Documentation Burden: What Primary Research Shows and Where Administrative Support Fits

Question: What does primary research measure about documentation and desk workload in clinical settings, and what does that evidence suggest about the kinds of administrative work that can reasonably be supported by a dedicated role?

Type: Sourced desk research.

Method

This review reads peer-reviewed studies retrieved through PubMed that directly measure time spent on documentation, electronic health record (EHR) work, or desk work by clinicians. Studies were selected for having a stated design, population, and quantitative result. The sources are reported with their scale so that confidence in each claim is visible.

Sources reviewed:

1. Sinsky C, et al. "Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties." Ann Intern Med. 2016;165(11):753-760. PMID 27595430.
2. Arndt BG, et al. "Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations." Ann Fam Med. 2017;15(5):419-426. PMID 28893811.
3. Overhage JM, Johnson KB. "Pediatrician Electronic Health Record Time Use for Outpatient Encounters." Pediatrics. 2020;146(6):e20194017. PMID 33139456.
4. Togunwa TO, Platt J. "Ambient AI Scribes as Emerging Infrastructure in the Learning Health System." Learn Health Syst. 2026;10(4):e70115. PMID 42578243.
5. Downing NL, Bates DW, Longhurst CA. "Physician Burnout in the Electronic Health Record Era: Are We Ignoring the Real Cause?" Ann Intern Med. 2018;169(1):50-51. PMID 29801050. (Viewpoint, used only for context.)

Source facts and interpretation are labeled separately. None of these studies examines peptide businesses specifically, and none evaluates a staffing intervention; the relevance to administrative support is an inference.

What the studies measured

Physicians spent roughly half the office day on EHR and desk work. Sinsky et al. observed 57 physicians in family medicine, internal medicine, cardiology, and orthopedics across four states for 430 hours, with after-hours diaries from 21 physicians. During the office day, physicians spent 27.0 percent of total time on direct clinical face time and 49.2 percent on EHR and desk work. In the examination room, 52.9 percent of time was direct face time and 37.0 percent was EHR and desk work. The after-hours diaries reported one to two hours of additional work each night, mostly EHR tasks. The authors note the practices were self-selected and high-performing and that the descriptive design did not support formal statistical comparisons. (Source facts.)

EHR event logs showed nearly six hours per weekday, with a large delegable share. Arndt et al. conducted a retrospective cohort study of 142 family medicine physicians in a single southern Wisconsin system, capturing EHR event logs over three years and validating them with direct observation. Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for 157 minutes (44.2 percent); inbox management accounted for another 85 minutes (23.7 percent). The authors concluded that EHR event logs can identify areas of EHR-related work that could be delegated. (Source facts.)

Per-encounter EHR time averaged about 16 minutes for pediatricians. Overhage and Johnson analyzed more than 20 million encounters by almost 30,000 physicians from 417 health systems using software log files for calendar year 2018. Pediatric physicians spent an average of 16 minutes per encounter in the EHR; chart review (31 percent), documentation (31 percent), and ordering (13 percent) accounted for most of the time. The authors reported wide variation within subspecialty and similar patterns across specialties, and noted data limitations prevented examining geographic or system-specific variation. (Source facts.)

Ambient documentation tools report early benefits but carry documented risks. Togunwa and Platt describe ambient AI scribes as systems that generate clinical documentation from clinician-patient conversations, being deployed at an accelerating pace. They state that early evaluations report reduced documentation burden, improved clinician well-being, and perceived efficiency gains, while cautioning that these systems can introduce systematic documentation errors — including hallucinated clinical details, omission of safety-critical information, and differential performance across patient populations — that may propagate downstream. (Source facts.) This source concerns AI documentation tools, not remote human administrative staff, so it should not be read as evidence about staffing. (Interpretation.)

