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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.

Question

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.

17.3%
Medicare beneficiaries with 6 or more chronic conditions, 2015 and rising
Up from about 14 percent in 2010.
40.5%
Medicare beneficiaries with 4 or more chronic conditions, 2015
About 45 percent by 2022 in partial data. These patients cannot be managed inside one clinic.

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.

40.5% HAVE 4+ CONDITIONS 0 to 1 conditions 28.3% · 28% 2 to 3 conditions 31.1% · 31% 4 to 5 conditions 23.2% · 23% 6 or more conditions 17.3% · 17%
⊞ data table⬇ CSV
Chronic conditionsShare of beneficiaries (percent), 2015
0 to 1 conditions28.3
2 to 3 conditions31.1
4 to 5 conditions23.2
6 or more conditions17.3

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.

0% 5% 10% 15% 20% 2010201120122015 6+ conditions YEAR BENEFICIARIES WITH 6+ CONDITIONS (PERCENT)
⊞ data table⬇ CSV
YearBeneficiaries with 6+ conditions (percent)
201014
201114
201215
201517.3

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.

0.0% 25.0% 50.0% 75.0% 100.0% Hypertension 66.8% Hyperlipidemia 65.5% Arthritis (RA or OA) 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 12.0%
⊞ data table⬇ CSV
ConditionPrevalence (percent), 2022
Hypertension66.8
Hyperlipidemia65.5
Rheumatoid arthritis or osteoarthritis36.2
Diabetes26.4
Acquired hypothyroidism21.5
Ischemic heart disease21.2
Chronic kidney disease18.7
Depression17.5
COPD13.1
Heart failure12

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.

43%
Hospitals that routinely exchange records across all four domains, 2023
Find, send, receive, and integrate, as routine practice.
70%
Hospitals capable of exchanging across all four domains, 2022 and 2023
Capability plateaued at 70 percent while routine use sits at 43 percent, a 27-point gap.

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.

0% 25% 50% 75% 100% 20182019202120222023 Capable all fourRoutinely all four YEAR HOSPITALS (PERCENT)
⊞ data table⬇ CSV
YearCapable all four (percent)Routinely all four (percent)
20184628
20195532
20216229
20227040
20237043

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.

0% 25% 50% 75% 100% 20182019202120222023 SendReceiveFindIntegrate YEAR HOSPITALS (PERCENT)
⊞ data table⬇ CSV
YearFindSendReceiveIntegrate
201865897862
201972908171
202178918474
202284938779
202384928778

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.

2,124
Information-blocking claims logged with ONC, April 2021 to May 2026
Thousands of live complaints, not a rounding error.
81.5%
US hospitals participating in a health information organization, 2022 to 2025
But participation ranges from 23.8 percent in New Hampshire to 100 percent in several states.
34.3%
US hospitals participating in TEFCA, the new federal exchange framework
Adoption is uneven and largely uncorrelated with HIO maturity.

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.

81.8% PROVIDERS Health care provider 81.8% · 82% Health IT developer 17.2% · 17% Health information network 1.0% · 1%
⊞ data table⬇ CSV
Accused actor typeShare of claims (percent)Claim count
Health care provider81.81694
Health IT developer17.2357
Health information network120

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.

AK 100.0% ME 100.0% WA 72.1% ID 63.0% MT 69.8% ND 76.7% MN 69.1% WI 89.1% MI 93.5% NY 96.6% VT 100.0% NH 23.8% OR 77.3% NV 73.9% WY 75.0% SD 100.0% IA 90.8% IL 57.0% IN 95.7% OH 91.4% PA 84.4% NJ 98.1% MA 97.6% CA 79.9% UT 90.2% CO 91.3% NE 94.6% MO 85.8% KY 98.5% WV 90.5% VA 98.6% MD 100.0% CT 100.0% RI 100.0% AZ 98.0% NM 70.8% KS 84.1% AR 89.8% TN 69.1% NC 96.6% SC 51.3% DC 100.0% DE 100.0% OK 68.2% LA 78.6% MS 75.8% AL 56.1% GA 66.7% TX 63.4% FL 80.5% HI 92.3% 0.0% 100.0%
⊞ data table⬇ CSV
StateHospitals in an HIO (percent)
New Hampshire23.8
South Carolina51.3
Alabama56.1
Illinois57
Idaho63
Texas63.4
Georgia66.7
Oklahoma68.2
Minnesota69.1
Tennessee69.1
Montana69.8
New Mexico70.8
Washington72.1
Nevada73.9
Wyoming75
Mississippi75.8
North Dakota76.7
Oregon77.3
Louisiana78.6
California79.9
Florida80.5
Kansas84.1
Pennsylvania84.4
Missouri85.8
Wisconsin89.1
Arkansas89.8
Utah90.2
West Virginia90.5
Iowa90.8
Colorado91.3
Ohio91.4
Hawaii92.3
Michigan93.5
Nebraska94.6
Indiana95.7
New York96.6
North Carolina96.6
Massachusetts97.6
Arizona98
New Jersey98.1
Kentucky98.5
Virginia98.6
Alaska100
Connecticut100
Delaware100
District of Columbia100
Maine100
Maryland100
Rhode Island100
South Dakota100
Vermont100

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.

