Care coordination
When a patient moves between care settings, does their record follow, and which link in the exchange chain is weakest?
Roughly four in five eligible hospitals are penalized for excess 30-day readmissions every year. Excess-readmission ratios cluster just above the peer-group median, with hip and knee replacement highest.
The problem
Care coordination fails where the hospital landscape is most complex: patients with multiple chronic conditions move across acute care, specialists, post-acute care, primary care, and payers without a single accountable handoff model. The result is avoidable readmissions, duplicated work, and information gaps at exactly the moments when risk is highest.
The recommendation
Make coordination a reimbursed operating capability for complex patients. The recommended model is to standardize shared care plans, require reliable record exchange, assign transition accountability, and evaluate hospitals and Medicare programs on whether high-risk handoffs actually work.
The coordination load
How many patients carry enough chronic conditions to require multi-provider coordination, what that burden is made of, and whether it is growing.
Chronic-condition burden across Medicare, 2015
Share of Medicare fee-for-service beneficiaries by number of chronic conditions. The 40.5 percent with four or more, highlighted, need coordination across multiple providers.
Read it this way The 40.5 percent slice combining the 4-to-5 and 6-or-more segments represents beneficiaries whose care realistically spans multiple providers. This is a single 2015 snapshot of the whole Medicare fee-for-service population. It does not show how condition burden is distributed within any one region or plan. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| Chronic conditions | Share of beneficiaries (percent), 2015 |
|---|---|
| 0 to 1 conditions | 28.3 |
| 2 to 3 conditions | 31.1 |
| 4 to 5 conditions | 23.2 |
| 6 or more conditions | 17.3 |
CMS Chronic Conditions Warehouse, condition-count distribution · 2015 · source
Beneficiaries with 6 or more chronic conditions, over time
The most complex tier climbed from about 14 percent in 2010 to 17.3 percent in 2015.
Read it this way The line climbs steadily from 14.0 percent in 2010 to 17.3 percent in 2015 with no year showing a decline, supporting the claim that the most complex patient tier is growing. Because a 2022 figure is not published in the sources reviewed, the chart cannot show whether that climb continued at the same pace afterward. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat The 2022 value is not published in the sources reviewed, so it is not plotted. Pre-2015 figures use slightly different CMS definitions and are approximate. Partial 2022 data suggests the share has grown beyond 17.3 percent.
⊞ data table⬇ CSV
| Year | Beneficiaries with 6+ conditions (percent) |
|---|---|
| 2010 | 14 |
| 2011 | 14 |
| 2012 | 15 |
| 2015 | 17.3 |
CMS Chronic Conditions Chartbook and Goodman et al., Annals of Internal Medicine · 2015 · source
Most common chronic conditions among Medicare beneficiaries, 2022
Prevalence among Medicare fee-for-service beneficiaries, 2022. Hypertension and hyperlipidemia dominate the comorbidity mix that coordination must manage.
Read it this way Hypertension and hyperlipidemia dominate at 66.8 and 65.5 percent, each affecting roughly two-thirds of beneficiaries, which is why they anchor the comorbidity mix coordination has to manage. Two of the ten figures carry a caveat: ischemic heart disease uses a 2021 figure rather than 2022, and heart failure includes under-65 disabled enrollees, so treat comparisons involving those two conditions as approximate. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat Ischemic heart disease is a 2021 figure. Heart failure includes under-65 disabled enrollees. Depression rounds a CCW-reported 17.54 percent.
⊞ data table⬇ CSV
| Condition | Prevalence (percent), 2022 |
|---|---|
| Hypertension | 66.8 |
| Hyperlipidemia | 65.5 |
| Rheumatoid arthritis or osteoarthritis | 36.2 |
| Diabetes | 26.4 |
| Acquired hypothyroidism | 21.5 |
| Ischemic heart disease | 21.2 |
| Chronic kidney disease | 18.7 |
| Depression | 17.5 |
| COPD | 13.1 |
| Heart failure | 12 |
CMS Chronic Conditions Warehouse, Table B.2.a · 2022 · source
Chronic-condition prevalence, 2017 vs 2022
Prevalence in 2017 versus 2022 for conditions with both endpoints. Hyperlipidemia, benign prostatic hyperplasia, and osteoporosis rose, while hypertension, COPD, and dementia edged down.
Read it this way Hyperlipidemia, BPH, and osteoporosis rose over the five years while hypertension, COPD, and dementia edged down, so the comorbidity mix is shifting rather than growing uniformly across the board. Depression is left out because its 2017 figure isn't published, so this chart cannot speak to whether depression prevalence changed over the same period. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat Depression is excluded because its 2017 CCW value is not published. Benign prostatic hyperplasia is among male beneficiaries only.
