Many types of health interventions fit the adage, “A pint of sweat saves a gallon of blood.” By engaging in preventive behaviors and consuming preventive care, the risk of future adverse events is lowered—saving both human suffering and the attendant financial costs. This is the kind of care where multiple parties in the health ecosystem all come out ahead.
Despite its “win-win” outcome, however, preventive care is often underfunded or investments in it are not maintained. It is not because these activities do not generate value, it is because that value is not correctly tracked and attributed back to the preventive activity in question. There are significant limitations in data capture and analytics in health-related markets, and due to these shortfalls, we are leaving value for patients and payers on the table.
Community health workers (CHWs) are one example of such an investment. Victoria Cargill and Anita Totten at the Milken Institute discuss how CHWs are effective at improving patient well-being yet remain underutilized in this capacity. This underutilization is puzzling on its surface, given that, on balance, CHWs save more than they cost. A randomized experiment published by Shreya Kangovi and coauthors in Health Affairs demonstrates the financial value of CHWs. The authors randomly assigned CHWs to half of a population of high-risk patients in a health system and tracked all subsequent patient expenses. On an annualized basis, CHWs had a return on investment of 247 percent, meaning that CHWs cost roughly $1,721 per patient while saving $4,246 per patient in prevented medical expenses. The CHWs in this experiment performed over 20 times better than the Dow Jones average annual return on investment of 12 percent for the last 10 years.
The cost savings in this instance are obvious because the patients who interacted with CHWs were directly compared to a control group. For an outlay of $450,000, the organization saved $1.1 million on medical care that these patients otherwise would have needed. In the field, this comparison is not done because, absent a control group, it is difficult to know how much would have been spent. A health system spends $450,000 on CHWs and records the expense, but no savings show up on their balance sheet because they come from hospitalizations that do not happen: the savings are unobserved. Because these savings go unmeasured, it is difficult to demonstrate that the investment in CHWs is paying off. As a result, these programs are not used to their full potential.
CHW programs are not only underutilized but are also underfunded and plagued by low wages and job insecurity. The Public Health Workforce Interests and Needs Survey shows that over 15 percent of CHWs are dissatisfied with their job security. Over a quarter of those surveyed by the National Association of Community Health Workers do not believe that they are paid a livable wage, and interviews of CHWs by Ibe et al., published in Health Affairs, reveal fears about the stability of institutional funding for their positions. Part of this instability comes from the nature of the funding used to pay CHWs. Often, CHW programs are paid for using grants or other one-time sources of funding, which leads to a boom in hiring when the funds arrive, followed by layoffs when the funds run out.
This is the fundamental difficulty with investments in prevention: the “pint of sweat” that shows up on a balance sheet cannot be offset by the “gallon of blood” that goes unmeasured and, therefore, unobserved. This is a failure of business analytics. Theoretically, following an outlay of seed funding, preventive programs should be self-sustaining, as savings down the road can be funneled back into the programs that generate them, resulting in a virtuous cycle of lower costs and better patient outcomes. However, when these savings go unmeasured and unattributed, they cannot be reinvested.
This problem is most easily remedied when the upfront spending and down-the-road savings are felt by the same entity, as is the case with integrated health systems. Well-designed pilot programs with appropriate data capture can measure cost savings, and the proper adjustments can be made to internal budgeting.
The problem becomes trickier when the entity that invests in prevention is not the entity that would otherwise have paid for care. However, suppose the down-the-road cost savings can be accurately measured and convincingly demonstrated. In that case, the latter has a clear financial incentive to enter a contract for such preventive services.
There are win-win scenarios in the health sector. We just need to measure them.
