Big Data, Small Data, All Data Is Good Data—But What Does It Mean to Seniors Housing Investors and Operators?
By Beth Burnham Mace, Chief Economist, NIC
Big data is among today’s buzzwords. Yet just 20 years ago, when I started out in the industry, data on the seniors housing and care sector was nearly nonexistent. Now calls for data are very different—and the voices are getting louder. Having the ability to collect and use data is presenting opportunities across the sector.
Big Versus Small
“Big data” refers to extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations. It is used in the hard sciences, social sciences, and business. “Small data” refers to smaller data sets derived through observation, surveys, and data collection efforts.
Both sets of data are good and help us understand cause and effect, correlations, historical patterns, relationships, and relevance.
The History of Data for Seniors Housing and Care
As I said, there was very limited data available to investors on the seniors housing and care sector twenty years ago. Unlike in other commercial and residential property type sectors (e.g., office, retail, industrial, and multi-family), familiar concepts such as simple property identification and classification, terminology, inventory counts, occupancy rates, and demand and supply measures simply did not exist. Comprehensive, reliable, and consistent information on transactions activity was no better than hearsay and word of mouth. Experience, intuition, and trust in your partner’s information sources (from the capital provider or capital seeker) was paramount. It was a bit of a “Wild West.” As a result of limited, inconsistent, and unreliable data, the sector experienced a higher cost of capital than exists today, with cap rates averaging 10.5% or more for high-quality product.
By the early 2000s, NIC began collecting data on property market fundamentals through our NIC MAP® Data Service. Today, data on inventory counts, development activity, changes in supply and demand fundamentals, rents, and occupancy exists for 99 large metropolitan markets in the U.S. And soon, there will be data on a total 140 markets (with NIC MAP’s Second Quarter 2016 data release in July 2016). Today, through NIC’s strategic alliance with Real Capital Analytics (RCA), time-series data exists on transactions volumes, property-level historical records of buyers and sellers, cap rates, and pricing on a per-unit basis. Analysis of trends, peak pricing, comparative per-unit pricing for single asset sales versus portfolio level sales, regional differences in values, and risk premiums can be determined and discussed. Greater transparency has, in part, helped to lower the sector’s cost of capital, with cap rates currently averaging 7.5% for seniors housing and 10% for skilled nursing properties. These are rates that would have been unfathomable a decade ago. Nevertheless, a risk premium compared with multifamily of 200 basis points or more still exists for seniors housing and care.
The Way Forward
Further transparency into the seniors housing and care sector is needed. As part of NIC’s mission to provide more transparency in the sector and through our Actual Rents Data Initiative, we are presently engaged in an effort to expand the seniors housing data we collect and report on to include data about:
- Actual rents (in-place rents as well as move-in rents, which are different than the asking rents currently being collected and reported by our NIC MAP® Data Service).
- Leasing activity (as measured by move-in and move-out velocities).
The data will be important for benchmarking, strategic planning efforts, and day-to-day business operations. The initial data from this initiative will be release during the third quarter of 2016.
Another notable NIC seniors housing and care data effort is NIC’s Skilled Nursing Data Initiative. The first release from the initiative is the quarterly Skilled Nursing Data Report, publishing for the first time on March 10, 2016. This report will provide operators and investors with monthly data collected by NIC from October 31, 2011 through December 31, 2015. It will be the first to break out managed Medicare census and rates and will publish select skilled nursing metrics:
- ADR by Payor Source (Includes Managed Medicare)
- Skilled Mix
- Quality Mix
- Patient Day Mix
While none of these initiatives qualify as “big data,” they are critically important for the sector in attracting institutional investment capital and possibly further lower the cost of capital for the sector.
The Opportunities of Big Data
Now, with big data and seniors housing, myriad opportunities are emerging. The implementation of the Affordable Care Act, changes in payment systems, and the move from fee-for-service payment schemes to value-based outcomes by private insurers and government payors (such as Medicare and Medicaid) are changing the landscape for both providers of health care services and providers of residential housing and care for seniors. Data systems and structures are beginning to provide transparency, dissemination, and integration of information on a resident/patient’s medical history, current health conditions, and medications between and among hospitals, physician groups, managed care organizations, and care providers (operators of skilled nursing and assisted living properties). While importance of privacy (HIPAA) remains paramount, the greater flow of information and collaboration among health care providers are generally considered net positives for patients/residents in terms of quality of care and quality of life, while simultaneously lowering costs. Seniors housing operators who align themselves with insurers and acute care providers by having the appropriate information and data infrastructure systems stand to win market share and revenue growth.
Big data applications are also being developed at a very practical and operational level. For examply, an operator of 40-plus properties has digitized operational details, such as resident-specific behaviors and patterns. In one instance, this includes system-wide review of the time of day of resident falls, concluding that most falls occurred in the early waking hours of the day, as opposed to the assumed middle-of-the-night timeframe. Based on this review, additional care providers were hired for the busy morning hours, which led to a decline in falls, improvement in residents’ quality of life, and a diminishing of cash flow disruptions, thereby helping the bottom line of the operations.
Data systems can also help a seniors housing provider identify a resident at risk of being readmitted to a hospital in order to potentially intervene prior to a re-hospitalization through electronic health records (EHRs) and other monitoring platforms. This provides a valuable competitive edge to a seniors housing operator and provides an incentive for a hospital to partner with an operator who can monitor and care for recently discharged patients. Hospitals face significant Medicare penalties if readmission rates are high. They increasingly are incentivized to discharge residents to appropriately-aligned seniors housing care providers to effectively create an integrated network of information and care systems.
Taken all together, data—be it “big” or “small”—has transformed the investment environment for seniors housing and care, and will continue to do so for the foreseeable future.