Telesight: A Telehealth Visit Copilot for the Three-Phase Encounter

Pre-visit chart preparation, intra-visit clinical decision support that respects the Five Rights, post-visit instructions and coding, augmenting the clinician across the full telehealth lifecycle.

Abstract Telemedicine reached 37.0% of U.S. adults in 2021 (43.3% among those 65+)[1] and never fully receded; Mehrotra et al. document the COVID-era visit-mix shift in JAMA Internal Medicine[2]. The telehealth visit has structural properties an in-person visit lacks, reduced ambient cues, asymmetric attention, no opportunistic chart review during the encounter, and these translate into a different copilot opportunity. Telesight is structured around the visit's three phases. Pre-visit: chart preparation using the Sinsky pre-visit-planning framework[6], AHRQ-recommended AI summarisation[7], and a written agenda. Intra-visit: real-time clinical decision support obeying Osheroff et al.'s Five Rights of CDS[8] with attention to Ancker et al.'s alert-fatigue evidence (acceptance drops 30% per additional reminder[9]). Post-visit: a teach-back-style instruction set (95% of studies show positive teach-back outcomes[11]) and AI-suggested billing codes, mindful that current LLMs achieve only 45.9% exact-match ICD-9-CM coding[15]. Telehealth visits show 29% lower no-show odds[4]; Telesight aims to widen the productivity gap further without degrading attention.

1 Introduction

Telehealth visits are not in-person visits delivered through a camera. They are a structurally different encounter: clinicians cannot fluidly scan the chart while listening, patients cannot read body language, and the visit has a hard endpoint that forces denser communication. The literature confirms operational benefits, telehealth shows 7.5% no-show versus 36.1% for in-office visits[3]; adjusted odds of no-show drop 29% across 2.6 million encounters at Parkland Health[4]; telepsychiatry is equivalent to in-person across PTSD, mood, and anxiety disorders in meta-analysis[5]. The opportunity is to design the AI copilot for the visit shape that exists, not a transliteration of in-person tools.

Telesight covers the three temporally distinct phases of a telehealth visit. Each phase has its own evidence base, its own success metric, and its own failure modes. The pre-visit phase is the most under-invested in current product practice; the post-visit phase is where the literature shows the strongest patient-side returns.

1.1 Contributions

1. A three-phase visit copilot whose pre-visit agenda generation, intra-visit CDS, and post-visit instruction set are each grounded in established evidence.
2. Explicit compliance with the Five Rights of CDS[8] and the Ancker alert-fatigue threshold[9], design constraints that production AI scribes typically ignore.
3. An evaluation harness that measures pre-visit time saved, intra-visit interruption rate, and post-visit instruction recall (teach-back proxy).

2 Background and Related Work

2.1 Telehealth's Empirical Profile

The CDC's 2022 NCHS Data Brief documents that 37.0% of U.S. adults used telemedicine in the prior 12 months as of 2021[1]. The Patel/Mehrotra cohort study of 16.7M commercial and Medicare Advantage enrollees[2] documents the rapid early-pandemic shift in visit modality, with telemedicine settling at a substantially elevated plateau through mid-2020 rather than reverting to baseline. Drerup et al.[3] document the ~5× no-show advantage (7.5% telehealth vs 36.1% in-office) and Khoong et al.[4] confirm a 29% adjusted odds reduction at safety-net scale. The Shaker et al. JMIR Mental Health meta-analysis[5] establishes equivalence for telepsychiatry across PTSD, mood, and anxiety disorders.

2.2 Pre-Visit Planning

Sinsky et al.'s AAFP guidance[6] reports that pre-visit lab ordering and chart review the evening before can save approximately one hour of physician time per day, with offsetting nursing-time investment. Holdsworth et al.'s 2021 Annals of Family Medicine analysis[7] describes patchy adoption of AI/NLP pre-visit summarisation across ambulatory practice, a substantial deployment gap remains.