0.0% 25.0% 50.0% 75.0% 100.0% Florida 66.4% Maryland 61.9% District of Columbia 60.0% Maine 55.6% Vermont 54.5% North Carolina 53.4% Idaho 51.9% South Carolina 51.3% Georgia 51.1% Rhode Island 50.0% Virginia 50.0% 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 19.0% Oklahoma 16.7% Nebraska 16.1% Wyoming 15.0% Alaska 14.3% South Dakota 11.4% Arizona 10.2% Delaware 0.0% North Dakota 0.0% National rate
⊞ data table⬇ CSV
StateHospitals in TEFCA (percent)
Florida66.4
Maryland61.9
District of Columbia60
Maine55.6
Vermont54.5
North Carolina53.4
Idaho51.9
South Carolina51.3
Georgia51.1
Rhode Island50
Virginia50
Massachusetts48.8
Wisconsin48.5
West Virginia47.6
Hawaii46.2
New Mexico45.8
Michigan45.2
Colorado43.5
Kansas43.2
Louisiana42.9
Illinois40.1
Mississippi38.7
New Jersey38.5
Minnesota36.2
Pennsylvania35.8
Indiana34.8
Tennessee33.8
Ohio33.6
Connecticut33.3
Arkansas32.2
Missouri32.1
Oregon31.8
New York27.1
Utah26.8
Iowa26.6
Nevada26.1
Alabama24.4
Montana23.3
California20.1
Kentucky19.7
Washington19.7
Texas19.5
New Hampshire19
Oklahoma16.7
Nebraska16.1
Wyoming15
Alaska14.3
South Dakota11.4
Arizona10.2
Delaware0
North Dakota0

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.

0.0 0.5 1.0 1.5 2.0 Hip and knee replacement 1.0052 1.0 CABG surgery 1.0028 1.0 Heart failure 1.0016 1.0 Pneumonia 1.0016 1.0 Heart attack (AMI) 1.0012 1.0 COPD 1.0008 1.0 Peer-group median (ERR = 1.0)
⊞ data table⬇ CSV
ConditionFY2024 mean excess readmission ratio
Hip and knee replacement1.0052
CABG surgery1.0028
Heart failure1.0016
Pneumonia1.0016
Heart attack (AMI)1.0012
COPD1.0008

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.

0% 25% 50% 75% 100% FY2018FY2019FY2020FY2021FY2022FY2023FY2024 Penalized share PROGRAM YEAR HOSPITALS PENALIZED (PERCENT)
⊞ data table⬇ CSV
Program yearHospitals penalized (percent)
FY201879
FY201982
FY202083
FY202183
FY202282
FY202375
FY202478

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.

$0M $250M $500M $750M $1,000M FY2018 $564M FY2020 $563M FY2022 $521M FY2023 $320M
⊞ data table⬇ CSV
Program yearTotal penalties (USD millions)
FY2018564
FY2020563
FY2022521
FY2023320

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.

AK 9.3% ME 10.0% WA 9.1% ID 9.6% MT 9.2% ND 9.4% MN 9.4% WI 10.5% MI 11.0% NY 10.7% VT 7.9% NH 8.5% OR 10.4% NV 11.3% WY 10.1% SD 11.0% IA 10.5% IL 10.9% IN 12.2% OH 12.3% PA NJ 10.2% MA 9.2% CA 11.2% UT 8.7% CO 8.3% NE 10.1% MO 11.3% KY WV 14.4% VA 11.7% MD 11.7% CT 9.4% RI 10.4% AZ 10.6% NM 12.3% KS 10.8% AR 12.4% TN 12.8% NC 11.3% SC 12.8% DC 8.2% DE 11.9% OK 12.2% LA 14.3% MS 14.5% AL 13.8% GA 12.7% TX 12.5% FL 12.3% HI 11.3% better than benchmark worse

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.

AK 32.1% ME 32.7% WA 29.4% ID 30.2% MT 29.9% ND 30.9% MN 29.4% WI 31.4% MI 34.7% NY 30.9% VT 29.0% NH 30.6% OR 30.9% NV 32.5% WY 29.9% SD 31.6% IA 32.2% IL 31.4% IN 36.3% OH 35.3% PA NJ 31.1% MA 29.4% CA 29.5% UT 27.8% CO 26.4% NE 31.3% MO 34.7% KY WV 41.2% VA 34.0% MD 35.1% CT 30.2% RI 32.0% AZ 31.0% NM 32.5% KS 33.0% AR 39.6% TN 37.9% NC 35.2% SC 36.5% DC 29.4% DE 35.5% OK 37.3% LA 41.0% MS 43.3% AL 41.5% GA 36.3% TX 32.8% FL 34.0% HI 29.3% better than benchmark worse

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