Educational note: This article discusses compensation and promotion implications of faculty workload data for general educational purposes only. It is not financial, legal, tax, employment contract, or human resources advice. Institutional policies vary, and readers should consult qualified advisors, faculty affairs leaders, or legal/tax professionals for guidance specific to their situation.
Academic medicine loves broad labels and bad comparisons. “MDs teach more.” “PhDs do all the committee work.” Nice hallway talk. Weak analysis.
The data shows that teaching and service metrics are measurable, but only if you define them correctly. On the teaching side, the common units are clerkship hours, lecture counts, lab sessions, small-group facilitation, course leadership roles, mentoring load, and recurring assignments across semesters. On the service side, the standard buckets are committee membership, admissions work, interview days, faculty governance, curriculum redesign, task-force participation, trainee advocacy, and community outreach. If you do not separate those categories, your comparison is already broken.
I have seen this mistake in faculty review meetings more times than I care to count. Someone presents raw totals as if all hours are equivalent. They are not. A 2-hour bedside session with rotating third-years is not the same operationally as a 2-hour preclinical lecture block repeated every fall. A seat on the promotions committee is not the same as running a curriculum overhaul for 8 months while answering everyone’s email. Same label. Different burden.
The real problem is confounding. MDs and PhDs are rarely hired into interchangeable jobs. Department type matters. Rank matters. Promotion track matters. Protected time matters most of all. A clinician with 0.7 clinical FTE and fragmented teaching time will almost always show a different metric pattern than a PhD with a formal education role and scheduled course ownership. That does not mean one contributes more. It means the work is organized differently.
So this article takes the cleaner route: averages, distributions, and recurring patterns. Less anecdote. More signal.
Teaching Metrics: Where MDs and PhDs Tend to Differ
The data shows a clear split in teaching format. MDs usually contribute more bedside teaching, clerkship supervision, case-based conferences, and procedural instruction. PhDs usually contribute more scheduled lectures, preclinical blocks, laboratory teaching, and structured foundational science sessions. That pattern is durable across many academic health centers because it tracks with role design, not personality.
A useful illustrative comparison looks like this:
MD faculty
- Higher clinical teaching exposure
- More ad hoc learner contact
- Greater involvement in clerkships, wards, and ambulatory precepting
- Lower predictability of teaching schedule
PhD faculty
- Higher concentration of formal classroom teaching
- More recurring lectures and small-group assignments
- Greater likelihood of course/module leadership in preclinical education
- Higher schedule density during teaching blocks
Those values are illustrative, but the pattern is realistic. The average MD may log fewer total scheduled teaching hours than the average PhD, yet still have substantial learner contact through bedside and clinical supervision that is difficult to capture cleanly. That is where institutions get sloppy. They count scheduled lectures precisely and undercount live clinical teaching because it is embedded in service delivery. Bad measurement leads to bad conclusions.
Student evaluation data is more interesting than people expect. Teaching quantity differs more than teaching quality. In many programs, learner ratings cluster tightly once you adjust for setting. A polished PhD lecturer in physiology and an experienced MD leading a medicine small group may both score in the same high band, say 4.4 to 4.7 on a 5-point scale. The difference is usually not who teaches “better.” It is who gets assigned what kind of teaching, how often, and under what constraints.
Clinical workload suppresses MD teaching volume. That is not a moral failing. It is arithmetic. A faculty internist with packed clinic templates, inpatient weeks, and inbox spillover cannot simply add 40 more lecture hours because a dean likes the idea of “more educational engagement.” The hours have to come from somewhere. Usually evenings. Usually weekends. Usually burnout.
PhDs, by contrast, often have teaching built directly into the appointment structure. The data shows higher scheduled density: more repeated lectures, more organized small groups, more formal assessment work, and more predictable teaching cycles. I have seen PhD faculty deliver the same foundational content to 180 students, revise exam blueprints, lead review sessions, and still have that work treated as routine. It is not routine. It is heavy instructional production.
Another useful metric is recurrence. MD teaching is often episodic and tied to service rotations. PhD teaching is more likely to recur semester after semester. That matters because recurring assignments create invisible labor: slide revision, LMS updates, assessment calibration, coordination with block directors, and student follow-up. Institutions love to ignore this because recurring work looks stable on a spreadsheet. Stable does not mean small.
The clean read is this: MDs often have broader clinical teaching reach, while PhDs often carry denser formal instructional loads. Raw hour comparisons miss that split.
Service Metrics: Committee Work, Leadership, and Institutional Citizenship
Service data is messier. Always. The data shows far more variability in service than in teaching because committee work and institutional citizenship follow a long-tail pattern. A modest subset of faculty carry a ridiculous share of the load. Everyone in academic medicine knows who they are. The same names on admissions. Curriculum. Promotions. Search committees. Diversity task forces. Problem-solving groups no one wanted until a crisis started.
MDs are often pulled toward clinically linked service:
- quality and safety committees
- credentialing or peer review
- hospital operations groups
- patient care pathway redesign
- residency and clerkship interview panels
PhDs are often overrepresented in:
- curriculum committees
- faculty senate or governance bodies
- research oversight groups
- graduate and preclinical education leadership
- assessment and accreditation work
That split makes sense. It is not random. It reflects domain expertise and institutional demand.
But visible service is only half the story. Hidden service distorts almost every workload report. Informal mentoring. Student rescue work. Writing letters at the last minute. Smoothing over departmental conflict. Troubleshooting course logistics when someone else drops the ball. I have watched a senior PhD faculty member spend six unlogged hours in one week helping struggling students prepare for remediation, then get “credited” only for the monthly committee meeting on paper. I have watched MD clerkship leaders absorb trainee complaints, schedule chaos, and hospital-site politics while their formal service count stayed at one committee. That is fake accounting.