⊞ data table⬇ CSV
| Condition | 2017 (percent) | 2022 (percent) |
|---|---|---|
| Hypertension | 67.8 | 66.8 |
| Hyperlipidemia | 61.3 | 65.5 |
| Benign prostatic hyperplasia (male only) | 25.4 | 29.1 |
| COPD | 15.9 | 13.1 |
| Osteoporosis | 9.9 | 11.7 |
| Non-Alzheimer's dementia | 8 | 7.4 |
| Stroke or TIA | 6.6 | 6.3 |
| Alzheimer's disease | 3.1 | 2.5 |
CMS Chronic Conditions Warehouse, Table B.2.a · 2022 · source
Does the record follow the patient?
Whether records move across care settings, whether the gap has stopped closing, and which link in the find-send-receive-integrate chain is the binding constraint.
Can exchange vs routinely does: the capability-practice gap
Capability to exchange across all four domains climbed to 70 percent and flattened, while routine use sits at 43 percent. That gap is the policy target.
Read it this way The 27-point gap between the capability line at 70 percent and the routine-use line at 43 percent in 2023 shows hospitals increasingly can exchange records across all four domains but mostly do not do so as routine practice. This chart identifies the size of that practice gap. It does not show why capable hospitals aren't using it routinely. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat The survey skipped 2020. Values are from the ONC and American Hospital Association Information Technology Supplement.
⊞ data table⬇ CSV
| Year | Capable all four (percent) | Routinely all four (percent) |
|---|---|---|
| 2018 | 46 | 28 |
| 2019 | 55 | 32 |
| 2021 | 62 | 29 |
| 2022 | 70 | 40 |
| 2023 | 70 | 43 |
ONC Data Brief, Interoperability among US Non-Federal Acute Care Hospitals · 2023 · source
Where the exchange chain breaks: find, send, receive, integrate
The four steps of a record handoff. Sending is near universal at 92 percent and Receive follows at 87 percent. Finding a record at 84 percent and integrating it at 78 percent lag furthest, so those are the binding constraints.
Read it this way Send sits highest at 92 percent and Receive follows at 87 percent, while Find at 84 percent and Integrate at 78 percent lag furthest behind, so those two steps are where a record handoff is most likely to break down. This is a national average across all four steps. It does not show whether the same hospitals struggle with both Find and Integrate or whether different hospitals are weak on different steps. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| Year | Find | Send | Receive | Integrate |
|---|---|---|---|---|
| 2018 | 65 | 89 | 78 | 62 |
| 2019 | 72 | 90 | 81 | 71 |
| 2021 | 78 | 91 | 84 | 74 |
| 2022 | 84 | 93 | 87 | 79 |
| 2023 | 84 | 92 | 87 | 78 |
ONC Data Brief, Interoperability among US Non-Federal Acute Care Hospitals · 2023 · source
Why it still fragments
Who is accused of blocking information sharing and at what volume, and which states have wired their hospitals into health information networks.
Information-blocking claims, by type of accused actor
Share of claims by accused actor. Providers are named in 81.8 percent, reframing the vendors-lock-data story toward provider-side behavior.
Read it this way Providers are named in 81.8 percent of claims versus 17.2 percent for health IT developers, which cuts against a story where vendors are the primary source of blocked information. These are unverified allegations, not adjudicated findings, and a single claim can name more than one actor, so the shares describe who gets accused, not who is proven at fault. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat These are unverified allegations, not adjudicated findings, and a single claim can name more than one actor. Shares are of identifiable actor associations.
⊞ data table⬇ CSV
| Accused actor type | Share of claims (percent) | Claim count |
|---|---|---|
| Health care provider | 81.8 | 1694 |
| Health IT developer | 17.2 | 357 |
| Health information network | 1 | 20 |
ONC Information Blocking Claims Portal, Health IT Feedback · 2026 · source
Share of hospitals participating in an HIO, by state
Each tile is one state. Deeper fill is more connected. The national average is 81.5 percent. Laggards include New Hampshire at 23.8 percent, South Carolina at 51.3, and Alabama at 56.1.
