MMHA 6601 Week 9 Innovation Proposal Draft Example

Ambient Documentation for Ridgeway Health Partners: An Innovation Proposal Draft From Criteria to a Conditioned Recommendation

Student Name

Walden University

MMHA 6601: Technology and Innovations in Healthcare

Instructor Name

Month Day, Year

Ambient Documentation for Ridgeway Health Partners: An Innovation Proposal Draft From Criteria to a Conditioned Recommendation

Purpose of This Draft

This draft proposes that Ridgeway Health Partners, the fictional fourteen-practice primary care group used in this course, adopt an ambient documentation tool for its physicians and nurse practitioners. It applies the seven screening questions the network adopted earlier in the term, summarizes the evidence, sets out costs and barriers and ends with a recommendation that carries conditions. It is a draft for review by the technology review group; the final version will incorporate their comments and the results of a short pilot.

Problem and Baseline

Ridgeway's clinicians spend a large share of their day on documentation. Record activity logs for the past quarter, an illustrative figure for this draft, show a median of 1.4 hours of record work outside scheduled hours per clinician per day, and 38 percent of notes are signed more than 48 hours after the visit. When notes lag, claims wait, and a colleague covering the next day opens a chart with no record of the last conversation. In the network's last engagement survey, documentation was the most frequently named source of frustration.

The pattern matches national findings. Observers who shadowed office-based physicians in four specialties counted close to two hours of screen and desk tasks for each hour in the exam room (Sinsky et al., 2016), and log data from primary care have shown physicians spending more than half their workday in the record, including substantial time after clinic hours (Arndt et al., 2017).

Evidence

Ambient documentation uses speech recognition and a language model to draft a note from the conversation during a visit, with patient consent, for the clinician to review and sign. The evidence base is young. The largest published deployment, at a large medical group, reported rapid uptake among physicians, positive feedback from patients and clinicians, and less reported time on documentation, along with occasional errors in drafts that required clinician correction (Tierney et al., 2024). Rigorous controlled studies remain limited, and effects on note quality, billing accuracy and patient experience in community primary care are not yet well established.

The draft therefore treats the evidence as promising but not settled, and builds the pilot to answer the questions the evidence leaves open.

Whose Work Changes

Table 1

Roles and Changes in Work

The largest change falls on clinicians, and the proposal's value depends on whether review takes less time than writing did.

Costs

The vendor charges per clinician per month. For 110 clinicians over five years, the license, integration, training and support come to an illustrative total of about $1.9 million. The draft does not claim the tool pays for itself through billing. If clinicians each regain about 30 minutes a day, the value lies mainly in retention: the cost of replacing a single primary care physician, including recruitment and lost revenue during the vacancy, is high enough that preventing a few departures would offset much of the cost. That argument rests on assumptions the pilot should test.

Preconditions and Barriers

Using the NASSS framework from Week 8, the main complex domain is adopters. Clinicians differ in their trust of drafted notes, and patients differ in their comfort with a recording device (Greenhalgh et al., 2017). The draft addresses this with voluntary participation, easy opt-out for patients, a light on the device whenever audio is captured, no retention of audio after the note is signed and a quality review of a sample of notes.

Table 2

Preconditions for Success

Measures Within a Year

Process measures for the pilot are evening and weekend record minutes from the logs, the proportion of notes closed within a day and a five-point burden rating from clinicians, with clinician retention intent as the outcome measure most relevant to the value case. A coder review of 50 notes per month will check that drafts support billed levels and contain no fabricated findings.

Questions for the Review Group

Three questions in this draft need the group's judgment before the pilot starts. First, is a 20 percent reduction in after-hours time the right threshold, or should the network require more, given the cost? Second, should nurse practitioners and physicians be included in equal numbers in the pilot, since their visit patterns differ? Third, should behavioral health integration visits, where privacy concerns are sharpest, be excluded from the pilot entirely or left to each clinician's judgment? The draft leans toward clinician judgment with patient consent, but the group may see risks the author has missed.

Equity and Access

The tool's speech recognition is validated mainly for English. Two of Ridgeway's practices see many Spanish-speaking patients, and visits with interpreters involve three voices and two languages. The pilot will exclude interpreted visits and visits in Spanish until the vendor provides validation data, and the draft flags this as a limit: if the tool helps clinicians mainly in English-language visits, it could widen differences in clinician attention between patient groups. A plan for non-English visits should be part of the final proposal.

Exit Plan

The contract will include a 90-day termination clause after the pilot, deletion of all audio and transcripts on exit and return of any configuration. If the pilot fails to reduce after-hours time or if error review finds a pattern of clinically significant errors, the network will stop, and clinicians will return to their current methods, which remain in place throughout.

Recommendation

Recommend adoption with conditions: begin with a twelve-week pilot of 20 volunteer clinicians at four practices; proceed to full rollout only if after-hours time falls by at least 20 percent, error review finds no pattern of significant errors and the data agreement is signed. The technology review group is asked to comment on the measures and thresholds before the pilot begins.

References

Arndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W.-J., Sinsky, C. A., & Gilchrist, V. J. (2017). Tethered to the EHR: Primary care physician workload assessment using EHR event log data and time-motion observations. Annals of Family Medicine, 15(5), 419-426. https://doi.org/10.1370/afm.2121

Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., A'Court, C., Hinder, S., Fahy, N., Procter, R., & Shaw, S. (2017). Beyond adoption: A new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of Medical Internet Research, 19(11), e367. https://doi.org/10.2196/jmir.8775

Sinsky, C., Colligan, L., Li, L., Prgomet, M., Reynolds, S., Goeders, L., Westbrook, J., Tutty, M., & Blike, G. (2016). Allocation of physician time in ambulatory practice: A time and motion study in 4 specialties. Annals of Internal Medicine, 165(11), 753-760. https://doi.org/10.7326/M16-0961

Tierney, A. A., Gayre, G., Hoberman, B., Mattern, B., Ballesca, M., Kipnis, P., Liu, V., & Lee, K. (2024). Ambient artificial intelligence scribes to alleviate the burden of clinical documentation. NEJM Catalyst Innovations in Care Delivery, 5(3). https://doi.org/10.1056/CAT.23.0404