The distribution also differs by role seniority. Junior faculty often have lighter official service portfolios, while midcareer and senior faculty accumulate memberships and leadership titles rapidly. The result is service compression: a handful of reliable people become institutional shock absorbers.
Service should be measured in categories, not just counts:
- number of committees
- leadership status within each committee
- hours per month
- cyclical intensity, such as admissions season or accreditation year
- hidden advising and mentoring activity
- outcome responsibility, not just attendance
If you only count seats, you reward decorative service and miss operational service. That is dumb. A faculty member who attends four low-intensity meetings is not necessarily doing more than one person running a major curricular transition.
The Data Behind Distribution: Averages, Ranges, and Outliers
If you use means alone, you will get fooled. The data shows that median is often the better summary statistic for service metrics because a few high-service faculty can inflate the average dramatically.
Take committee membership. In an illustrative department, the mean for MD faculty might be 3.2 committees, while the median is 2. That gap tells you a few people are carrying oversized portfolios. For PhD faculty, the mean might be 3.8 and the median 3. Same story, slightly less skew. Means are useful, but medians tell you what is typical.
Ranges matter because variation by institution and department is huge. In surgery, medicine, and obstetrics, MD teaching can be highly intensive but irregular, often clustered around service blocks. In anatomy, physiology, and pharmacology, PhD teaching can be concentrated, recurring, and tied to course ownership. Promotion track changes the numbers again. Research-heavy faculty, whether MD or PhD, often have lower service loads by design. Educator-track faculty often carry the opposite pattern.
The outliers are easy to spot once you look correctly:
- Clinician-educator MDs with very high teaching volume and high service load, often serving as clerkship or program leaders while maintaining substantial clinical duties.
- Education-focused PhDs with concentrated lecture and course leadership responsibilities plus major committee work around curriculum and assessment.
- Research-heavy PhDs with modest service counts but high-impact teaching in specialized blocks.
- Administrative MD leaders whose service hours explode once they step into division, program, or hospital roles.
I have seen annual reviews where two faculty looked “equal” on raw totals and were nowhere near equal after adjustment. One had 180 teaching hours at 1.0 academic FTE. Another had 110 teaching hours while carrying 0.6 clinical effort and a major clerkship role. Those are not comparable outputs without normalization.
Adjustment variables are not optional:
- FTE split
- protected time
- academic track
- rank
- department type
- course ownership versus session-level participation
Skip those, and the analysis is junk.
What the Data Means for Promotion, Recognition, and Workload Equity
This is where the numbers become policy. The data shows that promotion systems often reward teaching intensity and service breadth unevenly, and the imbalance can cut against both MDs and PhDs.
For MDs, the risk is overextension. Clinical productivity remains the dominant demand in many departments, yet those same faculty are also expected to supervise learners, sit on committees, interview applicants, and lead educational fixes when something breaks. Recognition lags behind actual labor. I have seen faculty praised for “dedication” right before being handed another committee. That is not recognition. That is extraction with polite wording.
For PhDs, the risk is underrecognition of high-volume teaching. Repeated lectures, assessment design, course administration, remediation support, and committee-heavy education service can consume enormous time, but because the work is scheduled and familiar, leaders often treat it as background noise. It is not background. It is infrastructure.
The cleanest workload equity measures are ratio-based:
- Service burden per protected hour
- Teaching assignments per 0.1 FTE
- Course leadership roles per faculty line
- Recognition events or promotion credit per contribution category
- Hidden mentoring hours per formal advising title
Those ratios expose distortions quickly. A department may discover that MDs average fewer formal teaching hours but far higher teaching burden per nonclinical hour. Or that PhDs carry more recurring instructional sessions per FTE with no corresponding increase in title, pay band, or promotion speed. The spreadsheet usually tells the truth once someone has the nerve to build it.
Because these workload patterns can affect pay, bonuses, promotion timing, and leadership opportunities, departments should be careful not to infer compensation fairness from a single metric. Teaching-heavy and service-heavy roles are valued differently across institutions, and compensation models may include clinical revenue, grant support, administrative stipends, incentives, or protected-time arrangements that are not visible in a simple dashboard.
Good departmental practice is not mysterious:
- Audit teaching and service annually.
- Separate teaching by format, not just total hours.
- Track visible and hidden service.
- Normalize by FTE and protected time.
- Review distribution by rank, degree type, and track.
- Tie recognition and promotion criteria to actual workload.
Transparent assignment tracking is especially powerful. Once faculty can see who is doing what, mythology dies fast. The person with one committee title may actually be doing 4 times the work of someone with three memberships. The clerkship lead answering student issues at 9:30 p.m. is not “less engaged” because they gave fewer lectures. The PhD who runs the exam blueprint, teaches every block, and mentors remediation students is not “just teaching.” That phrase should be banned.
Direct Bottom Line
The data shows that MDs and PhDs differ more in the type, timing, and distribution of teaching and service than in overall commitment to academic citizenship. That is the real finding. Not who cares more. Not who works harder in some cartoonish universal sense. The work is structured differently, counted differently, and too often rewarded badly.
Raw counts are weak evidence. Normalized, role-adjusted metrics are the only comparison worth trusting. Use medians, ranges, and FTE-adjusted rates. Separate bedside teaching from classroom teaching. Separate committee membership from committee leadership. Count hidden service or admit you are not measuring service honestly.
If you are an applicant, ask for numbers. Teaching hours. Committee load. Protected time. Promotion criteria. If a department cannot show you that data, assume the workload system is opaque for a reason.
If you are a department leader, stop managing by folklore. Build the dashboard. Audit the distribution. Reward the work that actually keeps the institution running.