Read it this way Most states cluster well above the 81.5 percent national benchmark, several near 100 percent, while New Hampshire at 23.8 percent stands out as a clear outlier alongside South Carolina at 51.3 and Alabama at 56.1. This map shows HIO participation only. A state near 100 percent here is not necessarily also near the top on the TEFCA map next to it. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| State | Hospitals in an HIO (percent) |
|---|---|
| New Hampshire | 23.8 |
| South Carolina | 51.3 |
| Alabama | 56.1 |
| Illinois | 57 |
| Idaho | 63 |
| Texas | 63.4 |
| Georgia | 66.7 |
| Oklahoma | 68.2 |
| Minnesota | 69.1 |
| Tennessee | 69.1 |
| Montana | 69.8 |
| New Mexico | 70.8 |
| Washington | 72.1 |
| Nevada | 73.9 |
| Wyoming | 75 |
| Mississippi | 75.8 |
| North Dakota | 76.7 |
| Oregon | 77.3 |
| Louisiana | 78.6 |
| California | 79.9 |
| Florida | 80.5 |
| Kansas | 84.1 |
| Pennsylvania | 84.4 |
| Missouri | 85.8 |
| Wisconsin | 89.1 |
| Arkansas | 89.8 |
| Utah | 90.2 |
| West Virginia | 90.5 |
| Iowa | 90.8 |
| Colorado | 91.3 |
| Ohio | 91.4 |
| Hawaii | 92.3 |
| Michigan | 93.5 |
| Nebraska | 94.6 |
| Indiana | 95.7 |
| New York | 96.6 |
| North Carolina | 96.6 |
| Massachusetts | 97.6 |
| Arizona | 98 |
| New Jersey | 98.1 |
| Kentucky | 98.5 |
| Virginia | 98.6 |
| Alaska | 100 |
| Connecticut | 100 |
| Delaware | 100 |
| District of Columbia | 100 |
| Maine | 100 |
| Maryland | 100 |
| Rhode Island | 100 |
| South Dakota | 100 |
| Vermont | 100 |
ONC, Hospital Health Information Exchange and TEFCA Participation · 2025 · source
State hospitals participating in TEFCA, ranked
Each dot is one state's share of hospitals participating in TEFCA. The line marks the national rate of 34.3 percent. Florida, Maryland, and DC lead while Delaware and North Dakota sit at 0.
Read it this way TEFCA participation ranges from Florida's 66.4 percent down to Delaware and North Dakota at 0 percent, around a national rate of just 34.3 percent, well below HIO participation. Compare this against the HIO tile map rather than assuming the two track together: several states with near-universal HIO participation still show low TEFCA adoption, since the two systems are largely uncorrelated. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| State | Hospitals in TEFCA (percent) |
|---|---|
| Florida | 66.4 |
| Maryland | 61.9 |
| District of Columbia | 60 |
| Maine | 55.6 |
| Vermont | 54.5 |
| North Carolina | 53.4 |
| Idaho | 51.9 |
| South Carolina | 51.3 |
| Georgia | 51.1 |
| Rhode Island | 50 |
| Virginia | 50 |
| Massachusetts | 48.8 |
| Wisconsin | 48.5 |
| West Virginia | 47.6 |
| Hawaii | 46.2 |
| New Mexico | 45.8 |
| Michigan | 45.2 |
| Colorado | 43.5 |
| Kansas | 43.2 |
| Louisiana | 42.9 |
| Illinois | 40.1 |
| Mississippi | 38.7 |
| New Jersey | 38.5 |
| Minnesota | 36.2 |
| Pennsylvania | 35.8 |
| Indiana | 34.8 |
| Tennessee | 33.8 |
| Ohio | 33.6 |
| Connecticut | 33.3 |
| Arkansas | 32.2 |
| Missouri | 32.1 |
| Oregon | 31.8 |
| New York | 27.1 |
| Utah | 26.8 |
| Iowa | 26.6 |
| Nevada | 26.1 |
| Alabama | 24.4 |
| Montana | 23.3 |
| California | 20.1 |
| Kentucky | 19.7 |
| Washington | 19.7 |
| Texas | 19.5 |
| New Hampshire | 19 |
| Oklahoma | 16.7 |
| Nebraska | 16.1 |
| Wyoming | 15 |
| Alaska | 14.3 |
| South Dakota | 11.4 |
| Arizona | 10.2 |
| Delaware | 0 |
| North Dakota | 0 |
ONC, Hospital Health Information Exchange and TEFCA Participation · 2025 · source
Readmissions, the outcome proxy
Neither file carries a patient-level handoff-outcome metric, so the CMS readmissions program stays on as the fourth lens, the downstream symptom of poor coordination.
Excess readmission ratio by condition, FY2024
Ratio of predicted to expected 30-day readmissions. A value above 1.0 means more readmissions than expected for similar patients. Hip and knee replacement is highest.
Read it this way All six ratios sit only fractionally above the 1.0 peer-group median, from 1.0008 for COPD to 1.0052 for hip and knee replacement, so no single condition is dramatically driving excess readmissions. This tightness shows hospitals cluster close to the benchmark, but it does not say whether that benchmark itself is demanding or lenient. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| Condition | FY2024 mean excess readmission ratio |
|---|---|
| Hip and knee replacement | 1.0052 |
| CABG surgery | 1.0028 |
| Heart failure | 1.0016 |
| Pneumonia | 1.0016 |
| Heart attack (AMI) | 1.0012 |
| COPD | 1.0008 |
CMS Hospital Readmissions Reduction Program Dataset · FY2024 · source
Share of eligible hospitals penalized for readmissions
Percent of eligible hospitals docked under the readmissions program each program year. The rate has stayed near 80 percent since FY2018.