2.3 Intra-Visit Clinical Decision Support

Osheroff et al.[8] codified the Five Rights of CDS: right information, right person, right format, right channel, right time. Ancker et al.[9] documented the operational corollary: alert acceptance drops 30% per additional reminder, with 25% of drug alerts being same-year repeats, alert fatigue is the dominant failure mode of intrusive CDS. Tierney et al. at Permanente Medical Group[10] reported on the ambient AI scribe rollout to 10,000 physicians, finding measurable reductions in after-hours EHR time and improved patient-encounter focus.

2.4 Post-Visit Patient Understanding

Talevski et al.'s teach-back systematic review[11] reports that 95% of included studies found positive effects on patient knowledge, adherence, and disease-specific outcomes. Federman et al.[12] document the patient-side reality of the After-Visit Summary: 82.8% of patients recalled receiving it and 67.4% consulted it, but only 31.6% shared with caregivers, a clear gap voice or text follow-up can close.

2.5 Billing and AI Coding

The 2025 CPT update[14] deleted 99441–99443 and introduced 98008–98015 for audio-only E/M; Medicare did not adopt the new codes and instructs use of 99202–99215 with modifier 93, Telesight must accommodate the policy split. The Soroush et al. NEJM AI benchmark[15] establishes a hard ceiling on autonomous AI coding: GPT-4 reaches only 45.9% exact-match on ICD-9-CM, 33.9% on ICD-10-CM, 49.8% on CPT. Telesight surfaces suggested codes; it does not autonomously code.

3 Proposed Approach

3.1 Three-Phase Pipeline

3.2 Pre-Visit: Chart Preparation Agent

Triggered the evening before the scheduled visit. Generates a one-page agenda: active problems, overdue routine items, medication adherence flags, last visit's open threads. Sends a patient questionnaire (priorities for the visit, symptom updates) and aggregates the response for the clinician. The empirical anchor is Sinsky's ~30-minute-per-day figure[6]; Telesight succeeds only if total clinician time spent reviewing its output is meaningfully shorter than the savings.

3.3 Intra-Visit: Five-Rights-Gated CDS

Telesight intra-visit operates as an ambient listener with a strict prompt budget. The Tierney NEJM Catalyst report[10] on 10,000-physician Permanente rollout informs the architecture: ambient scribe transcription is the substrate, but Telesight adds a CDS overlay that interjects only when (a) a guideline gap is detected, (b) the gap is high-priority by clinical risk, (c) the interjection format is non-modal (lateral notification, not pop-up), and (d) total interjections per visit are capped at two. Each rule corresponds to one of the Five Rights.

3.4 Post-Visit: Teach-Back-Style AVS + Suggested Codes

After the visit ends, Telesight produces a plain-language AVS structured for teach-back: three to five key points with explicit comprehension checks the clinician can review and personalise. The follow-up channel (voice call, SMS, patient portal) is chosen based on the AVS readership pattern Federman et al.[12] document, only 31.6% of patients share AVS with caregivers, motivating direct-to-caregiver delivery for elderly patients. Billing-code suggestions follow the AMA E/M time-or-MDM framework[13], surfaced as recommendations subject to the Soroush ceiling[15].

4 Evaluation Protocol

5 Expected Contributions

1. System. An open three-phase visit copilot with phase-specific design constraints grounded in the established literature.
2. Methodology. A reproducible evaluation harness with metrics per phase rather than a single aggregate.
3. Operating envelope. Documentation of the pre-visit-savings-vs-clinician-review-overhead tradeoff and the intra-visit interjection budget.

6 Limitations and Risks

Telesight's pre-visit chart preparation reduces in-visit cognitive load only if the clinician trusts and reads the output. The risk of a low-trust agent is that the clinician duplicates the work; the risk of a high-trust agent is that they miss what the agent missed. The pre-visit success metric is therefore net time saved, not gross. The intra-visit prompt budget is the most contested design choice and the most consequential, interjection patterns that work in observational pilots regularly fail when deployed at scale due to the Ancker effect[9]. The post-visit AI-coding ceiling is hard: until coding LLMs exceed ~70% exact-match, substantially above the current ~50%[15], autonomous coding remains unsafe.

7 Conclusion

Telesight treats the telehealth visit as three distinct problems rather than one. Each phase has a different evidence base, a different metric, and a different failure mode. The integration discipline, phase-specific constraints, phase-specific metrics, is the contribution, more than any individual phase implementation.