaluated. Continuous variables were non-parametric, therefore, group differences were determined by the Mann-Whitney U test and categorical data were evaluated with the Fisher Exact test.

Click here to download the whitepaper:

Some of the data in this whitepaper were previously published in the Journal of Arthroplasty (DOI: 10/1016/j.arth.2020.06.053) by senior surgeon Dr. Cass Nakasone of Straub Medical Center, Bone and Joint Center, Honolulu, HI 96813. Click here to view the article on arthroplastyjournal.org.

To request a HipGrid Drone product demo or a PhantomMSK Hip software demo, please click here.

Your experts belong here

Every story in MarketScale Healthcare starts with a company putting its clinicians, service-line leaders, and field engineers on the record. Buyers are already reading this topic. The only question is whose experts they find.

Service-line buyers vet vendors quietly, and your clinicians become the proof they find while doing it.

Get your team featuredSee how it works15 minutes, straight to a calendar.

Follow Healthcare Insights

Get new expert content in your inbox.

Healthcare: are you visible to AI?

Before they reach out, Healthcare buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one Healthcare expert. Your company is full of them.

This article was produced through MarketScale. The same platform turns your clinicians, service-line leaders, and field engineers into the articles, video, and social content Healthcare buyers are searching for. Create a free workspace and see it with your own people. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Healthcare Insights

Smart ICU and ambient AI cut errors when they feed data and notes into the EMR

Smart ICU and ambient AI cut errors when they feed data and notes into the EMR

Two HIMSS26 APAC case studies point to the same operational lesson: hospitals are getting measurable gains from “smart ICU” device integration and ambient AI documentation only when those tools are tightly integrated into core clinical workflows. Pondok Indah Hospital Group in Indonesia reported reductions of up to 70% in ICU administrative errors and 40% in adverse drug reactions after integrating smart devices, according to Healthcare IT News. Sir H.N. Reliance Foundation Hospital in India reported ambient AI is now used for nearly 90% of progress notes and shift handovers across five live use cases on a single EMR-integrated platform, also reported by Healthcare IT News. New JAMA Network cardiovascular research adds a parallel signal on the clinical side, with AI-enabled acquisition and interpretation approaches moving into screening and triage workflows, which raises procurement questions about validation, interoperability, and change management at the bedside.

  • 01A useful benchmark is emerging for documentation automation: “nearly 90% of progress notes and shift handovers” on ambient AI when it is deployed as one EMR-integrated platform, not a set of point tools (Healthcare IT News).
  • 02The measurable ROI in ‘smart ICU’ programs shows up where operators feel pain: fewer administrative errors and medication-related events, not in abstract “digitization” metrics (Healthcare IT News reported up to 70% and 40% reductions, respectively).
  • 03For hospitals with multiple device vendors and fragmented documentation workflows, integration work, interfaces, identity, order context, and governance, is likely to consume more effort than model selection, so contracts and implementation plans should price integration explicitly.

Sep 1, 2026

Gartner says AI budgets are growing faster than the rules to control them

Gartner says AI budgets are growing faster than the rules to control them

Gartner’s late-August 2026 research points to a familiar operational pattern in enterprise AI: budgets are rising faster than the controls meant to keep costs and risk predictable. In a Aug. 26 press release, Gartner said AI spending by customer service leaders surged 38% even as overall service and support budgets rose 2%. Earlier, at Gartner’s March 2026 Data & Analytics Summit, Gartner analysts said only 44% of organizations had adopted financial guardrails or AI FinOps practices, a gap that becomes more painful as AI workloads scale. The practical takeaway for CIOs, customer service operations leaders, and data and analytics teams is to treat AI governance, cost attribution, and human escalation paths as procurement requirements, not after-the-fact fixes.

  • 01A useful benchmark for planning: Gartner pegs AI spend growth in customer service at 38% versus 2% budget growth overall, a mismatch that forces reallocation and harder ROI proof.
  • 02Only 44% of organizations have adopted AI FinOps-style guardrails, according to Gartner. If AI is moving into production, chargeback and consumption limits need to be designed into the rollout.
  • 03Gartner also forecasts spending on securing AI will hit $4.8 billion in 2027, signaling that AI security is becoming a standalone budget line rather than a feature bundled into existing platforms.

Sep 1, 2026

How Targeted Patient Education Improves Outcomes - Stephen Page, SmarterHealth.AI

How Targeted Patient Education Improves Outcomes - Stephen Page, SmarterHealth.AI

Targeted patient education powered by AI can reduce preventable readmissions and improve health equity, but healthcare organizations must prioritize clinical oversight, data security, and ethical governance when implementing these solutions.

  • 01Preventable readmissions occur when patients misunderstand medications, miss symptom recognition, or lack clarity on follow-up instructions, creating clinical, operational and financial burdens for healthcare systems
  • 02AI-delivered patient education must meet three criteria: solve a meaningful clinical or financial problem, integrate naturally into care workflows, and avoid adding burden to patients or clinicians
  • 03Healthcare leaders evaluating AI tools should prioritize solutions that improve patient understanding, support clinicians, reduce avoidable utilization, protect data security, and demonstrate measurable clinical or financial results

Aug 31, 2026

Explore More Healthcare Insights

Read more expert perspectives from across Healthcare.

Browse Healthcare Hub

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Healthcare and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512