Read it this way The penalized share stays near 80 percent every year except FY2023, when it drops to 75 percent because of COVID-19 measurement adjustments, including the excluded pneumonia measure that year, not because hospitals suddenly performed better. Read the FY2023 dip as a measurement artifact rather than a real one-year improvement. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
Caveat The FY2023 dip reflects COVID-19 measurement adjustments, including exclusion of the pneumonia measure that year.
⊞ data table⬇ CSV
| Program year | Hospitals penalized (percent) |
|---|---|
| FY2018 | 79 |
| FY2019 | 82 |
| FY2020 | 83 |
| FY2021 | 83 |
| FY2022 | 82 |
| FY2023 | 75 |
| FY2024 | 78 |
CMS QualityNet, HRRP Overview · FY2024 · source
Total readmission penalties, years with published totals
Estimated total dollars withheld across all penalized hospitals. Only years with a publicly aggregated total are shown.
Read it this way Total withheld penalties fell from 564 million dollars in FY2018 to 320 million in FY2023, but only these four years have a publicly aggregated total, so this is not a complete year-by-year series and the drop could partly reflect which years happen to be published rather than a true trend. Use this chart to see which coordination failure is being measured, patient complexity, readmissions, or information flow, and how it supports the recommendation for accountable handoffs.
⊞ data table⬇ CSV
| Program year | Total penalties (USD millions) |
|---|---|
| FY2018 | 564 |
| FY2020 | 563 |
| FY2022 | 521 |
| FY2023 | 320 |
KFF, 10 Years of Hospital Readmissions Penalties · FY2023 · source
Geography
The same question, state by state and then county by county. Pick a state in the filter above to drill into its counties.
Diabetes prevalence
County · modeled prevalence (95% CI)Each tile is a state. Pick a state in the Scope control above to drill into its counties.
CDC PLACES (model-based small-area estimates) · 2024 · source
High blood pressure
County · modeled prevalence (95% CI)Each tile is a state. Pick a state in the Scope control above to drill into its counties.
CDC PLACES (model-based small-area estimates) · 2024 · source
Why this matters
The exchange chain itself is uneven: sending records is nearly universal at 92 percent, but finding a patient's record, 84 percent, and integrating it into the receiving clinician's workflow, 78 percent, lag furthest behind, meaning even when data moves it often does not land usably. Meanwhile the readmissions penalty program, the closest outcome proxy in this data, keeps penalizing a nearly fixed 78 to 83 percent of hospitals every year while excess-readmission ratios cluster only marginally above 1.0, which shows the program measures relative standing more than it proves coordination is or is not actually improving.
Recommended actions
- Target the Find and Integrate steps of the exchange chain specifically, since they trail Send and Receive by 8 to 14 points and are the likeliest points where a handoff breaks down.
- Monitor the 27-point capability-to-routine-use gap, 70 percent capable versus 43 percent routine, as the key KPI. Closing that gap is the near-term opportunity, not raising capability further.
- Shift oversight attention toward provider-side information-blocking behavior, since 81.8 percent of logged claims name providers rather than health IT developers.
- Watch state-level HIO and TEFCA participation for laggards, New Hampshire at 23.8 percent HIO participation and Delaware and North Dakota at 0 percent TEFCA participation, as targets for federal outreach.
- Track the growing multi-morbidity tier, 17.3 percent with six or more conditions and rising, as the demand-side pressure that makes closing the exchange gap more urgent each year.
The recommendation
Therefore, make coordination a reimbursed operating capability for complex patients. The recommended model is to standardize shared care plans, require reliable record exchange, assign transition accountability, and evaluate hospitals and Medicare programs on whether high-risk handoffs actually work.
Demographic slice none. CMS HRRP/Care Compare public files are hospital/condition-level.
Sources
- CMS Chronic Conditions Warehouse, Medicare beneficiary prevalence · 2022
- Goodman et al., Multimorbidity in Medicare, Annals of Internal Medicine · 2019
- ONC Data Brief, Interoperability among US Non-Federal Acute Care Hospitals · 2023
- ONC Information Blocking Claims Portal, Health IT Feedback · 2026
- ONC, Hospital Health Information Exchange and TEFCA Participation · 2025
- CMS Hospital Readmissions Reduction Program Dataset · FY2024
- CMS QualityNet, HRRP Overview · 2024
- KFF, 10 Years of Hospital Readmissions Penalties · 2021