Findings

1. Documentation and desk work consume a large, measured share of clinical time. Two independent studies using different methods (time and motion; EHR event logs) converge on roughly half of the workday devoted to EHR and desk work, with additional after-hours time. (Synthesis of Sinsky et al. and Arndt et al.)
2. A substantial portion of that work is clerical and administrative by the studies' own categorization. Arndt et al. classify documentation, order entry, billing and coding, and system security as clerical and administrative tasks, and report inbox management separately. Those categories are where administrative support is most plausibly relevant. (Synthesis; interpretation.)
3. The studies explicitly point toward delegation, but do not test it. Arndt et al. conclude that event logs can identify work that could be delegated; that is a hypothesis about delegation, not an evaluation of a delegated role. (Source fact; interpretation.)
4. Ordering and clinical judgment remain clinical. Overhage and Johnson found ordering accounted for 13 percent of per-encounter EHR time. Ordering, clinical interpretation, and documentation content that reflects clinical reasoning are not administrative work and should remain with licensed professionals. (Synthesis; interpretation.)
5. Documentation quality is not automatically improved by shifting effort. The ambient-scribe review documents risks of systematic documentation error. Any arrangement that changes who performs documentation needs a quality check, whether the work is done by software or by people. (Synthesis of Togunwa and Platt.)

Operational implications

For a peptide business weighing administrative support, the reviewed evidence supports a careful division:

• Support administrative and clerical work, not clinical reasoning. Billing and coding support, order-entry preparation, inbox triage and routing, records requests, and documentation routing are the categories the studies identify as clerical. Clinicians should retain clinical content, ordering decisions, and interpretation.
• Measure before and after. Because no reviewed study evaluates a staffing intervention, a local measurement is the only way to know whether support helps. Track inbox turnover, documentation backlog, and after-hours work.
• Protect documentation quality with review. Apply a sampled quality check to any documentation-related work, consistent with the caution in the ambient-scribe review.
• Be precise about claims. It is defensible to say that studies measure large documentation and desk workloads with delegable administrative components. It is not supported to claim that a specific staffing arrangement reduces burnout or improves care, because the reviewed studies did not test that.
• Treat after-hours work as a signal. Both Sinsky et al. and Arndt et al. document after-hours EHR time; measuring it locally is a reasonable indicator of whether administrative capacity is adequate.

A proposed measurement framework (not sourced) is to record, for a baseline period and again after any change: minutes of after-hours documentation work per clinician per week, inbox items per day and their median age, documentation backlog count, and a sampled documentation-quality score. These measures connect the published findings to a specific operation without overstating what the literature proves.

Limitations

All reviewed studies concern physicians in selected U.S. practices and systems, not peptide clinics, labs, or administrative staff, so generalizing to a peptide business requires caution. Sinsky et al. is descriptive, based in self-selected high-performing practices, and not statistically powered for subgroup comparisons. Arndt et al. studied one health system and one EHR vendor. Overhage and Johnson used log data with acknowledged limitations and could not examine geographic variation. Togunwa and Platt is a conceptual review of AI scribes, not a study of human administrative staffing. Downing et al. is a viewpoint used only for context. This review is purposive rather than systematic, and the delegation implications are interpretations that would need local testing. Nothing here is medical advice, and nothing here supports the idea that administrative staff make clinical decisions.

Sources

• Sinsky C, et al. Allocation of Physician Time in Ambulatory Practice. Ann Intern Med. 2016;165(11):753-760. https://pubmed.ncbi.nlm.nih.gov/27595430/
• Arndt BG, et al. Tethered to the EHR. Ann Fam Med. 2017;15(5):419-426. https://pubmed.ncbi.nlm.nih.gov/28893811/
• Overhage JM, Johnson KB. Pediatrician Electronic Health Record Time Use for Outpatient Encounters. Pediatrics. 2020;146(6):e20194017. https://pubmed.ncbi.nlm.nih.gov/33139456/
• Togunwa TO, Platt J. Ambient AI Scribes as Emerging Infrastructure in the Learning Health System. Learn Health Syst. 2026;10(4):e70115. https://pubmed.ncbi.nlm.nih.gov/42578243/
• Downing NL, Bates DW, Longhurst CA. Physician Burnout in the Electronic Health Record Era. Ann Intern Med. 2018;169(1):50-51. https://pubmed.ncbi.nlm.nih.gov/29801050/